numpy - Python: unziping special files into memory and getting them into a DataFrame -


i'm quite stuck code i'm writing in python, i'm beginner , maybe easy, can't see it. appreciated. thank in advance :)

here problem: have read special data files special extension .fen pandas dataframe.this .fen files inside zipped file .fenx contains .fen file , .cfg configuration file.

in code i've written use zipfile library in order unzip files, , them in dataframe. code following

import zipfile import numpy np import pandas pd  def readfenxfile(directory,file):      fenxzip = zipfile.zipfile(directory+ '\\' + file, 'r')     fenxzip.extractall()     fenxzip.close()      cfggeneral,cfgdevice,cfgchannels,cfgdtypes=readcfgfile(directory,file[:-5]+'.cfg')     #readcfgfile redas .cfg file , returns important data.      #here cfgdtypes important contains type of data inside .fen , become column index in final dataframe.     if cfgchannels!=none:                 dtdtype=eval('np.dtype([' + cfgdtypes + '])')         dt=np.fromfile(directory+'\\'+file[:-5]+'.fen',dtype=dtdtype)         dt=pd.dataframe(dt)     else:         dt=[]      return dt,cfgchannels,cfgdtypes

now, extract() method saves unzipped file in hard drive. .fenx files can quite big need of storing (and afterwards deleting them) slow. same now, getting .fen , .cfg files memory, not hard drive.

i have tried things fenxzip.read('whateverthenameofthefileis.fen')and other methods .open() zipfile library. can't .read() returns numpy array in anyway tried.

i know can difficult question answer, because don't have files try , see happens. if have ideas glad of reading them. :) thank much!

here solution found in case can helpful anyone. uses tempfile library create temporal object in memory.

import zipfile import tempfile import numpy np import pandas pd  def readfenxfile(directory,file,extractdirectory):       fenxzip = zipfile.zipfile(directory+ r'\\' + file, 'r')      fenfile=tempfile.spooledtemporaryfile(max_size=10000000000,mode='w+b')       fenfile.write(fenxzip.read(file[:-5]+'.fen'))      cfggeneral,cfgdevice,cfgchannels,cfgdtypes=readcfgfile(fenxzip,file[:-5]+'.cfg')      if cfgchannels!=none:                 dtdtype=eval('np.dtype([' + cfgdtypes + '])')         fenfile.seek(0)         dt=np.fromfile(fenfile,dtype=dtdtype)         dt=pd.dataframe(dt)     else:         dt=[]     fenfile.close()     fenxzip.close()         return dt,cfgchannels,cfgdtypes

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