pypa/hatch

"env show --json" fails with an error if some plugin is not installed

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#2,011 opened on Jun 24, 2025

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Description

I am working on integrating Hatch in PyCharm and encountered an issue with the --json flag, which breaks our integration.

steps to reproduce:

  1. hatch-container plugin is not installed

  2. git clone https://github.com/ofek/hatch-showcase

  3. ➜ hatch-showcase git:(master) hatch env show --json Environment all.py3.7 has unknown type: container

  4. hatch-showcase git:(master) hatch env show Standalone ┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓ ┃ Name ┃ Type ┃ Dependencies ┃ Scripts ┃ ┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩ │ default │ virtual │ coverage[toml]>=6.5 │ cov │ │ │ │ pytest │ cov-report │ │ │ │ │ test │ │ │ │ │ test-cov │ ├─────────┼─────────┼─────────────────────┼────────────┤ │ lint │ virtual │ black>=22.10.0 │ all │ │ │ │ mypy>=0.991 │ fmt │ │ │ │ ruff>=0.0.166 │ style │ │ │ │ │ typing │ └─────────┴─────────┴─────────────────────┴────────────┘ Matrices ┏━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓ ┃ Name ┃ Type ┃ Envs ┃ Dependencies ┃ Scripts ┃ ┡━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩ │ all │ container │ all.py3.7 │ coverage[toml]>=6.5 │ cov │ │ │ │ all.py3.8 │ pytest │ cov-report │ │ │ │ all.py3.9 │ │ test │ │ │ │ all.py3.10 │ │ test-cov │ │ │ │ all.py3.11 │ │ │ └──────┴───────────┴────────────┴─────────────────────┴────────────┘

Expected Behaviour:

Hatch shows environments in json format, at least available ones

Contributor guide

Research direction
Investigate the code path in the `env show` command that produces JSON output, specifically how it handles environment types that are not recognized because the corresponding plugin is not installed. Modify the logic to gracefully handle unknown types, e.g., by skipping such environments or showing a placeholder like `unknown`.
Tech stack
python
Domain
cli
Issue type
Bug
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
PythonGit
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
75