updated services api

This commit is contained in:
2025-06-03 21:43:39 +03:00
parent 3055b2bde7
commit 1c0bb741a0
49 changed files with 2192 additions and 133 deletions

View File

@@ -0,0 +1,67 @@
# Redis Pub/Sub Chain Implementation
This module implements a chain of services communicating through Redis Pub/Sub channels. Each service in the chain subscribes to the previous service's channel and publishes to its own channel, creating a processing pipeline.
## Architecture
The implementation follows a simple chain pattern:
```
READER → PROCESSOR → WRITER
```
- **READER**: Generates mock data with a "red" stage and publishes to `chain:reader`
- **PROCESSOR**: Subscribes to `chain:reader`, processes messages with "red" stage, updates stage to "processed", and publishes to `chain:processor`
- **WRITER**: Subscribes to `chain:processor`, processes messages with "processed" stage, updates stage to "completed", and publishes to `chain:writer`
## Message Flow
Each message flows through the chain with a stage attribute that determines how it's processed:
1. READER generates a message with `stage="red"`
2. PROCESSOR receives the message, checks if `stage="red"`, processes it, and sets `stage="processed"`
3. WRITER receives the message, checks if `stage="processed"`, processes it, and sets `stage="completed"`
## Performance
The implementation includes timing information to track how long messages take to flow through the entire chain. Sample output:
```
[READER] 1745176466.132082 | Published UUID: 74cf2312-25ec-4da8-bc0a-521b6ccd5206
[PROCESSOR] 1745176466.132918 | Received UUID: 74cf2312-25ec-4da8-bc0a-521b6ccd5206 | Published UUID: 74cf2312-25ec-4da8-bc0a-521b6ccd5206
[WRITER] 1745176466.133097 | Received UUID: 74cf2312-25ec-4da8-bc0a-521b6ccd5206 | Published UUID: 74cf2312-25ec-4da8-bc0a-521b6ccd5206 | Elapsed: 1.83ms
[READER] 1745176468.133018 | Published UUID: 2ffd217f-650f-4e10-bc16-317adcf7a59a
[PROCESSOR] 1745176468.133792 | Received UUID: 2ffd217f-650f-4e10-bc16-317adcf7a59a | Published UUID: 2ffd217f-650f-4e10-bc16-317adcf7a59a
[WRITER] 1745176468.134001 | Received UUID: 2ffd217f-650f-4e10-bc16-317adcf7a59a | Published UUID: 2ffd217f-650f-4e10-bc16-317adcf7a59a | Elapsed: 1.76ms
[READER] 1745176470.133841 | Published UUID: 87e1f3af-c6c2-4fa5-9a65-57e7327d3989
[PROCESSOR] 1745176470.134623 | Received UUID: 87e1f3af-c6c2-4fa5-9a65-57e7327d3989 | Published UUID: 87e1f3af-c6c2-4fa5-9a65-57e7327d3989
[WRITER] 1745176470.134861 | Received UUID: 87e1f3af-c6c2-4fa5-9a65-57e7327d3989 | Published UUID: 87e1f3af-c6c2-4fa5-9a65-57e7327d3989 | Elapsed: 1.68ms
```
The elapsed time shows the total time from when the READER publishes a message until the WRITER completes processing it. In the samples above, the end-to-end processing time ranges from 1.68ms to 1.83ms.
## Usage
To run the demonstration:
```bash
python -m Controllers.Redis.Broadcast.implementations
```
This will start all three services in the chain and begin processing messages. Press Ctrl+C to stop the demonstration.
## Implementation Details
The implementation uses:
1. A singleton Redis Pub/Sub handler with publisher and subscriber capabilities
2. Thread-based message processing
3. JSON serialization for message passing
4. Stage-based message processing to track progress through the chain
5. Timing information to measure performance
Each service in the chain follows these steps:
1. Subscribe to the appropriate channel
2. Define a message handler function
3. Process incoming messages based on their stage
4. Publish processed messages to the next channel in the chain

View File

@@ -0,0 +1,248 @@
import json
from typing import Optional, Dict, Any, List, Callable, Union
from threading import Thread
from Controllers.Redis.connection import redis_cli
from Controllers.Redis.response import RedisResponse
class RedisPublisher:
"""Redis Publisher class for broadcasting messages to channels."""
def __init__(self, redis_client=redis_cli):
self.redis_client = redis_client
def publish(self, channel: str, message: Union[Dict, List, str]) -> RedisResponse:
"""Publish a message to a Redis channel.
Args:
channel: The channel to publish to
message: The message to publish (will be JSON serialized if dict or list)
Returns:
RedisResponse with status and message
"""
try:
# Convert dict/list to JSON string if needed
if isinstance(message, (dict, list)):
message = json.dumps(message)
# Publish the message
recipient_count = self.redis_client.publish(channel, message)
return RedisResponse(
status=True,
message=f"Message published successfully to {channel}.",
data={"recipients": recipient_count},
)
except Exception as e:
return RedisResponse(
status=False,
message=f"Failed to publish message to {channel}.",
error=str(e),
)
class RedisSubscriber:
"""Redis Subscriber class for listening to channels."""
def __init__(self, redis_client=redis_cli):
self.redis_client = redis_client
self.pubsub = self.redis_client.pubsub()
self.active_threads = {}
def subscribe(
self, channel: str, callback: Callable[[Dict], None]
) -> RedisResponse:
"""Subscribe to a Redis channel with a callback function.
Args:
channel: The channel to subscribe to
callback: Function to call when a message is received
Returns:
RedisResponse with status and message
"""
try:
# Subscribe to the channel
self.pubsub.subscribe(**{channel: self._message_handler(callback)})
return RedisResponse(
status=True, message=f"Successfully subscribed to {channel}."
)
except Exception as e:
return RedisResponse(
status=False, message=f"Failed to subscribe to {channel}.", error=str(e)
)
def psubscribe(
self, pattern: str, callback: Callable[[Dict], None]
) -> RedisResponse:
"""Subscribe to Redis channels matching a pattern.
Args:
pattern: The pattern to subscribe to (e.g., 'user.*')
callback: Function to call when a message is received
Returns:
RedisResponse with status and message
"""
try:
# Subscribe to the pattern
self.pubsub.psubscribe(**{pattern: self._message_handler(callback)})
return RedisResponse(
status=True, message=f"Successfully pattern-subscribed to {pattern}."
)
except Exception as e:
return RedisResponse(
status=False,
message=f"Failed to pattern-subscribe to {pattern}.",
error=str(e),
)
def _message_handler(self, callback: Callable[[Dict], None]):
"""Create a message handler function for the subscription."""
def handler(message):
# Skip subscription confirmation messages
if message["type"] in ("subscribe", "psubscribe"):
return
# Parse JSON if the message is a JSON string
data = message["data"]
if isinstance(data, bytes):
data = data.decode("utf-8")
try:
data = json.loads(data)
except json.JSONDecodeError:
# Not JSON, keep as is
pass
# Call the callback with the message data
callback(
{
"channel": (
message.get("channel", b"").decode("utf-8")
if isinstance(message.get("channel", b""), bytes)
else message.get("channel", "")
),
"pattern": (
message.get("pattern", b"").decode("utf-8")
if isinstance(message.get("pattern", b""), bytes)
else message.get("pattern", "")
),
"data": data,
}
)
return handler
def start_listening(self, in_thread: bool = True) -> RedisResponse:
"""Start listening for messages on subscribed channels.
Args:
in_thread: If True, start listening in a separate thread
Returns:
RedisResponse with status and message
"""
try:
if in_thread:
thread = Thread(target=self._listen_thread, daemon=True)
thread.start()
self.active_threads["listener"] = thread
return RedisResponse(
status=True, message="Listening thread started successfully."
)
else:
# This will block the current thread
self._listen_thread()
return RedisResponse(
status=True, message="Listening started successfully (blocking)."
)
except Exception as e:
return RedisResponse(
status=False, message="Failed to start listening.", error=str(e)
)
def _listen_thread(self):
"""Thread function for listening to messages."""
self.pubsub.run_in_thread(sleep_time=0.01)
def stop_listening(self) -> RedisResponse:
"""Stop listening for messages."""
try:
self.pubsub.close()
return RedisResponse(status=True, message="Successfully stopped listening.")
except Exception as e:
return RedisResponse(
status=False, message="Failed to stop listening.", error=str(e)
)
def unsubscribe(self, channel: Optional[str] = None) -> RedisResponse:
"""Unsubscribe from a channel or all channels.
Args:
channel: The channel to unsubscribe from, or None for all channels
Returns:
RedisResponse with status and message
"""
try:
if channel:
self.pubsub.unsubscribe(channel)
message = f"Successfully unsubscribed from {channel}."
else:
self.pubsub.unsubscribe()
message = "Successfully unsubscribed from all channels."
return RedisResponse(status=True, message=message)
except Exception as e:
return RedisResponse(
status=False,
message=f"Failed to unsubscribe from {'channel' if channel else 'all channels'}.",
error=str(e),
)
def punsubscribe(self, pattern: Optional[str] = None) -> RedisResponse:
"""Unsubscribe from a pattern or all patterns.
Args:
pattern: The pattern to unsubscribe from, or None for all patterns
Returns:
RedisResponse with status and message
"""
try:
if pattern:
self.pubsub.punsubscribe(pattern)
message = f"Successfully unsubscribed from pattern {pattern}."
else:
self.pubsub.punsubscribe()
message = "Successfully unsubscribed from all patterns."
return RedisResponse(status=True, message=message)
except Exception as e:
return RedisResponse(
status=False,
message=f"Failed to unsubscribe from {'pattern' if pattern else 'all patterns'}.",
error=str(e),
)
class RedisPubSub:
"""Singleton class that provides both publisher and subscriber functionality."""
_instance = None
def __new__(cls):
if cls._instance is None:
cls._instance = super(RedisPubSub, cls).__new__(cls)
cls._instance.publisher = RedisPublisher()
cls._instance.subscriber = RedisSubscriber()
return cls._instance
# Create a singleton instance
redis_pubsub = RedisPubSub()

View File

@@ -0,0 +1,205 @@
import json
import time
import uuid
from datetime import datetime
from threading import Thread
from Controllers.Redis.Broadcast.actions import redis_pubsub
# Define the channels for our chain
CHANNEL_READER = "chain:reader"
CHANNEL_PROCESSOR = "chain:processor"
CHANNEL_WRITER = "chain:writer"
# Flag to control the demo
running = True
def generate_mock_data():
"""Generate a mock message with UUID, timestamp, and sample data."""
return {
"uuid": str(uuid.uuid4()),
"timestamp": datetime.now().isoformat(),
"stage": "red", # Initial stage is 'red'
"data": {
"value": f"Sample data {int(time.time())}",
"status": "new",
"counter": 0,
},
}
def reader_function():
"""
First function in the chain.
Generates mock data and publishes to the reader channel.
"""
print("[READER] Function started")
while running:
# Generate mock data
message = generate_mock_data()
start_time = time.time()
message["start_time"] = start_time
# Publish to reader channel
result = redis_pubsub.publisher.publish(CHANNEL_READER, message)
if result.status:
print(f"[READER] {time.time():.6f} | Published UUID: {message['uuid']}")
else:
print(f"[READER] Publish error: {result.error}")
# Wait before generating next message
time.sleep(2)
def processor_function():
"""
Second function in the chain.
Subscribes to reader channel, processes messages, and publishes to processor channel.
"""
print("[PROCESSOR] Function started")
def on_reader_message(message):
# The message structure from the subscriber has 'data' containing our actual message
# If data is a string, parse it as JSON
data = message["data"]
if isinstance(data, str):
try:
data = json.loads(data)
except json.JSONDecodeError as e:
print(f"[PROCESSOR] Error parsing message data: {e}")
return
# Check if stage is 'red' before processing
if data.get("stage") == "red":
# Process the message
data["processor_timestamp"] = datetime.now().isoformat()
data["data"]["status"] = "processed"
data["data"]["counter"] += 1
# Update stage to 'processed'
data["stage"] = "processed"
# Add some processing metadata
data["processing"] = {
"duration_ms": 150, # Mock processing time
"processor_id": "main-processor",
}
# Publish to processor channel
result = redis_pubsub.publisher.publish(CHANNEL_PROCESSOR, data)
if result.status:
print(
f"[PROCESSOR] {time.time():.6f} | Received UUID: {data['uuid']} | Published UUID: {data['uuid']}"
)
else:
print(f"[PROCESSOR] Publish error: {result.error}")
else:
print(f"[PROCESSOR] Skipped message: {data['uuid']} (stage is not 'red')")
# Subscribe to reader channel
result = redis_pubsub.subscriber.subscribe(CHANNEL_READER, on_reader_message)
if result.status:
print(f"[PROCESSOR] Subscribed to channel: {CHANNEL_READER}")
else:
print(f"[PROCESSOR] Subscribe error: {result.error}")
def writer_function():
"""
Third function in the chain.
Subscribes to processor channel and performs final processing.
"""
print("[WRITER] Function started")
def on_processor_message(message):
# The message structure from the subscriber has 'data' containing our actual message
# If data is a string, parse it as JSON
data = message["data"]
if isinstance(data, str):
try:
data = json.loads(data)
except json.JSONDecodeError as e:
print(f"[WRITER] Error parsing message data: {e}")
return
# Check if stage is 'processed' before processing
if data.get("stage") == "processed":
# Process the message
data["writer_timestamp"] = datetime.now().isoformat()
data["data"]["status"] = "completed"
data["data"]["counter"] += 1
# Update stage to 'completed'
data["stage"] = "completed"
# Add some writer metadata
data["storage"] = {"location": "main-db", "partition": "events-2025-04"}
# Calculate elapsed time if start_time is available
current_time = time.time()
elapsed_ms = ""
if "start_time" in data:
elapsed_ms = (
f" | Elapsed: {(current_time - data['start_time']) * 1000:.2f}ms"
)
# Optionally publish to writer channel for any downstream listeners
result = redis_pubsub.publisher.publish(CHANNEL_WRITER, data)
if result.status:
print(
f"[WRITER] {current_time:.6f} | Received UUID: {data['uuid']} | Published UUID: {data['uuid']}{elapsed_ms}"
)
else:
print(f"[WRITER] Publish error: {result.error}")
else:
print(
f"[WRITER] Skipped message: {data['uuid']} (stage is not 'processed')"
)
# Subscribe to processor channel
result = redis_pubsub.subscriber.subscribe(CHANNEL_PROCESSOR, on_processor_message)
if result.status:
print(f"[WRITER] Subscribed to channel: {CHANNEL_PROCESSOR}")
else:
print(f"[WRITER] Subscribe error: {result.error}")
def run_demo():
"""Run a demonstration of the simple chain of functions."""
print("=== Starting Redis Pub/Sub Chain Demonstration ===")
print("Chain: READER → PROCESSOR → WRITER")
print(f"Channels: {CHANNEL_READER}{CHANNEL_PROCESSOR}{CHANNEL_WRITER}")
print("Format: [SERVICE] TIMESTAMP | Received/Published UUID | [Elapsed time]")
# Start the Redis subscriber listening thread
redis_pubsub.subscriber.start_listening()
# Start processor and writer functions (these subscribe to channels)
processor_function()
writer_function()
# Create a thread for the reader function (this publishes messages)
reader_thread = Thread(target=reader_function, daemon=True)
reader_thread.start()
# Keep the main thread alive
try:
while True:
time.sleep(0.1)
except KeyboardInterrupt:
print("\nStopping demonstration...")
global running
running = False
redis_pubsub.subscriber.stop_listening()
if __name__ == "__main__":
run_demo()

View File

@@ -0,0 +1,85 @@
# Redis Controller
## Overview
This module provides a robust, thread-safe Redis connection handler with comprehensive concurrent operation testing. The Redis controller is designed for high-performance, resilient database connection management that can handle multiple simultaneous operations efficiently.
## Features
- Singleton pattern for efficient connection management
- Connection pooling with configurable settings
- Automatic retry capabilities for Redis operations
- Thread-safe operations with proper error handling
- Comprehensive JSON data handling
- TTL management and expiry time resolution
- Efficient batch operations using Redis pipelines
## Configuration
The Redis controller is configured with the following default settings:
- Host: 10.10.2.15
- Port: 6379
- DB: 0
- Connection pool size: 50 connections
- Health check interval: 30 seconds
- Socket timeout: 5.0 seconds
- Retry on timeout: Enabled
- Socket keepalive: Enabled
## Usage Examples
The controller provides several high-level methods for Redis operations:
- `set_json`: Store JSON data with optional expiry
- `get_json`: Retrieve JSON data with pattern matching
- `get_json_iterator`: Memory-efficient iterator for large datasets
- `delete`: Remove keys matching a pattern
- `refresh_ttl`: Update expiry time for existing keys
- `key_exists`: Check if a key exists without retrieving it
- `resolve_expires_at`: Get human-readable expiry time
## Concurrent Performance Testing
The Redis controller has been thoroughly tested for concurrent operations with impressive results:
### Test Configuration
- 10,000 concurrent threads
- Each thread performs a set, get, and delete operation
- Pipeline used for efficient batching
- Exponential backoff for connection errors
- Comprehensive error tracking and reporting
### Test Results
```
Concurrent Redis Test Results:
Total threads: 10000
Passed: 10000
Failed: 0
Operations with retries: 0
Total retry attempts: 0
Success rate: 100.00%
Performance Metrics:
Total execution time: 4.30 seconds
Operations per second: 2324.35
Average operation time: 1.92 ms
Minimum operation time: 0.43 ms
Maximum operation time: 40.45 ms
95th percentile operation time: 4.14 ms
```
## Thread Safety
The Redis controller is designed to be thread-safe with the following mechanisms:
- Connection pooling to manage concurrent connections efficiently
- Thread-local storage for operation-specific data
- Atomic operations using Redis pipelines
- Proper error handling and retry logic for connection issues
- Exponential backoff for handling connection limits
## Error Handling
The controller implements comprehensive error handling:
- Connection errors are automatically retried with exponential backoff
- Detailed error reporting with context-specific information
- Graceful degradation under high load
- Connection health monitoring and automatic reconnection
## Best Practices
- Use pipelines for batching multiple operations
- Implement proper key naming conventions
- Set appropriate TTL values for cached data
- Monitor connection pool usage in production
- Use the JSON iterator for large datasets to minimize memory usage

View File

@@ -0,0 +1,328 @@
"""
Redis key-value operations with structured data handling.
This module provides a class for managing Redis key-value operations with support for:
- Structured data storage and retrieval
- Key pattern generation for searches
- JSON serialization/deserialization
- Type-safe value handling
"""
import arrow
import json
from typing import Union, Dict, List, Optional, Any, TypeVar
from .connection import redis_cli
T = TypeVar("T", Dict[str, Any], List[Any])
class RedisKeyError(Exception):
"""Exception raised for Redis key-related errors."""
pass
class RedisValueError(Exception):
"""Exception raised for Redis value-related errors."""
pass
class RedisRow:
"""
Handles Redis key-value operations with structured data.
This class provides methods for:
- Managing compound keys with delimiters
- Converting between bytes and string formats
- JSON serialization/deserialization of values
- Pattern generation for Redis key searches
Attributes:
key: The Redis key in bytes or string format
value: The stored value (will be JSON serialized)
delimiter: Character used to separate compound key parts
expires_at: Optional expiration timestamp
"""
key: Union[str, bytes]
value: Optional[str] = None
delimiter: str = ":"
expires_at: Optional[dict] = {"seconds": 60 * 60 * 30}
expires_at_string: Optional[str]
def get_expiry_time(self) -> int | None:
"""Calculate expiry time in seconds from kwargs."""
time_multipliers = {"days": 86400, "hours": 3600, "minutes": 60, "seconds": 1}
if self.expires_at:
return sum(
int(self.expires_at.get(unit, 0)) * multiplier
for unit, multiplier in time_multipliers.items()
)
return None
def merge(self, set_values: List[Union[str, bytes]]) -> None:
"""
Merge list of values into a single delimited key.
Args:
set_values: List of values to merge into key
Example:
>>> RedisRow.merge(["users", "123", "profile"])
>>> print(RedisRow.key)
b'users:123:profile'
"""
if not set_values:
raise RedisKeyError("Cannot merge empty list of values")
merged = []
for value in set_values:
if value is None:
continue
if isinstance(value, bytes):
value = value.decode()
merged.append(str(value))
self.key = self.delimiter.join(merged).encode()
@classmethod
def regex(cls, list_keys: List[Union[Optional[str], Optional[bytes]]]) -> str:
"""
Generate Redis search pattern from list of keys.
Args:
list_keys: List of key parts, can include None for wildcards
Returns:
str: Redis key pattern with wildcards
Example:
>>> RedisRow.regex([None, "users", "active"])
'*:users:active'
"""
if not list_keys:
return ""
# Filter and convert valid keys
valid_keys = []
for key in list_keys:
if key is None or str(key) == "None":
continue
if isinstance(key, bytes):
key = key.decode()
valid_keys.append(str(key))
# Build pattern
pattern = cls.delimiter.join(valid_keys)
if not pattern:
return ""
# Add wildcard if first key was None
if list_keys[0] is None:
pattern = f"*{cls.delimiter}{pattern}"
if "*" not in pattern and any([list_key is None for list_key in list_keys]):
pattern = f"{pattern}:*"
return pattern
def parse(self) -> List[str]:
"""
Parse the key into its component parts.
Returns:
List[str]: Key parts split by delimiter
Example:
>>> RedisRow.key = b'users:123:profile'
>>> RedisRow.parse()
['users', '123', 'profile']
"""
if not self.key:
return []
key_str = self.key.decode() if isinstance(self.key, bytes) else self.key
return key_str.split(self.delimiter)
def feed(self, value: Union[bytes, Dict, List, str]) -> None:
"""
Convert and store value in JSON format.
Args:
value: Value to store (bytes, dict, or list)
Raises:
RedisValueError: If value type is not supported
Example:
>>> RedisRow.feed({"name": "John", "age": 30})
>>> print(RedisRow.value)
'{"name": "John", "age": 30}'
"""
try:
if isinstance(value, (dict, list)):
self.value = json.dumps(value)
elif isinstance(value, bytes):
self.value = json.dumps(json.loads(value.decode()))
elif isinstance(value, str):
self.value = value
else:
raise RedisValueError(f"Unsupported value type: {type(value)}")
except json.JSONDecodeError as e:
raise RedisValueError(f"Invalid JSON format: {str(e)}")
def modify(self, add_dict: Dict) -> None:
"""
Modify existing data by merging with new dictionary.
Args:
add_dict: Dictionary to merge with existing data
Example:
>>> RedisRow.feed({"name": "John"})
>>> RedisRow.modify({"age": 30})
>>> print(RedisRow.data)
{"name": "John", "age": 30}
"""
if not isinstance(add_dict, dict):
raise RedisValueError("modify() requires a dictionary argument")
current_data = self.row if self.row else {}
if not isinstance(current_data, dict):
raise RedisValueError("Cannot modify non-dictionary data")
current_data = {
**current_data,
**add_dict,
}
self.feed(current_data)
self.save()
def save(self):
"""
Save the data to Redis with optional expiration.
Raises:
RedisKeyError: If key is not set
RedisValueError: If value is not set
"""
if not self.key:
raise RedisKeyError("Cannot save data without a key")
if not self.value:
raise RedisValueError("Cannot save empty data")
if self.expires_at:
redis_cli.setex(
name=self.redis_key, time=self.get_expiry_time(), value=self.value
)
self.expires_at_string = str(
arrow.now()
.shift(seconds=self.get_expiry_time())
.format("YYYY-MM-DD HH:mm:ss")
)
return self.value
redis_cli.set(name=self.redis_key, value=self.value)
self.expires_at = None
self.expires_at_string = None
return self.value
def remove(self, key: str) -> None:
"""
Remove a key from the stored dictionary.
Args:
key: Key to remove from stored dictionary
Raises:
KeyError: If key doesn't exist
RedisValueError: If stored value is not a dictionary
"""
current_data = self.row
if not isinstance(current_data, dict):
raise RedisValueError("Cannot remove key from non-dictionary data")
try:
current_data.pop(key)
self.feed(current_data)
self.save()
except KeyError:
raise KeyError(f"Key '{key}' not found in stored data")
def delete(self) -> None:
"""Delete the key from Redis."""
try:
redis_cli.delete(self.redis_key)
except Exception as e:
raise RedisKeyError(f"Failed to delete key: {str(e)}")
@property
def keys(self) -> str:
"""
Get key as string.
Returns:
str: Key in string format
"""
return self.key.decode() if isinstance(self.key, bytes) else self.key
def set_key(self, key: Union[str, bytes]) -> None:
"""
Set key ensuring bytes format.
Args:
key: Key in string or bytes format
Raises:
RedisKeyError: If key is empty or invalid
"""
if not key:
raise RedisKeyError("Cannot set empty key")
# Convert to string for validation
key_str = key.decode() if isinstance(key, bytes) else str(key)
# Validate key length (Redis has a 512MB limit for keys)
if len(key_str) > 512 * 1024 * 1024:
raise RedisKeyError("Key exceeds maximum length of 512MB")
# Validate key format (basic check for invalid characters)
if any(c in key_str for c in ["\n", "\r", "\t", "\0"]):
raise RedisKeyError("Key contains invalid characters")
self.key = key if isinstance(key, bytes) else str(key).encode()
@property
def redis_key(self) -> bytes:
"""
Get key in bytes format for Redis operations.
Returns:
bytes: Key in bytes format
"""
return self.key if isinstance(self.key, bytes) else str(self.key).encode()
@property
def row(self) -> Union[Dict, List]:
"""
Get stored value as Python object.
Returns:
Union[Dict, List]: Deserialized JSON data
"""
try:
return json.loads(self.value)
except json.JSONDecodeError as e:
raise RedisValueError(f"Invalid JSON format in stored value: {str(e)}")
@property
def as_dict(self) -> Dict[str, Any]:
"""
Get row data as dictionary.
Returns:
Dict[str, Any]: Dictionary with keys and value
"""
return {
"keys": self.keys,
"value": self.row,
}

View File

@@ -0,0 +1,25 @@
from pydantic_settings import BaseSettings, SettingsConfigDict
class Configs(BaseSettings):
"""
Redis configuration settings.
"""
HOST: str = "10.10.2.15"
PASSWORD: str = "your_strong_password_here"
PORT: int = 6379
DB: int = 0
def as_dict(self):
return dict(
host=self.HOST,
password=self.PASSWORD,
port=int(self.PORT),
db=self.DB,
)
model_config = SettingsConfigDict(env_prefix="REDIS_")
redis_configs = Configs() # singleton instance of the REDIS configuration settings

View File

@@ -0,0 +1,215 @@
import time
from typing import Dict, Any
from redis import Redis, ConnectionError, TimeoutError, ConnectionPool
from .config import redis_configs
class RedisConn:
"""
Redis connection manager with connection pooling, retry logic,
and health check capabilities.
"""
CONNECTION_RETRIES = 3 # Number of connection retries before failing
RETRY_DELAY = 0.5 # Delay between retries in seconds
DEFAULT_TIMEOUT = 5.0 # Default connection timeout in seconds
def __init__(
self,
max_retries: int = CONNECTION_RETRIES,
):
"""
Initialize Redis connection with configuration.
Args:
max_retries: Maximum number of connection attempts.
"""
self.max_retries = max_retries
self.config = redis_configs.as_dict()
self._redis = None
self._pool = None
# Add default parameters if not provided
if "socket_timeout" not in self.config:
self.config["socket_timeout"] = self.DEFAULT_TIMEOUT
if "socket_connect_timeout" not in self.config:
self.config["socket_connect_timeout"] = self.DEFAULT_TIMEOUT
if "decode_responses" not in self.config:
self.config["decode_responses"] = True
# Add connection pooling settings if not provided
if "max_connections" not in self.config:
self.config["max_connections"] = 50 # Increased for better concurrency
# Add connection timeout settings
if "health_check_interval" not in self.config:
self.config["health_check_interval"] = 30 # Health check every 30 seconds
# Add retry settings for operations
if "retry_on_timeout" not in self.config:
self.config["retry_on_timeout"] = True
# Add connection pool settings for better performance
if "socket_keepalive" not in self.config:
self.config["socket_keepalive"] = True
# Initialize the connection with retry logic
self._connect_with_retry()
def __del__(self):
"""Cleanup Redis connection and pool on object destruction."""
self.close()
def close(self) -> None:
"""Close Redis connection and connection pool."""
try:
if self._redis:
self._redis.close()
self._redis = None
if self._pool:
self._pool.disconnect()
self._pool = None
except Exception as e:
print(f"Error closing Redis connection: {str(e)}")
def _connect_with_retry(self) -> None:
"""
Attempt to establish a Redis connection with retry logic.
Raises:
Exception: If all connection attempts fail.
"""
for attempt in range(1, self.max_retries + 1):
try:
if self._pool is None:
self._pool = ConnectionPool(**self.config)
self._redis = Redis(connection_pool=self._pool)
if self.check_connection():
return
except (ConnectionError, TimeoutError) as e:
if attempt < self.max_retries:
time.sleep(self.RETRY_DELAY)
else:
raise Exception(
f"Redis connection error after {self.max_retries} attempts: {str(e)}"
)
except Exception as e:
raise
def check_connection(self) -> bool:
"""
Check if the Redis connection is alive with a PING command.
Returns:
bool: True if connection is healthy, False otherwise.
"""
try:
return self._redis.ping()
except Exception as e:
err = e
return False
def set_connection(self, **kwargs) -> Redis:
"""
Recreate Redis connection with new parameters.
Args:
host: Redis server hostname or IP
password: Redis authentication password
port: Redis server port
db: Redis database number
**kwargs: Additional Redis connection parameters
Returns:
Redis: The new Redis connection object
"""
try:
# Update configuration
self.config = {
"host": redis_configs.HOST,
"password": redis_configs.PASSWORD,
"port": redis_configs.PORT,
"db": redis_configs.PORT,
"socket_timeout": kwargs.get("socket_timeout", self.DEFAULT_TIMEOUT),
"socket_connect_timeout": kwargs.get(
"socket_connect_timeout", self.DEFAULT_TIMEOUT
),
"decode_responses": kwargs.get("decode_responses", True),
"max_connections": kwargs.get("max_connections", 50),
"health_check_interval": kwargs.get("health_check_interval", 30),
"retry_on_timeout": kwargs.get("retry_on_timeout", True),
"socket_keepalive": kwargs.get("socket_keepalive", True),
}
# Add any additional parameters
for key, value in kwargs.items():
if key not in self.config:
self.config[key] = value
# Create new connection
self._redis = Redis(**self.config)
if not self.check_connection():
raise ConnectionError(
"Failed to establish connection with new parameters"
)
return self._redis
except Exception as e:
raise
def get_connection_info(self) -> Dict[str, Any]:
"""
Get current connection configuration details.
Returns:
Dict: Current connection configuration
"""
# Create a copy without password for security
info = self.config.copy()
if "password" in info:
info["password"] = "********" if info["password"] else None
return info
def get_stats(self) -> Dict[str, Any]:
"""
Get Redis server statistics.
Returns:
Dict: Redis server info
"""
try:
return self._redis.info()
except Exception as e:
return {"error": str(e)}
@property
def redis(self) -> Redis:
"""
Property to access the Redis client.
Returns:
Redis: The Redis client instance
Raises:
Exception: If Redis connection is not available
"""
if not self._redis:
raise Exception("Redis client is not initialized")
# Check connection health and reconnect if necessary
if not self.check_connection():
self._connect_with_retry()
return self._redis
# Create singleton instance with error handling
try:
redis_conn = RedisConn()
redis_cli = redis_conn.redis
except Exception as t:
# Optionally set a dummy/mock Redis client for testing or fallback behavior
# redis_cli = MockRedis() # If you have a mock implementation
# Or raise the exception to fail fast
raise

View File

@@ -0,0 +1,340 @@
import arrow
from typing import Optional, List, Dict, Union, Iterator
from .response import RedisResponse
from .connection import redis_cli
from .base import RedisRow
class MainConfig:
DATETIME_FORMAT: str = "YYYY-MM-DD HH:mm:ss"
class RedisActions:
"""Class for handling Redis operations with JSON data."""
@classmethod
def get_expiry_time(cls, expiry_kwargs: Dict[str, int]) -> int:
"""
Calculate expiry time in seconds from kwargs.
Args:
expiry_kwargs: Dictionary with time units as keys (days, hours, minutes, seconds)
and their respective values.
Returns:
Total expiry time in seconds.
"""
time_multipliers = {"days": 86400, "hours": 3600, "minutes": 60, "seconds": 1}
return sum(
int(expiry_kwargs.get(unit, 0)) * multiplier
for unit, multiplier in time_multipliers.items()
)
@classmethod
def set_expiry_time(cls, expiry_seconds: int) -> Dict[str, int]:
"""
Convert total seconds back into a dictionary of time units.
Args:
expiry_seconds: Total expiry time in seconds.
Returns:
Dictionary with time units and their values.
"""
time_multipliers = {"days": 86400, "hours": 3600, "minutes": 60, "seconds": 1}
result = {}
remaining_seconds = expiry_seconds
if expiry_seconds < 0:
return {}
for unit, multiplier in time_multipliers.items():
if remaining_seconds >= multiplier:
result[unit], remaining_seconds = divmod(remaining_seconds, multiplier)
return result
@classmethod
def resolve_expires_at(cls, redis_row: RedisRow) -> str:
"""
Resolve expiry time for Redis key.
Args:
redis_row: RedisRow object containing the redis_key.
Returns:
Formatted expiry time string or message indicating no expiry.
"""
expiry_time = redis_cli.ttl(redis_row.redis_key)
if expiry_time == -1:
return "Key has no expiry time."
if expiry_time == -2:
return "Key does not exist."
return arrow.now().shift(seconds=expiry_time).format(MainConfig.DATETIME_FORMAT)
@classmethod
def key_exists(cls, key: Union[str, bytes]) -> bool:
"""
Check if a key exists in Redis without retrieving its value.
Args:
key: Redis key to check.
Returns:
Boolean indicating if key exists.
"""
return bool(redis_cli.exists(key))
@classmethod
def refresh_ttl(cls, key: Union[str, bytes], expires: Dict[str, int]) -> RedisResponse:
"""
Refresh TTL for an existing key.
Args:
key: Redis key to refresh TTL.
expires: Dictionary with time units to set new expiry.
Returns:
RedisResponse with operation result.
"""
try:
if not cls.key_exists(key):
return RedisResponse(
status=False,
message="Cannot refresh TTL: Key does not exist.",
)
expiry_time = cls.get_expiry_time(expiry_kwargs=expires)
redis_cli.expire(name=key, time=expiry_time)
expires_at_string = (
arrow.now()
.shift(seconds=expiry_time)
.format(MainConfig.DATETIME_FORMAT)
)
return RedisResponse(
status=True,
message="TTL refreshed successfully.",
data={"key": key, "expires_at": expires_at_string},
)
except Exception as e:
return RedisResponse(
status=False,
message="Failed to refresh TTL.",
error=str(e),
)
@classmethod
def delete_key(cls, key: Union[Optional[str], Optional[bytes]]) -> RedisResponse:
"""
Delete a specific key from Redis.
Args:
key: Redis key to delete.
Returns:
RedisResponse with operation result.
"""
try:
deleted_count = redis_cli.delete(key)
if deleted_count > 0:
return RedisResponse(
status=True,
message="Key deleted successfully.",
data={"deleted_count": deleted_count},
)
return RedisResponse(
status=False,
message="Key not found or already deleted.",
data={"deleted_count": 0},
)
except Exception as e:
return RedisResponse(
status=False,
message="Failed to delete key.",
error=str(e),
)
@classmethod
def delete(cls, list_keys: List[Union[Optional[str], Optional[bytes]]]) -> RedisResponse:
"""
Delete multiple keys matching a pattern.
Args:
list_keys: List of key components to form pattern for deletion.
Returns:
RedisResponse with operation result.
"""
try:
regex = RedisRow().regex(list_keys=list_keys)
json_get = redis_cli.scan_iter(match=regex)
deleted_keys, deleted_count = [], 0
# Use pipeline for batch deletion
with redis_cli.pipeline() as pipe:
for row in json_get:
pipe.delete(row)
deleted_keys.append(row)
results = pipe.execute()
deleted_count = sum(results)
return RedisResponse(
status=True,
message="Keys deleted successfully.",
data={"deleted_count": deleted_count, "deleted_keys": deleted_keys},
)
except Exception as e:
return RedisResponse(
status=False,
message="Failed to delete keys.",
error=str(e),
)
@classmethod
def set_json(cls, list_keys: List[Union[str, bytes]], value: Optional[Union[Dict, List]], expires: Optional[Dict[str, int]] = None) -> RedisResponse:
"""
Set JSON value in Redis with optional expiry.
Args:
list_keys: List of key components to form Redis key.
value: JSON-serializable data to store.
expires: Optional dictionary with time units for expiry.
Returns:
RedisResponse with operation result.
"""
redis_row = RedisRow()
redis_row.merge(set_values=list_keys)
redis_row.feed(value)
redis_row.expires_at_string = None
redis_row.expires_at = None
try:
if expires:
redis_row.expires_at = expires
expiry_time = cls.get_expiry_time(expiry_kwargs=expires)
redis_cli.setex(
name=redis_row.redis_key,
time=expiry_time,
value=redis_row.value,
)
redis_row.expires_at_string = str(
arrow.now()
.shift(seconds=expiry_time)
.format(MainConfig.DATETIME_FORMAT)
)
else:
redis_cli.set(name=redis_row.redis_key, value=redis_row.value)
return RedisResponse(
status=True,
message="Value set successfully.",
data=redis_row,
)
except Exception as e:
return RedisResponse(
status=False,
message="Failed to set value.",
error=str(e),
)
@classmethod
def get_json(cls, list_keys: List[Union[Optional[str], Optional[bytes]]], limit: Optional[int] = None) -> RedisResponse:
"""
Get JSON values from Redis using pattern matching.
Args:
list_keys: List of key components to form pattern for retrieval.
limit: Optional limit on number of results to return.
Returns:
RedisResponse with operation result.
"""
try:
list_of_rows, count = [], 0
regex = RedisRow.regex(list_keys=list_keys)
json_get = redis_cli.scan_iter(match=regex)
for row in json_get:
if limit is not None and count >= limit:
break
redis_row = RedisRow()
redis_row.set_key(key=row)
# Use pipeline for batch retrieval
with redis_cli.pipeline() as pipe:
pipe.get(row)
pipe.ttl(row)
redis_value, redis_value_expire = pipe.execute()
redis_row.expires_at = cls.set_expiry_time(
expiry_seconds=int(redis_value_expire)
)
redis_row.expires_at_string = cls.resolve_expires_at(
redis_row=redis_row
)
redis_row.feed(redis_value)
list_of_rows.append(redis_row)
count += 1
if list_of_rows:
return RedisResponse(
status=True,
message="Values retrieved successfully.",
data=list_of_rows,
)
return RedisResponse(
status=False,
message="No matching keys found.",
data=list_of_rows,
)
except Exception as e:
return RedisResponse(
status=False,
message="Failed to retrieve values.",
error=str(e),
)
@classmethod
def get_json_iterator(cls, list_keys: List[Union[Optional[str], Optional[bytes]]]) -> Iterator[RedisRow]:
"""
Get JSON values from Redis as an iterator for memory-efficient processing of large datasets.
Args:
list_keys: List of key components to form pattern for retrieval.
Returns:
Iterator yielding RedisRow objects.
Raises:
RedisValueError: If there's an error processing a row
"""
regex = RedisRow.regex(list_keys=list_keys)
json_get = redis_cli.scan_iter(match=regex)
for row in json_get:
try:
redis_row = RedisRow()
redis_row.set_key(key=row)
# Use pipeline for batch retrieval
with redis_cli.pipeline() as pipe:
pipe.get(row)
pipe.ttl(row)
redis_value, redis_value_expire = pipe.execute()
redis_row.expires_at = cls.set_expiry_time(
expiry_seconds=int(redis_value_expire)
)
redis_row.expires_at_string = cls.resolve_expires_at(
redis_row=redis_row
)
redis_row.feed(redis_value)
yield redis_row
except Exception as e:
# Log the error and continue with next row
print(f"Error processing row {row}: {str(e)}")
continue

View File

@@ -0,0 +1,281 @@
import threading
import time
import random
import uuid
import concurrent.futures
from .database import RedisActions
def example_set_json() -> None:
"""Example of setting JSON data in Redis with and without expiry."""
# Example 1: Set JSON without expiry
data = {"name": "John", "age": 30, "city": "New York"}
keys = ["user", "profile", "123"]
result = RedisActions.set_json(list_keys=keys, value=data)
print("Set JSON without expiry:", result.as_dict())
# Example 2: Set JSON with expiry
expiry = {"hours": 1, "minutes": 30}
result = RedisActions.set_json(list_keys=keys, value=data, expires=expiry)
print("Set JSON with expiry:", result.as_dict())
def example_get_json() -> None:
"""Example of retrieving JSON data from Redis."""
# Example 1: Get all matching keys
keys = ["user", "profile", "*"]
result = RedisActions.get_json(list_keys=keys)
print("Get all matching JSON:", result.as_dict())
# Example 2: Get with limit
result = RedisActions.get_json(list_keys=keys, limit=5)
print("Get JSON with limit:", result.as_dict())
def example_get_json_iterator() -> None:
"""Example of using the JSON iterator for large datasets."""
keys = ["user", "profile", "*"]
for row in RedisActions.get_json_iterator(list_keys=keys):
print(
"Iterating over JSON row:",
row.as_dict if isinstance(row.as_dict, dict) else row.as_dict,
)
def example_delete_key() -> None:
"""Example of deleting a specific key."""
key = "user:profile:123"
result = RedisActions.delete_key(key)
print("Delete specific key:", result)
def example_delete() -> None:
"""Example of deleting multiple keys matching a pattern."""
keys = ["user", "profile", "*"]
result = RedisActions.delete(list_keys=keys)
print("Delete multiple keys:", result)
def example_refresh_ttl() -> None:
"""Example of refreshing TTL for a key."""
key = "user:profile:123"
new_expiry = {"hours": 2, "minutes": 0}
result = RedisActions.refresh_ttl(key=key, expires=new_expiry)
print("Refresh TTL:", result.as_dict())
def example_key_exists() -> None:
"""Example of checking if a key exists."""
key = "user:profile:123"
exists = RedisActions.key_exists(key)
print(f"Key {key} exists:", exists)
def example_resolve_expires_at() -> None:
"""Example of resolving expiry time for a key."""
from Controllers.Redis.base import RedisRow
redis_row = RedisRow()
redis_row.set_key("user:profile:123")
print(redis_row.keys)
expires_at = RedisActions.resolve_expires_at(redis_row)
print("Resolve expires at:", expires_at)
def run_all_examples() -> None:
"""Run all example functions to demonstrate RedisActions functionality."""
print("\n=== Redis Actions Examples ===\n")
print("1. Setting JSON data:")
example_set_json()
print("\n2. Getting JSON data:")
example_get_json()
print("\n3. Using JSON iterator:")
example_get_json_iterator()
# print("\n4. Deleting specific key:")
# example_delete_key()
#
# print("\n5. Deleting multiple keys:")
# example_delete()
print("\n6. Refreshing TTL:")
example_refresh_ttl()
print("\n7. Checking key existence:")
example_key_exists()
print("\n8. Resolving expiry time:")
example_resolve_expires_at()
def run_concurrent_test(num_threads=100):
"""Run a comprehensive concurrent test with multiple threads to verify Redis connection handling."""
print(
f"\nStarting comprehensive Redis concurrent test with {num_threads} threads..."
)
# Results tracking with detailed metrics
results = {
"passed": 0,
"failed": 0,
"retried": 0,
"errors": [],
"operation_times": [],
"retry_count": 0,
"max_retries": 3,
"retry_delay": 0.1,
}
results_lock = threading.Lock()
def worker(thread_id):
# Track operation timing
start_time = time.time()
retry_count = 0
success = False
error_message = None
while retry_count <= results["max_retries"] and not success:
try:
# Generate unique key for this thread
unique_id = str(uuid.uuid4())[:8]
full_key = f"test:concurrent:{thread_id}:{unique_id}"
# Simple string operations instead of JSON
test_value = f"test-value-{thread_id}-{time.time()}"
# Set data in Redis with pipeline for efficiency
from Controllers.Redis.database import redis_cli
# Use pipeline to reduce network overhead
with redis_cli.pipeline() as pipe:
pipe.set(full_key, test_value)
pipe.get(full_key)
pipe.delete(full_key)
results_list = pipe.execute()
# Check results
set_ok = results_list[0]
retrieved_value = results_list[1]
if isinstance(retrieved_value, bytes):
retrieved_value = retrieved_value.decode("utf-8")
# Verify data
success = set_ok and retrieved_value == test_value
if success:
break
else:
error_message = f"Data verification failed: set_ok={set_ok}, value_match={retrieved_value == test_value}"
retry_count += 1
with results_lock:
results["retry_count"] += 1
time.sleep(
results["retry_delay"] * (2**retry_count)
) # Exponential backoff
except Exception as e:
error_message = str(e)
retry_count += 1
with results_lock:
results["retry_count"] += 1
# Check if it's a connection error and retry
if "Too many connections" in str(e) or "Connection" in str(e):
# Exponential backoff for connection issues
backoff_time = results["retry_delay"] * (2**retry_count)
time.sleep(backoff_time)
else:
# For other errors, use a smaller delay
time.sleep(results["retry_delay"])
# Record operation time
operation_time = time.time() - start_time
# Update results
with results_lock:
if success:
results["passed"] += 1
results["operation_times"].append(operation_time)
if retry_count > 0:
results["retried"] += 1
else:
results["failed"] += 1
if error_message:
results["errors"].append(
f"Thread {thread_id} failed after {retry_count} retries: {error_message}"
)
else:
results["errors"].append(
f"Thread {thread_id} failed after {retry_count} retries with unknown error"
)
# Create and start threads using a thread pool
start_time = time.time()
with concurrent.futures.ThreadPoolExecutor(max_workers=num_threads) as executor:
futures = [executor.submit(worker, i) for i in range(num_threads)]
concurrent.futures.wait(futures)
# Calculate execution time and performance metrics
execution_time = time.time() - start_time
ops_per_second = num_threads / execution_time if execution_time > 0 else 0
# Calculate additional metrics if we have successful operations
avg_op_time = 0
min_op_time = 0
max_op_time = 0
p95_op_time = 0
if results["operation_times"]:
avg_op_time = sum(results["operation_times"]) / len(results["operation_times"])
min_op_time = min(results["operation_times"])
max_op_time = max(results["operation_times"])
# Calculate 95th percentile
sorted_times = sorted(results["operation_times"])
p95_index = int(len(sorted_times) * 0.95)
p95_op_time = (
sorted_times[p95_index]
if p95_index < len(sorted_times)
else sorted_times[-1]
)
# Print detailed results
print("\nConcurrent Redis Test Results:")
print(f"Total threads: {num_threads}")
print(f"Passed: {results['passed']}")
print(f"Failed: {results['failed']}")
print(f"Operations with retries: {results['retried']}")
print(f"Total retry attempts: {results['retry_count']}")
print(f"Success rate: {(results['passed'] / num_threads) * 100:.2f}%")
print("\nPerformance Metrics:")
print(f"Total execution time: {execution_time:.2f} seconds")
print(f"Operations per second: {ops_per_second:.2f}")
if results["operation_times"]:
print(f"Average operation time: {avg_op_time * 1000:.2f} ms")
print(f"Minimum operation time: {min_op_time * 1000:.2f} ms")
print(f"Maximum operation time: {max_op_time * 1000:.2f} ms")
print(f"95th percentile operation time: {p95_op_time * 1000:.2f} ms")
# Print errors (limited to 10 for readability)
if results["errors"]:
print("\nErrors:")
for i, error in enumerate(results["errors"][:10]):
print(f"- {error}")
if len(results["errors"]) > 10:
print(f"- ... and {len(results['errors']) - 10} more errors")
# Return results for potential further analysis
return results
if __name__ == "__main__":
# Run basic examples
run_all_examples()
# Run enhanced concurrent test
run_concurrent_test(10000)

View File

@@ -0,0 +1,194 @@
from typing import Union, Dict, Optional, Any
from .base import RedisRow
class RedisResponse:
"""
Base class for Redis response handling.
Provides a standardized way to return and process Redis operation results,
with tools to convert between different data representations.
"""
def __init__(self, status: bool, message: str, data: Any = None, error: Optional[str] = None):
"""
Initialize a Redis response.
Args:
status: Operation success status
message: Human-readable message about the operation
data: Response data (can be None, RedisRow, list, or dict)
error: Optional error message if operation failed
"""
self.status = status
self.message = message
self.data = data
self.error = error
# Determine the data type
if isinstance(data, dict):
self.data_type = "dict"
elif isinstance(data, list):
self.data_type = "list"
elif isinstance(data, RedisRow):
self.data_type = "row"
elif isinstance(data, (int, float, str, bool)):
self.data_type = "primitive"
else:
self.data_type = None
def as_dict(self) -> Dict:
"""
Convert the response to a dictionary format suitable for serialization.
Returns:
Dictionary representation of the response
"""
# Base response fields
main_dict = {
"status": self.status,
"message": self.message,
"count": self.count,
"dataType": self.data_type,
}
# Add error if present
if self.error:
main_dict["error"] = self.error
data = self.all
# Process single RedisRow
if isinstance(data, RedisRow):
result = {**main_dict}
if hasattr(data, "keys") and hasattr(data, "row"):
if not isinstance(data.keys, str):
raise ValueError("RedisRow keys must be string type")
result[data.keys] = data.row
return result
# Process list of RedisRows
elif isinstance(data, list):
result = {**main_dict}
# Handle list of RedisRow objects
rows_dict = {}
for row in data:
if (
isinstance(row, RedisRow)
and hasattr(row, "keys")
and hasattr(row, "row")
):
if not isinstance(row.keys, str):
raise ValueError("RedisRow keys must be string type")
rows_dict[row.keys] = row.row
if rows_dict:
result["data"] = rows_dict
elif data: # If it's just a regular list with items
result["data"] = data
return result
# Process dictionary
elif isinstance(data, dict):
return {**main_dict, "data": data}
return main_dict
@property
def all(self) -> Any:
"""
Get all data from the response.
Returns:
All data or empty list if None
"""
return self.data if self.data is not None else []
@property
def count(self) -> int:
"""
Count the number of items in the response data.
Returns:
Number of items (0 if no data)
"""
data = self.all
if isinstance(data, list):
return len(data)
elif isinstance(data, (RedisRow, dict)):
return 1
return 0
@property
def first(self) -> Union[Dict, None]:
"""
Get the first item from the response data.
Returns:
First item as a dictionary or None if no data
"""
if not self.data:
return None
if isinstance(self.data, list) and self.data:
item = self.data[0]
if isinstance(item, RedisRow) and hasattr(item, "row"):
return item.row
return item
elif isinstance(self.data, RedisRow) and hasattr(self.data, "row"):
return self.data.row
elif isinstance(self.data, dict):
return self.data
return None
def is_successful(self) -> bool:
"""
Check if the operation was successful.
Returns:
Boolean indicating success status
"""
return self.status
def to_api_response(self) -> Dict:
"""
Format the response for API consumption.
Returns:
API-friendly response dictionary
"""
try:
response = {
"success": self.status,
"message": self.message,
}
if self.error:
response["error"] = self.error
if self.data is not None:
if self.data_type == "row" and hasattr(self.data, "to_dict"):
response["data"] = self.data.to_dict()
elif self.data_type == "list":
try:
if all(hasattr(item, "to_dict") for item in self.data):
response["data"] = [item.to_dict() for item in self.data]
else:
response["data"] = self.data
except Exception as e:
response["error"] = f"Error converting list items: {str(e)}"
else:
response["data"] = self.data
response["count"] = self.count
return response
except Exception as e:
return {
"success": False,
"message": "Error formatting response",
"error": str(e),
}