study-docker-repro-longevity/analysis/output_analysis.py

125 lines
3.3 KiB
Python
Executable File

#!/bin/python3
"""
This script will analyze the outputs from ECG to generate tables that will
be later plotted.
"""
import argparse
import csv
import os
def softenv_analysis(input_table):
"""
Analyzes the given package lists table to determine the number of artifacts
using a package manager, Git packages or misc packages.
Parameters
----------
input_table: str
Table to analyse.
Returns
-------
dict
Output table of the analysis in the form of a dict with headers as keys.
"""
pkgmgr = {}
for row in input_table:
# Third column is the package source:
if row[2] in pkgmgr:
pkgmgr[row[2]] += 1
else:
pkgmgr[row[2]] = 1
return pkgmgr
def artifact_analysis(input_table):
"""
Analyzes the given artifact hash table to determine the number of artifacts
that change through time.
Parameters
----------
input_table: str
Table to analyse.
Returns
-------
dict
Output table of the analysis in the form of a dict with headers as keys.
"""
return {}
def buildstatus_analysis(input_table):
"""
Analyzes the given build status table.
Parameters
----------
input_table: str
Table to analyse.
Returns
-------
dict
Output table of the analysis in the form of a dict with headers as keys.
"""
return {}
def main():
# Command line arguments parsing:
parser = argparse.ArgumentParser(
prog = "output_analysis",
description = "This script analyzes the outputs from ECG to create " \
"tables."
)
parser.add_argument('-v', '--verbose',
action = 'store_true',
help = "Shows more details on what is being done."
)
parser.add_argument(
"-t", "--analysis-type",
help = "Specify the type of analysis to run.",
choices = ["soft-env", "artifact", "build-status"],
required = True
)
parser.add_argument(
"input_dir",
help = "Path to the directory where the CSV files used as input for " \
"the analysis function are stored. They must be all outputs from ECG."
)
parser.add_argument(
"output_path",
help = "Path to the output CSV file that will be created by the " \
"analysis function."
)
args = parser.parse_args()
analysis_type = args.analysis_type
input_dir = args.input_dir
output_path = args.output_path
# Parsing the inputs from the directory:
input_table = []
for input_path in os.listdir(input_dir):
input_file = open(os.path.join(input_dir, input_path))
input_table += list(csv.reader(input_file))
input_file.close()
# Analyzing the inputs:
output_file = open(output_path, "w+")
output_dict = {}
if analysis_type == "soft-env":
output_dict = softenv_analysis(input_table)
elif analysis_type == "artifact":
output_dict = artifact_analysis(input_table)
elif analysis_type == "build-status":
output_dict = buildstatus_analysis(input_table)
# Writing analysis to output file:
dict_writer = csv.DictWriter(output_file, fieldnames=output_dict.keys())
dict_writer.writeheader()
dict_writer.writerow(output_dict)
output_file.close()
if __name__ == "__main__":
main()