semvec/pypi-packages huggingface dataset:
habitat-lab 0.3.320250127
Habitat-Lab: a modular high-level library for end-to-end development in Embodied AI.
License: MIT License


[![codecov](https://codecov.io/gh/facebookresearch/habitat-lab/branch/main/graph/badge.svg)](https://codecov.io/gh/facebookresearch/habitat-lab)
[![GitHub license](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/facebookresearch/habitat-lab/blob/main/LICENSE)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/facebookresearch/habitat-lab)](https://github.com/facebookresearch/habitat-lab/releases/latest)
[![Supports Habitat_Sim](https://img.shields.io/static/v1?label=supports&message=Habitat%20Sim&color=informational&link=https://github.com/facebookresearch/habitat-sim)](https://github.com/facebookresearch/habitat-sim)
[![Python 3.7](https://img.shields.io/badge/python-3.7-blue.svg)](https://www.python.org/downloads/release/python-370/)
[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Imports: isort](https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336)](https://timothycrosley.github.io/isort/)
[![Twitter Follow](https://img.shields.io/twitter/follow/ai_habitat?style=social)](https://twitter.com/ai_habitat)

Habitat-Lab
==============================

Habitat-Lab is a modular high-level library for end-to-end development in embodied AI --
defining embodied AI tasks (e.g. navigation, rearrangement, instruction following, question answering),
configuring embodied agents (physical form, sensors, capabilities), training these agents (via imitation
or reinforcement learning, or no learning at all as in SensePlanAct pipelines), and benchmarking their
performance on the defined tasks using standard metrics.

Habitat-Lab uses [`Habitat-Sim`](https://github.com/facebookresearch/habitat-sim) as the core simulator.
For documentation refer [here](https://aihabitat.org/docs/habitat-lab/).

[![Habitat Demo](https://img.shields.io/static/v1?label=WebGL&message=Try%20AI%20Habitat%20In%20Your%20Browser%20&color=blue&logo=webgl&labelColor=%23990000&style=for-the-badge&link=https://aihabitat.org/demo)](https://aihabitat.org/demo)
FastAPI-Async-SQLA 0.2.4
SQLAlchemy extension for FastAPI with support for asynchronous SQLAlchemy sessions and pagination.
License: MIT License
Requires Python: >=3.12
Keywords: FastAPI, SQLAlchemy, AsyncIO

# PROJECT HAS BEEN RENAMED TO FastSQLA

Check [FastSQLA on Github](https://github.com/hadrien/FastSQLA) or [PyPI](https://pypi.org/project/FastSQLA/)

# FastAPI-Async-SQLA

[![PyPI - Version](https://img.shields.io/pypi/v/FastAPI-Async-SQLA?color=brightgreen)](https://pypi.org/project/FastAPI-Async-SQLA/)
[![Conventional Commits](https://img.shields.io/badge/Conventional%20Commits-1.0.0-brightgreen.svg)](https://conventionalcommits.org)
[![codecov](https://codecov.io/gh/hadrien/fastapi-async-sqla/graph/badge.svg?token=XK3YT60MWK)](https://codecov.io/gh/hadrien/fastapi-async-sqla)

FastAPI-Async-SQLA is an [SQLAlchemy] extension for [FastAPI]. It supports asynchronous
SQLAlchemy sessions using SQLAlchemy >= 2.0 and provides pagination support.

# Installing

Using [pip](https://pip.pypa.io/):
```
pip install fastapi-async-sqla
```

# Quick Example

Assuming it runs against a DB with a table `user` with 2 columns `id` and `name`:

```python
# main.py
from fastapi import FastAPI, HTTPException
from fastapi_async_sqla import Base, Item, Page, Paginate, Session, lifespan
from pydantic import BaseModel
from sqlalchemy import select


app = FastAPI(lifespan=lifespan)


class User(Base):
    __tablename__ = "user"


class UserIn(BaseModel):
    name: str


class UserModel(UserIn):
    id: int


@app.get("/users", response_model=Page[UserModel])
async def list_users(paginate: Paginate):
    return await paginate(select(User))


@app.get("/users/{user_id}", response_model=Item[UserModel])
async def get_user(user_id: int, session: Session):
    user = await session.get(User, user_id)
    if user is None:
        raise HTTPException(404)
    return {"data": user}


@app.post("/users", response_model=Item[UserModel])
async def create_user(new_user: UserIn, session: Session):
    user = User(**new_user.model_dump())
    session.add(user)
    await session.flush()
    return {"data": user}
```

Creating a db using `sqlite3`:
```bash
sqlite3 db.sqlite <<EOF
CREATE TABLE user (
    id    INTEGER PRIMARY KEY AUTOINCREMENT,
    name  TEXT NOT NULL
);
EOF
```

Installing [aiosqlite] to connect to the sqlite db asynchronously:
```bash
pip install aiosqlite
```

Running the app:
```bash
sqlalchemy_url=sqlite+aiosqlite:///db.sqlite?check_same_thread=false uvicorn main:app
```

[aiosqlite]: https://github.com/omnilib/aiosqlite
[FastAPI]: https://fastapi.tiangolo.com/
[SQLAlchemy]: http://sqlalchemy.org/