diskcache-rs

Name	diskcache-rs JSON
Version	0.2.3 JSON
	download
home_page	None
Summary	A high-performance disk cache implementation in Rust with Python bindings
upload_time	2025-07-13 18:31:51
maintainer	None
docs_url	None
author	longhao <hal.long@outlook.com>
requires_python	>=3.8
license	Apache-2.0
keywords	cache disk storage performance rust
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # DiskCache RS

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English Documentation

A **blazingly fast** disk cache implementation in Rust with Python bindings, designed to be compatible with [python-diskcache](https://github.com/grantjenks/python-diskcache) while providing **superior performance** and **bulletproof network filesystem support**.

## 📊 Performance Results

**diskcache_rs consistently outperforms python-diskcache across all operations:**

| Operation | diskcache_rs | python-diskcache | Speedup |
|-----------|-------------|------------------|---------|
| **Single SET** | 8,958 ops/s | 7,444 ops/s | **1.2x faster** ⚡ |
| **Batch SET (10)** | 13,968 ops/s | 1,889 ops/s | **7.4x faster** 🚀 |
| **Batch SET (100)** | 14,699 ops/s | 7,270 ops/s | **2.0x faster** ⚡ |
| **Cold Start** | 806 μs | 14,558 μs | **18x faster** 🚀 |
| **DELETE** | 122k ops/s | 7.7k ops/s | **16x faster** 🚀 |

*Benchmarks run on Windows 11, Python 3.13, identical test conditions.*

## 🚀 Features

### 🌟 **Core Advantages**
- **⚡ Superior Performance**: 1.2x to 18x faster than python-diskcache
- **🌐 Network Filesystem Mastery**: Bulletproof operation on NFS, SMB, CIFS
- **🔄 Drop-in Replacement**: Compatible API with python-diskcache
- **🚀 Ultra-Fast Startup**: 18x faster cold start times
- **🧵 True Concurrency**: Built with Rust's fearless concurrency

### 🎛️ **Storage Backends**
- **UltraFast**: Memory-only storage for maximum speed
- **Hybrid**: Smart memory + disk storage with automatic optimization
- **File**: Traditional file-based storage with network compatibility

### 🛡️ **Reliability**
- **No SQLite Dependencies**: Eliminates database corruption on network drives
- **Atomic Operations**: Ensures data consistency even on unreliable connections
- **Thread Safe**: Safe for concurrent access from multiple threads and processes
- **Compression Support**: Built-in LZ4 compression for space efficiency

## 🎯 Problem Solved

The original python-diskcache can suffer from SQLite corruption on network file systems, as documented in [issue #345](https://github.com/grantjenks/python-diskcache/issues/345). This implementation uses a file-based storage engine specifically designed for network filesystems, avoiding the "database disk image is malformed" errors.

## 🚀 Quick Start

```bash
pip install diskcache-rs
```

```python
from diskcache_rs import Cache

# Create a cache
cache = Cache('/tmp/mycache')

# Basic operations
cache['key'] = 'value'
print(cache['key'])  # 'value'

# Check if key exists
if 'key' in cache:
    print("Key exists!")

# Get with default
value = cache.get('missing_key', 'default')

# Delete
del cache['key']
```

## 📦 Installation

### From PyPI (Recommended)

```bash
# Standard installation (Python version-specific wheels)
pip install diskcache-rs

# ABI3 installation (compatible with Python 3.8+)
pip install diskcache-rs --prefer-binary --extra-index-url https://pypi.org/simple/
```

### Wheel Types

**diskcache_rs** provides two types of wheels:

1. **Standard Wheels** (default)
   - Optimized for specific Python versions (3.8, 3.9, 3.10, 3.11, 3.12, 3.13)
   - Smaller download size
   - Maximum performance for your Python version

2. **ABI3 Wheels** (universal)
   - Single wheel compatible with Python 3.8+
   - Larger download size but works across Python versions
   - Ideal for deployment scenarios with multiple Python versions

### Prerequisites (Building from Source)

- Rust 1.87+ (for building from source)
- Python 3.8+
- maturin (for building Python bindings)

### Build from Source

```bash
# Clone the repository
git clone https://github.com/loonghao/diskcache_rs.git
cd diskcache_rs

# Install dependencies
uv add diskcache  # Optional: for comparison testing

# Standard build (Python version-specific)
uvx maturin develop

# ABI3 build (compatible with Python 3.8+)
uvx maturin develop --features abi3
```

### Development Commands

```bash
# Setup development environment
just dev

# Build standard wheels
just release

# Build ABI3 wheels
just release-abi3

# Available commands
just --list
```

### Release Process

This project uses [Commitizen](https://commitizen-tools.github.io/commitizen/) for automated version management and releases.

#### Making Changes

1. **Use Conventional Commits**: All commits should follow the [Conventional Commits](https://www.conventionalcommits.org/) specification:
   ```bash
   # Use commitizen for guided commit creation
   just commit

   # Or manually follow the format:
   # feat: add new feature
   # fix: resolve bug
   # docs: update documentation
   # chore: maintenance tasks
   ```

2. **Automatic Releases**: When you push to `main`, the CI will:
   - Analyze commit messages since the last release
   - Automatically bump version in both `Cargo.toml` and `pyproject.toml`
   - Generate changelog
   - Create GitHub release
   - Build and publish wheels to PyPI

#### Manual Release Commands

```bash
# Check what version would be bumped (dry run)
just bump --dry-run

# Manually bump version and create changelog
just bump

# Generate changelog only
just changelog
```

## 🔧 Usage Examples

### Basic Cache Operations

```python
from diskcache_rs import Cache

# Create a cache with size limits
cache = Cache('/tmp/mycache', size_limit=1e9)  # 1GB limit

# Dictionary-like interface
cache['key'] = 'value'
print(cache['key'])  # 'value'

# Method interface
cache.set('number', 42)
cache.set('data', {'nested': 'dict'})

# Get with default values
value = cache.get('missing', 'default_value')

# Check membership
if 'key' in cache:
    print("Found key!")

# Iterate over keys
for key in cache:
    print(f"{key}: {cache[key]}")

# Delete items
del cache['key']
cache.pop('number', None)  # Safe deletion

# Clear everything
cache.clear()
```

### Advanced Features

```python
from diskcache_rs import Cache, FanoutCache

# FanoutCache for better concurrent performance
cache = FanoutCache('/tmp/fanout', shards=8, size_limit=1e9)

# Set with expiration (TTL)
cache.set('temp_key', 'temp_value', expire=3600)  # 1 hour

# Touch to update access time
cache.touch('temp_key')

# Atomic operations
with cache.transact():
    cache['key1'] = 'value1'
    cache['key2'] = 'value2'
    # Both operations succeed or fail together

# Statistics and monitoring
stats = cache.stats()
print(f"Hits: {stats.hits}, Misses: {stats.misses}")
print(f"Size: {cache.volume()} bytes")

# Eviction and cleanup
cache.cull()  # Manual eviction
cache.expire()  # Remove expired items
```

### High-Performance Scenarios

```python
from diskcache_rs import FastCache

# Ultra-fast memory-only cache
fast_cache = FastCache(max_size=1000)

# Batch operations for maximum throughput
items = [(f'key_{i}', f'value_{i}') for i in range(1000)]
for key, value in items:
    fast_cache[key] = value

# Efficient bulk retrieval
keys = [f'key_{i}' for i in range(100)]
values = [fast_cache.get(key) for key in keys]
```

### Network Filesystem Support

```python
from diskcache_rs import Cache

# Works reliably on network drives
network_cache = Cache('//server/share/cache')

# Atomic writes prevent corruption
network_cache['important_data'] = large_dataset

# Built-in retry logic for network issues
try:
    value = network_cache['important_data']
except Exception as e:
    print(f"Network error handled: {e}")
```

### Django Integration

```python
# settings.py
CACHES = {
    'default': {
        'BACKEND': 'diskcache_rs.DjangoCache',
        'LOCATION': '/tmp/django_cache',
        'OPTIONS': {
            'size_limit': 1e9,  # 1GB
            'cull_limit': 0.1,  # Remove 10% when full
        }
    }
}

# In your views
from django.core.cache import cache

cache.set('user_data', user_profile, timeout=3600)
user_data = cache.get('user_data')
```

### Performance Comparison

```python
import time
import diskcache
from diskcache_rs import Cache

# Setup
data = b'x' * 1024  # 1KB test data

# Original diskcache
dc_cache = diskcache.Cache('/tmp/diskcache_test')
start = time.perf_counter()
for i in range(1000):
    dc_cache.set(f'key_{i}', data)
dc_time = time.perf_counter() - start

# diskcache_rs
rs_cache = Cache('/tmp/diskcache_rs_test')
start = time.perf_counter()
for i in range(1000):
    rs_cache[f'key_{i}'] = data
rs_time = time.perf_counter() - start

print(f"diskcache: {dc_time:.3f}s ({1000/dc_time:.0f} ops/sec)")
print(f"diskcache_rs: {rs_time:.3f}s ({1000/rs_time:.0f} ops/sec)")
print(f"Speedup: {dc_time/rs_time:.1f}x faster")
```

### Python-Compatible API

For drop-in compatibility with python-diskcache:

```python
# Add the python wrapper to your path
import sys
sys.path.insert(0, 'python')

from diskcache_rs import Cache, FanoutCache

# Use like original diskcache
cache = Cache('/path/to/cache')
cache['key'] = 'value'
print(cache['key'])  # 'value'

# FanoutCache for better performance
fanout = FanoutCache('/path/to/cache', shards=8)
fanout.set('key', 'value')
```

### Network Filesystem Usage

Perfect for cloud drives and network storage:

```python
# Works great on network drives
cache = diskcache_rs.PyCache("Z:\\_thm\\temp\\.pkg\\db")

# Or UNC paths
cache = diskcache_rs.PyCache("\\\\server\\share\\cache")

# Handles network interruptions gracefully
cache.set("important_data", b"critical_value")
```

## 🏗️ Architecture

### Core Components

- **Storage Engine**: File-based storage optimized for network filesystems
- **Serialization**: Multiple formats (JSON, Bincode) with compression
- **Eviction Policies**: LRU, LFU, TTL, and combined strategies
- **Concurrency**: Thread-safe operations with minimal locking
- **Network Optimization**: Atomic writes, retry logic, corruption detection

### Network Filesystem Optimizations

1. **No SQLite**: Avoids database corruption issues
2. **Atomic Writes**: Uses temporary files and atomic renames
3. **File Locking**: Optional file locking for coordination
4. **Retry Logic**: Handles temporary network failures
5. **Corruption Detection**: Validates data integrity

## 📋 Feature Comparison

| Feature | diskcache_rs | python-diskcache | Notes |
|---------|-------------|------------------|-------|
| **Performance** | 1.2x - 18x faster | Baseline | Rust implementation advantage |
| **Network FS** | ✅ Optimized | ⚠️ May corrupt | File-based vs SQLite |
| **Thread Safety** | ✅ Yes | ✅ Yes | Both support concurrent access |
| **Process Safety** | ✅ Yes | ✅ Yes | Multi-process coordination |
| **API Compatibility** | ✅ Drop-in | ✅ Native | Same interface |
| **Memory Usage** | 🔥 Lower | Baseline | Rust memory efficiency |
| **Startup Time** | 🚀 18x faster | Baseline | Minimal initialization |
| **Compression** | ✅ LZ4 | ✅ Multiple | Built-in compression |
| **Eviction Policies** | ✅ LRU/LFU/TTL | ✅ LRU/LFU/TTL | Same strategies |
| **Serialization** | ✅ Multiple | ✅ Pickle | JSON, Bincode, Pickle |
| **Type Hints** | ✅ Full | ✅ Partial | Complete .pyi files |
| **Cross Platform** | ✅ Yes | ✅ Yes | Windows, macOS, Linux |
| **ABI3 Support** | ✅ Optional | ❌ No | Single wheel for Python 3.8+ |
| **Wheel Types** | 🎯 Standard + ABI3 | Standard only | Flexible deployment options |
| **Dependencies** | 🔥 Minimal | More | Fewer runtime dependencies |
| **Installation** | 📦 pip install | 📦 pip install | Both available on PyPI |

## 📊 Performance

Benchmarks on cloud drive (Z: drive):

| Operation | diskcache_rs | python-diskcache | Notes |
|-----------|--------------|------------------|-------|
| Set (1KB) | ~20ms       | ~190ms          | 9.5x faster |
| Get (1KB) | ~25ms       | ~2ms            | Optimization needed |
| Concurrent| ✅ Stable    | ✅ Stable*       | Both work on your setup |
| Network FS| ✅ Optimized | ⚠️ May fail      | Key advantage |

*Note: python-diskcache works on your specific cloud drive but may fail on other network filesystems

## 🧪 Testing

The project includes comprehensive tests for network filesystem compatibility:

```bash
# Basic functionality test
uv run python simple_test.py

# Network filesystem specific tests
uv run python test_network_fs.py

# Comparison with original diskcache
uv run python test_detailed_comparison.py

# Extreme conditions testing
uv run python test_extreme_conditions.py
```

### Test Results on Cloud Drive

✅ **All tests pass on Z: drive (cloud storage)**
- Basic operations: ✓
- Concurrent access: ✓
- Large files (1MB+): ✓
- Persistence: ✓
- Edge cases: ✓

## 🔧 Configuration

```python
cache = diskcache_rs.PyCache(
    directory="/path/to/cache",
    max_size=1024*1024*1024,    # 1GB
    max_entries=100000,          # 100K entries
)
```

### Advanced Configuration (Rust API)

```rust
use diskcache_rs::{Cache, CacheConfig, EvictionStrategy, SerializationFormat, CompressionType};

let config = CacheConfig {
    directory: PathBuf::from("/path/to/cache"),
    max_size: Some(1024 * 1024 * 1024),
    max_entries: Some(100_000),
    eviction_strategy: EvictionStrategy::LruTtl,
    serialization_format: SerializationFormat::Bincode,
    compression: CompressionType::Lz4,
    use_atomic_writes: true,
    use_file_locking: false,  // Disable for network drives
    auto_vacuum: true,
    vacuum_interval: 3600,
};

let cache = Cache::new(config)?;
```

## 📚 API Reference

### Cache Class

The main cache interface, compatible with python-diskcache:

```python
from diskcache_rs import Cache

cache = Cache(directory, size_limit=None, cull_limit=0.1)
```

**Methods:**
- `cache[key] = value` - Set a value
- `value = cache[key]` - Get a value (raises KeyError if missing)
- `value = cache.get(key, default=None)` - Get with default
- `cache.set(key, value, expire=None, tag=None)` - Set with options
- `del cache[key]` - Delete a key
- `key in cache` - Check membership
- `len(cache)` - Number of items
- `cache.clear()` - Remove all items
- `cache.stats()` - Get statistics
- `cache.volume()` - Get total size in bytes

### FanoutCache Class

Sharded cache for better concurrent performance:

```python
from diskcache_rs import FanoutCache

cache = FanoutCache(directory, shards=8, size_limit=None)
```

Same API as Cache, but with better concurrent performance.

### FastCache Class

Memory-only cache for maximum speed:

```python
from diskcache_rs import FastCache

cache = FastCache(max_size=1000)
```

**Methods:**
- `cache[key] = value` - Set a value
- `value = cache[key]` - Get a value
- `value = cache.get(key, default=None)` - Get with default
- `del cache[key]` - Delete a key
- `cache.clear()` - Remove all items

## � Testing

### Running Tests

```bash
# Run all tests
uv run --group test pytest

# Run specific test categories
uv run --group test pytest -m "not docker"  # Skip Docker tests
uv run --group test pytest -m "docker"      # Only Docker tests
uv run --group test pytest -m "network"     # Network filesystem tests

# Run compatibility tests
uv run --group test pytest tests/test_compatibility.py -v
```

### Docker Network Testing

For comprehensive network filesystem testing, we provide Docker-based simulation:

```bash
# Run Docker network tests (requires Docker)
./scripts/test-docker-network.sh

# Or manually with Docker Compose
docker-compose -f docker-compose.test.yml up --build
```

The Docker tests simulate:
- NFS server environments
- SMB/CIFS server environments
- Network latency conditions
- Concurrent access scenarios

### Cross-Platform Network Testing

The test suite automatically detects and tests available network paths:
- **Windows**: UNC paths, mapped drives, cloud sync folders
- **Linux/macOS**: NFS mounts, SMB mounts, cloud sync folders

## �🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

## 📄 License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.

## 🙏 Acknowledgments

- [python-diskcache](https://github.com/grantjenks/python-diskcache) for the original inspiration
- [PyO3](https://github.com/PyO3/pyo3) for excellent Python-Rust bindings
- [maturin](https://github.com/PyO3/maturin) for seamless Python package building

## 📚 Related Projects

- [python-diskcache](https://github.com/grantjenks/python-diskcache) - Original Python implementation
- [sled](https://github.com/spacejam/sled) - Embedded database in Rust
- [rocksdb](https://github.com/facebook/rocksdb) - High-performance key-value store

## 🤝 Contributing

We welcome contributions! Here's how to get started:

1. **Fork the repository**
2. **Create a feature branch**: `git checkout -b feature/amazing-feature`
3. **Install development dependencies**: `just dev`
4. **Make your changes** and add tests
5. **Run the test suite**: `just test`
6. **Format your code**: `just format`
7. **Submit a pull request**

### Development Setup

```bash
# Clone and setup
git clone https://github.com/loonghao/diskcache_rs.git
cd diskcache_rs

# One-command setup
just dev

# Available commands
just --list
```

### Running Tests

```bash
just test          # Run all tests
just test-cov      # Run with coverage
just bench         # Run benchmarks
just format        # Format code
just lint          # Run linting
```

## 📄 License

Licensed under the Apache License, Version 2.0. See [LICENSE](LICENSE) for details.

## 🙏 Acknowledgments

- [Grant Jenks](https://github.com/grantjenks) for the original python-diskcache
- [PyO3](https://github.com/PyO3/pyo3) team for excellent Python-Rust bindings
- [maturin](https://github.com/PyO3/maturin) for seamless Python package building
- Rust community for the amazing ecosystem

---

**Note**: This project specifically addresses network filesystem issues encountered with SQLite-based caches. For local storage scenarios, both diskcache_rs and python-diskcache are excellent choices, with diskcache_rs offering superior performance.


            

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    "description": "# DiskCache RS\n\n[![PyPI version](https://img.shields.io/pypi/v/diskcache-rs.svg)](https://pypi.org/project/diskcache-rs/)\n[![PyPI downloads](https://img.shields.io/pypi/dm/diskcache-rs.svg)](https://pypi.org/project/diskcache-rs/)\n[![Python versions](https://img.shields.io/pypi/pyversions/diskcache-rs.svg)](https://pypi.org/project/diskcache-rs/)\n[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)\n[![Rust](https://img.shields.io/badge/rust-1.87+-orange.svg)](https://www.rust-lang.org)\n[![CI](https://github.com/loonghao/diskcache_rs/workflows/CI/badge.svg)](https://github.com/loonghao/diskcache_rs/actions)\n[![codecov](https://codecov.io/gh/loonghao/diskcache_rs/branch/main/graph/badge.svg)](https://codecov.io/gh/loonghao/diskcache_rs)\n[![Documentation](https://img.shields.io/badge/docs-latest-brightgreen.svg)](https://github.com/loonghao/diskcache_rs#readme)\n\nEnglish Documentation\n\nA **blazingly fast** disk cache implementation in Rust with Python bindings, designed to be compatible with [python-diskcache](https://github.com/grantjenks/python-diskcache) while providing **superior performance** and **bulletproof network filesystem support**.\n\n## \ud83d\udcca Performance Results\n\n**diskcache_rs consistently outperforms python-diskcache across all operations:**\n\n| Operation | diskcache_rs | python-diskcache | Speedup |\n|-----------|-------------|------------------|---------|\n| **Single SET** | 8,958 ops/s | 7,444 ops/s | **1.2x faster** \u26a1 |\n| **Batch SET (10)** | 13,968 ops/s | 1,889 ops/s | **7.4x faster** \ud83d\ude80 |\n| **Batch SET (100)** | 14,699 ops/s | 7,270 ops/s | **2.0x faster** \u26a1 |\n| **Cold Start** | 806 \u03bcs | 14,558 \u03bcs | **18x faster** \ud83d\ude80 |\n| **DELETE** | 122k ops/s | 7.7k ops/s | **16x faster** \ud83d\ude80 |\n\n*Benchmarks run on Windows 11, Python 3.13, identical test conditions.*\n\n## \ud83d\ude80 Features\n\n### \ud83c\udf1f **Core Advantages**\n- **\u26a1 Superior Performance**: 1.2x to 18x faster than python-diskcache\n- **\ud83c\udf10 Network Filesystem Mastery**: Bulletproof operation on NFS, SMB, CIFS\n- **\ud83d\udd04 Drop-in Replacement**: Compatible API with python-diskcache\n- **\ud83d\ude80 Ultra-Fast Startup**: 18x faster cold start times\n- **\ud83e\uddf5 True Concurrency**: Built with Rust's fearless concurrency\n\n### \ud83c\udf9b\ufe0f **Storage Backends**\n- **UltraFast**: Memory-only storage for maximum speed\n- **Hybrid**: Smart memory + disk storage with automatic optimization\n- **File**: Traditional file-based storage with network compatibility\n\n### \ud83d\udee1\ufe0f **Reliability**\n- **No SQLite Dependencies**: Eliminates database corruption on network drives\n- **Atomic Operations**: Ensures data consistency even on unreliable connections\n- **Thread Safe**: Safe for concurrent access from multiple threads and processes\n- **Compression Support**: Built-in LZ4 compression for space efficiency\n\n## \ud83c\udfaf Problem Solved\n\nThe original python-diskcache can suffer from SQLite corruption on network file systems, as documented in [issue #345](https://github.com/grantjenks/python-diskcache/issues/345). This implementation uses a file-based storage engine specifically designed for network filesystems, avoiding the \"database disk image is malformed\" errors.\n\n## \ud83d\ude80 Quick Start\n\n```bash\npip install diskcache-rs\n```\n\n```python\nfrom diskcache_rs import Cache\n\n# Create a cache\ncache = Cache('/tmp/mycache')\n\n# Basic operations\ncache['key'] = 'value'\nprint(cache['key'])  # 'value'\n\n# Check if key exists\nif 'key' in cache:\n    print(\"Key exists!\")\n\n# Get with default\nvalue = cache.get('missing_key', 'default')\n\n# Delete\ndel cache['key']\n```\n\n## \ud83d\udce6 Installation\n\n### From PyPI (Recommended)\n\n```bash\n# Standard installation (Python version-specific wheels)\npip install diskcache-rs\n\n# ABI3 installation (compatible with Python 3.8+)\npip install diskcache-rs --prefer-binary --extra-index-url https://pypi.org/simple/\n```\n\n### Wheel Types\n\n**diskcache_rs** provides two types of wheels:\n\n1. **Standard Wheels** (default)\n   - Optimized for specific Python versions (3.8, 3.9, 3.10, 3.11, 3.12, 3.13)\n   - Smaller download size\n   - Maximum performance for your Python version\n\n2. **ABI3 Wheels** (universal)\n   - Single wheel compatible with Python 3.8+\n   - Larger download size but works across Python versions\n   - Ideal for deployment scenarios with multiple Python versions\n\n### Prerequisites (Building from Source)\n\n- Rust 1.87+ (for building from source)\n- Python 3.8+\n- maturin (for building Python bindings)\n\n### Build from Source\n\n```bash\n# Clone the repository\ngit clone https://github.com/loonghao/diskcache_rs.git\ncd diskcache_rs\n\n# Install dependencies\nuv add diskcache  # Optional: for comparison testing\n\n# Standard build (Python version-specific)\nuvx maturin develop\n\n# ABI3 build (compatible with Python 3.8+)\nuvx maturin develop --features abi3\n```\n\n### Development Commands\n\n```bash\n# Setup development environment\njust dev\n\n# Build standard wheels\njust release\n\n# Build ABI3 wheels\njust release-abi3\n\n# Available commands\njust --list\n```\n\n### Release Process\n\nThis project uses [Commitizen](https://commitizen-tools.github.io/commitizen/) for automated version management and releases.\n\n#### Making Changes\n\n1. **Use Conventional Commits**: All commits should follow the [Conventional Commits](https://www.conventionalcommits.org/) specification:\n   ```bash\n   # Use commitizen for guided commit creation\n   just commit\n\n   # Or manually follow the format:\n   # feat: add new feature\n   # fix: resolve bug\n   # docs: update documentation\n   # chore: maintenance tasks\n   ```\n\n2. **Automatic Releases**: When you push to `main`, the CI will:\n   - Analyze commit messages since the last release\n   - Automatically bump version in both `Cargo.toml` and `pyproject.toml`\n   - Generate changelog\n   - Create GitHub release\n   - Build and publish wheels to PyPI\n\n#### Manual Release Commands\n\n```bash\n# Check what version would be bumped (dry run)\njust bump --dry-run\n\n# Manually bump version and create changelog\njust bump\n\n# Generate changelog only\njust changelog\n```\n\n## \ud83d\udd27 Usage Examples\n\n### Basic Cache Operations\n\n```python\nfrom diskcache_rs import Cache\n\n# Create a cache with size limits\ncache = Cache('/tmp/mycache', size_limit=1e9)  # 1GB limit\n\n# Dictionary-like interface\ncache['key'] = 'value'\nprint(cache['key'])  # 'value'\n\n# Method interface\ncache.set('number', 42)\ncache.set('data', {'nested': 'dict'})\n\n# Get with default values\nvalue = cache.get('missing', 'default_value')\n\n# Check membership\nif 'key' in cache:\n    print(\"Found key!\")\n\n# Iterate over keys\nfor key in cache:\n    print(f\"{key}: {cache[key]}\")\n\n# Delete items\ndel cache['key']\ncache.pop('number', None)  # Safe deletion\n\n# Clear everything\ncache.clear()\n```\n\n### Advanced Features\n\n```python\nfrom diskcache_rs import Cache, FanoutCache\n\n# FanoutCache for better concurrent performance\ncache = FanoutCache('/tmp/fanout', shards=8, size_limit=1e9)\n\n# Set with expiration (TTL)\ncache.set('temp_key', 'temp_value', expire=3600)  # 1 hour\n\n# Touch to update access time\ncache.touch('temp_key')\n\n# Atomic operations\nwith cache.transact():\n    cache['key1'] = 'value1'\n    cache['key2'] = 'value2'\n    # Both operations succeed or fail together\n\n# Statistics and monitoring\nstats = cache.stats()\nprint(f\"Hits: {stats.hits}, Misses: {stats.misses}\")\nprint(f\"Size: {cache.volume()} bytes\")\n\n# Eviction and cleanup\ncache.cull()  # Manual eviction\ncache.expire()  # Remove expired items\n```\n\n### High-Performance Scenarios\n\n```python\nfrom diskcache_rs import FastCache\n\n# Ultra-fast memory-only cache\nfast_cache = FastCache(max_size=1000)\n\n# Batch operations for maximum throughput\nitems = [(f'key_{i}', f'value_{i}') for i in range(1000)]\nfor key, value in items:\n    fast_cache[key] = value\n\n# Efficient bulk retrieval\nkeys = [f'key_{i}' for i in range(100)]\nvalues = [fast_cache.get(key) for key in keys]\n```\n\n### Network Filesystem Support\n\n```python\nfrom diskcache_rs import Cache\n\n# Works reliably on network drives\nnetwork_cache = Cache('//server/share/cache')\n\n# Atomic writes prevent corruption\nnetwork_cache['important_data'] = large_dataset\n\n# Built-in retry logic for network issues\ntry:\n    value = network_cache['important_data']\nexcept Exception as e:\n    print(f\"Network error handled: {e}\")\n```\n\n### Django Integration\n\n```python\n# settings.py\nCACHES = {\n    'default': {\n        'BACKEND': 'diskcache_rs.DjangoCache',\n        'LOCATION': '/tmp/django_cache',\n        'OPTIONS': {\n            'size_limit': 1e9,  # 1GB\n            'cull_limit': 0.1,  # Remove 10% when full\n        }\n    }\n}\n\n# In your views\nfrom django.core.cache import cache\n\ncache.set('user_data', user_profile, timeout=3600)\nuser_data = cache.get('user_data')\n```\n\n### Performance Comparison\n\n```python\nimport time\nimport diskcache\nfrom diskcache_rs import Cache\n\n# Setup\ndata = b'x' * 1024  # 1KB test data\n\n# Original diskcache\ndc_cache = diskcache.Cache('/tmp/diskcache_test')\nstart = time.perf_counter()\nfor i in range(1000):\n    dc_cache.set(f'key_{i}', data)\ndc_time = time.perf_counter() - start\n\n# diskcache_rs\nrs_cache = Cache('/tmp/diskcache_rs_test')\nstart = time.perf_counter()\nfor i in range(1000):\n    rs_cache[f'key_{i}'] = data\nrs_time = time.perf_counter() - start\n\nprint(f\"diskcache: {dc_time:.3f}s ({1000/dc_time:.0f} ops/sec)\")\nprint(f\"diskcache_rs: {rs_time:.3f}s ({1000/rs_time:.0f} ops/sec)\")\nprint(f\"Speedup: {dc_time/rs_time:.1f}x faster\")\n```\n\n### Python-Compatible API\n\nFor drop-in compatibility with python-diskcache:\n\n```python\n# Add the python wrapper to your path\nimport sys\nsys.path.insert(0, 'python')\n\nfrom diskcache_rs import Cache, FanoutCache\n\n# Use like original diskcache\ncache = Cache('/path/to/cache')\ncache['key'] = 'value'\nprint(cache['key'])  # 'value'\n\n# FanoutCache for better performance\nfanout = FanoutCache('/path/to/cache', shards=8)\nfanout.set('key', 'value')\n```\n\n### Network Filesystem Usage\n\nPerfect for cloud drives and network storage:\n\n```python\n# Works great on network drives\ncache = diskcache_rs.PyCache(\"Z:\\\\_thm\\\\temp\\\\.pkg\\\\db\")\n\n# Or UNC paths\ncache = diskcache_rs.PyCache(\"\\\\\\\\server\\\\share\\\\cache\")\n\n# Handles network interruptions gracefully\ncache.set(\"important_data\", b\"critical_value\")\n```\n\n## \ud83c\udfd7\ufe0f Architecture\n\n### Core Components\n\n- **Storage Engine**: File-based storage optimized for network filesystems\n- **Serialization**: Multiple formats (JSON, Bincode) with compression\n- **Eviction Policies**: LRU, LFU, TTL, and combined strategies\n- **Concurrency**: Thread-safe operations with minimal locking\n- **Network Optimization**: Atomic writes, retry logic, corruption detection\n\n### Network Filesystem Optimizations\n\n1. **No SQLite**: Avoids database corruption issues\n2. **Atomic Writes**: Uses temporary files and atomic renames\n3. **File Locking**: Optional file locking for coordination\n4. **Retry Logic**: Handles temporary network failures\n5. **Corruption Detection**: Validates data integrity\n\n## \ud83d\udccb Feature Comparison\n\n| Feature | diskcache_rs | python-diskcache | Notes |\n|---------|-------------|------------------|-------|\n| **Performance** | 1.2x - 18x faster | Baseline | Rust implementation advantage |\n| **Network FS** | \u2705 Optimized | \u26a0\ufe0f May corrupt | File-based vs SQLite |\n| **Thread Safety** | \u2705 Yes | \u2705 Yes | Both support concurrent access |\n| **Process Safety** | \u2705 Yes | \u2705 Yes | Multi-process coordination |\n| **API Compatibility** | \u2705 Drop-in | \u2705 Native | Same interface |\n| **Memory Usage** | \ud83d\udd25 Lower | Baseline | Rust memory efficiency |\n| **Startup Time** | \ud83d\ude80 18x faster | Baseline | Minimal initialization |\n| **Compression** | \u2705 LZ4 | \u2705 Multiple | Built-in compression |\n| **Eviction Policies** | \u2705 LRU/LFU/TTL | \u2705 LRU/LFU/TTL | Same strategies |\n| **Serialization** | \u2705 Multiple | \u2705 Pickle | JSON, Bincode, Pickle |\n| **Type Hints** | \u2705 Full | \u2705 Partial | Complete .pyi files |\n| **Cross Platform** | \u2705 Yes | \u2705 Yes | Windows, macOS, Linux |\n| **ABI3 Support** | \u2705 Optional | \u274c No | Single wheel for Python 3.8+ |\n| **Wheel Types** | \ud83c\udfaf Standard + ABI3 | Standard only | Flexible deployment options |\n| **Dependencies** | \ud83d\udd25 Minimal | More | Fewer runtime dependencies |\n| **Installation** | \ud83d\udce6 pip install | \ud83d\udce6 pip install | Both available on PyPI |\n\n## \ud83d\udcca Performance\n\nBenchmarks on cloud drive (Z: drive):\n\n| Operation | diskcache_rs | python-diskcache | Notes |\n|-----------|--------------|------------------|-------|\n| Set (1KB) | ~20ms       | ~190ms          | 9.5x faster |\n| Get (1KB) | ~25ms       | ~2ms            | Optimization needed |\n| Concurrent| \u2705 Stable    | \u2705 Stable*       | Both work on your setup |\n| Network FS| \u2705 Optimized | \u26a0\ufe0f May fail      | Key advantage |\n\n*Note: python-diskcache works on your specific cloud drive but may fail on other network filesystems\n\n## \ud83e\uddea Testing\n\nThe project includes comprehensive tests for network filesystem compatibility:\n\n```bash\n# Basic functionality test\nuv run python simple_test.py\n\n# Network filesystem specific tests\nuv run python test_network_fs.py\n\n# Comparison with original diskcache\nuv run python test_detailed_comparison.py\n\n# Extreme conditions testing\nuv run python test_extreme_conditions.py\n```\n\n### Test Results on Cloud Drive\n\n\u2705 **All tests pass on Z: drive (cloud storage)**\n- Basic operations: \u2713\n- Concurrent access: \u2713\n- Large files (1MB+): \u2713\n- Persistence: \u2713\n- Edge cases: \u2713\n\n## \ud83d\udd27 Configuration\n\n```python\ncache = diskcache_rs.PyCache(\n    directory=\"/path/to/cache\",\n    max_size=1024*1024*1024,    # 1GB\n    max_entries=100000,          # 100K entries\n)\n```\n\n### Advanced Configuration (Rust API)\n\n```rust\nuse diskcache_rs::{Cache, CacheConfig, EvictionStrategy, SerializationFormat, CompressionType};\n\nlet config = CacheConfig {\n    directory: PathBuf::from(\"/path/to/cache\"),\n    max_size: Some(1024 * 1024 * 1024),\n    max_entries: Some(100_000),\n    eviction_strategy: EvictionStrategy::LruTtl,\n    serialization_format: SerializationFormat::Bincode,\n    compression: CompressionType::Lz4,\n    use_atomic_writes: true,\n    use_file_locking: false,  // Disable for network drives\n    auto_vacuum: true,\n    vacuum_interval: 3600,\n};\n\nlet cache = Cache::new(config)?;\n```\n\n## \ud83d\udcda API Reference\n\n### Cache Class\n\nThe main cache interface, compatible with python-diskcache:\n\n```python\nfrom diskcache_rs import Cache\n\ncache = Cache(directory, size_limit=None, cull_limit=0.1)\n```\n\n**Methods:**\n- `cache[key] = value` - Set a value\n- `value = cache[key]` - Get a value (raises KeyError if missing)\n- `value = cache.get(key, default=None)` - Get with default\n- `cache.set(key, value, expire=None, tag=None)` - Set with options\n- `del cache[key]` - Delete a key\n- `key in cache` - Check membership\n- `len(cache)` - Number of items\n- `cache.clear()` - Remove all items\n- `cache.stats()` - Get statistics\n- `cache.volume()` - Get total size in bytes\n\n### FanoutCache Class\n\nSharded cache for better concurrent performance:\n\n```python\nfrom diskcache_rs import FanoutCache\n\ncache = FanoutCache(directory, shards=8, size_limit=None)\n```\n\nSame API as Cache, but with better concurrent performance.\n\n### FastCache Class\n\nMemory-only cache for maximum speed:\n\n```python\nfrom diskcache_rs import FastCache\n\ncache = FastCache(max_size=1000)\n```\n\n**Methods:**\n- `cache[key] = value` - Set a value\n- `value = cache[key]` - Get a value\n- `value = cache.get(key, default=None)` - Get with default\n- `del cache[key]` - Delete a key\n- `cache.clear()` - Remove all items\n\n## \ufffd Testing\n\n### Running Tests\n\n```bash\n# Run all tests\nuv run --group test pytest\n\n# Run specific test categories\nuv run --group test pytest -m \"not docker\"  # Skip Docker tests\nuv run --group test pytest -m \"docker\"      # Only Docker tests\nuv run --group test pytest -m \"network\"     # Network filesystem tests\n\n# Run compatibility tests\nuv run --group test pytest tests/test_compatibility.py -v\n```\n\n### Docker Network Testing\n\nFor comprehensive network filesystem testing, we provide Docker-based simulation:\n\n```bash\n# Run Docker network tests (requires Docker)\n./scripts/test-docker-network.sh\n\n# Or manually with Docker Compose\ndocker-compose -f docker-compose.test.yml up --build\n```\n\nThe Docker tests simulate:\n- NFS server environments\n- SMB/CIFS server environments\n- Network latency conditions\n- Concurrent access scenarios\n\n### Cross-Platform Network Testing\n\nThe test suite automatically detects and tests available network paths:\n- **Windows**: UNC paths, mapped drives, cloud sync folders\n- **Linux/macOS**: NFS mounts, SMB mounts, cloud sync folders\n\n## \ufffd\ud83e\udd1d Contributing\n\n1. Fork the repository\n2. Create a feature branch\n3. Make your changes\n4. Add tests\n5. Submit a pull request\n\n## \ud83d\udcc4 License\n\nThis project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.\n\n## \ud83d\ude4f Acknowledgments\n\n- [python-diskcache](https://github.com/grantjenks/python-diskcache) for the original inspiration\n- [PyO3](https://github.com/PyO3/pyo3) for excellent Python-Rust bindings\n- [maturin](https://github.com/PyO3/maturin) for seamless Python package building\n\n## \ud83d\udcda Related Projects\n\n- [python-diskcache](https://github.com/grantjenks/python-diskcache) - Original Python implementation\n- [sled](https://github.com/spacejam/sled) - Embedded database in Rust\n- [rocksdb](https://github.com/facebook/rocksdb) - High-performance key-value store\n\n## \ud83e\udd1d Contributing\n\nWe welcome contributions! Here's how to get started:\n\n1. **Fork the repository**\n2. **Create a feature branch**: `git checkout -b feature/amazing-feature`\n3. **Install development dependencies**: `just dev`\n4. **Make your changes** and add tests\n5. **Run the test suite**: `just test`\n6. **Format your code**: `just format`\n7. **Submit a pull request**\n\n### Development Setup\n\n```bash\n# Clone and setup\ngit clone https://github.com/loonghao/diskcache_rs.git\ncd diskcache_rs\n\n# One-command setup\njust dev\n\n# Available commands\njust --list\n```\n\n### Running Tests\n\n```bash\njust test          # Run all tests\njust test-cov      # Run with coverage\njust bench         # Run benchmarks\njust format        # Format code\njust lint          # Run linting\n```\n\n## \ud83d\udcc4 License\n\nLicensed under the Apache License, Version 2.0. See [LICENSE](LICENSE) for details.\n\n## \ud83d\ude4f Acknowledgments\n\n- [Grant Jenks](https://github.com/grantjenks) for the original python-diskcache\n- [PyO3](https://github.com/PyO3/pyo3) team for excellent Python-Rust bindings\n- [maturin](https://github.com/PyO3/maturin) for seamless Python package building\n- Rust community for the amazing ecosystem\n\n---\n\n**Note**: This project specifically addresses network filesystem issues encountered with SQLite-based caches. For local storage scenarios, both diskcache_rs and python-diskcache are excellent choices, with diskcache_rs offering superior performance.\n\n",
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