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ChatGPT Helped Python Tweepy my Tweets Onto My Website

I used the Python package Tweepy and the ChatGPT assisted coding session to successfully access the Twitter API and pull 3K of my 11K tweets since 2007. I've posted the code on my website, and I've also created a CSV file of all the tweets I pulled. Come check out my website to see how I did it!

Successfully Pulled 3K of My 11K Tweets Using Python and ChatGPT!

By Michael Levin

Friday, January 27, 2023

It’s amazing to me that I don’t have it documented here in this journal yet, but a few days ago, I hit the Twitter API using the Python tweepy package and it went well. I only got about 3K of my 11K tweets since 2007, but it’s a start. Here’s the page https://mikelev.in/tweets/ and here’s the code. It’s going to need some cleanup, but it’s a start.

ChatGPT Assisted Coding Session, Hitting Twitter API

import tweepy
import pandas as pd
from sqlitedict import SqliteDict as sqldict

with open("creds/twitter.txt", "rt") as fh:
    api_key, api_key_secret, bearer_token = fh.read().split("\n")

auth = tweepy.OAuth2BearerHandler(bearer_token)
api = tweepy.API(auth)

username = "miklevin"

# Technique 1
with sqldict("tweets/raw_backfill.db") as db:
    max_id = None
    while True:
        tweets = api.user_timeline(
            screen_name=username, tweet_mode="extended", count=200, max_id=max_id
        if len(tweets) == 0:
        db[str(max_id)] = tweets
        max_id = tweets[-1].id - 1

# Technique 2
with sqldict("tweets/raw2_backfill.db") as db:
    max_id = 7567832972707979263
    for page in tweepy.Cursor(api.user_timeline, screen_name=username, max_id=max_id).pages():
        if len(tweets) == 0:
        db[str(max_id)] = tweets
        max_id = tweets[-1].id - 1

with sqldict("tweets/raw2_backfill.db") as db:
    for key in db:

with sqldict("tweets/raw_backfill.db") as db:
    with sqldict("tweets/tweets.db") as db2:
        for max_id in db:
            tweets = db[max_id]
            for tweet in tweets:
                db2[tweet.id_str] = tweet

table = []
with sqldict("tweets/tweets.db") as db:
    for i, tweet_id in enumerate(db):
        tweet = db[tweet_id]
        id = tweet.id
        created_at = tweet.created_at
        full_text = tweet.full_text
        url = f"https://twitter.com/miklevin/status/{id}"
        row = (id, created_at, full_text, url)

columns = ["id", "created_at", "full_text", "url"]

df = pd.DataFrame(table, columns=columns)

df.to_csv("tweets/tweets.csv", index=False)

front_matter = """---
title: Tweets
group: homepage
permalink: /tweets/
description: A page of all my tweets.


with open("../hide/MikeLev.in/tweets.md", "wt") as fh:

with open("../hide/MikeLev.in/tweets.md", "at") as fh:
    for i, row in enumerate(table):
        id, created_at, full_text, url = row
        fh.write(f"\n\n## {created_at}")