iterating through a file with millions of lines
I am trying to iterate through a file with millions of lines containg some data and I am retrieving it. Unfortunately this is going very slow and I was wondering how I could make it more efficient.
At the moment I am loading two files and I am iterating by each line.
The code:
# Retrieve session data
UBList = array([line.split('t') for line in source])
SID = set(UBList[:,1])
n_unique_sessions = len(Counter(UBList[:,1]))
source.close()
sessions =
session_info =
purchases = array([line.split('t') for line in open('Data/order_overview.txt', 'r').readlines()])
for sid in SID:
print sid
s = [line for line in UBList if line[1]==sid]
uline = [line for line in s if line[3]=='17']
tline = [line[2] for line in s]
t_format = "%Y-%m-%d %H:%M:%S.%f"
s_start = datetime.strptime(tline[0], t_format)
s_end = datetime.strptime(tline[-1], t_format)
s_length = (s_end - s_start).total_seconds()
d_time = [line[2] for line in s if line[3]=='4']
if len(uline) > 0:
uid = uline[0][12]
else:
uid = 'NotFound'
num_queries = len([line for line in s if line[3]=='27'])
num_purchases = nonzero(purchases[:,0]==sid)[0].shape[0]
sessions.update(sid: (uid, num_queries, num_purchases, s))
f = open('Results/' + sid + '_' + uid + '_' + str(num_queries) + '_' + str(num_purchases) + '_' + str(s_length) + '.txt', 'w')
f.writelines(['t'.join(line) for line in s])
f.close()
Would something like this speed things up?
somevar = dict([sid, for sid in SID])
for line in UBList:
sid = line[1]
dSID[sid].append('t'.join(line))
Also is it possible to get the next line after a certain criteria is met? For example I find a line get its value with the next and do a calculation. And add the results if the line with the criteria was found multiple times.
python loops large-files
|
show 1 more comment
I am trying to iterate through a file with millions of lines containg some data and I am retrieving it. Unfortunately this is going very slow and I was wondering how I could make it more efficient.
At the moment I am loading two files and I am iterating by each line.
The code:
# Retrieve session data
UBList = array([line.split('t') for line in source])
SID = set(UBList[:,1])
n_unique_sessions = len(Counter(UBList[:,1]))
source.close()
sessions =
session_info =
purchases = array([line.split('t') for line in open('Data/order_overview.txt', 'r').readlines()])
for sid in SID:
print sid
s = [line for line in UBList if line[1]==sid]
uline = [line for line in s if line[3]=='17']
tline = [line[2] for line in s]
t_format = "%Y-%m-%d %H:%M:%S.%f"
s_start = datetime.strptime(tline[0], t_format)
s_end = datetime.strptime(tline[-1], t_format)
s_length = (s_end - s_start).total_seconds()
d_time = [line[2] for line in s if line[3]=='4']
if len(uline) > 0:
uid = uline[0][12]
else:
uid = 'NotFound'
num_queries = len([line for line in s if line[3]=='27'])
num_purchases = nonzero(purchases[:,0]==sid)[0].shape[0]
sessions.update(sid: (uid, num_queries, num_purchases, s))
f = open('Results/' + sid + '_' + uid + '_' + str(num_queries) + '_' + str(num_purchases) + '_' + str(s_length) + '.txt', 'w')
f.writelines(['t'.join(line) for line in s])
f.close()
Would something like this speed things up?
somevar = dict([sid, for sid in SID])
for line in UBList:
sid = line[1]
dSID[sid].append('t'.join(line))
Also is it possible to get the next line after a certain criteria is met? For example I find a line get its value with the next and do a calculation. And add the results if the line with the criteria was found multiple times.
python loops large-files
I think this question suits better in codereview.stackexchange.com
– Ruben Bermudez
Apr 5 '14 at 17:33
Yeah, I'd try cache UBList as what you say, and use csvreader (docs.python.org/2/library/csv.html) to read the file, indicating that your separator is a tab (t) The example is a bit complex for me to understand what's happening there and provide a more definite answer.
– BorrajaX
Apr 5 '14 at 17:39
I think thatarray
is the function in thenumpy
module. Could you describe the structure of the lines insource
? I think there are several errors in your use of numpy objects
– eyquem
Apr 5 '14 at 20:07
@eyquem The line in the source are tab seperated strings on each line. so something like abc [tab] def [tab] 123 [tab] 456 and so on for each line. BorrajaX: so instead of storing UBList read it line for line? I am a bit confised should I store data in a csv file? My current data is in a txt file.
– Emrulez
Apr 5 '14 at 21:36
Isarray
the methodnumpy.array
or not ? If not, I wouldn't understand the writingUBList[:,1]
with a comma in it
– eyquem
Apr 6 '14 at 1:38
|
show 1 more comment
I am trying to iterate through a file with millions of lines containg some data and I am retrieving it. Unfortunately this is going very slow and I was wondering how I could make it more efficient.
At the moment I am loading two files and I am iterating by each line.
The code:
# Retrieve session data
UBList = array([line.split('t') for line in source])
SID = set(UBList[:,1])
n_unique_sessions = len(Counter(UBList[:,1]))
source.close()
sessions =
session_info =
purchases = array([line.split('t') for line in open('Data/order_overview.txt', 'r').readlines()])
for sid in SID:
print sid
s = [line for line in UBList if line[1]==sid]
uline = [line for line in s if line[3]=='17']
tline = [line[2] for line in s]
t_format = "%Y-%m-%d %H:%M:%S.%f"
s_start = datetime.strptime(tline[0], t_format)
s_end = datetime.strptime(tline[-1], t_format)
s_length = (s_end - s_start).total_seconds()
d_time = [line[2] for line in s if line[3]=='4']
if len(uline) > 0:
uid = uline[0][12]
else:
uid = 'NotFound'
num_queries = len([line for line in s if line[3]=='27'])
num_purchases = nonzero(purchases[:,0]==sid)[0].shape[0]
sessions.update(sid: (uid, num_queries, num_purchases, s))
f = open('Results/' + sid + '_' + uid + '_' + str(num_queries) + '_' + str(num_purchases) + '_' + str(s_length) + '.txt', 'w')
f.writelines(['t'.join(line) for line in s])
f.close()
Would something like this speed things up?
somevar = dict([sid, for sid in SID])
for line in UBList:
sid = line[1]
dSID[sid].append('t'.join(line))
Also is it possible to get the next line after a certain criteria is met? For example I find a line get its value with the next and do a calculation. And add the results if the line with the criteria was found multiple times.
python loops large-files
I am trying to iterate through a file with millions of lines containg some data and I am retrieving it. Unfortunately this is going very slow and I was wondering how I could make it more efficient.
At the moment I am loading two files and I am iterating by each line.
The code:
# Retrieve session data
UBList = array([line.split('t') for line in source])
SID = set(UBList[:,1])
n_unique_sessions = len(Counter(UBList[:,1]))
source.close()
sessions =
session_info =
purchases = array([line.split('t') for line in open('Data/order_overview.txt', 'r').readlines()])
for sid in SID:
print sid
s = [line for line in UBList if line[1]==sid]
uline = [line for line in s if line[3]=='17']
tline = [line[2] for line in s]
t_format = "%Y-%m-%d %H:%M:%S.%f"
s_start = datetime.strptime(tline[0], t_format)
s_end = datetime.strptime(tline[-1], t_format)
s_length = (s_end - s_start).total_seconds()
d_time = [line[2] for line in s if line[3]=='4']
if len(uline) > 0:
uid = uline[0][12]
else:
uid = 'NotFound'
num_queries = len([line for line in s if line[3]=='27'])
num_purchases = nonzero(purchases[:,0]==sid)[0].shape[0]
sessions.update(sid: (uid, num_queries, num_purchases, s))
f = open('Results/' + sid + '_' + uid + '_' + str(num_queries) + '_' + str(num_purchases) + '_' + str(s_length) + '.txt', 'w')
f.writelines(['t'.join(line) for line in s])
f.close()
Would something like this speed things up?
somevar = dict([sid, for sid in SID])
for line in UBList:
sid = line[1]
dSID[sid].append('t'.join(line))
Also is it possible to get the next line after a certain criteria is met? For example I find a line get its value with the next and do a calculation. And add the results if the line with the criteria was found multiple times.
python loops large-files
python loops large-files
edited Nov 13 '18 at 2:05
Cœur
17.4k9103145
17.4k9103145
asked Apr 5 '14 at 17:30
Emrulez
239414
239414
I think this question suits better in codereview.stackexchange.com
– Ruben Bermudez
Apr 5 '14 at 17:33
Yeah, I'd try cache UBList as what you say, and use csvreader (docs.python.org/2/library/csv.html) to read the file, indicating that your separator is a tab (t) The example is a bit complex for me to understand what's happening there and provide a more definite answer.
– BorrajaX
Apr 5 '14 at 17:39
I think thatarray
is the function in thenumpy
module. Could you describe the structure of the lines insource
? I think there are several errors in your use of numpy objects
– eyquem
Apr 5 '14 at 20:07
@eyquem The line in the source are tab seperated strings on each line. so something like abc [tab] def [tab] 123 [tab] 456 and so on for each line. BorrajaX: so instead of storing UBList read it line for line? I am a bit confised should I store data in a csv file? My current data is in a txt file.
– Emrulez
Apr 5 '14 at 21:36
Isarray
the methodnumpy.array
or not ? If not, I wouldn't understand the writingUBList[:,1]
with a comma in it
– eyquem
Apr 6 '14 at 1:38
|
show 1 more comment
I think this question suits better in codereview.stackexchange.com
– Ruben Bermudez
Apr 5 '14 at 17:33
Yeah, I'd try cache UBList as what you say, and use csvreader (docs.python.org/2/library/csv.html) to read the file, indicating that your separator is a tab (t) The example is a bit complex for me to understand what's happening there and provide a more definite answer.
– BorrajaX
Apr 5 '14 at 17:39
I think thatarray
is the function in thenumpy
module. Could you describe the structure of the lines insource
? I think there are several errors in your use of numpy objects
– eyquem
Apr 5 '14 at 20:07
@eyquem The line in the source are tab seperated strings on each line. so something like abc [tab] def [tab] 123 [tab] 456 and so on for each line. BorrajaX: so instead of storing UBList read it line for line? I am a bit confised should I store data in a csv file? My current data is in a txt file.
– Emrulez
Apr 5 '14 at 21:36
Isarray
the methodnumpy.array
or not ? If not, I wouldn't understand the writingUBList[:,1]
with a comma in it
– eyquem
Apr 6 '14 at 1:38
I think this question suits better in codereview.stackexchange.com
– Ruben Bermudez
Apr 5 '14 at 17:33
I think this question suits better in codereview.stackexchange.com
– Ruben Bermudez
Apr 5 '14 at 17:33
Yeah, I'd try cache UBList as what you say, and use csvreader (docs.python.org/2/library/csv.html) to read the file, indicating that your separator is a tab (t) The example is a bit complex for me to understand what's happening there and provide a more definite answer.
– BorrajaX
Apr 5 '14 at 17:39
Yeah, I'd try cache UBList as what you say, and use csvreader (docs.python.org/2/library/csv.html) to read the file, indicating that your separator is a tab (t) The example is a bit complex for me to understand what's happening there and provide a more definite answer.
– BorrajaX
Apr 5 '14 at 17:39
I think that
array
is the function in the numpy
module. Could you describe the structure of the lines in source
? I think there are several errors in your use of numpy objects– eyquem
Apr 5 '14 at 20:07
I think that
array
is the function in the numpy
module. Could you describe the structure of the lines in source
? I think there are several errors in your use of numpy objects– eyquem
Apr 5 '14 at 20:07
@eyquem The line in the source are tab seperated strings on each line. so something like abc [tab] def [tab] 123 [tab] 456 and so on for each line. BorrajaX: so instead of storing UBList read it line for line? I am a bit confised should I store data in a csv file? My current data is in a txt file.
– Emrulez
Apr 5 '14 at 21:36
@eyquem The line in the source are tab seperated strings on each line. so something like abc [tab] def [tab] 123 [tab] 456 and so on for each line. BorrajaX: so instead of storing UBList read it line for line? I am a bit confised should I store data in a csv file? My current data is in a txt file.
– Emrulez
Apr 5 '14 at 21:36
Is
array
the method numpy.array
or not ? If not, I wouldn't understand the writing UBList[:,1]
with a comma in it– eyquem
Apr 6 '14 at 1:38
Is
array
the method numpy.array
or not ? If not, I wouldn't understand the writing UBList[:,1]
with a comma in it– eyquem
Apr 6 '14 at 1:38
|
show 1 more comment
1 Answer
1
active
oldest
votes
If source
is your file object, don't read it all to memory beforehand. You can process it and read at the same time, and Python is clever enough to process data while waiting for next chunk to be read. To achieve that, use list generators, not list comprehensions.
You create a lot of arrays you don't actually need, like s
. Replace them with generators and get a speedup. Creating standard Python array is a heavy operation, and if it's bigger than a 4kB, generators should be better.
So instead of storing I should read it and process it? With something like while open(source) do .....
– Emrulez
Apr 5 '14 at 21:39
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
If source
is your file object, don't read it all to memory beforehand. You can process it and read at the same time, and Python is clever enough to process data while waiting for next chunk to be read. To achieve that, use list generators, not list comprehensions.
You create a lot of arrays you don't actually need, like s
. Replace them with generators and get a speedup. Creating standard Python array is a heavy operation, and if it's bigger than a 4kB, generators should be better.
So instead of storing I should read it and process it? With something like while open(source) do .....
– Emrulez
Apr 5 '14 at 21:39
add a comment |
If source
is your file object, don't read it all to memory beforehand. You can process it and read at the same time, and Python is clever enough to process data while waiting for next chunk to be read. To achieve that, use list generators, not list comprehensions.
You create a lot of arrays you don't actually need, like s
. Replace them with generators and get a speedup. Creating standard Python array is a heavy operation, and if it's bigger than a 4kB, generators should be better.
So instead of storing I should read it and process it? With something like while open(source) do .....
– Emrulez
Apr 5 '14 at 21:39
add a comment |
If source
is your file object, don't read it all to memory beforehand. You can process it and read at the same time, and Python is clever enough to process data while waiting for next chunk to be read. To achieve that, use list generators, not list comprehensions.
You create a lot of arrays you don't actually need, like s
. Replace them with generators and get a speedup. Creating standard Python array is a heavy operation, and if it's bigger than a 4kB, generators should be better.
If source
is your file object, don't read it all to memory beforehand. You can process it and read at the same time, and Python is clever enough to process data while waiting for next chunk to be read. To achieve that, use list generators, not list comprehensions.
You create a lot of arrays you don't actually need, like s
. Replace them with generators and get a speedup. Creating standard Python array is a heavy operation, and if it's bigger than a 4kB, generators should be better.
answered Apr 5 '14 at 18:44
Barafu Albino
1,019922
1,019922
So instead of storing I should read it and process it? With something like while open(source) do .....
– Emrulez
Apr 5 '14 at 21:39
add a comment |
So instead of storing I should read it and process it? With something like while open(source) do .....
– Emrulez
Apr 5 '14 at 21:39
So instead of storing I should read it and process it? With something like while open(source) do .....
– Emrulez
Apr 5 '14 at 21:39
So instead of storing I should read it and process it? With something like while open(source) do .....
– Emrulez
Apr 5 '14 at 21:39
add a comment |
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I think this question suits better in codereview.stackexchange.com
– Ruben Bermudez
Apr 5 '14 at 17:33
Yeah, I'd try cache UBList as what you say, and use csvreader (docs.python.org/2/library/csv.html) to read the file, indicating that your separator is a tab (t) The example is a bit complex for me to understand what's happening there and provide a more definite answer.
– BorrajaX
Apr 5 '14 at 17:39
I think that
array
is the function in thenumpy
module. Could you describe the structure of the lines insource
? I think there are several errors in your use of numpy objects– eyquem
Apr 5 '14 at 20:07
@eyquem The line in the source are tab seperated strings on each line. so something like abc [tab] def [tab] 123 [tab] 456 and so on for each line. BorrajaX: so instead of storing UBList read it line for line? I am a bit confised should I store data in a csv file? My current data is in a txt file.
– Emrulez
Apr 5 '14 at 21:36
Is
array
the methodnumpy.array
or not ? If not, I wouldn't understand the writingUBList[:,1]
with a comma in it– eyquem
Apr 6 '14 at 1:38