add-pipeline-stage

Add a pipeline stage

Add a single new stage to an existing Calkit pipeline—wiring up the right environment, inputs, outputs, and storage mode.

Before you start

Read calkit.yaml to understand what environments are already defined (you will reuse one if it fits) and what stages already exist and what they output (your new stage may depend on them).

Option A: Add with calkit xr

Use xr when the stage is a script or notebook file (.py, .ipynb, .R, .jl, .m, .sh, .tex) and you want auto-detection of I/O and environment.

calkit xr scripts/new-stage.py --dry-run   # preview first
calkit xr scripts/new-stage.py             # run for real

Override detected I/O or environment if needed:

calkit xr scripts/new-stage.py \
  --input data/processed.csv \
  --input config/params.yaml \
  --output results/output.csv \
  --environment main

After running, inspect the new stage in calkit.yaml to confirm I/O is correct.

Option B: Write the stage manually

Write YAML directly when the stage is a shell command, or when you need iterate_over, specific storage modes, or other fine-grained control.

File type	Stage kind
.py	python-script
.ipynb	jupyter-notebook
.sh	shell-script
Inline command	shell-command or command
.tex	latex
.R	r-script
.jl	julia-script
.m	matlab-script
docker run ...	docker-command

pipeline:
  stages:
    # ... existing stages ...

    new-stage-name:
      kind: python-script
      script_path: scripts/new-stage.py
      environment: main # must match a key in environments:
      inputs:
        - data/processed.csv
      outputs:
        - results/output.csv

Wiring dependencies

If the new stage reads files produced by an existing stage, declare them as inputs. List files explicitly, or depend on all outputs of a prior stage:

inputs:
  - data/processed.csv # explicit file
  - from_stage_outputs: process-data # all outputs of that stage

If an existing stage reads files your new stage now produces, update that stage's inputs too.

Output storage

• git—small or text files collaborators should see without calkit pull (PDFs, summary CSVs, HTML reports)
• dvc (default)—large or binary files

outputs:
  - results/large-matrix.npy # DVC (default)
  - path: results/summary.csv
    storage: git
  - path: results/report.html
    storage: git
    delete_before_run: false # keep old version if stage is skipped

After adding the stage

calkit run                                    # run full pipeline
calkit run new-stage-name                     # run only this stage
calkit status                                 # check what's stale
calkit commit -am "Add new-stage-name stage"

Common mistakes

• Wrong environment name: Must exactly match a key in environments. Run calkit check env --name <env> to verify.
• Two stages claiming the same output: Each file can only be the output of one stage.
• Missing inputs: If a stage reads a file but doesn't declare it, DVC won't re-run the stage when that file changes.
• Editing dvc.yaml: Don't—it's auto-generated from calkit.yaml.