csv-quality-gate 0.1.0

CSV preflight validation and batch CSV quality checks that fail fast before pipeline runs.

csv-quality-gate: CSV preflight validation before pipeline runs

Fail fast before pipeline runs when the input CSV is broken, incomplete, duplicated, or obviously junk.

csv-quality-gate runs batch CSV quality checks and returns pass, warn, or fail before expensive pipeline steps burn time on bad input.

• "We keep running expensive pipeline steps on broken CSVs."
• "A batch run fails 20 minutes in because the input CSV was junk."
• "We only discover missing required columns after the job already started."
• "Duplicate rows and empty contact fields keep polluting our batch runs."
• "I want CSV preflight validation, not a whole data platform."

Fastest install:

pip install csv-quality-gate

Fastest real usage:

csv-quality-gate check leads.csv --profile outreach

Exact outcome:

csv-quality-gate: FAIL
file: leads.csv
profile: outreach
rows: 125
  ERROR: missing required column: person_name
  WARNING: duplicate rate 12% exceeds warning threshold 10%

It is designed for narrow, honest use as a preflight gate, not as a full data quality platform.

Install

pip install csv-quality-gate

For development:

pip install -e ".[dev]"

Common search-intent use cases

• CSV preflight validation
• batch CSV quality checks
• fail fast before pipeline runs
• CSV validation before ETL or enrichment
• detect junk CSV rows before batch jobs

Usage

csv-quality-gate check leads.csv
csv-quality-gate check leads.csv --profile outreach
csv-quality-gate check leads.csv --profile generic --json

Exit codes:

• 0 pass
• 1 warnings only
• 2 fail

Profiles

Built-in profiles:

• generic
  • validates required columns, empties, duplicates, empty file
• outreach
  • adds suspicious company-name heuristics for GTM/contact pipelines

Output

csv-quality-gate: FAIL
file: leads.csv
profile: outreach
rows: 125
  ERROR: missing required column: person_name
  WARNING: duplicate rate 12% exceeds warning threshold 10%

JSON mode

csv-quality-gate check leads.csv --json

Limitations

• Heuristics are intentionally simple.
• The outreach profile is opinionated and should not be treated as universal truth.
• The tool validates shape and obvious noise, not semantic correctness.

When To Use It

• Before enrichment, outreach, ETL, or batch scoring runs
• In CI for checked-in CSV inputs
• As a preflight gate before expensive pipeline work

When Not To Use It

• When you need semantic validation of the data itself
• When your input is not CSV
• When you need a full data quality framework with lineage and profiling

More From Hermes Labs

• intent-verify: repo intent verification and spec drift checks

Development

ruff check .
python3 -m pytest -q
python3 -m py_compile src/csv_quality_gate/*.py