python存档

[summer506hai]

Python 打包自己的库到 PYPI

• https://zhuanlan.zhihu.com/p/79164800

• 输入 your-command 可执行自定义的方法（安装完pip后）
  entry_points={ 'console_scripts': [ 'your-command = your_package.your_module:main', ], },

your_project/ ├── your_package/ │ ├── init .py │ └── your_module.py ├── setup.py └── README.md

[summer506hai]

函数执行超时

• 使用func_timeout模块中提供的func_set_timeout装饰器
• 如下面的例子， f()方法 执行超过 10秒，结束f()方法的执行

import time
from threading import Thread

import func_timeout
from func_timeout import func_set_timeout

@func_set_timeout(10)
def f():
    while True:
        print("running.....")
        time.sleep(1)

def try_f():
    try:
        f()
    except func_timeout.exceptions.FunctionTimedOut:
        print("执行已超时10s")

if __name__ == '__main__':
    t1 = Thread(target=try_f, args=())
    t1.start()
    print("start.....")

[summer506hai]

获取url的域名

from urllib.parse import urlparse

parsed_url = urlparse(url)
print(parsed_url.netloc)

[summer506hai]

excel

excel中写数据

• 数据写入excel时，清洗excel中的非法字符

    writer = pd.ExcelWriter(your_file, engine="openpyxl")
    import re
    def data_clean(text):
        # 清洗excel中 非法字符，都是不常见的不可显示字符，例如退格，响铃等
        ILLEGAL_CHARACTERS_RE = re.compile(r'[\000-\010]|[\013-\014]|[\016-\037]')
        text = ILLEGAL_CHARACTERS_RE.sub(r'', text)
        return text
    df = pd.DataFrame(your_data)
    df = df.fillna('').astype(str)
    for col in df.columns:
        df[col] = df[col].apply(lambda x: data_clean(x))
    df.to_excel(writer, sheet_name="your_sheet_name", index=False)
    # writer.save()
    writer.close()

读excel中数据

• excel 中的列名 存在 同名（序号不同）

import pandas as pd

# 读取 Excel 文件 excel 列名为  query top1_url top1_title .....
df = pd.read_excel('your_excel.xlsx',sheet_name="your_sheet_name")

# 输出每行所有 url 列的内容
for index, row in df.iterrows():
    print(f'query is:{row["query"]}')
    #excel 中的列名 存在 同名（序号不同），使用 for 循环读取 
    for i in range(1,6):         
        url = row[f'top{i}_url']
        title = row[f'top{i}_title']
        print(f'url is: {url}, title is: {title}')

读excel中数据，并以json格式写到文件中

json格式如下：

{
    "query": "宝宝洗澡怎么洗",
    "data": [
        {
            "url": "https://www.    .htm",
            "title": "xxxxxxxxx"
        },
        {
            "url": "https://www.  .htm",
            "title": "xxxxxxx"
        },
   ...
    ]
}

import json
import pandas as pd

def read_excel_data(excel_name,sheet_name):
    # 读取 Excel 文件
    df = pd.read_excel(excel_name,sheet_name=sheet_name)
    all_data = []
    # 输出每行所有 url 列的内容
    for index, row in df.iterrows():
        each_data = {}
        each_data["query"] = row["query"]
        # print(type(row))
        each_data["data"] = []
        # print(f'query is:{row["query"]}')
        for i in range(1,6):
            each_result = {}
            url = row[f'top{i}_url']
            title = row[f'top{i}_title']
            if not pd.isna(url) and not pd.isna(title) : #不为 nan （float类型）
                each_result["url"] = url
                each_result["title"] = title
                each_data["data"].append(each_result)

        if len(each_data["data"]) != 0:
            all_data.append(each_data)
    return all_data

def write_to_json(txt_name,all_data): #写成json格式
    with open(txt_name, "w", encoding='utf-8') as f:
        for p in range(len(all_data)):
            # print(json.dumps(json_data_all[p], ensure_ascii=False))
            f.write(json.dumps(all_data[p], ensure_ascii=False) + "\n")

if __name__ == '__main__':
    all_data = read_excel_data('your_excel_file.xlsx',"your_sheet_name")
    write_to_json("your_json_file.txt",all_data)

[summer506hai]

处理json数据

json格式如下：

{
    "query": "宝宝洗澡怎么洗",
    "data": [
        {
            "url": "https://www.    .htm",
            "title": "xxxxxxxxx"
        },
        {
            "url": "https://www.  .htm",
            "title": "xxxxxxx"
        }
    ]
}

• 读json

  def read_json(json_file):
  '''
  读json文件，返回list
  '''
  f = open(json_file, encoding='utf-8')
  lines = f.readlines()  # 读取全部内容 ，并以列表方式返回
  all_lines = []
  for line in lines:
      _line = json.loads(line)
      all_lines.append(_line)
  return all_lines

• 写json

  def write_to_json(txt_name,all_data): #写成json格式
  with open(txt_name, "w", encoding='utf-8') as f:
      for p in range(len(all_data)):
          # print(json.dumps(json_data_all[p], ensure_ascii=False))
          f.write(json.dumps(all_data[p], ensure_ascii=False) + "\n")

• 相同的query 进行 合并

  def merge_same_query_data(data_list):
  '''
  json中，合并 query相同
  '''
  merge_data = {}
  for each_data in data_list:
      query = each_data["query"]
      data = each_data["data"]
      if query in merge_data:
          # If query already exists, append the results
          merge_data[query]["data"].extend(data)
      else:
          # If query doesn't exist, add it to the merged_results
          merge_data[query] = {"query":query,"data":data}
  # print(list(merge_data.values()))
  return list(merge_data.values())

• url相同（每一行中有相同的url）的剔除

def delete_same_url_data(data_list):
    '''
    删除掉 url一样的数据
    '''
    new_line = []
    for each_data in data_list:
        data = each_data["data"]
        url_list = []
        new_data = []
        for item in data:
            url = item["url"]
            if url not in url_list:
                url_list.append(url)
                new_data.append(item)
        each_data["data"] = new_data
        # print(each_data)
        new_line.append(each_data)
    return new_line