pytest-recording
Work with pytest-recording (VCR.py) for recording and replaying HTTP interactions in tests. Use when writing VCR tests, managing cassettes, configuring VCR options, filtering sensitive data, or debugging recorded HTTP responses.
Best use case
pytest-recording is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Work with pytest-recording (VCR.py) for recording and replaying HTTP interactions in tests. Use when writing VCR tests, managing cassettes, configuring VCR options, filtering sensitive data, or debugging recorded HTTP responses.
Work with pytest-recording (VCR.py) for recording and replaying HTTP interactions in tests. Use when writing VCR tests, managing cassettes, configuring VCR options, filtering sensitive data, or debugging recorded HTTP responses.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "pytest-recording" skill to help with this workflow task. Context: Work with pytest-recording (VCR.py) for recording and replaying HTTP interactions in tests. Use when writing VCR tests, managing cassettes, configuring VCR options, filtering sensitive data, or debugging recorded HTTP responses.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/pytest-recording/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How pytest-recording Compares
| Feature / Agent | pytest-recording | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Work with pytest-recording (VCR.py) for recording and replaying HTTP interactions in tests. Use when writing VCR tests, managing cassettes, configuring VCR options, filtering sensitive data, or debugging recorded HTTP responses.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# pytest-recording (VCR.py) Testing
## Overview
pytest-recording wraps VCR.py to record HTTP interactions as YAML cassettes, enabling deterministic tests without live API calls.
## Quick Reference
### Running Tests
```bash
# Run all tests (uses existing cassettes)
uv run pytest tests/
# Run a single test
uv run pytest tests/test_module.py::test_function
# Rewrite all cassettes with fresh responses
uv run pytest tests/ --vcr-record=rewrite
# Record only missing cassettes
uv run pytest tests/ --vcr-record=new_episodes
# Disable VCR (make live requests)
uv run pytest tests/ --disable-recording
```
### Recording Modes
| Mode | Flag | Behavior |
|------|------|----------|
| `none` | `--vcr-record=none` | Only replay, fail if no cassette |
| `once` | (default) | Record if no cassette exists |
| `new_episodes` | `--vcr-record=new_episodes` | Record new requests, keep existing |
| `all` | `--vcr-record=all` | Always record, overwrite existing |
| `rewrite` | `--vcr-record=rewrite` | Delete and re-record all cassettes |
### Writing VCR Tests
Basic test with VCR:
```python
import pytest
@pytest.mark.vcr()
def test_api_call():
response = my_api_function()
assert response.status_code == 200
```
Custom cassette name:
```python
@pytest.mark.vcr("custom_cassette_name.yaml")
def test_with_custom_cassette():
pass
```
Multiple cassettes:
```python
@pytest.mark.vcr("cassette1.yaml", "cassette2.yaml")
def test_with_multiple_cassettes():
pass
```
### VCR Configuration in conftest.py
The `vcr_config` fixture controls VCR behavior:
```python
@pytest.fixture(scope="module")
def vcr_config():
return {
# Filter sensitive headers from recordings
"filter_headers": ["authorization", "api-key", "x-api-key"],
# Filter query parameters
"filter_query_parameters": ["key", "api_key", "token"],
# Match requests by these criteria
"match_on": ["method", "scheme", "host", "port", "path", "query"],
# Ignore certain hosts (don't record)
"ignore_hosts": ["localhost", "127.0.0.1"],
# Record mode
"record_mode": "once",
}
```
### Filtering Sensitive Data
For LLM providers, filter authentication:
```python
@pytest.fixture(scope="module")
def vcr_config():
return {
"filter_headers": [
"authorization", # OpenAI, Anthropic
"api-key", # Azure OpenAI
"x-api-key", # Anthropic
"x-goog-api-key", # Google AI
],
"filter_query_parameters": ["key"],
}
```
### Response Processing
Use `pytest_recording_configure` for advanced processing:
```python
def pytest_recording_configure(config, vcr):
vcr.serializer = "yaml"
vcr.decode_compressed_response = True
# Sanitize response headers
def sanitize_response(response):
response['headers']['Set-Cookie'] = 'REDACTED'
return response
vcr.before_record_response = sanitize_response
```
### Cassette Location
Cassettes are stored in `tests/cassettes/` by default, organized by test module:
```
tests/
├── cassettes/
│ └── test_module/
│ └── test_function.yaml
└── test_module.py
```
## Debugging
### Cassette Not Found
If tests fail with "Can't find cassette":
1. Run with `--vcr-record=once` to create missing cassettes
2. Check cassette path matches test location
3. Verify cassette file exists and is valid YAML
### Request Mismatch
If VCR can't match requests:
1. Check `match_on` criteria in `vcr_config`
2. Compare request details in cassette vs actual request
3. Use `--vcr-record=new_episodes` to add missing interactions
### Stale Cassettes
When API responses change:
1. Delete specific cassette file and re-run test
2. Or use `--vcr-record=rewrite` to refresh all cassettes
### View Cassette Contents
```bash
# View a cassette file
cat tests/cassettes/test_module/test_function.yaml
# Search for specific content in cassettes
grep -r "error" tests/cassettes/
```
## Adding New LLM Providers
When adding a new provider:
1. Identify authentication headers (check provider docs)
2. Add headers to `filter_headers` in `vcr_config`
3. Add any query param auth to `filter_query_parameters`
4. Test with `--vcr-record=once` to create cassettes
5. Verify cassettes don't contain secrets
Common provider authentication:
| Provider | Headers to Filter |
|----------|-------------------|
| OpenAI | `authorization` |
| Anthropic | `x-api-key`, `authorization` |
| Azure OpenAI | `api-key` |
| Google AI | `x-goog-api-key` |
| Cohere | `authorization` |
## Best Practices
1. **Never commit secrets**: Always filter auth headers/params
2. **Use descriptive test names**: Cassette names derive from test names
3. **Keep cassettes small**: Mock only what you need to test
4. **Review cassettes in PRs**: Check for sensitive data leaks
5. **Regenerate periodically**: API responses may change over time
6. **Use scope appropriately**: `scope="module"` for shared fixturesRelated Skills
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