strapalchemy 0.1.0

Enhanced SQLAlchemy query builder with advanced filtering, sorting, pagination, and search capabilities.

StrapAlchemy

Enhanced SQLAlchemy query builder with advanced filtering, sorting, pagination, and search capabilities.

StrapAlchemy is a powerful query builder library for SQLAlchemy that provides Strapi-style query syntax for building complex database queries with ease.

Features

• Advanced Filtering: Strapi-style operators ($eq, $in, $contains, $between, etc.)
• Nested Relationship Filtering: Filter through related models with dot notation
• Flexible Sorting: Sort by direct fields or relationship fields
• Pagination: Support for both page-based and offset-based pagination
• Full-Text Search: BM25 search with ParadeDB integration and ILIKE fallback
• Field Selection: Select specific fields to optimize query performance
• Relationship Population: Eager load relationships to prevent N+1 queries
• Query Optimization: Built-in caching and optimization for better performance
• Model Serialization: Convert SQLAlchemy models to dictionaries easily

Installation

pip install strapalchemy

Quick Start

from sqlalchemy import select
from strapalchemy import FilterBuilder, SortBuilder, Paginator, SearchEngine
from strapalchemy.models import Base
from sqlalchemy import Column, Integer, String

# Define your model
class User(Base):
    __tablename__ = "users"
    id = Column(Integer, primary_key=True)
    name = Column(String)
    email = Column(String)
    status = Column(String)

# Build your query
query = select(User)

# Apply filters
filter_builder = FilterBuilder(User)
query = await filter_builder.apply_filters(query, {
    "name": {"$contains": "John"},
    "status": {"$eq": "active"}
})

# Apply sorting
sort_builder = SortBuilder(User)
query = await sort_builder.apply_sorting(query, ["name:asc", "created_at:desc"])

# Apply search
search_engine = SearchEngine()
query = await search_engine.apply_search(query, User, "search term")

# Apply pagination
paginator = Paginator(session, User)
query, meta = await paginator.apply_pagination(query, {"page": 1, "page_size": 20})

# Execute
result = await session.execute(query)
users = result.scalars().all()

Filtering

StrapAlchemy supports Strapi-style filtering operators:

Operator	Description	Example
$eq	Equal	{"status": {"$eq": "active"}}
$ne	Not equal	{"status": {"$ne": "deleted"}}
$lt	Less than	{"age": {"$lt": 18}}
$lte	Less than or equal	{"age": {"$lte": 18}}
$gt	Greater than	{"age": {"$gt": 18}}
$gte	Greater than or equal	{"age": {"$gte": 18}}
$in	In list	{"status": {"$in": ["active", "pending"]}}
$notIn	Not in list	{"status": {"$notIn": ["deleted"]}}
$contains	Contains	{"name": {"$contains": "John"}}
$containsi	Contains (case insensitive)	{"name": {"$containsi": "john"}}
$startsWith	Starts with	{"email": {"$startsWith": "admin"}}
$endsWith	Ends with	{"email": {"$endsWith": "@example.com"}}
$null	Is null	{"deleted_at": {"$null": true}}
$notNull	Is not null	{"email": {"$notNull": true}}
$between	Between	{"created_at": {"$between": ["2024-01-01", "2024-12-31"]}}
$or	Logical OR	{"$or": [{"status": {"$eq": "active"}}, {"status": {"$eq": "pending"}}]}
$and	Logical AND	{"$and": [{"status": {"$eq": "active"}}, {"verified": {"$eq": true}}]}

Nested Relationship Filtering

# Filter by relationship fields
query = await filter_builder.apply_filters(query, {
    "organization": {"slug": {"$eq": "acme"}}
})

# Or use dot notation
query = await filter_builder.apply_filters(query, {
    "organization.slug": {"$eq": "acme"}
})

Sorting

# Sort by single field
query = await sort_builder.apply_sorting(query, "name:asc")

# Sort by multiple fields
query = await sort_builder.apply_sorting(query, ["name:asc", "created_at:desc"])

# Sort by relationship field
query = await sort_builder.apply_sorting(query, ["organization.name:asc"])

Pagination

Page-based Pagination

query, meta = await paginator.apply_pagination(query, {
    "page": 1,
    "page_size": 20
})

# meta contains:
# {
#     "page": 1,
#     "page_size": 20,
#     "page_count": 5,
#     "total": 100,
#     "has_next": True,
#     "has_previous": False
# }

Offset-based Pagination

query, meta = await paginator.apply_pagination(query, {
    "start": 0,
    "limit": 20
})

Field Selection

from strapalchemy import FieldSelector

field_selector = FieldSelector(User)
query = await field_selector.apply_field_selection(query, ["id", "name", "email"])

# Select relationship fields
query = await field_selector.apply_field_selection(query, ["id", "name", "organization.slug"])

Model Serialization

from strapalchemy import ModelSerializer

# Serialize a single model
data = ModelSerializer.serialize(user, fields=["id", "name", "email"])

# Serialize a list
data = ModelSerializer.serialize(users, fields=["id", "name"])

# Serialize with relationships
data = ModelSerializer.serialize(user, populate="organization")

# Serialize with nested relationships
data = ModelSerializer.serialize(user, populate=["organization", "user.role"])

Search

from strapalchemy import SearchEngine

search_engine = SearchEngine()

# Add searchable fields to your model
class User(Base):
    __tablename__ = "users"
    __searchable__ = {
        "text_fields": ["name", "email", "bio"]
    }
    id = Column(Integer, primary_key=True)
    name = Column(String)
    email = Column(String)
    bio = Column(String)

# Apply search
query = await search_engine.apply_search(query, User, "John Doe")

Advanced Usage

Combining Multiple Builders

async def get_users(filters=None, sort=None, search=None, page=None):
    query = select(User)

    if filters:
        query = await filter_builder.apply_filters(query, filters)

    if sort:
        query = await sort_builder.apply_sorting(query, sort)

    if search:
        query = await search_engine.apply_search(query, User, search)

    if page:
        query, meta = await paginator.apply_pagination(query, page)

    result = await session.execute(query)
    return result.scalars().all(), meta

Requirements

• Python >= 3.12
• SQLAlchemy >= 2.0.45
• python-dateutil >= 2.9.0
• rich >= 13.0.0

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues and questions, please use the GitHub issue tracker.