# csv2pg: CSV → PostgreSQL without the shell dance

*2026-06-16*

> A standalone Python CLI that infers a Postgres schema from a CSV and loads it over the native COPY protocol — all in-process, one transaction.


Most "import this CSV" advice ends with `psql` invocations, `\copy` meta-commands, and a schema you hand-write after eyeballing the data in a spreadsheet. I got tired of that ritual, so `csv2pg` does the whole path in-process through psycopg3: analyze the file, infer the schema, create the table, stream the rows, verify the count, commit. No `psql` binary involved anywhere.

The interesting part is the type inference. It samples up to 100 random rows per column to guess a candidate PostgreSQL type, then validates that guess against *every* row in the file. If validation fails, the column widens to the next compatible type — up to five attempts — before falling back to `text`. You get a tabulated summary plus a generated `.sql` file before anything touches the database.

Features:

- Multi-pass type inference with validation against the full file, not just a sample
- Loads via PostgreSQL's native `COPY ... FROM STDIN` protocol — fast on real-sized files
- Single transaction end to end: any failure rolls back completely, no partial tables left behind
- `--autoimport` for scripted runs, `--dry-run` to validate everything without writing
- Custom target schema (`--schema`), auto-created if missing
- Credentials via a single libpq `$CONDB` string; passwords redacted from logs automatically
- Every run produces timestamped `.sql` and `.log` artifacts
- Unit tests run database-free; integration tests activate when `$CONDB` is set

Source: [github.com/rahlquist/csv2pg](https://github.com/rahlquist/csv2pg) · MIT licensed.