如何比较2个不同的csv文件并输出差异

Question

我有两个csv，分别是New.csv和Old.csv，它们有大约1K行和10列，结构如下：

如果new.csv中有一个longName（第一列），而不是old.csv中的longName，我希望将整个new.csv行追加到changes.csv中

我一开始是这样做的，但根本不起作用：

def deltaFileMaker():
    with open('Old.csv', 'r', encoding='utf-8') as t1, open('New.csv', 'r', encoding='utf-8') as t2:
        fileone = t1.readlines()
        filetwo = t2.readlines()

    with open('changes.csv', 'w', encoding='utf-8') as outFile:
        for line in filetwo:
            if line not in fileone:
                outFile.write(line)



deltaFileMaker()

我还尝试使用csv diff，但我找不到将其输出转换为csv文件的方法

更新

def deltaFileMaker():
    from csv_diff import load_csv, compare
    diff = compare(
        load_csv(open("old.csv",encoding="utf8"), key="longName"),
        load_csv(open("new.csv",encoding="utf8"), key="longName")
    )

        with open('changes.csv', 'w',encoding="utf8") as f:  
        w = csv.DictWriter(f, diff.keys())
        w.writeheader()
        w.writerow(diff)


deltaFileMaker()

这样做：

Answer 1

你看过csv-diff吗？他们的website有一个可能合适的例子：

from csv_diff import load_csv, compare
diff = compare(
    load_csv(open("one.csv"), key="id"),
    load_csv(open("two.csv"), key="id")
)

这将返回一个dict对象，您可以将其解析为CSV文件。要将的dict解析为行，下面是一个示例注意：要正确编写更改是很困难的，但这更像是一个概念证明-根据您的意愿进行修改

from csv_diff import load_csv, compare
fro csv import DictWriter

# Get all the row headers across all the changes
headers = set({'change type'})
for key, vals in diff.items():
    for val in vals: # Multiple of the same difference 'type'
        headers = headers.union(set(val.keys()))

# Write changes to file
with open('changes.csv', 'w', encoding='utf-8') as fh:
    w = DictWriter(fh, headers)
    w.writeheader()
    for key, changes in diff.items():
        for val in changes: # Add each instance of this type of change
            val.update({'change type': key}) # Add 'change type' data
            w.writerow(val)

对于文件one.csv：

id,     name, age
 1,     Cleo,   4
 2, Pancakes,   2

和two.csv：

id,   name, age
 1,   Cleo,   5
 3, Bailey,   1
4,  Elliot,  10

运行此命令将产生：

change type,     name, id,               changes, age, key
      added,   Bailey,  3,                      ,   1,
      added,   Elliot,  4,                      ,  10,
    removed, Pancakes,  2,                      ,   2,
    changed,         ,   , "{'age': ['4', '5']}",    ,   1

因此，并非所有更改都很好，但对于添加/删除的行来说效果非常好