https://github.com/jnsougata/driz
A fast lightweight k-v storage for hobbyists.
https://github.com/jnsougata/driz
kvstore nosql python3 sqlite3
Last synced: about 1 year ago
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A fast lightweight k-v storage for hobbyists.
- Host: GitHub
- URL: https://github.com/jnsougata/driz
- Owner: jnsougata
- License: mit
- Created: 2025-04-01T07:24:28.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-04-02T21:50:55.000Z (about 1 year ago)
- Last Synced: 2025-04-02T22:24:16.600Z (about 1 year ago)
- Topics: kvstore, nosql, python3, sqlite3
- Language: Python
- Homepage:
- Size: 26.4 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Driz - KV Store
A fast, lightweight key-value store designed for hobbyists, combining the simplicity of NoSQL with SQLite3's robust filtering and sorting capabilities.
## Features
- **NoSQL-like Experience** – Work with database records as Python dictionaries.
- **Simplified Access** – Retrieve data without remembering column names or indices.
- **SQL Power** – Use SQL queries for filtering and sorting.
- **Lightweight & Fast** – Minimal overhead with SQLite’s reliability.
## Installation
```sh
pip install git+https://github.com/jnsougata/driz.git
```
## Example Usage
```python
import driz
def main():
db = driz.DB("example.db")
users = db.collection(
"users",
schema=driz.Schema(
driz.Field("name", str, nullable=False),
driz.Field("age", int, nullable=False),
driz.Field("email", str),
driz.Field("active", bool, default=True),
)
)
posts = db.collection(
"posts",
schema=driz.Schema(
driz.Field("user_id", str, ref_collection="users", ref_field="key"),
driz.Field("content", str, nullable=False))
)
user_id = users.insert(
name="Sougata Jana",
age=25,
email="abc@xyz.com",
active=True,
)
print(f"Inserted user with ID: {user_id}")
posts.insert(
user_id=user_id,
content="This is a test post.",
)
if __name__ == "__main__":
main()
```
## Documentation
Half-baked docs [here.](https://driz.readthedocs.io/en/latest/)
## TODO
- Add more SQL features (e.g., `JOIN`, `GROUP BY`).
- Add more complex `queries` and `filtering` options.
- Implement `view` handling.
- Better error handling.
- Composite column support (no flattening).
- Hierarchical column search.
- More examples and documentation.
- Unit tests.
- Performance benchmarks.