Once the contents of a gzip file is extracted into a string called text, it looks like gibberish. How can I turn it into something human-readable?
with open("zipped_ex.gz.2016") as f:
text = f.read()
print text
Note: I'm not searching for a way to go from zipper_ex_gz.2016 to the contents. Instead, I'm searching for a way to go from the bytestring to the contents.
import gzip
with gzip.GzipFile("zipped_ex.gz.2016") as f:
text = f.read()
print text
On the disk, the file is a binary blop that is humanly unreadable.
To work with the data inside the archive you need to some how extract it.
In this case, in memory via the GzipFile module that decompresses the archive "on the fly" so when you do f.read() you get the archive contents, not the binary content that is the archive on your disk.
The same module can be used on a bytes string:
import io
import gzip
f = io.BytesIO(b"Your compressed gzip-file content here")
with gzip.GzipFile(fileobj=f) as fh:
plain_text = fh.read()
print(plain_text)
Note: gzip files are in fact a single data unit compressed with the gzip format, obviously. But if you want to work with a tar file within the gzip file if you have numerous text files compressed via tar, have a look at this question: How do I compress a folder with the Python GZip module?
Related
I am currently writing json files to disk using
print('writing to disk .... ')
f = open('mypath/myfile, 'wb')
f.write(getjsondata.read())
f.close()
Which works perfectly, except that the json files are very large and I would like to compress them. How can I do that automatically? What should I do?
Thanks!
Python has a standard module for zlib, which can compress and decompress data for you. You can use this immediately on your data and write (and read) a custom format, or use the module gzip, which wraps the inner workings of zlib to read and write gzip compatible files, while
automatically compressing or decompressing the data so that it looks like an ordinary file object.
It thus neatly replaces the default open format to interact with files, and all you need is this:
import gzip
print('writing to disk .... ')
with gzip.open('mypath/myfile', 'wb') as f:
f.write(getjsondata.read())
(with a change in the open line because I highly recommend using the with syntax to handle file objects.)
I have just hit an endpoint and can pull down a gzip compressed file.
I have tried saving it and extracting the csv inside but I keep getting errors around encoding whether I try casting from its current state in binary to utf-8/utf-16.
To write to the saved gzip I write in binary mode:
r = requests.get(url, auth=auth, stream=True)
with gzip.open('file.gz', 'wb') as f:
f.write(r.content)
Where r.content looks like:
b'PK\x03\x04\x14\x00\x08\x08\x08\x00f\x8dKM\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00A\x00\x00\x00RANKTRACKING_report_created_at_11_10_18_17_41-20181011-174141.csv\xec\xbdk\x8f\xe3V\x96\xae\xf9}\x80\xf9\x0f\ ... '
To extract the file on my machine manually I first have to extract to zip and then I can extract that to get the csv. I have tried the same there but ran into encoding errors there too.
Looking for a way to pull out this csv so I can print lines in python console.
That's not a gzip file. That's a zip file. You are then taking the zip file that you retrieved from the URL, and trying to compress it again as a gzip file. So now you have a zip file inside a gzip file. You have moved one step further away from extracting the CSV contents, as opposed to one step closer.
You need to use zipfile to extract the contents of the zip file that you downloaded.
I want to emulate the behavior of gzip -d <file.gz> within a Python script.
The compressed GZIP file is decompressed and written as a file with the same file name as the original GZIP file without the .gz extension.
file.abc.gz --> file.abc
It's not obvious how to do this using the gzip library, all the examples in the docs are for compressing data arrays, and I've not yet found a good example from research.
Edit
I've tried the below using tarfile module, but unfortunately it's not working, I think since the GZIP file wasn't created with tar.
# get the zipped file's contents list, extract the file
with tarfile.TarFile(local_zipped_filename) as tar_file:
# list the contents, make sure we only extract the expected named file
members = tar_file.getmembers()
for member in members:
if member.name == filename_unzipped:
members_to_extract = [member]
tar_file.extractall(path=destination_dir, members=members_to_extract)
break # we've extracted our file, done
import gzip, shutil
with gzip.open('file.abc.gz', 'r') as f_in, open('file.abc', 'wb') as f_out:
shutil.copyfileobj(f_in, f_out)
The gzip module provides a file-like object with the decompressed content of a gzip file; the shutil module provides a convenient helper for copying content from one file-like object to another.
This is a simple inversion of an example given in the official documentation:
Example of how to GZIP compress an existing file:
import gzip
import shutil
with open('/home/joe/file.txt', 'rb') as f_in:
with gzip.open('/home/joe/file.txt.gz', 'wb') as f_out:
shutil.copyfileobj(f_in, f_out)
You can use the tarfile module to what you are asking.
Example:
import tarfile
tar = tarfile.open("test.tar.gz")
tar.extractall()
tar.close()
How to decompress *.bz2 file in memory with python?
The bz2 file comes from a csv file.
I use the code below to decompress it in memory, it works, but it brings some dirty data such as filename of the csv file and author name of it, is there any other better way to handle it?
#!/usr/bin/python
# -*- coding: utf-8 -*-
import StringIO
import bz2
with open("/app/tmp/res_test.tar.bz2", "rb") as f:
content = f.read()
compressedFile = StringIO.StringIO(content)
decompressedFile = bz2.decompress(compressedFile.buf)
compressedFile.seek(0)
with open("/app/tmp/decompress_test", 'w') as outfile:
outfile.write(decompressedFile)
I found this question, it is in gzip, however my data is in bz2 format, I try to do as instructed in it, but it seems that bz2 could not handle it in this way.
Edit:
No matter the answer of #metatoaster or the code above, both of them will bring some more dirty data into the final decompressed file.
For example: my original data is attached below and in csv format with the name res_test.csv:
Then I cd into the directory where the file is in and compress it with tar -cjf res_test.tar.bz2 res_test.csv and get the compressed file res_test.tar.bz2, this file could simulate the bz2 data that I will get from internet and I wish to decompress it in memory without cache it into disk first, but what I get is data below and contains too much dirty data:
The data is still there, but submerged in noise, does it possible to decompress it into pure data just the same as the original data instead of decompress it and extract real data from too much noise?
For generic bz2 decompression, BZ2File class may be used.
from bz2 import BZ2File
with BZ2File("/app/tmp/res_test.tar.bz2") as f:
content = f.read()
content should contain the decompressed contents of the file.
However, given that this is a tar file (an archive file that is normally extracted to disk as a directory of files), the tarfile module could be used instead, and it has extended mode flags for handling bz2. Assuming the target file contains a res_test.csv, the following can be used
tf = tarfile.open('/app/tmp/res_test.tar.bz2', 'r:bz2')
csvfile = tf.extractfile('res_test.csv').read()
The r:bz2 flag opens the tar archive in a way that makes it possible to seek backwards, which is important as the alternative method r|bz2 makes it impractical to call extract files from the members it return by extractfile. The second line simply calls extractfile to return the contents of 'res_test.csv' from the archive file as a string.
The transparent open mode ('r:*') is typically recommended, however, so if the input tar file is compressed using gzip instead no failure will be encountered.
Naturally, the tarfile module has a lower level open method which may be used on arbitrary stream objects. If the file was already opened using BZ2File already, this can also be used
with BZ2File("/app/tmp/res_test.tar.bz2") as f:
tf = tarfile.open(fileobj=f, mode='r:')
csvfile = tf.extractfile('res_test.csv').read()
I have another doubt related to reading the dat file.
The file format is DAT file (.dat)
The content inside the file is in bytes.
When I tried the run open file code, the program built and ran successfully. However, the python shell has no output (I can't see the contents from the file).
Since the content inside the file is in bytes, should I modify the code ? What is the code to use for bytes?
Thank you.
There is no "DAT" file format and, as you say, the file contains bytes - as do all files.
It's possible that the file contains binary data for which it's best to open the file in binary mode. You do that by specifying b as part of the mode parameter to open(), like this:
f = open('file.dat', 'rb')
data = f.read() # read the entire file into data
print(data)
f.close()
Note that the full mode parameter is set to rb which means open the file in binary mode for reading.
A better way is to use with:
with open('file.dat', 'rb') as f:
data = f.read()
print(data)
No need to explicitly close the file.
If you know that the file contains text, possibly encoded in some specific encoding, e.g. UTF8, then you can specify the encoding when you open the file (Python 3):
with open('file.dat', encoding='UTF8') as f:
for line in f:
print(line)
In Python 2 you can use io.open().