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https://github.com/Vanderhoof/PyDBML
DBML parser and builder for Python
https://github.com/Vanderhoof/PyDBML
dbml parser python python3 sql
Last synced: about 2 months ago
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DBML parser and builder for Python
- Host: GitHub
- URL: https://github.com/Vanderhoof/PyDBML
- Owner: Vanderhoof
- License: mit
- Created: 2020-04-15T05:36:52.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2024-04-23T16:13:38.000Z (3 months ago)
- Last Synced: 2024-04-24T18:21:40.026Z (3 months ago)
- Topics: dbml, parser, python, python3, sql
- Language: Python
- Homepage:
- Size: 279 KB
- Stars: 81
- Watchers: 3
- Forks: 12
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Lists
- jimsghstars - Vanderhoof/PyDBML - DBML parser and builder for Python (Python)
README
[](https://pypi.org/project/pydbml/) [](https://pypi.org/project/pydbml/) [](https://github.com/Vanderhoof/PyDBML) 
# DBML parser for Python
*Compliant with DBML **v3.2.0** syntax*
PyDBML is a Python parser and builder for [DBML](https://www.dbml.org) syntax.
> The project was rewritten in May 2022, the new version 1.0.0 is not compatible with versions 0.x.x. See details in [Upgrading to PyDBML 1.0.0](docs/upgrading.md).
**Docs:**
* [Class Reference](docs/classes.md)
* [Creating DBML schema](docs/creating_schema.md)
* [Upgrading to PyDBML 1.0.0](docs/upgrading.md)
> PyDBML requires Python v3.8 or higher
## Installation
You can install PyDBML using pip:
```bash
pip3 install pydbml
```
## Quick start
To parse a DBML file, import the `PyDBML` class and initialize it with Path object
```python
>>> from pydbml import PyDBML
>>> from pathlib import Path
>>> parsed = PyDBML(Path('test_schema.dbml'))
```
or with file stream
```python
>>> with open('test_schema.dbml') as f:
... parsed = PyDBML(f)
```
or with entire source string
```python
>>> with open('test_schema.dbml') as f:
... source = f.read()
>>> parsed = PyDBML(source)
>>> parsed
```
The parser returns a Database object that is a container for the parsed DBML entities.
You can access tables inside the `tables` attribute:
```python
>>> for table in parsed.tables:
... print(table.name)
...
orders
order_items
products
users
merchants
countries
```
Or just by getting items by index or full table name:
```python
>>> parsed[1]
>>> parsed['public.countries']
```
Other attributes are:
* **refs** — list of all references,
* **enums** — list of all enums,
* **table_groups** — list of all table groups,
* **project** — the Project object, if was defined.
Generate SQL for your DBML Database by accessing the `sql` property:
```python
>>> print(parsed.sql) # doctest:+ELLIPSIS
CREATE TYPE "orders_status" AS ENUM (
'created',
'running',
'done',
'failure',
);
CREATE TYPE "product status" AS ENUM (
'Out of Stock',
'In Stock',
);
CREATE TABLE "orders" (
"id" int PRIMARY KEY AUTOINCREMENT,
"user_id" int UNIQUE NOT NULL,
"status" "orders_status",
"created_at" varchar
);
...
```
Generate DBML for your Database by accessing the `dbml` property:
```python
>>> parsed.project.items['author'] = 'John Doe'
>>> print(parsed.dbml) # doctest:+ELLIPSIS
Project "test_schema" {
author: 'John Doe'
Note {
'This schema is used for PyDBML doctest'
}
}
Enum "orders_status" {
"created"
"running"
"done"
"failure"
}
Enum "product status" {
"Out of Stock"
"In Stock"
}
Table "orders" [headercolor: #fff] {
"id" int [pk, increment]
"user_id" int [unique, not null]
"status" "orders_status"
"created_at" varchar
}
Table "order_items" {
"order_id" int
"product_id" int
"quantity" int [default: 1]
}
...
```