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Twitter Profile Scraper

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Twitter Profile Scraper

Twitter Profile Scraper

epctex/twitter-profile-scraper
Try for free

3 days trial then $10.00/month - No credit card required now

Scrape any Twitter profile of any user. Extract tweets, replies, favorites, retweets, conversation threads and many more without any limit. Gather user related information such as verification, location, profile image, friends, followers, following and much more! No limits on Twitter!

You can access the Twitter Profile Scraper programmatically from your own Python applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "startUrls": ["https://twitter.com/apify"],
10    "maxTweetsPerUser": 100,
11    "customMapFunction": "(object) => { return {...object} }",
12    "proxy": { "useApifyProxy": True },
13}
14
15# Run the Actor and wait for it to finish
16run = client.actor("epctex/twitter-profile-scraper").call(run_input=run_input)
17
18# Fetch and print Actor results from the run's dataset (if there are any)
19print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
20for item in client.dataset(run["defaultDatasetId"]).iterate_items():
21    print(item)
22
23# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Twitter Profile Scraper API in Python

The Apify API client for Python is the official library that allows you to use Twitter Profile Scraper API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

pip install apify-client

Other API clients include:

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Maintained by Community

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  • 158 monthly users

  • 19 stars

  • 99% runs succeeded

  • 21 hours response time

  • Created in Jul 2022

  • Modified 17 hours ago