import requests as r import pprint as pprint from github import Github import pandas as pd import numpy as np # or using an access token g = Github("XXXXXXXXXXXXXXXX") #create a loading pipeline import requests from pprint import pprint # github username username = "risenW" #check validation #url to request url = f"https://api.github.com/users/{username}" # make the request and return the json user_data = requests.get(url).json() user = g.get_user(username) for repo in user.get_repos(): reposs = repo lan = repo.language l = str(lan) data = {'name': user_data['name'], 'num_repo' : user_data['public_repos'] } df = pd.DataFrame(data, columns = ['name','num_repo'],index=[0]) print(df) engine = sqlalchemy.create_engine(DATABASE_LOCATION) conn = sqlite3.connect('my_played_tracks.sqlite') cursor = conn.cursor() sql_query = """CREATE TABLE IF NOT EXISTS my_played_tracks( name VARCHAR(200), repo VARCHAR(200), CONSTRAINT primary_key_constraint PRIMARY KEY (name, repo) ) """ cursor.execute(sql_query) print("Opened database successfully") try: df.to_sql("my_played_tracks", engine, index=False, if_exists='append') except: print("Data already exists in the database") conn.close() print("Close database successfully") # #load to a google big query datawarehouse

from pandas.io import gbq

import sqlalchemy from sqlalchemy.orm import sessionmaker import sqlite3

DATABASE_LOCATION = "sqlite:///my_played_tracks.sqlite"

df.to_gbq(destination_table = 'sample.sample', project_id = 'thread-290523', if_exists = 'replace')