Robot Framework execution time analyzer

rf-output-analyzer.py

"""
The script analyzes output file from Robot Framework execution
and calculates total time spent on specific keyword and libraries.
This can help to optimize the code in places where the execution is longer.
It takes XML file and outputs the results into 2 separate CSV files:
    - kw_stats.csv that includes time spent on each keyword
    - lib_stats.csv that includes time spent on each library
Each file content is structured like this:
    <keyword or library name>;<total time in seconds>
To run the script just provide the path to XML file:
    execution-time-checker.py output.xml
"""

import sys
from collections import defaultdict
from robot.api import ExecutionResult, ResultVisitor


total_time = defaultdict(int)
total_time_libs = defaultdict(int)


class ExecutionTimeChecker(ResultVisitor):
    def visit_keyword(self, kw):
        if kw.type in ["IF/ELSE ROOT", "FOR ITERATION"]:
            return
        if kw.type == "KEYWORD":
            total_time[kw.name] += kw.elapsedtime / 1000
        if kw.libname:
            total_time_libs[kw.libname] += kw.elapsedtime / 1000
        for keyword in kw.keywords:
            self.visit_keyword(keyword)


def check_keywords(xml_file):
    result = ExecutionResult(xml_file)
    result.visit(ExecutionTimeChecker())
    sorted_result = dict(sorted(total_time.items(), key=lambda x: x[1], reverse=True))
    with open('kw_stats.csv', 'w') as f:
        f.write("Keyword;Total time [s]\n")
        for keyword, time in sorted_result.items():
            f.write("{keyword};{time:.3f}\n")

    sorted_result = dict(sorted(total_time_libs.items(), key=lambda x: x[1], reverse=True))
    with open('lib_stats.csv', 'w') as f:
        f.write("Library;Total time [s]\n")
        for keyword, time in sorted_result.items():
            f.write(f"{keyword};{time:.3f}\n")


if __name__ == "__main__":
    check_keywords(sys.argv[1])