# RocksQ
An inproc RocksDB-based queue with Python bindings. It is implemented in Rust.
Features:
- max capacity limit in number of elements;
- size calculation based on filesystem space usage;
- length calculation based on number of elements;
- supports only bytes-like objects;
- can operate in a multithreaded environment efficiently (push and pop methods can release GIL if necessary);
- keeps the state between restarts;
- two implementations: blocking and nonblocking;
What is not supported:
- pub/sub is not supported intentionally (implement it on top of RocksQ if necessary);
- TTL is not supported intentionally (implement it on top of RocksQ if necessary).
## Implementation details
It works on RocksDB and uses a single column family. The keys are 64-bit integers, the values are byte arrays. The keys are generated by incrementing a counter. The read and write counters are stored in a separate key-value pairs.
It is implemented in Rust and PyO3, thus allows to release GIL when necessary. The library does not require external dependencies installed in the environment.
## Supported Platforms and Python Versions
**Windows**: Python versions: 3.7-3.12.
**Linux**: ManyLinux Python versions: 3.7-3.12. CI does not build for PyPy, but it should work if you build it manually.
**MacOS**: Currently, I do not have MacOS environment to debug the build process in MacOS, all volounteers are welcome.
## Installation
```
pip install rocksq
```
## Usage
See the examples in the [python](https://github.com/insight-platform/RocksQ/tree/main/python) directory.
API docs are located at: [https://insight-platform.github.io/RocksQ/](https://insight-platform.github.io/RocksQ/).
## Performance
The performance is mostly limited by the throughput of the underlying filesystem. The queue is able to saturate the throughput of the filesystem.
Raw data
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"description": "# RocksQ\n\nAn inproc RocksDB-based queue with Python bindings. It is implemented in Rust.\n\nFeatures:\n\n- max capacity limit in number of elements;\n- size calculation based on filesystem space usage;\n- length calculation based on number of elements;\n- supports only bytes-like objects;\n- can operate in a multithreaded environment efficiently (push and pop methods can release GIL if necessary);\n- keeps the state between restarts;\n- two implementations: blocking and nonblocking;\n\nWhat is not supported:\n\n- pub/sub is not supported intentionally (implement it on top of RocksQ if necessary);\n- TTL is not supported intentionally (implement it on top of RocksQ if necessary).\n\n## Implementation details\n\nIt works on RocksDB and uses a single column family. The keys are 64-bit integers, the values are byte arrays. The keys are generated by incrementing a counter. The read and write counters are stored in a separate key-value pairs.\n\nIt is implemented in Rust and PyO3, thus allows to release GIL when necessary. The library does not require external dependencies installed in the environment.\n\n## Supported Platforms and Python Versions\n\n**Windows**: Python versions: 3.7-3.12.\n\n**Linux**: ManyLinux Python versions: 3.7-3.12. CI does not build for PyPy, but it should work if you build it manually.\n\n**MacOS**: Currently, I do not have MacOS environment to debug the build process in MacOS, all volounteers are welcome.\n\n## Installation\n\n```\npip install rocksq\n```\n\n## Usage\n\nSee the examples in the [python](https://github.com/insight-platform/RocksQ/tree/main/python) directory. \n\nAPI docs are located at: [https://insight-platform.github.io/RocksQ/](https://insight-platform.github.io/RocksQ/).\n\n## Performance\n\nThe performance is mostly limited by the throughput of the underlying filesystem. The queue is able to saturate the throughput of the filesystem.\n\n\n",
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