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update notes/ci for Python313
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rpreen committed Oct 22, 2024
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2 changes: 1 addition & 1 deletion .github/workflows/tests.yml
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Expand Up @@ -18,7 +18,7 @@ jobs:
fail-fast: false
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
python-version: ['3.9', '3.10', '3.11', '3.12']

steps:
- name: Checkout
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---
name: Test Python312
name: Test Python313

on: workflow_dispatch

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fail-fast: false
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
python-version: ['3.12']
python-version: ['3.13']

steps:
- name: Checkout
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5 changes: 5 additions & 0 deletions CHANGELOG.md
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# Changelog

## Version 0.4.7 (Oct 22, 2024)

Changes:
* Add support for Pandas version 2 ([#237](https://github.com/AI-SDC/ACRO/pull/237))

## Version 0.4.6 (Jun 25, 2024)

Changes:
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7 changes: 4 additions & 3 deletions CITATION.cff
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cff-version: 1.2.0
title: ACRO
version: 0.4.6
doi: 10.5281/zenodo.12535291
date-released: 2024-06-25
version: 0.4.7
doi:
date-released: 2024-10-22
license: MIT
repository-code: https://github.com/AI-SDC/ACRO
languages:
Expand All @@ -13,6 +13,7 @@ keywords:
- privacy
- privacy tools
- statistical disclosure control
- statistical software
authors:
- family-names: Preen
given-names: Richard John
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29 changes: 12 additions & 17 deletions README.md
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This repository holds the Python ACRO package. An R wrapper package is available: [ACRO-R](https://github.com/AI-SDC/ACRO-R).

ACRO (Automatic Checking of Research Outputs) is an open source
tool for automating the statistical disclosure control (SDC) of research
outputs. ACRO assists researchers and output checkers by distinguishing between
research output that is safe to publish, output that requires further analysis,
and output that cannot be published because of substantial disclosure risk.

It does this by providing a light-weight 'skin' that sits over well-known
analysis tools, in a variety of languages researchers might use. This adds
functionality to:

* identify potentially disclosive outputs against a range of commonly used
disclosure tests;
A GUI for viewing and approving outputs is also available: [SACRO-Viewer](https://github.com/AI-SDC/SACRO-Viewer)

ACRO (Automatic Checking of Research Outputs) is an open source tool for automating the [statistical disclosure control](https://en.wikipedia.org/wiki/Statistical_disclosure_control) (SDC) of research outputs. ACRO assists researchers and output checkers by distinguishing between research output that is safe to publish, output that requires further analysis, and output that cannot be published because of a substantial risk of disclosing private data.

It does this by providing a lightweight 'skin' that sits over well-known analysis tools, in a variety of languages researchers might use. This adds functionality to:

* identify potentially disclosive outputs against a range of commonly used disclosure tests;
* suppress outputs where required;
* report reasons for suppression;
* produce simple summary documents TRE staff can use to streamline their
workflow.
* produce simple summary documents TRE staff can use to streamline their workflow.

![ACRO workflow and architecture schematic](docs/schematic.png)

Expand All @@ -37,15 +31,16 @@ If installed in this way, the example [notebooks](notebooks) and the [data](data
$ pip install acro
```

#### Notes for Python 3.12
#### Notes for Python 3.13

ACRO currently depends on an older version of Pandas (~1.5.0) for which no pre-compiled wheels are available within pip for Python 3.12. Therefore, in this scenario, Pandas must be built from source. This requires the installation of a C++ compiler before pip installing acro.
ACRO currently depends on numpy version 1.x.x for which no pre-compiled wheels are available within pip for Python 3.13. Therefore, in this scenario, numpy must be built from source. This requires the installation of a C++ compiler before pip installing acro.

For Windows, [Microsoft Visual Studio](https://visualstudio.microsoft.com/downloads/) and the [C++ build tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) will likely need to be installed first.
For Windows, the [Microsoft Visual Studio C++ build tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) will likely need to be installed first.

### Examples

See the example notebooks for:

* [Python charities dataset](notebooks/test.ipynb)
* [Python nursery dataset](notebooks/test-nursery.ipynb)
* [R charities dataset](https://ai-sdc.github.io/ACRO/_static/test.nb.html)
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7 changes: 0 additions & 7 deletions requirements.txt

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3 changes: 2 additions & 1 deletion setup.cfg
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Expand Up @@ -29,6 +29,7 @@ keywords =
privacy
privacy-tools
statistical-disclosure-control
statistical-software
project_urls =
Changelog = https://github.com/AI-SDC/ACRO/CHANGELOG.md
Documentation = https://github.com/AI-SDC/ACRO/wiki
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matplotlib
numpy<2.0.0
openpyxl
pandas>1.5.0,<2.3
pandas>=1.5.0,<2.3
PyYAML
statsmodels

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