Options

• Free software: MIT license

Supported data formats

• Pure Python

• YAML

• JSON

• CSV

• Pickle

Features

• Supports all SQL dialects supported by SQLAlchemy

• Coerces data into most specific data type valid on all column’s values

• Takes table name from file name

• Guesses format of input data if unspecified by file extension

• with -i/--inserts flag, adds INSERT statements

• with -u/--uniques flag, surmises UNIQUE constraints from data

• Handles nested data, creating child tables as needed

• Accepts wildcards in filenames (remember quote marks to avoid shell expansion)

Options

-h, --help            show this help message and exit
-k KEY, --key KEY     Field to use as primary key
-r, --reorder         Reorder fields alphabetically, ``key`` first
-u, --uniques         Include UNIQUE constraints where data is unique
-t, --text            Use variable-length TEXT columns instead of VARCHAR
-d, --drops           Include DROP TABLE statements
-i, --inserts         Include INSERT statements
--no-creates          Do not include CREATE TABLE statements
--save-metadata-to FILENAME
                      Save table definition in FILENAME for later --use-
                      saved-metadata run
--use-metadata-from FILENAME
                      Use metadata saved in FROM for table definition, do
                      not re-analyze table structure
-l LOG, --log LOG     log level (CRITICAL, FATAL, ERROR, DEBUG, INFO, WARN)

Large tables

As of now, ddlgenerator is not well-designed for table sizes approaching your system’s available memory. It does accept a –limit keyword that should help when creating DDL from very large tables.

Another (messier) approach is to break your input data into multiple files, then run ddlgenerator with --save-metadata against a small but representative sample. Then run with --no-creates and -use-saved-metadata to generate INSERTs from the remaining files without needing to re-determine the column types each time.

Installing

git clone git clone https://github.com/catherinedevlin/ddl-generator.git
cd ddl-generator
python setup.py install

Credits

• Mike Bayer for sqlalchemy

• coldfix and Mark Ransom for their StackOverflow answers

• Audrey Roy for cookiecutter

History