stringio

This code is simplification of code in a Django app that receives an uploaded zip file via HTTP multi-part POST and does read-only processing of the data inside: #!/usr/bin/env python import csv, sys, StringIO, traceback, zipfile try: import io except ImportError: sys.stderr.write('Could not import the `io` module.\n') def get_zip_file(filename, method): if method == 'direct': return zipfile.ZipFile(filename) elif method == 'StringIO': data = file(filename).read() return zipfile.ZipFile(StringIO.StringIO(data)) elif method == 'BytesIO': data = file(filename).read() return zipfile.ZipFile(io

I'm looking through the source of StringIO where it says says some notes: Using a real file is often faster (but less convenient) . There's also a much faster implementation in C, called cStringIO , but it's not subclassable. StringIO just like a memory file object, why is it slower than real file object? Python's file handling is implemented entirely in C . This means that it's quite fast (at least in the same order of magnitude as native C code). The StringIO library, however, is written in Python. The module itself is thus interpreted, with the associated performance penalties. As you know,

I am unable to read data in Pandas: Input: import pandas as pd data = 'a,b,c\n1,2,3\n4,5,6' pd.read_csv(StringIO(data),skipinitialspace=True) Output: NameError:name 'StringIO' is not defined Please let me know why the error occurred and also let me know what to import. Abhishek Found the solution here: The error occurred because I didn't import StringIO . Unlike Python 2, in Python 3 you are required to import it. from io import StringIO After importing no error occurred. Output to the above question was: a b c 0 1 2 3 1 4 5 6 It can also be imported from pandas.compat which works for both

I'm trying create and serve excel files using Django. I have a jar file which gets parameters and produces an excel file according to parameters and it works with no problem. But when i'm trying to get the produced file and serve it to the user for download the file comes out broken. It has 0kb size. This is the code piece I'm using for excel generation and serving. def generateExcel(request,id): if os.path.exists('./%s_Report.xlsx' % id): excel = open("%s_Report.xlsx" % id, "r") output = StringIO.StringIO(excel.read()) out_content = output.getvalue() output.close() response = HttpResponse(out

StringIO has the following notes in its code: Notes: - Using a real file is often faster (but less convenient). - There's also a much faster implementation in C, called cStringIO, but it's not subclassable. The "real file is often faster" line seemed really odd to me: how could writing to disk beat writing to memory? I tried profiling these different cases and got results that contradict these docs, as well as the answer to this question . This other question does explain why cStringIO is slower under some circumstances, though I'm not doing any concatenating here. The test writes a given

I'm using pandas to manage a large array of 8-byte integers. These integers are included as space-delimited elements of a column in a comma-delimited CSV file, and the array size is about 10000x10000. Pandas is able to quickly read the comma-delimited data from the first few columns as a DataFrame, and also quickly store the space-delimited strings in another DataFrame with minimal hassle. The trouble comes when I try to cast transform the table from a single column of space-delimited strings to a DataFrame of 8-bit integers. I have tried the following: intdata = pd.DataFrame(strdata