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Workflow Custom Code Writing Guidelines

Background: For security reasons, the code writing for 【Python custom skill code】 && 【Advanced Orchestration - Code Node】 is subject to standardized specifications.

Supported Python Packages​

1. Built-in Functions and Types​

  • dict
  • sorted
  • filter
  • map
  • enumerate

2. Standard Library Modules​

Data Processing​

  • json
  • decimal
  • uuid
  • base64
  • hashlib

String Processing​

  • re (regular expressions)
  • string
  • textwrap
  • difflib (difference comparison)

Data Structures and Algorithms​

  • copy
  • bisect (binary search)
  • heapq (heap queue)
  • statistics (statistical calculations)

Mathematical Computation​

  • math
  • operator (operator functions)

Date and Time​

  • datetime
  • time
  • calendar

Other Tools​

  • random (random number generation)
  • requests (HTTP requests)

3. Type Annotations (typing module)​

  • typing (the module itself)
  • Any
  • Union
  • Optional
  • Literal
  • Final
  • ClassVar
  • TypeVar
  • Generic
  • Protocol
  • runtime_checkable
  • overload
  • cast
  • TYPE_CHECKING
  • NoReturn
  • List
  • Dict
  • Set
  • Tuple
  • FrozenSet
  • Deque
  • Counter
  • ChainMap
  • OrderedDict
  • DefaultDict
  • MutableMapping
  • MutableSequence
  • MutableSet
  • Mapping
  • Sequence
  • AbstractSet
  • Collection
  • Container
  • Iterable
  • Iterator
  • Reversible
  • Sized
  • Hashable
  • Callable
  • Awaitable
  • Coroutine
  • AsyncIterable
  • AsyncIterator
  • AsyncGenerator
  • Generator
  • ContextManager
  • AsyncContextManager

Syntax Specifications​

Due to restrictions such as secure environment isolation, code authors are required to follow the relevant specifications when writing code. Prerequisite: only built-in syntax, built-in libraries, and a limited set of standard libraries are supported.

  1. Using the math module
import math

def calculate(a, b):
    result = math.fsum([a, b])
    return result

Incorrect usage:

from math import fsum

def calculate(a, b):
    result = fsum([a, b])
    return result

Explanation: Due to the import restrictions in the current code block, only parent package imports are supported when importing packages; the from a import b syntax is not supported.

  1. Using datetime

Correct usage:

import typing
from datetime import datetime


def get_weather(location: str, date: typing.Optional[str] = None) -> dict:
    # 处理默认日期
    if date is None:
        formatted_date = datetime.datetime.now().strftime("%Y-%m-%d")
    else:
        try:
            # 尝试解析常见日期格式
            if len(date) == 8 and date.isdigit():
                # 处理 YYYYMMDD 格式
                date_obj = datetime.datetime.strptime(date, "%Y%m%d")
            else:
                # 尝试标准格式 YYYY-MM-DD
                date_obj = datetime.datetime.strptime(date, "%Y-%m-%d")
            formatted_date = date_obj.strftime("%Y-%m-%d")
        except ValueError:
            # 如果格式不匹配，使用原始输入（可能导致API调用失败）
            formatted_date = date

    # 这里是模拟数据，实际应用中可能会调用天气API
    weather_data = {
        "location": location,
        "date": formatted_date,
        "forecast": "sunny",
        "temperature": "25°C",
        "wind": "light breeze"
    }
    return weather_data

Incorrect usage:

from typing import Optional, List, Dict, Any, Union, Callable
from datetime import datetime
...omitted...