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With a focus on squeezing out as much performance as possible, **py-excel-rs** is up to **65.5x** faster than `pandas` and **17.5x** faster than the next fastest `xlsx` writer on pip.
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With a focus on squeezing out as much performance as possible, **py-excel-rs** is up to **45.5x** faster than `pandas` and **12.5x** faster than the fastest `xlsx` writer on pip.
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**cli-excel-rs** also managed to out perform [csv2xlsx](https://github.com/mentax/csv2xlsx?tab=readme-ov-file), the most poopular csv to xlsx tool. It is up to **12x** faster given the same dataset.
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These tests used a sample dataset from [DataBlist](https://www.datablist.com/learn/csv/download-sample-csv-files) that contained 1,000,000 rows and 9 columns.
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@@ -100,37 +102,37 @@ Tests were conducted on an Macbook Pro M1 Max with 64GB of RAM
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### Python
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#### py-excel-rs (2.89s)
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```
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```bash
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$ time python test-py-excel-rs.py
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python3 test-py-excel-rs.py 2.00s user 0.18s system 99% cpu 2.892 total
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```
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#### openpyxl (97.38s)
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```
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```bash
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$ time python test-openpyxl.py
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python3 test-openpyxl.py 94.48s user 2.39s system 99% cpu 1:37.38 total
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```
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#### pandas `to_excel()` (131.24s)
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```
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```bash
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$ time python test-pandas.py
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python3 test-pandas.py 127.99s user 2.75s system 99% cpu 2:11.24 total
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