# shibudb-client-python
ShibuDb client library for python
# ShibuDb Python Client
A comprehensive Python client for ShibuDb database that supports authentication, key-value operations, vector similarity search, space management, and connection pooling.
## Features
- 🔐 **Authentication & User Management**: Secure login with role-based access control
- 🔑 **Key-Value Operations**: Traditional key-value storage with PUT, GET, DELETE operations
- 🧮 **Vector Similarity Search**: Advanced vector operations with multiple index types
- 🗂️ **Space Management**: Create, delete, and manage different storage spaces
- 🛡️ **Error Handling**: Comprehensive error handling with custom exceptions
- 📊 **Connection Management**: Automatic connection handling with context managers
- 🔗 **Connection Pooling**: High-performance connection pooling for concurrent operations
## Installation
### Prerequisites
1. **ShibuDb Server**: Ensure the ShibuDb server is running
```bash
# Start the server (requires sudo)
sudo shibudb start 4444
```
2. **Python Requirements**: The client uses only standard library modules
- Python 3.7+
- No external dependencies required
### Setup
1. **Clone or download the client files**:
```bash
# Copy the client files to your project
cp shibudb_client.py your_project/
```
2. **Import the client**:
```python
from shibudb_client import ShibuDbClient, User, connect
```
## Quick Start
### Basic Connection and Authentication
```python
from shibudb_client import ShibuDbClient
# Create client and authenticate
client = ShibuDbClient("localhost", 4444)
client.authenticate("admin", "admin")
# Use context manager for automatic cleanup
with ShibuDbClient("localhost", 4444) as client:
client.authenticate("admin", "admin")
# Your operations here
```
### Connection Pooling
```python
from shibudb_client import create_connection_pool
# Create a connection pool
pool = create_connection_pool(
host="localhost",
port=4444,
username="admin",
password="admin",
min_size=2,
max_size=10
)
# Use pooled connections
with pool.get_connection() as client:
response = client.list_spaces()
print(f"Available spaces: {response}")
# Pool automatically manages connections
pool.close()
```
### Key-Value Operations
```python
# Create and use a space
client.create_space("mytable", "key-value")
client.use_space("mytable")
# Basic operations
client.put("name", "John Doe")
response = client.get("name")
print(response["value"]) # "John Doe"
client.delete("name")
```
### Vector Operations
```python
# Create a vector space
client.create_space("vectors", "vector", dimension=128, index_type="Flat", metric="L2")
client.use_space("vectors")
# Insert vectors
client.insert_vector(1, [0.1, 0.2, 0.3, ...])
client.insert_vector(2, [0.4, 0.5, 0.6, ...])
# Search for similar vectors
results = client.search_topk([0.1, 0.2, 0.3, ...], k=5)
print(results["message"]) # Search results
# Range search
results = client.range_search([0.1, 0.2, 0.3, ...], radius=0.5)
```
## API Reference
### ShibuDbClient
#### Constructor
```python
ShibuDbClient(host="localhost", port=4444, timeout=30)
```
#### Authentication
```python
client.authenticate(username: str, password: str) -> Dict[str, Any]
```
#### Space Management
```python
client.create_space(name: str, engine_type: str, dimension: Optional[int] = None,
index_type: str = "Flat", metric: str = "L2") -> Dict[str, Any]
client.delete_space(name: str) -> Dict[str, Any]
client.list_spaces() -> Dict[str, Any]
client.use_space(name: str) -> Dict[str, Any]
```
#### Key-Value Operations
```python
client.put(key: str, value: str, space: Optional[str] = None) -> Dict[str, Any]
client.get(key: str, space: Optional[str] = None) -> Dict[str, Any]
client.delete(key: str, space: Optional[str] = None) -> Dict[str, Any]
```
#### Vector Operations
```python
client.insert_vector(vector_id: int, vector: List[float], space: Optional[str] = None) -> Dict[str, Any]
client.search_topk(query_vector: List[float], k: int = 1, space: Optional[str] = None) -> Dict[str, Any]
client.range_search(query_vector: List[float], radius: float, space: Optional[str] = None) -> Dict[str, Any]
client.get_vector(vector_id: int, space: Optional[str] = None) -> Dict[str, Any]
```
#### User Management (Admin Only)
```python
client.create_user(user: User) -> Dict[str, Any]
client.update_user_password(username: str, new_password: str) -> Dict[str, Any]
client.update_user_role(username: str, new_role: str) -> Dict[str, Any]
client.update_user_permissions(username: str, permissions: Dict[str, str]) -> Dict[str, Any]
client.delete_user(username: str) -> Dict[str, Any]
client.get_user(username: str) -> Dict[str, Any]
```
### Data Models
#### User
```python
@dataclass
class User:
username: str
password: str
role: str = "user"
permissions: Dict[str, str] = None
```
#### SpaceInfo
```python
@dataclass
class SpaceInfo:
name: str
engine_type: str
dimension: Optional[int] = None
index_type: Optional[str] = None
metric: Optional[str] = None
```
### Exceptions
- `ShibuDbError`: Base exception for all client errors
- `AuthenticationError`: Raised when authentication fails
- `ConnectionError`: Raised when connection fails
- `QueryError`: Raised when query execution fails
- `PoolExhaustedError`: Raised when connection pool is exhausted
## Examples
### Complete Example
```python
from shibudb_client import ShibuDbClient, User
def main():
# Connect and authenticate
with ShibuDbClient("localhost", 4444) as client:
client.authenticate("admin", "admin")
# Create spaces
client.create_space("users", "key-value")
client.create_space("embeddings", "vector", dimension=128)
# Store user data
client.use_space("users")
client.put("user1", "Alice Johnson")
client.put("user2", "Bob Smith")
# Store embeddings
client.use_space("embeddings")
client.insert_vector(1, [0.1, 0.2, 0.3, ...])
client.insert_vector(2, [0.4, 0.5, 0.6, ...])
# Search for similar embeddings
results = client.search_topk([0.1, 0.2, 0.3, ...], k=5)
print(f"Search results: {results}")
if __name__ == "__main__":
main()
```
### Error Handling
```python
from shibudb_client import ShibuDbClient, AuthenticationError, ConnectionError, QueryError
try:
client = ShibuDbClient("localhost", 4444)
client.authenticate("admin", "admin")
# Your operations here
except AuthenticationError as e:
print(f"Authentication failed: {e}")
except ConnectionError as e:
print(f"Connection failed: {e}")
except QueryError as e:
print(f"Query failed: {e}")
finally:
client.close()
```
### Advanced Usage
```python
from shibudb_client import ShibuDbClient, User
# Create admin user
admin_user = User(
username="admin",
password="adminpass",
role="admin"
)
# Create regular user with permissions
user = User(
username="user1",
password="userpass",
role="user",
permissions={"mytable": "read", "vectortable": "write"}
)
with ShibuDbClient("localhost", 4444) as client:
client.authenticate("admin", "admin")
# Create users
client.create_user(user)
# Create spaces for different purposes
client.create_space("users", "key-value")
client.create_space("products", "key-value")
client.create_space("embeddings", "vector", dimension=256)
client.create_space("recommendations", "vector", dimension=512)
# Store data in different spaces
client.use_space("users")
client.put("user1", "Alice Johnson")
client.use_space("embeddings")
client.insert_vector(1, [0.1, 0.2, 0.3, ...])
# Search for recommendations
query_vector = [0.1, 0.2, 0.3, ...]
results = client.search_topk(query_vector, k=10)
```
## Running Examples
### Simple Test
```bash
python simple_test.py
```
### Comprehensive Examples
```bash
python example.py
```
### Connection Pooling Examples
```bash
python pooling_example.py
```
### Comprehensive Connection Pooling Tests
```bash
python comprehensive_pool_test.py
```
## Connection Pooling
The ShibuDb client supports connection pooling for high-performance concurrent operations. Connection pooling provides:
- **Connection Reuse**: Efficiently reuse database connections
- **Concurrent Operations**: Support for multiple simultaneous operations
- **Automatic Health Checks**: Background health monitoring of connections
- **Configurable Pool Size**: Adjustable minimum and maximum pool sizes
- **Timeout Handling**: Configurable connection acquisition timeouts
### Pool Configuration
```python
from shibudb_client import create_connection_pool, ConnectionConfig
# Create pool with custom configuration
pool = create_connection_pool(
host="localhost",
port=4444,
username="admin",
password="admin",
min_size=2, # Minimum connections in pool
max_size=10, # Maximum connections in pool
acquire_timeout=30, # Timeout for acquiring connection (seconds)
health_check_interval=60 # Health check interval (seconds)
)
```
### Using Connection Pools
```python
# Basic usage
with pool.get_connection() as client:
response = client.list_spaces()
print(f"Spaces: {response}")
# Concurrent operations
import threading
from concurrent.futures import ThreadPoolExecutor
def worker(worker_id):
with pool.get_connection() as client:
client.create_space(f"space_{worker_id}", "key-value")
client.use_space(f"space_{worker_id}")
client.put(f"key_{worker_id}", f"value_{worker_id}")
return client.get(f"key_{worker_id}")
# Run concurrent workers
with ThreadPoolExecutor(max_workers=5) as executor:
futures = [executor.submit(worker, i) for i in range(5)]
for future in as_completed(futures):
result = future.result()
print(f"Result: {result}")
```
### Pool Statistics
```python
# Get pool statistics
stats = pool.get_stats()
print(f"Pool size: {stats['pool_size']}")
print(f"Active connections: {stats['active_connections']}")
print(f"Min size: {stats['min_size']}")
print(f"Max size: {stats['max_size']}")
```
### Error Handling with Pools
```python
from shibudb_client import PoolExhaustedError
try:
with pool.get_connection() as client:
# Your operations here
pass
except PoolExhaustedError as e:
print(f"Pool exhausted: {e}")
except AuthenticationError as e:
print(f"Authentication failed: {e}")
except ConnectionError as e:
print(f"Connection failed: {e}")
```
## Engine Types
### Key-Value Engine
- Traditional key-value storage
- Supports PUT, GET, DELETE operations
- No dimension required
### Vector Engine
- Vector similarity search
- Multiple index types:
- **Flat**: Exact search (default)
- **HNSW**: Hierarchical Navigable Small World
- **IVF**: Inverted File Index
- **IVF with PQ**: Product Quantization
- Distance metrics:
- **L2**: Euclidean distance (default)
- **IP**: Inner product
- **COS**: Cosine similarity
## Security
- **Authentication Required**: All operations require valid credentials
- **Role-Based Access**: Admin and user roles with different permissions
- **Space-Level Permissions**: Read/write permissions per space
- **Connection Security**: TCP-based communication with timeout handling
## Troubleshooting
### Common Issues
1. **Connection Failed**
- Ensure ShibuDb server is running: `sudo shibudb start 4444`
- Check server port and host settings
- Verify firewall settings
2. **Authentication Failed**
- Verify username and password
- Ensure user exists in the system
- Check user permissions
3. **Space Not Found**
- Use `list_spaces()` to see available spaces
- Create space before using: `create_space()`
- Use `use_space()` to switch to a space
4. **Vector Dimension Mismatch**
- Ensure vector dimension matches space dimension
- Check space creation parameters
- Verify vector format (comma-separated floats)
### Debug Mode
Enable debug logging:
```python
import logging
logging.basicConfig(level=logging.DEBUG)
```
## Contributing
1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Submit a pull request
## License
This client is provided as-is for use with ShibuDb database.
Raw data
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"description": "# shibudb-client-python\nShibuDb client library for python\n\n# ShibuDb Python Client\n\nA comprehensive Python client for ShibuDb database that supports authentication, key-value operations, vector similarity search, space management, and connection pooling.\n\n## Features\n\n- \ud83d\udd10 **Authentication & User Management**: Secure login with role-based access control\n- \ud83d\udd11 **Key-Value Operations**: Traditional key-value storage with PUT, GET, DELETE operations\n- \ud83e\uddee **Vector Similarity Search**: Advanced vector operations with multiple index types\n- \ud83d\uddc2\ufe0f **Space Management**: Create, delete, and manage different storage spaces\n- \ud83d\udee1\ufe0f **Error Handling**: Comprehensive error handling with custom exceptions\n- \ud83d\udcca **Connection Management**: Automatic connection handling with context managers\n- \ud83d\udd17 **Connection Pooling**: High-performance connection pooling for concurrent operations\n\n## Installation\n\n### Prerequisites\n\n1. **ShibuDb Server**: Ensure the ShibuDb server is running\n ```bash\n # Start the server (requires sudo)\n sudo shibudb start 4444\n ```\n\n2. **Python Requirements**: The client uses only standard library modules\n - Python 3.7+\n - No external dependencies required\n\n### Setup\n\n1. **Clone or download the client files**:\n ```bash\n # Copy the client files to your project\n cp shibudb_client.py your_project/\n ```\n\n2. **Import the client**:\n ```python\n from shibudb_client import ShibuDbClient, User, connect\n ```\n\n## Quick Start\n\n### Basic Connection and Authentication\n\n```python\nfrom shibudb_client import ShibuDbClient\n\n# Create client and authenticate\nclient = ShibuDbClient(\"localhost\", 4444)\nclient.authenticate(\"admin\", \"admin\")\n\n# Use context manager for automatic cleanup\nwith ShibuDbClient(\"localhost\", 4444) as client:\n client.authenticate(\"admin\", \"admin\")\n # Your operations here\n```\n\n### Connection Pooling\n\n```python\nfrom shibudb_client import create_connection_pool\n\n# Create a connection pool\npool = create_connection_pool(\n host=\"localhost\",\n port=4444,\n username=\"admin\",\n password=\"admin\",\n min_size=2,\n max_size=10\n)\n\n# Use pooled connections\nwith pool.get_connection() as client:\n response = client.list_spaces()\n print(f\"Available spaces: {response}\")\n\n# Pool automatically manages connections\npool.close()\n```\n\n### Key-Value Operations\n\n```python\n# Create and use a space\nclient.create_space(\"mytable\", \"key-value\")\nclient.use_space(\"mytable\")\n\n# Basic operations\nclient.put(\"name\", \"John Doe\")\nresponse = client.get(\"name\")\nprint(response[\"value\"]) # \"John Doe\"\n\nclient.delete(\"name\")\n```\n\n### Vector Operations\n\n```python\n# Create a vector space\nclient.create_space(\"vectors\", \"vector\", dimension=128, index_type=\"Flat\", metric=\"L2\")\nclient.use_space(\"vectors\")\n\n# Insert vectors\nclient.insert_vector(1, [0.1, 0.2, 0.3, ...])\nclient.insert_vector(2, [0.4, 0.5, 0.6, ...])\n\n# Search for similar vectors\nresults = client.search_topk([0.1, 0.2, 0.3, ...], k=5)\nprint(results[\"message\"]) # Search results\n\n# Range search\nresults = client.range_search([0.1, 0.2, 0.3, ...], radius=0.5)\n```\n\n## API Reference\n\n### ShibuDbClient\n\n#### Constructor\n```python\nShibuDbClient(host=\"localhost\", port=4444, timeout=30)\n```\n\n#### Authentication\n```python\nclient.authenticate(username: str, password: str) -> Dict[str, Any]\n```\n\n#### Space Management\n```python\nclient.create_space(name: str, engine_type: str, dimension: Optional[int] = None, \n index_type: str = \"Flat\", metric: str = \"L2\") -> Dict[str, Any]\nclient.delete_space(name: str) -> Dict[str, Any]\nclient.list_spaces() -> Dict[str, Any]\nclient.use_space(name: str) -> Dict[str, Any]\n```\n\n#### Key-Value Operations\n```python\nclient.put(key: str, value: str, space: Optional[str] = None) -> Dict[str, Any]\nclient.get(key: str, space: Optional[str] = None) -> Dict[str, Any]\nclient.delete(key: str, space: Optional[str] = None) -> Dict[str, Any]\n```\n\n#### Vector Operations\n```python\nclient.insert_vector(vector_id: int, vector: List[float], space: Optional[str] = None) -> Dict[str, Any]\nclient.search_topk(query_vector: List[float], k: int = 1, space: Optional[str] = None) -> Dict[str, Any]\nclient.range_search(query_vector: List[float], radius: float, space: Optional[str] = None) -> Dict[str, Any]\nclient.get_vector(vector_id: int, space: Optional[str] = None) -> Dict[str, Any]\n```\n\n#### User Management (Admin Only)\n```python\nclient.create_user(user: User) -> Dict[str, Any]\nclient.update_user_password(username: str, new_password: str) -> Dict[str, Any]\nclient.update_user_role(username: str, new_role: str) -> Dict[str, Any]\nclient.update_user_permissions(username: str, permissions: Dict[str, str]) -> Dict[str, Any]\nclient.delete_user(username: str) -> Dict[str, Any]\nclient.get_user(username: str) -> Dict[str, Any]\n```\n\n### Data Models\n\n#### User\n```python\n@dataclass\nclass User:\n username: str\n password: str\n role: str = \"user\"\n permissions: Dict[str, str] = None\n```\n\n#### SpaceInfo\n```python\n@dataclass\nclass SpaceInfo:\n name: str\n engine_type: str\n dimension: Optional[int] = None\n index_type: Optional[str] = None\n metric: Optional[str] = None\n```\n\n### Exceptions\n\n- `ShibuDbError`: Base exception for all client errors\n- `AuthenticationError`: Raised when authentication fails\n- `ConnectionError`: Raised when connection fails\n- `QueryError`: Raised when query execution fails\n- `PoolExhaustedError`: Raised when connection pool is exhausted\n\n## Examples\n\n### Complete Example\n\n```python\nfrom shibudb_client import ShibuDbClient, User\n\ndef main():\n # Connect and authenticate\n with ShibuDbClient(\"localhost\", 4444) as client:\n client.authenticate(\"admin\", \"admin\")\n \n # Create spaces\n client.create_space(\"users\", \"key-value\")\n client.create_space(\"embeddings\", \"vector\", dimension=128)\n \n # Store user data\n client.use_space(\"users\")\n client.put(\"user1\", \"Alice Johnson\")\n client.put(\"user2\", \"Bob Smith\")\n \n # Store embeddings\n client.use_space(\"embeddings\")\n client.insert_vector(1, [0.1, 0.2, 0.3, ...])\n client.insert_vector(2, [0.4, 0.5, 0.6, ...])\n \n # Search for similar embeddings\n results = client.search_topk([0.1, 0.2, 0.3, ...], k=5)\n print(f\"Search results: {results}\")\n\nif __name__ == \"__main__\":\n main()\n```\n\n### Error Handling\n\n```python\nfrom shibudb_client import ShibuDbClient, AuthenticationError, ConnectionError, QueryError\n\ntry:\n client = ShibuDbClient(\"localhost\", 4444)\n client.authenticate(\"admin\", \"admin\")\n \n # Your operations here\n \nexcept AuthenticationError as e:\n print(f\"Authentication failed: {e}\")\nexcept ConnectionError as e:\n print(f\"Connection failed: {e}\")\nexcept QueryError as e:\n print(f\"Query failed: {e}\")\nfinally:\n client.close()\n```\n\n### Advanced Usage\n\n```python\nfrom shibudb_client import ShibuDbClient, User\n\n# Create admin user\nadmin_user = User(\n username=\"admin\",\n password=\"adminpass\",\n role=\"admin\"\n)\n\n# Create regular user with permissions\nuser = User(\n username=\"user1\",\n password=\"userpass\",\n role=\"user\",\n permissions={\"mytable\": \"read\", \"vectortable\": \"write\"}\n)\n\nwith ShibuDbClient(\"localhost\", 4444) as client:\n client.authenticate(\"admin\", \"admin\")\n \n # Create users\n client.create_user(user)\n \n # Create spaces for different purposes\n client.create_space(\"users\", \"key-value\")\n client.create_space(\"products\", \"key-value\")\n client.create_space(\"embeddings\", \"vector\", dimension=256)\n client.create_space(\"recommendations\", \"vector\", dimension=512)\n \n # Store data in different spaces\n client.use_space(\"users\")\n client.put(\"user1\", \"Alice Johnson\")\n \n client.use_space(\"embeddings\")\n client.insert_vector(1, [0.1, 0.2, 0.3, ...])\n \n # Search for recommendations\n query_vector = [0.1, 0.2, 0.3, ...]\n results = client.search_topk(query_vector, k=10)\n```\n\n## Running Examples\n\n### Simple Test\n```bash\npython simple_test.py\n```\n\n### Comprehensive Examples\n```bash\npython example.py\n```\n\n### Connection Pooling Examples\n```bash\npython pooling_example.py\n```\n\n### Comprehensive Connection Pooling Tests\n```bash\npython comprehensive_pool_test.py\n```\n\n## Connection Pooling\n\nThe ShibuDb client supports connection pooling for high-performance concurrent operations. Connection pooling provides:\n\n- **Connection Reuse**: Efficiently reuse database connections\n- **Concurrent Operations**: Support for multiple simultaneous operations\n- **Automatic Health Checks**: Background health monitoring of connections\n- **Configurable Pool Size**: Adjustable minimum and maximum pool sizes\n- **Timeout Handling**: Configurable connection acquisition timeouts\n\n### Pool Configuration\n\n```python\nfrom shibudb_client import create_connection_pool, ConnectionConfig\n\n# Create pool with custom configuration\npool = create_connection_pool(\n host=\"localhost\",\n port=4444,\n username=\"admin\",\n password=\"admin\",\n min_size=2, # Minimum connections in pool\n max_size=10, # Maximum connections in pool\n acquire_timeout=30, # Timeout for acquiring connection (seconds)\n health_check_interval=60 # Health check interval (seconds)\n)\n```\n\n### Using Connection Pools\n\n```python\n# Basic usage\nwith pool.get_connection() as client:\n response = client.list_spaces()\n print(f\"Spaces: {response}\")\n\n# Concurrent operations\nimport threading\nfrom concurrent.futures import ThreadPoolExecutor\n\ndef worker(worker_id):\n with pool.get_connection() as client:\n client.create_space(f\"space_{worker_id}\", \"key-value\")\n client.use_space(f\"space_{worker_id}\")\n client.put(f\"key_{worker_id}\", f\"value_{worker_id}\")\n return client.get(f\"key_{worker_id}\")\n\n# Run concurrent workers\nwith ThreadPoolExecutor(max_workers=5) as executor:\n futures = [executor.submit(worker, i) for i in range(5)]\n for future in as_completed(futures):\n result = future.result()\n print(f\"Result: {result}\")\n```\n\n### Pool Statistics\n\n```python\n# Get pool statistics\nstats = pool.get_stats()\nprint(f\"Pool size: {stats['pool_size']}\")\nprint(f\"Active connections: {stats['active_connections']}\")\nprint(f\"Min size: {stats['min_size']}\")\nprint(f\"Max size: {stats['max_size']}\")\n```\n\n### Error Handling with Pools\n\n```python\nfrom shibudb_client import PoolExhaustedError\n\ntry:\n with pool.get_connection() as client:\n # Your operations here\n pass\nexcept PoolExhaustedError as e:\n print(f\"Pool exhausted: {e}\")\nexcept AuthenticationError as e:\n print(f\"Authentication failed: {e}\")\nexcept ConnectionError as e:\n print(f\"Connection failed: {e}\")\n```\n\n## Engine Types\n\n### Key-Value Engine\n- Traditional key-value storage\n- Supports PUT, GET, DELETE operations\n- No dimension required\n\n### Vector Engine\n- Vector similarity search\n- Multiple index types:\n - **Flat**: Exact search (default)\n - **HNSW**: Hierarchical Navigable Small World\n - **IVF**: Inverted File Index\n - **IVF with PQ**: Product Quantization\n- Distance metrics:\n - **L2**: Euclidean distance (default)\n - **IP**: Inner product\n - **COS**: Cosine similarity\n\n## Security\n\n- **Authentication Required**: All operations require valid credentials\n- **Role-Based Access**: Admin and user roles with different permissions\n- **Space-Level Permissions**: Read/write permissions per space\n- **Connection Security**: TCP-based communication with timeout handling\n\n## Troubleshooting\n\n### Common Issues\n\n1. **Connection Failed**\n - Ensure ShibuDb server is running: `sudo shibudb start 4444`\n - Check server port and host settings\n - Verify firewall settings\n\n2. **Authentication Failed**\n - Verify username and password\n - Ensure user exists in the system\n - Check user permissions\n\n3. **Space Not Found**\n - Use `list_spaces()` to see available spaces\n - Create space before using: `create_space()`\n - Use `use_space()` to switch to a space\n\n4. **Vector Dimension Mismatch**\n - Ensure vector dimension matches space dimension\n - Check space creation parameters\n - Verify vector format (comma-separated floats)\n\n### Debug Mode\n\nEnable debug logging:\n```python\nimport logging\nlogging.basicConfig(level=logging.DEBUG)\n```\n\n## Contributing\n\n1. Fork the repository\n2. Create a feature branch\n3. Add tests for new functionality\n4. Submit a pull request\n\n## License\n\nThis client is provided as-is for use with ShibuDb database.\n",
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