dataqual 0.1.0

CLI tool for auditing CSV, Excel, and PostgreSQL datasets — detects missing values, duplicates, type mismatches, and outliers

dataqual

CLI tool for auditing CSV/Excel/PostgreSQL datasets — detects missing values, duplicates, type mismatches, and outliers.

Install

pip install -e .

Check a dataset

Basic CSV check (Rich terminal report):

dataqual check --file data.csv

Export the report as a self-contained HTML page or JSON file (written to <name>_report.html / <name>_report.json):

dataqual check --file data.csv --report html
dataqual check --file data.csv --report json

Detect duplicates by key column(s) instead of full-row equality (rows with null keys are skipped, not treated as matching):

dataqual check --file data.csv --keys email
dataqual check --file data.csv --keys "email,phone"

Override alert thresholds with a YAML config (see dataqual.config.yaml for a commented example):

dataqual check --file data.csv --config dataqual.config.yaml

Load from Excel — --sheet takes a name or zero-based index, default first sheet:

dataqual check --file data.xlsx
dataqual check --file data.xlsx --sheet inventory

Check a PostgreSQL table or query

Use --db-url instead of --file, plus exactly one of --table or --query:

dataqual check --db-url postgresql://user:pass@host:5432/db --table public.users
dataqual check --db-url postgresql://user:pass@host:5432/db --query "SELECT * FROM users WHERE active"

Compare two datasets

Diff two files (CSV or Excel) — rows added, removed, and changed, with old/new values per column. --keys identifies "the same row" across both files and is strongly recommended; without it rows are matched by position:

dataqual compare --file1 old.csv --file2 new.csv --keys id

Development

pip install -e ".[dev]"
pytest
ruff check .