Speed Up Loop Time Iterating Over Relatively Large Excel Sheet in Python

I'm attempting to extract data from each row of an excel sheet when the number I am testing for each row matches the predefined ranges I have created. The code works, but moves at a crawl. I'm attempting to iterate over a sheet that contains 200,000 rows of data, and noticed that when I break the sheet down into smaller segments the program executes faster, but still not as fast as I would like. I can't quite figure out why that is either.

Any recommendations on how I might get this to speed up?

import xlsxwriter

import openpyxl

import os

from tqdm import tqdm



os.chdir(r'C:UsersJTNeumayDesktoptest folder')

xlfile = 'test.xlsx'

wb = openpyxl.load_workbook(xlfile, read_only=True)

sheet = wb['Sheet1']



newbook = xlsxwriter.Workbook('Commercial.xlsx')

newbook2 = xlsxwriter.Workbook('Industrial.xlsx')

newsheet = newbook.add_worksheet()

newsheet2 = newbook2.add_worksheet()

i = 1

j = 1



for row in tqdm(range(1, sheet.max_row + 1)):

    check = sheet.cell(row=row, column=11).value

    if check is not None:

        if (220000 <= check <= 221310 or 221320 <= check <= 221330 or 237200 <= check <= 237210 or 334611 <= check

                <= 334612 or 420000 <= check <= 493190 or 511210 <= check <= 512210 or 512240 <= check <= 541310 or

                541330 <= check <= 541340 or 541370 <= check <= 541700 or 541720 <= check <= 562900 or 562920 <= check

                <= 811430 or 812000 <= check <= 983000):

            for column in range(1, sheet.max_column + 1):

                newsheet.write(i, column, sheet.cell(row=row, column=column).value)

            i += 1

        elif (210000 <= check <= 213115 or 230000 <= check <= 237130 or 237300 <= check <= 334610 or 334613 <=

                check <= 339999 or 510000 <= check <= 511200 or 512220 <= check <= 512230 or check == 541320 or

                check == 541360 or check == 541710 or check == 562910 or check == 811490):

            for column in range(1, sheet.max_column + 1):

                newsheet2.write(i, column, sheet.cell(row=row, column=column).value)

            j += 1

        else:

            pass

    else:

        pass

newbook.close()

newbook2.close()

Note that I also used a method in which I created two lists with the ranges in the if statements, and found that that method took much longer.

asked Nov 19 '18 at 17:41

STRAT0CAST3R

Can you provide a sample of the sheet? Thanks.
– Deepak Saini
Nov 21 '18 at 4:05

I unfortunately cannot, it's for work so the information is proprietary. Unless you mean a sample of the way the sheet is formatted, which is that there is a 6 digit number in the 11th column and the rest of the columns have info that are not important to the program.
– STRAT0CAST3R
Nov 21 '18 at 18:56

add a comment |

Any recommendations on how I might get this to speed up?

import xlsxwriter

import openpyxl

import os

from tqdm import tqdm



os.chdir(r'C:UsersJTNeumayDesktoptest folder')

xlfile = 'test.xlsx'

wb = openpyxl.load_workbook(xlfile, read_only=True)

sheet = wb['Sheet1']



newbook = xlsxwriter.Workbook('Commercial.xlsx')

newbook2 = xlsxwriter.Workbook('Industrial.xlsx')

newsheet = newbook.add_worksheet()

newsheet2 = newbook2.add_worksheet()

i = 1

j = 1



for row in tqdm(range(1, sheet.max_row + 1)):

    check = sheet.cell(row=row, column=11).value

    if check is not None:

        if (220000 <= check <= 221310 or 221320 <= check <= 221330 or 237200 <= check <= 237210 or 334611 <= check

                <= 334612 or 420000 <= check <= 493190 or 511210 <= check <= 512210 or 512240 <= check <= 541310 or

                541330 <= check <= 541340 or 541370 <= check <= 541700 or 541720 <= check <= 562900 or 562920 <= check

                <= 811430 or 812000 <= check <= 983000):

            for column in range(1, sheet.max_column + 1):

                newsheet.write(i, column, sheet.cell(row=row, column=column).value)

            i += 1

        elif (210000 <= check <= 213115 or 230000 <= check <= 237130 or 237300 <= check <= 334610 or 334613 <=

                check <= 339999 or 510000 <= check <= 511200 or 512220 <= check <= 512230 or check == 541320 or

                check == 541360 or check == 541710 or check == 562910 or check == 811490):

            for column in range(1, sheet.max_column + 1):

                newsheet2.write(i, column, sheet.cell(row=row, column=column).value)

            j += 1

        else:

            pass

    else:

        pass

newbook.close()

newbook2.close()

Note that I also used a method in which I created two lists with the ranges in the if statements, and found that that method took much longer.

asked Nov 19 '18 at 17:41

STRAT0CAST3R

Can you provide a sample of the sheet? Thanks.
– Deepak Saini
Nov 21 '18 at 4:05

I unfortunately cannot, it's for work so the information is proprietary. Unless you mean a sample of the way the sheet is formatted, which is that there is a 6 digit number in the 11th column and the rest of the columns have info that are not important to the program.
– STRAT0CAST3R
Nov 21 '18 at 18:56

add a comment |

Any recommendations on how I might get this to speed up?

import xlsxwriter

import openpyxl

import os

from tqdm import tqdm



os.chdir(r'C:UsersJTNeumayDesktoptest folder')

xlfile = 'test.xlsx'

wb = openpyxl.load_workbook(xlfile, read_only=True)

sheet = wb['Sheet1']



newbook = xlsxwriter.Workbook('Commercial.xlsx')

newbook2 = xlsxwriter.Workbook('Industrial.xlsx')

newsheet = newbook.add_worksheet()

newsheet2 = newbook2.add_worksheet()

i = 1

j = 1



for row in tqdm(range(1, sheet.max_row + 1)):

    check = sheet.cell(row=row, column=11).value

    if check is not None:

        if (220000 <= check <= 221310 or 221320 <= check <= 221330 or 237200 <= check <= 237210 or 334611 <= check

                <= 334612 or 420000 <= check <= 493190 or 511210 <= check <= 512210 or 512240 <= check <= 541310 or

                541330 <= check <= 541340 or 541370 <= check <= 541700 or 541720 <= check <= 562900 or 562920 <= check

                <= 811430 or 812000 <= check <= 983000):

            for column in range(1, sheet.max_column + 1):

                newsheet.write(i, column, sheet.cell(row=row, column=column).value)

            i += 1

        elif (210000 <= check <= 213115 or 230000 <= check <= 237130 or 237300 <= check <= 334610 or 334613 <=

                check <= 339999 or 510000 <= check <= 511200 or 512220 <= check <= 512230 or check == 541320 or

                check == 541360 or check == 541710 or check == 562910 or check == 811490):

            for column in range(1, sheet.max_column + 1):

                newsheet2.write(i, column, sheet.cell(row=row, column=column).value)

            j += 1

        else:

            pass

    else:

        pass

newbook.close()

newbook2.close()

Note that I also used a method in which I created two lists with the ranges in the if statements, and found that that method took much longer.

asked Nov 19 '18 at 17:41

STRAT0CAST3R

Any recommendations on how I might get this to speed up?

import xlsxwriter

import openpyxl

import os

from tqdm import tqdm



os.chdir(r'C:UsersJTNeumayDesktoptest folder')

xlfile = 'test.xlsx'

wb = openpyxl.load_workbook(xlfile, read_only=True)

sheet = wb['Sheet1']



newbook = xlsxwriter.Workbook('Commercial.xlsx')

newbook2 = xlsxwriter.Workbook('Industrial.xlsx')

newsheet = newbook.add_worksheet()

newsheet2 = newbook2.add_worksheet()

i = 1

j = 1



for row in tqdm(range(1, sheet.max_row + 1)):

    check = sheet.cell(row=row, column=11).value

    if check is not None:

        if (220000 <= check <= 221310 or 221320 <= check <= 221330 or 237200 <= check <= 237210 or 334611 <= check

                <= 334612 or 420000 <= check <= 493190 or 511210 <= check <= 512210 or 512240 <= check <= 541310 or

                541330 <= check <= 541340 or 541370 <= check <= 541700 or 541720 <= check <= 562900 or 562920 <= check

                <= 811430 or 812000 <= check <= 983000):

            for column in range(1, sheet.max_column + 1):

                newsheet.write(i, column, sheet.cell(row=row, column=column).value)

            i += 1

        elif (210000 <= check <= 213115 or 230000 <= check <= 237130 or 237300 <= check <= 334610 or 334613 <=

                check <= 339999 or 510000 <= check <= 511200 or 512220 <= check <= 512230 or check == 541320 or

                check == 541360 or check == 541710 or check == 562910 or check == 811490):

            for column in range(1, sheet.max_column + 1):

                newsheet2.write(i, column, sheet.cell(row=row, column=column).value)

            j += 1

        else:

            pass

    else:

        pass

newbook.close()

newbook2.close()

Note that I also used a method in which I created two lists with the ranges in the if statements, and found that that method took much longer.

python excel python-3.x performance

asked Nov 19 '18 at 17:41

STRAT0CAST3R

asked Nov 19 '18 at 17:41

STRAT0CAST3R

asked Nov 19 '18 at 17:41

STRAT0CAST3R

asked Nov 19 '18 at 17:41

STRAT0CAST3R

asked Nov 19 '18 at 17:41

STRAT0CAST3R

Can you provide a sample of the sheet? Thanks.
– Deepak Saini
Nov 21 '18 at 4:05

I unfortunately cannot, it's for work so the information is proprietary. Unless you mean a sample of the way the sheet is formatted, which is that there is a 6 digit number in the 11th column and the rest of the columns have info that are not important to the program.
– STRAT0CAST3R
Nov 21 '18 at 18:56

add a comment |

Can you provide a sample of the sheet? Thanks.
– Deepak Saini
Nov 21 '18 at 4:05

I unfortunately cannot, it's for work so the information is proprietary. Unless you mean a sample of the way the sheet is formatted, which is that there is a 6 digit number in the 11th column and the rest of the columns have info that are not important to the program.
– STRAT0CAST3R
Nov 21 '18 at 18:56

Can you provide a sample of the sheet? Thanks.
– Deepak Saini
Nov 21 '18 at 4:05

I unfortunately cannot, it's for work so the information is proprietary. Unless you mean a sample of the way the sheet is formatted, which is that there is a 6 digit number in the 11th column and the rest of the columns have info that are not important to the program.
– STRAT0CAST3R
Nov 21 '18 at 18:56

add a comment |

1 Answer
1

active

oldest

votes

Question: Speed Up Loop Time Iterating

Try this openpyxl only solution:

Come back and report your speed experience.

# Create new Workbooks

wb1 = Workbook()

ws1 = wb1.active

wb2 = Workbook()

ws2 = wb2.active



# Predefine Ranges and Target Worksheet

# You can gain additional speed, by sorting the range tuples 

# of the most expected Ranges, to the beginning.

ranges = [(2, 3, ws1), (221320, 221330, ws2), (237200, 237210, ws1), (812000, 983000, ws2)]



# The Row to start

min_row = 2



# Iterate all Cells in Column 'min/max_col'

for row, cell in enumerate(next(ws.iter_cols(min_row=min_row, min_col=2, max_col=2)), min_row):



    if cell.value:

        # Condition: If cell.value in Range(...)

        for r in ranges:

            if (r[0] <= cell.value <= r[1]):

                # Match: Append this 'row' to the given Worksheet

                r[2].append([cell.value for cell in next(ws.iter_rows(min_row=row, max_row=row))])

                break



# Save Worksheets

wb1.save('../test/test1.xlsx')

wb2.save('../test/test2.xlsx')

Tested with Python: 3.4.2 - openpyxl: 2.4.1 - LibreOffice: 4.3.3.2

answered Nov 19 '18 at 21:18

stovfl

7,3953931

1

Gives me just about the same speed that I was getting previously
– STRAT0CAST3R
Nov 19 '18 at 22:37

As it's possible to split your input xlsx in chunks, therefore multiprocessing is a option. But, you have to pay for it, means 2 processes does not result in half excution time.
– stovfl
Nov 20 '18 at 16:15

I ended up using a concurrent.futures.ProcessPoolExecutor map and broke up the source data into multiple sheets to get it to multiprocess, and they did run concurrently. The thing I can't figure out is why analyzing a larger number of cells causes the program to run exponentially longer. it's as if it's loading the whole sheet with each iteration
– STRAT0CAST3R
Nov 21 '18 at 22:01

"why analyzing a larger number of cells ... run exponentially longer": Read openpyxl-read-excel-too-slow and openpyxl-optimizing-cells-search-speed
– stovfl
Nov 22 '18 at 8:09

add a comment |

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1 Answer
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1 Answer
1

active

oldest

votes

Question: Speed Up Loop Time Iterating

Try this openpyxl only solution:

Come back and report your speed experience.

# Create new Workbooks

wb1 = Workbook()

ws1 = wb1.active

wb2 = Workbook()

ws2 = wb2.active



# Predefine Ranges and Target Worksheet

# You can gain additional speed, by sorting the range tuples 

# of the most expected Ranges, to the beginning.

ranges = [(2, 3, ws1), (221320, 221330, ws2), (237200, 237210, ws1), (812000, 983000, ws2)]



# The Row to start

min_row = 2



# Iterate all Cells in Column 'min/max_col'

for row, cell in enumerate(next(ws.iter_cols(min_row=min_row, min_col=2, max_col=2)), min_row):



    if cell.value:

        # Condition: If cell.value in Range(...)

        for r in ranges:

            if (r[0] <= cell.value <= r[1]):

                # Match: Append this 'row' to the given Worksheet

                r[2].append([cell.value for cell in next(ws.iter_rows(min_row=row, max_row=row))])

                break



# Save Worksheets

wb1.save('../test/test1.xlsx')

wb2.save('../test/test2.xlsx')

Tested with Python: 3.4.2 - openpyxl: 2.4.1 - LibreOffice: 4.3.3.2

answered Nov 19 '18 at 21:18

stovfl

7,3953931

1

Gives me just about the same speed that I was getting previously
– STRAT0CAST3R
Nov 19 '18 at 22:37

As it's possible to split your input xlsx in chunks, therefore multiprocessing is a option. But, you have to pay for it, means 2 processes does not result in half excution time.
– stovfl
Nov 20 '18 at 16:15

I ended up using a concurrent.futures.ProcessPoolExecutor map and broke up the source data into multiple sheets to get it to multiprocess, and they did run concurrently. The thing I can't figure out is why analyzing a larger number of cells causes the program to run exponentially longer. it's as if it's loading the whole sheet with each iteration
– STRAT0CAST3R
Nov 21 '18 at 22:01

"why analyzing a larger number of cells ... run exponentially longer": Read openpyxl-read-excel-too-slow and openpyxl-optimizing-cells-search-speed
– stovfl
Nov 22 '18 at 8:09

add a comment |

Question: Speed Up Loop Time Iterating

Try this openpyxl only solution:

Come back and report your speed experience.

# Create new Workbooks

wb1 = Workbook()

ws1 = wb1.active

wb2 = Workbook()

ws2 = wb2.active



# Predefine Ranges and Target Worksheet

# You can gain additional speed, by sorting the range tuples 

# of the most expected Ranges, to the beginning.

ranges = [(2, 3, ws1), (221320, 221330, ws2), (237200, 237210, ws1), (812000, 983000, ws2)]



# The Row to start

min_row = 2



# Iterate all Cells in Column 'min/max_col'

for row, cell in enumerate(next(ws.iter_cols(min_row=min_row, min_col=2, max_col=2)), min_row):



    if cell.value:

        # Condition: If cell.value in Range(...)

        for r in ranges:

            if (r[0] <= cell.value <= r[1]):

                # Match: Append this 'row' to the given Worksheet

                r[2].append([cell.value for cell in next(ws.iter_rows(min_row=row, max_row=row))])

                break



# Save Worksheets

wb1.save('../test/test1.xlsx')

wb2.save('../test/test2.xlsx')

Tested with Python: 3.4.2 - openpyxl: 2.4.1 - LibreOffice: 4.3.3.2

answered Nov 19 '18 at 21:18

stovfl

7,3953931

1

Gives me just about the same speed that I was getting previously
– STRAT0CAST3R
Nov 19 '18 at 22:37

As it's possible to split your input xlsx in chunks, therefore multiprocessing is a option. But, you have to pay for it, means 2 processes does not result in half excution time.
– stovfl
Nov 20 '18 at 16:15

I ended up using a concurrent.futures.ProcessPoolExecutor map and broke up the source data into multiple sheets to get it to multiprocess, and they did run concurrently. The thing I can't figure out is why analyzing a larger number of cells causes the program to run exponentially longer. it's as if it's loading the whole sheet with each iteration
– STRAT0CAST3R
Nov 21 '18 at 22:01

"why analyzing a larger number of cells ... run exponentially longer": Read openpyxl-read-excel-too-slow and openpyxl-optimizing-cells-search-speed
– stovfl
Nov 22 '18 at 8:09

add a comment |

Question: Speed Up Loop Time Iterating

Try this openpyxl only solution:

Come back and report your speed experience.

# Create new Workbooks

wb1 = Workbook()

ws1 = wb1.active

wb2 = Workbook()

ws2 = wb2.active



# Predefine Ranges and Target Worksheet

# You can gain additional speed, by sorting the range tuples 

# of the most expected Ranges, to the beginning.

ranges = [(2, 3, ws1), (221320, 221330, ws2), (237200, 237210, ws1), (812000, 983000, ws2)]



# The Row to start

min_row = 2



# Iterate all Cells in Column 'min/max_col'

for row, cell in enumerate(next(ws.iter_cols(min_row=min_row, min_col=2, max_col=2)), min_row):



    if cell.value:

        # Condition: If cell.value in Range(...)

        for r in ranges:

            if (r[0] <= cell.value <= r[1]):

                # Match: Append this 'row' to the given Worksheet

                r[2].append([cell.value for cell in next(ws.iter_rows(min_row=row, max_row=row))])

                break



# Save Worksheets

wb1.save('../test/test1.xlsx')

wb2.save('../test/test2.xlsx')

Tested with Python: 3.4.2 - openpyxl: 2.4.1 - LibreOffice: 4.3.3.2

answered Nov 19 '18 at 21:18

stovfl

7,3953931

Question: Speed Up Loop Time Iterating

Try this openpyxl only solution:

Come back and report your speed experience.

# Create new Workbooks

wb1 = Workbook()

ws1 = wb1.active

wb2 = Workbook()

ws2 = wb2.active



# Predefine Ranges and Target Worksheet

# You can gain additional speed, by sorting the range tuples 

# of the most expected Ranges, to the beginning.

ranges = [(2, 3, ws1), (221320, 221330, ws2), (237200, 237210, ws1), (812000, 983000, ws2)]



# The Row to start

min_row = 2



# Iterate all Cells in Column 'min/max_col'

for row, cell in enumerate(next(ws.iter_cols(min_row=min_row, min_col=2, max_col=2)), min_row):



    if cell.value:

        # Condition: If cell.value in Range(...)

        for r in ranges:

            if (r[0] <= cell.value <= r[1]):

                # Match: Append this 'row' to the given Worksheet

                r[2].append([cell.value for cell in next(ws.iter_rows(min_row=row, max_row=row))])

                break



# Save Worksheets

wb1.save('../test/test1.xlsx')

wb2.save('../test/test2.xlsx')

Tested with Python: 3.4.2 - openpyxl: 2.4.1 - LibreOffice: 4.3.3.2

answered Nov 19 '18 at 21:18

stovfl

7,3953931

answered Nov 19 '18 at 21:18

stovfl

7,3953931

answered Nov 19 '18 at 21:18

stovfl

7,3953931

answered Nov 19 '18 at 21:18

stovfl

7,3953931

1

Gives me just about the same speed that I was getting previously
– STRAT0CAST3R
Nov 19 '18 at 22:37

As it's possible to split your input xlsx in chunks, therefore multiprocessing is a option. But, you have to pay for it, means 2 processes does not result in half excution time.
– stovfl
Nov 20 '18 at 16:15

I ended up using a concurrent.futures.ProcessPoolExecutor map and broke up the source data into multiple sheets to get it to multiprocess, and they did run concurrently. The thing I can't figure out is why analyzing a larger number of cells causes the program to run exponentially longer. it's as if it's loading the whole sheet with each iteration
– STRAT0CAST3R
Nov 21 '18 at 22:01

"why analyzing a larger number of cells ... run exponentially longer": Read openpyxl-read-excel-too-slow and openpyxl-optimizing-cells-search-speed
– stovfl
Nov 22 '18 at 8:09

add a comment |

1

Gives me just about the same speed that I was getting previously
– STRAT0CAST3R
Nov 19 '18 at 22:37

As it's possible to split your input xlsx in chunks, therefore multiprocessing is a option. But, you have to pay for it, means 2 processes does not result in half excution time.
– stovfl
Nov 20 '18 at 16:15

I ended up using a concurrent.futures.ProcessPoolExecutor map and broke up the source data into multiple sheets to get it to multiprocess, and they did run concurrently. The thing I can't figure out is why analyzing a larger number of cells causes the program to run exponentially longer. it's as if it's loading the whole sheet with each iteration
– STRAT0CAST3R
Nov 21 '18 at 22:01

"why analyzing a larger number of cells ... run exponentially longer": Read openpyxl-read-excel-too-slow and openpyxl-optimizing-cells-search-speed
– stovfl
Nov 22 '18 at 8:09

Gives me just about the same speed that I was getting previously
– STRAT0CAST3R
Nov 19 '18 at 22:37

As it's possible to split your input xlsx in chunks, therefore multiprocessing is a option. But, you have to pay for it, means 2 processes does not result in half excution time.
– stovfl
Nov 20 '18 at 16:15

I ended up using a concurrent.futures.ProcessPoolExecutor map and broke up the source data into multiple sheets to get it to multiprocess, and they did run concurrently. The thing I can't figure out is why analyzing a larger number of cells causes the program to run exponentially longer. it's as if it's loading the whole sheet with each iteration
– STRAT0CAST3R
Nov 21 '18 at 22:01

"why analyzing a larger number of cells ... run exponentially longer": Read openpyxl-read-excel-too-slow and openpyxl-optimizing-cells-search-speed
– stovfl
Nov 22 '18 at 8:09

add a comment |

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