semvec/pypi-packages huggingface dataset:
xlsxlite 1.1.0
Lightweight XLSX writer with emphasis on minimizing memory usage.
License: MIT
Requires Python: >=3.10

# XLSXLite

[![Build Status](https://github.com/nyaruka/xlsxlite/workflows/CI/badge.svg)](https://github.com/nyaruka/xlsxlite/actions?query=workflow%3ACI)
[![Coverage Status](https://codecov.io/gh/nyaruka/xlsxlite/branch/main/graph/badge.svg)](https://codecov.io/gh/nyaruka/xlsxlite)
[![PyPI Release](https://img.shields.io/pypi/v/xlsxlite.svg)](https://pypi.python.org/pypi/xlsxlite/)

This is a lightweight XLSX writer with emphasis on minimizing memory usage. It's also really fast.

```python
from xlsxlite.writer import XLSXBook
book = XLSXBook()
sheet1 = book.add_sheet("People")
sheet1.append_row("Name", "Email", "Age")
sheet1.append_row("Jim", "jim@acme.com", 45)
book.finalize(to_file="simple.xlsx")
```

## Benchmarks

The [benchmarking test](https://github.com/nyaruka/xlsxlite/blob/main/xlsxlite/test/test_perf.py) writes
rows with 10 cells of random string data to a single sheet workbook. The table below gives the times in seconds (lower is better)
to write a spreadsheet with the given number of rows, and includes [xlxswriter](https://xlsxwriter.readthedocs.io/) and
[openpyxl](https://openpyxl.readthedocs.io/) for comparison.

Implementation  | 100,000 rows | 1,000,000 rows
----------------|--------------|---------------
openpyxl        | 43.5         | 469.1
openpyxl + lxml | 21.1         | 226.3
xlsxwriter      | 17.2         | 186.2
xlsxlite        | 1.9          | 19.2

## Limitations

This library is for projects which need to generate large spreadsheets, quickly, for the purposes of data exchange, and
so it intentionally only supports a tiny subset of SpreadsheetML specification:

 * No styling or themes
 * Only strings, numbers, booleans and dates are supported cell types

If you need to do anything fancier then take a look at [xlxswriter](https://xlsxwriter.readthedocs.io/) and
[openpyxl](https://openpyxl.readthedocs.io/).

## Development

To run all tests:

```
uv run pytest xlsxlite -s
```
pylahman 0.7.0
Python Package for Sean Lahman's Baseball Database
License: MIT
Requires Python: >=3.12

# PyLahman


`pylahman` is a Python package for accessing the [**Lahman** Baseball
Database](https://sabr.org/lahman-database/) via `pandas`.

> The **data** used in this package is provided by
> [SABR](https://sabr.org/) and is licensed under [CC BY-SA
> 3.0](https://creativecommons.org/licenses/by-sa/3.0/). The data was
> last updated based on the source data available from
> <https://sabr.org/lahman-database/> on 2026-01-08.
>
> The surrounding **software** is licensed under the [MIT
> License](https://opensource.org/licenses/MIT).

## Installation

The `pylahman` package is available on
[PyPI](https://pypi.org/project/pylahman/) and can be installed via
`pip`.

``` bash
pip install pylahman
```

## Documentation and Usage

Each table in the Lahman Baseball Database has a corresponding data
loading function in `pylahman` with the same name. For example, the
`Pitching` table is accessed via the `Pitching()` function. Descriptions
of each data table can be found in the documentation for the
corresponding data loading function in the [API Reference](reference/).

``` python
import pylahman

Pitching = pylahman.Pitching()
print(Pitching.head())
```

        playerID  yearID  stint teamID lgID  W  L   G  GS  CG  ...  IBB  WP  HBP  \
    0  aardsda01    2004      1    SFN   NL  1  0  11   0   0  ...    0   0    2   
    1  aardsda01    2006      1    CHN   NL  3  0  45   0   0  ...    0   1    1   
    2  aardsda01    2007      1    CHA   AL  2  1  25   0   0  ...    3   2    1   
    3  aardsda01    2008      1    BOS   AL  4  2  47   0   0  ...    2   3    5   
    4  aardsda01    2009      1    SEA   AL  3  6  73   0   0  ...    3   2    0   

       BK  BFP  GF   R  SH  SF  GIDP  
    0   0   61   5   8   0   1     1  
    1   0  225   9  25   1   3     2  
    2   0  151   7  24   2   1     1  
    3   0  228   7  32   3   2     4  
    4   0  296  53  23   2   1     2  

    [5 rows x 30 columns]