I have up to 8 seperate Python processes creating temp files in a shared folder. Then I\'d like the controlling process to append all the temp files in a certain order into
In this code, you can indicate the path and name of the input/output files, and it will create the final big file in that path:
import os
dir_name = "Your_Desired_Folder/Goes_Here" #path
input_files_names = ["File1.txt", "File2.txt", "File3.txt"] #input files
file_name_out = "Big_File.txt" #choose a name for the output file
file_output = os.path.join(dir_name, file_name_out)
fout = open(file_output, "w")
for tempfile in input_files_names:
inputfile = os.path.join(dir_name, tempfile)
fin = open(inputfile, 'r')
for line in fin:
fout.write(line)
fin.close()
fout.close()
Simple & Efficient way to copy data from multiple files to one big file, Before that you need to rename your files to (int) eg. 1,2,3,4...etc, Code:
#Rename Files First
import os
path = 'directory_name'
files = os.listdir(path)
i = 1
for file in files:
os.rename(os.path.join(path, file), os.path.join(path, str(i)+'.txt'))
i = i+1
# Code For Copying Data from Multiple files
import os
i = 1
while i<50:
filename = i
for filename in os.listdir("directory_name"):
# %s is your filename # .txt is file extension
f = open("%s.txt" % i,'r')
fout = open("output_filename", "a")
for line in f:
fout.write(line)
i += 1
I feel a bit stupid to add another answer after 8 years and so many answers, but I arrived here by the "append to file" title, and didn't see the right solution for appending to an existing binary file with buffered read/write.
So here is the basic way to do that:
def append_file_to_file(_from, _to):
block_size = 1024*1024
with open(_to, "ab") as outfile, open(_from, "rb") as infile:
while True:
input_block = infile.read(block_size)
if not input_block:
break
outfile.write(input_block)
Given this building block, you can use:
for filename in ['a.bin','b.bin','c.bin']:
append_file_to_file(filename, 'outfile.bin')
Use fileinput:
with open("bigfile.txt", "w") as big_file:
with fileinput.input(files=tempfiles) as inputs:
for line in inputs:
big_file.write(line)
This is more memory efficient than @RafeKettler's answer as it doesn't need to read the whole file into memory before writing to big_file
.
Try this. It's very fast (much faster than line-by-line, and shouldn't cause a VM thrash for large files), and should run on about anything, including CPython 2.x, CPython 3.x, Pypy, Pypy3 and Jython. Also it should be highly OS-agnostic. Also, it makes no assumptions about file encodings.
#!/usr/local/cpython-3.4/bin/python3
'''Cat 3 files to one: example code'''
import os
def main():
'''Main function'''
input_filenames = ['a', 'b', 'c']
block_size = 1024 * 1024
if hasattr(os, 'O_BINARY'):
o_binary = getattr(os, 'O_BINARY')
else:
o_binary = 0
output_file = os.open('output-file', os.O_WRONLY | o_binary)
for input_filename in input_filenames:
input_file = os.open(input_filename, os.O_RDONLY | o_binary)
while True:
input_block = os.read(input_file, block_size)
if not input_block:
break
os.write(output_file, input_block)
os.close(input_file)
os.close(output_file)
main()
There is one (nontrivial) optimization I've left out: It's better to not assume anything about a good blocksize, instead using a bunch of random ones, and slowly backing off the randomization to focus on the good ones (sometimes called "simulated annealing"). But that's a lot more complexity for little actual performance benefit.
You could also make the os.write keep track of its return value and restart partial writes, but that's only really necessary if you're expecting to receive (nonterminal) *ix signals.
There's also the fileinput class in Python 3, which is perfect for this sort of situation