Simple DDL Parser to parse SQL & HQL ddl files to json/python dict with full information about columns: types, defaults, primary keys, etc.
Project description
Simple DDL Parser
Build with ply (lex & yacc in python). A lot of samples in ‘tests/’
How does it work?
Parser tested on different DDLs for PostgreSQL & Hive. But idea to support as much as possible DDL dialects, I already added such things as support MySQL ‘#’ comments. If you need to add something - please provide DDL example & information abotu that is it SQL dialect & DB.
Types that are used in your DB does not matter, so parser must also work successfuly to any DDL for SQL DB. Parser is NOT case sensitive, it did not expect that all queries will be in upper case or lower case. So you can write statements like this:
Alter Table Persons ADD CONSTRAINT CHK_PersonAge CHECK (Age>=18 AND City='Sandnes');
It will be parsed as is without errors.
If you have samples that cause an error - please open the issue (but don’t forget to add ddl example), I will be glad to fix it.
A lot of statements and output result you can find in tests on the github - https://github.com/xnuinside/simple-ddl-parser/tree/main/tests .
How to install
pip install simple-ddl-parser
How to use
Extract additional information from HQL (& other dialects)
In some dialects like HQL there is a lot of additional information about table like, fore example, is it external table, STORED AS, location & etc. This propertie will be always empty in ‘classic’ SQL DB like PostgreSQL or MySQL and this is the reason, why by default this information are ‘hidden’.
To get this ‘hql’ specific details about table in output please use ‘output_mode’ argument in run() method.
example:
ddl = """
CREATE TABLE IF NOT EXISTS default.salesorderdetail(
SalesOrderID int,
ProductID int,
OrderQty int,
LineTotal decimal
)
PARTITIONED BY (batch_id int, batch_id2 string, batch_32 some_type)
LOCATION 's3://datalake/table_name/v1'
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
COLLECTION ITEMS TERMINATED BY '\002'
MAP KEYS TERMINATED BY '\003'
STORED AS TEXTFILE
"""
result = DDLParser(ddl).run(output_mode="hql")
print(result)
And you will get output with additional keys ‘stored_as’, ‘location’, ‘external’, etc.
# additional keys examples
{
...,
'location': "'s3://datalake/table_name/v1'",
'map_keys_terminated_by': "'\\003'",
'partitioned_by': [{'name': 'batch_id', 'size': None, 'type': 'int'},
{'name': 'batch_id2', 'size': None, 'type': 'string'},
{'name': 'batch_32', 'size': None, 'type': 'some_type'}],
'primary_key': [],
'row_format': 'DELIMITED',
'schema': 'default',
'stored_as': 'TEXTFILE',
...
}
If you run parser with command line add flag ‘-o=hql’ or ‘–output-mode=hql’ to get the same result.
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/sql/test_one_statement.sql')
print(result)
From command line
simple-ddl-parser is installed to environment as command sdp
sdp path_to_ddl_file
# for example:
sdp tests/sql/test_two_tables.sql
You will see the output in schemas folder in file with name test_two_tables_schema.json
If you want to have also output in console - use -v flag for verbose.
sdp tests/sql/test_two_tables.sql -v
If you don’t want to dump schema in file and just print result to the console, use –no-dump flag:
sdp tests/sql/test_two_tables.sql --no-dump
You can provide target path where you want to dump result with argument -t, –targer:
sdp tests/sql/test_two_tables.sql -t dump_results/
More details
This parser take as input SQL DDL statements or files, for example like this:
CREATE TABLE employees (
id SERIAL PRIMARY KEY,
first_name VARCHAR (50),
last_name VARCHAR (50),
birth_date DATE CHECK (birth_date > '1900-01-01'),
joined_date DATE CHECK (joined_date > birth_date),
salary numeric CHECK(salary > 0),
phone_numbers varchar(16) array,
tags varchar ARRAY[1]
);
CREATE TABLE dev.Persons (
ID int NOT NULL,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Age int,
City varchar(255),
Country varchar(255),
CONSTRAINT CHK_Person CHECK (Age>=19 AND City='Sandnes')
);
ALTER TABLE dev.Persons ADD CHECK (Age>=18 AND City='Sandnes');
ALTER TABLE dev.Persons Add CONSTRAINT ck_person CHECK (Age>=18 AND City='Sandnes');
Alter Table dev.Persons ADD CONSTRAINT fk_group FOREIGN KEY (id) REFERENCES employees (id);
create unique index person_pk on dev.Persons (ID) ;
create index person_ix2 on dev.Persons (City, Country);
And produce output like this (information about table name, schema, columns, types and properties):
[{
'table_name': 'employees',
'index': [],
'primary_key': ['id'],
'schema': None,
'alter': {},
'checks': [],
'columns': [{'check': None,
'default': None,
'name': 'id',
'nullable': False,
'references': None,
'size': None,
'type': 'SERIAL',
'unique': False},
{'check': None,
'default': None,
'name': 'first_name',
'nullable': True,
'references': None,
'size': 50,
'type': 'VARCHAR',
'unique': False},
{'check': None,
'default': None,
'name': 'last_name',
'nullable': True,
'references': None,
'size': 50,
'type': 'VARCHAR',
'unique': False},
{'check': "birth_date > '1900-01-01'",
'default': None,
'name': 'birth_date',
'nullable': True,
'references': None,
'size': None,
'type': 'DATE',
'unique': False},
{'check': 'joined_date > birth_date',
'default': None,
'name': 'joined_date',
'nullable': True,
'references': None,
'size': None,
'type': 'DATE',
'unique': False},
{'check': None,
'default': None,
'name': 'phone_numbers',
'nullable': True,
'references': None,
'size': 16,
'type': 'varchar[]',
'unique': False},
{'check': None,
'default': None,
'name': 'tags',
'nullable': True,
'references': None,
'size': None,
'type': 'varchar[1]',
'unique': False}]},
{'table_name': 'Persons',
'index': [{'columns': ['ID'], 'index_name': 'person_pk', 'unique': True},
{'columns': ['City', 'Country'],
'index_name': 'person_ix2',
'unique': False}],
'primary_key': [],
'schema': 'dev', 'partitioned_by': [],
'alter': {'checks': [{'constraint_name': None,
'statement': ['Age>=18', 'AND', "City='Sandnes'"]},
{'constraint_name': 'ck_person',
'statement': ['Age>=18', 'AND', "City='Sandnes'"]}],
'columns': [{'constraint_name': 'fk_group',
'name': 'id',
'references': {'column': 'id',
'schema': None,
'table': 'employees'}}]},
'checks': [{'constraint_name': 'CHK_Person',
'statement': "Age>=19 AND City='Sandnes'"}],
'columns': [{'check': None,
'default': None,
'name': 'ID',
'nullable': False,
'references': None,
'size': None,
'type': 'int',
'unique': False},
{'check': None,
'default': None,
'name': 'LastName',
'nullable': False,
'references': None,
'size': 255,
'type': 'varchar',
'unique': False},
{'check': None,
'default': None,
'name': 'FirstName',
'nullable': True,
'references': None,
'size': 255,
'type': 'varchar',
'unique': False},
{'check': None,
'default': None,
'name': 'Age',
'nullable': True,
'references': None,
'size': None,
'type': 'int',
'unique': False},
{'check': None,
'default': None,
'name': 'City',
'nullable': True,
'references': None,
'size': 255,
'type': 'varchar',
'unique': False},
{'check': None,
'default': None,
'name': 'Country',
'nullable': True,
'references': None,
'size': 255,
'type': 'varchar',
'unique': False}]
}]
SEQUENCES
When we parse SEQUENCES each property stored as a separate dict KEY, for example for sequence:
CREATE SEQUENCE dev.incremental_ids
INCREMENT 1
START 1
MINVALUE 1
MAXVALUE 9223372036854775807
CACHE 1;
Will be output:
[
{'schema': 'dev', 'partitioned_by': [], 'incremental_ids': 'document_id_seq', 'increment': 1, 'start': 1, 'minvalue': 1, 'maxvalue': 9223372036854775807, 'cache': 1}
]
ALTER statements
Right now added support only for ALTER statements with FOREIGEIN key
For example, if in your ddl after table defenitions (create table statements) you have ALTER table statements like this:
ALTER TABLE "material_attachments" ADD FOREIGN KEY ("material_id", "material_title") REFERENCES "materials" ("id", "title");
This statements will be parsed and information about them putted inside ‘alter’ key in table’s dict. For example, please check alter statement tests - tests/test_alter_statements.py
More examples & tests
You can find in tests/ 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 .run(dump_path=’folder_that_use_for_dumps/’)
Supported Statements
CREATE TABLE [ IF NOT EXISTS ] + columns defenition, columns attributes: column name + type + type size(for example, varchar(255)), UNIQUE, PRIMARY KEY, DEFAULT, CHECK, NULL/NOT NULL, REFERENCES
STATEMENTS: PRIMARY KEY, CHECK, FOREIGN KEY in table defenitions (in create table();)
ALTER TABLE STATEMENTS: ADD CHECK (with CONSTRAINT), ADD FOREIGN KEY (with CONSTRAINT)
PARTITIONED BY statement
HQL Dialect statements
PARTITIONED BY statement
ROW FORMAT
STORED AS
LOCATION, FIELDS TERMINATED BY, COLLECTION ITEMS TERMINATED BY, MAP KEYS TERMINATED BY
TODO in next Releases (if you don’t see feature that you need - open the issue)
Add support for CREATE VIEW statement
Add support CREATE TABLE … LIKE statement
Add support for REFERENCES ON (https://github.com/xnuinside/simple-ddl-parser/issues/18)
non-feature todo
Provide API to get result as Python Object
Add online demo (UI) to parse ddl
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 run tests
git clone https://github.com/xnuinside/simple-ddl-parser.git
cd simple-ddl-parser
poetry install # if you use poetry
# or use `pip install .`
pytest tests/ -vv
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
Changelog
v0.8.1
Added support for HQL Structured types like ARRAY < STRUCT <street: STRING, city: STRING, country: STRING >>, MAP < STRING, STRUCT < year: INT, place: STRING, details: STRING >>, STRUCT < street_address: STRUCT <street_number: INT, street_name: STRING, street_type: STRING>, country: STRING, postal_code: STRING >
v0.8.0
To DDLParser’s run method was added ‘output_mode’ argument that expect valur ‘hql’ or ‘sql’ (by default). Mode change result output. For example, in hql exists statement EXTERNAL. If you want to see in table information is it EXTERNAL table or not - you need to set ‘hql’ output_mode.
Added suppport for hql EXTERNAL statement, STORED AS statement, LOCATION statement
Added suppport for PARTITIONED BY statement (for both hql & sql)
Added support for HQL ROW FORMAT statement, FIELDS TERMINATED BY statement, COLLECTION ITEMS TERMINATED BY statement, MAP KEYS TERMINATED BY statement
v0.7.4
Fix behaviour with – in strings. Allow calid table name like ‘table–name’
v0.7.3
Added support /* ... */ block comments
Added support for Mysql ‘#’ comments
v0.7.1
Ignore inline with ‘–’ comments
v0.7.0
Redone logic of parse CREATE TABLE statements, now they parsed as one statement (not line by line as previous)
Fixed several minor bugs with edge cases in default values and checks
Added support for ALTER FOREIGN KEY statement for several fields in one statement
v0.6.1
Fix minor bug with schema in index statements
v0.6.0
Added support for SEQUENCE statemensts
Added support for ARRAYs in types
Added support for CREATE INDEX statements
v0.5.0
Added support for UNIQUE column attribute
Add command line arg to pass folder with ddls (parse multiple files)
Added support for CHECK Constratint
Added support for FOREIGN Constratint in ALTER TABLE
v0.4.0
Added support schema for table in REFERENCES statement in column defenition
Added base support fot Alter table statements (added ‘alters’ key in table)
Added command line arg to pass path to get the output results
Fixed incorrect null fields parsing
v0.3.0
Added support for REFERENCES statement in column defenition
Added command line
Project details
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