A package for management of filtering queries of the Twitter API
Project description
TwiGet
TwiGet is a python package for the management of the queries on filtered stream of the Twitter API, and the collection of tweets from it.
It can be used as a command line tool (twiget-cli
) or as a python class (TwiGet
).
Installation
> pip install twiget
The command installs the package and also makes the twiget-cli
command available.
Command line tool: twiget-cli
TwiGet implements a command line interface that can be started with the command:
> twiget-cli
When launched without arguments the program searches for a .twiget.conf
file in the HOME
directory (the directory pointed by the $HOME
or %userprofile%
environment variable).
The file must contain in the first line the bearer token that allows the program to access the Twitter API.
Alternatively, the name of the file from which to obtain the bearer token can be given as argument when starting the program:
> twiget-cli -b path_to_file/with_token.txt
NOTE: store the bearer token in a file with minimum access permissions. Never share it. Revoke any tokens that may have been made public.
Another optional argument is the path where to save collected tweets.
By default, a data
subdirectory is created in the current working directory.
> twiget-cli -s ./save_dir
prompt
When started, twiget-cli shown the available commands, and the queries currently registered for the given bearer token (queries are permanently stored on Twitter's servers).
TwiGet 0.1.1
Available commands (type help <command> for details):
create, delete, exit, help, list, refresh, save_to, size, start, stop
Registered queries:
ID=1385892384573355842 query="#usa" tag="usa"
ID=1405490304970434817 query="bts" tag="bts"
The command prompt tells if twiget-cli is currently collecting tweets, the number of collected tweets, and the save path.
[not collecting (0 since last start), save path "data"]>
When collecting tweets, the prompt is automatically refreshed every time a given number of tweets is collected (see the refresh command).
Commands
create
Format:
> create <tag> <query>
Creates a filtering rule, associated to a given tag name.
Collected tweets are saved in json format in a file named <tag>.json
, in the given save path.
Tag name is the first argument of the command and cannot contain spaces.
Any word after the tag defines the query.
Info on how to define rules.
Example:
[not collecting (0 since last start), save path "data"]>create usa jow biden
Tweets matching the query "jow biden" will be saved in the file data/usa.json
ID=1395720345987340524
list
Format:
> list
Lists the queries, their ID and their tag, currently registered for the filtered stream.
Example:
[not collecting (0 since last start), save path "data"]> list
Registered queries:
ID=1385892384573355842 query="#usa" tag="usa"
ID=13905490304970434817 query="bts" tag="bts"
ID=1395720345987340524 query="joe biden" tag="usa"
delete
Format:
> delete <ID>
Deletes a query, given its ID.
Example:
[not collecting (0 since last start), save path "data"]> delete 1385892384573355842
start
Format:
> start
Starts a background process that collects tweets from the filtered stream and puts them in json files, according to the tag they are associated to.
Collection continues until a stop
or a exit
command is entered.
To let TwiGet collect data for longer periods of time, I suggest to use TwiGet within a virtual terminal session, using, e.g., screen
or tmux
.
Note: create and delete command can be issued also when collecting tweets. The collection process is updated immediately.
Example:
[not collecting (0 since last start), save path "data"]> start
[collecting (0 since last start), save path "data"]>
stop
Format:
> stop
Stop data collections.
Example:
[collecting (3000 since last start), save path "data"]> stop
[not collecting (3152 since last start), save path "data"]>
save_to
Format:
> save_to <path>
Sets the path where json files are saved.
_Note: changing path while collecting tweets will immediately create new json file in the new path, leaving all tweets collected until that moment in the old path.
Example:
[not collecting (0 since last start), save path "data"]> save_to ../my_project
[not collecting (0 since last start), save path "../my_project"]>
size
Format:
> size <size>
Sets the maximum size in bytes of json files. When a json file reaches this size, a new file with an incremented index (e.g., tag_0.json, tag_1.json, tag_2.json...) is created.
Example:
[not collecting (0 since last start), save path "data"]> size 1000000
refresh
Format:
> refresh <count>
Sets the number of collected tweets that triggers an automatic refresh of the prompt.
Example:
[not collecting (0 since last start), save path "data"]> refresh 10000
Implementing a custom command line tool
The TwiGetCLIBase
class in twiget_cli.py
module implements all the above fuctions except those related to saving to json file (i.e. save_to
and size
).
It can be used to implement a command line tool that performs a different processing of the collected data, e.g., saving to a db.
Python class: TwiGet
TwiGet core functionalities are implemented in a python class, which can be directly used in python code.
from twiget import TwiGet
bearer = 'put here the bearer token'
collector = TwiGet(bearer)
# Adding a filtering rule
# https://developer.twitter.com/en/docs/twitter-api/tweets/filtered-stream/api-reference/post-tweets-search-stream-rules
query = 'support vector machine'
tag = 'ml'
answer = collector.add_rule(query, tag)
# returns the parsed json answer from the server.
print(answer)
# Listing the current filtering rules
# https://developer.twitter.com/en/docs/twitter-api/tweets/filtered-stream/api-reference/get-tweets-search-stream-rules
answer = collector.get_rules()
# returns the parsed json answer from the server.
print(answer)
# Delete some rules by giving their ID
# https://developer.twitter.com/en/docs/twitter-api/tweets/filtered-stream/api-reference/post-tweets-search-stream-rules
ids = [48573094587309485,3029834285720978]
answer = collector.delete_rules(ids)
# returns the parsed json answer from the server.
print(answer)
# Adding a callback
# The data argument contains the content and information about the retrieved tweet
# https://developer.twitter.com/en/docs/twitter-api/tweets/filtered-stream/api-reference/get-tweets-search-stream
def print_tag(data):
print(data['matching_rules'][0]['tag'])
answer = collector.add_callback('print tag', print_tag)
# returns the parsed json answer from the server.
print(answer)
# Getting callbacks
callbacks = collector.get_callbacks()
# returns a list of pairs with the name of the callback and the callback method.
print(callbacks)
# Delete a callback
collector.delete_callback('print tag')
# Starting tweet collection
collector.start_getting_stream()
# Checking status of collection
running = collector.is_getting_stream()
# returns a boolean. True if collection is active.
print(running)
# Stopping tweet collection
collector.stop_getting_stream()
License
Author: Andrea Esuli
BSD 3-Clause License, see license file
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