https://github.com/aeturrell/smartrappy
Smart reproducible analytical pipeline inspection
Science Score: 26.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.3%) to scientific vocabulary
Repository
Smart reproducible analytical pipeline inspection
Basic Info
- Host: GitHub
- Owner: aeturrell
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://aeturrell.github.io/smartrappy/
- Size: 595 KB
Statistics
- Stars: 17
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
smartrappy
Smart reproducible analytical pipeline inspection.
Introduction
What does this package do?
smartrappy analyses a Python project and infers the directed acyclic graph (DAG) of the code and data dependencies, including the last time any data were refreshed and whether the data exist at all on disk. It is not perfect, and will miss a lot in complex projects: but for simple projects using, say, pd.read_csv(), it does a good job of inferring the steps. It can also infer writing to and from most databases. The inferred DAG is then visualised, and there are several options for doing that—the default being to produce a visualisation in the terminal.
What is smartrappy for?
smartrappy is designed to help you understand the dependencies in a project, especially in a context where there may be a lot of legacy code that resembles tangled spaghetti.
Quickstart
To use smartrappy as a command-line tool:
bash
smartrappy /path/to/your/project
Or to use it within a Python script:
```python from smartrappy import analyse_project from smartrappy.reporters import ConsoleReporter
model = analyseproject("/path/to/your/project") reporter = ConsoleReporter() reporter.generatereport(model) ```
Installation
To install smartrappy, you can use pip install smartrappy or uv add smartrappy if you are using Astral's uv. You can also use it as a standalone command-line tool with uv and the uvx command:
bash
uvx smartrappy path/to/your/project
Documentation
You can find the full documentation for smartrappy at https://aeturrell.github.io/smartrappy/.
Owner
- Login: aeturrell
- Kind: user
- Website: www.aeturrell.com
- Repositories: 9
- Profile: https://github.com/aeturrell
GitHub Events
Total
- Create event: 9
- Issues event: 5
- Release event: 4
- Watch event: 16
- Issue comment event: 3
- Public event: 1
- Push event: 30
- Pull request event: 14
Last Year
- Create event: 9
- Issues event: 5
- Release event: 4
- Watch event: 16
- Issue comment event: 3
- Public event: 1
- Push event: 30
- Pull request event: 14
Packages
- Total packages: 1
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Total downloads:
- pypi 12 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 4
- Total maintainers: 1
pypi.org: smartrappy
Smart reproducible analytical pipeline visualisation.
- Documentation: https://smartrappy.readthedocs.io/
- License: mit
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Latest release: 0.0.5
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout v4 composite
- crazy-max/ghaction-github-labeler v5 composite
- actions/checkout v4 composite
- actions/setup-python v5.4.0 composite
- astral-sh/setup-uv v5 composite
- pypa/gh-action-pypi-publish v1.12.4 composite
- quarto-dev/quarto-actions/setup v2 composite
- release-drafter/release-drafter v6.1.0 composite
- salsify/action-detect-and-tag-new-version v2.0.3 composite
- actions/cache v4.2.0 composite
- actions/checkout v4 composite
- actions/download-artifact v4 composite
- actions/setup-python v5.4.0 composite
- actions/upload-artifact v4 composite
- astral-sh/setup-uv v5 composite
- codecov/codecov-action v5.3.1 composite
- graphviz >=0.20.3
- matplotlib >=3.10.0
- pandas >=2.2.3
- 161 dependencies