I have a tar file with several files compressed in it. I need to read one specific file (it is in csv format) using pandas. I tried to use the following code:
import tarfile
tar = tarfile.open('my_files.tar', 'r:gz')
f = tar.extractfile('some_files/need_to_be_read.csv')
import pandas as pd
df = pd.read_csv(f.read())
but it throws up the following error:
OSError: Expected file path name or file-like object, got <class 'bytes'> type
on the last line of the code. How do I go about this to read this file?
When you call pandas.read_csv(), you need to give it a filename or file-like object. tar.extractfile() returns a file-like object. Instead of reading the file into memory, pass the file to Pandas.
So remove the .read() part:
import tarfile
tar = tarfile.open('my_files.tar', 'r:gz')
f = tar.extractfile('some_files/need_to_be_read.csv')
import pandas as pd
df = pd.read_csv(f)
Here is my scenario: I have a zip file that I am downloading with requests into memory rather than writing a file. I am unzipping the data into an object called myzipfile. Inside the zip file is a csv file. I would like to convert each row of the csv data into a dictionary. Here is what I have so far.
import csv
from io import BytesIO
import requests
# other imports etc.
r = requests.get(url=fileurl, headers=headers, stream=True)
filebytes = BytesIO(r.content)
myzipfile = zipfile.ZipFile(filebytes)
for name in myzipfile.namelist():
mycsv = myzipfile.open(name).read()
for row in csv.DictReader(mycsv): # it fails here.
print(row)
errors:
Traceback (most recent call last):
File "/usr/lib64/python3.7/csv.py", line 98, in fieldnames
self._fieldnames = next(self.reader)
_csv.Error: iterator should return strings, not int (did you open the file in text mode?)
Looks like csv.DictReader(mycsv) expects a file object instead of raw data. How do I convert the rows in the mycsv object data (<class 'bytes'>) to a list of dictionaries? I'm trying to accomplish this without writing a file to disk and working directly from csv objects in memory.
The DictReader expects a file or file-like object: we can satisfy this expectation by loading the zipped file into an io.StringIO instance.
Note that StringIO expects its argument to be a str, but reading a file from the zipfile returns bytes, so the data must be decoded. This example assumes that the csv was originally encoded with the local system's default encoding. If that is not the case the correct encoding must be passed to decode().
for name in myzipfile.namelist():
data = myzipfile.open(name).read().decode()
mycsv = io.StringIO(data)
reader = csv.DictReader(mycsv)
for row in reader:
print(row)
dict_list = [] # a list
reader = csv.DictReader(open('yourfile.csv', 'rb'))
for line in reader: # since we used DictReader, each line will be saved as a dictionary
dict_list.append(line)
I'm having problems reading from a gzipped csv file with the gzip and csv libs. Here's what I got:
import gzip
import csv
import json
f = gzip.open(filename)
csvobj = csv.reader(f,delimiter = ',',quotechar="'")
for line in csvobj:
ts = line[0]
data_json = json.loads(line[1])
but this throws an exception:
File "C:\Users\yaronol\workspace\raw_data_from_s3\s3_data_parser.py", line 64, in download_from_S3
self.parse_dump_file(filename)
File "C:\Users\yaronol\workspace\raw_data_from_s3\s3_data_parser.py", line 30, in parse_dump_file
for line in csvobj:
_csv.Error: iterator should return strings, not bytes (did you open the file in text mode?)
gunzipping the file and opening that with csv works fine. I've also tried decoding the file text to convert from bytes to str...
What am I missing here?
Default mode for gzip.open is rb, if you wish to work with strs, you have to specify it extra:
f = gzip.open(filename, mode="rt")
OT: it is a good practice to write I/O operations in a with block:
with gzip.open(filename, mode="rt") as f:
You are opening the file in binary mode (which is the default for gzip).
Try instead:
import gzip
import csv
f = gzip.open(filename, mode='rt')
csvobj = csv.reader(f,delimiter = ',',quotechar="'")
too late, you can use datatable package in python
import datatable as dt
df = dt.fread(filename)
df.head()
I'm working on a reporting application for my Django powered website. I want to run several reports and have each report generate a .csv file in memory that can be downloaded in batch as a .zip. I would like to do this without storing any files to disk. So far, to generate a single .csv file, I am following the common operation:
mem_file = StringIO.StringIO()
writer = csv.writer(mem_file)
writer.writerow(["My content", my_value])
mem_file.seek(0)
response = HttpResponse(mem_file, content_type='text/csv')
response['Content-Disposition'] = 'attachment; filename=my_file.csv'
This works fine, but only for a single, unzipped .csv. If I had, for example, a list of .csv files created with a StringIO stream:
firstFile = StringIO.StringIO()
# write some data to the file
secondFile = StringIO.StringIO()
# write some data to the file
thirdFile = StringIO.StringIO()
# write some data to the file
myFiles = [firstFile, secondFile, thirdFile]
How could I return a compressed file that contains all objects in myFiles and can be properly unzipped to reveal three .csv files?
zipfile is a standard library module that does exactly what you're looking for. For your use-case, the meat and potatoes is a method called "writestr" that takes a name of a file and the data contained within it that you'd like to zip.
In the code below, I've used a sequential naming scheme for the files when they're unzipped, but this can be switched to whatever you'd like.
import zipfile
import StringIO
zipped_file = StringIO.StringIO()
with zipfile.ZipFile(zipped_file, 'w') as zip:
for i, file in enumerate(files):
file.seek(0)
zip.writestr("{}.csv".format(i), file.read())
zipped_file.seek(0)
If you want to future-proof your code (hint hint Python 3 hint hint), you might want to switch over to using io.BytesIO instead of StringIO, since Python 3 is all about the bytes. Another bonus is that explicit seeks are not necessary with io.BytesIO before reads (I haven't tested this behavior with Django's HttpResponse, so I've left that final seek in there just in case).
import io
import zipfile
zipped_file = io.BytesIO()
with zipfile.ZipFile(zipped_file, 'w') as f:
for i, file in enumerate(files):
f.writestr("{}.csv".format(i), file.getvalue())
zipped_file.seek(0)
The stdlib comes with the module zipfile, and the main class, ZipFile, accepts a file or file-like object:
from zipfile import ZipFile
temp_file = StringIO.StringIO()
zipped = ZipFile(temp_file, 'w')
# create temp csv_files = [(name1, data1), (name2, data2), ... ]
for name, data in csv_files:
data.seek(0)
zipped.writestr(name, data.read())
zipped.close()
temp_file.seek(0)
# etc. etc.
I'm not a user of StringIO so I may have the seek and read out of place, but hopefully you get the idea.
def zipFiles(files):
outfile = StringIO() # io.BytesIO() for python 3
with zipfile.ZipFile(outfile, 'w') as zf:
for n, f in enumarate(files):
zf.writestr("{}.csv".format(n), f.getvalue())
return outfile.getvalue()
zipped_file = zip_files(myfiles)
response = HttpResponse(zipped_file, content_type='application/octet-stream')
response['Content-Disposition'] = 'attachment; filename=my_file.zip'
StringIO has getvalue method which return the entire contents. You can compress the zipfile
by zipfile.ZipFile(outfile, 'w', zipfile.ZIP_DEFLATED). Default value of compression is ZIP_STORED which will create zip file without compressing.
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.
I am now at a loss to achieve the next step.
My primary goal is to download and extract the zip file and pass the contents (CSV data) via a TCP stream. I would prefer not to actually write any of the zip or extracted files to disk if I could get away with it.
Here is my current script which works but unfortunately has to write the files to disk.
import urllib, urllister
import zipfile
import urllib2
import os
import time
import pickle
# check for extraction directories existence
if not os.path.isdir('downloaded'):
os.makedirs('downloaded')
if not os.path.isdir('extracted'):
os.makedirs('extracted')
# open logfile for downloaded data and save to local variable
if os.path.isfile('downloaded.pickle'):
downloadedLog = pickle.load(open('downloaded.pickle'))
else:
downloadedLog = {'key':'value'}
# remove entries older than 5 days (to maintain speed)
# path of zip files
zipFileURL = "http://www.thewebserver.com/that/contains/a/directory/of/zip/files"
# retrieve list of URLs from the webservers
usock = urllib.urlopen(zipFileURL)
parser = urllister.URLLister()
parser.feed(usock.read())
usock.close()
parser.close()
# only parse urls
for url in parser.urls:
if "PUBLIC_P5MIN" in url:
# download the file
downloadURL = zipFileURL + url
outputFilename = "downloaded/" + url
# check if file already exists on disk
if url in downloadedLog or os.path.isfile(outputFilename):
print "Skipping " + downloadURL
continue
print "Downloading ",downloadURL
response = urllib2.urlopen(downloadURL)
zippedData = response.read()
# save data to disk
print "Saving to ",outputFilename
output = open(outputFilename,'wb')
output.write(zippedData)
output.close()
# extract the data
zfobj = zipfile.ZipFile(outputFilename)
for name in zfobj.namelist():
uncompressed = zfobj.read(name)
# save uncompressed data to disk
outputFilename = "extracted/" + name
print "Saving extracted file to ",outputFilename
output = open(outputFilename,'wb')
output.write(uncompressed)
output.close()
# send data via tcp stream
# file successfully downloaded and extracted store into local log and filesystem log
downloadedLog[url] = time.time();
pickle.dump(downloadedLog, open('downloaded.pickle', "wb" ))
Below is a code snippet I used to fetch zipped csv file, please have a look:
Python 2:
from StringIO import StringIO
from zipfile import ZipFile
from urllib import urlopen
resp = urlopen("http://www.test.com/file.zip")
myzip = ZipFile(StringIO(resp.read()))
for line in myzip.open(file).readlines():
print line
Python 3:
from io import BytesIO
from zipfile import ZipFile
from urllib.request import urlopen
# or: requests.get(url).content
resp = urlopen("http://www.test.com/file.zip")
myzip = ZipFile(BytesIO(resp.read()))
for line in myzip.open(file).readlines():
print(line.decode('utf-8'))
Here file is a string. To get the actual string that you want to pass, you can use zipfile.namelist(). For instance,
resp = urlopen('http://mlg.ucd.ie/files/datasets/bbc.zip')
myzip = ZipFile(BytesIO(resp.read()))
myzip.namelist()
# ['bbc.classes', 'bbc.docs', 'bbc.mtx', 'bbc.terms']
My suggestion would be to use a StringIO object. They emulate files, but reside in memory. So you could do something like this:
# get_zip_data() gets a zip archive containing 'foo.txt', reading 'hey, foo'
import zipfile
from StringIO import StringIO
zipdata = StringIO()
zipdata.write(get_zip_data())
myzipfile = zipfile.ZipFile(zipdata)
foofile = myzipfile.open('foo.txt')
print foofile.read()
# output: "hey, foo"
Or more simply (apologies to Vishal):
myzipfile = zipfile.ZipFile(StringIO(get_zip_data()))
for name in myzipfile.namelist():
[ ... ]
In Python 3 use BytesIO instead of StringIO:
import zipfile
from io import BytesIO
filebytes = BytesIO(get_zip_data())
myzipfile = zipfile.ZipFile(filebytes)
for name in myzipfile.namelist():
[ ... ]
I'd like to offer an updated Python 3 version of Vishal's excellent answer, which was using Python 2, along with some explanation of the adaptations / changes, which may have been already mentioned.
from io import BytesIO
from zipfile import ZipFile
import urllib.request
url = urllib.request.urlopen("http://www.unece.org/fileadmin/DAM/cefact/locode/loc162txt.zip")
with ZipFile(BytesIO(url.read())) as my_zip_file:
for contained_file in my_zip_file.namelist():
# with open(("unzipped_and_read_" + contained_file + ".file"), "wb") as output:
for line in my_zip_file.open(contained_file).readlines():
print(line)
# output.write(line)
Necessary changes:
There's no StringIO module in Python 3 (it's been moved to io.StringIO). Instead, I use io.BytesIO]2, because we will be handling a bytestream -- Docs, also this thread.
urlopen:
"The legacy urllib.urlopen function from Python 2.6 and earlier has been discontinued; urllib.request.urlopen() corresponds to the old urllib2.urlopen.", Docs and this thread.
Note:
In Python 3, the printed output lines will look like so: b'some text'. This is expected, as they aren't strings - remember, we're reading a bytestream. Have a look at Dan04's excellent answer.
A few minor changes I made:
I use with ... as instead of zipfile = ... according to the Docs.
The script now uses .namelist() to cycle through all the files in the zip and print their contents.
I moved the creation of the ZipFile object into the with statement, although I'm not sure if that's better.
I added (and commented out) an option to write the bytestream to file (per file in the zip), in response to NumenorForLife's comment; it adds "unzipped_and_read_" to the beginning of the filename and a ".file" extension (I prefer not to use ".txt" for files with bytestrings). The indenting of the code will, of course, need to be adjusted if you want to use it.
Need to be careful here -- because we have a byte string, we use binary mode, so "wb"; I have a feeling that writing binary opens a can of worms anyway...
I am using an example file, the UN/LOCODE text archive:
What I didn't do:
NumenorForLife asked about saving the zip to disk. I'm not sure what he meant by it -- downloading the zip file? That's a different task; see Oleh Prypin's excellent answer.
Here's a way:
import urllib.request
import shutil
with urllib.request.urlopen("http://www.unece.org/fileadmin/DAM/cefact/locode/2015-2_UNLOCODE_SecretariatNotes.pdf") as response, open("downloaded_file.pdf", 'w') as out_file:
shutil.copyfileobj(response, out_file)
I'd like to add my Python3 answer for completeness:
from io import BytesIO
from zipfile import ZipFile
import requests
def get_zip(file_url):
url = requests.get(file_url)
zipfile = ZipFile(BytesIO(url.content))
files = [zipfile.open(file_name) for file_name in zipfile.namelist()]
return files.pop() if len(files) == 1 else files
write to a temporary file which resides in RAM
it turns out the tempfile module ( http://docs.python.org/library/tempfile.html ) has just the thing:
tempfile.SpooledTemporaryFile([max_size=0[,
mode='w+b'[, bufsize=-1[, suffix=''[,
prefix='tmp'[, dir=None]]]]]])
This
function operates exactly as
TemporaryFile() does, except that data
is spooled in memory until the file
size exceeds max_size, or until the
file’s fileno() method is called, at
which point the contents are written
to disk and operation proceeds as with
TemporaryFile().
The resulting file has one additional
method, rollover(), which causes the
file to roll over to an on-disk file
regardless of its size.
The returned object is a file-like
object whose _file attribute is either
a StringIO object or a true file
object, depending on whether
rollover() has been called. This
file-like object can be used in a with
statement, just like a normal file.
New in version 2.6.
or if you're lazy and you have a tmpfs-mounted /tmp on Linux, you can just make a file there, but you have to delete it yourself and deal with naming
Adding on to the other answers using requests:
# download from web
import requests
url = 'http://mlg.ucd.ie/files/datasets/bbc.zip'
content = requests.get(url)
# unzip the content
from io import BytesIO
from zipfile import ZipFile
f = ZipFile(BytesIO(content.content))
print(f.namelist())
# outputs ['bbc.classes', 'bbc.docs', 'bbc.mtx', 'bbc.terms']
Use help(f) to get more functions details for e.g. extractall() which extracts the contents in zip file which later can be used with with open.
All of these answers appear too bulky and long. Use requests to shorten the code, e.g.:
import requests, zipfile, io
r = requests.get(zip_file_url)
z = zipfile.ZipFile(io.BytesIO(r.content))
z.extractall("/path/to/directory")
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])
It wasn't obvious in Vishal's answer what the file name was supposed to be in cases where there is no file on disk. I've modified his answer to work without modification for most needs.
from StringIO import StringIO
from zipfile import ZipFile
from urllib import urlopen
def unzip_string(zipped_string):
unzipped_string = ''
zipfile = ZipFile(StringIO(zipped_string))
for name in zipfile.namelist():
unzipped_string += zipfile.open(name).read()
return unzipped_string
Use the zipfile module. To extract a file from a URL, you'll need to wrap the result of a urlopen call in a BytesIO object. This is because the result of a web request returned by urlopen doesn't support seeking:
from urllib.request import urlopen
from io import BytesIO
from zipfile import ZipFile
zip_url = 'http://example.com/my_file.zip'
with urlopen(zip_url) as f:
with BytesIO(f.read()) as b, ZipFile(b) as myzipfile:
foofile = myzipfile.open('foo.txt')
print(foofile.read())
If you already have the file downloaded locally, you don't need BytesIO, just open it in binary mode and pass to ZipFile directly:
from zipfile import ZipFile
zip_filename = 'my_file.zip'
with open(zip_filename, 'rb') as f:
with ZipFile(f) as myzipfile:
foofile = myzipfile.open('foo.txt')
print(foofile.read().decode('utf-8'))
Again, note that you have to open the file in binary ('rb') mode, not as text or you'll get a zipfile.BadZipFile: File is not a zip file error.
It's good practice to use all these things as context managers with the with statement, so that they'll be closed properly.