class Expenses(FlaskForm):
list_URL = "http://api.currencylayer.com/list?access_key=7edb40d73b258f5cf730f823f226aa7e"
response = requests.get(list_URL).json()
# retrieve the list of names and save it in a json file
currency_list_names_file_name = "JSON_Files\\currency_list_names.json"
main_functions.save_to_file(response, currency_list_names_file_name)
# read the json file and extract all the names in an array of tuples
currency_names = main_functions.read_from_file(
currency_list_names_file_name)
name_list = []
for x in currency_names[
"currencies"]: # range(len(currency_names['currencies'])):
name_list.append((x, currency_names['currencies'][x]))
# instantiate the required input fields and add the current parameters for the genre options
currency = SelectField(choices=[(x, y) for x, y in name_list])
categories = [
'Food & Drinks', 'Health', 'Travel', 'Entertainment', 'Shopping',
'Services'
]
description = StringField('Description')
category = SelectField('Categories', choices=categories)
cost = DecimalField('Cost ($)')
date = DateField('Date', format='%m/%d/%Y')
def get_most_popular_stories(type, period):
url2 = f'https://api.nytimes.com/svc/mostpopular/v2/{type}/{period}.json?api-key=' + api_key
response_most_pop = requests.get(url2).json()
main_functions.save_to_file(response_most_pop, 'JSON_files/most_pop.json')
my_pop_articles = main_functions.read_from_file('JSON_files/most_pop.json')
return my_pop_articles
#print(get_top_stories("arts")) #to test the functions
def mostPop(option1, option2):
url = "https://api.nytimes.com/svc/mostpopular/v2/{0}/{1}.json?api-key=".format(
option1, option2)
url = url + api_key
response = requests.get(url).json()
main_functions.save_to_file(response, "JSON_FILES/response.json")
popArticles = main_functions.read_from_file("JSON_Files/response.json")
str1 = ""
for i in popArticles["results"]:
str1 = str1 + i["abstract"]
return str1
def currency_converter(cost, currency):
float_cost = float(cost)
url = "http://api.currencylayer.com/live?access_key=37a47b066cccdff362e4e654150c43fd"
response = requests.get(url).json()
main_functions.save_to_file(response, "JSON_Documents/response.json")
currencies = main_functions.read_from_file("JSON_Documents/response.json")
if currency != 'USD':
float_cost = float(cost) / float(
currencies["quotes"]["USD" + currency])
converted_cost = "{:.2f}".format(float_cost)
return converted_cost
def currency_converter(cost, currency):
url = "http://api.currencylayer.com/live?"
my_key_dict = main_functions.read_from_file("JSON_Files/api_keys.json")
my_key = "access_key=" + my_key_dict["my_currency_key"]
final_url = url + my_key
get_api = requests.get(final_url).json()
main_functions.save_to_file(get_api, "JSON_Files/response.json")
api_response_dic = main_functions.read_from_file(
"JSON_Files/response.json")
if currency == "USD":
converted_cost = float(cost)
else:
countries = api_response_dic['quotes']
quote = countries[currency]
converted_cost = float(cost) / float(quote)
return round(converted_cost, 2)
def url_name(topic):
url = "https://api.nytimes.com/svc/topstories/v2/{0}.json?api-key=".format(
topic)
url = url + api_key
response = requests.get(url).json()
main_functions.save_to_file(response, "JSON_FILES/response.json")
my_articles = main_functions.read_from_file("JSON_Files/response.json")
str1 = ""
for i in my_articles["results"]:
str1 = str1 + i["abstract"]
return str1
def generate_data(type, response_type):
if (response_type == 'stories'):
response = main_functions.read_from_file("JSON_Files/response.json")
elif (response_type == 'articles'):
response = main_functions.read_from_file("JSON_Files/article_response.json")
str1 = ""
for i in response["results"]:
str1 = str1 + i["abstract"]
sentences = sent_tokenize(str1)
words = word_tokenize(str1)
fdist = FreqDist(words)
words_no_punc = []
for w in words:
if w.isalpha():
words_no_punc.append(w.lower())
fdist2 = FreqDist(words_no_punc)
stopwording = stopwords.words("english")
cleanwords = []
for w in words_no_punc:
if w not in stopwording:
cleanwords.append(w)
fdist3 = FreqDist(cleanwords)
fdist3.most_common(10)
wordcloud = WordCloud().generate(str1)
save_image = wordcloud.to_file('IMAGE_Files/cloud.png')
save_image
data = fdist3.most_common(10)
ind = np.arange(len(data))
names, values = zip(*data)
if (type == 'graph'):
dframe = pd.DataFrame({
'words': names,
'count': values
})
fig = px.line(dframe, x='words', y='count', title='Top 10 Most Common Words')
st.plotly_chart(fig)
if (type == 'wordcloud'):
st.image(Image.open('IMAGE_Files/cloud.png'), caption='Wordcloud', use_column_width = True)
def currency_converter(cost, currency):
url = "http://api.currencylayer.com/live?access_key=7edb40d73b258f5cf730f823f226aa7e"
response = requests.get(url).json()
# create the key for the exchange rate
conversion_to_find = "USD" + currency
# save the response to a json file
response_file_name = "JSON_Files\\currency_list_rates.json"
main_functions.save_to_file(response, response_file_name)
# read the json file and extract all the names in an array of tuples
currency_rates = main_functions.read_from_file(response_file_name)
# extract the relevant exchange rate
rate = currency_rates['quotes'][conversion_to_find]
# exchange formula
converted_cost = cost / Decimal(str(rate))
return converted_cost
st.title("COP 4813 - Project 1")
#Part 1
st.write("Part 1 - Top Stories API")
name = st.text_input("Please enter your name here")
option = st.selectbox("Please select your favorite topic", [
"arts", "automobiles", "books", "business", "fashion", "food", "health",
"home", "insider", "magazine", "movies", "nyregion", "obituaries",
"opinion", "politics", "realestate", "science", "sports", "sundayreview",
"technology", "theater", "t-magazine", "travel", "upshot", "us", "world"
])
name.capitalize() + ', you selected :', option + '.'
api_key_dict = main_functions.read_from_file("JSON_Files/api_key.json")
api_key = api_key_dict["my_key"]
url = "https://api.nytimes.com/svc/topstories/v2/" + option + ".json?api-key=" + api_key
response = requests.get(url).json()
main_functions.save_to_file(response, "JSON_Files/response.json")
my_articles = main_functions.read_from_file("JSON_Files/response.json")
str1 = ""
for i in my_articles["results"]:
str1 = str1 + i["abstract"]
sentences = sent_tokenize(str1)
words = word_tokenize(str1)
import json
import main_functions
import requests
print("Exercise 1 - How many humans are in space right now?")
url1 = "http://api.open-notify.org/astros.json"
#astronauts_json=requests.get(url1).json()
astronauts_filename = "astronauts.json"
#main_functions.save_to_file(astronauts_json,astronauts_filename)
astronauts_in_space = main_functions.read_from_file(astronauts_filename)
print(type(astronauts_in_space))
print(astronauts_in_space.keys())
print("The names of the people in space are: \n")
print(type(astronauts_in_space["people"]))
for i in astronauts_in_space["people"]:
print(i["name"])
for j in sorted(astronauts_in_space['people'], key=lambda x: x["name"]):
print(j["name"])
import json
import requests
import main_functions
print("Exercise 3 - Mars Rover Photos API: \n")
api_key = main_functions.read_from_file("nasa_api_key.json")
my_api_key = api_key["nasa_api_key"]
url4 = "https://api.nasa.gov/mars-photos/api/v1/rovers/curiosity/photos?sol=1000&api_key="
url5 = url4 + my_api_key
#mars_pics=requests.get(url5).json()
#main_functions.save_to_file(mars_pics,"mars_pics.json")
mars_pics = main_functions.read_from_file("mars_pics.json")
print(type(mars_pics))
print(mars_pics.keys())
print(mars_pics["photos"][0].keys())
#Print how many pictures we have:
print(len(mars_pics["photos"]))
for i in mars_pics["photos"]:
print(i["camera"]["full_name"])
#use FHAZ, RHAZ
for j in mars_pics["photos"]:
######################### Imports ################################
import requests
import nltk
import streamlit as st
import main_functions
import pandas as pd
from nltk import word_tokenize
from nltk.probability import FreqDist
from nltk.corpus import stopwords
from wordcloud import WordCloud
import matplotlib.pyplot as plt
######################### Variables ################################
apiKey = main_functions.read_from_file("JSON_Files/api_key.json")["my_key"]
urlTopBase = "https://api.nytimes.com/svc/topstories/v2/"
urlTopEnd = ".json?api-key=" + apiKey
#urlTop = urlTopBase + topic_choice + urlTopEnd
urlPopBase = "https://api.nytimes.com/svc/mostpopular/v2/"
urlPopEnd = ".json?api-key=" + apiKey
#urlPop= urlPopBase + form +"/" + days + urlPopEnd
topicsStr = "arts,automobiles,books,business,fashion,food,health,home,insider,magazine,movies,nyregion,obituaries,opinion,politics,realestate,science,sports,sundayreview,technology,theater,t-magazine,travel,upshot,us,world"
topicsStr = topicsStr.split(",")
topics = [""]
for t in topicsStr:
topics.append(t)
######################### Methods ################################
def get_abstracts():
my_articles = main_functions.read_from_file("JSON_Files/response.json")
all_abstracts = ""
for a in my_articles["results"]:
all_abstracts = all_abstracts + a["abstract"]
return all_abstracts
from flask import Flask, render_template, request, url_for
from flask_pymongo import PyMongo
from flask_wtf import FlaskForm
from wtforms import StringField, DecimalField, SelectField, DateField
import main_functions
# Passes database user without directly revealing it
user_info = main_functions.read_from_file("MongoUser.json")
username = user_info["username"]
password = user_info["password"]
# Links to MongoDB database
app = Flask(__name__)
app.config["SECRET_KEY"] = "KvloanMPIztpjVP8o7cPt-a-wG20Rqe5GvGvskbP"
app.config["MONGO_URI"] = "mongodb+srv://{0}:{1}@project3.5h3on.mongodb.net/" \
"db?retryWrites=true&w=majority".format(username, password)
mongo = PyMongo(app)
# Creates a list of categories
category_list = [
"Employment", "Supplies", "Utilities", "Rent", "Internet", "Phone",
"Advertising", "Events", "Other"
]
# Recreates the category list for use as a flask field
category_list_long = []
for i in category_list:
category_list_long.append((i, i))
import requests
import streamlit as st
import pandas as pd
import main_functions
from wordcloud import WordCloud
import matplotlib.pyplot as plt
# nltk.download("punkt")
# nltk.download("stopwords")
#Author: Andy Naranjo COP4813
# Get API Key
api_key_dic = main_functions.read_from_file("JSON_Files/api_key.json")
api_key = api_key_dic["my_key"]
# Intro body
st.title("COP 4813 - Web Application Programming")
st.title("Project - 1")
st.subheader("Part A - The Stories API")
st.write(
"This app uses the Top Stories API to display the most common words used in the top current articles based on a"
" specified topic selected by the user. The data is displayed as a line chart and as a wordcloud image."
)
# Creates and input field and the topic options select box
st.subheader("I - Topic Selection")
userName = st.text_input(label="Please enter your name:",
value='',
max_chars=None,
key=None,
type='default')
from nltk import word_tokenize
from nltk import pprint
from nltk.probability import FreqDist
from nltk.corpus import stopwords
import main_functions
from wordcloud import WordCloud
import matplotlib.pyplot as plt
import streamlit as st
import numpy as np
import pandas as pd
# nltk.download("punkt")
# nltk.download("stopwords")
# extract the api key fromthe json file
api_key_dict = main_functions.read_from_file("JSON_Files/api_key.json")
api_key = api_key_dict["my_key"]
# general formatting for the web page using streamlit
st.title("COP 4813 - Web Application Programming")
st.title("Project 1")
st.header("Part A - The Stories API")
st.subheader("This app uses the Top Stories API to display the most common words used in the top current articles "
"based on a specified topic selected by the user. The data is displayed as a line chart and as a "
"wordcloud image.")
st.subheader("")
st.header("**I - Topic Selection**")
# input for the first portion, the users name and the desired topic
name = st.text_input("Please enter your name")
import main_functions
import requests
import os.path
#Deserializes api key that is in .json format
myKey = main_functions.read_from_file("api_key.json")
api_key = myKey['apikey']
#The first header requests data in .json and the second passes the deserialized api key
headers = {'Content-Type': 'application/json', 'apikey': api_key}
#Within the response lib you can pass headers and params as a dic. Can also be a tuple.
params = {
'q': '',
'location': 'United States',
'search_engine': 'google.com',
'gl': 'US',
'hl': 'en',
'num': '10'
}
#Asks user for beauty product
productQ = input("What beauty product will you like to look for? : ")
print('Your product is', productQ)
params['q'] = productQ
#This will use request lib to make a custom url request.
#params will add "?" before first parameter "q".
#Output will be handled by .json function so that we may save it using main_functions/
response = requests.get('https://app.zenserp.com/api/v2/search',
headers=headers,
import json
import main_functions
import requests
my_nasa_api = main_functions.read_from_file(("nasa_api.json"))
my_nasa_api = my_nasa_api["nasa_api"]
url = "https://api.nasa.gov/planetary/apod?api_key="
url2 = url + my_nasa_api
# apod = requests.get(url2).json()
# main_functions.save_to_file(apod,"apod.json")
apod = main_functions.read_from_file("apod.json")
print(type(apod))
print(apod.keys())
print(apod["url"])
print(apod["explanation"])
import json
import main_functions
import requests
url = "http://api.open-notify.org/astros.json"
# astronauts_in_space = requests.get(url).json()
astronauts_filename = "astronauts.json"
# astronauts_dict = main_functions.save_to_file(astronauts_in_space,astronauts_filename)
astronauts_dict = main_functions.read_from_file(astronauts_filename)
print(type(astronauts_dict))
print(astronauts_dict.keys())
print(len(astronauts_dict))
print(type(astronauts_dict["message"]))
print(type(astronauts_dict["people"]))
print(type(astronauts_dict["number"]))
for i in astronauts_dict["people"]:
print(i["name"])
import requests
import json
import main_functions
import nltk
from nltk import sent_tokenize
from nltk import word_tokenize
from nltk.probability import FreqDist
from nltk.corpus import stopwords
from pprint import pprint
from wordcloud import WordCloud
import matplotlib.pyplot as plt
#nltk.download("punkt")
#nltk.download("stopwords")
api_key_dict = main_functions.read_from_file(
"JSON_File/api_key.json") # Assigns api_key_dict with the value that
# read_from_file method will return from
# the main_functions
api_key = api_key_dict["my_key"] # Assigns api_key with the value inside of
# json file that has the keyword "my_key"
st.title("COP4813 - Web Application Programming") # Displays a title
st.title("Project 1") # Displays a title
st.header("Part A - The Stories API") # Displays a header
st.write(
"This app uses the Top Stories API to display the most common words used in the top current"
" articles based on a specific topic selected by the user. The data is displayed as a line chart and"
import streamlit as st
import main_functions
import requests
st.title("Detect languages")
st.header("Please type a sentence in any language")
lang_list = main_functions.read_from_file("lang_list.json")
sent = st.text_input("Enter sentence")
if sent:
sent = sent.replace(" ", "+")
api_key = main_functions.read_from_file("api_key.json")
my_key = api_key["my_key"]
url = "https://ws.detectlanguage.com/0.2/detect?q=" + sent + "&key=" + my_key
response = requests.get(url).json()
conf = 10000
lang = ""
for i in response["data"]["detections"]:
if i['confidence'] < conf:
conf, lang = i['confidence'], i['language']
for i in lang_list:
if i["code"] == lang:
lang = i["name"].title()
st.text(
"in the top current articles based on a specified topic selected by the user"
)
st.text("The data is displayed as a line chart and as a wordcloud image.")
st.header("I - Topic Selection")
full_name = st.text_input("Enter name")
topics = st.selectbox("Pick a topic.", [
"", "arts", "automobiles", "books", "business", "fashion", "food",
"health", "home", "insider", "magazine", "movies", "ny region",
"obituaries", "opinion", "politics", "real estate", "science", "sports",
"sunday review", "technology", "theater", "t-magazine", "travel", "upshot",
"us", "world"
])
if full_name and topics:
api_key_dict = main_functions.read_from_file("json_files/api_key.json")
api_key = api_key_dict["my_key"]
url = "https://api.nytimes.com/svc/topstories/v2/" + topics + ".json?api-key=" + api_key
response = requests.get(url).json()
main_functions.save_to_file(response, "json_files/response.json")
results = main_functions.read_from_file("json_files/response.json")
firststring = ""
for i in results["results"]:
firststring = firststring + i["abstract"]
words = word_tokenize(firststring)
no_punc = []
for w in words:
if w.isalpha():
from flask import Flask, render_template, request, url_for
from flask_pymongo import PyMongo
from flask_wtf import FlaskForm
import requests
from wtforms import StringField, DecimalField, SelectField, DateField
import main_functions
credentials = main_functions.read_from_file("credentials.json")
password = credentials["password"]
connection_string = "mongodb+srv://Jordy:{0}@project3.rqprq.mongodb.net/Project3?retryWrites=true&w=majority".format(
password)
app = Flask(__name__)
app.config["SECRET_KEY"] = "COP4813"
app.config["MONGO_URI"] = connection_string
mongo = PyMongo(app)
class Expenses(FlaskForm):
description = StringField('Description')
category = SelectField('Category',
choices=[('日本語', '日本語'), ('ストロングゼロ', 'ストロングゼロ'),
('ライトノベル', 'ライトノベル'), ('𠮷野家', '𠮷野家'),
('大学', '大学'), ('コンピューター', 'コンピューター'),
('フライト', 'フライト'), ('電話', '電話'),
('動機', '動機'), ('生活', '生活')])
cost = DecimalField('Cost')
date = DateField('Date')
# TO BE COMPLETED (please delete the word pass above)
def get_top_stories(option):
url = f'https://api.nytimes.com/svc/topstories/v2/{option}.json?api-key=' + api_key
response = requests.get(url).json()
main_functions.save_to_file(response, 'JSON_files/response.json')
my_articles = main_functions.read_from_file('JSON_files/response.json')
return my_articles
import requests
import main_functions
from flask import Flask, render_template, request
from flask_pymongo import PyMongo
from flask_wtf import FlaskForm
from wtforms import StringField, DecimalField, SelectField, DateField
app = Flask(__name__)
credentials = main_functions.read_from_file("JSON_Documents/credentials.json")
username = credentials["username"]
password = credentials["password"]
app.config["SECRET_KEY"] = "010296db"
app.config[
"MONGO_URI"] = "mongodb+srv://{0}:{1}@cluster0.rhhi3.mongodb.net/db?retryWrites=true&w=majority".format(
username, password)
mongo = PyMongo(app)
class Expenses(FlaskForm):
description = StringField('description')
category = SelectField('category',
choices=[('rent', 'Rent'),
('electricity', 'Electricity'),
('water', 'Water'),
('insurance', 'Insurance'),
('internet', 'Internet'),
('restaurants', 'Restaurants'),
('groceries', 'Groceries'), ('gas', 'Gas'),
('college', 'College'), ('party', 'Party'),
('mortgage', 'Mortgage')])
cost = DecimalField('cost', places=2)
import json
import main_functions
import requests
print("Example 1 - How many astronauts are in space right now")
url = "http://api.open-notify.org/astros.json"
astronauts_json = requests.get(url).json()
#main_functions.save_to_file("astronauts.json", astronauts_json)
astronauts_in_space = main_functions.read_from_file("astronauts.json")
for i in astronauts_in_space['people']:
print(i['name'])
from nltk import sent_tokenize
from nltk import word_tokenize
from nltk.probability import FreqDist
from nltk.corpus import stopwords
import main_functions
from pprint import pprint
from wordcloud import WordCloud
import matplotlib.pyplot as plt
from bokeh.plotting import figure
from PIL import Image
import time
import numpy as np
import pandas as pd
import plotly.express as px
api_key_dict = main_functions.read_from_file("JSON_Files/api_key.json")
api_key = api_key_dict["my_key"]
def api_call(api_type, type, time_period):
if (api_type == 'stories'):
url = 'https://api.nytimes.com/svc/topstories/v2/'+ type + '.json?api-key=' + api_key
response = requests.get(url).json()
main_functions.save_to_file(response, "JSON_Files/response.json")
elif (api_type == 'articles'):
url = 'https://api.nytimes.com/svc/mostpopular/v2/' + type + '/' + time_period + '.json?api-key=' + api_key
response = requests.get(url).json()
main_functions.save_to_file(response, "JSON_Files/article_response.json")
def generate_data(type, response_type):
if (response_type == 'stories'):
import json
import main_functions
import requests
api_key_dict = main_functions.read_from_file('JSON_files/api_key.json')
api_key = api_key_dict['my_key']
#Top stories
def get_top_stories(option):
url = f'https://api.nytimes.com/svc/topstories/v2/{option}.json?api-key=' + api_key
response = requests.get(url).json()
main_functions.save_to_file(response, 'JSON_files/response.json')
my_articles = main_functions.read_from_file('JSON_files/response.json')
return my_articles
#Most viewed, shared, or emailed articles
def get_most_popular_stories(type, period):
url2 = f'https://api.nytimes.com/svc/mostpopular/v2/{type}/{period}.json?api-key=' + api_key
response_most_pop = requests.get(url2).json()
main_functions.save_to_file(response_most_pop, 'JSON_files/most_pop.json')
my_pop_articles = main_functions.read_from_file('JSON_files/most_pop.json')
return my_pop_articles
#print(get_top_stories("arts")) #to test the functions
import streamlit as st
import nltk
from nltk import word_tokenize
from nltk.probability import FreqDist
from nltk.corpus import stopwords
import requests
import main_functions
from wordcloud import WordCloud
import matplotlib.pyplot as plt
nltk.download("punkt")
nltk.download("stopwords")
# Extract API_key from api_key.jason
api_key_dict = main_functions.read_from_file("JSON_Files/api_key.json")
my_api_key = api_key_dict["my_api_key"]
# Display Title
st.title("COP 4813 - Web Application Programming")
st.title("Project 1")
# Part A - The Stories API
st.header("Part A - The Stories API")
st.write(
"This app uses the top stories API to display the most common words used in the top current "
"articles based on a specific topic selected by the user. The data is displayed as a line chart and "
"as a wordcloud image.")
# Topic Selection
import main_functions
import requests
url = "https://api.nasa.gov/mars-photos/api/v1/rovers/curiosty/photos?sol=1000&api_key="
nasa_api_dict = main_functions.read_from_file("nasa_api.json")
my_api_key = nasa_api_dict["nasa_api.json"]
url2 = url + my_api_key
mars_pics = requests.get(url2).json
main_functions.save_to_file(mars_pics, "mars_pics.json")
mars_pics = main_functions.read_from_file("mars_pics.json")
print(mars_pics.keys())
print(type(mars_pics["photos"]))
print(mars_pics["photos"][0].keys())
print(len(mars_pics["photos"]))
print(type(mars_pics["photos"][0]["camera"]))
print(mars_pics["photos"][0]["camera"].keys())
for i in mars_pics["photos"]:
print(i["camera"]["full_name"])
