I have the below code that takes my standardized .txt file and converts it into a JSON file perfectly. The only problem is that sometimes I have over 300 files and doing this manually (i.e. changing the number at the end of the file and running the script is too much and takes too long. I want to automate this. The files as you can see reside in one folder/directory and I am placing the JSON file in a differentfolder/directory, but essentially keeping the naming convention standardized except instead of ending with .txt it ends with .json but the prefix or file names are the same and standardized. An example would be: CRAZY_CAT_FINAL1.TXT, CRAZY_CAT_FINAL2.TXT and so on and so forth all the way to file 300. How can I automate and keep the file naming convention in place, and read and output the files to different folders/directories? I have tried, but can't seem to get this to iterate. Any help would be greatly appreciated.
import glob
import time
from glob import glob
import pandas as pd
import numpy as np
import csv
import json
csvfile = open(r'C:\Users\...\...\...\Dog\CRAZY_CAT_FINAL1.txt', 'r')
jsonfile = open(r'C:\Users\...\...\...\Rat\CRAZY_CAT_FINAL1.json', 'w')
reader = csv.DictReader(csvfile)
out = json.dumps([row for row in reader])
jsonfile.write(out)
****************************************************************************
I also have this code using the python library "requests". How do I make this code so that it uploads multiple json files with a standard naming convention? The files end with a number...
import requests
#function to post to api
def postData(xactData):
url = 'http link'
headers = {
'Content-Type': 'application/json',
'Content-Length': str(len(xactData)),
'Request-Timeout': '60000'
}
return requests.post(url, headers=headers, data=xactData)
#read data
f = (r'filepath/file/file.json', 'r')
data = f.read()
print(data)
# post data
result = postData(data)
print(result)
Use f-strings?
for i in range(1,301):
csvfile = open(f'C:\Users\...\...\...\Dog\CRAZY_CAT_FINAL{i}.txt', 'r')
jsonfile = open(f'C:\Users\...\...\...\Rat\CRAZY_CAT_FINAL{i}.json', 'w')
import time
from glob import glob
import csv
import json
import os
INPATH r'C:\Users\...\...\...\Dog'
OUTPATH = r'C:\Users\...\...\...\Rat'
for csvname in glob(INPATH+'\*.txt'):
jsonname = OUTPATH + '/' + os.basename(csvname[:-3] + 'json')
reader = csv.DictReader(open(csvname,'r'))
json.dump( list(reader), open(jsonname,'w') )
I've been trying to make my python code to fill a form in word with data that i scraped off the Internet. I wrote the data in a txt file and are now trying to fill the word file with this code:
import zipfile
import os
import tempfile
import shutil
import codecs
def getXml(docxFilename,ReplaceText):
zip = zipfile.ZipFile(open(docxFilename,"rb"))
xmlString= zip.read("word/document.xml")
for key in ReplaceText.keys():
xmlString = xmlString.replace(str(key), str(ReplaceText.get(key)))
return xmlString
def createNewDocx(originalDocx,xmlString,newFilename):
tmpDir = tempfile.mkdtemp()
zip = zipfile.ZipFile(open(originalDocx,"rb"))
zip.extractall(tmpDir)
#3tmpDir=tmpDir.decode("utf-8")
with open(os.path.join(tmpDir,"word/document.xml"),"w") as f:
f.write(xmlString)
filenames = zip.namelist()
zipCopyFilename = newFilename
with zipfile.ZipFile(zipCopyFilename,"w") as docx:
for filename in filenames:
docx.write(os.path.join(tmpDir,filename),filename)
shutil.rmtree(tmpDir)
f=open('test.txt', 'r',)
text=f.read().split("\n")
print text[1]
Pavarde = text[1]
Replace = {"PAVARDE1":Pavarde}
createNewDocx("test.docx",getXml("test.docx",Replace),"test2.docx")
The file is created but I cant open it.
I get the following error:
Illegal xlm character
My guess would be that theres something with the encoding but I cant find a solution.
I'm unable to modify the content of a NamedTemporaryFile after having created it initially.
As per my example below, I create a NamedTemporaryFile from the content of a URL (JSON data).
Then, what I aim to do is re-access that file, modify some of the content of the JSON in the file, and save it. The code below is my attempt to do so.
import json
import requests
from tempfile import NamedTemporaryFile
def create_temp_file_from_url(url):
response = requests.get(url)
temp_file = NamedTemporaryFile(mode='w+t', delete=False)
temp_file.write(response.text)
temp_file.close()
return temp_file.name
def add_content_to_json_file(json_filepath):
file = open(json_filepath)
content = json.loads(file.read())
# Add a custom_key : custom_value pair in each dict item
for repo in content:
if isinstance(repo, dict):
repo['custom_key'] = 'custom_value'
# Close file back ... if needed?
file.close()
# Write my changes to content back into the file
f = open(json_filepath, 'w') # Contents of the file disappears...?
json.dumps(content, f, indent=4) # Issue: Nothing is written to f
f.close()
if __name__ == '__main__':
sample_url = 'https://api.github.com/users/mralexgray/repos'
tempf = create_temp_file_from_url(sample_url)
# Add extra content to Temporary file
add_content_to_json_file(tempf)
try:
updated_file = json.loads(tempf)
except Exception as e:
raise e
Thanks for the help!
1: This line:
json.dumps(content, f, indent=4) # Issue: Nothing is written to f
doesn't dump content to f. It makes a string from content, with skipkeys value f, and then does nothing with it.
You probably wanted json.dump, with no s..
2: This line
updated_file = json.loads(tempf)
tries to load a JSON object from the temp filename, which isn't going to work. You'll have to either read the file in as a string and then use loads, or re-open the file and use json.load.
I have the following view code that attempts to "stream" a zipfile to the client for download:
import os
import zipfile
import tempfile
from pyramid.response import FileIter
def zipper(request):
_temp_path = request.registry.settings['_temp']
tmpfile = tempfile.NamedTemporaryFile('w', dir=_temp_path, delete=True)
tmpfile_path = tmpfile.name
## creating zipfile and adding files
z = zipfile.ZipFile(tmpfile_path, "w")
z.write('somefile1.txt')
z.write('somefile2.txt')
z.close()
## renaming the zipfile
new_zip_path = _temp_path + '/somefilegroup.zip'
os.rename(tmpfile_path, new_zip_path)
## re-opening the zipfile with new name
z = zipfile.ZipFile(new_zip_path, 'r')
response = FileIter(z.fp)
return response
However, this is the Response I get in the browser:
Could not convert return value of the view callable function newsite.static.zipper into a response object. The value returned was .
I suppose I am not using FileIter correctly.
UPDATE:
Since updating with Michael Merickel's suggestions, the FileIter function is working correctly. However, still lingering is a MIME type error that appears on the client (browser):
Resource interpreted as Document but transferred with MIME type application/zip: "http://newsite.local:6543/zipper?data=%7B%22ids%22%3A%5B6%2C7%5D%7D"
To better illustrate the issue, I have included a tiny .py and .pt file on Github: https://github.com/thapar/zipper-fix
FileIter is not a response object, just like your error message says. It is an iterable that can be used for the response body, that's it. Also the ZipFile can accept a file object, which is more useful here than a file path. Let's try writing into the tmpfile, then rewinding that file pointer back to the start, and using it to write out without doing any fancy renaming.
import os
import zipfile
import tempfile
from pyramid.response import FileIter
def zipper(request):
_temp_path = request.registry.settings['_temp']
fp = tempfile.NamedTemporaryFile('w+b', dir=_temp_path, delete=True)
## creating zipfile and adding files
z = zipfile.ZipFile(fp, "w")
z.write('somefile1.txt')
z.write('somefile2.txt')
z.close()
# rewind fp back to start of the file
fp.seek(0)
response = request.response
response.content_type = 'application/zip'
response.app_iter = FileIter(fp)
return response
I changed the mode on NamedTemporaryFile to 'w+b' as per the docs to allow the file to be written to and read from.
current Pyramid version has 2 convenience classes for this use case- FileResponse, FileIter. The snippet below will serve a static file. I ran this code - the downloaded file is named "download" like the view name. To change the file name and more set the Content-Disposition header or have a look at the arguments of pyramid.response.Response.
from pyramid.response import FileResponse
#view_config(name="download")
def zipper(request):
path = 'path_to_file'
return FileResponse(path, request) #passing request is required
docs:
http://docs.pylonsproject.org/projects/pyramid/en/latest/api/response.html#
hint: extract the Zip logic from the view if possible
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.