Encrypt vcrpy cassettes, so they can be safely kept under version control.
Sensitive data can easily end up in HTTP requests/responses during testing. Vcrpy has a way to scrub that data from its cassettes, but sometimes the tests that logged them actually need that information to pass.
This would normally result in a choice: either don't record those test cassettes or don't keep them under version control so that they can remain local only.
Enters vcrpy-encrypt: at its core it's a simple vcrpy persister that will encrypt cassettes before writing them to disk and decrypt them before replaying them when needed by a test. This means that tests can replay cassettes with sensitive data in them AND those cassettes can now be safely kept under version control and shared with others.
Simply run:
pip install vcrpy-encryptA secret key is needed to encrypt cassettes. It must be a 128, a 192 or a 256 bits long bytes object. vcrpy-encrypt
offers an easy way to generate a random key:
python -c "from vcrpy_encrypt import generate_key; print(generate_key())"By default this will result in a 128 bits key, but generate_key can take 128 or 192 or 256 as argument to
generate a longer key.
If a specific key is preferred, it can be converted from an utf-8, 16/24/32 characters long string like this:
key = "sixteensecretkey".encode("UTF-8")  # len(b'sixteensecretkey') == 16No matter the source, the key must be kept secret and separated from the code under version control!
Vcrpy's custom persister api needs a class reference. This class can be defined inheriting from
BaseEncryptedPersister like this:
from vcrpy_encrypt import BaseEncryptedPersister
key = ...  # recover the secret key from somewhere safe
class MyEncryptedPersister(BaseEncryptedPersister):
    # the encryption_key field must be initialized here with the chosen key
    encryption_key: bytes = keyThe encrypted persister can now be registered and used:
import vcr
import requests
# create a custom vcr object
my_vcr = vcr.VCR()
# register the encrypted persister into the custom vcr object
my_vcr.register_persister(MyEncryptedPersister)
# use that custom vcr object with use_cassette
with my_vcr.use_cassette("encoded-cassette"):
    # this request will produce an encrypted cassette and will replay it on following runs
    requests.get("https://localhost/?key=super-secret")Keep in mind that multiple vcr objects can coexists, so it's possible to use the default vcr everywhere while reserving the one with the encrypted persister only for requests resulting in cassettes with sensitive data.
Sometimes it can be handy to inspect the content of a cassette. This can be done even when using encrypted cassettes:
class MyEncryptedPersister(BaseEncryptedPersister):
    encryption_key: bytes = key
    should_output_clear_text_as_well = TrueThis persister will output a clear text cassette side by side with the encrypted one. Remember to blacklist all clear
text cassette in the version control system! For example this will cause git to ignore all .yaml file inside a
cassettes' folder (at any depth):
# file: .gitignore
**/cassettes/**/*.yamlClear text cassettes are only useful for human inspection: the persister will still use only the encrypted ones to replay network requests.
If different cassettes file name suffix are desired, they can be customized:
class MyEncryptedPersister(BaseEncryptedPersister):
    encryption_key: bytes = key
    should_output_clear_text_as_well = True
    clear_text_suffix = ".custom_clear"
    encoded_suffix = ".custom_enc"Currently this library is encrypting cassettes using cryptography with AES-GCM. This algorithm implementation is striking a good balance between security and performance.
Keep in mind that key length will have an impact on encrypt time: 128 bits keys should suffice for most use cases.
pip install invoke poetryNow clone the git repo:
git clone git@github.com:CarloDePieri/vcrpy-encrypt.git
cd vcrpy-encrypt
inv installThis will try to create a virtualenv based on python3.8 and install there all
project's dependencies. If a different python version is preferred, it can be
selected by specifying  the --python (-p) flag like this:
inv install -p python3.9The test suite can be run with commands:
inv test         # run the test suite
inv test-spec    # run the tests while showing the output as a spec document
inv test-cov     # run the tests suite and produce a coverage reportTo run the test suite against all supported python version (the executables must be in path!) run:
inv test-all-python-versionsTo test the GitHub workflow with act:
# First you need a .secrets file - do not version control this!
echo "repo_token: your_coveralls_token" > .secrets
# Then you can run one of these:
inv act                 # test the workflow
inv act -s legacy       # open a shell in the legacy-ci act container (the above must fail first!) 
inv act -s new          # open a shell in the ci act container (the above must fail first!) 
inv act -c legacy       # stop and delete a failed legacy-ci act container
inv act -c new          # stop and delete a failed ci act container