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Contributing to PyMC

PART 1: Pre-reqs to contributing

GitHub Account

https://github.com/reshamas

Git

git --version 

▶ git --version
git version 2.19.0

Conda

conda --version 

▶ conda --version
conda 4.10.3

Python

which python 

▶ which python
/Users/reshamashaikh/miniforge3/bin/python

python --version 

▶ python --version
Python 3.9.7

Text Editor

Visual Studio Code

PART 2: My working directory

NOTE: I use a directory called software-build where I clone my python libraries to which I contribute.

▶ pwd
/Users/reshamashaikh
(base) 
~                                                                     
▶ cd software-build 
(base) 
~/software-build                                                      
▶ pwd
/Users/reshamashaikh/software-build
(base) 
~/software-build                                                      
▶

PART 3: Fork & clone, set remotes

3.1: Fork the repo

3.2: Clone the repo

NOTE: this is my fork. You will need to update syntax with your user name.
Replace "reshamas" with "your_gh_username"

git clone git@github.com:reshamas/pymc.git 

▶ git clone git@github.com:reshamas/pymc.git
Cloning into 'pymc'...
remote: Enumerating objects: 57337, done.
remote: Counting objects: 100% (630/630), done.
remote: Compressing objects: 100% (292/292), done.
remote: Total 57337 (delta 419), reused 482 (delta 337), pack-reused 56707
Receiving objects: 100% (57337/57337), 735.38 MiB | 24.10 MiB/s, done.
Resolving deltas: 100% (41734/41734), done.
(base) 
~/software-build

3.3: cd into cloned repo

cd into the pymc folder:

▶ cd pymc
(base) 
~/software-build/pymc  main ✔                                     2d

3.4: Check remotes

Check remotes. Note there is one remote, the origin:

git remote -v 

▶ git remote -v
origin	git@github.com:reshamas/pymc.git (fetch)
origin	git@github.com:reshamas/pymc.git (push)
(base) 
~/software-build/pymc  main ✔                                     2d  
▶

3.5: Add another remote, called upstream

git remote add upstream git@github.com:pymc-devs/pymc.git 

▶ git remote add upstream git@github.com:pymc-devs/pymc.git
(base) 
~/software-build/pymc  main ✔                                     2d  
▶

3.6: Check remote(s)

git remote -v 

▶ git remote -v
origin	git@github.com:reshamas/pymc.git (fetch)
origin	git@github.com:reshamas/pymc.git (push)
upstream	git@github.com:pymc-devs/pymc.git (fetch)
upstream	git@github.com:pymc-devs/pymc.git (push)
(base) 
~/software-build/pymc  main ✔                                     2d  
▶

PART 4: Find an issue

I will work on this issue: xxx

PART 5: Create a feature branch

git checkout -b docstring_update 

▶ git checkout -b docstring_update
Switched to a new branch 'docstring_update'
(base) 
~/software-build/pymc  docstring_update ✔                         2d  
▶

git branch 

* docstring_update
  main
(END)

For me, I hit q to exit.

PART 6: Set up working environment

6.1: Create the working environment

conda env create -f conda-envs/environment-dev-py38.yml

NOTE: This step took me about 5 minutes on my Mac.

6.2: Activate the working environment

conda activate pymc-dev-py38 

▶ conda activate pymc-dev-py38 
(pymc-dev-py38) 
~/software-build/pymc  main ✔                                     2d  
▶

6.3: Install PyMC

pip install -e .

NOTE: This step took me about 1 minute on my Mac.

6.4: Install precommit

pip install pre-commit

PART 7: Work on issue (Ensure that functions's docstrings pass numpydoc validation)

  1. Will pick this one:
    pymc.sampling.instantiate_steppers
  2. Which is in this file: pymc/sampling.py
  3. Run numpy validation as:
pytest pymc/tests/test_docstrings.py -k pymc.sampling.instantiate_steppers

PART 8: changes made to file

  1. array-like of shape (n_samples, n_samples)
    Parameters
    ----------
    model : Model object
        A fully-specified model object
    steps : list, **array_like of shape (selected_steps, )**
        A list of zero or more step function instances that have been assigned to some subset of
        the model's parameters.
    selected_steps : dict
        A dictionary that maps a step method class to a list of zero or more model variables.
    step_kwargs : dict, **default=None**
        Parameters for the samplers. Keys are the lower case names of
        the step method, values a dict of arguments. Defaults to None.