Skip to main content

darkroom

Evidence capture and manifest management for autonomous software delivery.

darkroom is the evidence subsystem of the Judge-Builder framework. It provides typed records for evidence items, a producer protocol for capturing diverse evidence kinds, and manifest serialization for the handoff between Builder and Judge.

The name references the dark factory pattern -- lights-off autonomous production -- and the clean room pattern -- independent implementation from specification. A darkroom is a controlled, light-sealed environment where evidence is developed and evaluated without contamination from the implementation side.

Install

pip install darkroom-ai            # core: manifests, run lifecycle, pytest plugin,
                                   # log/command/HTTP/file-snapshot/diff/video producers
pip install darkroom-ai[playwright] # adds the screenshot producers

The distribution is named darkroom-ai (the bare darkroom name is squatted on PyPI); the import name is darkroom throughout.

Usage

Installing the package registers a pytest plugin -- no conftest wiring needed. Tests request the evidence fixture; the scenario name derives from the test name:

def test_login_flow(page, evidence):
    evidence.screenshot(page, "login_page")
    evidence.screenshot(page, "after_login", full_page=True)
    evidence.log("api_response", {"status": 200})

Run in evidence mode to get a manifest-backed run (otherwise captures fall back to flat directories and the session hooks stay out of the way):

EVIDENCE_MODE=1 EVIDENCE_DIR=./evidence pytest

The plugin starts the run at session start, records a full-page screenshot for any failing test that used a page fixture, and writes manifest.json at session end. Set the manifest's project name via ini:

[pytest]
darkroom_project = my-project

CLI

Installed as darkroom (alias: darkrm):

darkroom show evidence/runs/<run>/manifest.json     # summarize a run
darkroom verify evidence/runs/<run>/manifest.json   # structural checks
darkroom verify runs/*/manifest.json --contract evidence-contract.toml

verify exits nonzero when a run fails its evidence contract -- a declared set of per-scenario capture requirements -- making "this build produced its proof" a CI gate. A contract is TOML:

[[scenario]]
name = "client_approves_proof"

  [[scenario.requires]]
  kind = "screenshot"
  steps = ["proof_awaiting_approval", "proof_approved"]

  [[scenario.requires]]
  kind = "http_transcript"

Requirements may declare trials = N for nondeterministic scenarios checked across a series of runs (pass several manifests to verify).

Direct API

from darkroom import EvidenceCapture
from darkroom.run import start_run, end_run

run = start_run(project="my-project")

evidence = EvidenceCapture("login_flow")
evidence.screenshot(page, "login_page")
evidence.log("api_response", {"status": 200})

manifest_path = end_run()  # writes manifest.json

Manifest Format (v2)

{
  "schema_version": "2.0",
  "run_id": "2026-03-17T13-43-29",
  "project": "my-project",
  "timestamp": "2026-03-17T13:44:02.049178",
  "scenarios": [
    {
      "scenario": "login_flow",
      "items": [
        {
          "kind": "screenshot",
          "mime": "image/png",
          "path": "login_flow/01-login_page.png",
          "scenario": "login_flow",
          "step": "login_page",
          "captured_at": "2026-03-17T13:43:48.707534",
          "metadata": {}
        }
      ]
    }
  ]
}

All path values are relative to the manifest file's parent directory. Absolute paths (starting with /) are also accepted. v1 manifests are loaded transparently by load_manifest.

Documentation

Development

make venv       # create virtualenv and install deps
make test-unit  # run unit tests
make test       # run all tests with coverage
make help       # see all targets

Release files for darkroom-ai 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for darkroom-ai 0.6.0
File Size Uploaded
darkroom_ai-0.6.0.tar.gz 103.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for darkroom-ai 0.6.0
File Interpreter ABI Platform
darkroom_ai-0.6.0-py3-none-any.whl Python 3 none any Details

Total release size: 151.4 kB

Release files / darkroom_ai-0.6.0.tar.gz

Download URL darkroom_ai-0.6.0.tar.gz
Size 103.3 kB
Tags Source
SHA-256 checksum
How to use checksums
06c96ed164116775e5743c5fb9f68d5f8a8ae93ae400606574b738ab7b33d432
BLAKE2b-256 checksum
How to use checksums
af5adf1b5f30c47436ee18b7c1fa1ab2e8540c2f58e3b917be5a74c06b925190
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 20, 2026.

Transparency log

Release files / darkroom_ai-0.6.0-py3-none-any.whl

Download URL darkroom_ai-0.6.0-py3-none-any.whl
Size 48.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
16bf6b86acb5fe47f84f9e7bf4db9f5ca8f6f997315ed68de3843315423c1328
BLAKE2b-256 checksum
How to use checksums
30b4cb4aac66410e67713c233d2762e247e31fe1d50369f25efbc6b3446084f6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 20, 2026.

Transparency log

Release history Release notifications | RSS feed

0.7.0

2 release files

This release

0.6.0 This release

2 release files

0.5.0

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.0

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page