py-excel-rs 0.5.5

Some performant utility functions to convert common data structures to XLSX

excel-rs

An extremely fast set of Rust and Python utilities to efficiently convert CSVs to Excel XLSX files.

This library is available as a CLI tool and Python PIP package.

This library was created with the goal of being simple, lightweight, and extremely performant. 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.

The Python utilities also gives you the quickest possible way to export a Pandas DataFrame, Numpy 2D array or Postgres database as a .xlsx file.

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)

Command Line Tool

To install, download the latest release of cli-excel-rs for your platform from Github Releases here.

$ wget https://github.com/carlvoller/excel-rs/releases/download/cli-0.2.0/excel-rs-linux-aarch64.zip
$ unzip excel-rs-linux-aarch64.zip
$ chmod +x ./cli-excel-rs

Then simply run the binary:

$ ./cli-excel-rs csv --in my_csv.csv --out my_excel.xlsx

If you would like the build the binary yourself, you can do so using these commands:

$ git clone https://github.com/carlvoller/excel-rs
$ cargo build --release
$ ./target/release/cli-excel-rs csv --in my_csv.csv --out my_excel.xlsx

Rust

TODO: Add rust documentation

Benchmarks

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.

cli-excel-rs also managed to out perform csv2xlsx, the most poopular csv to xlsx tool. It is up to 12x faster given the same dataset.

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 2.892 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

Command Line Tools

cli-excel-rs (2.756s)

$ time ./cli-excel-rs csv --in organizations-1000000.csv --out results.xlsx
./cli-excel-rs csv --in organizations-1000000.csv --out 2.69s user 0.07s system 99% cpu 2.756 total

csv2xlsx (33.74s)

$ time ./csv2xlsx --output results.xlsx organizations-1000000.csv
./csv2xlsx --output results.xlsx organizations-1000000.csv  57.63s user 1.62s system 175% cpu 33.740 total

Rust

TODO: Add Rust Benchmark comparisons to rust_xlsxwriter, etc.