Twitter streaming library based on tweepy api
Python twitter streamer is a script that searches and downloads tweets in the real time (limited to 1 request/3s). The tweets are stored as a gzip compressed text file with json inside. The script stores the data in chunks of one day. This is done to clear the RAM and optimize the portability of the data.
In order for this script to work, you need to add your credentials to the TOKENS.txt file. (Use TOKENS.txt.example as your reference)
This script is designed to run to without interruption for extended period of time. All data is stored in a given folder. It is also fail tolerant. In order to stop the script, press "ctrl+c" twice or simply kill the process.
Download or clone the package and follow the usage instructions to run it.
Before using this scrip, follow the guidelines defined on Twitter site to obtain Tokens. They are authorization keys to streaming Twitter API. Follow these guidelines: https://dev.twitter.com/oauth/overview/application-owner-access-tokens
After the step above, add the tokens to local TOKENS.txt file (use TOKENS.txt.example as a reference). Make sure to keep this file secured and do not publish it anywhere. You might want to use "chmod -400 TOKENS.txt" if you are on Linux system. It will limit access to the file.
- Tweepy - https://github.com/tweepy/tweepy
pip install tweepy
$ python tweet_streamer.py <output_datafolder_path> <search_phrase1> [search_phrase2] [search_..n]
where: output_datafolder_path - path to a directory where the data will be stored search_phrase - a phrase or a sequence of phrases that will be used to search and retrieve tweets.
For example: in order to stream all news tweets related to the election in the USA, use the following command.
$ python tweet_streamer.py my_data/ news usa election
The data is stored in zipped gzip files. Each file contains one day of streaming. This approach will make data management much easier. The tweets itself are in json string representation (python dictionary). They are unaltered and contain information such as location, re-tweets, etc. An example of reading and working with the data can be found in tweet_data_reader.py
Copyright (c) 2017 Denys Katerenchuk
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