sql_insert_writer

Helps generate highly readable SQL INSERT statements

$ sql_insert_writer pet

INSERT INTO pet (
  id,
  name,
  species_name,
  planet,
  kg
)
VALUES
(
  DEFAULT,  -- ==> id
  DEFAULT,  -- ==> name
  DEFAULT,  -- ==> species_name
  DEFAULT,  -- ==> planet
  DEFAULT  -- ==> kg
)

$ sql_insert_writer pet animal

INSERT INTO pet (
  id,
  name,
  species_name,
  planet,
  kg
)
SELECT
  id,  -- ==> id
  name,  -- ==> name
  species_name,  -- ==> species_name
  planet,  -- ==> planet
  DEFAULT  -- ==> kg
FROM animal

• Documentation: https://sql-insert-writer.readthedocs.io.

Rationale

The syntax of INSERT statements makes it difficult to tell which destination columns a value is intended for, especially in inserts with many columns. (Our five-column example is not bad, but imagine fifty columns!)

Comments can clarify the link between data source and destination, but adding those comments manually is tedious and error-prone.

Explicitly listing the destination columns of an INSERT is another best practice often skipped due to tedium.

The output of sql_insert_writer will rarely be fully ready to execute, but it should save the bulk of the typing.

Features

• Supports PostgreSQL, SQLite, MySQL
• Accepts SQLAlchemy database URLs with --db option. Defaults to environment variable $DATABASE_URL.
• Any number of source tables; columns chosen in order specified
• Any number of tuples in VALUES clause with --tuples option
• Explicitly cast to destination column type with --cast option

Installtion

Installation instructions

Usage

See usage examples here

Planned features

• Support for more databases
• Approximate column name matches
• Omit inserts into auto-incrementing primary key columns
• Pre-fill JOIN clauses with foreign keys where possible

Limitations

We do not deal well with case-sensitive table or column names; for lo, they are an abomination unto Codd.

Credits

This package was created with Cookiecutter and the 18F/cookiecutter-pypackage project template.

Public domain

This project is in the worldwide public domain. As stated in CONTRIBUTING:

This project is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the CC0 1.0 Universal public domain dedication.

All contributions to this project will be released under the CC0 dedication. By submitting a pull request, you are agreeing to comply with this waiver of copyright interest.