[英]Is there a way to replace and trim values in individual fields using the dbf to csv python library dbf by ethanfurman?
I am using the python library, dbf , by Ethan Furman to convert a number of dbf files to csv.我正在使用 Ethan Furman 的 Python 库dbf将许多 dbf 文件转换为 csv。 It works extremely well for that.
它为此非常有效。 I would like to further edit some of the fields during the conversion process but am unsure how to do it.
我想在转换过程中进一步编辑一些字段,但不确定如何做。 Specifically, I would like to replace string fields that contain only 1 or more blanks with empty strings, (eg. " " replace with "") and date fields that contain "00000000" with empty strings "".
具体来说,我想用空字符串替换仅包含 1 个或多个空格的字符串字段,(例如,“” 替换为“”),将包含“00000000”的日期字段替换为空字符串“”。 I would very much appreciate it if someone could describe how to edit the fields and write out the updated records during the conversion process.
如果有人能描述如何在转换过程中编辑字段和写出更新的记录,我将不胜感激。 Obviously, I could write a simple secondary script to edit the csv files output during conversion but I would like to do it all in one step if possible.
显然,我可以编写一个简单的辅助脚本来编辑转换过程中输出的 csv 文件,但如果可能的话,我想一步完成所有操作。 Here is the code I am using to convert the files:
这是我用来转换文件的代码:
import csv
import dbf
import os
import sys
folder=sys.argv[1]
for dirpath, dirnames, filenames in os.walk(folder):
for filename in filenames:
if filename.endswith('.DBF'):
db=dbf.Table(filename, ignore_memos=True)
db.open()
csv_fn = filename[:-4]+ ".csv"
dbf.export(db, filename=csv_fn, format='csv', header=True)
By default, when using a dbf table the data types returned are simple -- ie int
, str
, bool
, datetime.datetime
, etc. But you can make your own data types and have those used instead by specifying them in the default_data_types
parameter:默认情况下,当使用 dbf 表时,返回的数据类型很简单——即
int
、 str
、 bool
、 datetime.datetime
等。 但是您可以创建自己的数据类型并通过在default_data_types
参数中指定它们来使用这些类型:
db = dbf.Table(
filename,
ignore_memos=True,
default_data_types={
'C': my_white_space_stripping_data_type,
'D': my_empty_date_str_data_type,
},
)
Fortunately, dbf
comes with four enhanced data types already:幸运的是,
dbf
已经提供了四种增强的数据类型:
Char
-- automatically strips trailing whitespace, and ignores trailing whitespace for comparisons Char
-- 自动去除尾随空格,并忽略尾随空格进行比较
Logical
-- supports True
, False
, and None
( None
is returned when the field value is not true or false -- I've seen ?
, ' '
, and other weird garbage) Logical
- 支持True
、 False
和None
(当字段值不是 true 或 false 时返回None
- 我见过?
、 ' '
和其他奇怪的垃圾)
Date
-- supports an empty date, such as 00000000
, and displays them as ''
Date
-- 支持空日期,例如00000000
,并显示为''
DateTime
-- supports an empty date/time, and displays them as ''
DateTime
-- 支持空日期/时间,并将它们显示为''
Typically, if you're using one of the enhanced data types you probably want them all, so instead of the dictionary you can just pass a string:通常,如果您使用一种增强型数据类型,您可能需要全部使用它们,因此您可以只传递一个字符串而不是字典:
db = dbf.Table(
filename,
ignore_memos=True,
default_data_types='enhanced_data_types',
)
Now, when a csv file is exported, trailing white-space is dropped, and empty date fields become ''
.现在,当导出 csv 文件时,会删除尾随空格,并且空日期字段变为
''
。
Keep in mind that empty logical fields will become '?'
请记住,空的逻辑字段将变为
'?'
instead of ''
, so you may want the longer form of specifying a dict
to default_data_types
and only overriding C
and D
.而不是
''
,因此您可能需要更长的形式为default_data_types
指定一个dict
并且只覆盖C
和D
。
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.