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https://github.com/yassun7010/turu-py

Simple Database API for Typed Python
https://github.com/yassun7010/turu-py

async bigquery pep249 postgres postgresql postgresql-database python snowflake snowflakedb sqlite sqlite-database sqlite3 sqlite3-database typed-python

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Simple Database API for Typed Python

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# Turu: Simple Database Client for Typed Python

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logo

---

**Documentation**: https://yassun7010.github.io/turu-py/

**Source Code**: https://github.com/yassun7010/turu-py

---

## Installation

```bash
pip install "turu[snowflake]"
```

## Why Turu?
SQL is a powerful language, but it has many dialects, and Cloud Native Databases are especially difficult to test automatically in a local environment.

Turu was developed as a simple tool to assist local development.
It provides a simple interface according to [PEP 249 – Python Database API Specification v2.0](https://peps.python.org/pep-0249/) and allows for easy recording of query results and injection mock data.

## Features

- :rocket: **Simple** - Turu is a simple database api wrapper of [PEP 249](https://peps.python.org/pep-0249/).
- :bulb: **Type Hint** - Full support for type hints.
- :zap: **Async/Await** - Async/Await supports.
- :test_tube: **Recoed and Mock** - Record and mock database queries for testing.

## Supprted Database

| Database | Sync Support | Async Support | Installation |
| ---------- | ------------ | ------------- | ------------------------------- |
| SQLite3 | Yes | Yes | `pip install "turu[sqlite3]"` |
| MySQL | Yes | Yes | `pip install "turu[mysql]"` |
| PostgreSQL | Yes | Yes | `pip install "turu[postgres]"` |
| Snowflake | Yes | Yes | `pip install "turu[snowflake]"` |
| BigQuery | Yes | No | `pip install "turu[bigquery]"` |

## Usage

### Basic Usage

```python
from pydantic import BaseModel

class Row(BaseModel):
id: int
name: str

connection = turu.sqlite3.connect("test.db")

with connection.cursor() as cursor:
assert cursor.execute_map(Row, "select 1, 'a'").fetchone() == Row(id=1, name="a")
```

## Testing

```python
import turu.sqlite3

from pydantic import BaseModel

class Row(BaseModel):
id: int
name: str

expected1 = [Row(id=1, name="a"), Row(id=2, name="b")]
expected2 = [Row(id=3, name="c"), Row(id=4, name="d")]
expected3 = [Row(id=5, name="e"), Row(id=6, name="f")]

connection = turu.sqlite3.MockConnection()

(
connection.chain()
.inject_response(Row, expected1)
.inject_response(Row, expected2)
.inject_response(Row, expected3)
)

for expected in [expected1, expected2, expected3]:
with connection.cursor() as cursor:
assert cursor.execute_map(Row, "select 1, 'a'").fetchall() == expected
```

## Recording and Testing

Your Production Code

```python
import os

import turu.sqlite3
from turu.core.record import record_to_csv

from your_package.data import RECORD_DIR
from your_package.schema import Row

def do_something(connection: turu.sqlite3.Connection):
with record_to_csv(
RECORD_DIR / "test.csv",
connection.curosr(),
enable=os.environ.get("ENABLE_RECORDING"),
limit=100,
) as cursor:
... # Your logic
```

Your Test Code

```python
import turu.sqlite3

from your_package.data import RECORD_DIR
from your_package.schema import Row

def test_do_something(connection: turu.sqlite3.MockConnection):
connection.inject_response_from_csv(Row, RECORD_DIR / "test.csv")

assert do_something(connection) is None
```