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Some performant utility functions to convert common data structures to XLSX

Project description

excel-rs

A set of Rust and Python utilities to efficiently convert CSVs to Excel XLSX files.

This library was created with the goal of being simple, lightweight, and extremely fast. As such, many features such as Excel formatting is not currently supported. This library gives you the quickest possible way to convert a .csv file to .xlsx.

Python

Installing

$ pip install py-excel-rs 

Convert a pandas DataFrame to Excel:

import pandas as pd
from py_excel_rs import df_to_xlsx

df = pd.read_csv("file.csv")
xlsx = df_to_xlsx(df)

with open('report.xlsx', 'wb') as f:
    f.write(xlsx)

Convert a csv file to Excel:

from py_excel_rs import csv_to_xlsx

f = open('file.csv', 'rb')

file_bytes = f.read()
xlsx = csv_to_xlsx(file_bytes)

with open('report.xlsx', 'wb') as f:
    f.write(xlsx)

Convert Postgres response to Excel:

import py_excel_rs

conn_string = "dbname=* user=* password=* host=*"
query = "SELECT * FROM table_name"
xlsx = py_excel_rs.pg_to_xlsx(query, conn_string, disable_strict_ssl=False)

with open('report.xlsx', 'wb') as f:
    f.write(xlsx)

Build Postgres Query to Excel:

from py_excel_rs import ExcelPostgresBuilder, OrderBy

conn_string = "dbname=* user=* password=* host=*"
builder = ExcelPostgresBuilder(conn_str=conn_string, table_name="my_schema.my_table")

xlsx = builder.select_all()
    .exclude(["Unwanted_Column1", "Unwanted_Column2"])
    .orderBy("Usernames", OrderBy.ASCENDING)
    .execute()

with open('report.xlsx', 'wb') as f:
    f.write(xlsx)

Rust

TODO: Add rust documentation

Benchmarks

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.

These tests used a sample dataset from DataBlist that contained 1,000,000 rows and 9 columns.

Tests were conducted on an Macbook Pro M1 Max with 64GB of RAM

Python

py-excel-rs (2.89s)

$ time python test-py-excel-rs.py
python3 test-py-excel-rs.py  2.00s user 0.18s system 99% cpu 2.186 total

openpyxl (97.38s)

$ time python test-openpyxl.py
python3 test-openpyxl.py  94.48s user 2.39s system 99% cpu 1:37.38 total

pandas to_excel() (131.24s)

$ time python test-pandas.py
python3 test-pandas.py  127.99s user 2.75s system 99% cpu 2:11.24 total

pandas to_excel(engine="xlsxwriter") (82.29s)

$ time python test-pandas-xlsxwriter.py
python3 test-pandas-xlsxwriter.py  76.86s user 1.95s system 95% cpu 1:22.29 total

xlsxwriter (42.543s)

$ time python test-xlsxwriter.py
python3 test-xlsxwriter.py  41.58s user 0.81s system 99% cpu 42.543 total

pyexcelerate (35.821s)

$ time python test-pyexcelerate.py
python3 test-pyexcelerate.py  35.27s user 0.33s system 99% cpu 35.821 total

Rust

TODO: Add Rust Benchmark comparisons to rust_xlsxwriter, etc.

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