问题

我的代码使用文本文件作为输入，并使用多线程来同时执行这些行，我需要输出CSV文件，其中每个线程在文件中填充另一列。我找不到一种方法来实现这个，有办法吗？

我的代码如下：

def generate_values(min, max, amount):
    arr = [None] * amount
    for i in range(amount):
        arr[i] = random.uniform(min, max)
        if thread.is_alive():
            output_csv.write(str(arr[i]))
    return arr

input_file = open("max_min.txt", "r")
output_csv = open("uniform_values.csv", "w")
for lines in input_file:
    line = lines.split("\n")
    for fields in line:
        if "\n" in line:
            line.remove("\n")
        for i in fields:
            i = fields.split(",")
        Emin = float(i[0])
        Emax = float(i[1])
        Eamount = int(i[2])
        thread = threading.Thread(target=generate_values, args=(Emin, Emax, Eamount))
        threads.append(thread)

for thread in threads:
    thread.start()

for thread in threads:
    thread.join()

输入文件如下：

2,5,1000
1,7,1000
4,25,1000

输出应该是每个线程的数字位于不同的列中，类似于：

3.4 ; 5.6 ; 21.4
4.2 ; 5.8 ; 31.2
.
.
.
等等（分号分隔每一列）

如果不使用`多线程`，如何将插入到CSV文件的数据插入到另一列中？

<details>
<summary>英文:</summary>

My code use text file as an input and use `multithreading` to execute the lines together,
I need to output CSV file that every thread fill another column in the file.
I can&#39;t find a way to do that, is there a way?

My code:

def generate_values(min, max, amount):
arr = [None] * amount
for i in range(amount):
arr[i] = random.uniform(min, max)
if thread.is_alive():
output_csv.write(str(arr[i]))
return arr

input_file = open("max_min.txt", "r")
output_csv= open("uniform_values.csv","w")
for lines in input_file:
line = lines.split("\n")
for fields in line:
if "\n" in line:
line.remove("\n")
for i in fields:
i = fields.split(",")
Emin = float(i[0])
Emax = float(i[1])
Eamount = int(i[2])
thread=threading.Thread(target=generate_values, args=(Emin,Emax,Eamount))
threads.append(thread)

for thread in threads:
thread.start()

for thread in threads:
thread.join()

The input file is:

2,5,1000
1,7,1000
4,25,1000

The output should be the numbers of each thread in different columns.
Something like:

3.4 ; 5.6 ; 21.4
4.2 ; 5.8 ; 31.2
.
.
.
etc. (The semicolon defined each column)

If not through `multithreading`, how to make the data that inserted to the CSV file insert to another column?


</details>


# 答案1
**得分**: 1

你不能从不同的线程写入文本文件的不同行的不同部分，因为这样做本质上是随机的，因此并发写入不同列的数据是不可行的。

此外，正如我在评论中所说，我不认为多线程会加速你正在做的工作。只有当线程进行I/O操作或调用使用其他语言编写的Python扩展时，它们才会真正并行运行，否则它们会协作多任务并共享由解释器执行的时间。

尽管如此，以下是如何使用线程进行操作。为了解决同时写入文件的限制，每个线程将列数据以及列索引放入共享的 `Queue` 中。当它们都完成时，将放入 `Queue` 的数据一次写入一行。

该代码还使用了 `csv` 模块来处理文件的读取和写入，因为输入和输出文件都是以这种格式。

```python
import csv
from queue import Queue
from random import uniform
from threading import Thread

def generate_values(index, min, max, amount):
    col = tuple(uniform(min, max) for _ in range(amount))
    cols.put((index, col))

with open("max_min.txt", "r", newline='') as input_file:
    # 生成值的列。
    cols = Queue()  # 先进先出
    kinds = float, float, int  # 输入字段的数据类型。
    threads = []

    for i, fields in enumerate(csv.reader(input_file)):
        # 将字段转换为适当的类型并将它们分配给命名变量。
        e_min, e_max, e_amount = (kind(field) for kind, field in zip(kinds, fields))
#        e_amount = 5  # 用于测试的行数限制。
        thread = Thread(target=generate_values, args=(i, e_min, e_max, e_amount))
        threads.append(thread)
        thread.start()

    # 等待所有线程完成。
    for thread in threads:
        thread.join()

    # 将列数据存储在以列索引编号为键的字典中。
    results = {index: col for index, col in sorted(cols.queue)}

# 将结果写入csv文件。
with open("uniform_values.csv", "w", newline='') as output_csv:
    writer = csv.writer(output_csv, delimiter=';')
    writer.writerows(row for row in zip(*results.values()))

print('done')

希望这能帮助你！

import csv
from queue import Queue
from random import uniform
from threading import Thread


def generate_values(index, min, max, amount):
    col = tuple(uniform(min, max) for _ in range(amount))
    cols.put((index, col))


with open("max_min.txt", "r", newline='') as input_file:

    # Generate the columns of values.
    cols = Queue()  # FIFO
    kinds = float, float, int  # Data types of input fields.
    threads = []

    for i, fields in enumerate(csv.reader(input_file)):
        # Convert fields to proper type and assign them to named variables.
        e_min, e_max, e_amount = (kind(field) for kind, field in zip(kinds, fields))
#        e_amount = 5  # Limit number of rows for testing.
        thread = Thread(target=generate_values, args=(i, e_min, e_max, e_amount))
        threads.append(thread)
        thread.start()

    # Wait for all the threads to finish.
    for thread in threads:
        thread.join()

    # Store column data into a dictionary keyed by column index number.
    results = {index: col for index, col in sorted(cols.queue)}

# Write the results to a csv file.
with open("uniform_values.csv", "w", newline='') as output_csv:
    writer = csv.writer(output_csv, delimiter=';')
    writer.writerows(row for row in zip(*results.values()))

print('done')