pixi-make-offline-channel
Use when the user wants to create a self-hosted, offline-installable Conda channel (mirror) containing a specific subset of packages using Pixi.
Best use case
pixi-make-offline-channel is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when the user wants to create a self-hosted, offline-installable Conda channel (mirror) containing a specific subset of packages using Pixi.
Teams using pixi-make-offline-channel should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/pixi-make-offline-channel/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How pixi-make-offline-channel Compares
| Feature / Agent | pixi-make-offline-channel | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when the user wants to create a self-hosted, offline-installable Conda channel (mirror) containing a specific subset of packages using Pixi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Pixi Make Offline Channel ## Trigger Use this skill when the user asks to: - "Create a local conda channel with pixi" - "Mirror a subset of conda packages for offline use" - "Download conda packages and dependencies using pixi" - "Create a self-hosted conda-forge mirror" ## Overview This skill guides the user to creating a **custom, self-hosted Conda channel** (mirror) that contains only a selected subset of packages but includes **all transitive dependencies**. This ensures the channel is fully installable on offline machines. The workflow uses Pixi's lockfile (`pixi.lock`) as the source of truth for dependency resolution and `rattler-index` for generating channel metadata. ## Workflow ### 1. Setup Builder Project Create a temporary "builder" project to define the package set. This project will not be used for running code, but for resolving the dependency tree. ```bash mkdir my-mirror-builder cd my-mirror-builder pixi init ``` ### 2. Define Package Subset Add the target packages you want to mirror. Also add the necessary build tools (`rattler-index` and `pyyaml`) to the environment. ```bash # Target packages to mirror pixi add pandas scikit-learn pytorch # Tools required for the mirroring process pixi add rattler-index pyyaml requests ``` ### 3. Fetch Artifacts (The "Mirror Script") Use a Python script to parse `pixi.lock`, extract the exact URLs for all resolved dependencies, and download them into a standard channel structure (e.g., `channel/linux-64/`). **Key Steps for the Script:** 1. Read `pixi.lock` (YAML format). 2. Iterate through `packages`. 3. Download the file at `url` to `output_dir/<platform>/<filename>`. *Ref: See `context/hints/howto-create-self-hosted-conda-subset-repo-with-pixi.md` for the complete `build_mirror.py` script.* ### 4. Index the Channel After downloading all artifacts, use `rattler-index` to generate the `repodata.json`. This turns the directory into a valid Conda channel. ```bash pixi run rattler-index local-channel ``` ### 5. Verify & Consume The channel is now ready. It can be used via `file://` or hosted via HTTP. **Verification:** ```bash # Create a test env using ONLY the local channel conda create -n test-offline -c file://$(pwd)/local-channel pandas --offline --override-channels ``` ## Tips * **Multi-Platform**: To support multiple platforms (e.g., `linux-64` AND `osx-arm64`), manually edit `pixi.toml` to include them (`platforms = ["linux-64", "osx-arm64"]`) and run `pixi lock` before running the download script. * **Updates**: To update the mirror, simply `pixi update` the builder project, re-run the download script (it should skip existing files), and re-run `rattler-index`. * **Pixi-Pack**: If the goal is just to *move* one environment, suggest `pixi-pack` instead. This skill is for creating a *reusable channel*. ## Resources * **[howto-create-self-hosted-conda-subset-repo-with-pixi.md](../../../../context/hints/howto-create-self-hosted-conda-subset-repo-with-pixi.md)**: Detailed step-by-step guide with the full Python script.
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