- Python cheatsheet
- 7+ Python Cheat Sheets for Beginners and Experts
- Comprehensive Python Cheat Sheet for Beginners
- Python Cheatsheet - DEV Community
- A Comprehensive Cheatsheet for python developer
- 파이썬 요약집(기초)
- a bunch of cheatsheats
- PB Python Article Roadmap - Practical Business Python
- Awesome Python
- Awesome-Python
- Awesome-Python
- pycrumbs: Bits and bytes of Python from the Internet
- pythonidae: Curated decibans of scientific programming resources in Python
- A Curated List of 57 Amazing GitHub Repositories for Every Python Developer | by Angelica Dietzel | Better Programming | Nov, 2020 | Medium
- The best of Python: a collection of my favorite articles from 2017 and 2018 (so far)
- Python Development Resources
- pawelmhm.github.io
- Python Koans
- Python Pedia - One Stop for Python Programming Resources. It's all about Python
- 파이썬을 여행하는 히치하이커를 위한 안내서!
- pythonfiddle.com
- sentdex
- practical-python dabeaz, David Beazley
- blog.thepythontutor.com
- Python Tutor code visualizer: Visualize code in Python, JavaScript, C, C++, and Java
- Think Python
- Learning Python: From Zero to Hero
- Top 11 Github Repositories to Learn Python | by Claire D. Costa | Nov, 2020 | Towards Data Science
- 파이썬을 배우는 최고의 방법
- codingbat.com/python
- Python 이해하기 20160815
- MIT 6.00 컴퓨터 공학과 프로그래밍(Python) 오픈 코스
- 산업공학과를 위한 프로그램밍 입문 (w/파이썬) Part 1
- 프로그래밍 포기자를 위한 파이썬 | 김왼손의 Khim Academy
- 미운코딩새끼
- 기술 경영을 위한 프로그래밍 NumPy, matplotlib, Pandas, excel 연동, scrapy
- Google for Education
- Full Stack Python의 'Best Python Resources'를 공부하면서 나름대로 정리한 자료
- python.zeef.com/luis.solis
- Practical Python for Astronomers
- Intermediate Python
- H3 2011 파이썬으로 클라우드 하고 싶어요_분산기술Lab_하용호
- 구글로 공부하는 파이썬
- An Algorithm to Extract Looping GIFs From Videos
- Search Trends Google and WikipediaTrends for feature generation
- effectivepython.com
- The Deceptive Anagram Question
- Working with Binary Data in Python
- joinc
- Korea Python Documents
- 파이썬 문서고 백업 저장소
- Microsoft Virtual Academy
- SB Coding Workshop
- pythonprogramming.net
- Problem Solving with Algorithms and Data Structures
- Hacking an epic NHL goal celebration with a hue light show and real-time machine learning
- Python without an operating system
- GIL Global Interpreter Lock
- GIL(Global Interpreter Lock) and Releasing it in C extensions
- python GIL
- 파이썬 GIL 깊숙히! (上)
- 파이썬 GIL 깊숙히! (상) 에 대한 몇 가지 변명
- Andrew Montalenti: Beating Python's GIL to Max Out Your CPUs
- Larry Hastings - Removing Python's GIL: The Gilectomy - PyCon 2016
- Why is Python so slow? | Hacker Noon
- 번역 파이썬 GIL은 사라질까?
- 번역 파이썬 GIL은 사라질까?
- python의 GIL과 threading
- 왜 Python에는 GIL이 있는가
- python gil이 있으니까 thread safe 할까요?
- 파이썬에서 멀티코어 활용하기 (feat. 라인 서버 개발자) | 라인개발실록 - YouTube
- Python Software Foundation News: The 2022 Python Language Summit: Python without the GIL
- 올바르게 GIL 이해하기 - 바이트코드와 쓰레드 안정성
- nogil: Multithreaded Python without the GIL
- “파이썬은 느리다”에 대한 반론 | 요즘IT
- Modern Python performance considerations LWN.net
- 3 PROGRAMMING LANGUAGES TO REPLACE SHELL SCRIPTING
- Do-nothing scripting: the key to gradual automation – Dan Slimmon
- Python Trainer
- Hands-on Introduction to Spatial Data Analysis in Python
- The Python IAQ: Infrequently Answered Questions
- Why I Hate Python (Or Any Dynamic Language, Really)
- Pipelining - A Successful Data Processing Model
- Software development skills for data scientists
- Infographic – Quick Guide to learn Python for Data Science
- Can assign
[] = (), but not() = [] - Mean Shift Clustering
- Optimizing Python - a Case Study
- 언어의 변천사를 통해 바라본 Python
- Statistics
- Python Web Crawler Development
- PyCruise
- How to generate and solve logical deduction problems
- Let’s Build A Simple Interpreter. Part 1
- 파이썬을 이용한 시스템 트레이딩 (기초편)
- Quantum Python: Animating the Schrodinger Equation
- Pycon KR 2019 Quantum Physics in Python
- Python for R Users
- Is it true that Python is a dying language?
- Python Is Not C
- A Pythonist getting Rusty these days... (Part 1)
- A Pythonist getting Rusty these days... (Part 2)
- Write a Python Calculator Imperatively
- asciinema.org/a/5bwbed0is2306d02xacmga6nx pycalculator
- Random Forest in Python
- Creating a bot for Checkers
- A Neural Network in 11 lines of Python
- Searching for Approximate Nearest Neighbours
- Best Practices for Managing Your Code Library
- Python Best Practices for a New Project in 2021 - Alex Mitelman
- Python Projects – Technozune
- Python Extras – Technozune
- CFD Python: 12 steps to Navier-Stokes
- How to create a text mining algorithm with Python
- Fun with BPF, or, shutting down a TCP listening socket the hard way
- Why write Python in Visual Studio?
- Building a dataflow graph in Python
- Ask HN: Good Python codebases to read?
매끄럽게 움직이는 실시간 스펙트럼 분석기를 만들자!- Bayesian Cookies
- Zen of python poster
- The Zen of Python: Write Beautiful Code | by Oleksii Kharkovyna | Towards Data Science
- bayesianPy
- Exploratory computing with Python
- quantitative economic modelling by python and julia
- Follow the Money with Python
- Procedural City Generation in Python
- Linear Programming in Python with CVXOPT
- Anna Nicanorova: Optimizing Life Everyday Problems Solved with Linear Programming in Python - YouTube
- Deobfuscating Shifu
- Python Malware On The Rise | Cyborg Security PyInstaller, py2exe, Nuitka
- On insecure software distribution practices
- 파이썬(Python) 시큐어코딩 가이드 및 매뉴얼 | 자료실 - KISA 인터넷 보호나라&KrCERT python secure coding guide
- R vs Python: head to head data analysis
- 27 languages to improve your Python
- python wats - A "wat" is what I call a snippet of code that demonstrates a counterintuitive edge case of a programming language
- From Python to Go, and Back Again
- Wrapping Go in Python
- 파이썬으로 만드는 첫 쓸모있는 프로그램 EBS 방송 녹화하기
- Let’s Build A Simple Interpreter. Part 1
- Let’s Build A Simple Interpreter. Part 2
- Let’s Build A Simple Interpreter. Part 3
- Let’s Build A Simple Interpreter. Part 4
- Let’s Build A Simple Interpreter. Part 5
- Let’s Build A Simple Interpreter. Part 6
- Z algorithm
- Recreational Maths in Python
- DoingMathWithPython
- Math Symbols Explained with Python
- A modern guide to getting started with Data Science and Python
- ultimate-python: Ultimate Python study guide for newcomers and professionals alike
- 빅데이터를 위한 파이썬(Python) 교육 내용 정리
- Python for Data Science - Python Brasil 11 (2015)
- 집단지성 프로그래밍 1(Machine Learning, Euclidean Distance, Pearson Correlation Coefficient)
- Tutorial – Getting Started with GraphLab For Machine Learning in Python
- python-tutorial: A Python 3 programming tutorial for beginners.
- Python for Quants. Volume I
- 문제에 집중하는 Python with Open Source
- Canyon decimation example
- BioPsyPy - 생물심리학 + 파이썬 프로그래밍
- PyML - Python을 이용한 머신러닝 (코세리 인증과정 도전 스터디)
- 싸이폴리 - 사회인지신경 심리학 + 계량적 사회행동 분석
- 통계적 사고: 파이썬을 이용한 탐색적 자료 분석
- Python Online Quiz | Online Test | Mock Exam
- Python Interview Questions and Answers
- 80 Python Interview Practice Questions | by Cornellius Yudha Wijaya | Jun, 2020 | Towards Data Science
- 10 Advanced Python Interview Questions | by Michael Krasnov | Better Programming | Sep, 2020 | Medium
- 이미지 캡션 API - CloudSight, Clarifai
- 파이썬 + 네트워크 20160210
- Code Puzzle
- Making Python on Apache Hadoop Easier with Anaconda and CDH
- blogs.msdn.microsoft.com/pythonengineering
- build-in 함수 overwrite 문제
- Welcome to Python for Social Scientists!
- Diving Into Other People's Code
- The World of Python
- Python Scripts as a Replacement for Bash Utility Scripts
- Dive Into Object-oriented Python
- Python integer objects implementation
- 파이썬을 활용한 금융공학모델링
- Facebook - Python in production engineering
- (E, K)Generating Python Module Dependency Graphs(종속성 그래프 생성하기)
- 파이썬 예제로 보는 직접 의존성과 간접 의존성
- 파이썬 프로젝트의 구조
- How to Structure Programming Projects for Beginners | Python Long-term Project Structuring - YouTube
- Organizing your Python Code. In spite of yourself | by Keno Leon | Medium
- 메모리 소비 크기 구하기
- 메모리 사용 및 persistent dict, list
- 배준현: 파이썬 메모리 이모저모 - PyCon Korea 2015
- 파이썬으로 아파트분석1 데이터 수집과 지역별 분석
- 파이썬 데이터분석, 민간아파트 분양가격 동향 v.2019 #1
- 파이썬으로 주식 상장기업 크롤링한 데이터 엑셀 저장 및 엑셀 파일 불러오기 feat.pandas
- sentdex
- Playing a mp3 stream with python
- Let's Write an LLVM Specializer for Python!
- LLVM Optimized Python for Scientific Computing
- Realtime Data Plotting in Python
- pythonplot.com - Python Plotting for Exploratory Analysis
- How a template engine works
- heatmap.py
- Python script for generating high quality heatmaps based on any coordinate data (GPS tracks, eye tracking, etc). http://www.sethoscope.net/heatmap
- Example python to perform GeoIP lookups for a list of IP addresses and then generate heatmap using http://www.sethoscope.net/heatmap
- GeoIP를 이용한 IP정보 활용(GeoIP + Matploitlib)
- CNC로 파이썬 배우기
- Python in production engineering
- python 수학이해하기
- github.com/simplexcomplexity/complexscience
- learn-python
- 파이썬 생존 안내서 (자막)
- 데이터 사이언스 스쿨 - Python 데이터 핸들링과 시각화 라이브러리 실무
- Mybridge for Professionals
- github.com/Mybridge/learn-python
- 34 Amazing Python Open Source Libraries for the Past Year (v.2019)
- Python Open Source of the Month (v.Aug 2019)
- Python Top 10 Articles for the Past Month (v.July 2019)
- Python Open Source of the Past Month (v.June 2019)
- Python Top 10 Articles for the Past Month (v.June 2019)
- Python Open Source for the Past Month (v.May 2019)
- Python Top 10 Articles for the Past Month (v.May 2019)
- 34 Amazing Python Open Source Libraries for the Past Year (v.2019)
- Learn Python from Top 50 Articles for the Past Year (v.2019)
- Python Top 10 Articles for the Past Month (v.Dec 2018)
- Python Open Source of the Month (v.Nov 2018)
- Python Top 10 Articles for the Past Month (v.Nov 2018)
- Python Open Source of the Month (v.Oct 2018)
- Python Open Source of the Month (v.Sep 2018)
- Python Top 10 Articles for the Past Month (v.Sep 2018)
- Python Open Source of the Month (v.Aug 2018)
- Python Top 10 Articles for the Past Month (v.July 2018)
- Python Open Source of the Month (v.June 2018)
- Python Open Source of the Month (v.May 2018)
- Python Top 10 Articles for the Past Month (v.May 2018)
- Python Top 10 Articles for the Past Month (v.Apr 2018)
- Python Top 10 Open Source of the Month (v.Apr 2018)
- Python Top 10 Open Source Projects (v.Mar 2018)
- Python Top 10 Articles for the Past Month (v.Mar 2018)
- Python Top 10 Articles for the Past Month (v.Feb 2018)
- Python Top 10 Open Source Projects (v.Feb 2018)
- Python Top 45 Articles for the Past Year (v.2018)
- 30 Amazing Python Projects for the Past Year (v.2018)
- Python Top 10 Articles for the Past Month (v.Dec 2017)
- Python Top 10 Articles For the Past Month (v.Oct 2017)
- Python Top 10 Articles (v.November)
- Python Top 10 Articles For the Past Month (v.Sep 2017)
- Python Top 10 Articles for the Past Year (v.2017)
- Python Top 10 Articles for the Past Month (v.May 2017)
- Python Top 10 Articles for the Past Month (v.August 2017)
- Python Top 10 Articles for the Past Month
- 10 Best Python Projects of 2018
- Travelling Salesman Problem, System Design Primer, Facial Recognition, WhatWaf, SimpleCoin, Detectron, Vid2Vid, The Algorithms, Pip Env
- 10 Crazy Cool Project Ideas for Python Developers | by Juan Cruz Martinez | Sep, 2020 | Towards Data Science
- Top 45 Python Project Ideas for Beginners - Intellipaat
- 140 Python Projects with Source Code | by Priyesh Sinha | May, 2021 | DataDrivenInvestor
- 70+ Python Projects For Beginners, Intermediate & Advanced Developers With Source Code
- 파이썬 데이터 검색
- Using Python to Parse Spreadsheet Data
- Python source code analysis by Prashanth Raghu
- 배포시스템 삽질기
- 바로 실행해보면서 배우는 파이썬
- 파이썬으로 텔레그램에 문자 보내보기
- Facebook API 포스팅 가져오기 #1 API 사용
- 10가지 팔로우 할만한 파이썬 기술 블로그
- The Elements of Python Style
- Google Python Style Guide
- Start Programming with Google Python Style Guide
- Nine simple steps for better-looking python code
- 예제로 배우는 Python 프로그래밍
- Optimization with Python I
- Python Code Optimization Tips and Tricks You Should Know
- 데이터 과학 여름 학교 2016
- Ecosystem of Python
- 한국의 파이썬 소식
- 파이썬, 처음 뵙겠습니다
- Hacking FFmpeg With Python – Part One
- Hack FFmpeg With Python, Part Two
- 4 things I want to see in Python 4.0
- mosky.tw
- Python Report Card
- Complementing Python With Rust
- Rust를 사용해서 당신의 Python에 날개를 달아주세요
- mindmap - Python for big data
- masnun.com/category/python
- NDC2017
- 파이썬의 Comma(,) 사용팁
- SIRI CONTROLS YOUR PC THROUGH PYTHON AND GMAIL
- 밥먹기를 최적화하자
- Python For Data Science - A Cheat Sheet For Beginners
- Cheat Sheet of Machine Learning and Python (and Math) Cheat Sheets
- billiARds: A Game of Augmented Reality Pool Python 으로 코딩한 AR
- 파이썬 뉴스 텍스트 워드 클라우드 feedparser, newspaper, konlpy 등 활용
- Controlling Hardware with Python
- 27 languages to improve your Python
- Kelsey Hightower - Keynote - Pycon 2017 Kubernetes for Pythonistas
- Generic Python App Structure
- Buggy Python Code: The 10 Most Common Mistakes That Python Developers Make
- 7 Python mistakes all beginner developers make — and how to avoid them
- Improve Your Craft: 6 Lazy Programming Mistakes and How to Avoid Them
- 번역 파이썬 함수 작성 시 자주 범하는 실수 5가지
- 7 Modern Python Mistakes To Fix NOW! | by Emmett Boudreau | Towards Data Science
- Top 10 Coding Mistakes in Python & How to Avoid Them - ActiveState
- Python Beginner Projects 2020 - Add them to your resume!
- 12 Beginner Python Projects - Coding Course - YouTube
- Watch a Directory for Changes
- 파이썬 (doc) 스타일 가이드에 대한 정리
- Why are slots so slow?
- ACM Month Of Code 2k17: Building Moodify
- Python Basics for Data Science
- Checking Your Daily Spending via SMS with Python, Plaid and Twilio
- 파이썬 Python 코딩 - SMS 문자보내기, SMS LMS API 연동 방법 - YouTube
- The Fun of Reinvention (Screencast) David Beazley
- Welcome to Intermediate and Advanced Software Carpentry!
- Wrapping C/C++ for Python wrapper
- Python Practices for Efficient Code: Performance, Memory, and Usability
- Python의 내부: 소개
- Right and left folds, primitive recursion patterns in Python and Haskell
- Tail Recursion in Python 실용적이진 않지만 재미있는 tail recursion 구현 이야기
- 싸이파이, 대스크, 눔바, 싸이썬, HPAT··· 더 좋아진 필수 파이썬 툴 5종
- Webinar Recording: 10 Tips for Pythonic Code
- 15 Python tips and tricks, so you don’t have to look them up on Stack Overflow
- 12 Python Tips and Tricks For Writing Better Code | by Pavel Tech | Jun, 2020 | Towards Data Science
- 12 Python Tips & Tricks You must know | Ayushi Rawat
- I Thought I Was Mastering Python Until I Discovered These Tricks
- 30 Magical Python Tricks to Write Better Code - Towards Data Science
- The ultimate guide to writing better Python code | by Rhea Moutafis | Towards Data Science
- 10 Smooth Python Tricks For Python Gods | by Emmett Boudreau | Towards Data Science
- Write Better Python Code With These 10 Tricks | by Yong Cui, Ph.D. | Aug, 2020 | Towards Data Science
- 7 Python Tricks You Should Know. Impress your friends with these useful… | by Nabilah Abu Bakar | Better Programming | Medium YouTube-Dl, Pdb, PyInstaller, Tqdm, Colorama, Tabulate, Ptpython
- Interesting Python Tips and Tricks | by Ravi | Analytics Vidhya | Sep, 2020 | Medium
- Here are some tips to speed up your Python program | by Anh T. Dang | Nov, 2021 | Level Up Coding
- 5 Useful Python Scripts. Part 10: Excel Files Merger, Extended… | by Harendra Verma | May, 2022 | Python in Plain English
- Python One-Liners Playlist - YouTube
- What are some one liners in Python that would take a hundred in C? - Quora
- 50 python one-liners everyone should know | by Allwin Raju | Medium
- 18 Python scripts that help you write code faster
- Pythonic Code, By Example
- Pythonic monotonic | Ned Batchelder 글쓴이가 말했듯 좋은 코드라고 생각하지 않음
- Write good examples by starting with real code
- TIL - How to Python "pythonically"
- win32 api in python
- win32print
- Sebastian Witowski - Writing faster Python
- 5 Ways to Make Your Python Code Faster | by Adarsh Bulusu | The Startup | Medium
- writing-faster-python3: Code examples for the writing faster Python 3 talk
- The one-stop guide to (easy) cross-platform Python freezing: Part 1
- Which is the fastest version of Python?
- 신묘한 Python locals() 의 세계
- Performance Python: 7 Strategies for Optimizing Your Numerical Code numpy, pandas, scipy, cython, numba, and more
- Basic method chaining
- bit manipulation
- practice - sum of two integers using bit manipulation
'{0:b}'.format(num)==bin(num)[2:]to make binary number string
- #3.1. Tensorflow vs. PyTorch
- 오픈소스 라이브러리 개발기
- Python으로 알송 가사 추출하기
- Master Python through building real-world applications (Part 1)
- Symbolic Computing Using Python: Part 1-Basics
- Python: Beyond the basics II - IPython, encapsulation & args
- Python stories, September 2018
- stdout_009.log: PEP 572, PEP 8000, Python Software Foundation
- How to write a simple toy database in Python within minutes
- Python APIs - APIs are an easy and standardized way to access information across different companies Google, Yelp, Youtube
- 연산자(operators)의 유용성
- 파이썬과 양자 컴퓨팅 — 제 1장은 사건과 함께 시작한다
- 파이썬과 양자 컴퓨팅 — 제 2장에서 원리 파악이 시작된다
- 파이썬과 양자 컴퓨팅 — 제 3장에서 자료 수집과 실전 테스트에 힘쓴다
- 파이썬과 양자 컴퓨팅 — 제 4장은 실용화 편이다
- 파이썬으로 체스 만들기
- (PlaywithData)1day seminar_0630
- SERP Analysis with Google Search Console+Python
- Google Search Console Data, CSVs into a Pandas Dataframe, Plot total clicks over time
- Static Analysis at Scale: An Instagram Story
- Python at Scale: Strict Modules
- Pointers in Python
- Python as C++’s Limiting Case
- How to Make Histograms in Pure Python
- 15 Python Projects in Under 15 Minutes (Code Included)
- 아래아한글
- 초간단 업무자동화 코딩 강좌 #1/10:상장 일괄제작 | 회사원생존코딩
- '파이썬-아래아한글 자동화 기초' 카테고리의 글 목록
- '파이썬-아래아한글 자동화 응용' 카테고리의 글 목록
- '파이썬-아래아한글 자동화 기초' 카테고리의 글 목록
- '파이썬-아래아한글 자동화 응용' 카테고리의 글 목록
- HWP여백조정 후 이미지 너비/높이를 폭에 맞게 일괄조정하는 방법
- 파이썬을 이용한 한/글 자동화 프로그램 튜토리얼(청구서 일괄작성 등) : 클리앙
- 한/글 없이 hwpx 파일의 표를 pd.DataFrame으로 추출하는 방법
- 모든 날짜 문자열 끝에 요일 붙이기
- 가볍게 살펴보는 새로운 한/글 파일 포맷 HWPX : NHN Cloud Meetup python 무관, 한글파일 포맷 자체에 대한 이야기
- 파이썬으로 아래아한글 실행하는 방법
- 파이썬+한/글로 가장 강력한 문자열 가공 프로그램 만들기 - YouTube
- 움짤로 빠르게 배우는 파이썬-아래아한글 자동화 레시피 | 학습 페이지
- 파이썬으로 기존에 열려 있는 아래아한글 프로그램을 제어하는 방법 : 클리앙
- pyhwp - .hwp file format v5 parser in python http://pythonhosted.org/pyhwp
- 파이썬으로 한컴오피스 한글2018 조작하는 방법6 : html table태그를 아래한글 표로 옮기기
- 모든 프로그래밍 요구를 충족하는 12가지 파이썬 여러가지 배포판 이야기
- Minimizing context switching between shell and Python
- 핑퐁팀의 Python 문화 구축기
- 파이썬을 올바르게, 현명하게 설치하는 방법
- Semantic Differences Between JavaScript and Python
- Python vs. Node.JS: Which One is Best for Your Project? | by Claire D. Costa | Jul, 2020 | Towards Data Science
- 4 Simple Ways to Refactor Your Python Code
- Introduction to Streaming Algorithms
- How to build HANGMAN with Python in 10 MINUTES - YouTube
- 파이썬 초보에서 중수가 되기 위한 9가지 스킬
- 파이썬 초보자가 저지르는 10가지 실수 | 요즘IT
- 파이썬으로 SAP Script 실행하기 (with argument)
- futurecoder: A platform for beginners to learn programming in Python
- Mutability and Immutability in Python — Let’s Break It Down | by Wendy Leung | Data Driven Investor | Medium
- 5 Levels of Understanding the Mutability of Python Objects | by Yang Zhou | TechToFreedom | Dec, 2020 | Medium
- Understanding Python Operator Overloading to prevent wrong code | by Doojin Kang | Aug, 2020 | Medium
- Chiel Peters - Python: From Source to Execution | PyData Fest Amsterdam 2020 - YouTube
- Clean Code in Python. “A long descriptive name is better than… | by Esteban Solorzano | Dev Genius | Medium
- 10 Quick Clean Coding Hacks in Python | by Sruthi Korlakunta | Towards Data Science
- KDnuggets™ News 21:n48, Dec 22: Write Clean Python Code Using Pipes; 5 Key Skills Needed To Become a Great Data Scientist - KDnuggets
- Use Python to Power Up Your Day Job | by Martin Andersson Aaberge | Better Programming | Medium
- The Unseen Pitfalls of Python. Because 257 is not 257 but 256 is 256 | by Salvador Aleguas | codeburst
- 5 Python Code Smells You Should Be Wary Of | by Anupam Chugh | Towards Data Science
- The Art of ‘One-Lining’ in Python | by Salvador Aleguas | Analytics Vidhya | Medium
- Advanced Python: Metaprogramming. Explaining what, why and how… | by Farhad Malik | FinTechExplained | Medium
- 7 Best Hosting Platforms for Python Application
- I created my own YouTube algorithm (to stop me wasting time) | by Chris Lovejoy | Nov, 2020 | Towards Data Science
- Lessons learnt from building my own library - presented by Stephanos - YouTube
- Start Python #3 Backend Program 만들기 - Class - Kowana's coding
- Common anti-patterns in Python - DeepSource
- Building a full-text search engine in 150 lines of Python code · Bart de Goede
- 내가 쓰고 있는 파이썬 버전과 구현체를 알아봅시다
- Python at Netflix. By Pythonistas at Netflix, coordinated… | by Netflix Technology Blog | Netflix TechBlog
- Clever vs Insightful Code • Hillel Wayne
- 파이썬 Python 코딩 - CID 발신번호표시장치 연동 - YouTube
- 5% of 666 Python repos had comma typos (including Tensorflow, and PyTorch, Sentry, and V8) | by Code Review Doctor | Jan, 2022 | Dev Genius
- Ask HN: Good Python projects to read for modern Python? | Hacker News
- 파이썬 40줄로 Wordle을 풀어보자
- Literate programming wordle — Literate Wordle documentation
- Patrick Mooney's blog - Some notes on writing parser-based interactive fiction in Python (part 1)
- Patrick Mooney's blog - Some notes on writing parser-based interactive fiction in Python (part 2)
- Patrick Mooney's blog - Some notes on writing parser-based interactive fiction in Python (part 3)
- Patrick Mooney's blog - Some notes on writing parser-based interactive fiction in Python (part 4)
- OAuth 2 and Authentication Choices for Your Python Project | Real Python Podcast #99 - YouTube
- Python은 pass-by-value입니다 · 감자도스
- ASMR Programming - coding Game OF Life in Python - No Talking - YouTube
- Day 16 : Live Weather Updates with Python - YouTube
- Bitbucket Server Api Python Code Example
- Extract Table from HTML using Python - PyShark
- keystroke practice
- 한글깨기.py
- 한글깨기.py & Enyg.py (은는이가.py)
- 한글과 관련된 여러가지 기능을 포함한 Python 라이브러리
- 파이썬으로 한/글 문서비교 툴 구현해보기(1/2)
- awesome-hangul#python
- hangul-toolkit - 한글 자모 분해, 조합(오토마타), 조사 붙이기, 초/중/종 분해조합, 한글/한자/영문 여부 체크 등을 지원
- hangul-utils - An integrated library for Korean language preprocessing
- hanja: 한글, 한자 라이브러리
- jamos_separator.py 한글 자모 분리
- jamotools
- langdetect - Port of Google's language-detection library (version from 03/03/2014) to Python
- py-hanspell - 파이썬 한글 맞춤법 검사 라이브러리. (네이버 맞춤법 검사기 사용)
- Python for Android Tutorial #1 - Using the Accelerometer
- Kivy
- kivy.org/planet
- Python on Android
- Introduction to Kivy
- Developing Python based Android Apps Using Kivy
- Kivy with Python tutorial for Mobile Application Development Part 1
- Kivy - Mobile and Desktop App Dev w/ Python
- KivyAndroidClassification
- Running NumPy in Android Devices using the Kivy Python Framework
- Kivy - 안드로이드 앱 만들기 - 강좌링크
- Starting With Kivy to Build Cross-Platform GUI Apps - YouTube
- NumPyCNNAndroid - This project builds Convolutional Neural Network (CNN) for Android using Kivy and NumPy
-
Advanced Python Features generator, collections, itertools, (un)packing, decorator, lru_cache, context manager
-
Five Advanced Python Features. Curly brace scopes, autovivification… | by James Briggs | Towards Data Science dict, list, decorator,
from __future__ import braces -
Records, Structs, and Data Transfer Objects in Python
dict,tuple, custom class,collections.namedtuple,typing.NamedTuple,struct.Struct,types.SimpleNamespace
-
Experienced python programmers: are there any standard features of the language that you still don't regularly use? 파이썬의 다양한 언어적 기능
-
What Is Elegant Code? (aka Elegant Solutions For Everyday Python Problems) dunder, custom iterator, functool.partial, contextmanager, closure, wraps/wrapt
-
Solve Your Problem With Sloppy Python os, subprocess, ...
-
7 More Tricks to Write Better Python Code
- Inline if-else statements, Sequence comparisons, Extended unpacking (Python-3 only), Dict comprehensions, collections.OrderedDict, collections.defaultdict, collections.Counter
-
I Thought I Was Mastering Python Until I Discovered These Tricks
-
8 Advanced Python Tricks Used by Seasoned Programmers | by Erik van Baaren | Towards Data Science attrs
-
Road to become a Python Ninja — Data Structures 기본 data structure
-
Iterables vs. Iterators vs. Generators 서로의 관계를 그림과 함께 잘 설명
-
🔝Top 29 Useful Python Snippets 🔝 That Save You Time | The Startup
-
Python — From Intermediate to Superhero list comprehension, lambda, map, filter, reduce, locals, globals, context manager, decorator, generator
-
Performant Python tuple, generator, slotted class, namedtuple, map, filter, comprehension에 대한 테스트
-
3 easy and noninvasive Ways to instantly boost your Python Code Performance
-
고성능 ML 백엔드를 위한 10가지 Python 성능 최적화 팁 | Hyperconnect Tech Blog 정말 좋은 글 배울 점도 많고 좋은 정보도 많음
-
Change The Way You Write Python Code With One Extra Character | by Dorel Masasa | The Startup | Medium asterisk, args, kwargs
-
3 Common Python Flaws You Need To Avoid | by Anupam Chugh | Towards Data Science
-
7 Deadly Sins Python Developers Do | by Anupam Chugh | Oct, 2020 | Towards Data Science
-
6 Typical Errors Python Newbie Should Know | by Vivek Coder | Towards Data Science
-
4 Super Useful Python Features. Four less well-known but incredibly… | by James Briggs | Towards Data Science List append and extend, Yield vs Return, print(start, end), map and lambda
-
Introduction to Priority Queues in Python | by Raivat Shah | Towards Data Science list, heapq, queue.PriorityQueue
-
10 Algorithms To Solve Before your Python Coding Interview | by AnBento | Towards Data Science string, array
-
내 코드를 우아하게 만드는 파이썬 꿀팁 😮 f-string, tuple, zip, enumerate, list comprehension, unpacking operators(
*,**), dictionary, product -
Handy Python Snippets for Cleaner Code | by Tate Galbraith | Better Programming | Nov, 2020 | Medium
-
11 Python Built-in Functions You Should Know | by Christopher Tao | Feb, 2021 | Towards Data Science
-
알아두면 쓸데없는 파이썬 내장 커맨드라인 스크립트 - Morgenrøde 다양한
python -m ...commands -
The difference between a=a+b and a+=b in Python | by Chetan Ambi | Jul, 2021 | Towards AI
-
3 ways to deal with large datasets in Python | by Georgia Deaconu | Jan, 2022 | Towards Data Science
-
- pymotw.com/3/argparse
- Comparing Python Command-Line Parsing Libraries - Argparse, Docopt, and Click
- Get selected subcommand with argparse
set_defaults를 사용해 어떤 sub command를 사용한지 구분 - 파이썬으로 만드는 나만의 커맨드라인 프로그램 #1 - argparse setup.py로 설치까지
- 파이썬으로 만드는 나만의 커맨드라인 프로그램 #2 - click setup.py로 설치까지
- Learn Enough Python to be Useful: argparse
- cliparse: CLI Framework with Argsparse
-
argument
- What does ** (double star) and * (star) do for parameters?
- Keyword argument confusion in Python
- Passing a dictionary to a function in python as keyword parameters
- This Is When Keyword Arguments Are Really Useful // Python Tips - YouTube
- Passion is like genius; a miracle. - 파이썬 positional only, keyword only argument
- 파이썬 positional only, keyword only argument – Passion is like genius; a miracle.
- "Default argument value is mutable" 경고 발생 시
- 함수 디폴트인자의 잘못된 사용
- 파이썬에서 arguments로 *(별표)만 쓴 경우!?
- What Are *args and **kwargs in Python? | by Jonathan Hsu | Better Programming | Medium
- *args & **kwargs in Python. What do they do ? | by Keno Leon | Level Up Coding
-
ast
-
asterisk
-
byte
-
cgitb
- cgitb로 자세한 오류를 찍어 봅니다 debugging
-
class
- practice -
RecursionError: maximum recursion depth exceeded while calling a Python object - Python’s objects and classes — a visual guide
- 클래스 구조 이해하기
- Run-time method patching in Python
- Python - 잘못된 클래스 변수의 사용
- Enriching Your Python Classes With Dunder (Magic, Special) Methods
- What’s in a (Python’s) name?
- What does “name” mean in Python? | by Sohaib Ahmad | Towards Data Science
- Python 과 Mixin
- Start Writing More Classes
- Stop Writing Classes
- The controller pattern is awful (and other OO heresy)
- Raymond Hettinger - Super considered super! - PyCon 2015
- super의 의미(Duet 다중상속), 안원석 - PyCon Korea 2022 - YouTube
__exit__must accept 3 arguments: type, value, traceback- A brief tour of Python 3.7 data classes
- Dynamically create a type with Python
- PYTHON Special methods - Customizing class creation
- Python's Instance, Class, and Static Methods Demystified
- Python Tutorial: class method vs static method
- Let’s get classy: how to create modules and classes with Python
- 파이썬 매직 메소드 (Python's Magic Methods)
- 매직 메서드를 이용한 객체 간의 diff 구하기
- 5 Pairs of Magic Methods in Python That You Should Know | by Yong Cui, Ph.D. | Better Programming | Aug, 2020 | Medium
- Class Attribute VS Instance Attribute of Python
- How to use Python classes effectively | by Rhea Moutafis | Towards Data Science
- Python Objects and Classes: The Most Important Python Concepts That You Need to Understand | Towards Data Science
- Classes & Subclasses in Python. What, how, why and when to use. | by Keno Leon | The Startup | Medium
- Public, Private, and Protected — Access Modifiers in Python | by Sarath Kaul | Better Programming | Medium
- 파이썬 클래스, 객체 개념 - 로스카츠의 AI 머신러닝
- A Simple & Effective Way To Improve Python Class Performance - YouTube
- practice -
-
closure
-
collections
- 파이썬 Collections 모듈 이해하기
- Introducing high-performance datatypes in Python with the collections library | by George Seif | Level Up Coding
- chainmap Python's ChainMap: Manage Multiple Contexts Effectively – Real Python
- Counter Counting Things in Python: A History
- deque Python - 데크(deque) 언제, 왜 사용해야 하는가?
-
configparser
-
contextlib
-
copy
-
coroutine
- A Curious Course on Coroutines and Concurrency
- Łukasz Langa - Thinking In Coroutines - PyCon 2016
- Curious Course on Coroutines and Concurrency
- Python coroutines with async and await
- practice - coroutine
- A brief introduction to concurrency and coroutines (Tutorial)
- Coroutines in Python with examples
- How Do Python Coroutines Work?
- PyconKR 2018 Deep dive into Coroutine
-
csv
- Reading and Writing to CSVs in Python Playing with tabular data the native Python way
- How to combine multiple CSV files with 8 lines of code
- Reading and Writing CSV Files in Python
- CSV Files for Storage? No Thanks. There’s a Better Option | by Dario Radečić | Aug, 2021 | Towards Data Science
- csvkit - A suite of utilities for converting to and working with CSV, the king of tabular file formats. http://csvkit.rtfd.org
- csvsort - Sort large CSV files on disk rather than in memory
- csvsql - Query CSV files using SQL
-
- ctypes tutorial
- ctypes_tutorial ctypes, ctypesgen
- Extending Python via Shared Libraries
- Extending Python With C Libraries and the “ctypes” Module
- Interfacing Python and C: Advanced “ctypes” Features
- python에서 C/C++부르기
- Extending Python with C - Delta Force - Medium
- Calling C/C++ from Python? - Stack Overflow
-
dataclass
- 파이썬 dataclasses가 뭘까?
- TypedDict vs dataclasses in Python — Epic typing BATTLE! | Meeshkan Website Optional
- 12 Examples of How To Write Better Code Using @dataclass | by Bruce H. Cottman, Ph.D. | Towards Data Science
- This Is Why Python Data Classes Are Awesome - YouTube
- An Introduction to Dataclass Decorators in Python | by Diane Khambu | May, 2022 | Python in Plain English
- 모르면 손해? 파이썬 dataclass 5분 설명! - YouTube
-
datetime
- practice
- practice -
datetime.strptime(<date as string>, <format>) - practice - business_duration, holidays library로 업무 시간 계산 시 holiday가 아닌 working hour만 사용
- 파이썬 Datetime 이해하기
datetime.datetime.strptime([DATE IN STRING], '%Y-%m-%d %H:%M:%S').strftime('%s')string time to epoch time(datetime.datetime.today() - datetime.timedelta(days=[# of DAYS])).strftime("%Y%m%d000000")python-get-datetime-for-3-years-ago-todaydatetime.datetime.strftime(datetime.datetime.now() - datetime.timedelta(1), '%Y%m%d')yesterday as YYYYMMDD formatdatetime.datetime.now().date().isoformat()insert into MySQL date type- 주차를 알고 싶을 땐 isocalendar
- elapsed time in milliseconds
- Day 40 : Calculation of Execution Time of a Python Program - YouTube
- 파이썬의 시간대(datetime.timezone)에 대해 알아보기
- Python UTC -6 to KST (UTC +9)
- Parsing and Formatting Dates in Python With Datetime
- 파이썬 날짜 다루기 date, datetime, yyyymmdd
- 파이썬(Python) datetime 클래스 치트시트
- 파이썬 Python 코딩 - 리눅스 크론 cron 스케줄러 기능 구현하기 - YouTube
- 개발자를 괴롭히는 주제 중 하나는 시간입니다.. 하여간 이런 문제가 있다 해도 우리가 평범하게 아는 정도의 시간 관련… | by 이상선 | Jan, 2022 | Medium
- Python에서 time 처리. 시간과 관련된 것을 처리하는 것은 좀 까다롭습니다. 일단, 시간 관련… | by 이상선 | Mar, 2022 | Medium
- Python Calendar Module - YouTube
- arrow: Better dates & times for Python
- datefinder: Find dates inside text using Python and get back datetime objects
- dateutil - powerful extensions to datetime — dateutil 2.8.2 documentation
- Delorean: Time Travel Made Easy — delorean 1.0.0 documentation
- parsedatetime: Parse human-readable date/time strings
- python-holidays: Generate and work with holidays in Python
- Python strftime reference cheatsheet
- pytz: pytz Python historical timezone library and database
-
decimal
-
decorator
- Understanding Python Decorators in 12 Easy Steps!
- Decorator to expose local variables of a function after execution (Python recipe)
- 파이썬 - 데코레이터 (Decorator)
- 서울대 경영대, 2016 벤처창업웹프로그래밍1 (이하 벤1), 파이썬 기말고사 시험문제 3, 4번
- 시간재기
- timer
- python - 함수가 완료되는데에 너무 오래 걸릴 때, timeout시키기 | Hashcode
- @decorators in Python
- Antonio Verardi - Write more decorators (and fewer classes)
- Write More Decorators And Fewer Classes
- Luciano Ramalho - Decorators and descriptors decoded - PyCon 2017
- Colton Myers: Decorators: A Powerful Weapon in your Python Arsenal - PyCon 2014
- Class Decorators: Radically Simple
- The Basics of Python Decorators
- Python Tutorial: Decorators - Dynamically Alter The Functionality Of Your Functions
- Decorators and Context Managers
- Python Decorators as Classes
- Decorators in Python (Mike Burns)
- Python Decorators
- Implementing Decorators in Python
- Python Tutorial: Decorators With Arguments
- Python OOP Tutorial 6: Property Decorators - Getters, Setters, and Deleters
- Why Bother Using Property Decorators in Python? | by Yong Cui, Ph.D. | Better Programming | Medium
- Decorators 101: A Gentle Introduction to Functional Programming - Jillian Munson
- 클래스에 메서드를 추가하는 decorator monkeypatch와 같이 기존 클래스에 새로운 메소드 추가하는 decorator
- decorator를 이용한 함수의 doc string 구하기
- Function Decorators in Python - Add extra functionality to your Python functions
- 파이썬 데코레이터(Decorator)에 파라미터 넣기
- Decorators in Python: Fundamentals for Data Scientists | by Erdem Isbilen | Jun, 2020 | Towards Data Science
- Handling exceptions in Python a cleaner way, using Decorators | by Shivam Batra | The Startup | Medium
- Using Class Decorators in Python. An example-led guide to using Class… | by Stephen Fordham | Towards Data Science
- Why You Need Decorators in Your Python Code | by Michael Krasnov | Better Programming | Medium
- Decorators in Python. Introduction to the design pattern. | by Keno Leon | Python In Plain English | Medium
- Practical Python: Introduction to Decorators | by Soner Yıldırım | Dec, 2020 | Towards Data Science
- 파이썬 데코레이터를 작성하는 법을 배워야 하는 5가지 이유 - 한빛출판네트워크
- 파이썬 5분 강좌: Higher Order Function(ft. Decorator) - 고위함수 - YouTube
- A Deep Dive into Python Decorators
-
descriptor
-
dict
- dict <=> str 변환 시 eval 또는 cPickle
- Replacements for switch statement in Python?
- Pythonic switch statement
- 두 파이썬 딕셔너리를 병합하는 법
z = {**x, **y}How can I merge two Python dictionaries in a single expression?- How to Merge two or more Dictionaries in Python ?
- Raymond Hettinger Modern Python Dictionaries A confluence of a dozen great ideas PyCon 2017
- dict()의 in의 의미
- Dictionaries compare equal if and only if they have the same (key, value) pairs
- Raymond Hettinger Modern Python Dictionaries A confluence of a dozen great ideas PyCon 2017
- Modern Dictionaries by Raymond Hettinger
- Raymond takes us back in time to the 70s and how technologies pioneered then in the field of database research are finding their way back into the modern era
- PyCon 2010: The Mighty Dictionary
- Brandon Rhodes The Dictionary Even Mightier PyCon 2017
- the internals of how dictionaries are implemented in Python
- 2014 PyCon KR: 위대한 dict 이해하고 사용하기
- 구종만 위대한 dict 이해하고 사용하기 PYCON KOREA 2014
- Python Dictionary 순서 보장 원리
- 사전 자료형, 불린 조합 표현식
- David Beazley | Keynote: Built in Super Heroes
- Python3에서 NestedDict 내의 특정 키값을 이용해서 Value를 가져오기
- Dicts are now ordered, get used to it
- The Idiomatic Way to Merge Dictionaries in Python
- Five Ways to Loop Through Python Dictionaries | by Jonathan Hsu | Better Programming | Medium
- Five Cool Python Looping Tips. 5 Tips to help your iterative looping… | by Emmett Boudreau | Towards Data Science 기초. zip, range, enumerate, sorted, filter
- Dictionary View Objects 101. Learning about dynamic view objects in… | by Indhumathy Chelliah | Aug, 2020 | codeburst
- 7 Advanced Python Dictionary Techniques | Towards Data Science
- Dictionary as an Alternative to If-Else | by Khuyen Tran | Towards Data Science
- Python’s Most Powerful Data Type. Everything you ever need to know about… | by Erik van Baaren | Better Programming | Nov, 2020 | Medium
- How to Flatten a Dictionary in Python in 4 Different Ways
- 파이썬 성능최적화 : sorted dict array 순회 로직 - YouTube
-
dis
-
encoding
- practice
- distinguish letter type by unicodedata, regex
- weird case from pyspark-hbase (utf8 & unicode mixed)
- print unicode character in window
locale.setlocale(locale.LC_CTYPE, 'kor')UnicodeEncodeError: locale codec can't encode character '\ub...'가 windows에서 발생하는 경우- string & bytes
- Python unicode cheatsheet encode decode ord normalize
- 파일명 깨짐 - 한글 자모 분리 현상 normalize
- How to convert string to byte arrays?
- Python bytearray ignoring encoding?
- python: how to convert a string to utf-8
- Python 2.x 한글 인코딩 관련 정리
- 파이썬 셸과 IDLE의 입출력 인코딩에 대해
- Python Unicode: Encode and Decode Strings (in Python 2.x)
- Encoding and Decoding Strings (in Python 3.x)
- 파이썬 2와 유니코드
- Python string formatting and UTF-8 problems workaround
- USING DHARMA TO REDISCOVER NODE.JS OUT-OF-BAND WRITE IN UTF8 DECODER
- 한상곤: 문자열? 그런 달달한 것이 남아있긴 한가? - PyCon APAC 2016 unicode는 문자셋, encoding은 문자셋을 메모리에 쓰는 것
- 파이썬 유니코드 이해하기
- 크롤링 데이터의 한글이 깨져요
- cChardet - universal character encoding detector
- The Updated Guide to Unicode on Python
- Everything you did not want to know about Unicode in Python 3
- 파이썬의 문자열 인코딩
- Processing Text Files in Python 3
- Common migration problems
- Strings, Bytes, and Unicode in Python 2 and 3
- python 3 의 string 정리
- Strings in 3.0: Unicode and Binary Data
- 이펙티브 파이썬 - 3. bytes, str, unicode의 차이점을 알자 · MinhoPark
- How to declare a byte array contains non-ascii characters without escape in python 3
- dotnetperls.com/bytes-python
- The only problem with Python 3's str is that you don't grok it
- Character Encoding in python
- Python one-liner to print Roman numerals
- practice
-
exception
- 예외처리 (Exceptions)
- Alex Martelli - Exception and error handling in Python 2 and Python 3 - PyCon 2016
- 예외처리 블록에 대한 잘못된 파라미터 지정
- Professional Error Handling With Python
- Amandine Lee Passing Exceptions 101 Paradigms in Error Handling PyCon 2017
- LBYL vs EAFP: Preventing or Handling Errors in Python – Real Python
- How to Define Custom Exception Classes in Python - Towards Data Science
- Eyal Trabelsi - Elegant Exception Handling - YouTube
- Quick Python Tip: Suppress Known Exception Without Try Except | by Christopher Tao | Towards Data Science
- Robust exception handling - Eli Bendersky's website
- Raise better errors with Exception Groups - presented by Or Chen - YouTube 3.11
-
ftplib
-
function
-
functools
-
You Can Do Really Cool Things With Functions In Python - YouTube
-
Functools is one of the MOST USEFUL Python modules - YouTube
-
partial
>>> from functools import partial >>> foo = partial(lambda a, b: a + b, b=3) >>> foo(2) 5
-
gc
- Visualizing Garbage Collection in Ruby and Python
- Dismissing Python Garbage Collection at Instagram
- 강성일: GC없는 Python을 추구하면 안 되는 걸까
- Copy-on-write friendly Python garbage collection
- COW(Copy-on-write)가 발생하는 Python garbage collection python3.7에 추가된 gc.freeze
- Python GC가 작동하는 원리
- 자동 Garbage Collection 주기
- Garbage collection in Python: things you need to know
- Do you know how python cleanses itself? | LinkedIn reference count
- heapsy: Python Heap Tracer
-
generator
- practice - read chars from list of string
- Extending Python’s generators to support mainloops
- 파이썬 - 제너레이터 (Generator)
- 파이썬의 제너레이터와 이터레이터
- 파이썬 iterator generator 이해하기
- Sieve daisy chain
- 이터레이터와 제너레이터
- Using Python Generator to Monitor Data
- Data Processing using Python Generators
- python - db stored procedure 호출에 generator 활용하기
- Threaded Generator in Python
- How — and why — you should use Python Generators
- Generators: The Final Frontier - Screencast
- David Beazley: Generators: The Final Frontier - PyCon 2014
- Python의 Generator 알아보기
- Python Generators Explained! (Sort of)
- How to Create a Generator in Python
- Optimize python code with generators - Chetan Mishra - Medium
- 파이썬 generator는 어떻게 실행 위치를 기억하고 있을까요?
- BayPiggies June 2021: Fun with Generators - YouTube
-
globals Alternatives to Using Globals in Python | by Keno Leon | Better Programming | Medium
-
hash
-
hashlib
- 패스워드와 토큰 자체 발행 - 이상선 - Medium hashlib, base64, uuid
-
idle
-
import
- practice - relative import
- The definitive guide to solve the infamous Python exception “ModuleNotFoundError”
- 같은 이름을 가진 root 패키지의 하위 모듈/패키지 접근
- Top to down, left to right (Surprise talk) - James Powell import, scope 이외의 내용도 많지만 분류가 애매해서
- 파이썬 상대경로 import 에러 ImportError: attempted relative import with no known parent package
- Start Python #4 Backend Program 만들기 – library import - Kowana's coding
- importify: Import and export your configuration like a boss
- import-tracker: Python utility for tracking third party dependencies within a library
- reorder_python_imports: Rewrites source to reorder python imports
-
__init__.py -
intern
-
io
-
isinstance
-
itertools
- 데이터 분석에 피가 되는 itertools 익히기
- You (Probably) Don’t Need For-Loops
- Tour of Python Itertools
- Reduce() vs Accumulate() in Python | by Indhumathy Chelliah | codeburst
- 5 Advanced Functions in Itertools To Simplify Iterations in Python | by Yong Cui, Ph.D. | Towards Data Science
- The Must-Know Tools from the Python Library itertools | Python in Plain English
-
- Python: Lambda Functions
- Yet Another Lambda Tutorial
- Python Functions - lambda 2015
- A tale of two lambdas: The joys of working in a polyglot team
- 파이썬+Lambda+이해하기 20160315
- Python Lambda Expressions in Data Science | by Sohaib Ahmad | Code Python | Sep, 2020 | Medium
- Anjana Vakil - Mary had a little lambda
- funcional programming in scala에서 하던 것과 비슷하게 lambda를 이용해 숫자를 정의하고 int로 변환하고 arithmetic operation등을 만듦
-
json
-
list
- Python List Comprehensions: Explained Visually
- Python List Tutorial With Simple Python Projects For Beginners
- Understanding nested list comprehension syntax in Python
- 3 Python list comprehension tricks you might not know yet
- 9 Things to Know to Master List Comprehensions in Python
- 파이썬의 Comprehension 소개
- Python List Comprehensions in 5-minutes | by Daniel Bourke | Towards Data Science
- List Comprehension in Python Explained for Beginners
- 왜 리스트 컴프리헨션에 if만 있을때와 else도 있을 때 문법이 다를까?
- Python Comprehension. A guided tour and quick start. | by Keno Leon | Medium
- 파이썬에서 2중 리스트를 flatten하게 만들기
- Python - 리스트 순회중 수정하는 문제
- Beginners guide to Iteration in python | by Keno Leon | Medium
- Printing Lists as Tabular Data
- [{...}] * 10 주의점
- Python: copying a list the right way
- Python 의 Filter / Map / Reduce 그리고 Comprehension
- A quick yet complete tour of lists in Python3 in just seven minutes
- How slow is python list.pop(0) ?. An empirical study on python list.pop… | by Hongjian Wang | Medium
- 파이썬의 list.pop(0)을 쓰면 안 되나요? collections.deque가 가장 빠르다는 이야기
- Python Lists Are Overrated. Consider these potentially superior… | by Aashish Nair | Oct, 2021 | Towards Data Science
-
- DEBUG < INFO < WARNING < ERROR < CRITICAL, 기본 설정은 WARNING
- practice - experiences
- practice - basic logging with yaml configuration
- Exceptional Logging of Exceptions in Python
- log.lpy
- example TimedRotatingFileHandler
- 주의; 로그를 쓰지 않으면 해당 시간이 되도 log file이 rotate되지 않는다. 예를 들어 서버에서 TimeRotatingFileHandler를 사용하는 경우, 서버에 request가 없어서 log를 기록하려는 시도가 없으면, 해당 주기가 되어도 log file이 rotate되지 않으므로 주의. 위의 예제에서
logger.info("This is a test!")를 제거하고 실행해보면 알 수 있음 - 로그를 쓰기 시작한 시간으로부터가 아니라 매일 정시에 log rotate를 하려면
d가 아니라midnight을 사용
- 주의; 로그를 쓰지 않으면 해당 시간이 되도 log file이 rotate되지 않는다. 예를 들어 서버에서 TimeRotatingFileHandler를 사용하는 경우, 서버에 request가 없어서 log를 기록하려는 시도가 없으면, 해당 주기가 되어도 log file이 rotate되지 않으므로 주의. 위의 예제에서
- Python logging best practices with JSON steroids
- Making Python loggers output all messages to stdout in addition to log
- Python Logging (function name, file name, line number) using a single file
- 파이썬 로깅의 모든것
- Python logging causing latencies?
- logging 관련 몇몇 정리
- logging - propagation
- Python's Built-In 'logging' Module
- pycon kr 2018.12 파이썬 로깅, 끝까지 파보면서 내가 배운 것 - 황현태
- Copy-Pastable Logging Scheme for Python | by Dalya Gartzman | codeburst
- Python3: Logging With Multiprocessing | by Jonathonbao | Medium
- Power-Up Your Python Logging. A guide to take you from beginner to… | by David Tippett | Better Programming | Medium
- What to Log? From Python ETL Pipelines! | by Shiva Koreddi | Nov, 2021 | Towards Data Science
- Lutz Ostkamp - How to format strings for logging in Python | PyData Global 2022 - YouTube
- Autologging — easier logging and tracing for Python classes
- Eliot: Logging that tells you why it happened — Eliot 1.14.0+0.g3584072 documentation
- json-logging-python: Cloud-native distributed Python logging library to emit JSON log that can be easily indexed by logging infrastructure
- loguru: Python logging made (stupidly) simple
- logzero Robust and effective logging for Python 2 and 3
- python-json-logger · PyPI
-
loop
-
map
-
match case
-
metaclass
- Python metaclasses
- python data model 이해하기
- Python data model
- Intro to the Python Data Model and Pythonic Programming
- It's metaclasses all the way down
- Metaclasses in Python
- The Fun of Reinvention (Screencast)
- The Fun Of Reinvention 파이썬3.6으로 흑마법을 부려보자
- Saving 9 GB of RAM with Python’s
__slots__ - A quick dive into Python’s “slots”
- Understand slots in Python. A simple way to improve your Python… | by Xiaoxu Gao | Towards Data Science
- CLASS ATTRIBUTE 와 INSTANCE ATTRIBUTE 의 구분과 구현
- 내부 동작을 이해하는 측면에서는 좋으나, 실제로는 전혀 쓸모없어 보임
- Underscore(_)로 시작하는 파이썬 클래스명
- PyCon Korea 2019 리얼월드 메타클래스 매우 좋은 발표 내용
- 리얼월드 메타클래스
- Python Reflection and Introspection | by Jamie Bullock | Better Programming | Medium
- How to Create Lazy Attributes to Improve Performance in Python | by Yong Cui, Ph.D. | Better Programming | Medium @property decorator,
__getattr__ - Mind-bending metaclasses - adding function overloads to Python - YouTube
- Python Metaclasses: Everything is an Object - YouTube
-
method
-
mmap
-
monkey patch
-
multiprocessing multithreading threading parallel
-
practice
-
logging
-
starmapmap은 multiprocessing으로 호출할 function argument로 하나만 줄 수 있어서 여러 개를 줘야 할 때는 starmap 사용 -
for ident, stack in sys._current_frames().items(): logger.info(("%d" % ident) + "".join(traceback.format_list(traceback.extract_stack(stack)))) -
파이썬 동시성 프로그래밍 - (9) Concurrent.Futures & ProcessPoolExecutor
-
Michal Wysokinski - Running Python code in parallel and asynchronously
-
Multithreading in Python with Global Interpreter Lock (GIL) Example
-
Functional Programming in Python: Parallel Processing with "multiprocessing"
-
Functional Programming in Python: Parallel Processing with "concurrent.futures"
-
Amber Brown Implementing Concurrency and Parallelism From The Ground Up PyCon 2017
-
Advanced Python: Concurrency And Parallelism | by Farhad Malik | FinTechExplained | Medium
-
Taking charge of your race conditions - presented by Borjan Tchakaloff - YouTube
-
An introduction to parallel programming using Python's multiprocessing module
-
Start Multithreading vs Multiprocessing in 5 minutes using Python
-
Unlocking your CPU cores in Python (feat. multiprocessing) - YouTube
-
Get a 2–6x speed-up on your pre-processing with these 3 lines of code! concurrent.futures
-
CUDA In Your Python: Effective Parallel Programming on the GPU
-
Parallel Computing in Python: Current State and Recent Advances
-
Cheryl Roberts - Parallelization of code in Python for beginners | PyData Global 2022 - YouTube
-
Shared Memory
- practice - shared memory with multiprocessing
- dijkstra_shm.py
- parallel_write.py
- Python Shared Memory in Multiprocessing - Mingze Gao
- Python Shared Memory in Multiprocessing | by Adrian Gao | Medium
- Multiprocessing example
- python - Use numpy array in shared memory for multiprocessing - Stack Overflow
- Fill a numpy array using the multiprocessing module
- On Sharing Large Arrays When Using Python's Multiprocessing
-
threading
- practice
- thread dump
- Vinicius Pacheco - Green threads in Python
- Python Multithreading Tutorial: Concurrency and Parallelism
- Running a method as a background thread in Python
- An Intro to Threading in Python
- How to Create a Thread in Python
- Using a global variable with a thread
- Thread Synchronization Mechanisms in Python
- Multithreading in Python | Set 2 (Synchronization)
- Python 3 - Multithreaded Programming
- Running a method as a background process in Python
- Using Locks to Prevent Data Races in Threads in Python | by Rachit Tayal | Python Features | Medium
- Threads in Python. The basics. | by Keno Leon | Medium
- Threads in Python: Speed Up Python With Concurrency - YouTube
- Python threads synchronization: Locks, RLocks, Semaphores, Conditions and Queues – Laurent Luce's Blog
-
-
namedtuple
-
namespace
-
number, numeric types
-
object
-
os
-
patch
-
pathlib
-
pep
-
pickle
pickle_file = '<filename>' with open(pickle_file, 'rb') as f: u = pickle._Unpickler(f) u.encoding = 'latin1' save = u.load() dataset = save['<key>'] -
print
-
pprint
-
profile
- PROFILING IN PYTHON
cPickle.PicklingError: Can't pickle <type 'function'>: attribute lookup __builtin__.function failed- happens when multiprocessing + cProfile
python -m cProfile some_multiprocessing.py
- happens when multiprocessing + cProfile
- How can you profile a Python script?
- Accurate Time Measurements Python
- Understand How Much Memory Your Python Objects Use
- memory_profiler
defaultdict(list), key는 (str, str), value는 list of (str, int)의 경우- 1,000,000개 memory 약 440MB, 입력 4m정도 소요
- 10,000,000개 memory 약 4.1GB, 입력 41m정도 소요
- Profiling Python in Production
- PUDB 콘솔 디버거
- profiling - An interactive continuous Python profiler
- Profiling CPython at Instagram
- Profiling and optimizing Python code
- Profiling Python Code
- Building FunctionTrace, a graphical Python profiler
- 파이썬 코드 프로파일링에 유용한 라이브러리 5가지 - ITWorld Korea Time, Timeit, cProfile, Pyinstrument, Py-spy, Yappi
- Visualizing the Results of Profiling Python Code - Thirld Word Blog pyprof2calltree pyinstrument
- How to profile slow code in Python - YouTube
- Finding performance problems: profiling or logging?
- Memray - a memory profiler for Python
- Prodfiler
- Pympler - a development tool to measure, monitor and analyze the memory behavior of Python objects in a running Python application
- pyperf: Toolkit to run Python benchmarks
- pyroscope Open Source Continuous Profiling Platform | Debug performance issues down to a single line of code | Open Source Continuous Profiling Platform
- Py-Spy: A sampling profiler for Python programs
- Sciagraph, performance observability for Python batch jobs
- StackImpact Python Agent - Production Profiler: CPU, memory allocations, blocking calls, exceptions, metrics, and more https://stackimpact.com
- tracemalloc — Trace memory allocations
- VMprof Python client profiler
- yappi: Yet Another Python Profiler, but this time thread&coroutine aware
- Profiling을 통해 python async web application 병목지점 찾기 ⛑ - make all
- Async web 작성 시에는 logging도 고려해야 하는 데 이 부분이 빠져있음
- 기본 logging은 sync이기 때문에 bufferred or async logging을 사용하지 않으면 async web에서 성능 저하 발생
- 또한 여기서 mysqlclient(libmysql 기반)와 aiomysql(PyMySQL)을 비교했는데, 기본적으로 PyMySQL이 mysqlclient보다 2~4배 느림
- mysqlclient는 sync 기반으로 threadpool로만 동작
- Async web 작성 시에는 logging도 고려해야 하는 데 이 부분이 빠져있음
- Profiling을 통해 python async web application 병목지점 찾기 ⛑ - make all
-
property
-
random
-
re
-
self
-
serialization
-
sets
-
setup.py, distutils, packaging
- setup.py와 requirements.txt의 차이점과 사용 방법
- 파이썬 프로젝트 시작하기 - Distutils
- 파이썬 프로젝트 시작하기 - Setuptools
- 파이썬 package 배포 하기
- Packaging and Distributing Projects
- pypi 패키지 만들어보기
- 파이썬 패키지 Pypi에 오픈소스 등록하는 방법
- 파이썬 Python 코딩 - 패키지 만들어서 PyPI에 등록하기, 파이썬 저장소에 소스코드 등록, 개발자 인증^^ - YouTube
- 로컬 PYPI 서버 설정하기
- 파이썬 패키지를 공유하는 법
- How We Deploy Python Code (hint: not using Git)
- The problem with packaging in Python
- From a python project to an open source package: an A to Z guide
- How to Prepare and Publish Your First Python Package | by Yong Cui, Ph.D. | Better Programming | Oct, 2020 | Medium
- devpi - Python PyPi staging server and packaging, testing, release tool http://doc.devpi.net
- Top PyPI Packages: A monthly dump of the 4,000 most-downloaded packages from PyPI
-
signal
-
socket
- Python Network Programming
- High-performance Networking with Python
- Finding local IP addresses using Python's stdlib
- 처음 만드는 온라인 게임 03-01 : Python HTTP server 개발
- 처음 만드는 온라인 게임 03-02 : Python HTTP server 개발
- 처음 만드는 온라인 게임 04-01 : Python web socket server 개발
- 처음 만드는 온라인 게임 04-02 : Python web socket server 개발
- How to Do Socket Programming in Python
- Python으로 채팅 구현하기
- 2017 파이컨 튜토리얼 - 네트워크 프로그래밍 개념 맛보기
- python을 이용한 다중 채팅 구현하기
- Sockets Tutorial with Python 3
- 남의 컴퓨터를 내 마음대로 다룬다? - Python Reverse Shell
- Learn Network Programming in Python by Building Four Projects
- Reverse Engineering A Mysterious UDP Stream in My Hotel - Gokberk Yaltirakli
- python - 파이썬의 epoll 및 비 블로킹
- 파이썬 소켓으로 직접 구현하는 SMTP 프로토콜
- Paul Butler – What does it mean to listen on a port?
-
sort
- Length-wise-sorted list but, same length in alphabetical-order in a step
- LAZY SORTING (PYTHON RECIPE)
- sorted 함수 예제
- 3 Reasons Why You Should Almost Always Use sorted() in Python
- 파이썬 sorted 사용 방법을 알아봅시다 custom class lt
- 파이썬 다중정렬 : tuple을 이용한 dsu 패턴으로 간단하게 처리합시다
- 파이썬 문자열 다중정렬 : sort가 stable 하다는 것을 이용합시다.
- cmp_to_key
-
ssl
-
__str__ -
string
-
The unreasonable effectiveness of f-strings and re.VERBOSE - death and gravity
-
0 padding for multi variables; Nicest way to pad zeroes to string
from datetime import datetime _today = datetime.today() '{0:04d}{1:02d}{2:02d}'.format(_today.year, _today.month, _today.day) -
replace
-
import string [string].translate(None, string.whitespace) -
5 Python String Methods For Better Formatting | by Tate Galbraith | Jul, 2020 | Level Up Coding
-
22 Pythonic Tricks for Working with Strings | by Richard Quinn | Python In Plain English | Medium
-
Python strings are immutable, but only sometimes - Austin Z. Henley
-
- pymotw.com/3/subprocess
- asyncio-subprocess
- pymotw.com/3/asyncio/subprocesses.html
- python, subprocess: reading output from subprocess
- 파이썬에서 bash 명령어 실행 subprocess, pexpect
- subprocess를 사용한 병렬 프로그래밍 - (1)
- python-daemon test해본 결과 daemon으로는 잘 동작하지만 크게 쓸모가 있는지는 모르겠음
subprocess.run([...], stdin=subprocess.DEVNULL, stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT)- Popen처럼 docker flask app에서 api를 호출해 시간이 오래 걸리는 작업을 별도 process로 실행하는 경우를 위해 사용
- 공식 문서에 따르면 3.5부터 추가되었으며 모든 경우 run 사용을 추천한다고 함
- Popen과 달리 똑같은 형식으로 호출해도 blocking되고 모든 작업이 끝나야 caller로 돌아옴
subprocess.Popen([...], stdin=subprocess.DEVNULL, stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT)- docker flask app에서 api를 호출해 시간이 오래 걸리는 작업을 별도 process로 실행하는 경우를 위해 사용
- async처럼 별도로 실행하고 바로 caller로 돌아옴
- pipe로 한글이 포함되는 경우
encoding=[utf8|euc-kr|cp949|...]oruniversal_newlines=True설정이 필요할 수도 있음
- Python trick: asynchronously reading subprocess pipes
- Streaming subprocess stdin and stdout with asyncio in Python
- Subprocess 모듈 사용법 – 파이썬에서 서브 프로세스를 생성하기
- Subprocess timeout failure
- sh - a full-fledged subprocess replacement for Python 2.6 - 3.8, PyPy and PyPy3 that allows you to call any program as if it were a function
-
sys
-
tarfile
-
timeit -
turtle
-
TypeError
TypeError: file() argument 1 must be encoded string without NULL bytes, not str- Common Mistakes as Python Web Developer
-
unicodedata
-
urllib
-
urlparse
-
uuid
-
webbrowser
-
with, context manager
-
xml
- XML parsing - untangle, xmltodict
- python3 Google News RSS XML DATA crawling / Parsing 구현 Sample MultiProcess Pool 적용
- 파이썬 Xml 이해하기
- Working with XML tree data in Python
- 박피디의 게임 개발 이야기 : Cubase drm xml 포멧 파일을 단순한 text 포멧으로 변경하는 python 코드 beautifulsoup
- 박피디의 게임 개발 이야기 : Cubase 드럼맵 파일을 drm <-> text 형태로 변환하는 파이썬 코드
- XML & ElementTree || Python Tutorial || Learn Python Programming - YouTube
-
yield
- Python의 yield 키워드 알아보기
- [Python의 Generator와 yield 키워드](Python의 Generator와 yield 키워드)
- Python의 yield from 키워드는 무엇일까
- What Are Generators, Yields, and Streams in Python?
-
zipfile
- docs.python.org/3/library/asyncio.html
- github.com/python/asyncio/wiki/ThirdParty
- A curated list of awesome Python asyncio frameworks, libraries, software and resources
- The new Python asyncio module aka “tulip”
- github.com/python/asyncio/wiki/Benchmarks
- Python tricks: Demystifying async, await, and asyncio
- Understanding Asynchronous IO With Python 3.4's Asyncio And Node.js
- Miguel Grinberg Asynchronous Python for the Complete Beginner PyCon 2017
- AsyncIO for the Working Python Developer
- Asyncio Coroutine Patterns: Beyond await
- Asyncio Coroutine Patterns: Errors and cancellation
- Asynchronous Python Await the Future
- 비동기 파이썬 gevent, tornado
- Async I/O and Python
- blocking, non blocking, eventlet, twisted, GLib, Tulip, Coroutines, Generators, and Subgenerators
- 배준현 Python 3 4; AsyncIO PYCON KOREA 2014
- A Weekend with Asyncio
- Python async/await Tutorial aiohttp
- Python 3, asyncio와 놀아보기
- A Web Crawler With asyncio Coroutines
- Concurrency in Python threading, multiprocessing, aiohttp
- asyncio 공부 echo server
- python async URL요청 aiohttp
- asyncio
- asyncio : 단일 스레드 기반의 Nonblocking 비동기 코루틴 완전 정복
- async with : 비동기 컨텍스트 매니저
- How the heck does async/await work in Python 3.5?
- 파이썬의 await vs return vs return await
- How to Scrape and Parse 600 ETF Options in 10 mins with Python and Asyncio
- Understanding Asynchronous Programming in Python
- Exploring Python 3’s Asyncio by Example
- ASYNC EXECUTION IN PYTHON USING MULTIPROCESSING POOL
- Playing with asyncio comparison with twisted & gevent
- 어릴 적 할머니가 들려주신 옛 wsgi wsgi & gevent
- asyncio.readthedocs.io
- Python 3 asyncio basic producer / consumer example
- Threaded Asynchronous Magic and How to Wield It
- Some Python 3 asyncio snippets
- Controlling Python Async Creep
- async_await_help.py
- Using asynchronous for loops in Python
- 파이썬과 비동기 프로그래밍
- Advanced asyncio: Solving Real-world Production Problems
- asyncio: We Did It Wrong
- 왜 asyncio에 뮤텍스 락이 필요할까? asyncio.Lock()
- asyncio를 이용한 비동기 처리 이해와 promise와 비교하기
- An Introduction to ASGI, Asynchronous Server Gateway Interface
- "파이썬 웹 개발의 미래" ASGI의 개념과 활용 방법 - ITWorld Korea
- Sync vs. Async Python: What is the Difference? - miguelgrinberg.com
- Exactly-Once Initialization in Asynchronous Python
- zzzeek : Asynchronous Python and Databases
- Fast & Asynchronous in Python. Accelerate Your Requests Using asyncio | by Dylan Castillo | Towards Data Science
- Stop Waiting! Start using Async and Await! | by Simon Hawe | Towards Data Science
- An Introduction to Asynchronous Programming in Python | by Konopka Kodes Blog | Medium
- I'm not feeling the async pressure | Armin Ronacher's Thoughts and Writings
- Async Python is not faster
- asyncio 뽀개기 1 - Coroutine과 Eventloop
- asyncio 뽀개기 2 - Future의 활용
- asyncio 뽀개기 3 - SIGTERM (CTRL+C) 올바르게 처리하기
- Python asyncio를 활용한 효율적인 광고 데이터 수집 | MADTECH
- youtube
- Fear and Awaiting in Async (Screencast)
- Common asynchronous patterns in Python
- Tulip: Async I/O for Python 3
- Python 3.5+ Async: An Easier Way to do Concurrency
- Yury Selivanov - async/await in Python 3.5 and why it is awesome
- Yury Selivanov asyncawait and asyncio in Python 3.6 and beyond PyCon 2017
- Yury Selivanov - Asyncio in Python 3 7 and 3 8 Trio
- Barry Warsaw aiosmtpd A better asyncio based SMTP server PyCon 2017
- Practical Python Async for Dummies
- Get to grips with asyncio in Python 3 - Robert Smallshire
- Coroutine Concurrency in Python 3 with asyncio - Robert Smallshire
- The Other Async (Threads + Async = ❤️)
- Jonas Obrist - Why you might want to go async
- Anton Caceres - Using the right Async tool, present day
- Amit Nabarro - Asynchronous I/O and the real-time web
- Asynchronous Python For The Complete Beginner
- ASYNCHRONOUS PROGRAMMING WITH PYTHON
- Get To Grips With Asyncio In Python 3
- Building real-world applications with
asyncio - Keynote David Beazley - Topics of Interest (Python Asyncio)
- Why should I care about asyncio
- Getting Started with asyncio and Python
- Asyncio Tasks in Python Tutorial
- A Really Gentle Introduction to Asyncio
- What Is Async, How Does It Work, and When Should I Use It? (PyCon APAC 2014)
- What in the World is Asyncio? by Josh Bartlett
- Asyncio - Asynchronous programming with coroutines - Intermediate Python Programming p.26
- Async / Await and Asyncio In Python
- Webscraping With Asyncio - Jose Manuel Ortega
- James Kirk Cropcho - Asynchronous Python A Gentle Introduction
- Hrafn Eiriksson - Asyncio in production asyncio migration에 대한 실용적인 안내
- Async & Await Tutorial
- Asyncio, websockets, and BTC sitting in a tree - Giovanni Lanzani
- John Reese - Thinking Outside the GIL with AsyncIO and Multiprocessing - PyCon 2018
- Async/Awaiting Production
- Dmitry Nazarov: "Future Pythonic Web: ASGI & Daphne"
- Build Your Own Async
- Python Asyncio, Requests, Aiohttp | Make faster API Calls - YouTube
- Diagnose slow Python code. (Feat. async/await) - YouTube
- How To Easily Do Asynchronous Programming With Asyncio In Python - YouTube
- 유튜브 조회수 수집기 (YouTube View count Scraper) — 글 쓰는 기획자 '길'
- aiofiles: file support for asyncio
- aiohttp: Asynchronous HTTP Client/Server
- practice - aiohttp
- aiohttp server deployment
- Aiohttp로 대량의 requests 처리하기
- Making 1 million requests with python-aiohttp
- Macro-benchmark with Django, Flask and AsyncIO (aiohttp.web+API-Hour)
- 황성현: aiohttp in Production
- Building the Real-time Web with Python and aiohttp (Steven Seguin)
- Building The Real Time Web With Python
- Day 2: Pau Freixes Alió - Running Aiohttp at scale
- aiohttp로 하는 비동기 HTTP 요청
- How to Speed Up API Requests With Async Python - YouTube
- aio-libs - The set of asyncio-based libraries built with high quality
- aiomysql - a library for accessing a MySQL database from the asyncio http://aiomysql.readthedocs.io
- aiosql: Simple SQL in Python
- aiotools - Idiomatic asyncio utilties
- Curio - a modern library for performing reliable concurrent I/O using Python coroutines and the explicit async/await syntax introduced in Python 3.5
- Quart - a Python asyncio web microframework with the same API as Flask
- Sanic - a Flask-like Python 3.5+ web server that's written to go fast
- 한동안 top 10 contributor였던 개발자 Jeong YunWon님의 경고
- flask와 비슷하다 = 사기. 이제 그런 소개도 빼버린것 같은데, 개발자들은 호환성 맞출 생각 없음. url path도, blueprint도, 사실은 아무것도 안맞으므로, flask와 비슷해 보여서 쓰기로 결심했다면 사용하면 안됨. decorator 씌워서 route하는거 딱 하나만 비슷
- 전반적으로 소프트웨어 디자인 자체에 대해 별 생각이 없음. 참고: sanic-org/sanic#37
- 품질 관리보다 벤치마크에 집착. 벤치마크에 큰 향상이 있으면 쉽게 릴리즈. 심각한 소프트웨어 버그는 때로는 몇달씩 릴리즈되지 않을 수 있음. http 헤더 fragment를 잘못 파싱해 헤더가 누락되는 버그는 master에 머지된 후 릴리즈되기 까지 6개월
- 프로파일링 기반으로 성능을 측정함에도 불구하고 합리적인 reasoning 없이 성능미신에 의해 최적화. 이 코드는 현재 사라졌으니 이 정도만 코멘트.
- 위와 같은 문제와 여러 변주 이후로 토론에 지친 "정상적인 설계"를 원하는 초기 기여자들은 대부분 떠남. Contributors에 들어가서 기여자들이 얼마나 빨리 떠나는지 보고, 그들이 어떤 이슈에 참여했나 보면 어떤 일이 일어나는지 알 수 있음
- sanic.readthedocs.io
- Dougal Matthews - Async Web Apps with Sanic
- Python Sanic Tutorial
- Introducing Myself to Sanic, a Python Web Server
- More Sanic/Python Fun. Submitting a Form via Ajax Post Request with Vuejs
- postit-sanic - An REST API and Single Page App with Sanic; A Python Webserver/Microframework
- programcreek.com/python/index/9697/sanic
- Pycon Korea 2018-Sanic을 활용하여 Microservice 구축하기-이재면
- Sanic RESTful open framework 제작 일지 — 1 Pytest | by 달가을 | Sep, 2020 | Medium
- 한동안 top 10 contributor였던 개발자 Jeong YunWon님의 경고
- Starlette - a lightweight ASGI framework/toolkit, which is ideal for building high performance asyncio services
- tokio - Asyncio event loop based on tokio-rs (WIP)
- Trio – Pythonic async I/O for humans and snake people 🐍
- Nathaniel J. Smith - Trio: Async concurrency for mere mortals - PyCon 2018
- 구조적 동시성에 대한 소고, 또는 Go 문의 해로움
- 정말 좋은 글. 특히 놀라운 건 Donald Knuth같은 사람도 한 때 goto를 옹호했다는 점
- Nathaniel J Smith - Python Concurrency for Mere Mortals - Pyninsula #10
- Trio: Structured Concurrency for Python (Alternative to Asyncio) - YouTube
- vibora - Fast, asynchronous and elegant Python web framework. https://vibora.io
- Music Genre Classifier
- 파이썬으로 계이름 맞히기
- Making A Synth With Python — Oscillators | Alan | Python in Plain English
- It is ridiculously easy to generate any audio signal using Python
- Convert Text into Audio using Python - YouTube
- cherrymusic - Stream your own music collection to all your devices! The easy to use free and open-source music streaming server http://www.fomori.org/cherrymusic
- kord: a music theory development framework in python
- Librosa - audio and music processing in Python
- pedalboard: 🎛 🔊 A Python library for working with audio
- pydub: Manipulate audio with a simple and easy high level interface
- PySynth — A Music Synthesizer for Python
- Automated, data-driven code review
- Automate the Boring Stuff with Python
- One Day Builds: Instagram Automation Using Python
- Super quick Python automation ideas
- Home Assistant - a home automation platform running on Python 3
- 유서원: Practical automation for beginners
- Anton Chernikov - Automate your tasks with Python and publish with Chat Apps - YouTube
- Automating Every Aspect of Your Python Project | by Martin Heinz | Towards Data Science
- Automate Your Reporting With Python, Vue.js and Gmail | The Startup
- Automating your daily tasks with Python | by Shivani Sinha | Analytics Vidhya | Medium
- 10 Automation Scripts for Your Daily Python Projects | Python in Plain English
- Baseball Analytics: An Introduction to Sabermetrics using Python
- Parses, Analyzes and Predicts for the Korean Baseball League
- 데이콘 야구대회 튜토리얼 2-1 판다스 기본 문법
- Linear Regression: Moneyball — Part 1 A statistical case study of the popular sports story
- Ryan Williams: Accelerating Single-cell Bioinformatics with N-dimensional Arrays | PyData Miami 2019 HDF5, Zarr, dask, zappy
- Let’s set up a code editor for Python and Bioinformatics | by rebelCoder | Python In Plain English | Medium
- Want to get into programming or bioinformatics but not sure where to start? | by rebelCoder | Medium
- Bioinformatics in Python; DNA Toolkit Introduction | by rebelCoder | Python In Plain English | Medium
- Getting started in Bioinformatics: A step-by-step guide. | by rebelCoder | Aug, 2020 | Medium
- Bioinformatics in Python; DNA Toolkit Part 1: Validating and counting nucleotides | by rebelCoder | Python In Plain English | Medium
- Bioinformatics in Python; DNA Toolkit Part 2: Transcription and Reverse Complement | by rebelCoder | Python In Plain English | Medium
- Bioinformatics in Python; DNA Toolkit. Part 3: GC Content Calculation | by rebelCoder | Python In Plain English | Medium
- Bioinformatics in Python; DNA Toolkit. Part 4: Translation, Codon Usage | by rebelCoder | Python In Plain English | Medium
- Bioinformatics in Python; DNA Toolkit. Part 5, 6 & 7: Open Reading Frames, Protein Search in NCBI database | by rebelCoder | Python In Plain English | Medium
- Bioinformatics Tools Programming in Python with Qt: Part 1. | by rebelCoder | Python In Plain English | Medium
- Bioinformatics Tools Programming in Python with Qt: Part 2. | by rebelCoder | Python In Plain English | Medium
- Python for Bioinformatics - Drug Discovery Using Machine Learning and Data Analysis - YouTube
- Biopython Tutorial and Cookbook.pdf
- PyCTD - programmatically access and analyze data provided by the Comparative Toxicogenomics Database
- Rosalind - a platform for learning bioinformatics and programming through problem solving
- 5 Python books for beginners
- 20 Best Free Tutorials to Learn Python: PDFs, eBooks, Online
- The Little Book of Python Anti-Patterns
- Collection Of 51 Free eBooks On Python Programming
- Jupyter Notebooks with Fluent Python examples https://github.com/AllenDowney/fluent-python-notebooks
- 50+ Free Python Programming Books PDF
- 정보교육을 위한 파이썬 Python for Informatics: Exploring Information
- 파이썬으로 풀어보는 수학
- 해커의 언어, 치명적 파이썬
- 시스템 트레이딩을 위한 데이터 사이언스 (파이썬 활용편)
- 파이썬 괴식 레시피 - 긱(Geek)스럽게 파이썬 활용하기
- 파이썬 라이브러리 - WikiDocs
- 파이썬 책 추천 목록 정리
- 중급 파이썬: 파이썬 팁들
- 강좌: 파이썬 코딩 도장
- 더북(TheBook): 파이썬을 이용한 컴퓨터 과학 입문 1장만
- 더북(TheBook): 씽크 파이썬
- 더북(TheBook): Try! helloworld 파이썬
- 더북(TheBook): 모두의 알고리즘 with 파이썬
- 더북(TheBook): 모두의 엔트리 with 엔트리파이선
- 더북(TheBook): 컴퓨터 사이언스 부트캠프 with 파이썬
- 더북(TheBook): 모던 파이썬 입문 2부(7~12장)만
- 더북(TheBook): 모두의 파이썬: 20일 만에 배우는 프로그래밍 기초(개정판)
- 더북(TheBook): 파이썬 코딩의 기술 - 개정 2판 1~2장만
- xwMOOC: 프로그래밍과 문제해결 파이썬, 리보그, 러플
- 정보교육을 위한 파이썬 저자: Charles Severance 번역: 이광춘(xwMOOC)
- FIND THE BEST PYTHON BOOKS
- 11 Best Python Books To Read in 2020 - Nextotech
- The Architecture of Open Source Applications
- Legally Free Python Books List - Python kitchen
- 그림으로 배우는 파이썬 기초 문법 - WikiDocs
- 100 Page Python Intro
- Al Sweigart
- Cracking Codes with Python
- Automate the Boring Stuff with Python: Practical Programming for Total Beginners
- Invent Your Own Computer Games with Python, 3rd Edition
- Making Games with Python & Pygame
- Hacking Secret Ciphers with Python: A beginners guide to cryptography and computer programming with Python
- The Big Book of Small Python Projects
- Books by Agiliq
- Django Admin Cookbook, Django ORM Cookbook, Building APIs with Django and Django Rest Framework, Building Multi Tenant Applications with Django, Django Projects Cookbook, Django Design Patterns, Django Gotchas
- Journeyman Python, Essential Python Tools, Tweetable Python, Software consulting Howto, Visual Arts with Python
- Best Python Books To Read Out in 2021 - Nextotech
- A Byte of Python Introduction · HonKit
- Clean Architectures in Python
- Clean Architectures in Python
- clean-architecture: Example project showing off clean/hexagonal architecture concepts in Python
- cosmic_python - Simple patterns for building complex applications architecture
- CPython Internals: Paperback Now Available – Real Python
- Demystifying Python’s Internals - YouTube
- Dive Into Python 3
- Django
- Effective Pandas
- Efficient Python Tricks and Tools for Data Scientists — Effective Python for Data Scientists
- Full Stack Python
- Flask 점프 투 플라스크 - WikiDocs
- free-python-books: Python books free to read online or download
- Invent with Python Beyond the Basic Stuff with Python
- Learn Python, Break Python: A Beginner's Guide to Programming, by Breaking Stuff Books
- Learn Python the Right way
- 마야 파이썬 (Maya Python)
- 실용 파이썬 프로그래밍(Practical Python Programming 번역) - WikiDocs
- pytudes: Python programs, usually short, of considerable difficulty, to perfect particular skills
- Python 101
- Python 3.4 공부 좀 해볼까?
- Python으로 배우는 BBC micro:bit
- Python Data Science Handbook Essential Tools for Working with Data
- Python 데이터 분석 실무
- Python for Scientists and Engineers
- Python for Signal Processing Featuring IPython Notebooks
- The Quick Python Book • Naomi Ceder & Luciano Ramalho • GOTO 2022 - YouTube
- Reeborg's world
- RUR-PLE
- SICP in Python
- The-Python-Workshop: A New, Interactive Approach to Learning Python
- Think DSP
- Think Python: How to Think Like a Computer Scientist 2판
- Think Stats 2e python + statistics, free download
- wtfpython: What the f*ck Python? 😱
- Understanding Python bytecode by implementing tail call optimization
- Python bytecode is quite heavily trusted by CPython
- Understanding Python Bytecode
- Python behind the scenes #4: how Python bytecode is executed
- Blip, a bytecode compiler and interpreter for Python 3
- black - The uncompromising Python code formatter
- isort: A Python utility / library to sort imports
- YAPF - Yet Another Python Formatter
- David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015
- Thinking about Concurrency, Raymond Hettinger, Python core developer
- Brett Slatkin: Fan-in and Fan-out: The crucial components of concurrency - PyCon 2014
- David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015
- Thinking about Concurrency, Raymond Hettinger, Python core developer
- Python is NOT Single Threaded (and how to bypass the GIL) - YouTube 여러가지 예제
- A viable solution for Python concurrency LWN.net
- Concurrency and Parallelism: What is the difference? | by Kieron Spearing | Feb, 2022 | Towards Data Science
- OctopusCon: Python Edition
- When Python Practices Go Wrong - YouTube
- 키노트 파이썬 커뮤니티가 교육에 기여할 수 있는 것들 - 송석리 - PyCon Korea 2020 - YouTube
- Python News Brief (Q2 2021) - Honeybadger Developer Blog
- 10 Tools & Techniques Python Web Developers Should Explore - YouTube
- EuroPython Podcast Questions
- EuroPython 2018
- EuroPython 2019 Unleash the power of C++ in Python
- How Thinking in Python Made Me a Better Software Engineer
- Elizaveta Shashkova - The Hidden Power of the Python Runtime - YouTube test, debug, code coverage, type, concurrent
- Almar Klein - Let’s embrace WebAssembly! - YouTube webassembly, wasm
- Prashant Chaubey - Writing Good Python - YouTube PEP8, pylint, PEP257, pydocstyle, PEP484, mypy, bandit, black
- PyCon Korea - YouTube
- pyvideo.org
- 2016년 12월 파이썬 격월 세미나 & 송년회 후기!
- 2017년 10월 파이썬 세미나 - Python & Data
- 2017년 1월 3주차 파이썬 주간 소식
- 2017년 1월 4주차 파이썬 주간 소식
- 2017년 2월 1주차 파이썬 주간 소식
- 2017년 2월 2주차 파이썬 주간 소식
- 2017년 2월 3주차 파이썬 주간 소식
- 격월 세미나
- Allen Downey - Introduction to Digital Signal Processing - PyCon 2018
- Machine Learning: Python and the Power of Ensembles by Bargava Raman Subramanian
- PyCon US 2023 - YouTube
- PyCon US 2022 Highlights - ehmatthes.com
- PyCon US 2021 - YouTube
- us.pycon.org/2020
- PyCon 2019
- Pycon 2019 Korea youtube 링크 정리
- Raymond Hettinger - Modern solvers: Problems well-defined are problems solved - PyCon 2019
- PyCon Korea 2019 법률을 디버깅하다 Debugging law
- PyCon Korea 2019 파이썬의 변수
- 파이콘 2019 튜토리얼 준비
- 파이썬 3대장을 만나보자 decorator, async, meta programming
- 머신러닝 및 데이터 과학 연구자를 위한 python 기반 컨테이너 분산처리 플랫폼 설계 및 개발 python이 아니라 프로젝트 설계 및 구현 관점에서 재미있게 볼 수 있는 이야기
- from banksalad import python 뱅크샐러드의 사내 python이용에 관한 발표
- 파이콘 한국 2019 스포카 코드 챌린지 수상작 및 참여작을 소개합니다
- LINE 개발자 3인의 파이콘 한국 2019 방문기
- PyCon 2017
- pycon 2016
- pycon 2015
- PyCon 2015
- python names and values
- pycon 2015: are we still changing the world?
- pycon 2015 montreal
- raymond hettinger - beyond pep 8 -- best practices for beautiful intelligible code - pycon 2015
- pycon 2015 talks: our must see picks (1/6)
- david beazley - modules and packages: live and let die! - pycon 2015
- brett slatkin - how to be more effective with functions - pycon 2015
- pycon 2014
- PyCon AU 2016 참가 후기
- PyCon.KR 2022 - YouTube
- PyCon Korea 2021
- PyCon.KR 2020 - YouTube
- PyConKr 2018
- PyCon KR 2018 영상 다운 받기
- 인생을 짧아요, 엑셀대신 파이썬
- A Development of Log-based Game AI using Deep Learning
- pyconkr-2018-booklet
- PyCon Korea 2018 Day1 Lightning Talk - Python으로 LibreOffice의 한자 목록 공헌하기
- PyconKR 2018 Python으로 나만의 IOT 구축하기
- 학습하는 조직과 Python: 뱅크샐러드 사례를 중심으로
- PYCON Korea 2018 Python Application Server for Recommender System
- Animal iris recognition
- pycon korea 2018 드론 및 인공위성 영상을 이용한 태양광발전소 입지분석
- 생활탐사 - 파이썬으로 일상에 도움 되는 뉴스 만들기
- PyCon KR 2018 땀내를 줄이는 Data와 Feature 다루기
- 파이콘 2018 후기
- 2018. 05 파이썬 개발환경 구성하기 거의 끝판왕 Docker Compose - 김승호 compose뿐만 아니라 docker 명령 기본에 대한 것도 알기 좋음
- pycon.kr/2017/program/list
- 2017 파이썬 코리아, 발표주제를 정해보자
- 2017 파이콘 부스 운영기 - PyCon Seoul 2017 행사 Elastic 부스 운영기
- PyCon 2017 후기
- 파이콘 한국 2017 발표 후기
- PYCON2017 api tutorial 관련 자료
- 파알못의 파이콘 2017 참가 후기
- Charles Ochoa: The Joy of Integer Programming: Solving Hard Combinatorial Problems in Python
- 박준철: Python 게임서버 안녕하십니까 : RPC framework 편
- 2017-10 강대명 - 파이썬으로 풀어보는 아주 심플한 검색엔진의 원리
- 천원경매
- 조인석: 파이썬 vs 자바 초보 대상
- 이성용 : 개발자 없는 통계업무 부서에서 Django+Pandas+Selenium+python-docx으로 통계업무도구 만들기
- pycon.kr/2016apac
- pycon.kr/2016apac/program/schedule
- Python으로 한자검색 텔레그램 봇 개발 후기
- 디자이너의 코딩 도전기
- 지적 대화를 위한 깊고 넓은 딥러닝 Pycon APAC 2016
-
- 이미지(사람의 얼굴 사진)을 이해하고 스스로 만드는 모델
-
- github.com/carpedm20/DCGAN-tensorflow
- 2. Atari 게임을 화면의 픽셀만 보고 배우는 모델
- 3. 이미지 버전의 '왕 - 남자 + 여자 = 여왕'
- 4. 뉴럴 네트워크로 만든 튜링 머신
- 5. 강화 학습 모델들
- 6. 픽셀을 하나씩 예측하며 이미지를 만드는 모델
- 7. Question Answering, Language Model
- 8. Character-level Language Models
- 9. Teaching Machines to Read and Comprehend
- 10. Neural Variational Inference for Text Processing
- 11. Text-based Games using Deep Reinforcement Learning
- 12. Continuous Deep Q-Learning with Normalized Advantage Functions
- 정경업: Django로 쇼핑몰 만들자 - PyCon APAC 2016
- PyCon APAC 2016 - 너의 사진은 내가 지난 과거에 한일을 알고 있다
- 파이콘 2016 pycon 1일차 후기
- 삶의 의미는 성장에 있다
- 파이콘 삼총사 : Tox, Travis 그리고 Coveralls
- PyConAPAC 2016 부스 운영기
- PyCon APAC 2016 후기
- 스프린트와 튜토리얼
- CODING BATTLE 가위바위보! - 못다한 이야기
- PyCon APAC 2016 후기
- PyCon APAC 2016 발표자 & 자원봉사자 후기
- 김대현 : 파이썬을 활용한 똑똑한 주식투자 (시스템 트레이딩) - PyCon APAC 2016
- 김영욱: Python으로 IoT, 인지(Cognitive), 머신러닝 삼종세트 활용하기 - PyCon APAC 2016
- 김경훈: 뉴스를 재미있게 만드는 방법; 뉴스잼 - PyCon APAC 2016
- 양민지: Regular expression
[A-Z]+- PyCon APAC 2016 - 김정주 : 기계학습을 활용한 게임 어뷰징 검출 - PyCon APAC 2016
- 임성준: Python, VTK를 만나다! - Python, VTK를 활용한 3차원 볼륨 데이터의 시각화 및 활용 - PyCon APAC 2016
- 김영근 : 어느 흔한 파이썬 개발자의 집 소개 - PyCon APAC 2016
- 안명호 : Python + Spark, 머신러닝을 위한 완벽한 결혼 - PyCon APAC 2016
- 김태훈: 지적 대화를 위한 깊고 넓은 딥러닝 (Feat. TensorFlow) - PyCon APAC 2016
- 이홍주: Python 으로 19대 국회 뽀개기 - PyCon APAC 2016
- 홍민희: RPC 프레임워크 제작 삽질기 - PyCon APAC 2016
- 김동문: 검색 로그 시스템 with Python - PyCon APAC 2016
- 정민영 : 10만 라인, 26280시간의 이야기 - PyCon APAC 2016
- 김무훈: 파이썬을 활용한 교육용 프로그래밍 언어, 리보그 - PyCon APAC 2016
- Amit Kumar: Demystifying Python Method Resolution Order - PyCon APAC 2016
- pyconkr 2015
- 파이콘 한국 2015 (pycon korea 2015) 후기!!
- 2015 py con word2vec이 추천시스템을 만났을 때
- 한국어와 nltk, gensim의 만남
- the hitchhiker's guide to the python memory
- 알파희 - pypy/rpython으로 20배 빨라지는 아희 jit 인터프리터
- celery의 빛과 그림자
- 약속
- profiling - 실시간 대화식 프로파일러
- 파이콘 코리아 2015 코드 골프 되돌아보기
- pycon korea 2015
- 후기
- 김도형: 파이썬 기반의 대규모 알고리즘 트레이딩 시스템 소개 - PyCon Korea 2015
- 김현호: 오늘 당장 딥러닝 실험하기 - PyCon Korea 2015
- 유재명: R vs. Python: 누가, 언제, 왜 - PyCon Korea 2015
- 김재석: 도도와 파이썬: 좋은 선택과 나쁜 선택 - PyCon Korea 2015
- 임덕규: 업무에서 빠르게 만들어 사용하는 PyQt 프로그래밍 - PyCon Korea 2015
- pyconkr 2014
- PyOhio 2019 Surviving Without Python python 전반
- A Machine Learning Data Pipeline - PyData SG
- Marco Bonzanini - Building Data Pipelines in Python
- PyData Paris 2016 - Automatic Machine Learning using Python & scikit-learn
- PyData London 2018
- PyData London 2019
- PyData Seattle 2017 Keynote Jake VanderPlas 여러가지 data 관련 library 역사(?)
- Optimizing numerical calculations in Python - Jakub Urban - PyData Prague, January 2019
- PyData Ann Arbor: Katie Bauer | Building "Time On Site" at Reddit
- Itamar Turner-Trauring - Speed up Python data processing with vectorization | PyData Global 2022 - YouTube
- 파이썬 코딩 강의를 제작하였습니다 (6시간 / 기본편) : 클리앙
- 모두를 위한 파이썬 (PY4E) 강좌소개 : 부스트코스
- MOOC: Python (파이썬 강좌)
- K-MOOC: Python
- K-MOOC Operation Research : Numpy Part #1
- Quantitative Economics with Python
- Sungchul Lee 연대 수학과 교수
- Microsoft: We want you to learn Python programming language for free
- Python for Beginners
- More “Python for Beginners” videos…times two!
- Learn Python On AWS Workshop :: Learn Python on AWS
- Python API Development - Comprehensive Course for Beginners - YouTube
- Elliptic Curve Cryptography: finite fields and discrete logarithms
- Basic Intro to Elliptic Curve Cryptography - Qvault
- How to Build a Simple Crypto Trading Simulator
- How to encrypting and decrypting the messages in python| | Cryptography | |
- bcrypt Hashing passwords with Python and Bcrypt
- Ciphey/Ciphey: Automated decryption tool
- logcoin - A toy crypto-currency based on a discrete logarithm zero-knowledge protocol, in <95 lines
- PyCryptodome
- 파이썬에서 디버깅하기
- Python debugging tools
- HOW TO DEBUG (DEADLOCKED) MULTI THREADED PROGRAMS (PYTHON RECIPE)
- Python Debugging Tips 20160814-1800 PyCon Asia Pacific
- Segmentation Fault 발생 시 gdb로 stack trace 해 보기
- 파이썬 코드에서 중간에 콘솔 띄우는 디버깅
import code; a = 3; code.interact(local=locals()) - LA오빠 즐거운 Data Science - 코딩효율 2x 늘리기 팁 1탄 PDB, VS Code, Jupyter
- Pit Stop for Software Maintenance | Pega Devlog
- Elizaveta Shashkova - Debugging in Python 3.6: Better, Faster, Stronger
- PyConKr 2018 GDB와 strace로 Hang 걸린 Python Process 원격 디버깅
- Ultimate Guide to Python Debugging
- How to Debug in Python Without an IDE | by Aviral Bhardwaj | Dec, 2021 | Towards Dev
- bugbuzz - Fall in love with debugging
- NoPdb: Non-interactive Python Debugger — NoPdb documentation
- PDB
- Aligning PDB structures with Biopython
- Python 디버깅 (PDB)
- pdb 튜토리얼
- Start Python Debugging With pdb
- Debugging in Python
- Python 3.7’s new builtin breakpoint — a quick tour
- Debugging in Python — A cakewalk with pdb
- Are you writing print() statements to debug your Python code? | by Pradeepa Gollapalli | Analytics Vidhya | Medium
- BayPiggies September 2022: Debugging with ipdb - YouTube
- PyCharm
- PySnooper - Never use print for debugging again
- python-devtools
- traceback_with_variables: Adds variables to python traceback. Simple, lightweight, controllable. Debug reasons of exceptions by logging or pretty printing colorful variable contexts for each frame in a stacktrace, showing every value. Dump locals environments after errors to console, files, and loggers. Works in Jupyter and IPython. Install with pip or conda
- Docker로 파이썬 배포 운영하기
- 파이썬 Docker 이미지 관리하기
- docker vs vagrant vs virtualenv
- Using Alpine can make Python Docker builds 50× slower
- mumps on ubuntu 18.04
- Anastasiia Tymoshchuk - Can we deploy yet? - YouTube
- Dmitry Figol - Optimizing Docker builds for Python applications - YouTube
- You’re living in 1985 if you don’t use Docker for your Data Science Projects | by Sohaib Ahmad | Towards Data Science
- Spoqa 기술 블로그 | Flask, marshmallow, apispec으로 API 문서화 자동화하기
- continuous-docs - Tutorial and example package for continuous documentation generation in Python
- portray - a Python3 command line tool and library that helps you create great documentation websites for your Python projects with as little effort as possible
- drf-yasg drf-yasg에 예제값 달기
- pydoc
- sphinx
- Django 문서
- www.askcompany.kr/r
- (번역) Django 공식문서 - Introduction to models
- Django resources
- Learn Django: Payment Processing
- Digging Into Django
- Pirates use Flask, the Navy uses Django
- TaskBuster Django Tutorial
- Django Tutorial - Create a Digital Resume with a Python Backend - YouTube
- 날로 먹는 Django 웹프레임워크 강좌
- 시나브로 Django 발표
- Category: start-with-django-webframework
- Django를 배우다, Django로 배우다
- Using Gabbi and Hypothesis to Test Django APIs
- The Django Test Driven Development Cookbook - Singapore Djangonauts
- 테스트 초보의 테스트 삽질기 with django
- 테스트 초보의 테스트 삽질기 with Django
- 한종원: Django API Server Unit Test and Remote Debugging
- Model Mommy: Smart fixtures for better tests
- Using Mocks to Test External Dependencies or Reduce Duplication
- Deploying a Django App with No Downtime
- Django, 저는 이렇게 씁니다
- Python Web Development: Understanding Django for Beginners
- 장고 걸스 튜토리얼 (Django Girls Tutorial)
- Django For Everybody - Full Python University Course - YouTube
- 작정하고 장고! Django로 Pinterest 따라하기 - YouTube
- Finally, Real-Time Django Is Here: Get Started with Django Channels
- pycon kr 2018.12 Django Channels 삽질기 - 방신우
- Add2paper printing system using Django-channels
- (엑셀만큼 쉬운) Django Annotation/Aggregation
- Djangogo!!! Building a Blog Application 총정리
- 8퍼센트 성능 개선
- Django Performance Improvements - Part 1: Database Optimizations | Product Blog • Sentry
- Django Performance Improvements - Part 2: Code Optimization | Product Blog • Sentry
- Django Performance Improvements - Part 3: Frontend Optimizations | Product Blog • Sentry
- Django Performance Improvements - Part 4: Caching in Django Applications | Product Blog • Sentry
- AskDjango 국회 사이트, 국회의원 목록 크롤링
- Django - 라이브 코딩쇼 #1 - 천천히 40분 만에 심플 사진 블로그 만들기
- AskDjango 여러분의 서비스 개발. 그 시작을 도와드리겠습니다
- Django Web Development with Python
- Dango에서 간단한 REST API 만들기
- Create a Django API in Under 20 Minutes
- Web Service Efficiency at Instagram with Python
- lazy_django
- Why Django Sucks - PyCon SE 2015
- Andrew Godwin - Reinventing Django for the Real-Time Web - PyCon 2016
- schoolofweb.net/blog/posts/tag/django
- State of the Real-time Web with Django
- Realtime Example app Tutorial - Using Django, django-realtime, iShout.js,Node.js & Redis
- 파이썬과 Node.js를 같이 쓰다가 망했던 경험
- Gnuboard to Django Series #01
- 클린 코드를 위한 테스트 주도 개발 - QUnit 버전 문제
- Django ORM 왜 어렵게 느껴질까?
- PyCon KR 2018 Effective Tips for Django ORM in Practice
- DjangoORM에서 SQL Driver 지정해 Query & Pandas DataFrame 얻어내기
- 장고 ORM 요리책
- 장고 ORM 요리책
- Django ORM cookbook 번역 후기 read the docs, sphinx
- Django ORM Relationships Cheat Sheet
- ORM으로 Aggregation 함수와 Group by 사용
- 반드시 알아야 할 5가지ORM 쿼리
- Django ORM (QuerySet)구조와 원리 그리고 최적화전략 - 김성렬 - PyCon Korea 2020 - YouTube
- Django ORM에 FastAPI를 얹어보자
- 장고 모델 행동(Django Model Behaviors) By Kevin Stone
- 김도현 : Django vs Flask, 까봅시다! - PyCon APAC 2016
- 박현우: Django in Production - PyCon Korea 2015
- 장고 페어코딩 후
- 도서 — 파이썬 웹프로그래밍 실전편 (요약)
- Django migration 궁금증
- How to migrate Django from SQLite to PostgreSQL
- Django에 postgresql 연동하기 - ㅁㄱㅈㄱ
- Disqus 장고 3.x 사용 중 migrate 에러 해결 방법
- ElasticSearch with Django the easy way
- 장고(Django)와 함께하는 Celery 첫걸음
- 아직도 보고서를 직접 보내시나요? django-celery-beat를 활용한 자동화 | by Paikend | Bigpearl | Medium
- Django에 Custom인증 붙이기
- Django에 Social Login 붙이기: Django세팅부터 Facebook/Google 개발 설정까지
- Django + SocialLogin + Email as User
- 배포한 Django 서비스 Exception Sentry로 받아보기
- AWS Elastic Beanstalk + CI 를 이용한 Django 배포 자동화
- CS50: Web Programming with Python
- Building Ribbit in Django
- Django로 웹 서비스 개발하기 (1. 환경구축 — Virtualenv, atom, django)
- Django로 웹 서비스 개발하기 (2. Class, Object)
- Django로 웹 서비스 개발하기 (3. Object 실습)
- Django로 웹 서비스 개발하기 (4. MTV, 프로젝트 생성)
- Django로 웹 서비스 개발하기 (5. View — urls.py와 views 수정)
- Django로 웹 서비스 개발하기 (6. Model — 생성, admin 등록)
- Django로 웹 서비스 개발하기 (7. test code, template, css)
- 장고, 빠르고 탄탄하게 웹사이트 개발하기
- Django initial data | fixture 또는 RunPython 이용하기
- Django에서 fixture사용하기
- Djangoでfixtureを使う
- modern-django - Modern Django: A Guide on How to Deploy Django-based Web Applications in 2017
- 테스트 코드의 여러가지 유형
- Django 나만의 Command 만들어보기
- Learn Django
- Mistakes I Made Writing a Django App (and How I Fixed Them)
- Handling webhooks using Django and ngrok
- Django 1.11 릴리스와 주요 변경 사항
- masnun.com/category/django
- Dockerizing a Python Django Web Application
- docker-with-django.md
- Django on Docker / Blog / codingforentrepreneurs.com
- Django & Github Actions / Blog / codingforentrepreneurs.com
- 굥대생의 "HelloWorld!"
- django-tdd-restful-api
- Analyzing Django requirement files on GitHub
- 5 ways to make Django Admin safer
- Optimizing Django Admin Paginator
- Django 템플릿에서 VariableDoesNotExist 예외 오류 대응하기
- select_related, prefetch_related 그리고 debug toolbar
- DjangoTDDStudy
- Pycon2017 이성용 Dances with the Last Samurai
- Django form 폼나게 쓰기
- coding-night-live - a Web-Based Communication Application for codelabs
- 장고 외부에서 Form, Serializer 활용하기 - request validation 용도로 사용 가능
- 번역 | 장고에서 리퀘스트를 처리하는 방법
- Django - 서드 파티 패키지
- (번역) 다운타임 없는 장고 마이그레이션
- (번역) How to Create Django Data Migrations
- (번역) Django Tips #8 Blank or Null?
- simple is better than complex
- SQLのSELECT文を、DjangoのQuerySet APIで書いてみた
- 장고 쿼리셋 합치기
- Django QuerySet 기능 간단하게 살펴보기
- Jupyter Notebook에서 Django 프로젝트 세팅해서 모델 돌려보기
- Azure Functions을 통한 파이썬 크롤링 자동화 (장고걸스 서울, 2017년 11월)
- Hassan Abid: Django for mobile applications
- The length of Django username
- Django 2.0 릴리스와 주요 변경 사항
- update_fields - 어떤 필드를 저장할지 지정하기
- Django에서 비밀 값(secrets) 관리하기
- 정적 파일을 기본값으로 갖는 ImageField구현
- Dynamically import django settings for multiple environment such as local, dev, beta, production
- 9 Django Tips for Working with Databases
- Configure a Read Replica Database in Django | Towards Data Science
- django에 MSSQL 연결하기
- code.djangoproject.com/wiki/DjangoAndPyPy
- Faster Django Sites with PyPy
- Django view 안에서 쿼리 개수 확인하기
- Django 배포연습
- Truncated or oversized response headers received from daemon process 에러 해결법
- labs-face-hol - Azure Face API를 활용
- Building and deploying an Enterprise Django Web App in 16 hours
- What I Wish I Knew When I Started Django Development 2018
- Django로 순식간에 블로그 만들기 - @chiyodad - 이모콘 EMOCON 2016 F/W
- Python으로 카카오톡 플러스친구 만들기
- Summernote - a simple WYSIWYG editor
- Taking Django Async
- Intro to Django's Annotate
- 2018년 8월 5일, 서울창조허브 10F에서 열리는 개발기술연합세미나, 파이썬 세션, 장고 샘플 프로젝트
- Django 2.1 Tutorial-Build a Travel Blog with Goorm IDE and Bootstrap 4(Unspoken version)
- Django Bootstrap 적용하기
- django 쿼리셋 수정을 통한 웹서비스 성능 개선 - select_related, prefetch_related
- (번역) Best practices working with Django models in Python
- 같은 Django model class에서 다른 schema가?(feat. Django는 이중인격?)
- pycon kr 2018.12 django model 삽질기 - 김정환
- snaker - django url shortener
- 장고의 배신(주니어 개발자의 삽질기)
- Django, Clean Architecture 연구하기
- Clean Architecture in Django
Ubuntu 환경에서 Django 배포하기- 우분투에서 장고(Django) 배포 경험담
- Django를 쓰는 이유, 쓰지 않는 이유
- django를 관리툴로 쓰자 - 서버를 둘로 나누자
- 레거시 시스템에 django로 다가가기
- How to build an e-commerce shop with Python, Django, & Wagtail
- A little hacker news in Django
- Merging Django ORM with SQLAlchemy for Easier Data Analysis
- Python Django Web Framework - Full Course for Beginners
- Python Django Course for Beginners 2021 - Learn Django from Scratch in this 100% Free & Tutorial! - YouTube
- 5 Best Django Online Courses for Beginners - DZone Web Dev
- The Basics of Django Models
- Using Django in a Standalone Script
- My Favorite Django Packages in 2019
- Django Web Development with Python Introduction
- Django 2.2 LTS 릴리스와 주요 변경 사항
- Serving React and Django together
- 장고(django) 설치하기
- 장고(django) 프로젝트 시작하기
- 장고(django) 모델(models) 사용해보기
- 장고(django)의 관리자 페이지
- 장고(django)의 라우팅(Routing)
- 장고(django)의 ORM
- 장고(django)의 뷰(View)
- 장고(django)의 폼(Form)
- 장고(django) 프로젝트를 헤로쿠(Heroku)에 업로드하기
- 장고(django) 프로젝트에 마스터 데이터 넣기
- 장고(django)의 모델(Models)을 JSON으로 응답(Response)하기
- 장고(django)에 JWT 사용하기
- 장고(django)의 커스텀 유저 모델(Custom User Model)
- 장고 프로젝트 Django Simple Web Project - 1 (장고 설치하기)
- python개발자 uwsgi를 버리고 gunicorn으로 갈아타다
- 운영중인 장고 + 지유니콘 백엔드 메모리 누수 문제 해결 production django + gunicorn backend memory leak fix (feat uwsgi)
- Deploying Django with Docker Compose, Gunicorn and Nginx - YouTube
- Python and django Python and django full stack Web Developer bootcamp
- How to Serve Protected Content With Django (Without Bogging Down Your Application Server) logout 후 content에 접근을 막는 방법
- Django: Truncated or oversized response headers received from daemon process 에러 해결법
- Django 구성 분석하기와 기본 세팅
- How to Install and Use Django on Windows for Beginners (2019)
- 20190818 PyCon Korea 2019 Django DB Router로 Database Read Replicas 100% 활용기 및 Troubleshooting 경험 공유
- How to Build an E-commerce Website with Django and Python
- Django - tweetme 소셜서비스 구현해보기 (1) - Django Setup
- Django Builder
- Django get_or_create() 함수에서 발생한 MySQL Deadlock 이슈 해결하기 - 구영민의 개발 블로그
- Django get_or_create 함수 쓸 때는 unique 같이 쓰자 - 구영민의 개발 블로그
- Django Mysql - Python DB 연동 방법
- 장고에서 C mysql 이 임포트 되지 않는 문제 해결하기 · 개발블로그
- MySQL과 장고(django) 연결하기 - 로스카츠의 AI 머신러닝
- Django 2 by Example, published by Packt
- Django Mini Project 부트스트랩 랜딩페이지 구름IDE
- Django, 공공데이터포털, Google Map으로 전기차 충전소 위치찍기
- Django 3.0 릴리스와 주요 변경 사항 - MariaDB 지원, ASGI 지원, 필터 표현식 등
- django-annoying - A django application that tries to eliminate annoying things in the Django framework
- Full Stack React & Django
- Survey WEB Application Tutorial 1
- 장고 라이트닝 토크 - YouTube
- django transaction 궁금증
- Django Transaction(트랜잭션) 1편 - Request와 DB Transaction 묶기(Feat. ATOMIC_REQUESTS)
- Django DB Transaction 2편 - 명시적으로 transaction 활용하기. (feat. savepoint)
- Django DB Transaction 3편 - DB Transaction Test 코드 작성하기
- Transaction 사용하기: #1 Django와 Mysql의 transaction
- Transaction 사용하기: #2 Django에서 transaction 적용하기
- Transaction 사용하기: #3 Django에서 transaction 과 동시성 처리
- Daniel Feldroy - YouTube
- Django 3.1 릴리스와 주요 변경 사항 | 44BITS
- Django 3.2 릴리스와 주요 변경 사항 | 44BITS
- How To Scale and Secure a Django Application with Docker, Nginx, and Let's Encrypt | DigitalOcean
- 장고 라이브 코딩쇼 (50분, 유튜브 St.) - YouTube
- Managing Sessions in Django. Understanding your Django session with… | by Goutom Roy | Better Programming | Medium
- Using the JSONField in Django - YouTube
- django로 크롤링해서 적용하기 +BeautifulSoup사용 — ChoSM'Programming
- Django(2.x)와 Asyncio를 함께 사용해보자 No Celery! - JIHUN KIM - Medium
- 참조
- (동영상) T24 장고(Django) 01강 웹프로그래밍과 Django
- 카카오톡 같은 채팅 시스템 데이터베이스 설계, 구현, 테스트 코드 만들어보기 - 구영민의 개발 블로그
- How to Write Complicated Queries in Django With F Expressions - YouTube
- How to Perform Full Text Searches in Django With Postgres - YouTube
- Django를 Django답게, Django로 뉴스 사이트 만들기
- Django, HTMX and Alpine.js: Modern websites, JavaScript optional
- Episode 2 — Creating a PDF generating Django Application | by Francisco Betancourt | Oct, 2021 | Medium
- Python Django Web Framework - YouTube
- Django 4.0 릴리스와 주요 변경 사항 | 44BITS
- Django 4.1 릴리스와 주요 변경 사항 | 44BITS
- Django 4.0.4 Best Practices Tutorial : Part 1
- Django를 Django답게, Django로 뉴스 사이트 만들기. 정경업 - PyCon Korea 2021 - YouTube
- 6 Harmful Defaults in Django | Confuzeus
- Improving Your Django and Python Developer Experience | Real Python Podcast #97 - YouTube
- Is the Django Framework Dead?. Find out whether Django is the right… | by Developer Codie | Feb, 2022 | Python in Plain English
- Django에서 toss 결제 연동하기
- django app config ready 한 번만 실행되게 하려면 어떻게 할까요?
- Django Channels, Celery, Redis: Real Time Broadcasting API response App (Jokes) | Django WebSockets - YouTube
- django mptt와 업뎃이 별로 없는 계층형 구조에 대해 알아봅시다
- Build And Deploy A REST API With Django REST Framework | Full Project
- How to Easily Style Your Django Form Fields With Django Widget Tweaks - YouTube
- 저는 Django 에서 단일 앱을 통한 개발을 제안합니다. :: 코드보단 말
- Django 데이터베이스 캐시의 데드락 이슈 해결. 소개 | by Siheon Kim | Mar, 2023 | HBsmith
- Step-by-Step Tutorial: How to Customize the Admin Site in Django
- django-allauth 소셜로그인 후의 redirect에 대해
- Django Background Tasks
- Django Doctor - Django code improvement bot
- django-dynamodb-cache: Fast, safe, cost-effective DynamoDB cache backend for Django
- django-gunicorn-nginx-docker: django gunicorn docker example
- django-hijack: With Django Hijack, admins can log in and work on behalf of other users without having to know their credentials
- Django-Kubernetes: Learn how to deploy a docker-based Django application into a Kubernetes cluster into production on DigitalOcean
- django manager 화해 블로그
- Django Pydenticon documentation
- django-query-capture: Shows queries, find slow queries, detects N+1 in Django
- Django REST framework - a powerful and flexible toolkit for building Web APIs
- How to use Serializers in the Django Python web framework | Opensource.com
- Building an API with Django REST Framework and Class-Based Views
- Building With Django REST Framework in Python - YouTube
- Python/Django 웹서비스 5년간의 개발 운영 경험기. 안정호 - PyCon Korea 2021 - YouTube
- Django Rest Framework 레시피 | 44BITS Justyna 번역 글. DRF라고도 많이 부르는 Django Rest Framework에서 사용하는 패턴별로 맥락과 해결책, 이유를 설명 & 정리
- drf-yasg
- django_session 테이블에 저장되어 있는 세션은 어떤 값들을 가지고 있을까요?
- kolo: See everything happening in your running Django app. All without leaving VSCode
- Paperless — Paperless-ng 1.5.0 documentation
- pytest-django
- python-social-auth/social-app-django: Python Social Auth - Application - Django
- Wagtail Django Content Management System | Wagtail CMS
- Extending Python Into the Future
- Cheuk Ho - How to be Pythonic? Design a Query Language in Python - YouTube
- Lark - a modern parsing library
- gmail 로 이메일 보내기
- Sending an Email in Python via Gmail
- Gmail API How To Send Email with Attachments Using GMAIL API For Beginners 2018
- Python - Sending Email With Gmail SMTP Server
- Send Email in Python using SMTP Server using Outlook and Gmail
- How to send email/gmail using python script step by step
- How To Send an Email in Python With Attachments Easy for Beginners
- Python Basics: Sending E-mails
- How to send an email with Python
- How to Read Emails using IMAP Download Attachments Python 3 for Beginners 2018
- Using Markdown to Create Responsive HTML Emails
- 파이썬을 이용하여 이메일(email) 전송 - 파일첨부, HTML 양식 사용
- 파이썬 Python 코딩 - 엑셀 내용 이메일 발송하기 - YouTube
- 파이썬 Python 코딩 - 엑셀 내용 이메일 발송하기 2 (파일첨부) - YouTube
- How to send email with Python | From your Gmail account - YouTube
- 이메일 보내기
- elven.io - Email us to get any Python programming task completed
- eml-attachment-extractor: Python script for extracting attachments from .eml files
- Envelopes - Mailing for human beings email
- exchangelib - Python client for Microsoft Exchange Web Services (EWS)
- extract_attachments.py A simple (and probably naive) script to extract attachments from .eml files for those of us who don't use software email clients
- smtplib
- How To Use Excel VBA In Python
- Python Basic - 파이썬 엑셀(Excel, CSV) 읽기 및 쓰기 (1)
- Python Basic - 파이썬 엑셀(Excel, CSV) 읽기 및 쓰기 (2)
- Excel vs Python: How to Do Common Data Analysis Tasks
- Learn How to (easily!!) do 3 Advanced Excel Tasks in Python
- Automate These 3 (Boring!!) Excel Tasks with Python!
- How to integrate Excel with Python | Towards Data Science
- Case Study: Automating Excel File Creation and Distribution with Pandas and Outlook - Practical Business Python
- python으로 excel 데이터 탭 별로 mysql DB로 이관 하기 (data migration)
- 예제 1 교육신청서 취합하기
- 예제 2 전종목 주가 데이터 다운로드
- 예제 3 연봉 계약서 자동 생성하기
- DOTXCEL - Paint Your Image To Excel!
- **Grid studio - a web-based spreadsheet application with full integration of the Python programming language. https://gridstudio.io **
- img2xls - Convert images to colored cells in an Excel table
- LibXL excel library for developers
- openpyxl How to create, read, update and search through Excel files using Python
- pandas
- practice - test_pandas.py key가 자동으로 정해지므로 필요하면 customize해야 함
- Combine Multiple Excel Worksheets Into a Single Pandas Dataframe
- Pycel - a small python library that can translate an Excel spreadsheet into executable python code
- PyXLL - The Python Excel Add-In
- xlrd practice - test_xlrd.py
- xls2sql - excel to sql script
- xlsx pandas Excel File Data Analysis(엑셀 파일 Pandas 분석)
- XlsxWriter - Creating Excel files with Python and XlsxWriter
-
practice; encoding 문제로 저장한 csv를 excel에서 열었더니 글자가 깨져 보일 때
$ pip install xlwt xlsxwriter import pandas as pd df = pd.read_csv('some_file.csv', encoding='utf-8') writer = pd.ExcelWriter('some_file-r.xlsx', engine='xlsxwriter',options={'encoding':'utf-8'}) df.to_excel(writer, sheet_name='Sheet1') writer.save() -
Using Document Properties to Track Your Excel Reports - Practical Business Python
-
- practice
- logging
- pytest
- practice - Refactoring the structure of project, and add test using pytest
- wkdtjsgur100.github.io/tags/#pytest
- pytest <.py file>과 python -m pytest <.py file>의 실행 결과가 다름. 이유는 아직 모르겠음
- Flask에서 Pytest Fixture로 테스트환경 구축하기
- T.D.D로 Flask API 맛보기)
- 다시쓰는 Flask unittest (상편)
- 다시쓰는 Flask unittest (하편)
- Automation Testing with Pytest. We live in an era where software is… | by Harshil Modi | Tenable TechBlog | Medium
- Start Python #6 Backend Program 만들기 – Test하기 - Kowana's coding
- 기획자가 한 번 추천한 음식은 당분간 추천하지 말라고 했다. 김다현 - PyCon Korea 2021 - YouTube
- Introduction to PyTest - TestingLPoint
- Intro to Automated Browser Testing Flask Apps With Playwright and Pytest - YouTube
- How to test Flask applications | Analytics Vidhya
- Getting Started With Testing in Flask - YouTube
- Flask resources
- Flask의 세계에 오신것을 환영합니다
- Flask 웹어플리케이션 구축하기
- 파이썬 플라스크 로 배우는 웹프로그래밍
- Setuptools 을 이용한 디플로이
- Flask Book
- Flask 애플리케이션 개발 환경 구성
- Flask 공식 튜토리얼 따라하기
- The Flask Mega-Tutorial
- Part I: Hello, World!
- Part II: Templates
- Part III: Web Forms
- Part IV: Database
- Part V: User Logins
- Part VI: Profile Page and Avatars
- Part VII: Error Handling
- Part VIII: Followers
- Part IX: Pagination
- Part X: Email Support
- Part XI: Facelift
- Part XII: Dates and Times
- Part XIII: I18n and L10n
- Part XIV: Ajax
- Part XV: A Better Application Structure
- Part XVI: Full-Text Search
- Part XVII: Deployment on Linux
- Part XVIII: Deployment on Heroku
- Part XIX: Deployment on Docker Containers
- Flask Tutorials
- Secure Flask REST API Server Template
- How to build a simple Flask RESTful API with Docker-Compose | by Daniel Carlier | Medium
- Docker image with uWSGI and Nginx for Flask applications in Python running in a single container
- Flask앱을 uWSGI와 Nginx를 사용하여 배포하기
- How To Serve Flask Applications with Gunicorn and Nginx on Ubuntu 16.04
- How To Serve Flask Applications with uWSGI and Nginx on Ubuntu 18.04
- 구글 애널리틱스 API를 사용한 Flask 앱을 uWSGI와 nginx로 배포한 과정
- Flask AWS에 프로덕션용으로 Deploy하기(nginx+uwsgi)
- Flask - uwsgi - Nginx 와 docker-compose를 사용해 서버를 만들자
- Flask 에 uwsgi 서버 적용하기
- Infra flask, nginx, uwsgi 연동하기 - 로스카츠의 AI 머신러닝
- Dockerize Simple Flask App
- Dockerize Flask API application with Dockerfile and Docker Compose - YouTube
- Containerizing Python Web Application | by Srinaveen Desu | The Startup | Sep, 2020 | Medium dockerfile
- How to make a Flask blog in one hour or less
- Flask is a microframework for Python based on Werkzeug, Jinja 2 and good intentions. And before you ask: It’s BSD licensed!
- Pirates use Flask, the Navy uses Django
- Django vs Flask - A practitioner’s perspective
- What is Flask-Admin
- A recipe for App Engine – Target – How does it work
- How To Structure Large Flask Applications
- Weird thing to understand from mongoengine in Flask
- Implementing a RESTful Web API with Python & Flask
- Python, Flask, WSGI, Apache 설정 삽질 ㅠ on CentOS 6
- Flask에서 예외(Exception)를 이용하여 HTTP 에러 응답에 사용자 정의 메세지 추가하기
- Flask 웹 앱과 Flask-OAuthlib를 이용하여 구현한 OAuth 2.0 서버 연동 및 토큰 갱신 방법
- 카카오톡 자동응답 API + FLASK 를 활용해서 카톡봇만들기
- Simple Flask Blog That I made
- Testing file upload handling in Flask
- HTTP Methods in Flask
- Flask-Login 예제
- Login authentication with Flask
- Using Google Login in Python With Flask - YouTube
- (flask) JSON 데이터 받기 및 예외처리
- flask - jinja2 tojson 필터
- flask - json_encoder 지정하기
- render_template 어떻게 사용할까?
- flask - request.script_root 이용하기
- flask-mqtt : subscribe 시 qos 설정 이슈 수정하기
- FLASK TDD with TESTING GOAT
- On-demand image server with Python
- Flask,VueJS,RethinkDB 로 파일 저장 서비스 만들기 - (1)
- Flask Python Web Framework Installation and Routing Rule | Deep Learning
- 한글이 보이는 Flask CSV Response 만들기
- Flask Response Encoding 문제 make_response 사용
- Flask 블루프린트(blueprint) 사용하기
- Using the url_for Function in Flask Blueprints
- Intro to Flask Blueprints
- Intermediate Flask - Structuring Larger Flask Applications w/Blueprints
- Asynchronous Task in Flask Using Celery
- Flask, Celery & SQLAlchemy Example
- Using Celery in Flask to Email Dynamic PDFs
- Optimizing task queues with Celery and Flask - LogRocket Blog
- Build MVP With Python Flask and ReactJS
- How I Reverse Engineered A Chrome Extension To Write My Own Flask App
- Flask 1.0 Changelog 우리말 번역
- Flask 1.0에서 달라진 점
- FLASK vs DJANGO
- Python Backends: Flask Versus Django
- 기술블로그 구독서비스 개발 후기
- Python Flask에서 페이지 Redirect 이동하는 방법
- Flask: redirect vs redirect(url_for)
- Creating a Weather App in Flask Using Python Requests
- Stub API Maker Served by Flask - It makes stub API based on under static folder structure and a setting file
- pycon kr 2018.12 파이썬 웹 배포 삽질!! 이제 그만 - 이새로찬
- 파이썬 웹 배포 삽질!! 이제 그만 gunicorn, nginx
- Deploying Flask with Gunicorn 3. Application deployments often come with… | by Emmett Boudreau | Towards Data Science
- Flask-Large-Application-Example
- Flask Routing & Sessions: A Subtle Symphony - With great flexibility comes great responsibility
- Flask for Beginners Tutorial - Learn Flask in 40 Minutes (2019)
- Flask TodoMVC Tutorial
- Beginner Flask Project: Create a Todo App With Flask and MongoDB - YouTube
- Creating a Todo App With Flask and MongoDB - YouTube
- Model-View-Controller (MVC) Explained – With Legos
- Generating HTML Pages from MongoDB with MongoEngine and Jinja2 (Flask Part 1)
- Building a Flask Web Application (Flask Part 2)
- Flask Movie API Example
- How to build a cryptobot in Python and connect it to Facebook messenger
- Building a URL Shortener in Flask
- Get Form Checkbox Data in Flask With .getlist
- Organizing a Flask Project Beyond Single File
- CORS in Flask
- 3 Quick Tips to Make Your Flask Apps Better
- Codelog Record all of url that you want to remind http://codelog.kr pocket하고 비슷해보임
- Full-stack single page application with Vue.js and Flask
- Developing a Single Page App with Flask and Vue.js
- Docker를 사용한 Vue - Flask 개발서버 작성 (front-back 연동)
- Advanced Flask Patterns
- Running Your Flask Application Over HTTPS
- Flask - DB (Mysql) 연동과 CRUD :: 개발자 울이 노트
- How To Use One-to-Many Database Relationships with Flask and SQLite | DigitalOcean
- Creating Middlewares with Python Flask | by Devesh Kharve | The Startup | Medium
- sqlcolab colab + Flask REST API daemon, MySQL 테이블 생성 쿼리, 샘플 csv 파일
- Python Flask REST API MySQL stored procedure colab
- Coding a REST API With Python | by Eric Chi | The Startup | Aug, 2020 | Medium
- Develop and sell a Python API — from start to end tutorial | by Daniel Deutsch | Sep, 2020 | Towards Data Science AWS
- How to deploy Flask on IIS with Windows Authentication | by Rudy W | Medium
- 12 requests per second in Python uvloop
- Flask Course - Python Web Application Development - YouTube
- Some New Features in Flask 2.0 - YouTube
- Using Async Functions Inside of Flask Routes - YouTube
- Asynchronous Tasks in Flask with Redis for Beginners | by Esther Vaati | Apr, 2022 | Medium
- Flask 한글 POST 요청 받기 - 로스카츠의 AI 머신러닝
- How to Enable User Invites in Flask-User - YouTube
- Uploading and Returning Files With a Database in Flask - YouTube
- Learn Data Structures by Building a Flask API with Python
- Flask 데코레이터 사용하기 | woolog - 개발자 울이
- Flask 스마트하게 구조 만들기 | woolog - 개발자 울이
- Docker로 작성한 서버, Debug모드 적용하기 | woolog - 개발자 울이
- Building a Full Stack Flask HTMx Application - Code Capsules
- Flask Web Framework - 생활코딩
- Python Flask Web Framework - YouTube
- darkmode-session: walk through darkmode with redis session clustering
- Athena: Athena is a web application developed in Python-Flask-SQLite for testing your skills as a Hacker, Coder and Warrior
- Bread pan 기본적인 웹서비스를 간단하게 만드는 프로젝트 틀 구조 참고
- Flask-aiohttp — Asynchronous Flask application with aiohttp
- Flask-AppBuilder - Simple and rapid application development framework, built on top of Flask. Includes detailed security, auto CRUD generation for your models, google charts and much more
- Flask-APScheduler is a Flask extension which adds support for the APScheduler
- Flask-Assets 사용 방법 (1)
- Flask-Assets 사용 방법 (2)
- Flask-babel을 통한 i18n(Internationalization)
- flask-babel 로 다국어 대응하기
- Flask-Bcrypt - a Flask extension that provides bcrypt hashing utilities for your application
- Flask-Cache
- Flask-Login
- Flask-Migrate SQLAlchemy Migrations Using Flask-Migrate - YouTube
- Flask-MongoEngine - a Flask extension that provides integration with MongoEngine
- Flask-MySQLdb provides MySQL connection for Flask
- Flask-Potion - a RESTful API framework for Flask and SQLAlchemy http://potion.readthedocs.org
- Flask-Praetorian Flask-Praetorian Walkthrough: A Library for API Security With JSON Web Tokens (JWT)
- flask-pytest - Runs pytest in a background process when DEBUG is True
- Flask-RESTPlus
- Flask & flask-restplus && swagger ui
- Flask-RestPlus 모듈 제대로 사용해 보기
- Structuring a Flask-RESTPlus Web Service for Production Builds
- Working with APIs using Flask, Flask-RESTPlus and Swagger UI
- How to structure a Flask-RESTPlus web service for production builds
- flask-restplus-boilerplate - A boilerplate for flask restful web service
- Flask로 API 서버 만들기 (1) - 개발 환경 준비
- Flask로 API 서버 만들기 (2) - config 와 실행 확인
- Flask로 API 서버 만들기 (3) - User 테이블 만들기
- Flask로 API 서버 만들기 (4) - Testing
- Flask로 API 서버 만들기 (5) - User Operations
- Flask로 API 서버 만들기 (6) - Security and Authentication
- Flask로 API 서버 만들기 (7) - Route protection and Authorization
- Flask로 API 서버 만들기 (8) - Extra tips (Makefiles)
- flask-security Intro to Flask-Security
- flask-session Server-Side Sessions in Flask with Flask-Session - YouTube
- Flask-SocketIO — Flask-SocketIO documentation
- Flask-SQLAlchemy
- SQLAlchemy Query를 Pandas DataFrame로 만들기
- flask-sqlalchemy 외래키 구현
- Understanding the Lazy Parameter in Flask-SQLAlchemy Relationships
- Creating a RESTFul API in Flask With JSON Web Token Authentication and Flask-SQLAlchemy
- Manage Database Models with Flask-SQLAlchemy
- Getting Started With Flask-SQLAlchemy 2019
- Use Flask-SQLAlchemy With Existing Database With Reflect and Automap
- How to build a JSON API with Python
- Flask-Sqlalchemy 소개
- 파이썬 웹 개발 #1, flask, flask-sqlalchemy, todolist - YouTube
- 파이썬 웹 개발 #2, flask, flask-sqlalchemy, todolist - YouTube
- Intro to Postgres JSON Columns in Flask-SQLAlchemy - YouTube
- Querying With Dates in Flask-SQLAlchemy - YouTube
- Connecting to a Database in Flask Using Flask-SQLAlchemy - YouTube
- Intro to Flask-SQLAlchemy Queries - YouTube
- Inserting, Updating, and Deleting from a Database in Flask-SQLAlchemy - YouTube
- How to Use Flask-SQLAlchemy With Flask Blueprints - YouTube
- How to Use One-to-Many Database Relationships with Flask-SQLAlchemy | DigitalOcean
- flask-sqlacodegen - 기존 DB를 Flask-SQLAlchemy ORM Model로 사용하기
- Flask-Validation
- Frest - the frame of the restful api server created with pallets/flask
- Quart - a Python ASGI web microframework
- Yellowid-Flask
- GraphQL server up and running with 50 lines of python
- Playing With GraphQL + Python Flask
- GraphQL in the Python World
- The Fullstack Tutorial for GraphQL
- GraphQL in Python and Django
- GraphQL in Python
- Backend.AI에서 사용되는 GraphQL batching과 Pagination | Lablup Blog
- GraphQL vs REST: What's The Difference And When To Use Which? - YouTube
- Awesome-GraphQL GraphQL server with Flask + Graphene
- GraphQL Python
- graphene-python.org
- strawberry: A GraphQL library for Python that leverages type annotations 🍓
- 사용할 Python GUI 비교 및 선택하기
- Python GUI Frameworks (Guide)
- Writing a GUI Application with Python and Py2App | by Matt Harzewski | The Startup | Medium
- github.com/soma0sd/python-study/GUI
- Create a Simple Python GUI With These Open Source Projects | by Tate Galbraith | The Startup | Nov, 2020 | Medium
- Which GUI Framework is the best for Python coders?
- Introduction to Python GUI Development with Delphi for Python - Part 1: Delphi VCL for Python - YouTube
- Python Desktop GUI App with SQLite DB (PyQt/PySide/Qt Designer) - YouTube
- Dear PyGUI API Docs
- Electron as GUI of Python Applications
- enaml: Declarative User Interfaces for Python
- Gooey (Beta) - Turn (almost) any Python Console Program into a GUI application with one line
- PyAutoGUI - Cross-platform GUI automation for human beings
- pyimgui: Cython-based Python bindings for dear imgui
- PyQT
- 예제로 배우는 PyQt 예제 중심으로 배우는 PyQt 프로그래밍
- QTBook - Qt Korea Developer Community
- PyQT Python GUI Application Development with Python
- PyCon 2015 - 업무에서 빠르게 활용하는 PyQt
- PyQT Basic Tutorial
- PyQT의 소개와 특징
- 파이썬 GUI - PyQt
- Detecting Keyboard Events in PyQt4
- Python, pyqt4 스톱워치 만들기
- Creating a web-browser with Python and PyQT
- PyCon 2017 예제로 살펴보는 PyQt
- mac에서 pyqt5 시작해 보기
- pyqt5 GUI unittest 수행 간단한 툴
- PyCon2018 PyQt로 만드는 웹 기반 어플리케이션 만들기
- Qt 입문자 및 Qt for Python을 위한 작은 소개
- 헬로우 큐트 포 파이썬 (Hello Qt for Python)
- Python and Qt: 3,000 hours of developer insight
- PyQt5 Tutorial : 파이썬으로 만드는 나만의 GUI 프로그램
- PyQt5 및 Qt Designer 설치
- PyQt5 Tutorial - Setup and a Basic GUI Application
- Handling SQL Databases With PyQt: The Basics – Real Python
- Creating PyQt Layouts for GUI Python Applications - YouTube
- Electron alternative: Python and Qt. Create desktop apps in minutes.
- 생짜 :: 'karma( 업 )/QT&QML 시작하기' 카테고리의 글 목록
- fbs - build-system.fman.io
- make-a-story
- user-group-csv-cleaner
- PyQtGraph - Scientific Graphics and GUI Library for Python
- PySide
- Python GUI with PyQT/PySide2. A look and guide at a popular GUI for… | by Keno Leon | The Startup | Medium
- '파이썬-PySide6(PyQt6)' 카테고리의 글 목록
- '파이썬-PySide6(PyQt6)' 카테고리의 글 목록
- Python build a responsive GUI | UI with ANIMATED transitions | PyQt PySide Custom Widgets Module - YouTube
- PyDracula - Modern Gui Python / Flat Style - Qt Designer/PySide6 or PyQt6 - YouTube
- PySimpleGUI
- PySimpleGUI: Launched in 2018 Actively developed & supported. Supports tkinter, Qt, WxPython, Remi (in browser). Create custom GUI Windows simply, trivially with a full set of widgets. Multi-Window applications are also simple. Python 2.7 & 3 Support. 300+ Demo programs & Cookbook for rapid start. Extensive documentation. Examples using Machine Learning(GUI, OpenCV Integration, Chatterbot), Desktop Widgets (Rainmeter-like), Matplotlib + Pyplot integration, add GUI to command line scripts, PDF & Image Viewer. For both beginning and advanced programmers. docs - PySimpleGUI.org GitHub - PySimpleGUI.com. Create complex windows simply
- Python GUI Development With PySimpleGUI - YouTube
- Simplify Python GUI Development With PySimpleGUI – Real Python
- Creating 10 apps in Python with PySimpleGUI - YouTube
- pytermgui: Python TUI framework with mouse support, modular widget system, customizable and rapid terminal markup language and more!
- tkinter
Python GUI Development with Tkinter- 076923.github.io/posts/#Python-Tkinter
- '기타/tkinter 한꼬집씩만 따라해보기' 카테고리의 글 목록
- 1. tkinter 모듈 시작하기
- 2. 위젯에 간단한 오브젝트 생성하기 : Alegruz
- 3. tkinter 키 입력 : Alegruz
- 4. 벽돌깨기. 게임 물리 구현하기. : Alegruz
- 5. 벽돌깨기. 경쟁적 요소 구성하기. : Alegruz
- 6. Cocos2d 입문 : Alegruz
- 7. Cocos2d 기초. 키 입력. : Alegruz
- 8. Cocos2D 기초. 충돌 판정. : Alegruz
- GUI with Python's Tkinter, by Robert Jomar Malate
- Learn Tkinter in 20 Minutes
- Learn to Program 20 : TkInter Tutorial
- Learn to Program 21 : TkInter Tutorial 2
- Craft your own GUIs with Python and Tkinter
- How to Program a GUI Application (with Python Tkinter)!
- 파이썬 Python 코딩 - GUI tkinter 음료주문 프로그램 업그레이드 - YouTube
- How to Build a Weather App in Python? | GeeksforGeeks - YouTube
- tkinter Archives - Artificial Intelligence
- How to Shut Down Computer Logout and Restart Computer with Python GUI
- Modern Graphical User Interfaces in Python - YouTube
- Make Tkinter Python Applications Look Modern In 10 Minutes! - YouTube
-
IPython and Jupyter in Depth: High productivity, interactive Python - PyCon 2017
-
IPython: An Interactive Computing and Development Environment
-
(Window) Jupyter 에서 파이썬 2 & 파이썬 3 동시에 사용하기
-
How To Implement These 5 Powerful Probability Distributions In Python
-
주피터(Jupyter, IPython >= 3)의 다중 커널 개념 이해하기 - 파이썬2와 파이썬3 동시에 사용하기
-
launchctl을 사용한 맥 OSX에서 서비스 등록하기 - 주피터(Jupyter, IPython >= 3) 노트북 서비스 등록 예제
-
How to Scrape Data From Facebook Page Posts for Statistical Analysis
-
A Collaborative Real-time iPython Jupyter Client for Self-hosted Jupyter Servers
-
How did we serve more than 20,000 IPython notebooks for Nature readers?
-
Run Python 2 and Python 3.5 kernels in IPython Jupyter Notebook
-
Top 10 IPython Tutorials for Data Science and Machine Learning
-
Cython can improve the speed with 1d numpy array in a IPython notebook
-
remote access
# server to start jupyter $ jupyter notebook --no-browser --port=7987 # terminal in another server $ ssh -N -f -L localhost:7987:localhost:7987 [user id]@[server] # open browser then type localhost:7987 -
How do I add python3 kernel to jupyter (IPython)
$ sudo /path/to/anaconda3/bin/ipython3 kernel install Installed kernelspec python3 in /usr/local/share/jupyter/kernels/python3 -
!jupyter nbconvert --to python file_name.ipynbwrite at the end of the notebook to save jupyter notebook codes as python file -
conda upgrade notebook동작하지 않음pip install --upgrade notebook- 오류 발생
Cannot remove entries from nonexistent file /path/to/anaconda/lib/python2.7/site-packages/easy-install.pth pip install --ignore-installed --upgrade pip setuptools실행 후 재실행하니 성공
- 오류 발생
-
Top 10 IPython Notebook Tutorials for Data Science and Machine Learning
-
Create Isolated Jupyter Ipython Kernels With Pyenv And Virtualenv
-
Jupyter notebook 파이썬 가상환경 Kernel 추가/제거 (on MAC) | by Kwoncheol Shin | Medium
-
Multi-user server for Jupyter notebooks https://jupyterhub.readthedocs.io
-
JupyterHub Tutorial: Set up your Lab, Classroom, or Business
-
webia.lip6.fr/~pajot/dataviz.html pandas, matplotlib, numpy, seaborn example
-
Jupyter Notebook Tricks for Data Science that Enhance your efficiency
-
IPython & Jupyter in depth: high productivity interactive and parallel python PyCon 2015
-
A very simple demo of interactive controls on Jupyter notebook
-
How To Set Up Jupyter Notebook with Python 3 on Ubuntu 18.04 | DigitalOcean
-
How to Automatically Import Your Favorite Libraries into IPython or a Jupyter Notebook
-
Building a Repeatable Data Analysis Process with Jupyter Notebooks
-
Jupyter Interactive Widget Ecosystem Tutorial | SciPy 2020 | Craig, Renou, Dafna, Bektas - YouTube
-
PyData Ann Arbor: Madicken Munk | Widgyts: yt Jupyter Widgets for Volumetric Data Exploration
-
4 Awesome Tips for Enhancing Jupyter Notebooks - Towards Data Science
-
William Horton - A Brief History of Jupyter Notebooks - YouTube
-
Making data science notebook collaborative - Jan Matas PyData Prague #8 2020 - YouTube
-
On writing clean Jupyter notebooks | by Eduardo Blancas | Jul, 2021 | Towards Data Science
-
How to code when all you know are Jupyter Notebooks | by Helene Kortschak | Towards Data Science
-
From Jupyter to Production - Filip Jankovic | PyData Global 2021 - YouTube
-
📚 Notebook To Production 👷🏼 - Nir Barazida | PyData Global 2021 - YouTube
-
Threat Alert: First Python Ransomware Attack Targeting Jupyter Notebooks
-
PyData Chicago: Running Notebooks in Production? Blessing or Curse? by Eduardo Blancas - YouTube
- Jupyter Notebook Extensions
- 주피터 노트북 익스텐션을 활용하여 생산성 높이기
- How to Write a Jupyter Notebook Extension
- Set Your Jupyter Notebook up Right with this Extension
- 10 Useful Jupyter Notebook Extensions for a Data Scientist in 2021 | Towards Data Science
- Low Code Python has Arrived. I started using Python for data science… | by Jake from Mito | trymito | Mar, 2022 | Medium Bamboolib Lux Mito
- awesome-jupyter: A curated list of awesome Jupyter projects, libraries and resources
- Binder - Turn a Git repo into a collection of interactive notebooks
- cheat-sheet
- Converter_py-ipynb-md: Converter : Python file(.py) , Jupyter Notebook file (.ipynb), Markdown file(.md)
- drawdata: Draw datasets from within Jupyter
- calmcode - learn code calmly
- 선을 그리거나, 점을 찍으면 2차원 데이터 생성. 데이터는 csv나 json 포맷 데이터셋으로 다운 가능
- 장점: 사용이 쉽고 직관적. 교육용 데이터셋 생성에 유용
- 단점: 아직 label을 4개(a,b,c,d)까지 생성 가능
- Emacs IPython Notebook
- handcalcs: Python library for converting Python calculations into rendered latex
- Hydrogen - an interactive coding environment that supports Python, R, JavaScript and other Jupyter kernels
- ipython-sql · PyPI
- ipytracer 알고리즘 시각화 라이브러리 ipytracer 개발기
- ipywidgets
- jnotebook_reader: An awesome viewer to browse and render Jupyter Notebooks from local, Amazon S3, Google Cloud Storage or MinIO
- jovian.ml - Make Jupyter notebooks commentable collaborative sharable
-
- 주피터 노트북 버전관리 (diff 도 가능)
-
- 주피터 노트북의 버전별, 코드/마크다운 셀별 Comment 기능 (댓글의 댓글도 가능)
-
- 프레젠테이션 모드
-
- Colab, Kaggle, Binder 로 원클릭 포팅 및 실행
-
- 다른 사람이 만든 주피터 노트북 탐색
-
- 주피터 노트북 clone시, 필요한 패키지 자동 탐색 및 environment.yml 파일 자동 생성
-
- JupyShare lets you release your notebook to the cloud and gives you a public endpoint for it through ngrok
- JupyterLab - An extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture
- jupyterlab.readthedocs.io
- jupyterlab-github: GitHub integration for JupyterLab
- github jupyterlab-extension
- JupyterLab: the next generation of the Jupyter Notebook
- JupyterLab: The Next-Generation Jupyter Frontend
- JupyterLab is Ready for Users
pip install jupyterlabconda install -c conda-forge jupyterlab
- 주피터 노트북의 진화!
- A Diagram Editor for JupyterLab
- How to change JupyterLab Theme(Easy Method)
- JupyterLab first impressions
- Jupyter Notebook보다 쉽고 편리하다, Jupyter Lab!
- Jupyter Lab: Evolution of the Jupyter Notebook
- A visual debugger for Jupyter
- 3 Must-have JupyterLab 2.0 extensions - Towards Data Science
- AI-Powered Code Completion in JupyterLab | by Robert Ritz | Towards Data Science
- JupyterLab 3.0 is released!. The 3.0 release of JupyterLab brings… | by Jeremy Tuloup | Jan, 2021 | Jupyter Blog
- Jupyter 노트북 테마적용
- Jupyter Theme 적용
- JupyterLab Desktop App now available! | by Mehmet Bektas | Sep, 2021 | Jupyter Blog
- Introducing the new JupyterLab Desktop! | by Mehmet Bektas | Feb, 2023 | Jupyter Blog
- jupyterlab-interactive-dashboard-editor
- JupyterLite
- jupyterlite: Wasm powered Jupyter running in the browser
- JupyterLite - WASM 기반 Jupyter | GeekNews
- Blog - Jeremy Tuloup
- JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python | by Jeremy Tuloup | Jul, 2021 | Jupyter Blog
- Jeremy Tuloup - JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python PyData Prague 2022-05-10 - YouTube
- Ep(207) 파이썬 무설치 버전? JupyterLite 써봅시다! - YouTube
- jupyterthemes
- jupyter-vim-binding
- jupytext Version Control With Jupyter Notebook | by Shinichi Okada | Towards Data Science
- jupyverse: A Jupyter server based on FastAPI (Experimental)
- koreanize-matplotlib: install & import하는 것만으로 matplotlib에서 한국어를 표시할 수 있습니다
- MakinaRocks Link
- 특징
- 👉 Jupyter Cell을 컴포넌트로 파이프라인 구성
- 👉 Jupyter Lab 위에서 동일하게 실행 (cmd & ctrl + Enter)
- 👉 실행시 파이프라인 내 dependency가 있는 컴포넌트들을 순서대로 실행하고나서 실행
- 👉 Caching 기능 제공 (반복 실행시 시간 단축)
- 👉 Pipeline Export & Import (협업, Kubeflow Pipeline 과 호환)
- 👉 JupyterLab Extension - 터미널에서 “jupyter lab” 커맨드로 실행
- 👉 whl파일로 개인 가상환경에 설치 (+ 별도의 가상환경을 제공하는 Desktop App 형태로도 제공)
- 파이프라인 작성으로 해당 노트북은 언제든지 재현 가능
- 메타 머신러닝 테크리드가 지적한 쥬피터의 단점 - “재현등의 이슈로 쥬피터로는 머신러닝 프로젝트에서 프로토타이핑만 하라" - 을 상당 부분 보완
- 예시
- Spiral Pattern Classification
- Image Restoration using Denoising Autoencoder
- Text Data Classification using RNN
- Image Generation using Variational Autoencoder
- Link 시작 방법
- 1️⃣ 아래 첨부한 제품 페이지에서 본인 환경에 맞는 whl 파일 or Desktop App 다운로드
- 2️⃣ 본인 가상환경에 "python -m pip install <whl 파일>" 로 설치 or Desktop App 설치
- 3️⃣ 제품 페이지에서 Product Key 발급 → 이메일로 전달
- 4️⃣ "jupyter lab" 커맨드 혹은 App 실행
- 5️⃣ Product Key 입력
- 6️⃣ Link 시작!
- 프롤로그 - MakinaRocks Link
- Link Examples - MakinaRocks Link
- link-example: Machine Learning Study
- The Best Jupyterlab Extension That You Didn't Know Existed! - YouTube
- 특징
- Mercury – Build Data Web Apps in Jupyter Notebook
- nbextension Jupyter notebook 테마 및 확장기능(nbextensions) 설치 방법
- nbterm - edit and execute Jupyter Notebooks in the terminal
- notebook-environments Manage python virtual environments on the working notebook server
- Notebooks Academy — Notebooks Academy
- nteract and create with data, words, and visuals jupyter notebook을 web이 아니라 local에서 실행
- Oasis Data system opens its doors to all Liners
- ob-ipython - org-babel integration with IPython for evaluation
- Papermill is a tool for parameterizing and executing Jupyter Notebooks
- Pineapple - The next generation of scientific notebook. A standalone frontend to IPython for Mac
- ploomber: Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud
- polynote - The polyglot notebook with first-class Scala support
- powerbiclient Announcing Power BI in Jupyter notebooks | Microsoft Power BI Blog | Microsoft Power BI
- Pyflyby: Improving Efficiency of Jupyter Interactive Sessions | Quansight Labs
- pyxll-jupyter · PyPI
- 엑셀 주피터 노트북 결합
- 엑셀 데이터를 파이선으로 조작하거나, 파이선으로 조작된 데이터나 시각화 정보를 엑셀로 가져오는 2-way binding 작업에 유용
- pyxll-jupyter 패키지 설치하면, 엑셀에 PyXLL 이라는 확장이 설치. 여기서 Jupyter를 클릭하면, 엑셀과 주피터 노트북을 사이드-바이-사이드로 작업 가능. 단, Windows only
- 주피터 노트북, %xl_get 매직 커맨드로, 엑셀의 선택된 부분을 Numpy 또는 Pandas Dataframe으로 들고오기 (선택된 부분 임의로 코드 상에서 지정 가능)
- 주피터 노트북, %xl_set 매직 커맨드로, 엑셀의 원하는 부분에 파이선 데이터 내보내기
- 주피터 노트북, %xl_plot 매직 커맨드로, 파이선 시각화 라이브러리 (matplotlib, plotly)로 그려진 도표를 엑셀로 내보내기 (크기 조절 가능)
- 주피터 노트북, xl_app 함수를 사용하여, 엑셀 Application 객체 접근 가능 (즉, 엑셀의 모든것을 건드릴 수 있음 - VB Script와 사실상 거의 동일)
- 주피터 노트북을 떠나서 다음과 같은 일도 가능
- @xl_func 데코레이터로 래핑된 파이선 함수를 작성, 파이선 함수 자체를 엑셀에서 호출 (해당 함수가 반환하는 값이 그대로 엑셀에 삽입) 단, 작성된 파이선 함수 위치를 config에 등록해야 함
- Python Jupyter Notebooks in Excel | by Tony Roberts | Dec, 2020 | Towards Data Science
- ReviewNB - Code Reviews for Jupyter Notebooks Say Goodbye to messy JSON diffs!
- 주피터 노트북을 깃헙에 올리고, raw 한 환경에서 리뷰하면 JSON 파일. 따라서, 실질적인 리뷰를 하려면 로컬환경이나 Colab 등에 포팅한 다음 validation 체크를 하고, PR을 처리해 줘야 함
- ReviewNB는 깃헙에서 노트북 코드의 리뷰를 실제 노트북이 렌더링 된 상태에서, 직관적으로 할 수 있도록 도와주는 툴
- Public 저장소는 개수 상관없이 무료로 무제한 사용 가능
- "Install GitHub App" 버튼을 누르시고 Free 버전을 마켓플레이스에서 설치하면 ok. 현재 진행중인 PR에 대해 comment, 과거의 PR을 선택하여 노트북이 사이드-바이-사이드로 렌더링된 상태로 diff 확인 가능
- RISE: Live Reveal.js Jupyter/IPython Slideshow Extension
- Rodeo: A data science IDE for Python
- Saturn: Web IDE for Machine Learning http://saturn.proinlab.com
- Traitlets
- Voila Voila를 사용해 Jupyter Notebook Dashboard 만들기
- xeus-python: Jupyter kernel for the Python programming language
- Six easy ways to run your Jupyter Notebook in the cloud
- colab.research.google.com 설치 후 keras 사용 가능
-
Getting Started With Google Colab | by Anne Bonner | Towards Data Science
-
Neural Networks with Google CoLaboratory | Artificial Intelligence Getting started
-
Train Your Machine Learning Models on Google’s GPUs for Free — Forever
-
EN-FR Machine Translation with Various RNN Models in Google CoLab (1)
-
구글 드라이브의 Colabortory를 통해 파이썬 데이터 시각화툴(Matplotlib, Seaborn, Altair, Plotly, bokeh) 사용하기
-
Deep_Learning_3: Importing Kaggle's dataset in Google Colaboratory
-
A Complete guide to Google Colab for Deep Learning - KDnuggets
-
Getting Started With Google Colab - A Simple Tutorial for the Frustrated and Confused
-
코랩 시작하기 file upload, google drive 연동 방법
-
example read file
# 1. local to colab for small files from google.colab import files uploaded = files.upload() for fn in uploaded.keys(): print('User uploaded file "{name}" with length {length} bytes'.format(name=fn, length=len(uploaded[fn]))) # 2. google drive from google.colab import drive drive.mount('/content/gdrive/') -
The speed of your input pipeline counts .cache를 이용한 속도 향상. ipynb
-
Configuring Google Colab Like A Pro | by Made-Up Masters | Aug, 2020 | Medium
-
colabctl: Google Colaboratory background/task executioner & controller
-
colab-tf-utils - Simple GDrive-Based model checkpointing from within Google's Colab service
-
HC.Dle Colab 한글 폰트 코드
- Jupyter Enterprise Gateway
- jupyter.nims.re.kr github api 연동, keras 사용 가능
- notebooks.azure.com 계정에 따라 다른데 login이 자꾸 풀리는 경우가 있음
- Java class를 Python에서 사용하기 결국 subprocess 이야기
- JPype - an effort to allow python programs full access to java class libraries. http://www.jpype.org
- Jython
- VOC - A transpiler that converts Python bytecode into Java bytecode
- JSPyBridge: Bridge to interoperate Node.js and Python
- spidermonkey - Python/JavaScript bridge module, making use of Mozilla's spidermonkey JavaScript implementation
- Awesome Python - A curated list of awesome Python frameworks, packages, software and resources
- Top 5 Useful Python Libraries Web Developers Can't Live Without
- Scrapy, Zappa, Boto, Requests, Tensorflow
- Command Line
- How to Write Perfect Python Command-line Interfaces — Learn by Example
- Build your own Command Line with ANSI escape codes
- 한종원 : Daily Continuous Deployment를 위한 custom CLI 개발 및 AWS Elastic Beanstalk에 적용하기
- 4 Python libraries for building great command-line user interfaces
- Tools for Writing Python CLI Applications
- bpython - A fancy curses interface to the Python interactive interpreter http://bpython-interpreter.org
- bun: A Python package for a basic CLI and GUI user interface
- Girok - The most powerful CLI task manager
- prompt-toolkit Tools for building command line applications in Python
- python_snippet: Python and data science snippets on the command line
- PyVNCs - Simple command line multiplatform python VNC Server
- Rich is a Python library for rich text and beautiful formatting in the terminal
- simm.py - announcing command line file similarity tool
- soccer-cli - Football scores for hackers. A command line interface for all the football scores
- topydo - A command-line todo list application using the todo.txt format
- Python Development: 7 Libraries to Look For in 2017
- My top 5 ‘new’ Python modules of 2015 tqdm, joblib, folium, tinydb, dill
- 10 Python Machine Learning Projects on GitHub
- 9 Python Analytics Libraries
- Machine Learning Exercises In Python, Part 1 python exercises of Andrew Ng's maching learning class on Coursera
- Three Useful Python Libraries for Startups
- Like builtins, but boltons. Constructs/recipes/snippets that would be handy in the standard library. Nothing like Michael Bolton
- 50 Popular Python open-source projects on GitHub in 2018
- Top 10 Python Web Frameworks to Learn in 2018
- A Beginner’s Introduction to Python Web Frameworks
- 11 new Python web frameworks
- Learning A New Data Science Language Pandas, Framequery, SciKit-Learn, Pandas-gbq
- 모든 파이썬 프로그래머를 위한 20가지 실용적인 파이썬 라이브러리
- 아파치 Libcloud, 애로우(Arrow), 비홀드(Behold), 보틀(Bottle), EbookLib, 구이(Gooey), 인보크(Invoke), 누이트카(Nuitka), 눔바(Numba), 피위(Peewee), 필로우(Pillow), 파이파일시스템(PyFilesystem), 파이게임(Pygame), 파이글릿(Pyglet), 파이인스톨러(PyInstaller), 파이심플GUI(PySimpleGUI), 파이썬-docx, 스크래피(Scrapy), Sh, 스플린터(Splinter)
- Let’s Build A Web Server
- The Top 10 Python Frameworks for Web Development
- Magnificent app which corrects your previous console command
- PROBABILISTIC M2M RELATIONSHIPS USING BLOOM FILTERS pyhash, bitstring
- Top 20 Python Machine Learning Open Source Projects
- Top 10 Python libraries of 2016
- Don’t Miss out on these 24 Amazing Python Libraries for Data Science
- 파이썬 활용, 파이썬 프로젝트로 할 수 있는 일들을 알아보자!
- Top 10 Python libraries of 2019
- 20 Python libraries you aren’t using (but should) – O’Reilly
- 3 Insane Secret Weapons for Python kite, mypy, sonarlint
- 10 Tools I Use to Craft Better Python Code | by Richard Quinn | Level Up Coding Black, Eradicate, Vulture, Coverage, Pycodestyle, Pylint, Mypy, Pyflakes, Doctest, Bandit, Radon
- Building Tools with Python. Leveraging the open source… | by Animesh Javali | Medium argparse, tkinter
- State-of-the-art python project setup | by Nitin Aggarwal | Towards Data Science pipenv, flake8-black, isort, mypy, pytest, coverage, VSCode
- 파이썬의 기본 도구들 · 개발블로그 pip, pytest, black, pyenv, virtualenv, jupyter notebook
- Top 15 Python Packages You Must Try | by Erik van Baaren | Programming with Erik | Medium Dash, PyGame, Pillow, Colorama, JmesPath, Requests, Simplejson, Emoji, Chardet, Python-dateutil, Progress bars: progress and tqdm, IPython, Homeassistant, Flask, Beautiful soup
- Top 10 Python Tools for IT Administrators ActiveState ActiveState
- The Top 10 Most Downloaded Python Packages By Developers | by Sunil Sandhu | Python In Plain English | Nov, 2020 | Medium Urllib3, Six, Botocore, Pip, Python-dateutil, Requests, Certifi, Idna, Pyasn1
- Top 16 Python Applications in Real-World | by Claire D. Costa | Nov, 2020 | Towards Data Science
- 10 examples of using Python in 2020 | Opensource.com
- What Can I Do With Python? – Real Python
- Top Python Libraries And Frameworks - My Guide Info
- Must-Know Python Libraries - DZone Web Dev PySnooper Faker Pickle
- Abseil Python Common Libraries
- Advanced Python Scheduler
- AGATE: A BETTER DATA ANALYSIS LIBRARY FOR JOURNALISTS
- AI-Personal-Voice-assistant-using-Python
- How to build your own AI personal assistant using Python | by M.Mirthula | Towards Data Science speech_recognition, pyttsx3, wikipedia, webbrowser, ecapture, wolframalpha
- anaconda - http://continuum.io/downloads
- install
- installations
- Anaconda3.5 설치 & 오류 해결 방법
- How to Install Anaconda Python on Windows | How to Install Anaconda on Windows
- Visual Studio Code로 편리한 Pylife!
- 파이썬/아나콘다 설치 안내
- 통컨(통계컨설팅) :: 첫째날 1.3 아나콘다 시작하기 - 회귀분석 까지(P1)
- 정해영의 블로그 - JEONG Haeyoung's blog: SSL과 관련한 conda 설치 에러 - anaconda3 해결
- Using Anaconda behind a company proxy — Anaconda documentation
- Conda Package Repository
- conda.pydata.org
conda install -c anaconda cx_oracle- might need to proxy
https_proxy=http[s]://x.y.z.w:port ... - might need to execute after
sudo -i
- might need to proxy
- jjhelmus
- 파이선 가상환경 콘다 시작하기
- 아나콘다 가상환경
- conda tab completion (자동완성) 만들기
- practice - 다른 버전의 파이썬 설치하고 사용하기
- How to Start a Data Science Project in Python
- 데이터 분석을 위한 기본적인 Python 환경 설정 방법
- Anaconda의 Conda를 활용해 분리된 환경 설정
- 하나의 Python 데이터 분석 프로젝트의 디렉토리를 구성하는 방법
- Python Tutorial: Anaconda - Installation and Using Conda
- Python - Install Anaconda, Jupyter Notebook, Spyder on Windows 10
- How To Install Anaconda!
- Install Python 🐍 with Anaconda: Jupyter Notebook and Spyder
- What is Anaconda? Install Anaconda On Windows
- Install Python (Anaconda) on Windows + Setting Python and Conda Path (2017)
- how to install anaconda python on windows 10
- How to Download and Install Python 3.6 on Windows 10
- Advanced Features of Conda Part 1
- Advanced Features of Conda Part 2
- Conda에 대한 간단 고찰 및 mac에서 Jupyter notebook 시 오류 해결
- Why you need Python environments and how to manage them with Conda
- conda 환경에서 pip 패키지도 동시에 업데이트 하기
conda install accelerateHow to put that GPU to good use with Python- conda env 터미널 명령어. 아나콘다 가상환경 명령어 정리 (진짜 간단한데, 구글링하기 귀찮아서… | by 5eo1ab | Medium
- Using conda on an M1 Mac. Run multiple conda distributions to get… | by Nils Flaschel | Jul, 2021 | Towards Data Science
- Pip vs Conda: an in-depth comparison of Python’s two packaging systems
- Serving and Managing Reproducible Conda Environments via Conda-store | PyData Global 2021 - YouTube
- Makefiles: One Great Trick for Making Your Conda Environments More Managable | PyData Global 2021 - YouTube
- Data Science for Losers
- LEARNING PYTHON FOR DATA SCIENCE: CHEAT SHEETS
- Python Anaconda & GPU - 세팅 및 성능 비교
- gtc_fall: GPU Optimization for Python
- 초간단 머신러닝 개발 환경 세팅하기 (with 아나콘다)
- Accelerate Python Performance Powered by Anaconda
- Anaconda-Python 환경에서 VSCode를 사용하는 방법(프로젝트 생성, 환경 구축, 디버깅)
- 데이터 분석을 위한 파이썬 개발환경 구축 (Windows)
- How to get started with Python for Deep Learning and Data Science
- 아나콘다 소개와 주피터 확장 설치방법 소개 - YouTube
- miniconda Stop Using Anaconda for Your Data Science Projects | by Rionaldi Chandraseta | The Startup | Sep, 2020 | Medium
- install
- angr is a framework for analyzing binaries
- Anime2Sketch: A sketch extractor for anime/illustration
- API-Hour - Write efficient network daemons (HTTP, SSH...) with ease. http://pythonhosted.org/api_hour
- Asyncio Time Travel Loop
- asyncwsgi
- Bake — the strangely familiar workflow utility makefile과 비슷하게 bakefile을 통해 작업 처리. automation
- barcode Generate Barcode using Python - Python Programming - PyShark
- BARF : A multiplatform open source Binary Analysis and Reverse engineering Framework
- BaseCrack A Python tool that can decode all alphanumeric base encoding schemes
- Bin Packing Algorithm http://towry.me
- bioread - for reading the files produced by BIOPAC's AcqKnowledge software
- Blaze-Tracker: Automated Production Package Deployment Solution
- BlueLink - 현대자동차 제어용 Python API Wrapper (Unofficia | GeekNews
- Bokken - Open Source Reverse Code Engineering
- bolt: 10x faster matrix and vector operations
- BoopSuite - A Suite of Tools written in Python for wireless auditing and security testing
- Boost.Python
- BrickRegistration - a tool to generate synthetic 3d scenes for toying with bricks registration
- BTables: A fast, compact disk format for machine learning
- bwa: 이거 봐(Bwa): Notification Sender for Discord, E-mail, Slack, and Telegram
- c8d - A Chip-8 disassembler in Python
- calcengine: Simple Python Calculation Engine
- castervoice - On Voice Coding
- Celery
- Introduction to Celery
- Introduction to Celery
- Three quick tips from two years with Celery
- Celery 관련 기사/튜토리얼/How-To를 읽고 메모한 내용
- Asynchronous Tasks With Django and Celery
- Celery 4.0의 주요 변경사항 정리
- 파이썬 동시성 프로그래밍 - (6) 분산 (celery)
- Celery를 이용한 긴 작업 처리
- Real time celery monitoring using websockets https://wscelery.readthedocs.io
- Checklist to build great Celery async tasks
- Celery로 TelegramBot 알림 보내기
- 셀러리: 시작하기
- 셀러리 입문하기
- Asynchronous Tasks in Python - Celery Backend Tutorial
- Asynchronous Tasks in Python - Getting Started With Celery
- Celery 관련 기사/튜토리얼/How-To를 읽고 메모한 내용
- Flower - Celery monitoring tool
- How to Cancel a Running Task in Celery - YouTube
- clubhouse-py: Clubhouse API written in Python. Standalone client included. For reference and education purposes only
- Clutterm - A clutter based terminal written in pure python (no vte lib)
- colout - a simple command to add colors to a text stream in your terminal
- Conductor - A system for testing distributed systems across a network
- conference-tracker - Minimal-maintenance conference tracker
- Connexion - a framework that automagically handles HTTP requests based on OpenAPI Specification (formerly known as Swagger Spec) of your API described in YAML format
- countryinfo Day 13 : Country info in Python - YouTube
- CPython
- CPython internals: A ten-hour codewalk through the Python interpreter source code
- CPython internals: A ten-hour codewalk through the Python interpreter source code
- Escaping a Python sandbox with a memory corruption bug
- Back to the Low Level
- Python Is Fast!
- Peephole: CPython은 어떻게 코드를 최적화하는가
- Kavya Joshi The Memory Chronicles A Tale of Two Pythons PyCon 2017
- A fantastic dive into the internals of how CPython and Micropython manage memory differently
- Under the C
- Make Python Hundreds of Times Faster With a C-Extension | by JOSHUA WEINSTEIN | The Startup | Medium
- CPython internals: why bother? (James Powell)
- Getting Started with Python Internals
- Why Python's The Best Language For AI (and How To Make It Even Better)
- Dynamic Code Instrumentation with Hacked Interpreters || James Powell
- Blurb-it is now available CPython contribution 방법
- Your Guide to the CPython Source Code
- Memory Management in Python
- python 메모리 관리(memory allocation)
- Python behind the scenes #1: how the CPython VM works
- Python behind the scenes #2: how the CPython compiler works
- Python behind the scenes #3: stepping through the CPython source code
- Python behind the scenes #5: how variables are implemented in CPython
- Python behind the scenes #6: how Python object system works
- Python behind the scenes #7: how Python attributes work
- Python behind the scenes #8: how Python integers work
- Python behind the scenes #9: how Python strings work
- Python behind the scenes #10: how Python dictionaries work
- Python behind the scenes #11: how the Python import system works
- Learn CPython by Breaking It - YouTube
- Python 내부의 C 코드 들여다보기 | tempkdw blog
- How we are making Python 3.11 faster (CPython project) - YouTube
- How we are making Python 3.11 faster - presented by Mark Shannon - YouTube
- Python의 최적화 그리고 C 바인딩 이야기. 한성민 - PyCon Korea 2021 - YouTube
- cinder: Instagram's performance oriented fork of CPython
- faster-cpython/plan.md at master · markshannon/faster-cpython
- FasterCPythonDark.pdf at main · faster-cpython/ideas
- credstash - A little utility for managing credentials in the cloud
- Chromote - Simple wrapper to drive Google Chrome from Python using the Remote Debugging Protocol 1.1 API
- cx_Oracle - PYTHON – CX_ORACLE THROWS MISSING LIBCLNTSH.SO.11.1 WHEN EXECUTED BY DJANGO-CHRONOGRAPH
- dash - a Python framework for building analytical web applications. No JavaScript required
- Datajoy - Python & R, for scientists Easy to use, online data processing with Python and R
- Datalore란 무엇인가요? | The JetBrains Datalore Blog
- DataMatrix - an intuitive Python library for working with column-based and continuous data
- Dedupe de-duplication and entity resolution quickly on structured data
- deduplipy: Python package for deduplication/entity resolution using active learning
- Depix: Recovers passwords from pixelized screenshots
- DET (extensible) Data Exfiltration Toolkit
- DiffPy - Atomic Structure Analysis in Python A free and open source software project to provide python software for diffraction analysis and the study of the atomic structure of materials
- docx Microsoft Office Word 2007
- DoGelang
- domhttpx A google search engine dorker with HTTP toolkit built with python
- dontasq - Extend built-in Python collections with LINQ-for-objects style methods
- Edward is a Python library for probabilistic modeling, inference, and criticism
- Elizabeth - a Python library, which helps generate mock data for various purposes. This data can be particularly useful during software development and testing. http://lk-geimfari.github.io/elizabeth
- enaml - Declarative User Interfaces for Python
- extruct is a library for extracting embedded metadata from HTML markup
- fabric
- Faster CPython FAT Python
- fatcat-scholar: search interface for scholarly works
- Faust - A library for building streaming applications in Python
- fawkes: Fawkes, privacy preserving tool against facial recognition systems. More info at https://sandlab.cs.uchicago.edu/fawkes
- fbchat: Facebook Chat (Messenger) for Python
- Feather: A Fast On-Disk Format for Data Frames for R and Python, powered by Apache Arrow
- FinTech package for Python (SEPA, EBICS & more)
- Flanker - an open source parsing library written in Python by the Mailgun Team
- flexx - Python UI tookit based on web technology http://flexx.readthedocs.org
- flickrd - 파이썬3으로 작성한 플리커 사진 다운로드 프로그램
- FilterPy - a Python library that implements a number of Bayesian filters, most notably Kalman filters
- forex_python Day 26 : Real time Currency Converter with Python - YouTube
- fsspec: Filesystem interfaces for Python — fsspec 2021.06.1+1.gd915d3e.dirty documentation
- GDB dashboard - Modular visual interface for GDB in Python
- gevent - Coroutine-based concurrency library for Python http://gevent.org
- ghapi: A delightful and complete interface to GitHub's amazing API
- Ghost.py - Webkit based scriptable web browser for python. http://ghost-py.readthedocs.org
- GNU Radio A free toolkit that provides signal processing blocks to implement software radios
- GOOGLER: NOW YOU CAN GOOGLE FROM LINUX TERMINAL!
- google API
- calendar One Day Builds: Task Automation With Python
- drive
- sheet
- sheetfu - Python library to interact with Google Sheets V4 API
- Advanced Drive Service in Apps Script
- golpy: Efficient Conway's Game of Life implemented in Python using NumPy
- goSecure - an easy-to-use and portable Virtual Private Network (VPN) solution
- goto - A function decorator to use goto in Python
- gping - Ping, but with a graph
- Grumpy: Go running Python
- guietta - A tool for making simple Python GUIs
- happybase
- HASK - Haskell language features and standard libraries in pure Python
- hazelnut - an APACHE licensed library written in Python designed to provide a simple and pythonic way to parse the /proc/meminfo file on LINUX based systems
- High-Frequency-Trading-Model-with-IB - A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python
- highlander - There can be only one... process
- howdoi - 파이썬 유틸 howdoi 분석
- HPy - A better C API for Python | HPy
- htsint: a Python library for sequencing pipelines that combines data through gene set generation
- Hy
- Hydra | Hydra
- Ibis: Scaling the Python Data Experience
- Informer (TGInformer) - a bot library that allows you to masquerade as multiple REAL users on telegram and spy on 500+ Telegram channels per account
- Instagram-API-python
- Instagram Private API - A Python wrapper for the Instagram private API with no 3rd party dependencies. Supports both the app and web APIs
- instaviz: Instant visualization of Python AST and Code Objects
- iterfzf: Pythonic interface to fzf
- Japronto! - screaming-fast, scalable, asynchronous Python 3.5+ web micro-framework integrated with pipelining HTTP server based on uvloop and picohttpparser
- Kanna makes html components easier to display. like table, panel, etc
- Kazoo - a Python library designed to make working with Zookeeper a more hassle-free experience that is less prone to error
- KeePassC is a curses-based password manager compatible to KeePass v.1.x and KeePassX
- Keras: Theano-based Deep Learning library
- KicomAV
- Kite - Your programming copilot Kite augments your coding environment with all the internet’s programming knowledge
- Kore4 and Python
- Krill - The hacker's way of keeping up with the world
- latexify_example.ipynb - Colaboratory
- LemonGraph - a log-based transactional graph (nodes/edges/properties) database engine that is backed by a single file
- Levenshtein Automata implementations
- libtclpy - This is a Tcl extension to effortlessly to call bidirectionally between Tcl and Python, targeting Tcl >= 8.5 and Python 2.6 - 2.7
- LightNet: Bringing pjreddie's DarkNet out of the shadows
- LinkedList
- logpy - Logic Programming in Python
- Lomond
- lupa - Lua in Python http://pypi.python.org/pypi/lupa
- macropy - Macros in Python: quasiquotes, case classes, LINQ and more!
- magic-wormhole: get things from one computer to another, safely Get things from one computer to another, safely
- Mani - a distribued cron like scheduler
- MicroPython
- MicroPython - a lean and efficient Python implementation for microcontrollers and constrained systems
- Writing Fast and Efficient MicroPython by the Creator of MicroPython
- MicroPython Used in Industrial Applications
- MicroPython in Docker Containers
- awesome-micropython: A curated list of awesome MicroPython libraries, frameworks, software and resources
- minikeyvalue
- miracle-ad - AAA 중 Authorization 관련 모듈 - miracle-acl
- MORPHiS is a global encrypted distributed datastore intended to replace the cloud for storage and far more
- moviepy: Video editing with Python
- MUMPS : a parallel sparse direct solver
- natsort - Simple yet flexible natural sorting in Python
- NBAPB (Blog Auto Posting Bot)
- ndindex - Introducing ndindex, a Python library for manipulating indices of ndarrays
- NetworkX -> graph
- NeuPy - Neural Networks in Python
- Neural Doodle - Use a deep neural network to borrow the skills of real artists and turn your two-bit doodles into masterpieces
- nonoCAPTCHA: An asynchronized Python library to automate solving ReCAPTCHA v2 using audio
- notion-py 파이썬에서 노션 API를 사용하여 뉴스 크롤링한 정보를 노션에 업로드하기 (notion-py)
- notion-sdk-py
- Numba
- Optimizing Python in the Real World: NumPy, Numba, and the NUFFT
- numba - 성능 업!
- Numba - Numpy Aware Dynamic Python Compiler Using LLVM
- High Performance Data Processing in Python || Donald Whyte numpy & numba
- Massively Speed-Up Python Code With Numba Compilation - YouTube
- Make Python code 1000x Faster with Numba - YouTube
- Faster Python calculations with Numba: 2 lines of code, 13× speed-up
- Nuitka - the extremely compatible Python compiler
- OpenBCI On Brain-Computer Interfaces and Explainable Workflows using Python | PyData Boston Meetup - YouTube BrainWave
- Ohmu - View space usage in your terminal
- oneliner - Convert any Python file into a single line of code
- Opnieuw: A simple and intuitive retrying library for Python
- Orator - AN ACTIVERECORD ORM FOR PYTHON
- orfipy A python tool to extract ORFs in an extremely and fast and flexible manner
- Oso Documentation a batteries-included framework for building authorization in your application
- outrun: Execute a local command using the processing power of another Linux machine
- Oxyry Python Obfuscator
- p - Dead Simple Interactive Python Version Management
- Pampy: The Pattern Matching for Python you always dreamed of
- paramiko
- Passpie: manage login credentials from the terminal
- pattern.graph
- PeachPy is a Python framework for writing high-performance assembly kernels
- Pendulum - PYTHON DATETIMES MADE EASY
- petl - Extract, Transform and Load (Tables of Data) — petl 1.1.1
- plotline - A Grammar of Graphics for Python based on ggplot2
- plydata is a library that provides a small grammar for data manipulation
- pomegranate - a package for graphical models and Bayesian statistics for Python, implemented in cython
- ppml - labs/material for the Privacy Preserving Machine Learning Class I am teaching, hence ppml
- PSMVC : a terminal hack generator built in python
- Pseudo takes an algorithm / a simple program and generates idiomatic code for it in Python, JavaScript, C#, Go and Ruby
- Ptop - An awesome task manager written in Python !
- ptracer - A library for ptrace-based tracing of Python programs https://ptracer.readthedocs.io
- PTVS - Python Tools for Visual Studio https://microsoft.github.io/PTVS
- pullbox - A dead-simple dropbox alternative using Git
- Pulsar - Concurrent framework for Python
- py-ascii-graph - A simple python lib to print data as ascii histograms
- PyBetween: Wrapper for Between - 비트윈을 위한 파이썬 라이브러리
- pyClamd - use ClamAV antivirus from Python
- pyclovaocr: Unofficial Clova AI OCR Python Wrapper
- PycURL - Python interface to libcurl http://pycurl.io
- pyDash - A Python App For Monitoring Your Linux Server
- pydbgen
- PyEBPF — eBPF proxy routines generation and Python callbacks (iovisor/bcc wrapper)
- pyexperiment - Run experiments with Python - quick and clean
- PyFuzz2 - My little fuzzing framework inspired by grinder
- pygal chart
- pygit: Just enough of a Git client to create a repo, commit, and push itself to GitHub
- py-googletrans - Free Unofficial Google Translate API for Python. Translates totally free of charge. http://py-googletrans.rtfd.org/en/latest/googletrans.html
- PyIDM: python open source alternative to IDM (Internet Download Manager) with multi-connections, high speed engine, based on python, pycurl, youtube_dl, and pysimplegui
- Pyjion - A Python JIT Compiler
- pyinotify
- pyjs is a Rich Internet Application (RIA) Development Platform for both Web and Desktop. With pyjs you can write your JavaScript-powered web applications entirely in Python
- Pykka - a Python implementation of the actor model
- pyldap
- pylearn2-practice
- Pylons
- PyNaver: naver open api for python
- PyMC: Bayesian Stochastic Modelling in Python http://pymc-devs.github.com/pymc
- Pymunk - a easy-to-use pythonic 2d physics library that can be used whenever you need 2d rigid body physics from Python
- pyo3 - Rust bindings for the Python interpreter
- pyOpenCL
- pyOpt - a Python-based package for formulating and solving nonlinear constrained optimization problems in an efficient, reusable and portable manner
- pyp - Easily run Python at the shell! Magical, but never mysterious
- pypapago 개발기
- pyparsing
- PyPatt: Python Pattern Matching
- PyPinkSign - Small python code for K-PKI certificates. 공인인증서를 다루는 파이선 코드
- PyPy.js - an experiment in building a fast and compliant python environment for the web
- pyrax Creating Cloud Servers using Python & Pyrax
- py-rubik_solver Makes a 3D representation of a rubiks cube and solves it step by step
- Pysa: Open Source static analysis for Python code - Facebook Engineering
- pyscale - Predicting Application Workload via Extreme Value Analysis
- pysftp a kind of wrapper of paramiko
- Pyston - an open source Python implementation that aims to be both highly compatible and high-performance
- PyStruct - Structured Learning in Python
- python-getdents: Python binding to linux syscall getdents64
- Python tools for Vivado Projects
- Python Wheels
- PyTongue - Write python in any language
- PyTree - a python package, which you can use to generate trees, realistic or fractal one. However the whole pricipale is based on fractals
- pyvim - Pure Python Vim clone
- Pyxley: Python Powered Dashboards
- PyV8 - a python wrapper for Google V8 engine
- QPython
- quack - Build system on top of build systems
- qutebrowser - a keyboard-focused browser with a minimal GUI based on Python and PyQt5 and free software, licensed under the GPL
- ReactPy
- readchar - Utilities to read single characters and key-strokes
- readability - fast python port of arc90's readability tool, updated to match latest readability.js!
- Remap: Nested Data Multitool for Python
- REMOVESTAR Tool to automatically replace 'import *' in Python files with explicit imports
- Requests - an elegant and simple HTTP library for Python, built for human beings
- practice - requests vs. http client speed
- practice - download file
- practice - authorization token
- practice - put & post
- api
timeout=(connect timeout, read timeout)
- 매우 큰 파일을 --data-binary로 보낼 때는 적절한 크기로 file을 나눠서 여러 번 호출하는 방법밖에 없는 거 같음
- mmap을 사용해서도 해보려고 했지만, mmap object를 그냥 넘겨주는 건 되도, mmap의 일부를 읽으면 str이 되거나 다시 file로 저장해야 하기 때문에 결국 다를 바 없음
- Line Notification with python
pip install --upgrade requests[security]- PYTHON: USING THE
REQUESTSMODULE TO DOWNLOAD LARGE FILES EFFICIENTLY - 네이버 실시간 급상승 크롤링
- 네이버 실시간 급상승 크롤링 02
- How I used Python to find interesting people to follow on Medium
- Requests' secret: pool_connections and pool_maxsize
- Python Requests Throttle
- The right way to use requests in parallel in Python
- Python parallel http requests using multiprocessing
- Make sessions safer in multi-process environment
- Requests hang multiprocessing
- Cory Benfield Requests Under The Hood PyCon 2017
- not so much about the requests library per se than about tradeoffs in programming, handling of exotic edge cases and an exercise in pragmatism
- Python Tutorial: Write a Script to Monitor a Website, Send Alert Emails, and Reboot Servers
- LINE Messaging API 사용해보기(2)
- 아이패드 PYTHONISTA 어플로 구글번역 EXTENSION 만들기
- Using My Python Skills To Punish Credit Card Scammers - YouTube
- asynchronous requests
- mureq: Single-file alternative to python-requests
- requests-file requests에서 file://... 로컬 URL 내용 가져오기
- requests-html: Pythonic HTML Parsing for Humans™
- requests-mock provides a building block to stub out the HTTP requests portions of your testing code
- SniRequests2 Sni 필드 차단당한 사이트에 정상적으로 웹 요청을 할 수 있도록 도와줍니다
- retroactive - Fun with time travel: Implementing retroactive data structures in Python http://python-retroactive-data-structures.readthedocs.org
- RIBOSOME - A simple generic code generation tool
- RiceDB – A simple, portable configuration file manager
- rlundo - interactive interpreters magical undo powers
- RPyC - Transparent, Symmetric Distributed Computing remote python call
- RPython
- Ryu component-based software defined networking framework http://osrg.github.io/ryu
- RxPy
- Sake - A self-documenting build automation tool
- schedule - Python job scheduling for humans
- schema - a library for validating Python data structures
- schwifty docs IBAN is the Internation Bank Account Number and BIC the Business Identifier Code. Both are used for international money transfer
- Scrapy
-
proxy 설정을 통해 해결 cf. scrapy-not-scraping-https@stackoverflow
localhost: ssh_exchange_identification: Connection closed by remote host scrapy tcp connection timed out 110 connection timed out scrapy scrapy.core.downloader.handlers.http11.TunnelError: Could not open CONNECT tunnel
-
- secure: Secure 🔒 headers for Python web frameworks
- secure.py — secure.py 0.3.0 documentation
- Shiny for Python
- ShinySDR - This is the software component of a software-defined radio receiver
- SimPy
- Introduction to Simulation with SimPy | by Darío Weitz | Towards Data Science
- Simulating Real-World Processes in Python With SimPy – Real Python
- Getting Started Simulating Real-World Processes in Python with SimPy - YouTube
- Lara Kattan - Simulations in Python: Discrete Event Simulation with SimPy | PyData NYC 2022 - YouTube
- SlopPy: An error-tolerant Python interpreter that facilitates sloppy programming
- Slouchy uses your webcam to check if you're slouching and alert you if you are
- Snake - Full Python Scripting in Vim
- Snakebite is a python library that provides a pure python HDFS client and a wrapper around Hadoops minicluster
- SnoPy - Snobol Pattern Matching Extension for Python
- sofi - an OS agnostic UI module for Python
- Sorted Containers sorted collections type
- sounddevice Day 44 : Voice Recorder in Python - YouTube
- spongebob-cli: Watch classic spongebob from the terminal!
- stackhut
- Supervisor: A Process Control System Supervisor is a client/server system that allows its users to monitor and control a number of processes on UNIX-like operating systems
- TabPy 다양한 태블로 차트 (14. TabPy 분석 확장 프로그램) :: 디포커스 태블로 tableau
- Talk Python To Me - A podcast on Python and related technologies
- tauthon - Fork of Python 2.7 with new syntax, builtins, and libraries backported from Python 3
- Template Engine
- TermFeed - Terminal Feed is a minimal feed reader for the terminal (without curses)
- terminal-palette - A simple library to color texts in terminal
- TextBlob -> nlp
- TAICHI: OPEN-SOURCE COMPUTER GRAPHICS LIBRARY
- Taichi Lang, parallel programming for everyone
- tomorrow - Magic decorator syntax for asynchronous code in Python
- tox
- Tesseract-OCR
- transcript - Python 3.6 to JavaScript compiler - Lean, fast, open! - http://www.transcrypt.org
- transducers-python
- transitions - A lightweight, object-oriented finite state machine implementation in Python with many extensions
- Twisted Introduction
- Twitter
- Twitter API tutorial
- rainbowstream - A Twitter client on terminal
- Retweet automatically retweets tweets from a Twitter user
- Writing a Console Twitter Client in Python
- Create A Twitter Bot With Python
- 트위터 언팔로워 트래커
- Build A Twitter Bot With Python That Gets You Followers
- Accessing the Twitter API with Python
- From Zero to a Working Twitter Bot in Python - All You Need to do in 6 Easy Steps - Learn Python with Rune
- Working with Text , Twitter and Databases with python - YouTube
- How to Access Twitter Data using Twitter API in Python | Twitter Data Analysis - YouTube
- Tweepy Documentation — tweepy 4.10.1 documentation
- TwoTerm - Simple side-by-side terminal program. PyQt4/PyQt5 based. Python2/Python3
- uBiome Open Source - A place for microbiome enthusiasts to share tools, tips, sequences, and more
- UltraDict: Shared, streaming Python dict
- usbkill: « usbkill » is an anti-forensic kill-switch that waits for a change on your USB ports and then immediately shuts down your computer
- uvicorn - The lightning-fast asyncio server, for Python 3. 🦄 http://www.uvicorn.org
- uvloop is a fast, drop-in replacement of the built-in asyncio event loop
- Uzi - an stunning Ransomeware due to its features
- validus - A dead simple Python data validation library. It supports Python 3 only
- vineyard in-memory immutable data manager that provides out-of-the-box high-level abstraction
- Visual Python GUI based Python code generator
- viztracer: VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution
- VPython
- vtcheck - Virus Total API Python Script
- Vy - A vim-like in python made from scratch
- vyper Pythonic Smart Contract Language for the EVM
- wakaq: Distributed background task queue for Python backed by Redis, a super minimal Celery
- Watchdog Python API library and shell utilities to monitor file system events
- Wavelet rasterization is a method for analytically calculating an anti-aliased rasterization of arbitrary polygons or shape bounded by Bezier curves
- wdb - An improbable web debugger through WebSockets
- websockets - a library for building WebSocket servers and clients in Python with a focus on correctness and simplicity
- Whoosh
- wrapt - A Python module for decorators, wrappers and monkey patching
- wttr.in - Web frontend for wego terminal에서 curl로 날씨 확인
- xarray - N-D labeled arrays and datasets in Python
- xincapio - Get IP address, MAC address and Disk Serial Number
- xs-vm - eXtremely small virtual machine written in Python
- yosai - A Security Framework for Python Applications
- YTFS - File system which enables you to search and play movies from YouTube as files - with tools of your choice
- Jean Baptiste Aviat Writing a C Python extension in 2017 PyCon 2017
- cffi
- Flexible runtime interface to shared libraries with libffi
- Python FFI with ctypes and cffi
- cffi-example: an example project showing how to use Python's CFFI
- Interfacing Python and C: The CFFI Module
- C로 파이썬 모듈 작성하는 법
- Caroline Arnold - Lessons learned from using the C Foreign Function Interface | PyData Global 2022 - YouTube
- configs/default.py src/lib/config.cc
- cython
- cython
- Speeding up non-vectorizable code with Cython
- Fast Python loops with Cython
- Easy wins with Cython: fast and multi-core by Caleb Hattingh
- CYTHON JOURNEY
- WRAPPING MAPLESIM C CODE FOR PYTHON
- Cython Tutorial - Bridging between Python and C/C++ for performance gains
- Cython: Speed up Python and NumPy, Pythonize C, C++, and Fortran, SciPy2013 Tutorial, Part 1 of 4
- Cython: Blend the Best of Python and C++ | SciPy 2015 Tutorial | Kurt Smith
- Pycon 2016: Fast Python! Don't Bother?
- Parallel Python – Making Code Run 2000x Faster
- Alex Orlov Cython as a Game Changer for Efficiency PyCon 2017
- Achieving C-like performance in Python without Cython or other libraries?
- Protecting Python Sources With Cython
- Boosting Python Scripts With Cython
- Make Your Python Code Dramatically Faster With Cython | by Halil Yıldırım | Better Programming | Medium
- runcython - Making cython as easy as python
- Pupy is an opensource, cross-platform (Windows, Linux, OSX, Android) remote administration and post-exploitation tool mainly written in python
- pybind11 - a lightweight header-only library that exposes C++ types in Python and vice versa, mainly to create Python bindings of existing C++ code
- Pythran
- ShivyC - C compiler created in Python
- cache 데코레이터로 최적화하기 functools.lru_cache functools.cache
- Caching in Python: the LRU algorithm - Analytics Vidhya
- cachetools - Extensible memoizing collections and decorators
- functools.lru_cache
- methodtools.lru_cache functools.lru_cache가 classmethod나 staticmethod에 대해 제대로 동작하지 않아 이를 보완하기 위해 작성했다고 함
- Ring - Cache interface as a programming language integration
- supycache - Simple yet capable caching decorator for python
- Quick & Simple Call Graphs in Python
- Callgraph - a Python package that defines a decorator, and Jupyter magic, to draw dynamic call graphs of Python function calls
- Call Map: A Tool for Navigating Call Graphs in Python
- Code2graph: Automatic Generation of Static Call-Graphs for Python Source Code
- Pyan3: Offline call graph generator for Python 3
- pycallgraph - call graph visualizations for Python applications
pycallgraph [--max-depth=n] [--include "path.to.\*"] graphviz -- <python src>
- Luigi - Batch data processing in Python
- Managing Containerized Data Pipeline Dependencies With Luigi
- Luigi 예제
- Jonathan Dinu: Scalable Pipelines with Luigi or: I’ll have the Data Engineering, hold the Java!
- Intro to Building Data Pipelines in Python with Luigi
- Luigi, The Friendly Pipeline Plumber by IanMLewis
- Using Luigi Pipelines in a Data Science Workflow
- Luigi workflow engine을 사용하여 기계 학습 파이프 라인을 작성하는 데 필요한 예제 코드 포함
- 예제의 주요 기능은 Apache MADlib (incubating)
- Luigi 태스크의 PL/pgSQL을 통해 실행
- Data pipelines, Luigi, Airflow: everything you need to know
- Create your first ETL in Luigi
- Daan de Bruin - Fighting COVID with Python | PyData Eindhoven 2021 - YouTube
- Prefect - The New Standard in Dataflow Automation - Prefect Workflow Management System e.g. Luigi, Airflow
- Snakemake
- free.codebashing.com/courses/python/lessons/sql_injection 파이썬으로 대화형 sql injection test
- Write an SQL query builder in 150 lines of Python! - death and gravity
- python, db library benchmark (feat. sqlalchemy vs aiomysql)
- Ajgu - a simple graph database power by BerkleyDB key-value store
- connector-x: Fastest library to load data from DB to DataFrames in Rust and Python
- LanderDB - An embedded database engine written in Python
- marshmallow: simplified object serialization
- MySQL-python
- practice - installation on Redhat & Ubuntu
- practice - installation on macos sierra
- Escaping Strings for MySQL in Python 난 잘 되지 않음
- A quick guide to using MySQL in Python
- Python MySQL Tutorial
- Unofficial Windows Binaries for Python Extension Packages
- Insert / Retrieve file and images as a Blob in MySQL using Python
- Python & MySQL Crash Course - YouTube
- PewSQL - Analytics Done inside RDBMS
- PyMySQL
- PYODBC
- How to Use PYODBC With SQL Servers in Python
- pyodbc 라이브러리를 사용하여 SQL Server, Access 데이터베이스 및 Excel 통합 문서에 연결하는 것과 데이터를 데이터베이스에 삽입하는 방법
- Building a Regression Testing Framework for your SQL Database
- How to Use PYODBC With SQL Servers in Python
- PyPika - a python SQL query builder that exposes the full richness of the SQL language using a syntax that reflects the resulting query. PyPika excels at all sorts of SQL queries but is especially useful for data analysis
- RasgoQL: Write python locally, execute SQL in your data warehouse
- SQLAlchemy
- 10 Reasons to love SQLAlchemy
- SQLAlchemy 1.1 - index_property
- Python에서 SQLAlchemy로 MS-SQL 연동하기
- SQLAlchemy의 연결 풀링 이해하기
- Pythonic Database Management with SQLAlchemy
- Basics of SQL in Python for Data Scientists | by Nick Minaie, PhD | Towards Data Science
- How to Create Joins in SQLAlchemy - YouTube
- book-rental-service/models.py at master · RavenKyu/book-rental-service
- Migrating to SQLAlchemy 2.0 — SQLAlchemy 1.4 Documentation
- SQLAlchemy add, flush, commit
- SQLAlchemy와 cryptography로 민감한 데이터 암호화하기 – Linewalks Blog
- The next generation SQLAlchemy with asyncio. 김준기 - PyCon Korea 2021 - YouTube
- 파이썬 개발자를 위한 SQLAlchemy
- Hide :: SQLAlchemy AsyncSession으로 비동기 적용하기
- Hide :: SQLAlchemy AsyncSession으로 비동기 적용하며 생긴 문제점
- FastAPI에서 SQLAlchemy Session 다루는 방법 | by YoungSik Choo | 원티드 제품 팀블로그 | Mar, 2022 | Medium
- How to Use Async SQLAlchemy in FastAPI - YouTube
- Session vs scoped_session :: Jay's Code Factory
- async_scoped_session과 context-local :: Jay's Code Factory
- sqlalchemy nullpool과 staticpool을 설정하면서 왜 커넥션 풀이 필요한지 이해해 봅시다.
- 업데이트에서 배우는것 — SQLAlchemy 2.0. 저는 업데이트를 좋아합니다. 프로젝트에서 사용하는 라이브러리의 새… | by Choi Geonu | Jun, 2023 | Medium
- Alembic - a lightweight database migration tool for usage with the SQLAlchemy Database Toolkit for Python
- sqlbuilder
- sqlbuilder.readthedocs.io
- practice - sqlbuilder 간단히 test해봤는데 python에서 호출할 query를 만드는 데는 확실히 유용할 거 같음
- tortoise-orm: Familiar asyncio ORM for python, built with relations in mind
- Dependency Injection in Python: The Java Guy’s Perspective - Dependency Injection (DI) in Python? Seriously?
- Autowire - light & simple dependency injection library for Python
- Dependency Injector — Dependency injection framework for Python — Dependency Injector 4.35.2 documentation
- Best Python IDEs and Code Editors You Must Use in 2020
- A Python IDE meant for learning programming
- Top 5 open source Python IDEs | Opensource.com
- BeeWare - The IDEs of Python
- Eric - a full featured Python editor and IDE, written in Python
- PyCharm
- practice - 별도 설치한 python으로 설정하기
- Pycharm 원격 빌드 설정하기
- Mac에서 PyCharm Docker를 원격 연결하기
- PyCharm Professional 버전에서 Docker로 Remote Debugging
- PyCharm + Docker로 파이썬 개발환경 셋업하기 (Dockerization)
- 파이참 원격 디버깅
- 파이참(pycharm)에서 pep8 가이드 검사하기
- Python에도 스타일이 있다
- PyCharm에서 PEP8 맞추기
- settings.jar 개발환경 공유
- bookmarks 북마크
- 화면 모드
- Pylinting with PyCharm
- 2017.1 iPython 설치 후 디버깅 콘솔에서 KeyError 발생 시
- PyCharm에서 임의의 코드를 디버깅하는 방법
- How to use PyCharm to debug your Python code
- Korean translation of PyCharm IDE
- PyCharm에서 matplotlib.animation이 작동하지 않을 때
- PyCharm에서 multiarray numpy 확장 모듈 임포트 실패할 때
- Configuring Jupyter Notebook
- 파이참, 파이썬 강좌가 필요없는 튜토리얼 활용법!
- 상대경로와 PyCharm 그리고 명령행
- 파이참 interpreter 설정하기
- Pycharm에서 anaconda의 python.exe를 base interpreter로 사용하려면?
- PyCharm에서 테스트 중 AssertionError발생시점의 Breakpoint설정
- Pycharm Python Console에서 한글깨짐 해결방법
- PyCharm vs VSCode. Is it time to change your IDE? | by S Ahmad | Towards Data Science
- Getting Started with PyCharm for Python Anaconda Plugin - YouTube
- PyCharm Tutorial | Full Course 2021 - YouTube
- Jupyter notebook support - Help | PyCharm
- Photonai 21 Techniques to Write Better Code | by Bruce H. Cottman, Ph.D. | The Startup | Medium
- PyScripter An Introduction to PyScripter — The Best Free Python IDE | by Sohom Das | Jan, 2022 | Python in Plain English
- Spyder IDE
- Thonny - Python IDE for beginners
- 10 Python image manipulation tools
- Image Text Recognition in Python
- Ravi Chityala, "Image processing using Python", PyBay2016
- Create ASCII Art Text Banners in Python
- CNN-Image-Processing - Python module for image processing using cellular neural networks (CNN)
- EyeLipCropper : a Python tool to crop eyes and mouth ROIs of the given video
- gallery-dl: Command-line program to download image-galleries and -collections from several image hosting sites
- gif2txt - Gif image to to Ascii Text. (Just a toy)
- img2txt - Image to Ascii Text, can output to html or ansi terminal
- imgaug - Image augmentation for machine learning experiments. http://imgaug.readthedocs.io
- Legofy - a python program that takes a static image or gif and makes it so that it looks as if it was built out of LEGO
- maryjane - MaryJane MJPEG server in < 30 lines Python
- PIL
- Pillow, the friendly PIL fork
- Python Pillow (PIL) examples
- Grabs the dominant color or a representative color palette from an image. Uses Python and Pillow. http://lokeshdhakar.com/projects/color-thief
- The fastest production-ready image resize out there, part 0
- Processing Images in Python With Pillow | Real Python Podcast #45 - YouTube
- Image processing in Python using Pillow - LogRocket Blog
- WebRemoteDesktop pyautogui
- PyCNN - Image Processing in Cellular Neural Networks with Python
- SIPSkia : Simple Image Processing by Skia
- '오류 줄이고 보기도 좋은' 파이썬 코드 정리 툴 5가지 - ITWorld Korea pycodestyle, autopep8, flake8, pylint, black
- Lint All the Things! - presented by Luke Lee - YouTube
- [flake8 - a python tool that glues together pep8, pyflakes, mccabe, and third-party plugins to check the style and quality of some python code]((https://gitlab.com/pycqa/flake8)
- Pylint - Star your Python code!
- Ruff An extremely fast Python linter, written in Rust
- Adaptive process and memory management for Python web servers
- Diagnosing Memory "Leaks" in Python
- How to recover lost Python source code if it's still resident in-memory
- 파이썬이 메모리를 관리하는 방법 | seonghyeon.dev 내부 메모리 관리 설명, pymalloc
- Memspector - Inspect memory usage of python functions
- psutil documentation — cross-platform library for retrieving information on running processes and system utilization (CPU, memory, disks, network, sensors) in Pytho
- PyDataSentry - Memory for Data Science
- My Python Development Environment, 2020 Edition
- Overview of python dependency management tools
- State-of-the-art python project setup - Towards Data Science
- 파이썬 패키징, 배포 툴의 과거와 현재 · 개발블로그
- Michał Wodyński - Difficulties of Python code development:packages,virtualenvs and package mangers - YouTube
- Wei Lee - Python Table Manners: Cut the Cookie Gracefully - YouTube
- Our Python Monorepo. At Opendoor we started putting all our… | by Dan Hipschman | Open House | Medium
- Python Monorepos: What, Why and How - YouTube Pants, Bazel, Buck
- Publishing Well Formed Python Packages - Julin Shaji - PyCon Korea 2020 - YouTube
- Virtual Environments Demystified | Lukas Waymann 임의로 가상 환경 구성
- How to make an awesome Python package in 2021 | Anton Zhiyanov
- 나의 파이썬 환경 구축기 1 - 써본 것들에 대한 생각 pyenv poetry
- 나의 파이썬 환경 구축기 2 - pyenv + poetry pyenv poetry
- 패키지 관리와 파이썬 버전관리를 위한 poetry, pyenv
- 파이썬 패키징 – 과거, 현재, 미래 – 야단법썬과 함께하는 블로그
- How to Package Python Projects in 2021 - ActiveState
- Which Python Dependency Manager Should I Choose? - ActiveState
- 파이썬 패키징의 과거, 현재, 그리고 미래 - Morgenrøde
- Abandon requirements.txt for managing dependencies in Python immediately | by Vitor Ramalho | Medium
- Python is Actually Portable
- Convert PY to EXE Automatically - YouTube
- Packaging Python in 2022 - presented by Jeremiah Paige - YouTube
- Packaging Python in 2022 - YouTube
- ezpypi: Very simple and easy to use pip on any os
- Flit
- pex - a library for generating .pex (Python EXecutable) files which are executable Python environments in the spirit of virtualenvs
- pip
-
apt-get install -y python-dev python-pipfatal error: Python.h: No such file or directoryyum install epel-release -y && yum install python-pip -y && yum install python-devel -yHow to install python-pip in CentOS7 Docker Container
-
"pip -t": A simple and transparent alternative to virtualenv
-
pip --index-url/--trusted-host옵션 자동 지정$ cat requirements.txt --index-url http://my.pypi.internal/index --trusted-host my.pypi.internal myteam.common==0.0.1 ... -
pip 설치 SSLError 오류 해결 방법: SSLCertVerificationError SSL: CERTIFICATE_VERIFY_FAILED
-
How to Create Python Packages for Sharing Code and Installing with pip - YouTube
-
- pipx - Install and Run Python Applications in Isolated Environments
- pypc The Python3 Package Creator
- Python: beyond the basics I - pip, virtualenv, pipenv & list comprehensions
- pipenv
- pipreqs - Generate pip requirements.txt file based on imports of any project
- pipwin
pip install pipwin& e.g.pipwin install opencv-python- www.lfd.uci.edu/~gohlke/pythonlibs에 올려져있는 윈도우용 whl 파일을 pip 와 비슷하게 설치
- Poetry - Python dependency management and packaging made easy. https://poetry.eustace.io
- 파이썬 의존성 관리자 Poetry 사용기
- GitHub Action과 Poetry를 사용한 파이썬 패키지 개발
- 포에트리를 사용한 파이썬 프로젝트 관리 방법
- Hypermodern Python pyenv, click, requests
- A hygienic Python setup for Linux, Mac, and WSL | by Ben Kehoe | Sep, 2020 | A Cloud Guru
- Hello Poetry (Dependency Management for Python)
- Poetry를 사용한 파이썬 패키지 관리
- Document docker poetry best practices · Discussion #1879 · python-poetry/poetry
- setup.py 멈춰!
- poetry 로 파이썬 패키지 관리하기 | woolog - 개발자 울이
- How to Create and Use Virtual Environments in Python With Poetry - YouTube
- py2app - Create standalone Mac OS X applications with Python
- pyenv
- pyenv Tutorial
- 맥에서의 파이썬 개발 환경 자동화(pyenv, virtualenv, autoenv)
- pyenv, virtualenv, autoenv 를 사용하여 Python 개발환경 구축하기
- pyenv, virtualenv, autoenv를 활용한 자동화 구현하기
- pyenv + virtualenv + autoenv 를 통한 Python 개발 환경 구축하기
- PYTHON: PYENV, PYVENV, VIRTUALENV – WHAT’S THE DIFFERENCE?
- pyenv, conda, virtualenv, pip, autoenv
Pyenv 와 Virtualenv 를 이용한 Python 패키지 및 버전 의존성문제 해결- pyenv와 virtualenv를 사용한 파이썬 개발환경 구성
- Python 실전 개발 생태계 pyenv, docker
- Pyenv 삽질기… 파이썬 버전관리와 가상환경 구축하는 방법 | by Jake Lee | Jul, 2021 | Medium
- Managing Python versions with pyenv | The Python Corner
- 개발 런타임 환경 구축하기 - 파이썬 pyenv편 | 요즘IT
- PyInstaller is a program that freezes (packages) Python programs into stand-alone executables, under Windows, Linux, Mac OS X, FreeBSD, Solaris and AIX
- PyOxidizer
- State Tool CLI :: ActiveState Platform Documentation
- subpar: Subpar is a utility for creating self-contained python executables. It is designed to work well with Bazel
- virtualenv
- practice - use virtualenv in shell script
- How To Setup Python Virtualenv on Ubuntu 15.04
- 독립적인 가상의 파이썬 실행환경, virtualenv (1)
- 독립적인 가상의 파이썬 실행환경, virtualenv (2)
- pip와 virtualenv를 이용한 파이썬 디플로이먼트
- python virtual environment setup in ubuntu
- 개발환경 구축하기
- 파이썬 프로젝트 시작하기 - Virtualenv
- Connect virtualenv
- 파이썬의 개발 “환경”(env) 도구들
- Python 개발환경 구성
- 파이썬의 실행 환경을 지탱하는 도구들
- dh-virtualenv - a tool that aims to combine Debian packaging with self-contained virtualenv based Python deployments
- Virtualenv 설치 및 dependencies 관리하기
- Python Virtual(Isolated) Environments
- 파이썬 가상환경(virtualenv)만들기
- Python Virtual Environments made easy
- Comparing Python Virtual Environment tools
- Virtual Environments in Python Made Easy
- The Python Package Dreamteam
- Python Virtualenv with Hadoop Streaming
- 가상환경 virtualenv(1)
- 가상환경 virtualenv(2) - 실행/설치/관리
- 가상환경 virtualenv(3) - 설치 패키지 사용하기
- How to use Python virtualenv
- Python virtualenv 정리 (Linux/Windows) :: 개발새발로그
- Advice and Tips to Properly Work with Virtual Environments | by François St-Amant | Towards Data Science
- Virtual Environments — Setup and Importance in Python | by Robbie Prior | Jul, 2021 | Towards Data Science
- 윈도우의 powershell에서 가상환경이 활성화 안되는 이유
- virtualenvwrapper
- High Performance Python - YouTube coiled, numba, dask, rapids
- Parallel Processing in Python || Aaron Richter - YouTube
- Anyscale - Parallelizing Python Code
- Daft: The Distributed Python Dataframe — getdaft.io documentation
- Dask Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love
- Out-of-Core Dataframes in Python: Dask and OpenStreetMap
- Analyzing Reddit Comments with Dask and Castra
- Xray + Dask
- matthewrocklin.com/blog
- How to Run Parallel Data Analysis in Python using Dask Dataframes
- Dask Version 1.0
- Scaling PyData with Dask - Martin Durant and Jim Crist
- Matthew Rocklin - Dask at Global Scale with Coiled | PyData Eindhoven 2020 - YouTube
- Dask for Everyone - Hugo Bowne-Anderson | PyData Global 2021 - YouTube
- Dask: From POC to Production - April Rathe | PyData Global 2021 - YouTube
- Scale EDA & ML Workloads To Clusters & Back With Dask I PyData Chicago January 2022 Meetup - YouTube
- Introduction to Dask: Scaling EDA & ML Workloads - YouTube
- PyData Triangle March 2022 Meetup - YouTube
- Scaling Python - Bank Edition | PyData NYC 2022 - YouTube pyGPU-CUDA, prefect, argo
- Martin Durant - Single node shared memory comes to dask | PyData Global 2022 - YouTube
- Coiled: Scaling Python Simply
- dask-sql: Query Your (Big) Data With The Power of Python & SQL - Nils Braun - YouTube
- s3fs Using S3 Just Like a Local File System in Python | by Sven Balnojan | The Startup | Medium
- exax.org | exax.org
- Parsl: Parallel Scripting in Python
- PyParallel.org
- Ray Welcome to the Ray documentation — Ray 2.3.0
- ray - A system for parallel and distributed Python that unifies the ML ecosystem
- Modern Parallel and Distributed Python: A Quick Tutorial on Ray
- 10x Faster Parallel Python Without Python Multiprocessing
- How I built a GPU Deep Learning Cluster with ray — And why I would do it again
- Ray 아키텍쳐 백서 (번역)
- Python Ray 사용법 - Python 병렬처리, 분산처리 · 어쩐지 오늘은
- Ray 로 내 파이썬 코드 10배 빠르게 만들기. Ray 를 이용한 python 병렬처리 방법에 대해 알아봅니다. | by t.k.woo | Naver Shopping dev | Jan, 2021 | Medium
- Retrieval Augmented Generation with Huggingface Transformers and Ray | Distributed Computing with Ray
- Getting Started with Distributed Machine Learning with PyTorch and Ray | by PyTorch | PyTorch | Feb, 2021 | Medium
- Anyscale - Parallelizing Python Code
- Ray 아키텍쳐 백서 (번역)
- Ray AI Runtime (AIR) — Ray 2.3.0
- Generate PDF with Python - Reportlab
- Day 25 : Extract Text from PDF with Python - YouTube
- Google-Search-PDF-Crawler-pdf2txt-
- horrifying-pdf-experiments: Stuff which works in Chrome and maybe Acrobat and Foxit
- invoice2data - Data extractor for PDF invoices
- ptext-release: pText is a library for reading, creating and manipulating PDF files in python
- pystitcher: pystitcher stitches your PDF files together, generating nice customizable bookmarks for you using a declarative markdown file as input
- Python Progress Bars in 9 minutes - YouTube tqdm, alive-bar
- mdk.fr – How APT does its fancy progress bar
- alive-progress: A new kind of Progress Bar, with real time throughput, eta and very cool animations!
- progress: Easy to use progress bars for Python
- python-progressbar: Progressbar 2 - A progress bar for Python 2 and Python 3 - "pip install progressbar2"
- tqdm A Fast, Extensible Progress Meter (progress bar)
- Python | Create a QR Code with your data using Python (5 lines of code) - YouTube
- Code and Decode QR in Python - YouTube
- PyKIPass: 📱사장님들을 위한 QR체크인, 전자출입명부, KIPass API 파이썬 라이브러리
- pyzbar 파이썬 Python 코딩 - 바코드 QR코드 리더기 만들기 Scanning Bar Code Qr Code - Opencv, Pyzbar with Python - YouTube
- 플랫폼 리팩터링 경험 공유. Code Complexity 줄이기 with Python | by David K. Kim | 네이버 플레이스 개발 블로그 | Aug, 2022 | Medium
- Brett Slatkin - Refactoring Python: Why and how to restructure your code - PyCon 2016
- Tech Debt and Refactoring at Yelp! with Andrew Mason – Episode 110
- Bowler: Safe code refactoring for modern Python
- Sourcery | Automatically Improve Python Code Quality Instant Python refactoring
- Undebt is a fast, straigPygmentshtforward, reliable tool for performing massive, automated code refactoring used @Yelp
- jurigged: Hot reloading for Python
- reloadium: Advanced hot reloading & profiling for Python
- reloadr: Hot code reloading tool for Python
- Jellyfish - a python library for doing approximate and phonetic matching of strings
- pyahocorasick - a fast and memory efficient library for exact or approximate multi-pattern string search
- rapidfuzz - Rapid fuzzy string matching in Python and C++ using the Levenshtein Distance
- textsearch - Find strings/words in text; convenience and C speed
- Magic Python - a package with preferences and syntax highlighter for cutting edge Python 3, although Python 2 is well supported, too
- Pygments Welcome! — Pygments
- Building Beautiful Command Line Interfaces with Python | by Oyetoke Tobi Emmanuel | codeburst
- curses
- npyscreen
- picotui - Lightweight, pure-Python Text User Interface (TUI) widget toolkit with minimal dependencies. Dedicated to the Pycopy project. https://github.com/pfalcon/pycopy
- PyInquirer - A Python module for common interactive command line user interfaces
- Urwid - Console user interface library for Python
- xonsh shell a Python-powered, cross-platform, Unix-gazing shell language and command prompt
- Scaling Python Microservices with Kubernetes
- BUILDING MICROSERVICES WITH PYTHON AND FLASK
- Miguel Grinberg - Microservices with Python and Flask - PyCon 2017
- Python in Serverless Architectures
- Building a Microservice in Python | by Sonu Sharma | Medium
- 모놀리식에서 MSA로 가는 여정, 조민우 - PyCon Korea 2022 - YouTube
- Armada is a complete solution for development, deployment, configuration and discovery of microservices
- Chalice Python Serverless Microframework for AWS
- Python Serverless Microframework, Chalice 사용하기, 01
- Python Serverless Microframework, Chalice 사용하기, 02
- Python Serverless Microframework, Chalice 사용하기, 03
- Python Serverless Microframework, Chalice 사용하기, 04
- Python Serverless Microframework, Chalice 사용하기, 05
- Python Serverless Microframework, Chalice 사용하기, 06
- Python Serverless Microframework, Chalice 사용하기, 07
- Python Serverless Microframework, Chalice 사용하기, 08
- Nirum: IDL compiler and RPC/distributed object framework for microservices http://nirum.org
- opyrator: 🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more
- Somata - a protocol and framework for building software on a network of connected microservices
- 파이썬 데이터 사이언스 Cheat Sheet: NumPy 기본
- あなたのデータサイエンス力を 飛躍的に向上させるNumPy徹底入門
- Python Basics for Data Science
- Python Numpy Tutorial
- Python Numpy Tutorial
- NUMPY TUTORIAL : STEP BY STEP GUIDE
- cs228-python-tutorial.ipynb
- NumPy Tutorial: Data analysis with Python
- What is Numpy in Python - Everything you Need to Know About
- 100 numpy exercises
- 100 numpy exercises (100% complete)
- NumPy Exercises
- NumPy Cheat Sheet: Data Analysis in Python
- github.com/zerosum99/python_numpy
- How to pip install NumPy in two seconds flat
- Peak detection in the Python world
- 파이썬 + Numpy + 선형대수 기초 + 이해하기 20160519
- Chapter 4. Numpy 기본 : 배열과 벡터 계산
- Python numpy 기초 - 선형대수학 풀어보기
- Python numpy pandas matplotlib 이해하기 20160815
- TF-KR 첫 모임: Zen of NumPy
- numpy
- 파이썬에 numpy 설치하기 For Windows
- Numpy
- GT-Py: Accelerating NumPy Programs with Minimal Programming Effort
- Practical Tutorial on Data Manipulation with Numpy and Pandas in Python
- Data Analysis with Python
- 머신러닝을 위한 기초 수학 살펴보기
- numpy 맛보기
- Why you should start using .npy file more often…
- 파이썬으로 데이터 분석하기 #4-1
- NumPy와 C++ Extensions의 성능 비교
- NumPy와 C++ Extensions의 성능 비교
- NumPy Python Tutorial 2018
- python1010 azure notebooks
- PyData Tel Aviv Meetup: Creating Meaningful Features from Clickstream Data - Shir Meir Lador
- numpy tutorial
- Numpy — Python made efficient
- A Visual Intro to NumPy and Data Representation
- Python NumPy Tutorial for Beginners
- Numpy: What Has Changed and What Is Going To Change?
- Data Engineering with Python Numpy & Pandas
- Pythonic Data Cleaning With Pandas and NumPy
- 파이썬(python) numpy 의 array(ndarray)와 matrix 데이터 타입
- Matrix Subtraction Explained (with Python Examples) - Linear Algebra
- NumPy Tutorial 2020 - YouTube
- Python NumPy Tutorial | NumPy Array | Python Tutorial For Beginners | Python Training | Simplilearn - YouTube
- Python Numpy. Overview & Getting started | by Keno Leon | Medium
- NumPy Illustrated: The Visual Guide to NumPy | by Lev Maximov | Better Programming | Dec, 2020 | Medium
- Random Number Generator Tutorial with Python | Towards AI
- Illustrating Gershgorin disks with NumPy
- NumPy — Why is it so fast?
- numpy 인덱싱 성능은 어떨까요?
- NumPy for Data Science Interviews | by Nathan Rosidi | Jan, 2022 | Towards Data Science
- My Favorite Free NumPy Courses for Beginners - DZone Web Dev
- Why Datetimes Need Units - Christopher Ariza | PyData Global 2021 - YouTube Y2262 problem, datetime64 datatype
- Python Numpy and Jupyter Tutorials - YouTube
- 넘파이 튜토리얼 - YouTube
- Learn NumPy In 2(Two Hrs)H | NumPy Tutorial | NumPy For Data Science & Data Analysis| Python-NumPy | - YouTube
- Fundamentals of Numpy | Apply Neural Network Fundamentals - YouTube
- Pseudo Lab - Data Science Cheatsheet
- NumPy의 axis 변경
- Awkward Array documentation — Awkward Array 2.0.9 documentation
- Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems
- dmatrix2np: Convert XGBoost's DMatrix format to np.array
- einsum
- F2PY user guide and reference manual — NumPy v1.22 Manual
- JAX reference documentation — JAX documentation
- Mars Alibaba Open-Sources Mars to Complement NumPy
- Numexpr - a fast numerical expression evaluator for NumPy
- numpy-financial
- How to Use the Future Value Function in Python NumPy Financial - YouTube
- How to Use NPV & IRR in NumPy Financial for Python | Net Present Value & Internal Rate of Return - YouTube
- How to Use NumPy Financial for Python Present Value (pv) Function - YouTube
- Calculate Loan Payments with Python NumPy Financial - YouTube
- Python Automation Project: Make a Mortgage Loan Analyzer Class - YouTube
- Python Automation Project: Mortgage Loan Analysis Application Part II - YouTube
- tinynumpy - A lightweight, pure Python, numpy compliant ndarray class
- Zarr-Python — zarr 2.14.1 documentation
- pandas - Python Data Analysis Library
- pandas documentation — pandas 1.3.1 documentation
- 파이썬의 대표적인 데이터 분석도구 판다스 공식 문서 활용하기 - YouTube
- practice
- read excel
data.iloc[:,0:8].values.tolist()행은 모두 사용하고, 열은 [0,8]만 추출해서 리스트로 변환data = pd.read_csv("pima-indians-diabetes.csv", encoding = 'euc-kr', [header=None])header=None 첫 번째 행을 헤더가 아니라 데이터로 간주- Visualization of pd.DataFrame as a Markdown format
- troubleshooting
pd.read_csv('filename', error_bad_lines=False)Python Pandas Error tokenizing datapandas.parser.CParserError: Error tokenizing data. C error: Buffer overflow caught - possible malformed input file.read_csv C-engine CParserError: Error tokenizing data 제대로 해결되지 않는 경우가 있음
- Pandas Profiling
- 판다스 기초
- Pandas 팬더스 강의 기초 실습
- 10 Minutes to pandas
- Python Pandas Basics. With Pandas ? | by Keno Leon | Medium
- Pandas Archives - SETScholars: Coding and Math Resources
- Data analysis in Python with pandas
- Pandas Cheat Sheet: Data Wrangling in Python
- Data Wrangling with pandas Cheat Sheet
- github.com/zerosum99/python_pandas
- pandas.pivot_table
- Data Munging with Pandas - John Fries, CTO, OpenMail
- Ultimate guide for Data Exploration in Python using NumPy, Matplotlib and Pandas
- Working with Text Data in Pandas - YouTube
- Pandas writing dataframe to CSV file
- Improving Pandas’s Excel Output
- Updated: Using Pandas To Create an Excel Diff
- 3 Excel Functions and How to Do Them in Python!
- Reading Poorly Structured Excel Files with Pandas - Practical Business Python
- IO Tools (Text, CSV, HDF5, ...)
- Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
- Python Pandas Tutorial | Pandas For Data Analysis | Python Pandas | Python Tutorial | Simplilearn
- pandas .head() to .tail() (Beginner) | SciPy 2018 Tutorial | Niederhut, Augspurger, Van den Bossche
- Pandas Tutorial (Data Analysis In Python)
- Python Pandas Tutorial | What is Pandas | Features of Pandas # 1 - YouTube
- Python Pandas Tutorial : Series and DataFrame Basics #2 - YouTube
- Introduction to pandas Library (Python Tutorial & Examples) | Learn Basics
- Pandas tutorial time series - YouTube
- Pandas Ultimate Tutorial 2023 | Python Data Analysis - YouTube
- 엑셀 자동화 - 사무직을 위한 파이썬 excel xlwings
- Bringing the python data stack to the shell prompt
- Discovery Engines: Statistical Learning with Python and pandas
- Efficient Tabular Storage
- Pandas Categoricals
- Adding a Simple GUI to Your Pandas Script
- 스타워즈 TATOOINE행성의 비밀
- Pandas 기초 이해하기 20160422
- Pandas 이해하기 20160423
- Pandas series 이해하기 20160425
- Pandas data frame 이해하기 20160425
- Pandas data frame 이해하기 2편 20160501
- GroupBy-fu: improvements in grouping and aggregating data in pandas
- Comprehensive Guide to Grouping and Aggregating with Pandas - Practical Business Python
- Q . Pandas GroupBy의 대괄호 & 소괄호는 어떻게 구분해서 사용하나요? - YouTube
- Pandas Groupby Warning - Practical Business Python
- An Introduction to scientific python: Pandas
- Data Analysis with Python and Pandas
- Data Analysis w/ Python 3 and Pandas
- 네이버 파이낸스 - 재무제표 크롤링
- (Daum부동산) DataFrame 행 추출과 컬럼으로 합치기
- Python & JSON: Working with large datasets using Pandas
- pandas.pydata.org/pandas-docs/stable/10min.html
- Quick Tip: The easiest way to grab data out of a web page in Python
- Graphing bike path data with IPython Notebook and pandas
- 김영근 - pandas contribution 하기
- Pycon2017 이성용 Dances with the Last Samurai django + pandas + python-docx 를 이용한 통계업무도구 만들기
- 파이썬에서 주가데이터 읽어오기
- Open Machine Learning Course. Topic 1. Exploratory data analysis with Pandas
- The Pandas DataFrame – loading, editing, and viewing data in Python
- Quick dive into Pandas for Data Science
- Selecting Subsets of Data in Pandas
- pandas column 의 위아래 값의 차이를 비교해보자
- pandas 시간정보로 .srt 자막을 만들어보자
- Pandas: 한 셀의 데이터를 여러 행으로 나누기
- Pandas: 그룹 내에서 상위 n개 가져오기
- 23 great Pandas codes for Data Scientists
- Tidying Up Pandas
- How to build your data science muscle memory: Slicing and Mapping Data for Machine Learning
- Minimally Sufficient Pandas
- Cleaning and Tidying Data in Pandas - Daniel Chen
- Using The Pandas Category Data Type
- Pandas 10분 완성
- Pandas 기초 - cheat sheet 따라하기
- Pandas 핵심 명령어 Cheat Sheet
- 10 Python Pandas tricks that make your work more efficient
- 파이썬 판다스 데이터프레임 apply함수 사용 - 특정 조건(if)의 값 바꾸기!
- Pandas - 연비 TEST Data 분석 1
- Pandas - Gapminder Data 분석(그래프 분석) 3
- Pandas - 1880 ~ 2010 년까지 출생 자료 분석 - 남/여 출생 수
- Pandas - Json Data 분석 4(Data 시각화)
- Pandas - 영화 진흥원 API 상영 순위 분석
- Best practices with pandas
- SQL과 파이썬 pandas의 비교
- My top 25 pandas tricks
- 판다스 코드 속도 최적화를 위한 초보자 안내서
- PyData Tel Aviv Meetup: Getting to Know any Dataset in 4 Lines of Python - Eyal Trabelsi
pandas_profiling,pivottablejs,pydqc.data_compare - One-stop Guide to Data Manipulation in Python 여러가지 pandas 사용법 예제
- Learn a new pandas trick every day!
- 편리한 판다스 무조건 좋을까?
- Why and How to Use Pandas with Large Data
- Binning Data with Pandas qcut and cut
- Cleaning Up Currency Data with Pandas
- 상관관계 분석(Pandas) & Heatmap 그리기
- Tips for Selecting Columns in a DataFrame
- Finding Natural Breaks in Data with the Fisher-Jenks Algorithm
- Data Preparation Basic(데이터 전처리 기초) 1
- Data Preparation Basic(데이터 전처리 기초) 2
- Data Preparation Basic(데이터 전처리 기초) 3
- Efficient Pandas: Using Chunksize for Large Data Sets
- 파이썬으로 로또 당첨번호 및 당첨금 데이터 분석 하기 feat.pandas, pyplot
- Python Tools for Record Linking and Fuzzy Matching fuzzymatcher, recordlinkage
- 파이썬과 판다스로 배우는 통계 기초
- 판다스 튜토리얼 - 10분안에 못 끝내는 분량 10분안에 끝내기
- Tidy Animated Verbs
- How to Export Pandas DataFrame to CSV
- Data Cleaning using Python pandas in Jupyter Notebook - How to clean CSV data in Jupyter Notebook? - YouTube
- Extracting features from dates
- 랜덤한 데이터로 DataFrame 생성 및 원하는 행과 열 데이터 선택하기 미래 실험실 pYTHON
- 금 시세 분석하기(feat. Pandas)
- Calculating Streaks in Pandas
- Slicing and Indexing with Pandas - Towards Data Science
- Pandas versus SQL Comparison : JOIN | Data Yoshi | Blog and Jobs in Data Science, Machine Learning, AI and more
- R, Python 분석과 프로그래밍의 친구 (by R Friend) :: 'pandas' 태그의 글 목록
- Working With DataFrames In Pandas - YouTube
- How to write ETL operations in Python | by Hassan Syyid | Aug, 2020 | Towards Data Science
- Ian Ozsvald - Making Pandas Fly | PyData Fest Amsterdam 2020 - YouTube
- Data Analysis with Python: Part 1 of 6 (Live Course) - YouTube
- Data Analysis with Python: Part 2 of 6 - Python Functions and Working with Files (Live Course) - YouTube
- Data Analysis with Python: Part 3 of 6 Numerical Computing with Numpy (Live Course) - YouTube
- Data Analysis with Python: Part 4 of 6 - Analyzing tabular data with Pandas - YouTube
- Data Analysis with Python: Part 5 of 6 - Visualization with Matplotlib and Seaborn (Live Course) - YouTube
- Data Analysis with Python: Part 6 of 6 - Exploratory Data Analysis - A Case Study (Live Course) - YouTube
- Reading HTML tables with Pandas - Practical Business Python
- Ian Ozsvald - Making Pandas Fly - YouTube
- Case Study: Processing Historical Weather Pattern Data - Practical Business Python
- pandas and friends - Marc Garcia - YouTube
- 자주쓰는 명령어로 배우는 Pandas #1 : Pandas와 데이터 살펴보기
- 자주쓰는 명령어로 배우는 Pandas #2 : Index와 Column 조작하기
- 자주쓰는 명령어로 배우는 Pandas #3 : 데이터 조작하기
- 자주쓰는 명령어로 배우는 Pandas #4 : 데이터 능숙하게 다루기
- Wes McKinney: pandas in 10 minutes | Walkthrough - YouTube
- Effective Pandas by Matt Harrison - YouTube
- Efficiently Cleaning Text with Pandas - Practical Business Python
- Scaling Pandas: Dask vs Ray vs Modin vs Vaex vs RAPIDS
- Pareto and Pandas
- Practical SQL for Data Analysis | Haki Benita
- Exploring Your Dataset With Pandas and Python - YouTube
- The ten most important Pandas functions, and how to work with them
- How To Make Your Pandas Loop 71803 Times Faster | by Benedikt Droste | Towards Data Science
- Pandas not enough? Here are a few good alternatives to processing larger and faster data in Python - KDnuggets
- Faster Pandas: Make your code run faster and consume less memory| Miki Tebeke, CEO 353solutions. - YouTube
- Make Your Pandas Code Lightning Fast - YouTube
- Py) 전처리-데이터프레임 데이터타입 확인 - Data Doctor
- How To Add New Column to Pandas DataFrame | Towards Data Science
- 데이터분석 최근, 넷플릭스의 콘텐츠 보유 현황과 수급 전략에 대하여
- Spreadsheets to Python: it's time | Clive Siviour | Towards Data Science
- Python Pandas Interview Questions for Data Science | by Nathan Rosidi | Nov, 2021 | Towards Data Science
- Numpy와 Pandas에서의 배열 연산
- UCL Data Science Society: Pandas. Workshop 6: What is Pandas, Pandas… | by Philip Wilkinson | Nov, 2021 | Towards Data Science
- 파이썬이 빅데이터를 다루기에 느리다고요? (pyspark와 pandas UDF) 박현우 - PyCon Korea 2021 - YouTube
- Export Pandas DataFrames — Write Your Own Utility Functions in Python | by Zoltan Guba | Jan, 2022 | Python in Plain English
- 판다스 텍스트 분석과 전처리 - YouTube
- 텍스트 분석을 위한 파이썬 기초 - YouTube
- 대한민국 인구통계 분석(위키) - YouTube
- 파이썬으로 서울시 코로나19 현황 분석하기 - YouTube
- How to handle Missing Values in Python, using Rank Method - YouTube
- How to DeDuplicate in Python using Hashing Technique - YouTube
- 나도 판다스 오픈소스 기여자?! - YouTube
- Loading Data into Pandas: 5 Tips and Tricks You May or May Not Know
- Effective Pandas I Matt Harrison I PyData Salt Lake City Meetup - YouTube
- Top Five Tricks for Coding in Pandas — with Matt Harrison - YouTube
- So You Wanna Be a Pandas Expert? (Tutorial) - James Powell | PyData Global 2021 - YouTube
- 파일 용량을 1/10 로 줄이는 방법?! pandas 로 parquet 파일 포맷 다루기 - YouTube
- Pandas NaN이란 그리고 None 차이
- Pandas dataframe 메모리 사용량 확인하기
- Hossein Mortazavi - How to use Pandas Efficiently | PyData Yerevan 2022 - YouTube
- Jeff Reback: pandas at a Crossroads, the Past, Present, and Future | PyData NYC 2022 - YouTube
- 25 Nooby Pandas Coding Mistakes You Should NEVER make. - YouTube
- How to cache function output to the disk given pandas obj params – Passion is like genius; a miracle
- Joris Van den Bossche - On copies and views: updating pandas' internals | PyData Global 2022 - YouTube
- Rehan Durrani - How to maximally parallelize the entire pandas API | PyData Global 2022 - YouTube
- Srikanth - Use pandas in tidy style | PyData Global 2022 - YouTube
- Python Data Analysis Tips - How to plot many histograms in Pandas without a For loop
- Matt Harrison - Testing Pandas- Shoots, leaves, and garbage! | PyData Global 2022 - YouTube
- Py) Pandas - 2버전 출시!! - Data Doctor
- downcast Essential basic functionality — pandas 1.4.3 documentation
- Season6 데이타 사이언스 - YouTube
- dtale: Visualizer for pandas data structures
- Modin: Speed up your Pandas workflows by changing a single line of code
- optimus: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF and PySpark
- pandas-ai: Pandas AI is a Python library that integrates generative artificial intelligence capabilities into Pandas, making dataframes conversational
- pandera: A light-weight, flexible, and expressive statistical data testing library
- Polars
- polars: Fast multi-threaded DataFrame library in Rust and Python
- Pypolars | What is Pypolars and How Pypolars Compares With Pandas
- 3x times faster Pandas with PyPolars | by Satyam Kumar | May, 2021 | Towards Data Science
- Polars - Rust/Python 용 빠른 DataFrame 라이브러리 | GeekNews
- Polars, the Fastest Dataframe Library You Never Heard of. - Ritchie Vink | PyData Global 2021 - YouTube
- Expressive and Fast Dataframes in Python with Polars || Juan Luis - YouTube
- pygwalker: PyGWalker: Turn your pandas dataframe into a Tableau-style User Interface for visual analysis
- sidetable - Create Simple Summary Tables in Pandas
- swifter: A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
- vaex - Out-of-Core DataFrames for Python, ML, visualize and explore big tabular data at a billion rows per second. https://vaex.io
- Vaex: A DataFrame with super strings spark보다 빠르다는 benchmark
- A Billion Rows A Second - Working with BIG! data in Python
- How to analyse 100 GB of data on your laptop with Python
- Beyond Pandas: Spark, Dask, Vaex and other big data technologies battling head to head | by Jonathan Alexander | Towards Data Science
- 7 reasons why I love Vaex for data science | by Jovan Veljanoski | Towards Data Science
- Uncluster Your Data Science Using Vaex • Maarten Breddels & Jovan Veljanoski • GOTO 2021 - YouTube
- Juan Luis Cano Rodríguez - Beyond Pandas: The Great Python Dataframe Showdown | PyData London 2022 - YouTube
- Jovan Veljanoski & Maarten Breddels - Vaex: the perfect DataFrame Library for Python Apps - YouTube
- ydata-profiling provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution
- Full Javascript Parser - Abstract Syntax Tree
- Writing a Fuzzy Receipt Parser in Python
- pycparser: Complete C99 parser in pure Python
- TrumpScript parser, tokenizer, compiler 참고
- PyPy Vectorization
- PyPy warmup improvements
- Automatic SIMD vectorization support in PyPy
- "파이썬 성능 향상을 위한" 파이파이란 무엇인가
- cppyy: C++ bindings for PyPy
- ubuntu pypy 설치 & benchmark
- PyPy's new JSON parser
- Why Python Written in Python Is Faster Than Regular Python | by Michael Krasnov | Better Programming | Jul, 2020 | Medium
- 2 & 3 호환
- Cheat Sheet: Writing Python 2-3 compatible code
from __future__ import print_functionif sys.version_info[:2] <= (2, 7): import urllib else: from urllib.parse import urlencode- Python 2 & 3 Compatible print and input
- Python 2 와 3 공존하기
- 파이썬 3에 뛰어들기
- Zero to Hero with Python Tutorial FULL- Easy Learning python 3.4 from begin to advance (Compact)
- Python 3 in Science: the great migration has begun!
- How we rolled out one of the largest Python 3 migrations ever
- Python의 미래, Python 3로 넘어가기
- Python 3.5 Brings New Language Features and Library Modules
- Python 3.5 and multitasking
- Python Changes 2014+
- The Bottom-Line Single Main Difference Between Python 2 and 3
- Why Python 3 exists
- 10 awesome features of Python that you can't use because you refuse to upgrade to Python 3
- Python 3 Basics Tutorial Series
- Python 3 Patterns, Recipes and Idioms
- 파이썬 마이크로 실전 패턴
- The Case Against Python 3 (For Now)
- The Case Against “The Case Against Python 3”
- 파이썬 3.6에서 바뀐 점
- Tiny Python 3.6 Notebook
- Lessons Learned: Digital Ocean for Python 3
- Optimizations which made Python 3.6 faster than Python 3.5
- Instagram Makes a Smooth Move to Python 3
- python3에서 자주 실수하는 부분
- Migrating to Python 3 with pleasure
- 5 speed improvements in Python 3.7
- Python 3.7의 새로운 기능들
- Modern Functions in Python 3
- PyCon KR 2019 Why is Python 3.7 fastest
- What’s New In Python 3.8
- Try out walrus operator in Python 3.8 Get started with Python 3.8 alpha 1
- The Walrus Operator: Python 3.8 Assignment Expressions – Real Python
- When and Why to Use := Over = in Python | by Andre Ye | Towards Data Science
- 파이썬(Python) 3.8 릴리스와 주요 변경 사항
- Some New Features in Python 3.8
- Cool New Features in Python 3.8
- 놓쳐서는 안 될' 파이썬의 새로운 기능 6가지 3.8
- Reimplementing a Solaris command in Python gained 17x performance improvement from C
- Dictionary Merging and Updating in Python 3.9
- New Features in Python 3.9
- What's new in Python 3.9? - DeepSource
- Take a Look at the Awesome New Features Coming in Python 3.9 | by Michael Krasnov | Better Programming | Medium
- 10 Awesome Python 3.9 Features. The Must-Know Python 3.9 Features | by Farhad Malik | Oct, 2020 | Towards Data Science
- 파이썬(Python) 3.9 릴리스와 주요 변경 사항 | 44BITS
- Python 3.9 Update New Features. Write less code, achieve more! | by Radian Krisno | Towards Data Science
- 파이썬 3.9의 새로운 기능과 더 나아진 기능 - ITWorld Korea
- Python Will be Dead in 2021? A review of the final version of Python 3.9 | by Rizky Maulana N | Towards Data Science
- Python 3.9에 등장한 상큼한 8가지 Features | MADTECH
- New Features in Python 3.10 | Towards Data Science
- How to use the coolest new features in Python 3.10
- Python 3.10 – Top 5 Features in the new Version | Rubik's Code
- 패턴 매칭 지원 外··· '파이썬 3.10', 무엇이 달라졌을까 - CIO Korea
- Python 3.10 톺아보기 | Lablup Blog
- Python 3.11 새로운 기능 및 수정점 : 네이버 블로그
- Python is About to Become 64% Faster — Python 3.10 vs. Python 3.11 Benchmark | by Dario Radečić | Apr, 2022 | Towards Data Science
- Python 3.11 Is Indeed Faster Than 3.10 | by Thuwarakesh Murallie | May, 2022 | Towards Data Science
- Some New Features in Python 3.11 - YouTube
- How we are making Python 3.11 faster - presented by Mark Shannon - YouTube
- Writing Faster Python 3 - YouTube
- Python 3.11: Cool New Features for You to Try – Real Python
- Features You Likely Don’t Use in Python 3 — But You Should | LaptrinhX
- 9 Python 3 Hacks Programmers Probably Don’t Utilize | Better Programming
- 2to3
- concurrent.futures - Easy parallel python with concurrent.futures
- python3statement.org 2020까지 python2.7 지원 중단하기로 하는 project 모음
- search-script-scrape - 101 real world web scraping exercises in Python 3 for data journalists https://github.com/compjour/search-script-scrape#repo-status
- syntax_sugar
- zippy: ZipPy is a Python3 interpreter on top of Truffle framework
- github.com/elegant-scipy
- Scipy Lecture Notes
- SciPy Cheat Sheet: Linear Algebra in Python
- SciPy 2015: Scientific Computing with Python Conference
- Keynote: Machine Learning for Social Science | SciPy 2016 | Hanna Wallach
- 2D Convolution in Python similar to Matlab's conv2
- Area of sinc and jinc function lobes
- SciPy 1.0: fundamental algorithms for scientific computing in Python
- Envelope for Least Square Filtering and Smoothing | Pega Devlog
- Scipy Lecture Notes — Scipy lecture notes
- SciPy Conference 2022, Austin -- Scientific Computing with Python
- Roman Neruda, Petra Vidnerová: Tested on agents - an agent-based epidemiological model PyData Prg - YouTube
- Scipy 소개 + curve fitting | Pega Devlog
- 파이썬으로 Slack에 문자 보내기
- AWS Lambda에 Python Slack Chatbot을 통해서 미세먼지 대기정보 알림이 만들기
- Python Slack 봇 개발 및 CI 연동 삽질기
- slack api 연동
- Slack Slash Command를 통해 집 근처 약국 마스크 수량 알아보기
- Python and Slack: A Natural Match
- How To Build a Slackbot in Python on Ubuntu 20.04 | DigitalOcean
- Slack Webhook API 생성하기
- Slack webhook 으로 Upsource 코드 리뷰 알람 받기 (멀티 슬랙 채널)
- HUFS WEB project Notion & Slack 연동
- 파이썬으로 슬랙 메시지 보내기 - 로스카츠의 AI 머신러닝
- 게으른 자를 위한 취소표 알리미 · 감자도스
- Python으로 Slack Bot 만들기 - 정우일 블로그
- bolt-python: A framework to build Slack apps using Python
- kakao-to-slack: send kakao talk message to slack
- Slack Developer Kit for Python — Slack Developer Kit for Python
- slacker: Full-featured Python interface for the Slack API
- SymPy
- Unification in SymPy
- Matrix Computations in SymPy
- Python Sympy 모듈 이해하기
- 파이썬 심파이(Sympy)와 함께하는 수학여행
- Generating Python code from SymPy
- Doing symbolic math with SymPy LWN.net
- Quantum Addition of Angular Momentum in Python: Obtaining the Clebsch-Gordan Coefficients - YouTube
- Software Carpentry: 기호 수학(Symbolic Math)
- Beginning Test-Driven Development in Python
- Python 프로젝트에 Codecov 연동하기
- 파이썬 시작하기 TDD부터 PyPI에 배포까지 (1)
- 파이썬 시작하기 TDD부터 PyPI에 배포까지 (2)
- TDD와 Flipped Classroom을 활용한 파이썬 교육 - 설진석 - PyCon Korea 2020 - YouTube
- A simple introduction to Test Driven Development with Python
- Automated Tests in Python
- python testing
- Unit Tests in Python || Python Tutorial || Learn Python Programming
- Reduce testing time by Multiprocessing in python
- Don’t trust your gut!
- The Template Method Pattern in Python | by Tomas Ye | Better Programming | Sep, 2020 | Medium
- Unit Testing in Python -The Basics | The Startup
- Unit Testing in Python — Patching, Mocks and Dependency Injection | by Martin Thoma | Level Up Coding
- CI Pipelines for Python Projects. What is a Continuous Integration… | by Martin Thoma | Level Up Coding
- 파이썬으로 테스트 데이터 만들기 · 개발블로그
- Test Automation with Python - The 3 Best Tools in 2021
- My Python testing style guide - Stargirl (Thea) Flowers
- 3 ways to test your API with Python | Opensource.com
- A/B 테스트 플랫폼 MVP 개발기. 권오빈 - PyCon Korea 2021 - YouTube
- The Ultimate Guide to A/B Testing with Python | by Rahulraj Singh | Jan, 2022 | Towards Data Science
- Unit testing with Python. Like most developers who started using… | by Saif | Mar, 2022 | Dev Genius
- How To Write Unit Tests For Existing Python Code // Part 1 of 2 - YouTube
- How To Write Unit Tests For Existing Python Code // Part 2 of 2 - YouTube
- A/B Testing for Data Science ( Python and R) | June 30th, 2021
- How to Support A/B Testing in Your Python Code - YouTube
- Code coverage through unit tests running in sub-processes/threads - presented by Saransh Chopra - YouTube
- Testing in Python - YouTube
- atheris: A Coverage-Guided, Native Python Fuzzer
- behave Welcome to behave! — behave 1.2.6 documentation BDD
-
junit2html: Turn Junit XML reports into self contained HTML reports
pip install junit2html behave code_examples/chapter22/features/ --junit junit2html <filename>
-
- Coverage.py — a tool for measuring code coverage of Python programs
- Faker - a Python package that generates fake data for you
- mutation testing
- property based testing
- Property-based Testing from Scratch (in Python)
- Hypothesis - a powerful, flexible, and easy to use library for property-based testing. http://hypothesis.works
- Hypothesis
- Introduction to property-based testing
- 5-minute intro to property-based testing in Python with hypothesis
- Episode #67: Property-based Testing with Hypothesis
- Hypothesis with David MacIver - Episode 52
- Stop Writing Tests (Next Generation Tools To Automate Testing) - YouTube
- Cheuk Ting Ho - I hate writing tests, that's why I use Hypothesis | PyData Global 2022 - YouTube
- Intro to property-based testing in Python
- Unit Testing in Python — Property-based Testing | Level Up Coding
- 우아하게 준비하는 테스트와 리팩토링 - 한성민
- PyCon KR 2019 테스트에 걸리는 시간을 92% 줄이기 주로 Django 기반이지만 매우 좋은 내용
- Adinata Thayib - Running Unit Test on Top of Serverless Service - YouTube
- nosetests
- pynguin: The PYthoN General UnIt Test geNerator is a test-generation tool for Python
- pytest: helps you write better programs
-
installaion; anaconda에서
pip install -U pytest로 오류가 발생하면conda update pytest이용$ [http_proxy=http://x.y.z:port https_proxy=http://x.y.z:port] pip install -U pytest ... Cannot remove entries from nonexistent file /path/to/anaconda/lib/python2.7/site-packages/easy-install.pth $ [http_proxy=http://x.y.z:port https_proxy=http://x.y.z:port] conda update pytest -
PyTest, the testing framework you've been dreaming of by Eli Gur
-
Open Sourcing Pytest Tools pytest-flakefinder, unittest2pytest
-
Start Python #2 Unit Test 사용하기 ( feat. pytest ) - Kowana's coding
-
테스트 코드 작성기(1) — 단위 테스트 프레임워크 | by Paikend | 오늘의헤드라인 | Jan, 2021 | Medium
-
Web UI Testing in Python - YouTube selenium
-
Beyond Unit Tests End to End Web UI Testing – Andrew Knight (PyCon Taiwan 2021) - YouTube
-
playwright-python: Python version of the Playwright testing and automation library
-
pytest-flakefinder - Runs tests multiple times to expose flakiness
-
- Tabletests
- unittest
- unittest.mock
- practice - unittest
- practice - unittest.main() or unittest.TextTestRunner(verbosity=2).run()
- Python Tutorial: Unit Testing Your Code with the unittest Module
- Mock Everything
- Python Mock Cookbook
- Python Mock Gotchas
- Python Mocking 101: Fake It Before You Make It
- Using the Python mock library to fake regular functions during tests
- Mocking Python With Kung Fu Panda
- Python Mocking, You Are A Tricksy Beast
- Mocking Objects in Python
- Mocking private methods in python
- Mocking complicated
__init__in Python - Assigning instance variables in function called by
__init__vs. function called from__init__ - Another approach to mocking properties in Python
- Another approach to mocking properties
- How in the world do you Mock a name attribute?
- How to Mock a name attribute?
- Allow doubling a particular instance method on all instances of a class
- Today I Learned: 파이썬 단위 테스트 모듈, unittest
- Python Unit Testing With VS Code
- Python Tutorial: Unit Testing Your Code with the unittest Module - YouTube
- unittest2pytest - Convert unittest asserts to pytest rewritten asserts
- vcr.py - Automatically mock your HTTP interactions to simplify and speed up testing
- Learn How to Use Static Type Checking in Python 3.6 in 10 minutes
- Panel Discussion: What is Static Typing in Python? | PyBay 2017
- Dynamic Typing in Python
- 파이썬의 타입 힌트
- Python 3 정적 타이핑 소개 및 소감(?)
- Next Steps with Python Type System
- callable() in Python
- Typesetting With Python
- Our journey to type checking 4 million lines of Python
- Falling into a type world with Python
- Grzegorz Kocjan - Don't start with a database - YouTube dataclass, abc, injector, TypeVar
- Dustin Ingram - Static Typing in Python - YouTube
- 군더더기 없는 파이썬 코드를 위한 타입 체커 4종 - ITWorld Korea
- Static Typing in Python. Conducting Type Checking with Ease | by Eden Au | Towards Data Science
- You Should Start Using Type Annotations in Python | by Tivadar Danka | Towards Data Science
- Generics/templates in python? - Stack Overflow
- No, not typing. Types. - YouTube
- Type Hints in Python: What, Why, and How - YouTube
- Tests aren’t enough: Case study after adding type hints to urllib3 — sethmlarson.dev
- Code Better With Type Hints - Part 1 - PyBites
- Code Better With Type Hints – Part 2 - PyBites
- Code Better With Type Hints – Part 3 - PyBites
- 파이썬 Typing 파헤치기 - 기초편
- 파이썬 Typing 파헤치기 - 심화편
typing.Protocol: type hints as Guido intended - presented by Luciano Ramalho - YouTubetyping.Protocol: Type Hints in Python - YouTube- Protocol Or ABC In Python - When to use which one? - YouTube
- Protocols - Static duck typing for decoupled code - presented by Ran Zvi - YouTube
- Protocols in Python: Why You Need Them - presented by Rogier van der Geer - YouTube
- Protocols in Python: Why You Need Them - YouTube
- 파이썬 타입 힌트 제대로 활용하기, 최보성 - PyCon Korea 2022 - YouTube
- TypedDict is a LIFESAVER - YouTube
- beartype: Unbearably fast O(1) runtime type-checking in pure Python
- Enforce.py - Python 3.5+ runtime type checking for integration testing and data validation
- LibCST - A concrete syntax tree parser and serializer library for Python that preserves many aspects of Python's abstract syntax tree https://libcst.readthedocs.io
- MonkeyType - A system for Python that generates static type annotations by collecting runtime types
- mypy an experimental optional static type checker for Python
- Static Typing for Python
- Dec 2016 BayPiggies Talk at LinkedIn: Introducing Type Annotations for Python
- Python Type Hints by Sunghyun Hwang
- Type Hints(PEP 484, PEP 526) - 1
- Jukka Lehtosalo, David Fisher Static Types for Python PyCon 2017
- PYCON UK 2017: MyPy: The Good, The Bad and The Ugly
- mypy Python's gradual typing implementation - Itzhak Kasovitch - Pycon Israel 2017
- Type-Checking Python Programs With Type Hints and mypy
- Python tricks: Type hints and static type checking
- Type-checked Python In The Real World
- Clearer Code at Scale (Static Types in Python)
- Python static type checker (mypy)
- Type checking in Python using mypy
- mypy와 함께하는 Python Typing
- Python typing으로 인한 순환 참조 대응책
- mypy 사용하기 static typing 테스트 해보기
- PyCon KR 2019 Python Type Hinting and Static Type Checking
- Python Type Hints: Pros & Cons
- Release: Static type checker in Python
- mypyc Welcome to mypyc documentation!
- PyAnnotate: Auto-generate PEP-484 annotations
- pydantic - Data validation and settings management using python 3.6 type hinting
- Pyre - A performant typechecker for Python
- pyright - Static type checker for the Python language
- pytype - A static analyzer for Python code
- Tsukkomi for Python types, inspired by typeannotations package https://pypi.python.org/pypi/tsukkomi
- typeguard - Run-time type checker for Python
- Python Tutorial for Beginners
- Python Programming Course
- Python Programming Tutorials (Computer Science)
- Python Programming Tutorials
- Python Tutorial | Beginners & Experienced – Learn Python
- 안녕 프로그래밍
- 네 Python은 느립니다, 하지만 저는 신경쓰지 않습니다
- 파이썬 코딩 무료 강의 (기본편) - 6시간 뒤면 여러분도 개발자가 될 수 있어요 나도코딩 - YouTube
- 파이썬 YouTube 뮤직플레이어 개발 강좌
- The Best Way to Learn Python – Python Programming Tutorial for Beginners
- Tips and Examples - Codetorial
- Python for JavaScript developers
- Learn basics Python Programming with Smartphone 1 - YouTube
- 시리즈 | 파이썬 입문자를 위한 기초 다지기! - hyunbeen0216.log
- 파이썬을 처음 사용하는 동료와 효율적으로 일하는 방법. 자동화된 방식으로 빠르게 비즈니스 로직에 집중하기 | by weekwith.me | 당근마켓 팀블로그 | Feb, 2023 | Medium
- colab-tutorial.ipynb - Colaboratory python 기초문법
- futurecoder: learn python from scratch
- Learn Python - Free Interactive Python Tutorial
- Misha Sv - YouTube
- python-mini-projects: A collection of simple python mini projects to enhance your python skills
- tinkerstellar | Learn by tinkering
Web -> web
- py2exe로 생성된 exe에서 py 소스 구하기 및 \xec... 문자열 변환
- py2exe와 py2app을 통한 Windows/OS X용 실행파일 만들기
- Windows COM (ActiveX) client 사용
- Create a standalone Windows installer for your Python application
- 윈도우에서 여러 버전의 파이썬을 설치
- Lesson One Video - Intro to the VBA Model in Python
- Using Events in Python Win32 | Part 1
- 이벤트를 만들고, COM 개체에 이벤트를 할당하고, 이벤트의 메시지를 표시하는 방법
- VBA 개체 모델에서는 사용자가 이벤트를 일으킬 때, VBA 코드를 실행할 수 있는 이벤트에 액세스 가능
- 이 이벤트들은 클래스 객체를 사용하여 Python 내부의 Win32 COM 라이브러리를 통하여 액세스 가능
- How to Use the PyIDispatch Object in Pythoncom
- PyIDispatch 객체와 이 객체를 활용하여 COM 객체에 속한 다른 방법 및 속성을 호출하는 방법
- Win32COM 라이브러리는 표준화 된 방식으로 다른 COM 개체들과 통신할 수 있는 디스패치 인터페이스 개체를 활용
- How to Use Word VBA in Python
- 새로운 Word 문서를 만들고, 문서에 테이블을 추가하고, Python을 사용하여 링크를 추가하는 방법
- Word VBA 모델
- Building a Windows Shortcut with Python
- Python과 Windows Program간의 데이터 공유 memory mapped file, MFC <-> python
- 처음 시작하시는 분들을 위한 윈도우 파이썬 개발환경 구축 - YouTube
- Automating Windows Applications using Python for Efficiency
- Dependency Walker - free utility that scans any 32-bit or 64-bit Windows module (exe, dll, ocx, sys, etc.) and builds a hierarchical tree diagram of all dependent modules
- DUMPBIN Reference examine COFF, exe, DLL files
- ironpython
- pywin32 파이썬 윈도우 핸들 포커스 방법, 실행중인 윈도우 핸들 가져오는 방법, 윈도우창 제어하는 방법
- pywinauto - a set of python modules to automate the Microsoft Windows GUI
- win32clipboard clipboard 로 text, image 복사하기 , 가져오기
- win32gui 응용프로그램창 백그라운드로 숨기는 방법(win32gui)
- WSl Using WSL to Build a Python Development Environment on Windows