Question

我正在尝试创建一个查看2个CSV文件的python v3.x程序。
最初，我需要将CAR CSV列表分为两个列表，“昂贵的汽车”和“廉价的汽车”，并为每个列表分配相关的行。

然后我打算从指标CSV中获取一个指标，看看它是针对昂贵汽车，廉价车还是两者的指标，然后将该指标CSV行中的值与匹配的行连接起来在汽车CSV中。

CAR CSV-列出许多汽车的详细信息

“汽车代码”，“价格”，“别名”，“组”
  “ Car1”，“ 100”，“ Blue Car”，“ Cheap Cars”
  “ Car2”，“ 900”，“金车”，“昂贵的汽车”
  “ Car3”，“ 150”，“ Red Car”，“ Cheap Cars”
  “ Car4”，“ 999”，“白金车”，“昂贵的车”
  “ Car5”，“ 122”，“棕色汽车”，“便宜的汽车”
  “ Car6”，“ 500”，“粉红色汽车”，“便宜的汽车”，“昂贵的汽车”



指示器CSV-列出汽车的可能故障/错误

“ Indicator_Field”，“ Indicator_Value”，“ Desc”，“ Groups”
  “故障”，“生锈”，“车身生锈”，“便宜的汽车；昂贵的汽车”
  “错误”，“窗户绕线器已停止”，“手动窗户绕线器已损坏”，“廉价汽车”
  “故障”，“ V12问题”，“ V12发动机问题”，“昂贵的汽车”



连接示例

{“ code”：“ Car1”，“ Error”：“ Rusting”}
  {“代码”：“ Car2”，“故障”：“ V12问题”}
  {“ code”：“ Car5”，“ Error”：“ Window Winder Stopped”}
  {“ code”：“ Car1”，“ Error”：“ Window Winder Stopped”}

到目前为止，我所能做的就是从每个CSV中选择一条随机行，并从每个CSV中连接特定的值。问题是现在所有指标和汽车类别都匹配。

from sys import argv
from time import sleep
import random
import csv
import heapq

script, indicator_file, car_file = argv
ind = ''
car = ''

def indicatorDefinition(i):
    with open(i) as file:
        reader = csv.DictReader(file)
        random_line, = heapq.nlargest(1, reader, key=lambda L: random.random())
        global ind
        ind = random_line['Indicator_Field']+'":"'+random_line['Indicator_Value']+'"'

def carDefinition(n):
    with open(n) as file:
        reader = csv.DictReader(file)
        random_line, = heapq.nlargest(1, reader, key=lambda L: random.random())
        global net
        net = '"code":"'+random_line['Car code']+'","'




def counter():
    count = 0
    while count < 6:
        carDefinition(car_file)
        indicatorDefinition(indicator_file)
        print("{"+car+ind+"}")
        sleep(random.randint(1,10))
        count += 1


counter()

Answer 1

也许是这样的事情？ ~~我认为“组”字段应该拆分并且不能按原样使用。~~根据注释进行了更新以读取所有组。

import csv
import io
import random
import collections
import itertools

# Data included in source for clarity

car_csv = """
"Car code","Price","Alias","Groups"
"Car1","100","Blue Car","Cheap Cars"
"Car2","900","Gold Car","Expensive Cars"
"Car3","150","Red Car","Cheap Cars"
"Car4","999","Platinum Car","Expensive Cars"
"Car5","122","Brown Car","Cheap Cars"
"Car6","500","Pink Car","Cheap Cars","Expensive Cars"
"TestCarWithThreeGroups","500","Pink Car","Cheap Cars","Expensive Cars","Broken Cars"
""".lstrip()

indicator_csv = """
"Indicator_Field","Indicator_Value","Desc","Groups"
"Fault","Rusting","Bodywork is rusting","Cheap Cars; Expensive Cars"
"Error","Window Winder Stopped","Manual window winder broken","Cheap Cars"
"Fault","V12 Issues","V12 Engine Problems","Expensive Cars"
""".lstrip()

# Read data (replace io.StringIO(...) with a file object to read from a file)
indicator_data = list(csv.DictReader(io.StringIO(indicator_csv)))

# Note `restkey` to capture all of the additional columns into `OtherGroups`.
car_data = list(csv.DictReader(io.StringIO(car_csv), restkey='OtherGroups'))

# Pre-massage the car data so `Groups` is always a set of groups, and `OtherGroups` is no longer there:
for car in car_data:
    car['Groups'] = {car['Groups']} | set(car.pop('OtherGroups', ()))


# Create a mapping of groups <-> indicators
indicators_by_group = collections.defaultdict(list)
for indicator in indicator_data:
    for group in indicator['Groups'].split('; '):
        indicators_by_group[group].append(indicator)


def generate_car():
    car = random.choice(car_data)
    # Concatenate all indicators based on the groups of the car
    available_indicators = list(itertools.chain(
        *(indicators_by_group.get(group, []) for group in car['Groups'])
    ))
    # Choose a random indicator -- this will crash if there are no available indicators
    # for the car.
    indicator = random.choice(available_indicators)
    # Generate output datum
    return {
        'code': car['Car code'],
        indicator['Indicator_Field']: indicator['Indicator_Value'],
    }


for x in range(10):
    print(generate_car())

示例输出：

{'code': 'Car1', 'Error': 'Window Winder Stopped'}
{'code': 'Car6', 'Error': 'Window Winder Stopped'}
{'code': 'Car2', 'Fault': 'Rusting'}
{'code': 'Car6', 'Error': 'Window Winder Stopped'}
{'code': 'TestCarWithThreeGroups', 'Error': 'Window Winder Stopped'}
{'code': 'Car5', 'Fault': 'Rusting'}
{'code': 'Car2', 'Fault': 'Rusting'}
{'code': 'TestCarWithThreeGroups', 'Fault': 'V12 Issues'}
{'code': 'Car6', 'Fault': 'Rusting'}
{'code': 'TestCarWithThreeGroups', 'Error': 'Window Winder Stopped'}

匹配来自单独CSV文件的特定值并连接行

1 个答案: