Metadata-Version: 2.4
Name: tableskill
Version: 0.3.0
Summary: A Python package to visualize tabular data via https://www.tableskill.com/
Author-email: Walter Levy <klwlevy@hotmail.com>
License: MIT License
        
        Copyright (c) 2026 Walter Levy <klwlevy@hotmail.com> and contributors
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
Project-URL: Repository, https://github.com/klwlevy/tableskill.git
Classifier: Programming Language :: Python
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: polars>=1.0
Provides-Extra: docs
Requires-Dist: mkdocs; extra == "docs"
Requires-Dist: mkdocs-material; extra == "docs"
Requires-Dist: mkdocstrings-python; extra == "docs"
Provides-Extra: dev
Requires-Dist: tableskill[docs]; extra == "dev"
Requires-Dist: black; extra == "dev"
Dynamic: license-file

# TableSkill

Python package for visualization of tabular data via https://www.tableskill.com/  
Specifically, polars (https://pola.rs/) dataframes are supported.

# Usage:

You can comfortably visualize your polars dataframes in tableskill as in this self-contained example:
```python

import tableskill as ts
import polars as pl

from datetime import datetime

# Create two dataframes from scratch
my_df1 = pl.DataFrame(
    {
        "integer": [1, 2, 3],
        "date": [
            datetime(2025, 1, 1),
            datetime(2025, 1, 2),
            datetime(2025, 1, 3),
        ],
        "float": [4.1, 5.2, 6.3],
        "string": ["a", "b", "c"],
    }
)

my_df2 = pl.DataFrame(
    {
        "an_integer": range(10),
    }
)

# Define a dictionary for the 2 dataframes
my_dataframe_dict = {
    "1 my_df": my_df1,
    "2 my_df": my_df2,
}

# Export the dataframes to tableskill using the tableskill function
ts.tableskill(
    dataframe_dict = my_dataframe_dict,
    sub_folder_in_export = "tableskill_sample",
)
```

The above will generate flat files suitable for https://www.tableskill.com/ on your hard drive under 
`~\<LAST_NAME>\temp\tableskill\<YYYYMMDD>\tableskill_sample\`  
You can simply drag invidual files or an entire folder structure into TableSkill.
