Python 3.x 使用Python3使用Faker屏蔽现有数据时出错

我使用Python3使用Faker包屏蔽数据集。我在以下网址获得了一个代码： .

代码：

但我不断得到如下错误：

C:\Anaconda3.4\lib\site packages\spyderlib\widgets\externalshell\start\U ipython\U kernel.py:1:deprecation警告：“U”模式已被弃用 #--编码：utf-8-- 回溯（最近一次呼叫最后一次）：

文件“”，第5行，在 writer=csv.DictWriter（o，reader.fieldnames）

文件“C:\Anaconda3.4\lib\csv.py”，第96行，字段名 self.\u fieldnames=next（self.reader）

文件“C:\Anaconda3.4\lib\site packages\unicodesv\py3.py”，第55行，在next 返回self.reader.下一步（）

文件“C:\Anaconda3.4\lib\site packages\unicodesv\py3.py”，第51行，在 f=（对于f中的bs，bs.decode（编码，错误=错误）

AttributeError:“str”对象没有属性“decode”

---

有人能帮我用Python 3实现代码吗？非常感谢。

对于Python3，使用标准csv（导入csv）并删除“rU”中的U

我也花了一些时间将在线找到的python2伪造示例转换为Python3。下面的转换应该有效（非常感谢您的回答！）

def anonymize_rows(rows):

"""
Rows is an iterable of dictionaries that contain name and
email fields that need to be anonymized.
"""
    # Load the faker and its providers
    faker  = Factory.create()

    # Create mappings of names & emails to faked names & emails.
    c1  = defaultdict(faker.CARD_NO_ID)
    c2 = defaultdict(faker.ISS_USER_NAME)

    # Iterate over the rows and yield anonymized rows.
    for row in rows:
        # Replace the name and email fields with faked fields.
        row['CARD_NO_ID']  = c1[row['CARD_NO_ID']]
        row['ISS_USER_NAME'] = c2[row['ISS_USER_NAME']]

        # Yield the row back to the caller
        yield row

    """
    The source argument is a path to a CSV file containing data to 
    anonymize, while target is a path to write the anonymized CSV data to.
    """

source = 'card_transaction_data_all.csv'
target = 'card_transaction_data_all_fake.csv'

with open(source, 'rU') as f:
    with open(target, 'w') as o:
    # Use the DictReader to easily extract fields
        reader = csv.DictReader(f)
        writer = csv.DictWriter(o, reader.fieldnames)
        # Read and anonymize data, writing to target file.
        for row in anonymize_rows(reader):
            writer.writerow(row)

    import csv
    from faker import Faker
    from collections import defaultdict

    def anonymize_rows(rows):

    """
    Rows is an iterable of dictionaries that contain name and
    email fields that need to be anonymized.
    """
        # Load the faker and its providers
        faker  = Faker()

        # Create mappings of names & emails to faked names & emails.
        c1  = defaultdict(faker.msisdn)
        c2 = defaultdict(faker.name)

        # Iterate over the rows and yield anonymized rows.
        for row in rows:
            # Replace the name and email fields with faked fields.
            row['CARD_NO_ID']  = c1[row['CARD_NO_ID']]
            row['ISS_USER_NAME'] = c2[row['ISS_USER_NAME']]

            # Yield the row back to the caller
            yield row

        """
        The source argument is a path to a CSV file containing data to 
        anonymize, while target is a path to write the anonymized CSV data to.
        """

    source = 'card_transaction_data_all.csv'
    target = 'card_transaction_data_all_fake.csv'

    with open(source, 'r') as f:
        with open(target, 'w', newline='') as o:
        # Use the DictReader to easily extract fields
            reader = csv.DictReader(f)
            writer = csv.DictWriter(o, reader.fieldnames)
            # Read and anonymize data, writing to target file
            # with header!
            writer.writeheader()
            for row in anonymize_rows(reader):
                writer.writerow(row)