Warning The library is currently in the early stages of development and is not suitable for production, the api can and will change. Opening the development to the community at an early stage, will generate discussion on the direction, increase bug detection and promote faster iterations towards a beta release.

What is supplychainpy?

Supplychainpy is a python library for common supply chain data analysis tasks. The library aims to reduce the work required for supply chain analysis and expand the tools available to analysts.

Why is supplychainpy useful?

• A Common Tool. Several types of supply chain analysis require many calculations and often a spreadsheet. Domains such as Finance, Econometrics and Statistics already have libraries across several programming languages. In fact statics libraries like pystatmodel can be used for supply chain analysis fundamentals like forecasting etc. Supplychainpy is more focused on being a decision support tool for analysts in commercial inventory and demand planning roles. The library focuses on domain specific implementation issues.
• More tools Using an object orientated programming language like python exposes your data and analysis to cutting edge tools outside the remit of a spreadsheet. Tools like Pandas and Jupyter as well as other libraries. Supplychainpy allows you to include these optional dependencies in your work flow, lowering the bar to entry by providing a supply chain specific library with api.
• Scalability. use a .txt or .csv source or data direct from a database using a dapi or orm like sqlalchemy.
• Quicker Development. Writing and rewriting formulas can become a repetitive task and may include manual steps, when moving from project to project or organisation to organisation. A comprhensive library of common supply chain computations prepackaged in a library for an accessible programming language, could greatly speed up analysis and free up the analyst for more decision making instead of tool making.
• Fast Implementation. while spreadsheets excel at calculations, data intensive computations are difficult without using a programming language. Although VBA is provided by default in Microsoft Excel, it is not a panacea for these type of tasks, better alternatives exist. Python with the assistance of openpyxl or xlwings can add the power of python to your spreadsheet computations.

Where can you get supplychainpy?

Download and install using pip, from Pypi or the source directly by cloning the Github repo.