birdy 0.3.2

Description:

birdy 0.3.2

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

TL;DR

Features

Future proof dynamic API with full REST and Streaming API
coverage
OAuth1 (user) and OAuth2 (app) authentication
workflows
Automatic JSON decoding,
JSONObject
ApiResponse, StreamResponse
objects
Informative exceptions
Easily customizable through
subclassing
Built on top of the excellent requests and requests-ouathlib
libraries



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](https://twitter.com/sect2k/)).