Python Environment Dependency Resolution

---
name: python-environment-dependency-resolution
description: Use when when you have cloned a Python project repository and need to
  set up a working environment with all required packages, or when requirements.txt
  exists but dependencies are not yet installed in your current Python environment.
license: CC-BY-4.0
metadata:
  edam_operation: http://edamontology.org/operation_0004
  edam_topics:
  - http://edamontology.org/topic_0091
  tools:
  - pip
  - conda
  license_tier: open
  provenance_tier: literature
derived_from:
- doi: 10.1038/s41587-025-02663-3
  title: DreaMS
evidence_spans:
- pip install -r requirements.txt
claims: []
provenance:
  collection: https://w3id.org/holobiomicslab/asb-skill/collection/metabolomics/v2
  assembled_by: scripts/collect_metabolomics_collection.py
  sources:
  - build: coll_dreams_cq
    doi: 10.1038/s41587-025-02663-3
    title: DreaMS
  dedup_kept_from: coll_dreams_cq
schema_version: 0.2.0
attribution:
  generator: AgenticScienceBuilder
  original_doi: 10.1038/s41587-025-02663-3
  all_source_dois:
  - 10.1038/s41587-025-02663-3
  zenodo_doi: 10.5281/zenodo.20794027
  curators: []
  promoter: Louis-Félix Nothias
  sponsor: CNRS & Université Côte d'Azur
---

# Python Environment Dependency Resolution

## Summary

Resolve and install Python package dependencies declared in a requirements.txt file using pip, enabling creation of an importable and reproducible Python environment. This skill ensures all necessary libraries are available before executing code that depends on them.

## When to use

When you have cloned a Python project repository and need to set up a working environment with all required packages, or when requirements.txt exists but dependencies are not yet installed in your current Python environment. Specifically triggered when attempting to import a package fails with ModuleNotFoundError, or when documentation instructs environment setup before proceeding to analysis or tutorial steps.

## When NOT to use

- If you are using a different package manager (e.g., conda with environment.yml, or Poetry with pyproject.toml); use the package manager native to the project instead.
- If the requirements.txt file is missing or the project uses a setup.py-only distribution; use 'pip install -e .' or 'pip install .' to install from the project's setup configuration.
- If you need to pin versions for reproducibility across machines and environments; use a locked requirements file (e.g., requirements-lock.txt generated by pip-freeze or pip-tools) instead.

## Inputs

- requirements.txt file (text file with one Python package specification per line)
- Active Python environment (conda, venv, or system Python)
- Network access to PyPI (Python Package Index)

## Outputs

- Installed Python packages in the target environment
- Updated site-packages directory with all dependencies
- Importable module namespace matching requirements.txt declarations

## How to apply

Locate the requirements.txt file in the project root directory. Execute 'pip install -r requirements.txt' from the command line within the target Python environment (activate the conda/virtual environment first if using one). The pip tool parses the requirements.txt file to identify all declared package names and version constraints, then downloads and installs them from PyPI. Verify successful installation by attempting to import each key package in a Python interpreter. If installation fails, check that pip and setuptools are up-to-date, that the requirements.txt syntax is valid (one package per line, with optional version specifiers like ==, >=, or <), and that you have internet access to PyPI.

## Related tools

- **pip** (Package installer and dependency resolver that reads requirements.txt and installs packages from PyPI) — https://pip.pypa.io/en/stable/
- **conda** (Alternative environment and package manager; useful if requirements.txt contains non-Python dependencies or if conda-specific packages are needed) — https://conda.io/projects/conda/en/latest/

## Examples

```
pip install -r requirements.txt
```

## Evaluation signals

- No error messages or warnings when running 'pip install -r requirements.txt'
- Successful import of key packages in Python interpreter (e.g., 'python -c "import dreams"' or 'python -c "import ppiref"')
- Output of 'pip list' shows all packages from requirements.txt with matching or compatible versions
- Tutorial or downstream workflow scripts run without ModuleNotFoundError
- Version constraints in requirements.txt are satisfied (verify with 'pip show <package>')

## Limitations

- requirements.txt may reference outdated or pinned versions that conflict with other packages in the environment; resolving such conflicts may require manual version negotiation or use of a more sophisticated resolver like pip-tools.
- Platform-specific or compiled packages (e.g., PyTorch with CUDA support) may require additional configuration beyond pip install; check project documentation for platform-specific installation steps.
- Transitive dependencies (dependencies of dependencies) are handled automatically by pip, but if requirements.txt does not pin indirect dependencies, different installation orders or times may yield different resolved versions.
- Network connectivity and PyPI availability are required; installation will fail if PyPI is unreachable or if a package has been removed from PyPI.

## Evidence

- [other] DreaMS Python dependencies are declared in a requirements.txt file and can be installed using pip with the command 'pip install -r requirements.txt'.: "DreaMS Python dependencies are declared in a requirements.txt file and can be installed using pip with the command 'pip install -r requirements.txt'."
- [methods] pip install -r requirements.txt as documented workflow step for dependency installation: "Install requirements  [section=methods; evidence='pip install -r requirements.txt']"
- [readme] Installation instructions in DreaMS README showing environment setup followed by pip install -e: "# Install DreaMS
pip install -e ."
- [readme] PPIRef installation workflow using pip install with editable mode: "git clone https://github.com/anton-bushuiev/PPIRef.git
cd PPIRef; pip install -e ."