datavudeja

from typing import Callable, Any
import functools
import traceback


def handle_exceptions(func: Callable[..., Any]) -> Callable[..., Any]:
    """
    Decorate a function to catch and handle exceptions by returning a detailed error message.

    Args:

datavudeja

#!/usr/bin/env python3

'''
`@beartype` decorator, implementing a rudimentary subset of PEP 484-style type
checking based on Python 3.x function annotations.

See Also
----------
https://stackoverflow.com/a/37961120/2809027
    Stackoverflow answer introducing the `@beartype` decorator.

datavudeja

"""A ``debounce`` decorator implementation in Python similar to debounce_ in ``lodash``.

.. _debounce: https://lodash.com/docs#debounce
"""
from functools import wraps
from threading import Timer
import time
from typing import Any, Callable, Dict, Optional, Tuple

datavudeja

from __future__ import annotations

import builtins
from datetime import datetime
import functools
import inspect
import logging
import os
import re
import sys

datavudeja

from __future__ import absolute_import, print_function

from abc import ABCMeta
import functools
import inspect
import logging
from collections import defaultdict, namedtuple

import boltons.typeutils
import six

datavudeja

This is a library of helper functions that I use when writing Python Jupyter code.

Usually, I just copy-paste this between notebooks, but I've found a need for simplifying the code-reuse story across different notebooks.

from __future__ import annotations
try:
    from mediocreatbest import auto
except ImportError:
 %pip install --quiet --upgrade pip

datavudeja

#!/usr/bin/env python3

# * ABOUT
# ---------------------------------------------------------------------
# This section try to explain about the basic python things which will
# help to make your program simpler.  It's time you switch from
# interpreter to some text-editor/IDE.
#
# May be you want to start with turtle before this

datavudeja

import torch
import time
import functools
from typing import Literal, Optional, Callable, Any

class TimerContext:
    
  @staticmethod
  def cuda_timer(unit: Literal['ms', 's'] = 's'):
      """返回CUDA计时上下文管理器"""

datavudeja

"""
webapp/core/utilities/stopwatch.py

Example Usage:
    ```
    def countdown(n):
        while n > 0:
            n -= 1

    # Use 1: Explicit start/stop

datavudeja

"""
```
from . import timefunc, timing_manager
```
This module provides a comprehensive and thread-safe toolkit for performance monitoring
in Python applications. It is designed to be both easy to use for quick debugging
and powerful enough for detailed performance analysis.

The module is built around two core components: