sample_data_factory 0.2.0

Reusable test data factory for CSV and FIDE XML archives.

sample_data_factory

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Short description

sample_data_factory is a reusable Python helper for generating deterministic ZIP archives used in test flows, including URS CSV exports and FIDE players XML exports.

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Release Highlights

• Package metadata and import paths have been aligned to sample_data_factory and sdf.
• Archive generation now covers both URS CSV and FIDE players XML ZIP outputs through SampleDataFactory.
• RTE API URS player export generation now produces pipe-delimited player CSV archives from FIDE-style source rows.
• Google Drive uploads support optional nested sub-folder creation for organized artifact output.
• Python runtime support is aligned to >=3.10 in project configuration.

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Versioning and Releases

• Current package version: 0.2.0.
• Versioning follows SemVer (MAJOR.MINOR.PATCH) for all package releases.
• Release notes are generated from the active branch diff against master.

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Module Overview

Key Features

• Builds URS publication ZIP archives containing CSV payloads.
• Builds FIDE players-list ZIP archives containing XML payloads.
• Builds RTE API URS player ZIP archives containing pipe-delimited CSV payloads.
• Supports either local byte output or upload to Google Drive.
• Can create nested Google Drive sub-folders when uploading files.
• Includes unit tests for archive generation and constructor validation.

Project Structure

• src/sdf/: Core package implementation (sample_data_factory.py).
• tests/unit/: Unit tests for archive builders and helper methods.
• scripts/: SQL/bootstrap assets (legacy resources have been removed).
• legacy/: Archived resources excluded from normal test runs.
• *.ps1: Environment and dependency setup scripts.

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Getting Started

Prerequisites

• Python 3.10+
• Poetry

Setup

# 1) Generate .env values from environment variables
.\SetupDotEnv.ps1

# 2) Configure private Poetry sources when required
.\SetupPrivateRepoAccess.ps1

# 3) Optional: configure GitHub CLI access
.\SetupGitHubAccess.ps1

# 4) Install and sync project dependencies
.\InstallDevEnv.ps1

# 5) Run tests
poetry run pytest

Usage Example

from datetime import date

from sdf.sample_data_factory import SampleDataFactory

factory = SampleDataFactory(
    data_structure={
        "headers": ["PlayerID", "PlayerName"],
        "rows": [["1", "Player One"], ["2", "Player Two"]],
    },
    drive=None,
    file_prefix="Players",
    out_file_date=date(2026, 1, 1),
    target_folder_id=None,
    sub_folder_name=None,
)

archive_bytes = factory.build_urs_rating_pub_zip()

Common Commands

poetry install
poetry run pytest
poetry run pytest --cov=src --cov=tests --cov-report=term-missing
poetry run black src tests
poetry run isort src tests
poetry run flake8 src tests
poetry run pre-commit run --all-files

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Automation Scripts

• InstallPy.ps1: Bootstraps Python/Poetry setup.
• InstallDevEnv.ps1: Installs development dependencies and pre-commit hooks.
• SetupDotEnv.ps1: Generates .env from required environment variables.
• SetupPrivateRepoAccess.ps1: Configures private package source credentials.
• SetupGitHubAccess.ps1: Configures GitHub authentication for local automation.

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Active Workflows

• .github/workflows/py-temp-pr-pub-no_docker-def.yaml: Pull request validation workflow.
• .github/workflows/py-temp-publish-pub-build_release_notify_after_merge-def.yaml: Post-merge release and publish workflow.