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Process for Improving PTL Framework

The process for improving the PTL framework is the same as .

PTL Directory Structure

true

Construction of PTL

PTL is derived from Python's unittest.

PTL uses nose plugins.

Testing PTL

Tests that test PTL are in pbspro/test/test/selftest, at https://github.com/PBSPro/pbspro/tree/master/test/tests/selftest

Enhancing PTL for New PBS Attributes

How to Add a New Attribute to the Library

This section is for PBS developers who may be adding a new job, queue, server, or vnode attribute, and need to write tests that depend on their new attribute. PTL does not automatically generate mappings from API to CLI, so when adding new attributes, it is the responsibility of the test writer to define the attribute conversion in ptl/lib/pbs_api_to_cli.py. They must also define the new attribute in ptl/lib/pbs_ifl_mock.py so that the attribute name can be dereferenced if the SWIG wrapping was not performed.
For example, let's assume we are introducing a new job attribute called ATTR_geometry that maps to the string "job_geometry". In order to be able to set this attribute for a job:

We need to define it in pbs_api_to_cli.py as follows:

ATTR_geometry: "W job_geometry="

Add it to ptl/lib/pbs_ifl_mock.py as follows:

ATTR_geometry: "job_geometry"

In order to get the API to use the new attribute, rerun pbs_swigify, so that symbols from pbs_ifl.h are read in

Nose Plugins for PTL

true

Improving the PTL Framework