wdadaptivepy 0.2.1

Wrapper for Workday Adaptive Planning's API

wdadaptivepy

A python wrapper for the Workday Adaptive Planning API, providing an easy-to-use library to create, read, update, and delete data, metadata, and other information within Adaptive.

Overview

Workday Adaptive Planning is a cloud-based planning, reporting, and analysis solution. This library simplifies interacting with the Adaptive Planning API via a Pythonic interface.

Features

• Functionality
  • Retrieve information from Adaptive
    • Support for metadata
      • Account
      • Attributes
      • Currencies
      • Dimensions
      • Level
      • Time
      • Version
    • Support for data
      • Generic Data
      • Modeled Sheet Data
    • Support for users
      • Users
      • Groups
    • Support for security
      • Permission Sets
  • Support for data formats
    • Import/export data using JSON
    • Import/export data using XML
    • Export data using CSV
  • Helper functions
    • Get base/leaf members
    • Get parent/branch members
    • Get parent of a member
    • Get children of a member
    • Get ancestors of a member
    • Get descendents of a member

Planned Features

• Functionality
  • Send information to Adaptive
    • Support for metadata
      • Account
      • Attributes
      • Currencies
      • Dimensions
      • Level
      • Time
      • Version
    • Support for data
      • Generic Data
      • Modeled Sheet Data
    • Support for users
      • Users
      • Groups
    • Support for security
      • Permission Sets
  • Integrations
    • Tasks
  • Support for data formats
    • Import/export data using XLSX
    • Import data using CSV
    • Import/export data using TXT
  • Helper functions
    • Get raw API requests
    • Get raw API responses
  • Logging
  • Workday Authentication Token

Getting Started

Pre-requisites

• Python 3.10+
• Valid credentials (username/password) for an active Workday Adaptive Planning account
  • wdadaptivepy will be limited to the access granted to the Adaptive user (ie: wdadaptivepy will respect Adaptive's user security)

Installation

• Run pip install wdadaptivepy

Example Usage

Retrieving Levels

from wdadaptivepy import AdaptiveConnection


adaptive = AdaptiveConnection(username="[e-mail]", password="Y0urP@$$w0rd!")

levels = adaptive.levels.get_all()

Retrieving Data

from wdadaptivepy import AdaptiveConnection


adaptive = AdaptiveConnection(username="[e-mail]", password="Y0urP@$$w0rd!")

query = (
    adaptive.data.query_data()
    .add_account_filter(accounts="Revenue")
    .add_level_filter(levels="Total Company")
    .set_version_filter(version="Default Version")
    .set_time_filter(start_period="01/2023", end_period="01/2023")
)
data = query.get_data()

Documentatation

• wdadaptivepy

  • wdadaptivepy Source Code
  • wdadaptivepy Documentation
  • wdadaptivepy PyPI Project

• Workday Adaptive Planning

  • Workday Adaptive Planning XML API Documentation
  • Workday Adaptive Planning JSON API Documentation
  • Workday Adaptive Planning API Changelog

Issues

Please submit an issue on the GitHub repository for any bugs or issues that are found. For any security vulnerabilities, please email [e-mail] with a summary of the vulnerability.

Contribute

The preferred tools for developing wdadaptivepy are listed below. Other tools can be used, but the guide will assume the stack below is used.

• Github (code repository)
• git (version control system)
• uv (Python manager, Python builder)
• Visual Studio Code (editor)
• ruff (linter, formatter)
• pyright (static type checker)
• pytest (testing)
• mkdocs-material (documentation)

Develop

1. Fork the wdadaptivepy repo
2. Git clone the forked repo onto your device (eg: git clone [e-mail]:YOUR_GITHUB_ACCOUNT/YOUR_FORKED_REPO_NAME.git)
3. Within the cloned directory, run uv sync --no-install-project to create a Python virtual environment and install all dependencies
4. Complete any modifications to the source code
5. Ensure all modified code is covered by tests via uv run pytest --cov
6. Ensure all tests pass
7. Commit all changes (eg: git commit -m "Added functionality for recent Adaptive release")
8. Create pull request for committed changes