for row in csv.DictReader

这是一个常见的用法，用于遍历一个以字典形式存储的CSV文件的每一行数据。在这个循环中，每一行都会被解析为一个字典，其中每个键对应CSV文件的列名，对应的值则是该列在当前行的数值。

例如，假设你有一个名为 "data.csv" 的CSV文件，其中包含以下数据：

name,age,city
John,25,New York
Alice,30,San Francisco
Bob,35,Los Angeles

你可以使用以下代码来遍历每一行数据：

import csv

with open('data.csv', 'r') as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row)

输出结果将会是：

{'name': 'John', 'age': '25', 'city': 'New York'}
{'name': 'Alice', 'age': '30', 'city': 'San Francisco'}
{'name': 'Bob', 'age': '35', 'city': 'Los Angeles'}

你可以根据具体需求从字典中获取相应的值，比如 `row['name']` 获取姓名，`row['age']` 获取年龄等。

相关问题

降低这段代码重复率：def readCSVFile(demand_file, depot_file, model): model['demand_dict'] = {int(row['id']): Demand(id=int(row['id']), x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), demand=float(row['demand']), start_time=float(row['start_time']), end_time=float(row['end_time']), service_time=float(row['service_time'])) for row in csv.DictReader(open(demand_file))} model['demand_id_list'] = list(model['demand_dict'].keys()) model['number_of_demands'] = len(model['demand_id_list']) model['vehicle_dict'] = {row['vehicle_type']: Vehicle(depot_id=row['depot_id'], x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), type=row['vehicle_type'], capacity=float(row['vehicle_capacity']), free_speed=float(row['vehicle_speed']), numbers=float(row['number_of_vehicle']), fixed_cost=float(row['fixed_cost']), variable_cost=float(row['variable_cost']), start_time=float(row['start_time']), end_time=float(row['end_time'])) for row in csv.DictReader(open(depot_file))} model['vehicle_type_list'] = list(model['vehicle_dict'].keys())

可以将相似的代码提取出来，写成一个函数。比如：

def readDictFromFile(file_path, key_fn, value_fn):
    with open(file_path) as f:
        return {key_fn(row): value_fn(row) for row in csv.DictReader(f)}

然后就可以用这个函数来读取需求和车辆的字典了，代码如下：

model['demand_dict'] = readDictFromFile(demand_file, lambda row: int(row['id']), lambda row: Demand(id=int(row['id']), x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), demand=float(row['demand']), start_time=float(row['start_time']), end_time=float(row['end_time']), service_time=float(row['service_time'])))
model['demand_id_list'] = list(model['demand_dict'].keys())
model['number_of_demands'] = len(model['demand_id_list'])
model['vehicle_dict'] = readDictFromFile(depot_file, lambda row: row['vehicle_type'], lambda row: Vehicle(depot_id=row['depot_id'], x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), type=row['vehicle_type'], capacity=float(row['vehicle_capacity']), free_speed=float(row['vehicle_speed']), numbers=float(row['number_of_vehicle']), fixed_cost=float(row['fixed_cost']), variable_cost=float(row['variable_cost']), start_time=float(row['start_time']), end_time=float(row['end_time'])))
model['vehicle_type_list'] = list(model['vehicle_dict'].keys())

优化这段代码：降低这段代码重复率：def readCSVFile(demand_file, depot_file, model): model['demand_dict'] = {int(row['id']): Demand(id=int(row['id']), x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), demand=float(row['demand']), start_time=float(row['start_time']), end_time=float(row['end_time']), service_time=float(row['service_time'])) for row in csv.DictReader(open(demand_file))} model['demand_id_list'] = list(model['demand_dict'].keys()) model['number_of_demands'] = len(model['demand_id_list']) model['vehicle_dict'] = {row['vehicle_type']: Vehicle(depot_id=row['depot_id'], x_coord=float(row['x_coord']), y_coord=float(row['y_coord']), type=row['vehicle_type'], capacity=float(row['vehicle_capacity']), free_speed=float(row['vehicle_speed']), numbers=float(row['number_of_vehicle']), fixed_cost=float(row['fixed_cost']), variable_cost=float(row['variable_cost']), start_time=float(row['start_time']), end_time=float(row['end_time'])) for row in csv.DictReader(open(depot_file))} model['vehicle_type_list'] = list(model['vehicle_dict'].keys())

可以将其中的一些重复代码提取出来，写成函数或者变量。比如：

def parse_demand_row(row):
    return Demand(id=int(row['id']),
                  x_coord=float(row['x_coord']),
                  y_coord=float(row['y_coord']),
                  demand=float(row['demand']),
                  start_time=float(row['start_time']),
                  end_time=float(row['end_time']),
                  service_time=float(row['service_time']))

def parse_vehicle_row(row):
    return Vehicle(depot_id=row['depot_id'],
                   x_coord=float(row['x_coord']),
                   y_coord=float(row['y_coord']),
                   type=row['vehicle_type'],
                   capacity=float(row['vehicle_capacity']),
                   free_speed=float(row['vehicle_speed']),
                   numbers=float(row['number_of_vehicle']),
                   fixed_cost=float(row['fixed_cost']),
                   variable_cost=float(row['variable_cost']),
                   start_time=float(row['start_time']),
                   end_time=float(row['end_time']))

demand_dict = {int(row['id']): parse_demand_row(row) for row in csv.DictReader(open(demand_file))}
demand_id_list = list(demand_dict.keys())
number_of_demands = len(demand_id_list)
vehicle_dict = {row['vehicle_type']: parse_vehicle_row(row) for row in csv.DictReader(open(depot_file))}
vehicle_type_list = list(vehicle_dict.keys())

model['demand_dict'] = demand_dict
model['demand_id_list'] = demand_id_list
model['number_of_demands'] = number_of_demands
model['vehicle_dict'] = vehicle_dict
model['vehicle_type_list'] = vehicle_type_list

这样可以大大降低代码的重复率，同时也方便了代码的维护和修改。