Move a Project to Another Machine¶

This guide teaches you how to move a pytask project to another machine or environment and reuse existing outputs where possible.

Update the lockfile on the source machine¶

Run a normal build with pytask build before moving the project with its pytask.lock and files and outputs are up-to-date:

$ pytask build

Move the project files and reusable outputs¶

If you have not done it yet, commit pytask.lock to your repository and move it with the project. In practice, move:

• the project files tracked in version control, including source files, configuration, data inputs, and pytask.lock
• the build artifacts you want to reuse, often in bld/ if you follow the tutorial layout
• the .pytask folder if you use the data catalog and it manages some of your files

Keep external files in the same relative layout¶

If tasks use files outside the project root, keep the same relative layout on the target machine. The project root is the folder with the pyproject.toml file.

For example, if a task reads ../shared/input.csv from the source machine, the moved project also needs a readable ../shared/input.csv next to the project root on the target machine.

Run pytask on the target machine¶

After you moved the project to the target machine, run pytask to build the project:

$ pytask build

Assuming that the project was fully built before the move, pytask will not rebuild the project and skip all tasks.

Clean stale lockfile entries¶

If you removed, renamed, or moved tasks before transferring the project, clean up stale lockfile entries on the source machine before you move the project:

$ pytask build --clean-lockfile

This rewrites the lockfile after a successful build with only the currently collected tasks and their current state values.

If your project uses custom nodes¶

Make sure custom node IDs and state values stay stable across machines:

• Use project-relative IDs instead of absolute paths.
• Prefer file content hashes over timestamps.
• Avoid machine-specific paths or timestamps in custom state() implementations.
• Provide a custom hash function for PythonNode values that are not natively stable.

Most projects that only use built-in nodes do not need extra work here.