Hugo Ewalds Twitter scraper

This is my twist on the already fantastic Twitter scraper by Brendan Brown. I've added several other scripts which gives you the possibility tto scrape mentions and search for tweets. They work basically the same as the original scraper.

Twitter Scraper

Twitter makes it hard to get all of a user's tweets (assuming they have more than 3200). This is a way to get around that using Python, Selenium, and Tweepy.

Essentially, we will use Selenium to open up a browser and automatically visit Twitter's search page, searching for a single user's tweets on a single day. If we want all tweets from 2015, we will check all 365 days / pages. This would be a nightmare to do manually, so the scrape.py script does it all for you - all you have to do is input a date range and a twitter user handle, and wait for it to finish.

The scrape.py script collects tweet ids. If you know a tweet's id number, you can get all the information available about that tweet using Tweepy - text, timestamp, number of retweets / replies / favorites, geolocation, etc. Tweepy uses Twitter's API, so you will need to get API keys. Once you have them, you can run the get_metadata.py script.

Requirements

• basic knowledge on how to use a terminal
• Safari 10+ with 'Allow Remote Automation' option enabled in Safari's Develop menu to control Safari via WebDriver.
• python3
  • to check, in your terminal, enter python3
  • if you don't have it, check YouTube for installation instructions
• pip or pip3
  • to check, in your terminal, enter pip or pip3
  • if you don't have it, again, check YouTube for installation instructions
• selenium (3.0.1)
  • pip3 install selenium
• tweepy (3.5.0)
  • pip3 install tweepy

Running the scraper

• open up scrape.py and edit the user, start, and end variables (and save the file)
• run python3 scrape.py
• you'll see a browser pop up and output in the terminal
• do some fun other task until it finishes
• once it's done, it outputs all the tweet ids it found into all_ids.json
• every time you run the scraper with different dates, it will add the new ids to the same file
  • it automatically removes duplicates so don't worry about small date overlaps

Troubleshooting the scraper

• do you get a no such file error? you need to cd to the directory of scrape.py
• do you get a driver error when you try and run the script?
  • open scrape.py and change the driver to use Chrome() or Firefox()
    • if neither work, google the error (you probably need to install a new driver)
• does it seem like it's not collecting tweets for days that have tweets?
  • open scrape.py and change the delay variable to 2 or 3

Getting the metadata

• first you'll need to get twitter API keys
  • sign up for a developer account here https://dev.twitter.com/
  • get your keys here: https://apps.twitter.com/
• put your keys into the sample_api_keys.json file
• change the name of sample_api_keys.json to api_keys.json
• open up get_metadata.py and edit the user variable (and save the file)
• run python3 get_metadata.py
• this will get metadata for every tweet id in all_ids.json
• it will create 4 files
  • username.json (master file with all metadata)
  • username.zip (a zipped file of the master file with all metadata)
  • username_short.json (smaller master file with relevant metadata fields)
  • username.csv (csv version of the smaller master file)