A Python package to capture and reproduce command execution contexts
Project description
Capsula
:warning: NOTE: This project is still work in progress.
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
-
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.
-
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.
-
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'
subdirectory-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, each of which contains the captured context of a single execution. The subdirectory name is generated using the subdirectory-template
option in the capsula.toml
file. The default template is %Y%m%d_%H%M%S
, which generates a subdirectory 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"
}
}
}
Roadmap
See #1.
Project details
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