https://github.com/phelps-sg/py-frm

Functional-relational mapping framework for Python
https://github.com/phelps-sg/py-frm

functional-relational-mapping python relational-databases

Last synced: 11 days ago
JSON representation

Functional-relational mapping framework for Python

• Host: GitHub
• URL: https://github.com/phelps-sg/py-frm
• Owner: phelps-sg
• License: mit
• Created: 2023-12-02T13:31:39.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-12-02T22:56:53.000Z (almost 2 years ago)
• Last Synced: 2025-06-10T11:12:56.742Z (6 months ago)
• Topics: functional-relational-mapping, python, relational-databases
• Language: Python
• Homepage:
• Size: 28.3 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-functional-python - py-frm - "Proof-of-concept Functional-Relational Mapping (FRM) for Python" (Awesome Functional Python / Libraries)

README

          
# py-frm

This repo illustrates a proof-of-concept type-safe functional-relational mapping framework for Python inspired by [Slick](https://scala-slick.org/doc/stable/introduction.html).  The idea is that we can work with relational databases as if we are working with Python collections and dataclasses.  Moreover we can use [mypy](https://www.mypy-lang.org/) to provide type-safety.  

If you would like to see this project turned into a fully capable production-ready SDK, please star this repository and consider contributing by submitting issues and PRs.

## Illustrative end-user code

Our database model is represented using Python dataclasses, e.g.:

~~~python

from dataclasses import dataclass, field

from py_frm import sqlalchemy_model

@sqlalchemy_model(table="students")

@dataclass

class Student:

    student_id: int = field(metadata={"primary_key": True})

    name: str

@sqlalchemy_model(table="courses")

@dataclass

class Course:

    course_id: int = field(metadata={"primary_key": True})

    title: str

    student_id: int = field(metadata={"foreign_key": ("students", "student_id")})

~~~

Database queries are written as type-annotated Python generators using generator comprehensions:

~~~python

from typing import Iterable, Generator, Tuple

def get_student_courses(

    students: Iterable[Student], courses: Iterable[Course]

) -> Generator[Tuple[str, str], None, None]:

    return (

        (s.name, c.title)

        for s in students

        for c in courses

        if s.student_id == c.student_id

    )

~~~

The above type-annotated function can be statically checked by [mypy](https://www.mypy-lang.org/), and is automatically mapped onto the corresponding SQL query:

~~~sql

SELECT students.name, courses.title 

FROM students, courses 

WHERE students.student_id = courses.student_id;

~~~

See [the example](./example.py) for the complete runnable code.