Skip to content

📝 Add docstrings to feature/coderabbit-auto-improvements #18

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
coderabbitai wants to merge 1 commit into from
Closed

📝 Add docstrings to feature/coderabbit-auto-improvements #18

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 14 additions & 3 deletions llm/continuous_learning_system.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -65,6 +65,17 @@ class ContinuousLearningLLM:
"""

def __init__(self, model_name: str = "continuous_learner"):
"""
Initialize a ContinuousLearningLLM instance for managing continuous, quantum-accelerated LLM training.

This constructor sets up the model name, connectors for classical and quantum resources, training state variables, model and data storage directories, and performance tracking structures.

Args:
model_name (str, optional): The name of the model instance. Defaults to "continuous_learner".

Example:
learner = ContinuousLearningLLM(model_name="my_incremental_llm")
"""
self.model_name = model_name
self.llm_connector = LLMConnector()
self.quantum_connector = DWaveQuantumConnector()
Expand Down Expand Up @@ -93,13 +104,13 @@ def __init__(self, model_name: str = "continuous_learner"):

async def initialize(self, config: Dict[str, Any] = None) -> bool:
"""
Initializes the continuous learning system by connecting to LLM and quantum resources, loading or creating the initial model, and starting the background training loop.
Initializes the continuous learning system by connecting to LLM and quantum computing resources, loading or creating the initial model, and starting the background training loop.

Args:
config (Optional[Dict[str, Any]]): Configuration dictionary containing connection parameters for LLM and quantum resources. If not provided, defaults are used.
config (Optional[Dict[str, Any]]): Optional configuration dictionary with connection parameters for LLM and quantum resources. If omitted, default settings are used.

Returns:
bool: True if initialization succeeds, False otherwise.
bool: True if initialization is successful; False otherwise.

Example:
success = await continuous_learner.initialize({
Expand Down
20 changes: 19 additions & 1 deletion run_comprehensive_tests.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,25 @@
import time

def run_tests():
"""Run comprehensive test suite"""
"""
Runs the comprehensive test suite for utility helper functions, including both standard and performance/stress tests.

This function executes two categories of tests using `pytest` via subprocess calls:
1. Standard tests (excluding those marked as slow).
2. Performance and stress tests (marked as slow).

Test results are printed to the console, including detailed output if any tests fail. The function returns an exit code indicating overall success or failure.

Returns:
int: Returns 0 if all tests pass, or 1 if any test fails.

Example:
status = run_tests()
if status == 0:
print("All tests succeeded.")
else:
print("Some tests failed.")
"""
print("Running comprehensive tests for utils/helpers.py...")
print("=" * 60)

Expand Down
4 changes: 2 additions & 2 deletions scripts/auto-improve.sh
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@ WAIT_DURATION=${CODERABBIT_WAIT_DURATION:-30}
MAX_WAIT_TIME=${CODERABBIT_MAX_WAIT:-300}
POLL_INTERVAL=${CODERABBIT_POLL_INTERVAL:-10}

# check_for_new_commits determines if the remote branch has new commits compared to the local HEAD.
# check_for_new_commits checks if the remote branch has commits not present in the local HEAD and returns success if new commits are detected.
check_for_new_commits() {
local initial_commit=$(git rev-parse HEAD)
git fetch origin >/dev/null 2>&1
Expand All @@ -19,7 +19,7 @@ check_for_new_commits() {
fi
}

# wait_for_coderabbit polls the remote repository to detect new commits from CodeRabbit, waiting up to a maximum duration before proceeding.
# wait_for_coderabbit waits for new commits from CodeRabbit by polling the remote repository until a commit is detected or a maximum wait time is reached.
wait_for_coderabbit() {
local start_time=$(date +%s)
local initial_commit=$(git rev-parse HEAD)
Expand Down
82 changes: 43 additions & 39 deletions utils/helpers.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,13 +11,13 @@

def safe_json_parse(json_string: str) -> Optional[Dict[str, Any]]:
"""
Parses a JSON string into a dictionary, returning None if parsing fails.
Safely parses a JSON string into a dictionary, returning None if parsing fails.

Args:
json_string (str): The JSON string to parse.
json_string (str): JSON-formatted string to parse.

Returns:
Optional[Dict[str, Any]]: The parsed dictionary if successful, or None if the input is invalid or cannot be parsed.
Optional[Dict[str, Any]]: Parsed dictionary if successful; None if the input is invalid or cannot be parsed.

Example:
>>> safe_json_parse('{"key": "value"}')
Expand All @@ -33,11 +33,11 @@ def safe_json_parse(json_string: str) -> Optional[Dict[str, Any]]:

def safe_json_dumps(data: Any, indent: int = 2) -> str:
"""
Serialize data to a JSON-formatted string, returning an empty string if serialization fails.
Serializes data into a JSON-formatted string with indentation, returning an empty string if serialization fails.

Args:
data (Any): The data to serialize to JSON.
indent (int, optional): Number of spaces for indentation in the output. Defaults to 2.
Parameters:
data (Any): The object to serialize to JSON.
indent (int): Number of spaces to use for indentation in the output. Defaults to 2.

Returns:
str: The JSON-formatted string, or an empty string if serialization fails.
Expand All @@ -54,13 +54,15 @@ def safe_json_dumps(data: Any, indent: int = 2) -> str:

def generate_hash(data: Union[str, bytes]) -> str:
"""
Generates a SHA256 hash for the given input data.
Generate a SHA256 hash of the input string or bytes.

If the input is a string, it is encoded as UTF-8 before hashing.

Args:
data (str or bytes): The input to hash. If a string is provided, it is encoded as UTF-8 before hashing.
data (str or bytes): Input data to hash.

Returns:
str: The hexadecimal representation of the SHA256 hash.
str: Hexadecimal SHA256 hash of the input.

Example:
>>> generate_hash("hello")
Expand All @@ -73,17 +75,17 @@ def generate_hash(data: Union[str, bytes]) -> str:

def retry_with_backoff(func, max_retries: int = 3, base_delay: float = 1.0):
"""
Executes a function with retries using exponential backoff.
Execute a no-argument function with retries using exponential backoff.

Retries the provided function up to `max_retries` times, doubling the delay after each failure starting from `base_delay` seconds. If all attempts fail, the last exception is raised.
Retries the given function up to `max_retries` times, doubling the delay after each failure starting from `base_delay` seconds. If all attempts fail, the last exception is raised.

Parameters:
func (Callable[[], Any]): The function to execute. Should take no arguments.
max_retries (int, optional): Maximum number of attempts. Defaults to 3.
base_delay (float, optional): Initial delay in seconds before retrying. Defaults to 1.0.
func: A callable that takes no arguments and returns any value.
max_retries: The maximum number of attempts to execute the function. Defaults to 3.
base_delay: The initial delay in seconds before retrying after a failure. Defaults to 1.0.

Returns:
Any: The result returned by `func` if successful.
The result returned by `func` if it succeeds within the allowed retries.

Raises:
Exception: The last exception raised by `func` if all retries fail.
Expand Down Expand Up @@ -111,12 +113,12 @@ def flatten_dict(data: Dict[str, Any], prefix: str = "") -> Dict[str, Any]:
"""
Recursively flattens a nested dictionary into a single-level dictionary with dot-separated keys.

Parameters:
Args:
data (Dict[str, Any]): The dictionary to flatten.
prefix (str, optional): A prefix to prepend to each key. Defaults to "".
prefix (str, optional): Prefix to prepend to each key in the flattened dictionary. Defaults to "".

Returns:
Dict[str, Any]: A flattened dictionary where nested keys are joined by dots.
Dict[str, Any]: A new dictionary with all nested keys flattened and joined by dots.

Example:
>>> flatten_dict({'a': {'b': 1, 'c': 2}, 'd': 3})
Expand All @@ -134,10 +136,10 @@ def flatten_dict(data: Dict[str, Any], prefix: str = "") -> Dict[str, Any]:

def ensure_directory_exists(path: Union[str, Path]) -> Path:
"""
Ensures that the specified directory exists, creating it and any necessary parent directories if they do not already exist.
Ensure that a directory exists at the specified path, creating it and any missing parent directories if necessary.

Args:
path (str or Path): The path to the directory to ensure exists.
Parameters:
path (str or Path): The directory path to check or create.

Returns:
Path: A Path object representing the ensured directory.
Expand All @@ -153,13 +155,15 @@ def ensure_directory_exists(path: Union[str, Path]) -> Path:

def sanitize_filename(filename: str) -> str:
"""
Cleans a filename by replacing invalid characters and trimming unwanted characters.
Sanitize a filename by replacing invalid characters and trimming unwanted leading or trailing characters.

Parameters:
filename (str): The original filename to sanitize.
Replaces characters not allowed in filenames (`<>:"/\\|?*`) with underscores, removes leading and trailing spaces and dots, and ensures the result is not empty or only underscores. Returns "unnamed" if the sanitized filename is empty or invalid.

Args:
filename (str): The filename to sanitize.

Returns:
str: A sanitized filename with invalid characters replaced by underscores, leading/trailing spaces and dots removed, and guaranteed to be non-empty. Returns "unnamed" if the sanitized result is empty or only underscores.
str: The sanitized filename, or "unnamed" if the result is empty or only underscores.

Example:
>>> sanitize_filename(' my<file>:name?.txt ')
Expand All @@ -178,14 +182,14 @@ def sanitize_filename(filename: str) -> str:

def merge_dicts(dict1: Dict[str, Any], dict2: Dict[str, Any]) -> Dict[str, Any]:
"""
Recursively merges two dictionaries, combining nested dictionaries and giving precedence to values from the second dictionary.
Recursively merge two dictionaries, combining nested dictionaries and prioritizing values from the second dictionary.

Args:
Parameters:
dict1 (Dict[str, Any]): The base dictionary to merge into.
dict2 (Dict[str, Any]): The dictionary whose values take precedence. Nested dictionaries are merged recursively.

Returns:
Dict[str, Any]: A new dictionary containing the merged keys and values.
Dict[str, Any]: A new dictionary containing the merged result.

Example:
>>> merge_dicts({'a': 1, 'b': {'x': 2}}, {'b': {'y': 3}, 'c': 4})
Expand All @@ -202,14 +206,14 @@ def merge_dicts(dict1: Dict[str, Any], dict2: Dict[str, Any]) -> Dict[str, Any]:

def chunk_list(data: List[Any], chunk_size: int) -> List[List[Any]]:
"""
Splits a list into sublists (chunks) of a specified size.
Split a list into sublists (chunks) of a specified maximum size.

Args:
data (List[Any]): The list to be divided into chunks.
chunk_size (int): The maximum size of each chunk. Must be a positive integer.
Parameters:
data (List[Any]): The list to split into chunks.
chunk_size (int): The maximum number of elements per chunk. Must be greater than zero.

Returns:
List[List[Any]]: A list of sublists, where each sublist contains up to `chunk_size` elements from the original list. The last chunk may contain fewer elements if the total is not divisible by `chunk_size`.
List[List[Any]]: A list of sublists, each containing up to `chunk_size` elements. The final chunk may have fewer elements if the list size is not a multiple of `chunk_size`.

Example:
>>> chunk_list([1, 2, 3, 4, 5], 2)
Expand All @@ -220,15 +224,15 @@ def chunk_list(data: List[Any], chunk_size: int) -> List[List[Any]]:

def format_duration(seconds: float) -> str:
"""
Converts a duration in seconds to a human-readable string in seconds, minutes, or hours.
Convert a duration in seconds to a human-readable string in seconds, minutes, or hours.

Args:
seconds (float): The duration in seconds.
Parameters:
seconds (float): Duration in seconds.

Returns:
str: The formatted duration as a string, using seconds with two decimals if under 60, minutes with one decimal if under 3600, or hours with one decimal otherwise.
str: Formatted duration string. Uses seconds with two decimals if under 60, minutes with one decimal if under 3600, or hours with one decimal otherwise.

Example:
Examples:
>>> format_duration(45)
'45.00s'
>>> format_duration(125)
Expand Down
Loading