# ZenithDB
SQLite-powered document database with MongoDB-like syntax, full-text search, and advanced querying capabilities.
For complete examples of all features, PLEASE check out [usage.py](usage.py).
## Features
- **Document Storage & Validation**: Store and validate JSON-like documents with nested structures
- **Advanced Querying**: Full-text search, nested field queries, array operations
- **Multiple Query Styles**: Support for both MongoDB-style dict queries and fluent Query builder
- **Indexing**: Single and compound indexes for optimized performance
- **Aggregations**: Group and aggregate data with functions like COUNT, AVG, SUM
- **Bulk Operations**: Efficient batch processing with transaction support
- **Connection Pooling**: Built-in connection pool for concurrent operations
- **Migration Support**: Versioned database migrations with up/down functions
## Installation
```bash
pip install zenithdb
```
## Quick Start
```python
from zenithdb import Database
# Initialize database
db = Database("myapp.db")
users = db.collection("users")
# Add document validation
def age_validator(doc):
return isinstance(doc.get('age'), int) and doc['age'] >= 0
users.set_validator(age_validator)
# Insert documents
users.insert({
"name": "John Doe",
"age": 30,
"tags": ["premium"],
"profile": {"city": "New York"}
})
# Query documents
users.find({
"age": {"$gt": 25},
"tags": {"$contains": "premium"}
})
# Full-text search
users.find({"*": {"$contains": "John"}})
# Nested updates
users.update(
{"name": "John Doe"},
{"$set": {
"profile.city": "Brooklyn",
"tags.0": "vip"
}}
)
# Aggregations
users.aggregate([{
"group": {
"field": "profile.city",
"function": "COUNT",
"alias": "count"
}
}])
```
## Collection Management
```python
# List and count collections
db.list_collections()
db.count_collections()
# Drop collections
db.drop_collection("users")
db.drop_all_collections()
# Print collection contents
users.print_collection()
users.count()
```
## Advanced Features
### Indexing
```python
# Create indexes
db.create_index("users", ["email"])
db.create_index("users", ["profile.city", "age"])
# List indexes
db.list_indexes("users")
```
### Bulk Operations
```python
bulk_ops = users.bulk_operations()
with bulk_ops.transaction():
bulk_ops.bulk_insert("users", [
{"name": "User1", "age": 31},
{"name": "User2", "age": 32}
])
```
### Migrations
```python
from zenithdb.migrations import MigrationManager
manager = MigrationManager(db)
migration = {
'version': '001',
'name': 'add_users',
'up': lambda: db.collection('users').insert({'admin': True}),
'down': lambda: db.collection('users').delete({})
}
manager.apply_migration(migration)
```
## Development
```bash
# Install development dependencies
pip install -e ".[dev]"
# Run tests
pytest tests/
pytest tests/test_migrations.py
pytest --cov=zenithdb tests/
```
For complete examples of all features, check out [usage.py](usage.py).
I would not recommend using this as a production database, but it's a fun project to play around with.
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