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https://github.com/taspinar/twitterscraper

Scrape Twitter for Tweets
https://github.com/taspinar/twitterscraper

Last synced: about 2 months ago
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Scrape Twitter for Tweets

Host: GitHub
URL: https://github.com/taspinar/twitterscraper
Owner: taspinar
License: mit
Created: 2016-06-16T06:51:10.000Z (over 8 years ago)
Default Branch: master
Last Pushed: 2022-10-05T15:48:52.000Z (almost 2 years ago)
Last Synced: 2024-07-19T07:54:50.338Z (2 months ago)
Language: Python
Homepage:
Size: 1.23 MB
Stars: 2,392
Watchers: 87
Forks: 581
Open Issues: 144
Metadata Files:
- Readme: README.rst
- Changelog: changelog.txt
- License: LICENSE

Awesome Lists containing this project

README

.. |Downloads| image:: https://pepy.tech/badge/twitterscraper
:target: https://pepy.tech/project/twitterscraper
.. |Downloads_month| image:: https://pepy.tech/badge/twitterscraper/month
:target: https://pepy.tech/project/twitterscraper/month
.. |PyPI version| image:: https://badge.fury.io/py/twitterscraper.svg
:target: https://badge.fury.io/py/twitterscraper
.. |GitHub contributors| image:: https://img.shields.io/github/contributors/taspinar/twitterscraper.svg
:target: https://github.com/taspinar/twitterscraper/graphs/contributors

Backers
========

Thank you to all our backers! 🙏 [`Become a backer`_]

Sponsors
========

Support this project by becoming a sponsor. Your logo will show up here
with a link to your website. [`Become a sponsor`_]

.. _Become a backer: https://opencollective.com/twitterscraper#backer
.. _Become a sponsor: https://opencollective.com/twitterscraper#sponsor

Synopsis
========

A simple script to scrape Tweets using the Python package ``requests``
to retrieve the content and ``Beautifulsoup4`` to parse the retrieved
content.

1. Motivation
=============

Twitter has provided `REST
API's `__ which can be used by
developers to access and read Twitter data. They have also provided a
`Streaming API `__ which can
be used to access Twitter Data in real-time.

Most of the software written to access Twitter data provide a library
which functions as a wrapper around Twitter's Search and Streaming API's
and are therefore constrained by the limitations of the API's.

With Twitter's Search API you can only send 180 Requests every 15
minutes. With a maximum number of 100 tweets per Request, you
can mine 72 tweets per hour (4 x 180 x 100 =72) . By using
TwitterScraper you are not limited by this number but by your internet
speed/bandwith and the number of instances of TwitterScraper you are
willing to start.

One of the bigger disadvantages of the Search API is that you can only
access Tweets written in the **past 7 days**. This is a major bottleneck
for anyone looking for older data. With TwitterScraper there is no such
limitation.

Per Tweet it scrapes the following information:
+ Tweet-id
+ Tweet-url
+ Tweet text
+ Tweet html
+ Links inside Tweet
+ Hashtags inside Tweet
+ Image URLS inside Tweet
+ Video URL inside Tweet
+ Tweet timestamp
+ Tweet Epoch timestamp
+ Tweet No. of likes
+ Tweet No. of replies
+ Tweet No. of retweets
+ Username
+ User Full Name / Screen Name
+ User ID
+ Tweet is an reply to
+ Tweet is replied to
+ List of users Tweet is an reply to
+ Tweet ID of parent tweet

In addition it can scrape for the following user information:
+ Date user joined
+ User location (if filled in)
+ User blog (if filled in)
+ User No. of tweets
+ User No. of following
+ User No. of followers
+ User No. of likes
+ User No. of lists
+ User is verified

2. Installation and Usage
=========================

To install **twitterscraper**:

.. code:: python

(sudo) pip install twitterscraper

or you can clone the repository and in the folder containing setup.py

.. code:: python

python setup.py install

If you prefer more isolation you can build a docker image

.. code:: python

docker build -t twitterscraper:build .

and run your container with:

.. code:: python

docker run --rm -it -v/:/app/data twitterscraper:build

2.2 The CLI
-----------

You can use the command line application to get your tweets stored to
JSON right away. Twitterscraper takes several arguments:

- ``-h`` or ``--help`` Print out the help message and exits.

- ``-l`` or ``--limit`` TwitterScraper stops scraping when *at least*
the number of tweets indicated with ``--limit`` is scraped. Since
tweets are retrieved in batches of 20, this will always be a multiple
of 20. Omit the limit to retrieve all tweets. You can at any time abort the
scraping by pressing Ctrl+C, the scraped tweets will be stored safely
in your JSON file.

- ``--lang`` Retrieves tweets written in a specific language. Currently
30+ languages are supported. For a full list of the languages print
out the help message.

- ``-bd`` or ``--begindate`` Set the date from which TwitterScraper
should start scraping for your query. Format is YYYY-MM-DD. The
default value is set to 2006-03-21. This does not work in combination with ``--user``.

- ``-ed`` or ``--enddate`` Set the enddate which TwitterScraper should
use to stop scraping for your query. Format is YYYY-MM-DD. The
default value is set to today. This does not work in combination with ``--user``.

- ``-u`` or ``--user`` Scrapes the tweets from that users' profile page.
This also includes all retweets by that user. See section 2.2.4 in the examples below
for more information.

- ``--profiles`` : Twitterscraper will in addition to the tweets, also scrape for the profile
information of the users who have written these tweets. The results will be saved in the
file userprofiles_.

- ``-p`` or ``--poolsize`` Set the number of parallel processes
TwitterScraper should initiate while scraping for your query. Default
value is set to 20. Depending on the computational power you have,
you can increase this number. It is advised to keep this number below
the number of days you are scraping. For example, if you are
scraping from 2017-01-10 to 2017-01-20, you can set this number to a
maximum of 10. If you are scraping from 2016-01-01 to 2016-12-31, you
can increase this number to a maximum of 150, if you have the
computational resources. Does not work in combination with ``--user``.

- ``-o`` or ``--output`` Gives the name of the output file. If no
output filename is given, the default filename 'tweets.json' or 'tweets.csv'
will be used.

- ``-c`` or ``--csv`` Write the result to a CSV file instead of a JSON file.

- ``-d`` or ``--dump``: With this argument, the scraped tweets will be
printed to the screen instead of an outputfile. If you are using this
argument, the ``--output`` argument doe not need to be used.

- ``-ow`` or ``--overwrite``: With this argument, if the output file already exists
it will be overwritten. If this argument is not set (default) twitterscraper will
exit with the warning that the output file already exists.

- ``-dp`` or ``--disableproxy``: With this argument, proxy servers are not used when scrapping tweets or user profiles from twitter.

2.2.1 Examples of simple queries
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Below is an example of how twitterscraper can be used:

``twitterscraper Trump --limit 1000 --output=tweets.json``

``twitterscraper Trump -l 1000 -o tweets.json``

``twitterscraper Trump -l 1000 -bd 2017-01-01 -ed 2017-06-01 -o tweets.json``

2.2.2 Examples of advanced queries
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can use any advanced query Twitter supports. An advanced query
should be placed within quotes, so that twitterscraper can recognize it
as one single query.

Here are some examples:

- search for the occurence of 'Bitcoin' or 'BTC':
``twitterscraper "Bitcoin OR BTC" -o bitcoin_tweets.json -l 1000``
- search for the occurence of 'Bitcoin' and 'BTC':
``twitterscraper "Bitcoin AND BTC" -o bitcoin_tweets.json -l 1000``
- search for tweets from a specific user:
``twitterscraper "Blockchain from:VitalikButerin" -o blockchain_tweets.json -l 1000``
- search for tweets to a specific user:
``twitterscraper "Blockchain to:VitalikButerin" -o blockchain_tweets.json -l 1000``
- search for tweets written from a location:
``twitterscraper "Blockchain near:Seattle within:15mi" -o blockchain_tweets.json -l 1000``

You can construct an advanced query on `Twitter Advanced Search `__ or use one of the operators shown on `this page `__.
Also see `Twitter's Standard operators `__

2.2.3 Examples of scraping user pages
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can also scraped all tweets written or retweeted by a specific user.
This can be done by adding the boolean argument ``-u / --user`` argument.
If this argument is used, the search term should be equal to the username.

Here is an example of scraping a specific user:

``twitterscraper realDonaldTrump --user -o tweets_username.json``

This does not work in combination with ``-p``, ``-bd``, or ``-ed``.

The main difference with the example "search for tweets from a specific user" in section 2.2.2 is that this method really scrapes
all tweets from a profile page (including retweets).
The example in 2.2.2 scrapes the results from the search page (excluding retweets).

2.3 From within Python
----------------------

You can easily use TwitterScraper from within python:

from twitterscraper import query_tweets

if __name__ == '__main__':
list_of_tweets = query_tweets("Trump OR Clinton", 10)

#print the retrieved tweets to the screen:
for tweet in query_tweets("Trump OR Clinton", 10):
print(tweet)

#Or save the retrieved tweets to file:
file = open(“output.txt”,”w”)
for tweet in query_tweets("Trump OR Clinton", 10):
file.write(str(tweet.text.encode('utf-8')))
file.close()

2.3.1 Examples of Python Queries
--------------------------------

- Query tweets from a given URL:
Parameters:
- query: The query search parameter of url
- lang: Language of queried url
- pos: Parameter passed for where to start looking in url
- retry: Number of times to retry if error

.. code:: python

query_single_page(query, lang, pos, retry=50, from_user=False, timeout=60)

- Query all tweets that match qeury:
Parameters:
- query: The query search parameter
- limit: Number of tweets returned
- begindate: Start date of query
- enddate: End date of query
- poolsize: Tweets per poolsize
- lang: Language of query

.. code:: python

query_tweets('query', limit=None, begindate=dt.date.today(), enddate=dt.date.today(), poolsize=20, lang='')

- Query tweets from a specific user:
Parameters:
- user: Twitter username
- limit: Number of tweets returned

.. code:: python

query_tweets(user, limit=None)

2.4 Scraping for retweets
----------------------

A regular search within Twitter will not show you any retweets.
Twitterscraper therefore does not contain any retweets in the output.

To give an example: If user1 has written a tweet containing ``#trump2020`` and user2 has retweetet this tweet,
a search for ``#trump2020`` will only show the original tweet.

The only way you can scrape for retweets is if you scrape for all tweets of a specific user with the ``-u / --user`` argument.

2.5 Scraping for User Profile information
----------------------
By adding the argument ``--profiles`` twitterscraper will in addition to the tweets, also scrape for the profile information of the users who have written these tweets.
The results will be saved in the file "userprofiles_".

Try not to use this argument too much. If you have already scraped profile information for a set of users, there is no need to do it again :)
It is also possible to scrape for profile information without scraping for tweets.
Examples of this can be found in the examples folder.

3. Output
=========

All of the retrieved Tweets are stored in the indicated output file. The
contents of the output file will look like:

[{"fullname": "Rupert Meehl", "id": "892397793071050752", "likes": "1", "replies": "0", "retweets": "0", "text": "Latest: Trump now at lowest Approval and highest Disapproval ratings yet. Oh, we're winning bigly here ...\n\nhttps://projects.fivethirtyeight.com/trump-approval-ratings/?ex_cid=rrpromo\u00a0\u2026", "timestamp": "2017-08-01T14:53:08", "user": "Rupert_Meehl"}, {"fullname": "Barry Shapiro", "id": "892397794375327744", "likes": "0", "replies": "0", "retweets": "0", "text": "A former GOP Rep quoted this line, which pretty much sums up Donald Trump. https://twitter.com/davidfrum/status/863017301595107329\u00a0\u2026", "timestamp": "2017-08-01T14:53:08", "user": "barryshap"}, (...)
]

3.1 Opening the output file
---------------------------

In order to correctly handle all possible characters in the tweets
(think of Japanese or Arabic characters), the output is saved as utf-8
encoded bytes. That is why you could see text like
"\u30b1 \u30f3 \u3055 \u307e \u30fe ..." in the output file.

What you should do is open the file with the proper encoding:

.. figure:: https://user-images.githubusercontent.com/4409108/30702318-f05bc196-9eec-11e7-8234-a07aabec294f.PNG

Example of output with Japanese characters

3.1.2 Opening into a pandas dataframe
---------------------------

After the file has been opened, it can easily be converted into a ```pandas``` DataFrame

import pandas as pd
df = pd.read_json('tweets.json', encoding='utf-8')