python优雅写出文件之csv

将各种常见的数据类型写出到csv
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预计收录：list（√）、dict（√）、numpy 等写出到csv

1. 列表写出到csv

import csv

data_list = [['John', 23, 'USA'],
         ['Jose', 44, 'Spain'],
         ['Anne', 29, 'UK'],
         ['Japan', 35, 'Lee']]

with open('data_list.csv', 'w', newline='') as csvfile:
    writer = csv.writer(csvfile)
    for row in data_list:
        writer.writerow(row)

data_list.csv内容

John,23,USA
Jose,44,Spain
Anne,29,UK
Japan,35,Lee

2. 字典写出到csv

import csv

data = {'Name': 'John', 'Age': '23', 'Country': 'USA'}

with open('data.csv', 'w', newline='') as f:
    writer = csv.writer(f)
    for k, v in data.items():
        writer.writerow([k, v])

data.csv 内容

Name,John
Age,23
Country,USA

3. 字典数组写出到csv

import csv

labels = ['Name', 'Age', 'Country']
dct_arr = [
  {'Name': 'John', 'Age': '23', 'Country': 'USA'},
  {'Name': 'Jose', 'Age': '44', 'Country': 'Spain'},
  {'Name': 'Anne', 'Age': '29', 'Country': 'UK'},
  {'Name': 'Lee', 'Age': '35', 'Country': 'Japan'}
]
# 用异常处理来包装操作文件的代码，可以防止外部错误或关于文件写入过程的不兼容。
# 字典的kv对顺序可以与labels不一致，可以缺少，但不能有labels不存在的key
try:
    with open('data_dict.csv', 'w', encoding='utf-8', newline='') as f:
        writer = csv.DictWriter(f, fieldnames=labels)
        writer.writeheader()
        for elem in dct_arr:
            writer.writerow(elem)
except IOError:
    print("I/O error")

data_dict.csv 内容

Name,Age,Country
John,23,USA
Jose,44,Spain
Anne,29,UK
Lee,35,Japan

参考： 在 Python 中将字典写入 CSV

小结：字典数组比嵌套列表更能保证数据可靠哦~

n. 补充

1. 字典数组写出到 json

import json
data_list = [
    {'Name': 'John', 'Age': '23', 'Country': 'USA'},
    {'Name': 'Jose', 'Age': '44', 'Country': 'Spain'},
    {'Name': 'Anne', 'Age': '29', 'Country': 'UK'},
    {'Name': 'Lee', 'Age': '35', 'Country': 'Japan'}
]
with open('data.json', 'w', encoding='utf-8')as f:
    # ensure_ascii=False:不使用ascii，能显示中文; indent=5：缩进5
    f.write(json.dumps(data_list, ensure_ascii=False, indent=5))

data.json内容：

[
     {
          "Name": "John",
          "Age": "23",
          "Country": "USA"
     },
     {
          "Name": "Jose",
          "Age": "44",
          "Country": "Spain"
     },
     {
          "Name": "Anne",
          "Age": "29",
          "Country": "UK"
     },
     {
          "Name": "Lee",
          "Age": "35",
          "Country": "Japan"
     }
]