Runnable example
Resilient batch data pipeline
Build an isolated, bounded data batch processing pipeline with error recovery using the standard library.
The problem
Batch jobs receive semi-structured input where one malformed record cannot be allowed to kill the run. A resilient pipeline isolates failures, validates field types, and produces a structured summary of what succeeded and what failed.
The contract
- Isolate per-record failures so one bad record never aborts the batch.
- Validate field types before processing and collect structured errors.
- Generate structured run summaries of successes and failures without crashing.
Verify it locally
From the root of the FlyPython repository, reproduce the broken starter first, then verify the reviewed solution:
python examples/structured-pipeline/verify.py starter --expect-failurepython examples/structured-pipeline/verify.py solutionHand it to a coding agent
- Clone the repository and reproduce the starter failure with the command above.
- Give the task contract ↗ to your coding agent and allow changes only in
starter/pipeline.py. - Run
python examples/structured-pipeline/verify.py starterand treat any failure as unfinished work. - Compare the patch with the reference solution ↗ — the goal is the same contract with a small, readable diff, not identical syntax.
Keep going
Where this example sits in the roadmap.
Reviewed 2026-09-02 · Repository content version 1. Continue with the related learning path, the repository directory, or the MCP migration guide for the specification background.