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How to read the last line of a file in Python?
(10 answers)
Closed 1 year ago.
I have a csv file that grows until it reaches approximately 48M of lines.
Before adding new lines to it, I need to read the last line.
I tried the code below, but it got too slow and I need a faster alternative:
def return_last_line(filepath):
with open(filepath,'r') as file:
for x in file:
pass
return x
return_last_line('lala.csv')
Here is my take, in python:
I created a function that lets you choose how many last lines, because the last lines may be empty.
def get_last_line(file, how_many_last_lines = 1):
# open your file using with: safety first, kids!
with open(file, 'r') as file:
# find the position of the end of the file: end of the file stream
end_of_file = file.seek(0,2)
# set your stream at the end: seek the final position of the file
file.seek(end_of_file)
# trace back each character of your file in a loop
n = 0
for num in range(end_of_file+1):
file.seek(end_of_file - num)
# save the last characters of your file as a string: last_line
last_line = file.read()
# count how many '\n' you have in your string:
# if you have 1, you are in the last line; if you have 2, you have the two last lines
if last_line.count('\n') == how_many_last_lines:
return last_line
get_last_line('lala.csv', 2)
This lala.csv has 48 million lines, such as in your example. It took me 0 seconds to get the last line.
Here is code for finding the last line of a file mmap, and it should work on Unixen and derivatives and Windows alike (I've tested this on Linux only, please tell me if it works on Windows too ;), i.e. pretty much everywhere where it matters. Since it uses memory mapped I/O it could be expected to be quite performant.
It expects that you can map the entire file into the address space of a processor - should be OK for 50M file everywhere but for 5G file you'd need a 64-bit processor or some extra slicing.
import mmap
def iterate_lines_backwards(filename):
with open(filename, "rb") as f:
# memory-map the file, size 0 means whole file
with mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ) as mm:
start = len(mm)
while start > 0:
start, prev = mm.rfind(b"\n", 0, start), start
slice = mm[start + 1:prev + 1]
# if the last character in the file was a '\n',
# technically the empty string after that is not a line.
if slice:
yield slice.decode()
def get_last_nonempty_line(filename):
for line in iterate_lines_backwards(filename):
if stripped := line.rstrip("\r\n"):
return stripped
print(get_last_nonempty_line("datafile.csv"))
As a bonus there is a generator iterate_lines_backwards that would efficiently iterate over the lines of a file in reverse for any number of lines:
print("Iterating the lines of datafile.csv backwards")
for l in iterate_lines_backwards("datafile.csv"):
print(l, end="")
This is generally a rather tricky thing to do. A very efficient way of getting a chunk that includes the last lines is the following:
import os
def get_last_lines(path, offset=500):
""" An efficient way to get the last lines of a file.
IMPORTANT:
1. Choose offset to be greater than
max_line_length * number of lines that you want to recover.
2. This will throw an os.OSError if the file is shorter than
the offset.
"""
with path.open("rb") as f:
f.seek(-offset, os.SEEK_END)
while f.read(1) != b"\n":
f.seek(-2, os.SEEK_CUR)
return f.readlines()
You need to know the maximum line length though and ensure that the file is at least one offset long!
To use it, do the following:
from pathlib import Path
n_last_lines = 10
last_bit_of_file = get_last_lines(Path("/path/to/my/file"))
real_last_n_lines = last_bit_of_file[-10:]
Now finally you need to decode the binary to strings:
real_last_n_lines_non_binary = [x.decode() for x in real_last_n_lines]
Probably all of this could be wrapped in one more convenient function.
If you are running your code in a Unix based environment, you can execute tail shell command from Python to read the last line:
import subprocess
subprocess.run(['tail', '-n', '1', '/path/to/lala.csv'])
You could additionally store the last line in a separate file, which you update whenever you add new lines to the main file.
This works well for me:
https://pypi.org/project/file-read-backwards/
from file_read_backwards import FileReadBackwards
with FileReadBackwards("/tmp/file", encoding="utf-8") as frb:
# getting lines by lines starting from the last line up
for l in frb:
if l:
print(l)
break
An easy way to do this is with deque:
from collections import deque
def return_last_line(filepath):
with open(filepath,'r') as f:
q = deque(f, 1)
return q[0]
since seek() returns the position that it moved to, you can use it to move backward and position the cursor to the beginning of the last line.
with open("test.txt") as f:
p = f.seek(0,2)-1 # ignore trailing end of line
while p>0 and f.read(1)!="\n": # detect end of line (or start of file)
p = f.seek(p-1,0) # search backward
lastLine = f.read().strip() # read from start of last line
print(lastLine)
To get the last non-empty line, you can add a while loop around the search:
with open("test.txt") as f:
p,lastLine = f.seek(0,2),"" # start from end of file
while p and not lastLine: # want last non-empty line
while p>0 and f.read(1)!="\n": # detect end of line (or start of file)
p = f.seek(p-1,0) # search backward
lastLine = f.read().strip() # read from start of last line
Based on #kuropan
Faster and shorter:
# 60.lastlinefromlargefile.py
# juanfc 2021-03-17
import os
def get_last_lines(fileName, offset=500):
""" An efficient way to get the last lines of a file.
IMPORTANT:
1. Choose offset to be greater than
max_line_length * number of lines that you want to recover.
2. This will throw an os.OSError if the file is shorter than
the offset.
"""
with open(fileName, "rb") as f:
f.seek(-offset, os.SEEK_END)
return f.read().decode('utf-8').rstrip().split('\n')[-1]
print(get_last_lines('60.lastlinefromlargefile.py'))
I have a text file which contains a time stamp on each line. My goal is to find the time range. All the times are in order so the first line will be the earliest time and the last line will be the latest time. I only need the very first and very last line. What would be the most efficient way to get these lines in python?
Note: These files are relatively large in length, about 1-2 million lines each and I have to do this for several hundred files.
To read both the first and final line of a file you could...
open the file, ...
... read the first line using built-in readline(), ...
... seek (move the cursor) to the end of the file, ...
... step backwards until you encounter EOL (line break) and ...
... read the last line from there.
def readlastline(f):
f.seek(-2, 2) # Jump to the second last byte.
while f.read(1) != b"\n": # Until EOL is found ...
f.seek(-2, 1) # ... jump back, over the read byte plus one more.
return f.read() # Read all data from this point on.
with open(file, "rb") as f:
first = f.readline()
last = readlastline(f)
Jump to the second last byte directly to prevent trailing newline characters to cause empty lines to be returned*.
The current offset is pushed ahead by one every time a byte is read so the stepping backwards is done two bytes at a time, past the recently read byte and the byte to read next.
The whence parameter passed to fseek(offset, whence=0) indicates that fseek should seek to a position offset bytes relative to...
0 or os.SEEK_SET = The beginning of the file.
1 or os.SEEK_CUR = The current position.
2 or os.SEEK_END = The end of the file.
* As would be expected as the default behavior of most applications, including print and echo, is to append one to every line written and has no effect on lines missing trailing newline character.
Efficiency
1-2 million lines each and I have to do this for several hundred files.
I timed this method and compared it against against the top answer.
10k iterations processing a file of 6k lines totalling 200kB: 1.62s vs 6.92s.
100 iterations processing a file of 6k lines totalling 1.3GB: 8.93s vs 86.95.
Millions of lines would increase the difference a lot more.
Exakt code used for timing:
with open(file, "rb") as f:
first = f.readline() # Read and store the first line.
for last in f: pass # Read all lines, keep final value.
Amendment
A more complex, and harder to read, variation to address comments and issues raised since.
Return empty string when parsing empty file, raised by comment.
Return all content when no delimiter is found, raised by comment.
Avoid relative offsets to support text mode, raised by comment.
UTF16/UTF32 hack, noted by comment.
Also adds support for multibyte delimiters, readlast(b'X<br>Y', b'<br>', fixed=False).
Please note that this variation is really slow for large files because of the non-relative offsets needed in text mode. Modify to your need, or do not use it at all as you're probably better off using f.readlines()[-1] with files opened in text mode.
#!/bin/python3
from os import SEEK_END
def readlast(f, sep, fixed=True):
r"""Read the last segment from a file-like object.
:param f: File to read last line from.
:type f: file-like object
:param sep: Segment separator (delimiter).
:type sep: bytes, str
:param fixed: Treat data in ``f`` as a chain of fixed size blocks.
:type fixed: bool
:returns: Last line of file.
:rtype: bytes, str
"""
bs = len(sep)
step = bs if fixed else 1
if not bs:
raise ValueError("Zero-length separator.")
try:
o = f.seek(0, SEEK_END)
o = f.seek(o-bs-step) # - Ignore trailing delimiter 'sep'.
while f.read(bs) != sep: # - Until reaching 'sep': Read sep-sized block
o = f.seek(o-step) # and then seek to the block to read next.
except (OSError,ValueError): # - Beginning of file reached.
f.seek(0)
return f.read()
def test_readlast():
from io import BytesIO, StringIO
# Text mode.
f = StringIO("first\nlast\n")
assert readlast(f, "\n") == "last\n"
# Bytes.
f = BytesIO(b'first|last')
assert readlast(f, b'|') == b'last'
# Bytes, UTF-8.
f = BytesIO("X\nY\n".encode("utf-8"))
assert readlast(f, b'\n').decode() == "Y\n"
# Bytes, UTF-16.
f = BytesIO("X\nY\n".encode("utf-16"))
assert readlast(f, b'\n\x00').decode('utf-16') == "Y\n"
# Bytes, UTF-32.
f = BytesIO("X\nY\n".encode("utf-32"))
assert readlast(f, b'\n\x00\x00\x00').decode('utf-32') == "Y\n"
# Multichar delimiter.
f = StringIO("X<br>Y")
assert readlast(f, "<br>", fixed=False) == "Y"
# Make sure you use the correct delimiters.
seps = { 'utf8': b'\n', 'utf16': b'\n\x00', 'utf32': b'\n\x00\x00\x00' }
assert "\n".encode('utf8' ) == seps['utf8']
assert "\n".encode('utf16')[2:] == seps['utf16']
assert "\n".encode('utf32')[4:] == seps['utf32']
# Edge cases.
edges = (
# Text , Match
("" , "" ), # Empty file, empty string.
("X" , "X" ), # No delimiter, full content.
("\n" , "\n"),
("\n\n", "\n"),
# UTF16/32 encoded U+270A (b"\n\x00\n'\n\x00"/utf16)
(b'\n\xe2\x9c\x8a\n'.decode(), b'\xe2\x9c\x8a\n'.decode()),
)
for txt, match in edges:
for enc,sep in seps.items():
assert readlast(BytesIO(txt.encode(enc)), sep).decode(enc) == match
if __name__ == "__main__":
import sys
for path in sys.argv[1:]:
with open(path) as f:
print(f.readline() , end="")
print(readlast(f,"\n"), end="")
docs for io module
with open(fname, 'rb') as fh:
first = next(fh).decode()
fh.seek(-1024, 2)
last = fh.readlines()[-1].decode()
The variable value here is 1024: it represents the average string length. I choose 1024 only for example. If you have an estimate of average line length you could just use that value times 2.
Since you have no idea whatsoever about the possible upper bound for the line length, the obvious solution would be to loop over the file:
for line in fh:
pass
last = line
You don't need to bother with the binary flag you could just use open(fname).
ETA: Since you have many files to work on, you could create a sample of couple of dozens of files using random.sample and run this code on them to determine length of last line. With an a priori large value of the position shift (let say 1 MB). This will help you to estimate the value for the full run.
Here's a modified version of SilentGhost's answer that will do what you want.
with open(fname, 'rb') as fh:
first = next(fh)
offs = -100
while True:
fh.seek(offs, 2)
lines = fh.readlines()
if len(lines)>1:
last = lines[-1]
break
offs *= 2
print first
print last
No need for an upper bound for line length here.
Can you use unix commands? I think using head -1 and tail -n 1 are probably the most efficient methods. Alternatively, you could use a simple fid.readline() to get the first line and fid.readlines()[-1], but that may take too much memory.
This is my solution, compatible also with Python3. It does also manage border cases, but it misses utf-16 support:
def tail(filepath):
"""
#author Marco Sulla (marcosullaroma#gmail.com)
#date May 31, 2016
"""
try:
filepath.is_file
fp = str(filepath)
except AttributeError:
fp = filepath
with open(fp, "rb") as f:
size = os.stat(fp).st_size
start_pos = 0 if size - 1 < 0 else size - 1
if start_pos != 0:
f.seek(start_pos)
char = f.read(1)
if char == b"\n":
start_pos -= 1
f.seek(start_pos)
if start_pos == 0:
f.seek(start_pos)
else:
char = ""
for pos in range(start_pos, -1, -1):
f.seek(pos)
char = f.read(1)
if char == b"\n":
break
return f.readline()
It's ispired by Trasp's answer and AnotherParker's comment.
First open the file in read mode.Then use readlines() method to read line by line.All the lines stored in a list.Now you can use list slices to get first and last lines of the file.
a=open('file.txt','rb')
lines = a.readlines()
if lines:
first_line = lines[:1]
last_line = lines[-1]
w=open(file.txt, 'r')
print ('first line is : ',w.readline())
for line in w:
x= line
print ('last line is : ',x)
w.close()
The for loop runs through the lines and x gets the last line on the final iteration.
with open("myfile.txt") as f:
lines = f.readlines()
first_row = lines[0]
print first_row
last_row = lines[-1]
print last_row
Here is an extension of #Trasp's answer that has additional logic for handling the corner case of a file that has only one line. It may be useful to handle this case if you repeatedly want to read the last line of a file that is continuously being updated. Without this, if you try to grab the last line of a file that has just been created and has only one line, IOError: [Errno 22] Invalid argument will be raised.
def tail(filepath):
with open(filepath, "rb") as f:
first = f.readline() # Read the first line.
f.seek(-2, 2) # Jump to the second last byte.
while f.read(1) != b"\n": # Until EOL is found...
try:
f.seek(-2, 1) # ...jump back the read byte plus one more.
except IOError:
f.seek(-1, 1)
if f.tell() == 0:
break
last = f.readline() # Read last line.
return last
Nobody mentioned using reversed:
f=open(file,"r")
r=reversed(f.readlines())
last_line_of_file = r.next()
Getting the first line is trivially easy. For the last line, presuming you know an approximate upper bound on the line length, os.lseek some amount from SEEK_END find the second to last line ending and then readline() the last line.
with open(filename, "rb") as f:#Needs to be in binary mode for the seek from the end to work
first = f.readline()
if f.read(1) == '':
return first
f.seek(-2, 2) # Jump to the second last byte.
while f.read(1) != b"\n": # Until EOL is found...
f.seek(-2, 1) # ...jump back the read byte plus one more.
last = f.readline() # Read last line.
return last
The above answer is a modified version of the above answers which handles the case that there is only one line in the file
I'm facing a problem in reading random rows from a large csv file and moving it to another CSV file using 0.18.1 pandas and 2.7.10 Python on Windows.
I want to load only the randomly selected rows into the memory and move them to another CSV. I don't want to load the entire content of first CSV into memory.
This is the code I used:
import random
file_size = 100
f = open("customers.csv",'r')
o = open("train_select.csv", 'w')
for i in range(0, 50):
offset = random.randrange(file_size)
f.seek(offset)
f.readline()
random_line = f.readline()
o.write(random_line)
The current output looks something like this:
2;flhxu-name;tum-firstname; 17520;buo-city;1966/04/24;wfyz-street; 96;GA;GEORGIA
1;jwcdf-name;fsj-firstname; 13520;oem-city;1954/02/07;amrb-street; 145;AK;ALASKA
1;jwcdf-name;fsj-firstname; 13520;oem-city;1954/02/07;amrb-street; 145;AK;ALASKA
My problems are 2 fold:
I want to see the header also in the second csv and not just the rows.
A row should be selected by random function only once.
The output should be something like this:
id;name;firstname;zip;city;birthdate;street;housenr;stateCode;state
2;flhxu-name;tum-firstname; 17520;buo-city;1966/04/24;wfyz-street; 96;GA;GEORGIA
1;jwcdf-name;fsj-firstname; 13520;oem-city;1954/02/07;amrb-street; 145;AK;ALASKA
You have do simpler than that:
first, read the customers file fully, title is a special case, keep it out.
shuffle the list of lines (that's what you were looking for)
write back title + shuffled lines
code:
import random
with open("customers.csv",'r') as f:
title = f.readline()
lines = f.readlines()
random.shuffle(lines)
with open("train_select.csv", 'w') as f:
f.write(title)
f.writelines(lines)
EDIT: if you don't want to hold the whole file in memory, here's an alternative. The only drawback is that you have to read the file once (but not store in memory) to compute line offsets:
import random
input_file = "customers.csv"
line_offsets = list()
# just read the title
with open(input_file,'r') as f:
title = f.readline()
# store offset of the first
while True:
# store offset of the next line start
line_offsets.append(f.tell())
line = f.readline()
if line=="":
break
# now shuffle the offsets
random.shuffle(line_offsets)
# and write the output file
with open("train_select.csv", 'w') as fw:
fw.write(title)
for offset in line_offsets:
# seek to a line start
f.seek(offset)
fw.write(f.readline())
At OP request, and since my 2 previous implementations had to read the input file, here's a more complex implementation where the file is not read in advance.
It uses bisect to store the couples of offsets of the lines, and a minimum line len (to be configured) in order to avoid that the random list is too long for nothing.
Basically, the program generates randomly ordered offsets ranging from offset of the second line (title line skipped) to the end of file, by step of minimum_line_len.
For each offset, it checks if line has not already been read (using bisect, which is fast but further testing is complex because of the corner cases).
- if not read, skip back to find previous linefeed (that is reading the file, can't do otherwise) write it in the output file, store the start/end offsets in the couple list
- if already read, skip
the code:
import random,os,bisect
input_file = "csv2.csv"
input_size = os.path.getsize(input_file)
smallest_line_len = 4
line_offsets = []
# just read the title
with open(input_file,'r') as f, open("train_select.csv", 'w') as fw:
# read title and write it back
title = f.readline()
fw.write(title)
# generate offset list, starting from current pos to the end of file
# with a step of min line len to avoid generating too many numbers
# (this can be 1 but that will take a while)
offset_list = list(range(f.tell(),input_size,smallest_line_len))
# shuffle the list at random
random.shuffle(offset_list)
# now loop through the offsets
for offset in offset_list:
# look if the offset is already contained in the list of sorted tuples
insertion_point = bisect.bisect(line_offsets,(offset,0))
if len(line_offsets)>0 and insertion_point == len(line_offsets) and line_offsets[-1][1]>offset:
# bisect tells to insert at the end: check if within last couple boundary: if so, already processed
continue
elif insertion_point < len(line_offsets) and (offset==line_offsets[insertion_point][0] or
(0 < insertion_point and line_offsets[insertion_point-1][0]<=offset<=line_offsets[insertion_point-1][1])):
# offset is already known, line has already been processed: skip
continue
else:
# offset is not known: rewind until we meet an end of line
f.seek(offset)
while True:
c=f.read(1)
if c=="\n":
# we found the line terminator of the previous line: OK
break
offset -= 1
f.seek(offset)
# now store the current position: start of the current line
line_start = offset+1
# now read the line fully
line = f.readline()
# now compute line end (approx..)
line_end = f.tell() - 1
# and insert the "line" in the sorted list
line_offsets.insert(insertion_point,(line_start,line_end))
fw.write(line)
if
I have a huge text file (~1GB) and sadly the text editor I use won't read such a large file. However, if I can just split it into two or three parts I'll be fine, so, as an exercise I wanted to write a program in python to do it.
What I think I want the program to do is to find the size of a file, divide that number into parts, and for each part, read up to that point in chunks, writing to a filename.nnn output file, then read up-to the next line-break and write that, then close the output file, etc. Obviously the last output file just copies to the end of the input file.
Can you help me with the key filesystem related parts: filesize, reading and writing in chunks and reading to a line-break?
I'll be writing this code test-first, so there's no need to give me a complete answer, unless its a one-liner ;-)
linux has a split command
split -l 100000 file.txt
would split into files of equal 100,000 line size
Check out os.stat() for file size and file.readlines([sizehint]). Those two functions should be all you need for the reading part, and hopefully you know how to do the writing :)
Now, there is a pypi module available that you can use to split files of any size into chunks. Check this out
https://pypi.org/project/filesplit/
As an alternative method, using the logging library:
>>> import logging.handlers
>>> log = logging.getLogger()
>>> fh = logging.handlers.RotatingFileHandler("D://filename.txt",
maxBytes=2**20*100, backupCount=100)
# 100 MB each, up to a maximum of 100 files
>>> log.addHandler(fh)
>>> log.setLevel(logging.INFO)
>>> f = open("D://biglog.txt")
>>> while True:
... log.info(f.readline().strip())
Your files will appear as follows:
filename.txt (end of file)
filename.txt.1
filename.txt.2
...
filename.txt.10 (start of file)
This is a quick and easy way to make a huge log file match your RotatingFileHandler implementation.
This generator method is a (slow) way to get a slice of lines without blowing up your memory.
import itertools
def slicefile(filename, start, end):
lines = open(filename)
return itertools.islice(lines, start, end)
out = open("/blah.txt", "w")
for line in slicefile("/python27/readme.txt", 10, 15):
out.write(line)
don't forget seek() and mmap() for random access to files.
def getSomeChunk(filename, start, len):
fobj = open(filename, 'r+b')
m = mmap.mmap(fobj.fileno(), 0)
return m[start:start+len]
While Ryan Ginstrom's answer is correct, it does take longer than it should (as he has already noted). Here's a way to circumvent the multiple calls to itertools.islice by successively iterating over the open file descriptor:
def splitfile(infilepath, chunksize):
fname, ext = infilepath.rsplit('.',1)
i = 0
written = False
with open(infilepath) as infile:
while True:
outfilepath = "{}{}.{}".format(fname, i, ext)
with open(outfilepath, 'w') as outfile:
for line in (infile.readline() for _ in range(chunksize)):
outfile.write(line)
written = bool(line)
if not written:
break
i += 1
You can use wc and split (see the respective manpages) to get the desired effect. In bash:
split -dl$((`wc -l 'filename'|sed 's/ .*$//'` / 3 + 1)) filename filename-chunk.
produces 3 parts of the same linecount (with a rounding error in the last, of course), named filename-chunk.00 to filename-chunk.02.
I've written the program and it seems to work fine. So thanks to Kamil Kisiel for getting me started.
(Note that FileSizeParts() is a function not shown here)
Later I may get round to doing a version that does a binary read to see if its any quicker.
def Split(inputFile,numParts,outputName):
fileSize=os.stat(inputFile).st_size
parts=FileSizeParts(fileSize,numParts)
openInputFile = open(inputFile, 'r')
outPart=1
for part in parts:
if openInputFile.tell()<fileSize:
fullOutputName=outputName+os.extsep+str(outPart)
outPart+=1
openOutputFile=open(fullOutputName,'w')
openOutputFile.writelines(openInputFile.readlines(part))
openOutputFile.close()
openInputFile.close()
return outPart-1
usage - split.py filename splitsizeinkb
import os
import sys
def getfilesize(filename):
with open(filename,"rb") as fr:
fr.seek(0,2) # move to end of the file
size=fr.tell()
print("getfilesize: size: %s" % size)
return fr.tell()
def splitfile(filename, splitsize):
# Open original file in read only mode
if not os.path.isfile(filename):
print("No such file as: \"%s\"" % filename)
return
filesize=getfilesize(filename)
with open(filename,"rb") as fr:
counter=1
orginalfilename = filename.split(".")
readlimit = 5000 #read 5kb at a time
n_splits = filesize//splitsize
print("splitfile: No of splits required: %s" % str(n_splits))
for i in range(n_splits+1):
chunks_count = int(splitsize)//int(readlimit)
data_5kb = fr.read(readlimit) # read
# Create split files
print("chunks_count: %d" % chunks_count)
with open(orginalfilename[0]+"_{id}.".format(id=str(counter))+orginalfilename[1],"ab") as fw:
fw.seek(0)
fw.truncate()# truncate original if present
while data_5kb:
fw.write(data_5kb)
if chunks_count:
chunks_count-=1
data_5kb = fr.read(readlimit)
else: break
counter+=1
if __name__ == "__main__":
if len(sys.argv) < 3: print("Filename or splitsize not provided: Usage: filesplit.py filename splitsizeinkb ")
else:
filesize = int(sys.argv[2]) * 1000 #make into kb
filename = sys.argv[1]
splitfile(filename, filesize)
Here is a python script you can use for splitting large files using subprocess:
"""
Splits the file into the same directory and
deletes the original file
"""
import subprocess
import sys
import os
SPLIT_FILE_CHUNK_SIZE = '5000'
SPLIT_PREFIX_LENGTH = '2' # subprocess expects a string, i.e. 2 = aa, ab, ac etc..
if __name__ == "__main__":
file_path = sys.argv[1]
# i.e. split -a 2 -l 5000 t/some_file.txt ~/tmp/t/
subprocess.call(["split", "-a", SPLIT_PREFIX_LENGTH, "-l", SPLIT_FILE_CHUNK_SIZE, file_path,
os.path.dirname(file_path) + '/'])
# Remove the original file once done splitting
try:
os.remove(file_path)
except OSError:
pass
You can call it externally:
import os
fs_result = os.system("python file_splitter.py {}".format(local_file_path))
You can also import subprocess and run it directly in your program.
The issue with this approach is high memory usage: subprocess creates a fork with a memory footprint same size as your process and if your process memory is already heavy, it doubles it for the time that it runs. The same thing with os.system.
Here is another pure python way of doing this, although I haven't tested it on huge files, it's going to be slower but be leaner on memory:
CHUNK_SIZE = 5000
def yield_csv_rows(reader, chunk_size):
"""
Opens file to ingest, reads each line to return list of rows
Expects the header is already removed
Replacement for ingest_csv
:param reader: dictReader
:param chunk_size: int, chunk size
"""
chunk = []
for i, row in enumerate(reader):
if i % chunk_size == 0 and i > 0:
yield chunk
del chunk[:]
chunk.append(row)
yield chunk
with open(local_file_path, 'rb') as f:
f.readline().strip().replace('"', '')
reader = unicodecsv.DictReader(f, fieldnames=header.split(','), delimiter=',', quotechar='"')
chunks = yield_csv_rows(reader, CHUNK_SIZE)
for chunk in chunks:
if not chunk:
break
# Do something with your chunk here
Here is another example using readlines():
"""
Simple example using readlines()
where the 'file' is generated via:
seq 10000 > file
"""
CHUNK_SIZE = 5
def yield_rows(reader, chunk_size):
"""
Yield row chunks
"""
chunk = []
for i, row in enumerate(reader):
if i % chunk_size == 0 and i > 0:
yield chunk
del chunk[:]
chunk.append(row)
yield chunk
def batch_operation(data):
for item in data:
print(item)
with open('file', 'r') as f:
chunks = yield_rows(f.readlines(), CHUNK_SIZE)
for _chunk in chunks:
batch_operation(_chunk)
The readlines example demonstrates how to chunk your data to pass chunks to function that expects chunks. Unfortunately readlines opens the whole file in memory, its better to use the reader example for performance. Although if you can easily fit what you need into memory and need to process it in chunks this should suffice.
You can achieve splitting any file to chunks like below, here the CHUNK_SIZE is 500000 bytes(500kb) and content can be any file :
for idx,val in enumerate(get_chunk(content, CHUNK_SIZE)):
data=val
index=idx
def get_chunk(content,size):
for i in range(0,len(content),size):
yield content[i:i+size]
This worked for me
import os
fil = "inputfile"
outfil = "outputfile"
f = open(fil,'r')
numbits = 1000000000
for i in range(0,os.stat(fil).st_size/numbits+1):
o = open(outfil+str(i),'w')
segment = f.readlines(numbits)
for c in range(0,len(segment)):
o.write(segment[c]+"\n")
o.close()
I had a requirement to split csv files for import into Dynamics CRM since the file size limit for import is 8MB and the files we receive are much larger. This program allows user to input FileNames and LinesPerFile, and then splits the specified files into the requested number of lines. I can't believe how fast it works!
# user input FileNames and LinesPerFile
FileCount = 1
FileNames = []
while True:
FileName = raw_input('File Name ' + str(FileCount) + ' (enter "Done" after last File):')
FileCount = FileCount + 1
if FileName == 'Done':
break
else:
FileNames.append(FileName)
LinesPerFile = raw_input('Lines Per File:')
LinesPerFile = int(LinesPerFile)
for FileName in FileNames:
File = open(FileName)
# get Header row
for Line in File:
Header = Line
break
FileCount = 0
Linecount = 1
for Line in File:
#skip Header in File
if Line == Header:
continue
#create NewFile with Header every [LinesPerFile] Lines
if Linecount % LinesPerFile == 1:
FileCount = FileCount + 1
NewFileName = FileName[:FileName.find('.')] + '-Part' + str(FileCount) + FileName[FileName.find('.'):]
NewFile = open(NewFileName,'w')
NewFile.write(Header)
NewFile.write(Line)
Linecount = Linecount + 1
NewFile.close()
import subprocess
subprocess.run('split -l number_of_lines file_path', shell = True)
For example if you want 50000 lines in one files and path is /home/data then you can run below command
subprocess.run('split -l 50000 /home/data', shell = True)
If you are not sure how many lines to keep in split files but knows how many split you want then In Jupyter Notebook/Shell you can check total number of Lines using below command and then divide by total number of split you want
! wc -l file_path
in this case
! wc -l /home/data
And Just so you know output file will not have file extension but its same extension as input file You can change it manually if Windows
Or, a python version of wc and split:
lines = 0
for l in open(filename): lines += 1
Then some code to read the first lines/3 into one file, the next lines/3 into another , etc.
Is it possible to split a file? For example you have huge wordlist, I want to split it so that it becomes more than one file. How is this possible?
This one splits a file up by newlines and writes it back out. You can change the delimiter easily. This can also handle uneven amounts as well, if you don't have a multiple of splitLen lines (20 in this example) in your input file.
splitLen = 20 # 20 lines per file
outputBase = 'output' # output.1.txt, output.2.txt, etc.
# This is shorthand and not friendly with memory
# on very large files (Sean Cavanagh), but it works.
input = open('input.txt', 'r').read().split('\n')
at = 1
for lines in range(0, len(input), splitLen):
# First, get the list slice
outputData = input[lines:lines+splitLen]
# Now open the output file, join the new slice with newlines
# and write it out. Then close the file.
output = open(outputBase + str(at) + '.txt', 'w')
output.write('\n'.join(outputData))
output.close()
# Increment the counter
at += 1
A better loop for sli's example, not hogging memory :
splitLen = 20 # 20 lines per file
outputBase = 'output' # output.1.txt, output.2.txt, etc.
input = open('input.txt', 'r')
count = 0
at = 0
dest = None
for line in input:
if count % splitLen == 0:
if dest: dest.close()
dest = open(outputBase + str(at) + '.txt', 'w')
at += 1
dest.write(line)
count += 1
Solution to split binary files into chapters .000, .001, etc.:
FILE = 'scons-conversion.7z'
MAX = 500*1024*1024 # 500Mb - max chapter size
BUF = 50*1024*1024*1024 # 50GB - memory buffer size
chapters = 0
uglybuf = ''
with open(FILE, 'rb') as src:
while True:
tgt = open(FILE + '.%03d' % chapters, 'wb')
written = 0
while written < MAX:
if len(uglybuf) > 0:
tgt.write(uglybuf)
tgt.write(src.read(min(BUF, MAX - written)))
written += min(BUF, MAX - written)
uglybuf = src.read(1)
if len(uglybuf) == 0:
break
tgt.close()
if len(uglybuf) == 0:
break
chapters += 1
def split_file(file, prefix, max_size, buffer=1024):
"""
file: the input file
prefix: prefix of the output files that will be created
max_size: maximum size of each created file in bytes
buffer: buffer size in bytes
Returns the number of parts created.
"""
with open(file, 'r+b') as src:
suffix = 0
while True:
with open(prefix + '.%s' % suffix, 'w+b') as tgt:
written = 0
while written < max_size:
data = src.read(buffer)
if data:
tgt.write(data)
written += buffer
else:
return suffix
suffix += 1
def cat_files(infiles, outfile, buffer=1024):
"""
infiles: a list of files
outfile: the file that will be created
buffer: buffer size in bytes
"""
with open(outfile, 'w+b') as tgt:
for infile in sorted(infiles):
with open(infile, 'r+b') as src:
while True:
data = src.read(buffer)
if data:
tgt.write(data)
else:
break
Sure it's possible:
open input file
open output file 1
count = 0
for each line in file:
write to output file
count = count + 1
if count > maxlines:
close output file
open next output file
count = 0
import re
PATENTS = 'patent.data'
def split_file(filename):
# Open file to read
with open(filename, "r") as r:
# Counter
n=0
# Start reading file line by line
for i, line in enumerate(r):
# If line match with teplate -- <?xml --increase counter n
if re.match(r'\<\?xml', line):
n+=1
# This "if" can be deleted, without it will start naming from 1
# or you can keep it. It depends where is "re" will find at
# first time the template. In my case it was first line
if i == 0:
n = 0
# Write lines to file
with open("{}-{}".format(PATENTS, n), "a") as f:
f.write(line)
split_file(PATENTS)
As a result you will get:
patent.data-0
patent.data-1
patent.data-N
You can use use this pypi filesplit module.
This is a late answer, but a new question was linked here and none of the answers mentioned itertools.groupby.
Assuming you have a (huge) file file.txt that you want to split in chunks of MAXLINES lines file_part1.txt, ..., file_partn.txt, you could do:
with open(file.txt) as fdin:
for i, sub in itertools.groupby(enumerate(fdin), lambda x: 1 + x[0]//3):
fdout = open("file_part{}.txt".format(i))
for _, line in sub:
fdout.write(line)
import subprocess
subprocess.run('split -l number_of_lines file_path', shell = True)
For example if you want 50000 lines in one files and path is /home/data then you can run below command
subprocess.run('split -l 50000 /home/data', shell = True)
If you are not sure how many lines to keep in split files but knows how many split you want then In Jupyter Notebook/Shell you can check total number of Lines using below command and then divide by total number of split you want
! wc -l file_path
in this case
! wc -l /home/data
And Just so you know output file will not have file extension but its same extension as input file
You can change it manually if Windows
All the provided answers are good and (probably) work However, they need to load the file into memory (as a whole or partially). We know Python is not very efficient in this kind of tasks (or at least is not as efficient as the OS level commands).
I found the following is the most efficient way to do it:
import os
MAX_NUM_LINES = 1000
FILE_NAME = "input_file.txt"
SPLIT_PARAM = "-d"
PREFIX = "__"
if os.system(f"split -l {MAX_NUM_LINES} {SPLIT_PARAM} {FILE_NAME} {PREFIX}") == 0:
print("Done:")
print(os.system(f"ls {PREFIX}??"))
else:
print("Failed!")
Read more about split here: https://linoxide.com/linux-how-to/split-large-text-file-smaller-files-linux/