How to open excel file fast in Python?

Question

I am now using PyExcelerator for reading excel files, but it is extremely slow. As I always need to open excel files more than 100MB, it takes me more than twenty minutes to only load one file.

The functionality I need are:

• Open Excel Files, Select Specific Tables, And Load Them Into a Dict or List object.
• Sometimes: Select Specific Columns And Only Load Whole Lines Which Have the Specific Columns in Specific Values.
• Read Excel Files With Password Protected.

And the code I am using now is:

book = pyExcelerator.parse_xls(filepath)
parsed_dictionary = defaultdict(lambda: '', book[0][1])
number_of_columns = 44
result_list = []
number_of_rows = 500000
for i in range(0, number_of_rows):
    ok = False
    result_list.append([])
    for h in range(0, number_of_columns):
        item = parsed_dictionary[i,h]
        if type(item) is StringType or type(item) is UnicodeType:
            item = item.replace("\t","").strip()
        result_list[i].append(item)
        if item != '':
            ok = True
    if not ok:
        break

Any suggestions?

Answer 1

pyExcelerator appears not to be maintained. To write xls files, use xlwt, which is a fork of pyExcelerator with bug fixes and many enhancements. The (very basic) xls reading capability of pyExcelerator was eradicated from xlwt. To read xls files, use xlrd.

If it's taking 20 minutes to load a 100MB xls file, you must be using one or more of: a slow computer, a computer with very little available memory, or an older version of Python.

Neither pyExcelerator nor xlrd read password-protected files.

Here's a link that covers xlrd and xlwt .

Disclaimer: I'm the author of xlrd and maintainer of xlwt.

Answer 2

xlrd is pretty good for reading files and xlwt is pretty good for writing. Both superior to pyExcelerator in my experience.

Answer 3

You could try to pre-allocate the list to its size in a single statement instead of appending one item at a time like this: (one large allocation of memory should be faster than many small ones)

book = pyExcelerator.parse_xls(filepath)
parsed_dictionary = defaultdict(lambda: '', book[0][1])
number_of_columns = 44
number_of_rows = 500000
result_list = [] * number_of_rows 
for i in range(0, number_of_rows):
    ok = False
    #result_list.append([])
    for h in range(0, number_of_columns):
        item = parsed_dictionary[i,h]
        if type(item) is StringType or type(item) is UnicodeType:
            item = item.replace("\t","").strip()
        result_list[i].append(item)
        if item != '':
            ok = True
    if not ok:
        break

If doing this gives appreciable performance increase you could also try to preallocate each list item with the number of columns and then assign them by index rather than appending one value at a time. Here's a snippet that creates a 10x10, two-dimensional list in a single statement with an initial value of 0:

L = [[0] * 10 for i in range(10)]

So folded into your code, it might work something like this:

book = pyExcelerator.parse_xls(filepath)
parsed_dictionary = defaultdict(lambda: '', book[0][1])
number_of_columns = 44
number_of_rows = 500000
result_list = [[''] * number_of_rows for x in range(number_of_columns)]
for i in range(0, number_of_rows):
    ok = False
    #result_list.append([])
    for h in range(0, number_of_columns):
        item = parsed_dictionary[i,h]
        if type(item) is StringType or type(item) is UnicodeType:
            item = item.replace("\t","").strip()
        result_list[i,h] = item
        if item != '':
            ok = True
    if not ok:
        break

Answer 4

Unrelated to your question : If you're trying to check if none of the columns are empty string, then you set ok = True initially, and do this instead in the inner loop ( ok = ok and item != '' ). Also, you can just use isinstance(item, basestring) to test whether a variable is string or not.

Revised version

for i in range(0, number_of_rows):
    ok = True
    result_list.append([])
    for h in range(0, number_of_columns):
        item = parsed_dictionary[i,h]
        if isinstance(item, basestring):
            item = item.replace("\t","").strip()
        result_list[i].append(item)
        ok = ok and item != ''

    if not ok:
        break

Answer 5

I built a library recently that may be of interest: https://github.com/ktr/sxl . It essentially tries to "stream" Excel files like Python does with normal files and is therefore very fast when you only need a subset of data (esp. if it is near the beginning of the file).