simple-ddl-parser 0.2.1a0

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Simple DDL Parser

Parser tested on DDL for PostgreSQL & Hive.

If you have samples that cause an error - please open the issue, I will be glad to fix it.

This parser take as input SQL DDL statements or files, for example like this:

    create table prod.super_table
(
    data_sync_id bigint not null,
    sync_count bigint not null,
    sync_mark timestamp  not  null,
    sync_start timestamp  not null,
    sync_end timestamp  not null,
    message varchar(2000) null,
    primary key (data_sync_id, sync_start)
);

And produce output like this (information about table name, schema, columns, types and properties):

[{
'columns': [
    {'name': 'data_sync_id', 'type': 'bigint', 'mode': False, 'size': None},
    {'name': 'sync_count', 'type': 'bigint', 'mode': False, 'size': None},
    {'name': 'sync_mark', 'type': 'timestamp', 'mode': False, 'size': None},
    {'name': 'sync_start', 'type': 'timestamp', 'mode': False, 'size': None},
    {'name': 'sync_end', 'type': 'timestamp', 'mode': False, 'size': None},
    {'name': 'message', 'type': 'varchar', 'mode': False, 'size': 2000}],
'table_name': 'super_table', 'schema': 'prod',
'primary_key': ['data_sync_id', 'sync_start']
}]

Or one more example

CREATE TABLE "paths" (
  "id" int PRIMARY KEY,
  "title" varchar NOT NULL,
  "description" varchar(160),
  "created_at" timestamp,
  "updated_at" timestamp
);

and result

[{
'columns': [
    {'name': 'id', 'type': 'int', 'nullable': False, 'size': None},
    {'name': 'title', 'type': 'varchar', 'nullable': False, 'size': None},
    {'name': 'description', 'type': 'varchar', 'nullable': False, 'size': 160},
    {'name': 'created_at', 'type': 'timestamp', 'nullable': False, 'size': None},
    {'name': 'updated_at', 'type': 'timestamp', 'nullable': False, 'size': None}],
'primary_key': ['id'],
'table_name': 'paths', 'schema': ''
}]

If you pass file or text block with more when 1 CREATE TABLE statement when result will be list of such dicts. For example:

Input

CREATE TABLE "countries" (
  "id" int PRIMARY KEY,
  "code" varchar(4) NOT NULL,
  "name" varchar NOT NULL
);

CREATE TABLE "path_owners" (
  "user_id" int,
  "path_id" int,
  "type" int DEFAULT 1
);

Output:

[
    {'columns': [
        {'name': 'id', 'type': 'int', 'size': None, 'nullable': False, 'default': None},
        {'name': 'code', 'type': 'varchar', 'size': 4, 'nullable': False, 'default': None},
        {'name': 'name', 'type': 'varchar', 'size': None, 'nullable': False, 'default': None}],
     'primary_key': ['id'],
     'table_name': 'countries',
     'schema': None},
    {'columns': [
        {'name': 'user_id', 'type': 'int', 'size': None, 'nullable': False, 'default': None},
        {'name': 'path_id', 'type': 'int', 'size': None, 'nullable': False, 'default': None},
        {'name': 'type', 'type': 'int', 'size': None, 'nullable': False, 'default': '1a'}],
     'primary_key': [],
     'table_name': 'path_owners',
     'schema': None}
]

How to use

From python code

from simple_ddl_parser import DDLParser


parse_results = DDLParser("""create table dev.data_sync_history(
    data_sync_id bigint not null,
    sync_count bigint not null,
    sync_mark timestamp  not  null,
    sync_start timestamp  not null,
    sync_end timestamp  not null,
    message varchar(2000) null,
    primary key (data_sync_id, sync_start)
); """).run()

print(parse_results)

To parse from file

from simple_ddl_parser import parse_from_file

result = parse_from_file('tests/test_one_statement.sql')
print(result)

More examples & tests

You can find in tests/functional folder.

Dump result in json

To dump result in json use argument .run(dump=True)

You also can provide a path where you want to have a dumps with schema with argument

TODO in next Releases

1. Support for references (Foreigein key) in column defenition

2. Support for separate ALTER TABLE statements for Foreigein keys like

ALTER TABLE "material_attachments" ADD FOREIGN KEY ("material_id") REFERENCES "materials" ("id");

1. Support for parse CREATE INDEX statements

2. Add command line

Historical context

This library is an extracted parser code from https://github.com/xnuinside/fakeme (Library for fake relation data generation, that I used in several work projects, but did not have time to make from it normal open source library)

For one of the work projects I needed to convert SQL ddl to Python ORM models in auto way and I tried to use https://github.com/andialbrecht/sqlparse but it works not well enough with ddl for my case (for example, if in ddl used lower case - nothing works, primary keys inside ddl are mapped as column name not reserved word and etc.). So I remembered about Parser in Fakeme and just extracted it & improved.

How to contribute

Please describe issue that you want to solve and open the PR, I will review it as soon as possible.

Any questions? Ping me in Telegram: https://t.me/xnuinside