A super awesome Twitter API client for Python.

Overview

birdy

birdy is a super awesome Twitter API client for Python in just a little under 400 LOC.

TL;DR

Features

Installation

The easiest and recommended way to install birdy is from PyPI

pip install birdy

Usage

Import client and initialize it:

from birdy.twitter import UserClient
client = UserClient(CONSUMER_KEY,
                    CONSUMER_SECRET,
                    ACCESS_TOKEN,
                    ACCESS_TOKEN_SECRET)

GET example (GET users/show):

response = client.api.users.show.get(screen_name='twitter')
response.data

POST example (POST statuses/update):

response = client.api.statuses.update.post(status='Hello @pybirdy!')

Dynamic URL example (POST statuses/destroy/:id):

response = client.api.statuses.destroy['240854986559455234'].post()

Streaming API example (Public Stream POST statuses/filter):

response = client.stream.statuses.filter.post(track='twitter')

for data in response.stream():
    print data

Supported Python version

birdy works with both python2 (2.7+) and python3 (3.4+).

Why another Python Twitter API client? Aren't there enough?

The concept behind birdy is so simple and awesome that it just had to be done, and the result is a super light weight and easy to use API client, that covers the whole Twitter REST API in just a little under 400 lines of code.

To achieve this, birdy relies on established, battle tested python libraries like requests and requests-ouathlib to do the heavy lifting, but more importantly it relies on Python's dynamic nature to automatically construct API calls (no individual wrapper functions for API resources needed). This allows birdy to cover all existing Twitter API resources and any future additions, without the need to update birdy itself.

Includes full support for both OAuth1 (user) and OAuth2 (application) authentication workflows.

Finally, birdy is simple and explicit by design, besides error handling and JSON decoding it doesn't process the returned data in any way, that is left for you to handle (who'd know better what to do with it).

OK, I'm sold, but how do I use it? How does this dynamic API construction work?

The easiest way to show you is by example. Lets say you want to query Twitter for @twitter user information. The Twitter API resource for this is GET users/show (Twitter docs).

First you will need to import a client, here we import UserClient (OAuth1) and than initialize it.

from birdy.twitter import UserClient
client = UserClient(CONSUMER_KEY,
                    CONSUMER_SECRET,
                    ACCESS_TOKEN,
                    ACCESS_TOKEN_SECRET)

To query the GET /users/show API resource and pass in the parameter screen_name='twitter' you do this.

resource = client.api.users.show
response = resource.get(screen_name='twitter')

What happens here is very simple, birdy translates the users.show part after client.api into the appropriate API resource path ('users/show'). Then when you call get() on the resource, birdy constructs a full resource URL, appends any parameters passed to get() to it and makes a GET request to that URL and returns the result.

Usually the above example would be shortened to just one line like this.

response = client.api.users.show.get(screen_name='twitter')

Making a post request is similar, if for example, you would like to post a status update, this is how to do it. The API resource is POST statuses/update (Twitter docs).

response = client.api.statuses.update.post(status='Hello @pybirdy!')

Like before the part after client.api gets converted to the correct path, only this time post() is called instead of get(), so birdy makes a POST request and pass parameters (and files) as part of the request body.

For cases when dynamic values are part of the API resource URL, like when deleting a tweet at POST statuses/destroy/:id (Twitter docs), birdy supports an alternative, dictionary lookup like, syntax. For example, deleting a tweet with id '240854986559455234' looks like this.

response = client.api.statuses.destroy['240854986559455234'].post()

By now it should be clear what happens above, birdy builds the API resource path and than makes a POST request, the only difference is that part of the API path is provided like a dictionary key lookup.

Actually any call can be written in this alternative syntax, use whichever you prefer. Both syntax forms can be freely combined as in the example above. Some more examples:

response = client.api['users/show'].get(screen_name='twitter')

response = client.api['users']['show'].get(screen_name='twitter')

response = client.api['statuses/destroy']['240854986559455234'].post()

Is Streaming API supported as well?

Sure, since version 0.2, birdy comes with full support for Streaming API out of the box. Access to the Streaming API is provided by a special StreamClient.

StreamClient can't be used to obtain access tokens, but you can use UserClient to get them.

To work with the Streaming API, first import the client and initialize it.

from birdy.twitter import StreamClient
client = StreamClient(CONSUMER_KEY,
                    CONSUMER_SECRET,
                    ACCESS_TOKEN,
                    ACCESS_TOKEN_SECRET)

To access resources on the Public stream, like POST statuses/filter (Twitter docs)

resource = client.stream.statuses.filter.post(track='twitter')

For User stream resource GET user (Twitter docs)

resource = client.userstream.user.get()

And for Site stream resource GET site (Twitter docs)

resource = client.sitestream.site.get()

To access the data in the stream you iterate over resource.stream() like this

for data in resource.stream():
   print data

Great, what about authorization? How do I get my access tokens?

birdy supports both OAuth1 and OAuth2 authentication workflows by providing two different clients, a UserClient and AppClient respectively. While requests to API resources, like in above examples are the same in both clients, the workflow for obtaining access tokens is slightly different.

Before you get started, you will need to register your application with Twitter, to obtain your application's CONSUMER_KEY and CONSUMER_SECRET.

OAuth1 workflow for user authenticated requests (UserClient)

Step 1: Creating a client instance

First you need to import the UserClient and create an instance with your apps CONSUMER_KEY and CONSUMER_SECRET.

from birdy.twitter import UserClient

CONSUMER_KEY = 'YOUR_APPS_CONSUMER_KEY'
CONSUMER_SECRET = 'YOUR_APPS_CONSUMER_SECRET'
CALLBACK_URL = 'https://127.0.0.1:8000/callback'

client = UserClient(CONSUMER_KEY, CONSUMER_SECRET)

Step 2: Get request token and authorization URL

Pass callback_url only if you have a Web app, Desktop and Mobile apps do not require it.

Next you need to fetch request token from Twitter. If you are building a Sign-in with Twitter type application it's done like this.

token = client.get_signin_token(CALLBACK_URL)

Otherwise like this.

token = client.get_authorize_token(CALLBACK_URL)

Save token.oauth_token and token.oauth_token_secret for later user, as this are not the final token and secret.

ACCESS_TOKEN = token.oauth_token
ACCESS_TOKEN_SECRET = token.oauth_token_secret

Direct the user to Twitter authorization url obtained from token.auth_url.

Step 3: OAuth verification

If you have a Desktop or Mobile app, OAUTH_VERIFIER is the PIN code, you can skip the part about extraction.

After authorizing your application on Twitter, the user will be redirected back to the callback_url provided during client initialization in Step 1.

You will need to extract the OAUTH_VERIFIER from the URL. Most web frameworks provide an easy way of doing this or you can parse the URL yourself using urlparse module (if that is your thing).

Django and Flask examples:

#Django
OAUTH_VERIFIER = request.GET['oauth_verifier']

#Flash
OAUTH_VERIFIER = request.args.get('oauth_verifier')

Once you have the OAUTH_VERIFIER you can use it to obtain the final access token and secret. To do that you will need to create a new instance of UserClient, this time also passing in ACCESS_TOKEN and ACCESS_TOKEN_SECRET obtained in Step 2 and then fetch the tokens.

client = UserClient(CONSUMER_KEY, CONSUMER_SECRET,
                    ACCESS_TOKEN, ACCESS_TOKEN_SECRET)

token = client.get_access_token(OAUTH_VERIFIER)

Now that you have the final access token and secret you can save token.oauth_token and token.oauth_token_secret to the database for later use, also you can use the client to start making API request immediately. For example, you can retrieve the users home timeline like this.

response = client.api.statuses.home_timeline.get()
response.data

That's it you have successfully authorized the user, retrieved the tokens and can now make API calls on their behalf.

OAuth2 workflow for app authenticated requests (AppClient)

Step 1: Creating a client instance

For OAuth2 you will be using the AppClient, so first you need to import it and create an instance with your apps CONSUMER_KEY and CONSUMER_SECRET.

from birdy.twitter import AppClient

CONSUMER_KEY = 'YOUR_APPS_CONSUMER_KEY'
CONSUMER_SECRET = 'YOUR_APPS_CONSUMER_SECRET'

client = AppClient(CONSUMER_KEY, CONSUMER_SECRET)

Step 2: Getting the access token

OAuth2 workflow is much simpler compared to OAuth1, to obtain the access token you simply do this.

access_token = client.get_access_token()

That's it, you can start using the client immediately to make API request on behalf of the app. It's recommended you save the access_token for later use. You initialize the client with a saved token like this.

client = AppClient(CONSUMER_KEY, CONSUMER_SECRET, SAVED_ACCESS_TOKEN)

Keep in mind that OAuth2 authenticated requests are read-only and not all API resources are available. Check Twitter docs for more information.

Any other useful features I should know about?

Of course, birdy comes with some handy features, to ease your development, right out of the box. Lets take a look at some of the goodies.

Automatic JSON decoding

JSON data returned by the REST and Streaming API is automatically decoded to native Python objects, no extra coding necessary, start using the data right away.

JSONObject

When decoding JSON data, objects are, instead of a regular Python dictionary, converted to a JSONObject, which is dictionary subclass with attribute style access in addition to regular dictionary lookup style, for convenience. The following code produces the same result

followers_count = response.data['followers_count']

followers_count = response.data.followers_count

ApiResponse

Calls to REST API resources return a ApiResponse, which in addition to returned data, also gives you access to response headers (useful for checking rate limits) and resource URL.

response.data           # decoded JSON data
response.resource_url   # resource URL
response.headers        # dictionary containing response HTTP headers

StreamResponse

StreamResponse is returned when calling Streaming API resources and provides the stream() method which returns an iterator used to receive JSON decoded streaming data. Like ApiResponse it also gives you access to response headers and resource URL.

response.stream()       # a generator method used to iterate over the stream

for data in response.stream():
    print data 

Informative exceptions

There are 4 types of exceptions in birdy all subclasses of base BirdyException (which is never directly raised).

  • TwitterClientError raised for connection and access token retrieval errors
  • TwitterApiError raised when Twitter returns an error
  • TwitterAuthError raised when authentication fails, TwitterApiError subclass
  • TwitterRateLimitError raised when rate limit for resource is reached, TwitterApiError subclass

TwitterApiError and TwitterClientError instances (exepct for access token retrieval errors) provide a informative error description which includes the resource URL and request method used (very handy when tracking errors in logs), also available is the following:

exception.request_method    # HTTP method used to make the request (GET or POST)
exception.resource_url      # URL of the API resource called
exception.status_code       # HTTP status code returned by Twitter
exception.error_code        # error code returned by Twitter
exception.headers           # dictionary containing response HTTP headers

Customize and extend through subclassing

birdy was built with subclassing in mind, if you wish to change the way it works, all you have to do is subclass one of the clients and override some methods and you are good to go.

Subclassing a client and then using the subclass instance in your codeis actually the recommended way of using birdy.

For example, if you don't wish to use JSONObject you have to override get_json_object_hook() method.

from birdy.twitter import UserClient

class MyClient(UserClient):
    @staticmethod
    def get_json_object_hook(data):
        return data

client = MyClient(...)
response = client.api.users.show.get(screen_name='twitter')

Or maybe, if you want global error handling for common errors, just override handle_response() method.

class MyClient(UserClient):
    def handle_response(self, method, response):
        try:
            response = super(MyClient, self).handle_response(method, response)
        except TwitterApiError, e:
            ...
            # Your error handling code
            ...
        return response

Another use of subclassing is configuration of requests.Session instance (docs) used to make HTTP requests, to configure it, you override the configure_oauth_session() method.

class MyClient(UserClient):
    def configure_oauth_session(self, session):
        session = super(MyClient, self).configure_oauth_session(session)
        session.proxies = {'http': 'foo.bar:3128'}
    return session

Do you accept contributions and feature requests?

Yes, both contributions (including feedback) and feature requests are welcome, the proper way in both cases is to first open an issue on GitHub and we will take if from there.

Keep in mind that I work on this project on my free time, so I might not be able to respond right way.

Credits

birdy would not exists if not for the excellent requests and requests-oauthlib libraries and the wonderful Python programing language.

Question, comments, ...

If you need to contact me, you can find me on Twitter (@sect2k).

Owner
Inueni
Inueni
Analog clock that shows the weather instead of the actual numerical hour it points to.

Eli's weatherClock An digital analog clock but instead of showing the hours, the clock shows the weather at that hour of the day. So instead of showin

Kovin 154 Dec 01, 2022
HinamiRobot - Telegram Group Manager Bot Written In Python Using Pyrogram

✨ HINAMI CHAN ✨ Telegram Group Manager Bot Written In Python Using Pyrogram. Rea

DARK LEGEND088 2 Jan 27, 2022
TuShare is a utility for crawling historical data of China stocks

TuShare Tushare Pro版已发布,请访问新的官网了解和查询数据接口! https://tushare.pro TuShare是实现对股票/期货等金融数据从数据采集、清洗加工 到 数据存储过程的工具,满足金融量化分析师和学习数据分析的人在数据获取方面的需求,它的特点是数据覆盖范围广,接口

挖地兔 11.9k Dec 30, 2022
A MassDM selfbot which is working in 2021

mass-dm-discord - Little preview of the Logger and the Spammer Features Logging User IDS Sending DMs to the logged IDs Blacklist IDs (add the ID of th

karma.meme 88 Dec 26, 2022
A python Discord wrapper made in well, python.

discord.why A python Discord wrapper made in well, python. Made to be used by devs who want something a bit more, general. Basic Examples Sending a me

HellSec 6 Mar 26, 2022
File-sharing-Bot: Telegram Bot to store Posts and Documents and it can Access by Special Links.

Bromélia HSS bromelia-hss is the second official implementation of a Diameter-based protocol application by using the Python micro framework Bromélia.

1 Dec 17, 2021
Sniper for Anigame and Izzi discord bots!

Anigame Sniper Gen-3 Features Inbuilt Spammer Responds to your messages in discord (on/off) Snipes only where you want it to Set latency so that the b

22 Nov 13, 2022
Discord Token Checker

Discord-Token-Checker Optimizations Asynchronous Fast & Efficient Multi Tasked Proxy support (socks4/socks5/http) Usage Put tasks depending on your PC

scripted 6 May 05, 2022
Python app to notify via slack channel the status_code change from an URL

Python app to notify, via slack channel you choose to be notified, for the status_code change from the URL list you setup to be checked every yy seconds

Pedro Nunes 1 Oct 25, 2021
Eclipse-grabber - Generate Discord Token Grabbers for both Windows and MacOS

Eclipse Grabber Eclipse Discord Token Grabber What is Eclipse? Eclipse is an ope

Dimitris Kalopisis 117 Dec 23, 2022
Sie_banxico - A python class for the Economic Information System (SIE) API of Banco de México

sie_banxico A python class for the Economic Information System (SIE) API of Banco de México. Args: token (str): A query token from Banco de México id_

Dillan 2 Apr 07, 2022
Python wrapper for Interactive Brokers Client Portal Web API

EasyIB: Unofficial Wrapper for Interactive Brokers API EasyIB is an unofficial python wrapper for Interactive Brokers Client Portal Web API. Features

39 Dec 13, 2022
A repository of publicly verifiable token Sale contracts

Token-Sale-Plutus-Contract A repository of publicly verifiable token sale and royalty contracts. This will be the storage solution since it is easily

Logical Mechanism 29 Aug 18, 2022
Simple discord token generator good for memberboosting your server! Uses Hcaptcha bypass

discord-tokens-generator INFO This is a Simple Discord Token Generator which creates unverified discord accounts These accounts are good for member bo

Avenger 41 Dec 20, 2022
Python wrapper to simplify calls to AncestryDNA API.

AncestryDNA API wrapper Ancestry exposes an undocumented REST API for its DNA features. This Python wrapper inventories the available calls, and expos

Matt 2 Jun 10, 2022
Tglogging - A python package to send your app logs to a telegram chat in realtime

Telegram Logger A simple python package to send your app logs to a telegram chat

SUBIN 60 Dec 27, 2022
Rhythm bot clone for discord written in Python and uses YouTube to get media files.

Tunebot About Rhythm bot clone for discord written in Python and uses YouTube to get media files. Usage You need a .env file within the same directory

1 Oct 21, 2021
AWS Blog post code for running feature-extraction on images using AWS Batch and Cloud Development Kit (CDK).

Batch processing with AWS Batch and CDK Welcome This repository demostrates provisioning the necessary infrastructure for running a job on AWS Batch u

AWS Samples 7 Oct 18, 2022
Telegram Voice Chat Music Player UserBot Written with Pyrogram Smart Plugin and tgcalls

Telegram Voice Chat UserBot A Telegram UserBot to Play Audio in Voice Chats. This is also the source code of the userbot which is being used for playi

Dash Eclipse 7 May 21, 2022
Easy and simple, Telegram Bot to Show alert when some edits a message in Group

Edit-Message-Alert Just a simple bot to show alert when someone edits a message sent by them, Just 17 Lines of Code These codes are for those who incu

Nuhman Pk 6 Dec 15, 2021