Scenario Processing¶
The workflow for processing files uploaded via the IIASA Scenario Explorer is implemented in a modular fashion. This makes it straightforward to execute programs, code and tools developed by (non-IIASA) research partners as part of the processing workflow.
Requirements for processing modules¶
Any module (a.k.a. program, code or tool) must adhere to the following standards of best-practice software development. The aim of these guidelines is to ensure reliability of our services, minimize maintenance requirements, and guarantee reproducibility of results across platforms.
General requirements¶
The program, code or tool must be implemented in Python (≥3.7) or R; compiled executables are not acceptable for security reasons
Distribution of the source code - via an online version-controlled repository (preferably GitHub) to which the IIASA admin team has access; or - installation via a package manager (pip, conda, CRAN).
The program must run on Windows and Linux to give us flexibility where/how we execute the processing workflow.
The dependencies must be clearly stated, e.g. as Dockerfile (describing execution environment, library dependencies etc.) Python package dependencies according to packaging user guide (e.g. as environment.yml, requirements.txt etc.) R dependencies
The license must be clearly stated.
The documentation of the program, code or tool must include:
Purpose of the program and individual top-level functions
Instructions how to run the program
Expected input (variables, region mappings) and standard output
Explanation of any settings and optional parameters
Application programming interface¶
Option 1:
The module is called via a command-line interface (CLI) and take the following arguments:
input
: path to an IAMC-formatted file (xlsx
orcsv
)output
: path where to write an output file (usually derived timeseries data) in the same formatAny relevant settings and optional parameters must also be specified via the CLI
e.g. "python process.py --input path-to-input-file.xlsx --output path-to-output-file.xlsx"
Option 2 (applicable for packages/functions written in Python):
Importable Python functions that take and return
pandas.DataFrame
(with columns folllowing the IAMC format)
or pyam.IamDataFrame
objects
can be called as part of the processing workflow.
Any settings or optional parameters must be given as keyword arguments
to the top-level function.