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data_backend.py
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# data for index => feeds data from searcher.py and model
import json
import requests
from searchinator import *
from flask import Flask
from flask import request
from flask import render_template
from searchinator import *
import nltk
from newspaper import Article
from newspaper import fulltext
app = Flask(__name__)
headline_policies_1 = headline_policies_2 = headline_policies_3 = headline_policies_4 = headline_policies_5 = " default"
headline_education_1 = headline_education_2 = headline_education_3 = headline_education_4 = headline_education_5 = " default"
headline_biology_1 = headline_biology_2 = headline_biology_3 = headline_biology_4 = headline_biology_5 = " default"
headline_economy_1 = headline_economy_2 = headline_economy_3 = headline_economy_4 = headline_economy_5 = " default"
headline_statistics_1 = headline_statistics_2 = headline_statistics_3 = headline_statistics_4 = headline_statistics_5 = " default"
# Paragraphs
text_policies_1 = text_policies_2 = text_policies_3 = text_policies_4 = text_policies_5 = "text about policies"
text_education_1 = text_education_2 = text_education_3 = text_education_4 = text_education_5 = "text about education"
text_biology_1 = text_biology_2 = text_biology_3 = text_biology_4 = text_biology_5 = "text about biology"
text_economy_1 = text_economy_2 = text_economy_3 = text_economy_4 = text_economy_5 = "text about economy"
text_statistics_1 = text_statistics_2 = text_statistics_3 = text_statistics_4 = text_statistics_5 = "text about statistics"
text_donations_1 = text_donations_2 = text_donations_3 = text_donations_4 = text_donations_5 = "Donate to help fight COVID-19"
# images
img_policies_1 = img_policies_2 = img_policies_3 = img_policies_4 = img_policies_5 = "https://imgur.com/lNhUEmK.png"
img_education_1 = img_education_2 = img_education_3 = img_education_4 = img_education_5 = "https://imgur.com/KiDWiTr.png"
img_biology_1 = img_biology_2 = img_biology_3 = img_biology_4 = img_biology_5 = "https://imgur.com/aY2TasC.png"
img_economy_1 = img_economy_2 = img_economy_3 = img_economy_4 = img_economy_5 = "https://imgur.com/W9kLJHc.png"
img_statistics_1 = img_statistics_2 = img_statistics_3 = img_statistics_4 = img_statistics_5 = "https://imgur.com/8IzNJTT.png"
# urls
url_policies_1 = url_policies_2 = url_policies_3 = url_policies_4 = url_policies_5 = "https://compression.stanford.edu/"
url_education_1 = url_education_2 = url_education_3 = url_education_4 = url_education_5 = "https://compression.stanford.edu/"
url_biology_1 = url_biology_2 = url_biology_3 = url_biology_4 = url_biology_5 = "https://compression.stanford.edu/"
url_economy_1 = url_economy_2 = url_economy_3 = url_economy_4 = url_economy_5 = "https://compression.stanford.edu/"
url_statistics_1 = url_statistics_2 = url_statistics_3 = url_statistics_4 = url_statistics_5 = "https://compression.stanford.edu/"
url_donations_1 = url_donations_2 = url_donations_3 = url_donations_4 = url_donations_5 = "https://covid19responsefund.org/en/"
# tag names
tag1_policies_1 = tag1_policies_2 = tag1_policies_3 = tag1_policies_4 = tag1_policies_5 = "policies tag1"
tag1_education_1 = tag1_education_2 = tag1_education_3 = tag1_education_4 = tag1_education_5 = "edu tag1"
tag1_biology_1 = tag1_biology_2 = tag1_biology_3 = tag1_biology_4 = tag1_biology_5 = "bio tag1"
tag1_economy_1 = tag1_economy_2 = tag1_economy_3 = tag1_economy_4 = tag1_economy_5 = "econ tag1"
tag1_statistics_1 = tag1_statistics_2 = tag1_statistics_3 = tag1_statistics_4 = tag1_statistics_5 = "stat tag1"
tag2_policies_1 = tag2_policies_2 = tag2_policies_3 = tag2_policies_4 = tag2_policies_5 = "policies tag2"
tag2_education_1 = tag2_education_2 = tag2_education_3 = tag2_education_4 = tag2_education_5 = "edu tag2"
tag2_biology_1 = tag2_biology_2 = tag2_biology_3 = tag2_biology_4 = tag2_biology_5 = "bio tag2"
tag2_economy_1 = tag2_economy_2 = tag2_economy_3 = tag2_economy_4 = tag2_economy_5 = "econ tag2"
tag2_statistics_1 = tag2_statistics_2 = tag2_statistics_3 = tag2_statistics_4 = tag2_statistics_5 = "stat tag2"
tag3_policies_1 = tag3_policies_2 = tag3_policies_3 = tag3_policies_4 = tag3_policies_5 = "policies tag3"
tag3_education_1 = tag3_education_2 = tag3_education_3 = tag3_education_4 = tag3_education_5 = "edu tag3"
tag3_biology_1 = tag3_biology_2 = tag3_biology_3 = tag3_biology_4 = tag3_biology_5 = "bio tag3"
tag3_economy_1 = tag3_economy_2 = tag3_economy_3 = tag3_economy_4 = tag3_economy_5 = "econ tag3"
tag3_statistics_1 = tag3_statistics_2 = tag3_statistics_3 = tag3_statistics_4 = tag3_statistics_5 = "stat tag3"
lavaa = {
"policies":
{
"url": [
url_policies_1,
url_policies_2,
url_policies_3,
url_policies_4,
url_policies_5
],
"image": [
img_policies_1,
img_policies_2,
img_policies_3,
img_policies_4,
img_policies_5
],
"text": [
text_policies_1,
text_policies_2,
text_policies_3,
text_policies_4,
text_policies_5
],
"headlines": [
headline_policies_1,
headline_policies_2,
headline_policies_3,
headline_policies_4,
headline_policies_5
],
"tags": [
[tag1_policies_1,
tag2_policies_1,
tag3_policies_1],
[tag1_policies_2,
tag2_policies_2,
tag3_policies_2],
[tag1_policies_3,
tag2_policies_3,
tag3_policies_3],
[tag1_policies_4,
tag2_policies_4,
tag3_policies_4],
[tag1_policies_5,
tag2_policies_5,
tag3_policies_5]
]
},
"education":
{
"url": [
url_education_1,
url_education_2,
url_education_3,
url_education_4,
url_education_5
],
"image": [
img_education_1,
img_education_2,
img_education_3,
img_education_4,
img_education_5
],
"text": [
text_education_1,
text_education_2,
text_education_3,
text_education_4,
text_education_5
],
"headlines": [
headline_education_1,
headline_education_2,
headline_education_3,
headline_education_4,
headline_education_5
],
"tags": [
[tag1_education_1,
tag2_education_1,
tag3_education_1],
[tag1_education_2,
tag2_education_2,
tag3_education_2],
[tag1_education_3,
tag2_education_3,
tag3_education_3],
[tag1_education_4,
tag2_education_4,
tag3_education_4],
[tag1_education_5,
tag2_education_5,
tag3_education_5]
]
},
"biology":
{
"url": [
url_biology_1,
url_biology_2,
url_biology_3,
url_biology_4,
url_biology_5
],
"image": [
img_biology_1,
img_biology_2,
img_biology_3,
img_biology_4,
img_biology_5
],
"text": [
text_biology_1,
text_biology_2,
text_biology_3,
text_biology_3,
text_biology_4,
text_biology_5
],
"headlines": [
headline_biology_1,
headline_biology_2,
headline_biology_3,
headline_biology_4,
headline_biology_5
],
"tags": [
[tag1_biology_1,
tag2_biology_1,
tag3_biology_1],
[tag1_biology_2,
tag2_biology_2,
tag3_biology_2],
[tag1_biology_3,
tag2_biology_3,
tag3_biology_3],
[tag1_biology_4,
tag2_biology_4,
tag3_biology_4],
[tag1_biology_5,
tag2_biology_5,
tag3_biology_5]
]
},
"economy":
{
"url": [
url_economy_1,
url_economy_2,
url_economy_3,
url_economy_4,
url_economy_5
],
"image": [
img_economy_1,
img_economy_2,
img_economy_3,
img_economy_4,
img_economy_5
],
"text": [
text_economy_1,
text_economy_2,
text_economy_3,
text_economy_4,
text_economy_5
],
"headlines": [
headline_economy_1,
headline_economy_2,
headline_economy_3,
headline_economy_4,
headline_economy_5
],
"tags": [
[tag1_economy_1,
tag2_economy_1,
tag3_economy_1],
[tag1_economy_2,
tag2_economy_2,
tag3_economy_2],
[tag1_economy_3,
tag2_economy_3,
tag3_economy_3],
[tag1_economy_4,
tag2_economy_4,
tag3_economy_4],
[tag1_economy_5,
tag2_economy_5,
tag3_economy_5]
]
},
"statistics":
{
"url": [
url_statistics_1,
url_statistics_2,
url_statistics_3,
url_statistics_4,
url_statistics_5
],
"image": [
img_statistics_1,
img_statistics_2,
img_statistics_3,
img_statistics_4,
img_statistics_5
],
"text": [
text_statistics_1,
text_statistics_2,
text_statistics_3,
text_statistics_4,
text_statistics_5
],
"headlines": [
headline_statistics_1,
headline_statistics_2,
headline_statistics_3,
headline_statistics_4,
headline_statistics_5
],
"tags": [
[tag1_statistics_1,
tag2_statistics_1,
tag3_statistics_1],
[tag1_statistics_2,
tag2_statistics_2,
tag3_statistics_2],
[tag1_statistics_3,
tag2_statistics_3,
tag3_statistics_3],
[tag1_statistics_4,
tag2_statistics_4,
tag3_statistics_4],
[tag1_statistics_5,
tag2_statistics_5,
tag3_statistics_5]
]
},
"donations":
{
"url": [
url_donations_1,
url_donations_2,
url_donations_3,
url_donations_4,
url_donations_5
],
"text": [
text_donations_1,
text_donations_2,
text_donations_3,
text_donations_4,
text_donations_5
]
}
}
@app.route('/', methods=['GET','POST'])
def home():
if(request.method == 'POST'):
jsdata = request.form
print(jsdata['county_name'], jsdata['state_code'])
send_urls(jsdata['county_name'], jsdata['state_code'])
# send_urls("Santa Clara", "California") #! testing
# rescor = coord(jsdata['county_name'] , jsdata['state_code'])
return render_template(
"index.html",
lavaa = lavaa
)
@app.route('/mobile', methods=['GET','POST'])
def mobile():
if(request.method == 'POST'):
jsdata = request.form
print(jsdata)
send_urls(jsdata['county_name'], jsdata['state_code'])
# send_urls("Santa Clara", "California") #! testing
# rescor = coord(jsdata['county_name'] , jsdata['state_code'])
return render_template(
"mobile.html",
lavaa = lavaa
)
def coord(geolat, geolong):
geolat = str(geolat)
geolong = str(geolong)
x = requests.get("https://geo.fcc.gov/api/census/area?lat=" + geolat + "&lon=" + geolong)
data = (x.json())
if(len(data['results']) != 0): return [data['results'][0]['county_name'], data['results'][0]['state_name']]
else: return ["global", "international"]
# def img_scrape(url_list):
# arrayinator = []
# for url in url_list:
# arrayinator.append(img_scraper(url))
# return arrayinator
def popinator(lst, index):
lst.append(lst.pop(index)) # moves element to end of list
cat_list = ['policies', 'education', 'biology','economy', 'statistics']
# search => urls
def send_urls(county_name, state_code):
# try:
url_data = v1(county_name, state_code)
for i in cat_list:
lavaa[i]['url'] = url_data['data'][i]['urls']
print('\n%s \n', i)
for r in range(5):
article = Article(str(lavaa[i]['url'][r]))
try:
article.download()
article.parse()
article.nlp()
lavaa[i]['headlines'][r] = article.title
lavaa[i]['image'][r] = article.top_image
lavaa[i]['text'][r] = article.summary[:100]
lavaa[i]['tags'][r] = article.keywords[0:2]
except:
lavaa[i]['headlines'][r] = "Error"
lavaa[i]['text'][r] = "default text"
lavaa[i]['tags'][r] = ['1' ,'2', '3']
continue
for site in range(5): # donations list
lavaa['donations']['url'] = url_data['data']['donations']['urls']
donation_site = Article(str(lavaa['donations']['url'][site]))
donation_site.download()
donation_site.parse()
# print(donation_site.title)
# print(str(lavaa['donations']['url'][site]))
lavaa['donations']['text'][r] = donation_site.title
print("success")
# send_urls("SantaClara", "CA") #! use this for testing
# print(lavaa)
# res = requests.get("https://coveragee-api.herokuapp.com/api/v1/Fulton/GA")
# url_data = res.json()
# print(url_data)