{"id":1123286,"date":"2025-01-08T19:30:53","date_gmt":"2025-01-08T11:30:53","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1123286.html"},"modified":"2025-01-08T19:30:57","modified_gmt":"2025-01-08T11:30:57","slug":"python%e5%a6%82%e4%bd%95%e5%ad%98%e5%82%a8%e5%87%a0%e7%99%be%e4%b8%87%e8%a1%8c%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1123286.html","title":{"rendered":"python\u5982\u4f55\u5b58\u50a8\u51e0\u767e\u4e07\u884c\u6570\u636e"},"content":{"rendered":"

\"python\u5982\u4f55\u5b58\u50a8\u51e0\u767e\u4e07\u884c\u6570\u636e\"<\/p>\n

\u5728Python\u4e2d\uff0c\u5b58\u50a8\u51e0\u767e\u4e07\u884c\u6570\u636e\u7684\u6709\u6548\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528\u6570\u636e\u5e93\u3001\u4f7f\u7528\u6587\u4ef6\u7cfb\u7edf\uff08\u5982CSV\u3001JSON\u7b49\uff09\u3001\u4f7f\u7528\u5185\u5b58\u6570\u636e\u7ed3\u6784\uff08\u5982pandas DataFrame\u3001\u5217\u8868\u3001\u5b57\u5178\u7b49\uff09\u3001\u4f7f\u7528\u5206\u5e03\u5f0f\u5b58\u50a8\u7cfb\u7edf\u3002<\/strong> \u5728\u8fd9\u4e9b\u65b9\u6cd5\u4e2d\uff0c\u4f7f\u7528\u6570\u636e\u5e93<\/strong>\u662f\u4e00\u79cd\u5e38\u89c1\u4e14\u9ad8\u6548\u7684\u65b9\u6cd5\uff0c\u5c24\u5176\u662f\u5f53\u6570\u636e\u91cf\u5e9e\u5927\u4e14\u9700\u8981\u8fdb\u884c\u590d\u6742\u67e5\u8be2\u65f6\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528\u6570\u636e\u5e93<\/h3>\n<\/p>\n

\u4f7f\u7528\u6570\u636e\u5e93\u5b58\u50a8\u51e0\u767e\u4e07\u884c\u6570\u636e\u662f\u4e00\u79cd\u5e38\u89c1\u7684\u65b9\u6cd5\uff0c\u5c24\u5176\u9002\u7528\u4e8e\u9700\u8981\u9891\u7e41\u67e5\u8be2\u548c\u66f4\u65b0\u7684\u573a\u666f\u3002\u6570\u636e\u5e93\u7cfb\u7edf\u5982MySQL\u3001PostgreSQL\u3001SQLite\u7b49\u90fd\u80fd\u591f\u6709\u6548\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u3002<\/p>\n<\/p>\n

1.1\u3001\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u5e93<\/h4>\n<\/p>\n

\u4e0d\u540c\u7684\u6570\u636e\u5e93\u7cfb\u7edf\u5728\u6027\u80fd\u3001\u6269\u5c55\u6027\u548c\u6613\u7528\u6027\u4e0a\u5404\u6709\u4f18\u52a3\u3002\u5e38\u7528\u7684\u5173\u7cfb\u578b\u6570\u636e\u5e93\u5305\u62ec\uff1a<\/p>\n<\/p>\n

    \n
  • MySQL<\/strong>\uff1a\u5e7f\u6cdb\u4f7f\u7528\uff0c\u652f\u6301\u590d\u6742\u67e5\u8be2\u548c\u4e8b\u52a1\uff0c\u4f46\u5728\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u4e0a\u53ef\u80fd\u9700\u8981\u8fdb\u884c\u4f18\u5316\u3002<\/li>\n
  • PostgreSQL<\/strong>\uff1a\u529f\u80fd\u5f3a\u5927\uff0c\u652f\u6301\u590d\u6742\u67e5\u8be2\u548c\u9ad8\u7ea7\u7279\u6027\uff0c\u5982\u5168\u6587\u641c\u7d22\u548c\u5730\u7406\u7a7a\u95f4\u6570\u636e\u3002<\/li>\n
  • SQLite<\/strong>\uff1a\u8f7b\u91cf\u7ea7\u6570\u636e\u5e93\uff0c\u9002\u7528\u4e8e\u4e2d\u5c0f\u89c4\u6a21\u6570\u636e\u5b58\u50a8\uff0c\u4e0d\u9002\u5408\u9ad8\u5e76\u53d1\u548c\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u3002<\/li>\n<\/ul>\n

    1.2\u3001\u5b89\u88c5\u548c\u914d\u7f6e\u6570\u636e\u5e93<\/h4>\n<\/p>\n

    \u4ee5MySQL\u4e3a\u4f8b\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5MySQL\u670d\u52a1\u5668\u548c\u5ba2\u6237\u7aef\u5de5\u5177\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

    sudo apt-get update<\/p>\n
    sudo apt-get install mysql-server<\/p>\n
    sudo apt-get install mysql-client<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u542f\u52a8MySQL\u670d\u52a1\u5e76\u8fdb\u884c\u5b89\u5168\u914d\u7f6e\uff1a<\/p>\n<\/p>\n
    sudo service mysql start<\/p>\n
    sudo mysql_secure_installation<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    1.3\u3001\u4f7f\u7528Python\u8fde\u63a5\u548c\u64cd\u4f5c\u6570\u636e\u5e93<\/h4>\n<\/p>\n
    \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528mysql-connector<\/code>\u5e93\u6765\u8fde\u63a5\u548c\u64cd\u4f5cMySQL\u6570\u636e\u5e93\u3002\u9996\u5148\uff0c\u901a\u8fc7pip<\/code>\u5b89\u88c5\u8be5\u5e93\uff1a<\/p>\n<\/p>\n
    pip install mysql-connector-python<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u7136\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u8fde\u63a5MySQL\u6570\u636e\u5e93\u5e76\u521b\u5efa\u8868\uff1a<\/p>\n<\/p>\n
    import mysql.connector<\/p>\n
    \u8fde\u63a5\u5230MySQL\u6570\u636e\u5e93<\/strong><\/h2>\n
    cnx = mysql.connector.connect(<\/p>\n
        user='yourusername',<\/p>\n
        password='yourpassword',<\/p>\n
        host='127.0.0.1',<\/p>\n
        database='yourdatabase'<\/p>\n
    )<\/p>\n
    cursor = cnx.cursor()<\/p>\n
    \u521b\u5efa\u8868<\/strong><\/h2>\n
    cursor.execute("""<\/p>\n
    CREATE TABLE IF NOT EXISTS your_table (<\/p>\n
        id INT AUTO_INCREMENT PRIMARY KEY,<\/p>\n
        data_column VARCHAR(255)<\/p>\n
    )<\/p>\n
    """)<\/p>\n
    \u63d2\u5165\u6570\u636e<\/strong><\/h2>\n
    data = [('data1',), ('data2',), ('data3',)]  # \u793a\u4f8b\u6570\u636e<\/p>\n
    cursor.executemany("INSERT INTO your_table (data_column) VALUES (%s)", data)<\/p>\n
    \u63d0\u4ea4\u4e8b\u52a1<\/strong><\/h2>\n
    cnx.commit()<\/p>\n
    \u5173\u95ed\u8fde\u63a5<\/strong><\/h2>\n
    cursor.close()<\/p>\n
    cnx.close()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    1.4\u3001\u4f18\u5316\u6570\u636e\u5e93\u6027\u80fd<\/h4>\n<\/p>\n
    \u5bf9\u4e8e\u51e0\u767e\u4e07\u884c\u6570\u636e\uff0c\u6570\u636e\u5e93\u6027\u80fd\u4f18\u5316\u81f3\u5173\u91cd\u8981\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u4f18\u5316\u7b56\u7565\uff1a<\/p>\n<\/p>\n
      \n
    • \u7d22\u5f15<\/strong>\uff1a\u4e3a\u5e38\u7528\u67e5\u8be2\u7684\u5b57\u6bb5\u521b\u5efa\u7d22\u5f15\uff0c\u4ee5\u52a0\u901f\u67e5\u8be2\u901f\u5ea6\u3002<\/li>\n
    • \u5206\u533a<\/strong>\uff1a\u5c06\u6570\u636e\u8868\u6309\u67d0\u4e9b\u89c4\u5219\u5206\u6210\u591a\u4e2a\u5206\u533a\uff0c\u4ee5\u63d0\u9ad8\u67e5\u8be2\u6548\u7387\u3002<\/li>\n
    • \u7f13\u5b58<\/strong>\uff1a\u4f7f\u7528\u7f13\u5b58\u673a\u5236\u51cf\u5c11\u6570\u636e\u5e93\u7684\u76f4\u63a5\u8bbf\u95ee\u6b21\u6570\uff0c\u5982\u4f7f\u7528Redis\u7b49\u7f13\u5b58\u5de5\u5177\u3002<\/li>\n
    • \u4f18\u5316\u67e5\u8be2<\/strong>\uff1a\u907f\u514d\u4f7f\u7528\u4f4e\u6548\u7684\u67e5\u8be2\u8bed\u53e5\uff0c\u5c3d\u91cf\u51cf\u5c11\u5168\u8868\u626b\u63cf\u3002<\/li>\n<\/ul>\n
      \u4e8c\u3001\u4f7f\u7528\u6587\u4ef6\u7cfb\u7edf<\/h3>\n<\/p>\n
      \u4f7f\u7528\u6587\u4ef6\u7cfb\u7edf\u5b58\u50a8\u6570\u636e\u662f\u4e00\u79cd\u7b80\u5355\u4e14\u76f4\u89c2\u7684\u65b9\u6cd5\uff0c\u9002\u7528\u4e8e\u4e00\u6b21\u6027\u5199\u5165\u548c\u8bfb\u53d6\u8f83\u591a\u7684\u573a\u666f\u3002\u5e38\u89c1\u7684\u6587\u4ef6\u683c\u5f0f\u5305\u62ecCSV\u3001JSON\u3001HDF5\u7b49\u3002<\/p>\n<\/p>\n
      2.1\u3001\u4f7f\u7528CSV\u6587\u4ef6<\/h4>\n<\/p>\n
      CSV\u6587\u4ef6\u662f\u4e00\u79cd\u5e7f\u6cdb\u4f7f\u7528\u7684\u6587\u672c\u6587\u4ef6\u683c\u5f0f\uff0c\u9002\u7528\u4e8e\u5b58\u50a8\u7ed3\u6784\u5316\u6570\u636e\u3002Python\u7684csv<\/code>\u6a21\u5757\u548cpandas<\/code>\u5e93\u90fd\u53ef\u4ee5\u65b9\u4fbf\u5730\u5904\u7406CSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
      import csv<\/p>\n
      \u5199\u5165CSV\u6587\u4ef6<\/strong><\/h2>\n
      with open('data.csv', mode='w', newline='') as file:<\/p>\n
          writer = csv.writer(file)<\/p>\n
          writer.writerow(['Column1', 'Column2'])  # \u5199\u5165\u8868\u5934<\/p>\n
          for i in range(1000000):  # \u793a\u4f8b\u6570\u636e<\/p>\n
              writer.writerow([i, f'data_{i}'])<\/p>\n
      \u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
      with open('data.csv', mode='r') as file:<\/p>\n
          reader = csv.reader(file)<\/p>\n
          for row in reader:<\/p>\n
              print(row)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      2.2\u3001\u4f7f\u7528JSON\u6587\u4ef6<\/h4>\n<\/p>\n
      JSON\u6587\u4ef6\u662f\u4e00\u79cd\u8f7b\u91cf\u7ea7\u7684\u6570\u636e\u4ea4\u6362\u683c\u5f0f\uff0c\u9002\u7528\u4e8e\u5b58\u50a8\u5d4c\u5957\u7ed3\u6784\u7684\u6570\u636e\u3002Python\u7684json<\/code>\u6a21\u5757\u53ef\u4ee5\u65b9\u4fbf\u5730\u5904\u7406JSON\u6587\u4ef6\u3002<\/p>\n<\/p>\n
      import json<\/p>\n
      \u5199\u5165JSON\u6587\u4ef6<\/strong><\/h2>\n
      data = [{'id': i, 'data': f'data_{i}'} for i in range(1000000)]  # \u793a\u4f8b\u6570\u636e<\/p>\n
      with open('data.json', 'w') as file:<\/p>\n
          json.dump(data, file)<\/p>\n
      \u8bfb\u53d6JSON\u6587\u4ef6<\/strong><\/h2>\n
      with open('data.json', 'r') as file:<\/p>\n
          data = json.load(file)<\/p>\n
          for item in data:<\/p>\n
              print(item)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      2.3\u3001\u4f7f\u7528HDF5\u6587\u4ef6<\/h4>\n<\/p>\n
      HDF5\u662f\u4e00\u79cd\u7528\u4e8e\u5b58\u50a8\u548c\u7ec4\u7ec7\u5927\u89c4\u6a21\u6570\u636e\u7684\u6587\u4ef6\u683c\u5f0f\uff0c\u9002\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u548c\u9ad8\u6027\u80fd\u8ba1\u7b97\u3002Python\u7684h5py<\/code>\u5e93\u53ef\u4ee5\u5904\u7406HDF5\u6587\u4ef6\u3002<\/p>\n<\/p>\n
      import h5py<\/p>\n
      import numpy as np<\/p>\n
      \u5199\u5165HDF5\u6587\u4ef6<\/strong><\/h2>\n
      with h5py.File('data.h5', 'w') as file:<\/p>\n
          data = np.arange(1000000)  # \u793a\u4f8b\u6570\u636e<\/p>\n
          file.create_dataset('dataset', data=data)<\/p>\n
      \u8bfb\u53d6HDF5\u6587\u4ef6<\/strong><\/h2>\n
      with h5py.File('data.h5', 'r') as file:<\/p>\n
          data = file['dataset'][:]<\/p>\n
          print(data)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u4e09\u3001\u4f7f\u7528\u5185\u5b58\u6570\u636e\u7ed3\u6784<\/h3>\n<\/p>\n
      \u5bf9\u4e8e\u67d0\u4e9b\u5e94\u7528\u573a\u666f\uff0c\u53ef\u4ee5\u5c06\u6570\u636e\u5b58\u50a8\u5728\u5185\u5b58\u4e2d\uff0c\u4ee5\u83b7\u5f97\u66f4\u5feb\u7684\u8bfb\u5199\u901f\u5ea6\u3002\u5e38\u7528\u7684\u5185\u5b58\u6570\u636e\u7ed3\u6784\u5305\u62ecpandas DataFrame<\/code>\u3001\u5217\u8868\u3001\u5b57\u5178\u7b49\u3002<\/p>\n<\/p>\n
      3.1\u3001\u4f7f\u7528pandas DataFrame<\/h4>\n<\/p>\n
      pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5e93\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u529f\u80fd\u3002\u53ef\u4ee5\u4f7f\u7528DataFrame<\/code>\u6765\u5b58\u50a8\u548c\u64cd\u4f5c\u5927\u89c4\u6a21\u6570\u636e\u3002<\/p>\n<\/p>\n
      import pandas as pd<\/p>\n
      \u521b\u5efaDataFrame<\/strong><\/h2>\n
      data = {'Column1': range(1000000), 'Column2': [f'data_{i}' for i in range(1000000)]}<\/p>\n
      df = pd.DataFrame(data)<\/p>\n
      \u4fdd\u5b58\u4e3aCSV\u6587\u4ef6<\/strong><\/h2>\n
      df.to_csv('data.csv', index=False)<\/p>\n
      \u4eceCSV\u6587\u4ef6\u8bfb\u53d6<\/strong><\/h2>\n
      df = pd.read_csv('data.csv')<\/p>\n
      print(df.head())<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      3.2\u3001\u4f7f\u7528\u5217\u8868\u548c\u5b57\u5178<\/h4>\n<\/p>\n
      \u5217\u8868\u548c\u5b57\u5178\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u5185\u5b58\u6570\u636e\u7ed3\u6784\uff0c\u9002\u7528\u4e8e\u7b80\u5355\u7684\u6570\u636e\u5b58\u50a8\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
      # \u4f7f\u7528\u5217\u8868<\/p>\n
      data = [f'data_{i}' for i in range(1000000)]  # \u793a\u4f8b\u6570\u636e<\/p>\n
      print(data[:10])<\/p>\n
      \u4f7f\u7528\u5b57\u5178<\/strong><\/h2>\n
      data_dict = {i: f'data_{i}' for i in range(1000000)}  # \u793a\u4f8b\u6570\u636e<\/p>\n
      print(list(data_dict.items())[:10])<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u56db\u3001\u4f7f\u7528\u5206\u5e03\u5f0f\u5b58\u50a8\u7cfb\u7edf<\/h3>\n<\/p>\n
      \u5bf9\u4e8e\u8d85\u5927\u89c4\u6a21\u6570\u636e\uff0c\u5355\u673a\u5b58\u50a8\u548c\u5904\u7406\u80fd\u529b\u53ef\u80fd\u4e0d\u8db3\uff0c\u5206\u5e03\u5f0f\u5b58\u50a8\u7cfb\u7edf\u53ef\u4ee5\u63d0\u4f9b\u66f4\u9ad8\u7684\u6269\u5c55\u6027\u548c\u6027\u80fd\u3002\u5e38\u89c1\u7684\u5206\u5e03\u5f0f\u5b58\u50a8\u7cfb\u7edf\u5305\u62ecHadoop HDFS\u3001Apache Cassandra\u3001Amazon S3\u7b49\u3002<\/p>\n<\/p>\n
      4.1\u3001\u4f7f\u7528Hadoop HDFS<\/h4>\n<\/p>\n
      Hadoop HDFS\u662f\u4e00\u4e2a\u5206\u5e03\u5f0f\u6587\u4ef6\u7cfb\u7edf\uff0c\u9002\u7528\u4e8e\u5b58\u50a8\u548c\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u3002\u53ef\u4ee5\u4f7f\u7528pydoop<\/code>\u5e93\u6765\u64cd\u4f5cHDFS\u3002<\/p>\n<\/p>\n
      import pydoop.hdfs as hdfs<\/p>\n
      \u5199\u5165HDFS<\/strong><\/h2>\n
      with hdfs.open('\/user\/yourusername\/data.txt', 'w') as file:<\/p>\n
          for i in range(1000000):  # \u793a\u4f8b\u6570\u636e<\/p>\n
              file.write(f'data_{i}\\n')<\/p>\n
      \u8bfb\u53d6HDFS<\/strong><\/h2>\n
      with hdfs.open('\/user\/yourusername\/data.txt', 'r') as file:<\/p>\n
          data = file.readlines()<\/p>\n
          print(data[:10])<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      4.2\u3001\u4f7f\u7528Apache Cassandra<\/h4>\n<\/p>\n
      Apache Cassandra\u662f\u4e00\u4e2a\u9ad8\u6027\u80fd\u7684\u5206\u5e03\u5f0f\u6570\u636e\u5e93\u7cfb\u7edf\uff0c\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u5b58\u50a8\u548c\u5b9e\u65f6\u67e5\u8be2\u3002\u53ef\u4ee5\u4f7f\u7528cassandra-driver<\/code>\u5e93\u6765\u64cd\u4f5cCassandra\u3002<\/p>\n<\/p>\n
      from cassandra.cluster import Cluster<\/p>\n
      \u8fde\u63a5\u5230Cassandra\u96c6\u7fa4<\/strong><\/h2>\n
      cluster = Cluster(['127.0.0.1'])<\/p>\n
      session = cluster.connect('yourkeyspace')<\/p>\n
      \u521b\u5efa\u8868<\/strong><\/h2>\n
      session.execute("""<\/p>\n
      CREATE TABLE IF NOT EXISTS your_table (<\/p>\n
          id INT PRIMARY KEY,<\/p>\n
          data TEXT<\/p>\n
      )<\/p>\n
      """)<\/p>\n
      \u63d2\u5165\u6570\u636e<\/strong><\/h2>\n
      query = "INSERT INTO your_table (id, data) VALUES (%s, %s)"<\/p>\n
      for i in range(1000000):  # \u793a\u4f8b\u6570\u636e<\/p>\n
          session.execute(query, (i, f'data_{i}'))<\/p>\n
      \u67e5\u8be2\u6570\u636e<\/strong><\/h2>\n
      rows = session.execute("SELECT * FROM your_table LIMIT 10")<\/p>\n
      for row in rows:<\/p>\n
          print(row)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      4.3\u3001\u4f7f\u7528Amazon S3<\/h4>\n<\/p>\n
      Amazon S3\u662f\u4e00\u4e2a\u9ad8\u53ef\u7528\u7684\u5bf9\u8c61\u5b58\u50a8\u670d\u52a1\uff0c\u9002\u7528\u4e8e\u5b58\u50a8\u548c\u68c0\u7d22\u4efb\u610f\u89c4\u6a21\u7684\u6570\u636e\u3002\u53ef\u4ee5\u4f7f\u7528boto3<\/code>\u5e93\u6765\u64cd\u4f5cS3\u3002<\/p>\n<\/p>\n
      import boto3<\/p>\n
      \u8fde\u63a5\u5230S3<\/strong><\/h2>\n
      s3 = boto3.client('s3')<\/p>\n
      \u4e0a\u4f20\u6587\u4ef6\u5230S3<\/strong><\/h2>\n
      s3.upload_file('data.csv', 'yourbucket', 'data.csv')<\/p>\n
      \u4e0b\u8f7d\u6587\u4ef6\u4eceS3<\/strong><\/h2>\n
      s3.download_file('yourbucket', 'data.csv', 'data_downloaded.csv')<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u7ed3\u8bba<\/h3>\n<\/p>\n
      \u5b58\u50a8\u51e0\u767e\u4e07\u884c\u6570\u636e\u7684\u65b9\u6cd5\u6709\u5f88\u591a\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53d6\u51b3\u4e8e\u5177\u4f53\u7684\u5e94\u7528\u573a\u666f\u548c\u9700\u6c42\u3002\u4f7f\u7528\u6570\u636e\u5e93<\/strong>\u662f\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u7684\u5e38\u89c1\u4e14\u9ad8\u6548\u7684\u65b9\u6cd5\uff0c\u5c24\u5176\u662f\u9700\u8981\u8fdb\u884c\u590d\u6742\u67e5\u8be2\u548c\u5b9e\u65f6\u66f4\u65b0\u65f6\u3002\u6b64\u5916\uff0c\u4f7f\u7528\u6587\u4ef6\u7cfb\u7edf<\/strong>\u3001\u5185\u5b58\u6570\u636e\u7ed3\u6784<\/strong>\u548c\u5206\u5e03\u5f0f\u5b58\u50a8\u7cfb\u7edf<\/strong>\u4e5f\u5404\u6709\u4f18\u52a3\uff0c\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u8fdb\u884c\u9009\u62e9\u3002\u65e0\u8bba\u91c7\u7528\u54ea\u79cd\u65b9\u6cd5\uff0c\u4f18\u5316\u6570\u636e\u5b58\u50a8\u548c\u8bbf\u95ee\u7684\u6027\u80fd\u90fd\u662f\u81f3\u5173\u91cd\u8981\u7684\u3002<\/p>\n<\/p>\n
      \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
       \u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\u6765\u5b58\u50a8\u51e0\u767e\u4e07\u884c\u6570\u636e\uff1f<\/strong>
      \u5728\u5b58\u50a8\u51e0\u767e\u4e07\u884c\u6570\u636e\u65f6\uff0c\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\u975e\u5e38\u5173\u952e\u3002\u5e38\u89c1\u7684\u683c\u5f0f\u5305\u62ecCSV\u3001JSON\u3001Parquet\u548cHDF5\u7b49\u3002CSV\u683c\u5f0f\u6613\u4e8e\u9605\u8bfb\u548c\u5199\u5165\uff0c\u4f46\u5728\u5904\u7406\u5927\u6570\u636e\u65f6\u6027\u80fd\u53ef\u80fd\u8f83\u5dee\u3002JSON\u9002\u5408\u7ed3\u6784\u5316\u6570\u636e\uff0c\u4f46\u6587\u4ef6\u4f53\u79ef\u8f83\u5927\u3002Parquet\u548cHDF5\u5219\u4e3a\u9ad8\u6548\u7684\u4e8c\u8fdb\u5236\u683c\u5f0f\uff0c\u9002\u5408\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\uff0c\u652f\u6301\u538b\u7f29\u548c\u5206\u5757\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u5927\u6570\u636e\u5206\u6790\u3002<\/p>\n
      \u4f7f\u7528Python\u4e2d\u7684\u54ea\u4e9b\u5e93\u53ef\u4ee5\u9ad8\u6548\u5730\u5904\u7406\u5927\u91cf\u6570\u636e\uff1f<\/strong>
      \u5728Python\u4e2d\uff0c\u6709\u591a\u79cd\u5e93\u53ef\u4ee5\u9ad8\u6548\u5904\u7406\u5927\u91cf\u6570\u636e\u3002\u4f8b\u5982\uff0cPandas\u5e93\u63d0\u4f9b\u5f3a\u5927\u7684\u6570\u636e\u6846\u67b6\uff0c\u53ef\u4ee5\u8f7b\u677e\u8bfb\u53d6\u3001\u5199\u5165\u548c\u5206\u6790\u6570\u636e\u3002Dask\u662f\u4e00\u4e2a\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u7684\u5e93\uff0c\u5b83\u80fd\u591f\u5e76\u884c\u8ba1\u7b97\u5e76\u652f\u6301\u5206\u5e03\u5f0f\u8ba1\u7b97\u3002\u5bf9\u4e8e\u66f4\u5e95\u5c42\u7684\u64cd\u4f5c\uff0cNumPy\u53ef\u4ee5\u9ad8\u6548\u5730\u5904\u7406\u6570\u7ec4\u6570\u636e\uff0c\u800cSQLite\u5e93\u53ef\u4ee5\u7528\u4e8e\u5b58\u50a8\u548c\u7ba1\u7406\u5173\u7cfb\u578b\u6570\u636e\u3002<\/p>\n
      \u5982\u4f55\u4f18\u5316\u8bfb\u53d6\u548c\u5199\u5165\u6027\u80fd\u4ee5\u63d0\u9ad8\u6570\u636e\u5b58\u50a8\u6548\u7387\uff1f<\/strong>
      \u5728\u5904\u7406\u51e0\u767e\u4e07\u884c\u6570\u636e\u65f6\uff0c\u4f18\u5316\u8bfb\u53d6\u548c\u5199\u5165\u6027\u80fd\u81f3\u5173\u91cd\u8981\u3002\u9009\u62e9\u5408\u9002\u7684\u6587\u4ef6\u683c\u5f0f\uff08\u5982Parquet\u6216HDF5\uff09\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u6027\u80fd\u3002\u4f7f\u7528\u6279\u91cf\u64cd\u4f5c\u800c\u4e0d\u662f\u9010\u884c\u8bfb\u53d6\u548c\u5199\u5165\uff0c\u53ef\u4ee5\u51cf\u5c11I\/O\u64cd\u4f5c\u7684\u6b21\u6570\u3002\u6b64\u5916\uff0c\u8003\u8651\u4f7f\u7528\u591a\u7ebf\u7a0b\u6216\u5f02\u6b65\u7f16\u7a0b\uff0c\u4ee5\u4fbf\u5728\u8bfb\u53d6\u6216\u5199\u5165\u65f6\u5145\u5206\u5229\u7528\u7cfb\u7edf\u8d44\u6e90\u3002\u540c\u65f6\uff0c\u786e\u4fdd\u5728\u6570\u636e\u5b58\u50a8\u524d\u8fdb\u884c\u5fc5\u8981\u7684\u9884\u5904\u7406\u548c\u6e05\u6d17\uff0c\u4ee5\u51cf\u5c11\u5197\u4f59\u6570\u636e\uff0c\u63d0\u9ad8\u5b58\u50a8\u6548\u7387\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u5b58\u50a8\u51e0\u767e\u4e07\u884c\u6570\u636e\u7684\u6709\u6548\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528\u6570\u636e\u5e93\u3001\u4f7f\u7528\u6587\u4ef6\u7cfb\u7edf\uff08\u5982CSV\u3001JSON\u7b49\uff09\u3001\u4f7f\u7528\u5185\u5b58\u6570 […]","protected":false},"author":3,"featured_media":1123297,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1123286"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1123286"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1123286\/revisions"}],"predecessor-version":[{"id":1123301,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1123286\/revisions\/1123301"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1123297"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1123286"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1123286"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1123286"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}