Rust-powered HTTP cassette recorder for Python tests. Safe by default.
Project description
Cassetter
Rust-powered HTTP cassette recorder for Python tests. Safe by default.
Why?
VCR.py works, but has fundamental problems:
- Unsafe by default - doesn't filter sensitive headers, tokens, or API keys
- Unsafe YAML - uses
yaml.load()with an unsafe loader that can execute arbitrary Python code from cassette files - Slow - pure Python YAML parsing, matching, and serialization
- Fragile - relies on undocumented internals that break on minor version bumps
- Poor readability - JSON bodies stored as escaped strings in YAML
cassetter fixes all of this with a Rust core (PyO3) for speed, safe-by-default security filtering, and secure YAML parsing.
Install
uv add cassetter
Quick start
With pytest (recommended)
Mark tests with @pytest.mark.vcr:
import httpx
import pytest
@pytest.mark.vcr
async def test_api_call():
async with httpx.AsyncClient() as client:
response = await client.get("https://api.example.com/users")
assert response.status_code == 200
First run records real HTTP interactions. Subsequent runs replay from the cassette file - no network needed.
If you need direct access to the cassette (e.g. to inspect recorded interactions), request the fixture explicitly:
from cassetter import Cassette
@pytest.mark.vcr
async def test_with_cassette(vcr_cassette: Cassette):
...
assert len(vcr_cassette.interactions) == 1
With the context manager
from cassetter import use_cassette
async with use_cassette("tests/cassettes/my_test.yaml", record_mode="once"):
async with httpx.AsyncClient() as client:
response = await client.get("https://api.example.com/users")
Record modes
| Mode | Behavior |
|---|---|
none |
Replay only. Raises if no match found. |
once |
Record if cassette doesn't exist. Replay if it does. |
new_episodes |
Replay existing interactions. Record new ones. |
all |
Record everything, overwriting the cassette. |
Set via CLI: pytest --record-mode=none
Safe by default
Sensitive data is filtered at write time - cassettes never contain secrets. These headers are stripped automatically:
authorization, cookie, set-cookie, x-api-key, api-key, x-auth-token, proxy-authorization, www-authenticate
Query params like api_key, access_token, token, client_secret are replaced with [FILTERED].
JSON body fields like password, access_token, refresh_token, client_secret are scrubbed.
Customize filtering:
from cassetter import use_cassette
async with use_cassette(
"cassette.yaml",
filtered_headers=["x-custom-secret"],
body_scrub_patterns=["my_secret_field"],
filter_replacement="***REDACTED***",
):
...
Cassette format
JSON bodies are stored as structured YAML - not escaped strings:
version: 1
interactions:
- request:
method: POST
uri: https://api.openai.com/v1/chat/completions
headers:
content-type:
- application/json
body:
type: json
content:
model: gpt-4o
messages:
- role: user
content: Hello!
response:
status: 200
headers:
content-type:
- application/json
body:
type: json
content:
id: chatcmpl-abc123
choices:
- message:
role: assistant
content: Hi there!
recorded_at: '2026-02-20T10:30:01Z'
Request matching
Default: match on method + URI. Configurable:
from cassetter import use_cassette
async with use_cassette(
"cassette.yaml",
match_on=["method", "uri", "json_body"],
ignore_json_paths=["request_id", "timestamp"],
):
...
Available matchers: method, uri, headers, body, json_body.
Supported libraries
| Library | Protocol | Interception method |
|---|---|---|
| httpx | HTTP | AsyncBaseTransport / BaseTransport |
| aiohttp | HTTP | Session _request patch |
| requests | HTTP | Session send patch |
| urllib3 | HTTP | HTTPConnectionPool.urlopen patch |
| grpcio | gRPC | grpc.aio.Channel wrapper |
| websockets | WebSocket | websockets.connect patch |
By default, interceptors are auto-detected based on which libraries are installed. To limit interception to specific libraries:
async with use_cassette("cassette.yaml", intercept=["httpx", "aiohttp"]):
...
gRPC support
Install the gRPC extra:
uv add "cassetter[grpc]"
Record and replay gRPC calls by adding "grpc" to the interceptor list:
async with use_cassette("cassette.yaml", intercept=["grpc"]):
channel = grpc.aio.insecure_channel("localhost:50051")
stub = my_service_pb2_grpc.MyServiceStub(channel)
response = await stub.Echo(my_service_pb2.EchoRequest(message="hello"))
All four gRPC call patterns are supported: unary-unary, server streaming, client streaming, and bidirectional streaming. Request and response bodies are stored as binary in the cassette, with an optional json_debug section for human-readable protobuf representation (when google.protobuf is available):
grpc_interactions:
- request:
method: /mypackage.MyService/Echo
metadata: {}
body:
type: binary
content: 0a0568656c6c6f
response:
status_code: 0
status_message: OK
metadata: {}
body:
type: binary
content: 0a0568656c6c6f
json_debug:
request:
message: hello
response:
message: hello
Streaming responses use length-prefixed binary encoding - multiple response chunks are stored in a single body field and decoded back into individual messages on replay.
WebSocket support
Install the WebSocket extra:
uv add "cassetter[websockets]"
Record and replay WebSocket connections:
async with use_cassette("cassette.yaml", intercept=["websockets"]):
async with websockets.connect("wss://ws.example.com/stream") as ws:
await ws.send('{"subscribe": "ticker"}')
data = await ws.recv()
WebSocket interactions record each frame with direction, type, and timing offset:
ws_interactions:
- uri: wss://ws.example.com/stream
headers: {}
frames:
- direction: send
frame_type: text
body:
type: text
content: '{"subscribe": "ticker"}'
offset_ms: 0
- direction: recv
frame_type: text
body:
type: json
content:
price: 42.5
offset_ms: 120
On replay, recv() returns recorded frames in order without a real connection. send() is a no-op. Both text and binary frames are supported.
Streaming / SSE support
SSE (Server-Sent Events) responses - used by OpenAI, Anthropic, Groq, and other LLM APIs for streaming - work out of the box. The full response body is recorded as readable text in the cassette:
response:
status: 200
headers:
content-type:
- text/event-stream
body:
type: text
content: |+
data: {"id":"chatcmpl-abc","choices":[{"delta":{"role":"assistant"}}]}
data: {"id":"chatcmpl-abc","choices":[{"delta":{"content":"Hello"}}]}
data: [DONE]
On replay, the buffered body is returned to the client SDK, which parses SSE events from it. This matches how VCR.py handles streaming - chunk boundaries aren't preserved, but SSE parsers split on \n\n boundaries regardless of how bytes are delivered.
Request filtering
Ignore hosts
Bypass the cassette entirely for requests to specific hosts. Matched requests pass through to the real server - no recording, no replay:
async with use_cassette(
"cassette.yaml",
ignore_hosts=["*.googleapis.com", "accounts.google.com"],
):
...
Patterns use fnmatch syntax (* matches any sequence of characters). Combine with ignore_localhost for full control:
async with use_cassette(
"cassette.yaml",
ignore_localhost=True,
ignore_hosts=["*.googleapis.com"],
):
...
Before record request hook
For advanced filtering, use a callback that runs before each request is recorded or replayed. Raise BypassCassette to let the request pass through live:
from cassetter import BypassCassette, RawRequest, use_cassette
def my_hook(request: RawRequest) -> None:
if not request.uri.startswith("https://api.mycompany.com"):
raise BypassCassette
async with use_cassette("cassette.yaml", before_record_request=my_hook):
...
Both options work with the pytest plugin via vcr_config:
@pytest.fixture(scope="module")
def vcr_config():
return {
"ignore_hosts": ["*.googleapis.com"],
}
Cassette expiry
Force re-recording when cassettes get stale:
async with use_cassette("cassette.yaml", max_age="30d", on_expiry="rerecord"):
...
max_age accepts durations like "24h", "7d", "4w". on_expiry controls the behavior:
| Action | Behavior |
|---|---|
warn |
Emit a warning (default) |
fail |
Raise CassetteExpiredError |
rerecord |
Delete and re-record the cassette |
Also configurable via pytest:
[tool.pytest.ini_options]
vcr_max_age = "30d"
vcr_on_expiry = "warn"
Or per-test:
@pytest.mark.vcr(max_age="7d", on_expiry="fail")
async def test_fresh_data():
...
Orphan detection
Find cassette files that no test uses:
pytest --vcr-check-orphans=tests/cassettes/
Performance
Rust-powered YAML parsing and serialization is 3-6x faster than vcrpy (which uses PyYAML/libyaml):
1000 interactions
cassetter vcrpy speedup
load 13.53 ms 58.90 ms 4.4x
match 0.98 ms 1.29 ms 1.3x
save 7.58 ms 45.64 ms 6.0x
Run uv run python benchmarks/bench.py to reproduce.
YAML safety
vcrpy uses yaml.load() with an unsafe loader (CLoader/Loader) that can execute arbitrary Python via !!python/object tags. A malicious cassette file could run code when loaded.
cassetter parses YAML in Rust, which has no concept of Python object construction - only data types are supported.
Development
Requires Rust toolchain and Python 3.10+.
git clone https://github.com/marcelotryle/cassetter.git
cd cassetter
uv sync
uv run maturin develop
uv run pytest
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