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A Python package to capture and reproduce command execution context

Project description

Capsula

:warning: NOTE: This project is still work in progress. Consider pinning the version to avoid breaking changes.

Capsula, a Latin word meaning box, is a Python package designed to help researchers and developers easily capture and reproduce their command execution context. The primary aim of Capsula is to tackle the reproducibility problem by providing a way to capture the execution context at any point in time, preserving it for future use. This ensures that you can reproduce the exact conditions of a past command execution, fostering reproducibility and consistency over time.

Features

  1. Context Capture (under development): Capsula logs the details of the execution context for future reference and reproduction. The context includes, but not limited to, Python version, system environment variables, and the Git commit hash of the current working directory.

  2. Execution Monitoring (to be implemented): Capsula monitors the execution of Python scripts, Jupyter notebooks, and CLI commands, logging information such as the execution status, output, duration, etc.

  3. Context Reproduction (to be implemented): Capsula enables the reproduction of the captured context. This ensures the consistency and reproducibility of results.

Installation

You can install Capsula via pip:

pip install capsula

At the root of your project, create a capsula.toml file wit the following content:

[capture]
vault-directory = 'vault'

capsule-template = '%Y%m%d_%H%M%S'

include-cpu = false

pre-capture-commands = [
    'poetry lock --check'
]

environment-variables = [
    'HOME',
]

[capture.files]
"pyproject.toml" = { hash = "sha256", copy = true }
"poetry.lock" = { hash = "sha256", copy = true }


[capture.git.repositories]
capsula = '.'

Usage

Context Capture

Running capsula capture in the project root (the directory where capsula.toml is located) captures the execution context and stores it in a vault directory. The vault directory is specified in the capsula.toml file. The vault directory is organized by subdirectories ("capsules"), each of which contains the captured context of a single execution. The capsule name is generated using the capsule-template option in the capsula.toml file. The default template is %Y%m%d_%H%M%S, which generates a capsule name in the format of YYYYMMDD_HHMMSS. The context is stored in a JSON file named context.json.

Example of context.json:

{
    "platform": {
        "machine": "x86_64",
        "node": "DESKTOP-XXXXXXX",
        "platform": "Linux-5.15.90.1-microsoft-standard-WSL2-x86_64-with-glibc2.31",
        "release": "5.15.90.1-microsoft-standard-WSL2",
        "version": "#1 SMP Fri Jan 27 02:56:13 UTC 2023",
        "system": "Linux",
        "processor": "x86_64",
        "python": {
            "executable_architecture": {
                "bits": "64bit",
                "linkage": "ELF"
            },
            "build_no": "main",
            "build_date": "Dec 30 2022 17:24:31",
            "compiler": "GCC 9.4.0",
            "branch": "",
            "implementation": "CPython",
            "version": "3.11.1"
        }
    },
    "cpu": null,
    "environment_variables": {
        "HOME": "/home/directory"
    },
    "cwd": "/current/working/directory",
    "git": {
        "capsula": {
            "path": ".",
            "sha": "7dbaa0389ca4553b3d8b6e35c2d0e4d9e2501764",
            "branch": "git-config",
            "remotes": [
                {
                    "name": "origin",
                    "url": "git@github.com:shunichironomura/capsula.git"
                }
            ]
        }
    },
    "files": {
        "pyproject.toml": {
            "hash_algorithm": "sha256",
            "file_hash": "e412f8efcdfc12aa7ec36f219a2037c90ade279df5fb11fdefa5a5c3f583a1df"
        },
        "poetry.lock": {
            "hash_algorithm": "sha256",
            "file_hash": "bd2ee84e4ab22528f89431ca4693c6db58aa304380b36cee7d3e21e19f756df2"
        }
    }
}

Execution Monitoring

Running capsula monitor <commands> in the project root (the directory where capsula.toml is located) monitors the execution of the specified commands. The context is logged in the context.json file in the capsule directory, and the command execution is logged in the pre-run-info.json and post-run-info.json files in the capsule directory.

Try it out

Prerequisites

Steps

  1. Clone this repository:
git clone git@github.com:shunichironomura/capsula.git
  1. Install the package, including the examples:
poetry install --with examples
  1. Run the example:

Context capture:

capsula capture

Execution monitoring:

capsula monitor python examples/calculate_pi.py

Roadmap

See #1.

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