env-repair 0.2.2

Scan and repair conda/mamba/micromamba environments with mixed conda/pip installs.

🩺 EnvRepair

Fixing broken Python environments – safely, transparently, reproducibly

EnvRepair is a practical repair tool for the messy reality of Python environments:
Conda / Mamba / Micromamba mixed with pip, plus plain venv / virtualenv.

Instead of starting over (again), EnvRepair helps you understand what’s broken, why it’s broken, and fix it safely – with snapshots and rollback support, so you’re never locked in.

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🤕 Why EnvRepair Exists

If you’ve ever seen things like:

• duplicate .dist-info folders
• mysterious .pyd conflicts on Windows
• conda-meta JSON files that suddenly break tools like PyInstaller
• environments that are “inconsistent” but still half-working
• pip + conda silently stepping on each other’s toes

…then EnvRepair is for you.

It doesn’t try to replace conda or pip.
It steps in after things already went wrong.

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✨ What EnvRepair Can Do

🔍 Diagnose

• Detect duplicates and leftovers (.dist-info, stale artifacts, some Windows .pyd duplicates).
• Find corrupted or incomplete conda-meta entries.
• Detect pip/conda case-sensitivity conflicts.

🛠️ Repair (carefully!)

• Repair mixed conda + pip installs using the right tool.
• Reinstall broken packages with source awareness.
• “Adopt” pip packages into conda where possible (--adopt-pip).
• Handle plain venv / virtualenv setups (pip-only mode).

🛟 Safety First

• Automatic rescue snapshots before any destructive action.
• Graceful recovery after Ctrl+C.
• Clear prompts instead of silent force-fixes.

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🧰 Requirements

• Windows, Linux, or macOS.
• mamba in PATH for conda-style envs (preferred). conda/micromamba also work in many cases.
• Python available in the target environment.

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🚀 Quick Start

All examples below use Windows cmd.exe syntax (.bat blocks).
Adjust paths/shells as needed for Linux/macOS.

Basic scan (auto-discovers conda envs):

python env_repair.py

Install as a CLI (editable):

pip install -e .
env-repair --help

Install from local checkout (non-editable):

pip install .

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🔁 Common Workflows

Fix base:

python env_repair.py --env base --fix

Fix a plain venv (pip-only):

python env_repair.py --env .venv --fix

Same via installed CLI:

env-repair --env base --fix

Adopt pip packages into conda (where possible):

python env_repair.py --env base --fix --adopt-pip

Verify imports (and fix what can be fixed):

python env_repair.py verify-imports --env base --full --fix

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⏪ Rollback & Rebuild

Rollback to previous conda revision:

env-repair rollback --env base --to prev

Rollback without prompt:

env-repair rollback --env base --to prev -y

Rebuild into a new env (name):

env-repair rebuild --env base --to base-rebuilt --verify

Rebuild into a new env (path):

env-repair rebuild --env base --to C:\temp\base-rebuilt --verify

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🧪 Advanced Diagnostics

Diagnose a ClobberError from a logfile:

env-repair diagnose-clobber --env base --logfile clobber.txt

Diagnose / fix “inconsistent” env:

env-repair diagnose-inconsistent --env base
env-repair fix-inconsistent --env base --level safe

Cache check / fix:

env-repair cache-check
env-repair cache-fix --level safe

SSL diagnosis:

env-repair diagnose-ssl --base
env-repair diagnose-ssl --env base

Create a conda-style snapshot (YAML):

python env_repair.py --env base --snapshot snapshots\base.yaml

Debug output:

python env_repair.py --env base --fix --adopt-pip --debug

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🛟 Safety Net (Ctrl+C / Rescue)

• When you run with --fix, EnvRepair creates a rescue snapshot under:

  .env_repair\snapshots\...
  

• If you abort during a pip/mamba/conda step, EnvRepair will prompt:
  • r restore from snapshot
  • c continue (skip)
  • a abort (default)
• A .env_repair\state.json file records progress so you can inspect what happened and re-run later.

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🔎 Import Verification (verify-imports)

EnvRepair can scan installed distributions and run python -c "import <name>" for their top-level modules.

Full scan + auto-fix (recommended when an env is “mostly working but randomly broken”):

python env_repair.py verify-imports --env base --full --fix --debug

Notes:

• Repairs use batched conda/mamba operations (no slow one-by-one reinstalls).
• If the solver fails for a specific package, EnvRepair retries the batch without the offending spec and remembers it in:
  • .env_repair\verify_imports_blacklist.json
• Platform-only modules are skipped (e.g. sh on Windows, ptyprocess missing fcntl on Windows).

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🧑‍💻 Development

Run tests:

python -m unittest discover -s tests -p "test_*.py"

JSON output:

python env_repair.py --env base --json

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📝 Notes

• --adopt-pip installs only mapped PyPI packages.
• --adopt-pip is conda-only; for plain venvs it is ignored.
• After successful adoption, env-repair uninstalls the pip version by default; use --keep-pip to skip.
• For alias-like mappings (e.g. pip msgpack → conda msgpack-python), pip is only removed if both versions match.
• Channels are loaded from .condarc first, then defaults and anaconda unless disabled.
• --debug prints the exact external command lines as [cmd] ... (mamba/conda/pip), and streams live output to keep long operations transparent.

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📁 Files

• env_repair.py – CLI shim (kept for convenience).
• env_repair/ – actual implementation.
• docs/ – design notes, feature specs, and roadmaps.

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📦 Releases

PyPI releases are automated via GitHub Actions (Trusted Publishing) on tags:

• vX.Y.Z → .github/workflows/release-pypi.yml

conda-forge publishing is done via a feedstock (standard conda-forge process). For details see:

• docs/releasing.md

Local conda recipe (for testing) lives in:

• conda.recipe/

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❤️ Philosophy

EnvRepair is opinionated, but cautious.
It prefers understanding and repair over brute-force reinstallation.

If you’ve ever said “I’ll just recreate the environment…”
EnvRepair is here to save you that hour.