Downloading and unzipping a .zip file without writing to disk

Question

I have managed to get my first python script to work which downloads a list of .ZIP files from a URL and then proceeds to extract the ZIP files and writes them to disk.

Answer 1

Vishal's example, however great, confuses when it comes to the file name, and I do not see the merit of redefing 'zipfile'.

Here is my example that downloads a zip that contains some files, one of which is a csv file that I subsequently read into a pandas DataFrame:

from StringIO import StringIO
from zipfile import ZipFile
from urllib import urlopen
import pandas

url = urlopen("https://www.federalreserve.gov/apps/mdrm/pdf/MDRM.zip")
zf = ZipFile(StringIO(url.read()))
for item in zf.namelist():
    print("File in zip: "+  item)
# find the first matching csv file in the zip:
match = [s for s in zf.namelist() if ".csv" in s][0]
# the first line of the file contains a string - that line shall de ignored, hence skiprows
df = pandas.read_csv(zf.open(match), low_memory=False, skiprows=[0])

(Note, I use Python 2.7.13)

This is the exact solution that worked for me. I just tweaked it a little bit for Python 3 version by removing StringIO and adding IO library

Python 3 Version

from io import BytesIO
from zipfile import ZipFile
import pandas
import requests

url = "https://www.nseindia.com/content/indices/mcwb_jun19.zip"
content = requests.get(url)
zf = ZipFile(BytesIO(content.content))

for item in zf.namelist():
    print("File in zip: "+  item)

# find the first matching csv file in the zip:
match = [s for s in zf.namelist() if ".csv" in s][0]
# the first line of the file contains a string - that line shall de     ignored, hence skiprows
df = pandas.read_csv(zf.open(match), low_memory=False, skiprows=[0])