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sqlalchemy-filterset

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SQLAlchemy Filterset. An easy way to filter, sort, paginate SQLAlchemy queries

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<h1>
  <span style="font-size: 65px; color: #7e56c2; font-weight: 600">
    <strong>SQLAlchemy Filterset</strong>
  </span>
</h1>

<p align="left">
    <em>An easy way to filter, sort, paginate SQLAlchemy queries</em>
</p>

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---
**Documentation**: <a href="https://sqlalchemy-filterset.github.io/sqlalchemy-filterset/" target="_blank">https://sqlalchemy-filterset.github.io/sqlalchemy-filterset</a>

**Source Code**: <a href="https://github.com/sqlalchemy-filterset/sqlalchemy-filterset" target="_blank">https://github.com/sqlalchemy-filterset/sqlalchemy-filterset</a>

---
The library provides a convenient and organized way to filter your database records.
By creating a `FilterSet` class, you can declaratively define the filters you want to apply to your `SQLAlchemy` queries.
This library is particularly useful in web applications, as it allows users to easily search, filter, sort, and paginate data.

The key features are:

* [X] Declarative definition of filters.
* [X] Keeping all of your filters in one place, making it easier to maintain and change them as needed.
* [X] Constructing complex filtering conditions by combining multiple simple filters.
* [X] Offer of a standard approach to writing database queries.
* [X] Reduction of code duplication by reusing the same filters in multiple places in your code.
* [X] Sync and Async support of modern SQLAlchemy.

## Installation

```bash
pip install sqlalchemy-filterset
```
Requirements: `Python 3.7+` `SQLAlchemy 2.0+`

## Basic FilterSet and Filters Usage

In this example we specify criteria for filtering the database records
by simply setting the attributes of the `ProductFilterSet` class.
This is more convenient and easier to understand than writing raw SQL queries, which
can be more error-prone and difficult to maintain.

### Define a FilterSet

```python
from sqlalchemy_filterset import BaseFilterSet, Filter, RangeFilter, BooleanFilter

from myapp.models import Product

class ProductFilterSet(BaseFilterSet):
    id = Filter(Product.id)
    price = RangeFilter(Product.price)
    is_active = BooleanFilter(Product.is_active)
```
### Define a FilterSchema
```python
import uuid
from pydantic import BaseModel

class ProductFilterSchema(BaseModel):
    id: uuid.UUID | None
    price: tuple[float, float] | None
    is_active: bool | None
```

### Usage
```python
# Connect to the database
engine = create_engine("postgresql://user:password@host/database")
Base.metadata.create_all(bind=engine)
SessionLocal = sessionmaker(bind=engine)
session = SessionLocal()

# Define sqlalchemy query
query = select(Product)

# Define parameters for filtering
filter_params = ProductFilterSchema(price=(10, 100), is_active=True)

# Create the filterset object
filter_set = ProductFilterSet(query)

# Apply the filters to the query
query = filter_set.filter_query(filter_params.dict(exclude_unset=True))

# Execute the query
session.execute(query).unique().scalars().all()
```

This example will generate the following query:
```sql
select product.id, product.title, product.price, product.is_active
from product
where product.price >= 10
  and product.price <= 100
  and product.is_active = true;
```

## License

This project is licensed under the terms of the MIT license.

## Supported by
<a href="https://idaproject.com/" target="_blank" title="idaproject"><img width=150 src="https://sqlalchemy-filterset.github.io/sqlalchemy-filterset/img/idaproject.png"></a>

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