访问csv标头空白区域并且不区分大小写

Question

I'm overriding the csv.Dictreader.fieldnames property like the following to read all headers from csv files without white space and in lower case.

import csv
class MyDictReader(csv.DictReader):

    @property
    def fieldnames(self):
        return [field.strip().lower() for field in super(MyDictReader, self).fieldnames]

Now my question is, how can I access the fieldnames with automatically strip() and lower() the query?

This is, how I do it manually:

csvDict = MyDictReader(open('csv-file.csv', 'rU'))

for lineDict in csvDict:
    query = ' Column_A'.strip().lower()
    print(lineDict[query])

Any ideas?

Answer 1

Based on Pedro Romano's suggestion I coded the following example.

import csv

class DictReaderInsensitive(csv.DictReader):
    # This class overrides the csv.fieldnames property.
    # All fieldnames are without white space and in lower case

    @property
    def fieldnames(self):
        return [field.strip().lower() for field in super(DictReaderInsensitive, self).fieldnames]

    def __next__(self):
        # get the result from the original __next__, but store it in DictInsensitive

        dInsensitive = DictInsensitive()
        dOriginal = super(DictReaderInsensitive, self).__next__()

        # store all pairs from the old dict in the new, custom one
        for key, value in dOriginal.items():
            dInsensitive[key] = value

        return dInsensitive

class DictInsensitive(dict):
    # This class overrides the __getitem__ method to automatically strip() and lower() the input key

    def __getitem__(self, key):
        return dict.__getitem__(self, key.strip().lower())

For a file containing headers like

• "column_A"
• " column_A"
• "Column_A"
• " Column_A"
• ...

you can access the columns like this:

csvDict = DictReaderInsensitive(open('csv-file.csv', 'rU'))

for lineDict in csvDict:
    print(lineDict[' Column_A']) # or
    print(lineDict['Column_A']) # or
    print(lineDict[' column_a']) # all returns the same

Answer 2

You'll have to do it in two steps:

1. Create your dict specialisation with a __getitem__ method that applies the .strip().lower() to the its key parameter.
2. Override __next__ on your MyDictReader specialised class to return one of your special dictionaries initialised with the dictionary returned by the csv.DictReader superclass's __next__ method.