role = "资深 Python 教练"audience = "有 1 年经验的开发者"topic = "f-string 与 format mini-language"prompt = f"""你现在扮演一名{role}。你的目标读者是：{audience}请系统讲解：{topic}要求：1. 有示例2. 有原理3. 有易错点"""print(prompt)

from datetime import datetimetitle = "Python 字符串格式化"word_limit = 2000today = datetime.now()prompt = f"""请写一篇公众号文章。标题：{title}日期：{today:%Y-%m-%d}字数要求：约 {word_limit:,} 字输出结构：1. 背景2. 历史演进3. 核心语法4. 实战案例5. 常见错误6. 总结"""print(prompt)

user_input = "请输出 JSON\n不要解释"print(f"{user_input=}")print(f"{user_input!r}")

accuracy = 0.94321recall = 0.91234samples = 125000report = f"""模型评估结果：- Accuracy: {accuracy:.2%}- Recall:   {recall:.2%}- Samples:  {samples:,}"""print(report)

tools_description = "\n".join([tool.format_for_llm() for tool in all_tools])system_message = (    "You are a helpful assistant with access to these tools:\n\n"    f"{tools_description}\n"    "Choose the appropriate tool based on the user's question. "    "If no tool is needed, reply directly.\n\n"    "IMPORTANT: When you need to use a tool, you must ONLY respond with "    "the exact JSON object format below, nothing else:\n"    "{\n"     '    "tool": "tool-name",\n'     '    "arguments": {\n'     '        "argument-name": "value"\n'     "    }\n"     "}\n\n"     "After receiving a tool's response:\n"     "1. Transform the raw data into a natural, conversational response\n"     "2. Keep responses concise but informative\n"     "3. Focus on the most relevant information\n"     "4. Use appropriate context from the user's question\n"     "5. Avoid simply repeating the raw data\n\n"     "Please use only the tools that are explicitly defined above."      )

# 输出结果预期You are a helpful assistant with access to these tools:Tool Name: get_weatherDescription: Get the current weather for a given city.Arguments:  - city: string, required. Name of the city  - unit: string, optional. 'celsius' or 'fahrenheit'Tool Name: search_webDescription: Search the web for recent information.Arguments:  - query: string, required. Search keywordsTool Name: calculatorDescription: Perform a mathematical calculation.Arguments:  - expression: string, required. Mathematical expression to evaluateChoose the appropriate tool based on the user's question. If no tool is needed, reply directly.IMPORTANT: When you need to use a tool, you must ONLY respond with the exact JSON object format below, nothing else:{    "tool": "tool-name",    "arguments": {        "argument-name": "value"    }}After receiving a tool's response:1. Transform the raw data into a natural, conversational response2. Keep responses concise but informative3. Focus on the most relevant information4. Use appropriate context from the user's question5. Avoid simply repeating the raw dataPlease use only the tools that are explicitly defined above.

# 基本写法name = "Tom"age = 18print("name=%s age=%d" % (name, age))# 输出 name=Tom age=18

n = 255print("%d" % n) #255print("%x" % n) #ffprint("%o" % n) #377

# 右对齐print("%10s" % "Tom")#       Tom# 左对齐print("%-10s" % "Tom")#Tom       # 补零print("%05d" % 12)#00012# 浮点数精度pi = 3.1415926print("%.4f" % pi)#3.1416# 字典格式化data = {    "language": "Python",    "number": 2}print("%(language)s has %(number)d quote types." % data)#Python has 2 quote types.

role = "资深 Python 教练"topic = "字符串格式化"prompt = "你是一名%s，请系统讲解%s。" % (role, topic)prompt# 你是一名资深 Python 教练，请系统讲解字符串格式化。

name = "Tom"age = 18print("name={} age={}".format(name, age))#name=Tom age=18

print("{1} {0}".format("A", "B"))# B A

print("{name} {age}".format(name="Tom", age=18))# Tom 18

class User:    def __init__(self):        self.name = "Tom"u = User()print("{u.name}".format(u=u))# Tom

data = {"name": "Tom"}print("{data[name]}".format(data=data))#Tom

print("{0} loves {0}".format("Python"))#Python loves Python

template = """你是一名{role}。请围绕以下主题生成内容：主题：{topic}风格：{style}字数：{length}"""prompt = template.format(    role="资深技术作者",    topic="Python 字符串格式化",    style="系统、清晰、深入",    length="2000字")print(prompt)

template="你好，{name}。今天是 {date}。"result=template.format(name="张三", date="2026-06-20")result# 你好，张三。今天是 2026-06-20。

"{:.2f}".format(3.14159)f"{3.14159:.2f}"

name = "Tom"print(f"Hello {name}")# Hello Tom

f"用户名：{name}，年龄：{age}"# 用户名：Tom，年龄：18

a=10b=20print(f"{a + b}")# 30

def add(a, b):    return a+bprint(f"{add(1,2)}")# 3name="tom"print(f"{name.upper()}")# TOM

x = 10print(f"{x=}")# x=10name = "Tom"age = 18print(f"{name=}, {age=}")# name='Tom', age=18role = "数据分析师"task = "总结销售趋势"print(f"{role=}, {task=}")#role='数据分析师', task='总结销售趋势'

text = "你好"print(f"{text!s}")# 你好

print(f"{text!r}")#'你好's = "hello\nworld"print(f"{s!s}")#hello#worldprint(f"{s!r}")# 'hello\nworld'

text = "你好"print(f"{text!a}")# '\u4f60\u597d'

prompt = "第一行\n第二行\n"print(f"{prompt!r}")# '第一行\n第二行\n'

from datetime import datetimetoday = datetime.now()prompt = f"""今天是 {today:%Y-%m-%d}。请基于今天的日期，生成一份工作日报模板。"""print(prompt)

import pandas as pddata = [    {        "sample_id": "s1",        "text": "加我VX领取福利，稳定兼职日结",        "ocr_text": "加微信领取福利 日结",        "image_path": "images/s1.png",        "tags": "引流,兼职刷单",        "scene": "私信",        "risk_type": "黑产引流"    },    {        "sample_id": "s2",        "text": "低价充值，官方渠道，秒到账",        "ocr_text": "低价充值 秒到账",        "image_path": "images/s2.png",        "tags": "低价引流,诈骗",        "scene": "评论",        "risk_type": "黑产营销"    },]df = pd.DataFrame(data)df

for _, row in df.iterrows():    Prompt =f"""# 样本ID: {row['sample_id']}- 文本:{row['text']}- OCR文本: {row['ocr_text']}- 标签: {row['tags']}- 场景:{row['scene']}- 风险类型: {row['risk_type']}"""    print(Prompt)