SheetReader Python Bindings

SheetReader allows to read your Excel spreadsheet files (.xlsx) blazingly fast. This repository contains the Python bindings, as the core library is implemented in C++.

Quickstart

Sheetreader is available through:

pip install pysheetreader

After successful installation, spreadsheets can be loaded:

import pysheetreader as sr
sheet = sr.read_xlsx("my_favorite_sheet.xlsx")

To convert a spreadsheet into a pandas Dataframe:

import pysheetreader as sr
import pandas as pd
sheet = sr.read_xlsx("my_favorite_sheet.xlsx")
df = pd.DataFrame.from_dict(sheet[0])

Parameters:

Parameter	Type	Description	Default
path	string	The path of the .xlsx file to parse.	-
sheet	integer or string	The sheet of the file to parse, can be either the index (starting at 1) or the name.	1
headers	boolean	Whether to interpret the first parsed row as headers.	True
skip_rows	integer	How many rows to skip before parsing data.	0
skip_columns	integer	How many columns to skip before parsing data.	0
num_threads	integer	How many threads to use for parsing. Use -1 for automatic threading.	-1
col_types	dict or list	How to interpret parsed data, either by names (dict) or by position (list). Types: numeric, text, logical, date, skip, guess.	None

Build Instructions

First install the submodules, which contain the sheetreader-core dependency with:

git clone --recurse-submodules https://github.com/polydbms/sheetreader-python.git

To build from source, this repository provides a pyproject.toml. The SheetReader wheel file can be generated through:

python -m build .

or installed with pip through:

pip install .

More resources

SheetReader is part of the PolyDB Project. We also provide bindings/extensions for several other environments:

• R language: Load spreadsheets into dataframes, also available via CRAN.
• PostgreSQL FDW: Foreign data wrapper for PostgreSQL; allows to register spreadsheets as foreign tables.
• DuckDB Extension: Extension for DuckDB that allows loading spreadsheets into tables. Also available as a community extension.

Paper

SheetReader was published in the Information Systems Journal. Cite as:

@article{DBLP:journals/is/GavriilidisHZM23,
  author       = {Haralampos Gavriilidis and
                  Felix Henze and
                  Eleni Tzirita Zacharatou and
                  Volker Markl},
  title        = {SheetReader: Efficient Specialized Spreadsheet Parsing},
  journal      = {Inf. Syst.},
  volume       = {115},
  pages        = {102183},
  year         = {2023},
  url          = {https://doi.org/10.1016/j.is.2023.102183},
  doi          = {10.1016/J.IS.2023.102183},
  timestamp    = {Mon, 26 Jun 2023 20:54:32 +0200},
  biburl       = {https://dblp.org/rec/journals/is/GavriilidisHZM23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}