DataProperty
Python library for extract property from data.
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and solves a specific problem—extracting data properties for inspection and formatting. It's appropriate for data processing, validation, and table rendering tasks. The MIT license poses no restrictions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later.
- Low friction: pure Python wheel with only two runtime dependencies (mbstrdecoder, typepy).
- Active maintenance with a recent release (97 days ago) and current commit history.
License · maintenance · safety
MIT License (permissive) — MIT License permits unrestricted use, modification, and distribution in both open-source and proprietary projects with minimal obligations.
last release 2026-05-09 (97 days) · last repo commit 2026-07-27 · 17 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 13,610,310 downloads/mo, #1,272 on PyPI
Alternatives
Verify before relying
pip install DataProperty
from dataproperty import DataProperty
result = DataProperty(-1.1)
print(result) # data=-1.1, type=REAL_NUMBER, align=right, ascii_width=4, ...- Performance characteristics when processing large matrices or high-cardinality datasets.
- Whether the package handles edge cases like very large numbers or unusual string encodings beyond the documented examples.
What it is and what it does
DataProperty is a Python library that analyzes individual values and tabular data to extract structural and formatting properties. For a single value, it determines its type (integer, float, string, boolean, datetime, NaN, infinity) and computes metadata like display width, alignment, digit counts, and decimal places. For matrices, it can extract properties for each cell or aggregate properties by column, returning objects that describe the characteristics of each column's data.
The library is designed for data inspection and formatting tasks—useful when you need to understand how data should be displayed, validate type consistency across columns, or prepare metadata for table rendering. It handles multi-byte strings, special numeric values, and mixed-type columns, making it practical for data cleaning, validation, and presentation workflows.
Use it for
- Inspect and classify the type and formatting properties of individual values before processing or display.
- Analyze tabular data to determine column types and optimal display widths for formatted output.
- Validate data consistency by extracting type information from each cell in a matrix.
- Generate metadata for table rendering systems that need alignment, width, and type hints.
- Detect and handle edge cases like NaN, infinity, and mixed-type columns in data validation pipelines.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and solves a specific problem—extracting data properties for inspection and formatting. It's appropriate for data processing, validation, and table rendering tasks. The MIT license poses no restrictions.
Install
dataproperty on PyPI
Before you install
Low friction: pure Python wheel with only two runtime dependencies (mbstrdecoder, typepy). Active maintenance with a recent release (97 days ago) and current commit history.
Requires Python 3.9 or later.
License in practice
MIT License permits unrestricted use, modification, and distribution in both open-source and proprietary projects with minimal obligations.
Quickstart
pip install DataProperty
from dataproperty import DataProperty
result = DataProperty(-1.1)
print(result) # data=-1.1, type=REAL_NUMBER, align=right, ascii_width=4, ...Verify before relying
- Performance characteristics when processing large matrices or high-cardinality datasets.
- Whether the package handles edge cases like very large numbers or unusual string encodings beyond the documented examples.
Package facts
| License | MIT License permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesmbstrdecodertypepy |
| Maintenance | Actively maintained 97 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 13,610,310 / month, #1,272 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Information TechnologyLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python ModulesTyping :: Typed |
Evidence: dataproperty-1.1.1-py3-none-any.whl
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