Python标准库之csv(1)

Python标准库之csv(1)

1.Python处理csv文件之csv.writer()

import csv

def csv_write(path,data):
    with open(path,'w',encoding='utf-8',newline='') as f:
        writer = csv.writer(f,dialect='excel')
        for row in data:
            writer.writerow(row)
    return True

调用上面的函数

data = [
    ['Name','Height'],
    ['Keys','176cm'],
    ['HongPing','160cm'],
    ['WenChao','176cm']
]

csv_write('test.csv',data)

运行结果

2.Python处理csv文件之csv.reader()

def csv_read(path):
    data = []
    with open(path,'r',encoding='utf-8') as f:
        reader = csv.reader(f,dialect='excel')
        for row in reader:
            data.append(row)
    return data

调用上面的函数

data = csv_read('test.csv')
print(data)

运行结果

[['Name', 'Height'], ['Keys', '176cm'], ['HongPing', '160cm'], ['WenChao', '176cm']]

3.Python处理csv文件之csv.DictWriter()

def csv_dict_write(path,head,data):
    with open(path,'w',encoding='utf-8',newline='') as f:
        writer = csv.DictWriter(f,head)
        writer.writeheader()
        writer.writerows(data)
        return True

调用上面的函数

head = ['Name','Age']

data = [
    {'Name':'Keys', 'Age':28},
    {'Name':'HongPing', 'Age':29},
    {'Name':'WenChao', 'Age':15}
]

csv_dict_write('test2.csv',head,data)

运行结果

4.Python处理csv文件之csv.DictReader()

def csv_dict_read(path):
    with open(path,'r',encoding='utf-8') as f:
        reader = csv.DictReader(f,dialect='excel')
        for row in reader:
            print(row['Name'])

调用上面的函数

csv_dict_read('test2.csv')

运行结果

Keys
HongPing
WenChao