Tablib: Pythonic Tabular Datasets

Warnings

• breaking The logic for `Row.lpush` and `Row.rpush` methods was reversed in Tablib 2.0.0. In versions 1.x, `lpush` appended and `rpush` prepended, which was non-standard. This was corrected in 2.0.0.
  Fix: Review code using `lpush` or `rpush` on `Row` objects when upgrading to 2.0.0+ to ensure the intended prepend/append behavior.
• breaking Python 2 support was dropped with Tablib 1.0.0. Python 3.5 support was dropped with Tablib 3.0.0.
  Fix: Ensure your project uses Python 3.6+ for Tablib 3.x.
• breaking Starting with Tablib 1.0.0, all format dependencies became optional. Previously, they might have been installed by default. To install all possible format dependencies, you now need to use `pip install "tablib[all]"`.
  Fix: If upgrading from pre-1.0.0 and encountering `ImportError` for format-specific modules, use `pip install "tablib[all]"` or install specific format dependencies like `pip install "tablib[xlsx]"`.
• gotcha When exporting CSV files on Windows, if you don't specify `newline=''` when opening the file in write mode, Excel might display a blank line between each row.
  Fix: Always open CSV files with `newline=''` when exporting Tablib's CSV output to a file: `with open('output.csv', 'w', newline='') as f: f.write(data.export('csv'))`.
• gotcha The legacy XLS format (Excel 97-2003) has a limitation of 65,000 rows. If you are dealing with larger datasets, you should use the XLSX format instead.
  Fix: For datasets exceeding 65,000 rows, export to XLSX (`data.export('xlsx')`) rather than XLS (`data.export('xls')`).
• gotcha When importing XLSX or ODS files with `read_only=True` (which is the default for XLSX), Tablib relies on the spreadsheet declaring correct dimensions. Some programs might generate files with incorrect dimensions, leading to incomplete reads.
  Fix: If encountering issues with large XLSX/ODS files not importing fully, consider checking the spreadsheet source or, if possible, disable `read_only` (though this might increase memory usage for large files).

Install

• pip install tablib Core installation
• pip install "tablib[all]" Installation with all optional format dependencies
• pip install "tablib[xlsx, pandas, yaml]" Installation with specific optional format dependencies

Imports

• Dataset

  from tablib import Dataset

• Databook

  from tablib import Databook

  Used for handling multiple Dataset objects, typically for multi-sheet Excel files.

Quickstart

This quickstart demonstrates how to create a `Dataset` object, add headers, append rows, add a new column, and then export the data to different formats like CSV and JSON. It also includes a commented-out example for exporting to an XLSX file.

import tablib

# Create a new Dataset
data = tablib.Dataset()

# Add headers
data.headers = ['First Name', 'Last Name', 'Age']

# Add rows
data.append(['Kenneth', 'Reitz', 22])
data.append(['Bessie', 'Monke', 20])

# Add a new column with data
data.append_col([True, False], header='Is Student')

print("CSV Export:")
print(data.export('csv'))

print("\nJSON Export:")
print(data.export('json'))

# Example of saving to a file (uncomment to run)
# with open('output.xlsx', 'wb') as f:
#     f.write(data.export('xlsx'))
# print("\nData exported to output.xlsx")