python-csv文件数据处理

概要

使用csv文件可以较容易地存储多行且列相同的数据，便于数据的读取与解析，也常用于自动化测试过程中的数据参数化。本文简单示例一种使用python处理csv文件的思路。

提示：以下为本篇文章正文内容，案例仅供参考。

一、所需插件

csv。python自带库，无需额外安装。

二、使用步骤

1.引入库

import csv

2.读取数据

# 读取完整csv文件内容，包括首行
def read_csv(self, filepath=None):
    if filepath is None:
        filepath = self.filepath
    with open(filepath, 'r', encoding = 'utf-8') as file:
        # 1、创建阅读器对象
        reader = csv.reader(file)
        # 2、读取文件数据
        rows = [row for row in reader]
        return rows

3.写入数据

# 读取完整csv文件内容，包括首行
# 按行写入数据到csv文件
# way写入方式，w-覆盖写入 at-追加写入
def write_csv(self, filepath, way, row):
    if filepath is None:
        filepath = self.filepath
    with open(filepath, way, encoding = 'utf-8', newline = '') as file:
        writer = csv.writer(file)
        writer.writerow(row)

4.应用示例

import csv
import os

class neo_csv:
    def __init__(self):
        self.filepath = os.getcwd() + "\\neo_data.csv"
    
    # 读取csv首行
    def get_headrow(self, filepath=None):
        if filepath is None:
            filepath = self.filepath
        with open(filepath, 'r', encoding = 'utf-8') as file:
            reader = csv.reader(file)
            row = next(reader)
            return row
    
    # 转换首行列名为字典key
    def headrow_to_dict(self, filepath=None):
        head_row = self.get_headrow(filepath)
        head_col = {}
        for index, col_name in enumerate(head_row):
            head_col[col_name] = index
        return head_col

    # 读取完整csv文件内容，包括首行
    def read_csv(self, filepath=None):
        if filepath is None:
            filepath = self.filepath
        with open(filepath, 'r', encoding = 'utf-8') as file:
            # 1、创建阅读器对象
            reader = csv.reader(file)
            # 2、读取文件数据
            rows = [row for row in reader]
            return rows
    
    # 按行写入数据到csv文件
    # way写入方式，w-覆盖写入 at-追加写入
    def write_csv(self, filepath, way, row):
        if filepath is None:
            filepath = self.filepath
        with open(filepath, way, encoding = 'utf-8', newline = '') as file:
            writer = csv.writer(file)
            writer.writerow(row)

if __name__ == "__main__":
    my_test = neo_csv()

    # 创建csv文件：接口描述-参数化-参数校验
    head_row = ['switch', 'method', 'url', 'need_token', 'urldata', 'jsondata', 'filedata', 'pars_genwith_sql', 'pars_genwith_upfile', 'pars_ck_required','pars_ck_boundary', 'pars_ck_legal', 'pars_ck_illegal']
    filepath = os.getcwd() + '\\gendata.csv'
    my_test.write_csv(filepath, 'w', head_row)
    result = my_test.get_headrow(filepath)
    print("表头为", result)

    # 添加一行示例数据
    data_row = ['true', 'post', '/user/login', 'false', '', {'username':'${username}','passwd':'${passwd}'},'','','',['username','passwd'],{'username':'8-15'},{'username':r'/w'},{'username':r'/s'}]
    my_test.write_csv(filepath, 'at', data_row)

    # 将列名称转换为字典的key
    head_col = my_test.headrow_to_dict(filepath)
    print("表头字典为", head_col)
 
    # 读取csv文件全部内容
    csv_content = my_test.read_csv(filepath)
    print("完整内容为", csv_content)

    # 读取行的某列内容
    for index in range (1, len(csv_content)):
        row = csv_content[index]
        print("该行内容为", row)
        # 根据列字典的key获取数组序号，再取该行该列的值
        switch = row[head_col['switch']]
        method = row[head_col['method']]
        url = row[head_col['url']]
        print(switch, method, url)

后记

示例代码的执行结果如图。对于csv文件中数据的处理，还是需要结合实际需求去设计代码实现。