This repo is a collection of Jupyter Notebooks in which I try to collect data using APIs and web scraping. These examples are for educational purposes only.
cookie-parser- Library for setting, accessing, and clearing cookies on request and response objects.dotenv- Library for populating environment variables from a.envfile.express- Lightweight web framework.superagent- Library for making HTTP requests.
beautifulsoup- Library for web scraping that makes parsing HTML content a breeze.environs- Library for reading in environment varbiales.google-api-python-client- Library for interacting with various Google APIs with Python.jupyterlab- Library for running a Jupyter Lab server and Jupyter Notebooks.requests- Library for making HTTP requests.selenium- Library for controlling web browsers.
This scraper gathers details for available seasons and episodes featured on a specific show's page on AdultSwim.com.
This scraper goes through the housing page of Seattle's Craigslist and collects the titles of all of the listings on the first page of listings.
This scraper takes in an Instagram profile name. If the user's profile is public, the scraper will download every photo available on their profile.
This scraper takes in the URL to a Medium article and scrapes the text content of the article. The text content is then written to a Markdown file.
This lightweight server goes through the auth process for generating account-approved access tokens as described in TMDB API version 4's documentation. Once the access token has been generated it makes a quick request to retrieve info about every list the user has created (even private lists).
This scraper attempts to locate areas where citations are needed within a specific article on Wikipedia.
This is an example of using a library to access API data from YouTube without having to make the API calls directly with a tool like requests.