Configuring Betamax

By now you’ve seen examples where we pass a great deal of keyword arguments to use_cassette(). You have also seen that we used betamax.Betamax.configure(). In this section, we’ll go into a deep description of the different approaches and why you might pick one over the other.

Global Configuration

Admittedly, I am not too proud of my decision to borrow this design from VCR, but I did and I use it and it isn’t entirely terrible. (Note: I do hope to come up with an elegant way to redesign it for v1.0.0 but that’s a long way off.)

The best way to configure Betamax globally is by using betamax.Betamax.configure(). This returns a betamax.configure.Configuration instance. This instance can be used as a context manager in order to make the usage look more like VCR‘s way of configuring the library. For example, in VCR, you might do

VCR.configure do |config|
  config.cassette_library_dir = 'examples/cassettes'
  config.default_cassette_options[:record] = :none
  # ...

Where as with Betamax you might do

from betamax import Betamax

with Betamax.configure() as config:
    config.cassette_library_dir = 'examples/cassettes'
    config.default_cassette_options['record_mode'] = 'none'

Alternatively, since the object returned is really just an object and does not do anything special as a context manager, you could just as easily do

from betamax import Betamax

config = Betamax.configure()
config.cassette_library_dir = 'examples/cassettes'
config.default_cassette_options['record_mode'] = 'none'

We’ll now move on to specific use-cases when configuring Betamax. We’ll exclude the portion of each example where we create a Configuration instance.

Setting the Directory in which Betamax Should Store Cassette Files

Each and every time we use Betamax we need to tell it where to store (and discover) cassette files. By default we do this by setting the cassette_library_dir attribute on our config object, e.g.,

config.cassette_library_dir = 'tests/integration/cassettes'

Note that these paths are relative to what Python thinks is the current working directory. Wherever you run your tests from, write the path to be relative to that directory.

Setting Default Cassette Options

Cassettes have default options used by Betmax if none are set. For example,

  • The default record mode is once.
  • The default matchers used are method and uri.
  • Cassettes do not preserve the exact body bytes by default.

These can all be configured as you please. For example, if you want to change the default matchers and preserve exact body bytes, you would do

config.default_cassette_options['match_requests_on'] = [
config.preserve_exact_body_bytes = True

Filtering Sensitive Data

It’s unlikely that you’ll want to record an interaction that will not require authentication. For this we can define placeholders in our cassettes. Let’s use a very real example.

Let’s say that you want to get your user data from GitHub using Requests. You might have code that looks like this:

def me(username, password, session):
    r = session.get('', auth=(username, password))
    return r.json()

You would test this something like:

import os

import betmax
import requests

from my_module import me

session = requests.Session()
recorder = betamax.Betamax(session)
username = os.environ.get('USERNAME', 'testuser')
password = os.environ.get('PASSWORD', 'testpassword')

with recorder.use_cassette('test-me'):
    json = me(username, password, session)
    # assertions about the JSON returned

The problem is that now your username and password will be recorded in the cassette which you don’t then want to push to your version control. How can we prevent that from happening?

import base64

username = os.environ.get('USERNAME', 'testuser')
password = os.environ.get('PASSWORD', 'testpassword')
        '{0}:{1}'.format(username, password).encode('utf-8')


Obviously you can refactor this a bit so you can pull those environment variables out in only one place, but I’d rather be clear than not here.

The first time you run the test script you would invoke your tests like so:

$ USERNAME='my-real-username' PASSWORD='supersecretep@55w0rd' \

Future runs of the script could simply be run without those environment variables, e.g.,

$ python

This means that you can run these tests on a service like Travis-CI without providing credentials.

In the event that you can not anticipate what you will need to filter out, version 0.7.0 of Betamax adds before_record and before_playback hooks. These two hooks both will pass the Interaction and Cassette to the function provided. An example callback would look like:

def hook(interaction, cassette):

You would then register this callback:

# Either
# Or

You can register callables for both hooks. If you wish to ignore an interaction and prevent it from being recorded or replayed, you can call the ignore(). You also have full access to all of the methods and attributes on an instance of an Interaction. This will allow you to inspect the response produced by the interaction and then modify it. Let’s say, for example, that you are talking to an API that grants authorization tokens on a specific request. In this example, you might authenticate initially using a username and password and then use a token after authenticating. You want, however, for the token to be kept secret. In that case you might configure Betamax to replace the username and password, e.g.,

config.define_cassette_placeholder('<USERNAME>', username)
config.define_cassette_placeholder('<PASSWORD>', password)

And you would also write a function that, prior to recording, finds the token, saves it, and obscures it from the recorded version of the cassette:

from betamax.cassette import cassette

def sanitize_token(interaction, current_cassette):
    # Exit early if the request did not return 200 OK because that's the
    # only time we want to look for Authorization-Token headers
    if['response']['status']['code'] != 200:

    headers =['response']['headers']
    token = headers.get('Authorization-Token')
    # If there was no token header in the response, exit
    if token is None:

    # Otherwise, create a new placeholder so that when cassette is saved,
    # Betamax will replace the token with our placeholder.
        cassette.Placeholder(placeholder='<AUTH_TOKEN>', replace=token)

This will dynamically create a placeholder for that cassette only. Once we have our hook, we need merely register it like so:


And we no longer need to worry about leaking sensitive data.

Setting default serializer

If you want to use a specific serializer for every cassette, you can set serialize_with as a default cassette option. For example, if you wanted to use the prettyjson serializer for every cassette you would do:

config.default_cassette_options['serialize_with'] = 'prettyjson'

Per-Use Configuration

Each time you create a Betamax instance or use use_cassette(), you can pass some of the options from above.

Setting the Directory in which Betamax Should Store Cassette Files

When using per-use configuration of Betamax, you can specify the cassette directory when you instantiate a Betamax object:

session = requests.Session()
recorder = betamax.Betamax(session,

Setting Default Cassette Options

You can also set default cassette options when instantiating a Betamax object:

session = requests.Session()
recorder = betamax.Betamax(session, default_cassette_options={
    'record_mode': 'once',
    'match_requests_on': ['method', 'uri', 'headers'],
    'preserve_exact_body_bytes': True

You can also set the above when calling use_cassette():

session = requests.Session()
recorder = betamax.Betamax(session)
with recorder.use_cassette('cassette-name',
                           match_requests_on=['method', 'uri', 'headers'],

Filtering Sensitive Data

Filtering sensitive data on a per-usage basis is the only difficult (or perhaps, less convenient) case. Cassette placeholders are part of the default cassette options, so we’ll set this value similarly to how we set the other default cassette options, the catch is that placeholders have a specific structure. Placeholders are stored as a list of dictionaries. Let’s use our example above and convert it.

import base64

username = os.environ.get('USERNAME', 'testuser')
password = os.environ.get('PASSWORD', 'testpassword')
session = requests.Session()

recorder = betamax.Betamax(session, default_cassette_options={
    'placeholders': [{
        'placeholder': '<GITHUB-AUTH>',
        'replace': base64.b64encode(
            '{0}:{1}'.format(username, password).encode('utf-8')

Note that what we passed as our first argument is assigned to the 'placeholder' key while the value we’re replacing is assigned to the 'replace' key.

This isn’t the typical way that people filter sensitive data because they tend to want to do it globally.

Mixing and Matching

It’s not uncommon to mix and match configuration methodologies. I do this in I use global configuration to filter sensitive data and set defaults based on the environment the tests are running in. On Travis-CI, the record mode is set to 'none'. I also set how we match requests and when we preserve exact body bytes on a per-use basis.