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

#!/bin/python3

"""
    This script performs a software environment analysis on the outputs
    of the workflow to generate tables that can then be plotted by another
    program.
"""

import argparse
import csv
import os

def sources_stats(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 = {}
    i = 0
    for row in input_table:
        # Third column is the package source:
        if row[2] not in pkgmgr:
            pkgmgr[row[2]] = 1
        else:
            pkgmgr[row[2]] += 1
    return pkgmgr

def pkg_changed(table, artifact_name, pkgname, pkgsource):
    """
    Analyzes the given package lists table to determine if the given package
    changed for the given artifact.

    Parameters
    ----------
    table: str
        Table to analyse.

    artifact_name: str
        Name of the artifact for which we want to analyze package changes.

    pkgname: str
        The package we want to track changes.

    pkgsource: str
        Source of the package, in case there is multiple packages with the
        same name but different sources.

    Returns
    -------
    changed: bool
        True if the version number of the package changed over time, False
        otherwise.
    """
    changed = False
    i = 0
    pkgver = ""
    while i < len(table) and not changed:
        row = table[i]
        # Artifact name is in the 4th column, package name in the first,
        # and package source in the 3rd:
        if row[3] == artifact_name and row[0] == pkgname and row[2] == pkgsource:
            # If the first version number has not been saved yet:
            if pkgver == "":
                pkgver = row[1] # Package version is in the 2nd column
            elif row[1] != pkgver:
                changed = True
        i += 1
    return changed

def pkgs_changes(input_table):
    """
    Analyzes the given package lists table to determine the number of packages
    that changed for every package source.

    Parameters
    ----------
    input_table: str
        Table to analyse.

    Returns
    -------
    dict
        Output table of the analysis in the form of a dict with headers as keys.
    """
    pkgchanges_dict = {}
    # Key is the artifact name, and value is a list of tuples constituted
    # of the package that has been checked and its source for this artifact:
    # FIXME: Memory usage?
    checked_artifacts = {}
    i = 0
    for row in input_table:
        artifact_name = row[3] # Artifact name is in the 4th column
        if artifact_name not in checked_artifacts.keys():
            checked_artifacts[artifact_name] = []
        pkgname = row[0] # Package name is in the first column
        pkgsource = row[2] # Package source is in the 3rd column
        if (pkgname, pkgsource) not in checked_artifacts[artifact_name]:
            if pkg_changed(input_table, artifact_name, pkgname, pkgsource):
                # Third column is the package source:
                if row[2] not in pkgchanges_dict:
                    pkgchanges_dict[row[2]] = 1
                else:
                    pkgchanges_dict[row[2]] += 1
            checked_artifacts[artifact_name].append((pkgname, pkgsource))
    return pkgchanges_dict

def pkgs_per_container(input_table):
    """
    """
    pass

def main():
    # Command line arguments parsing:
    parser = argparse.ArgumentParser(
        prog = "softenv_analysis",
        description =
        """
        This script performs a software environment analysis on the outputs
        of the workflow to generate tables that can then be plotted
        by another program.
        """
    )
    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 software analysis to run. Depending on the
        type of analysis, multiple tables can be generated:
        the number of packages per source (a package manager, git or misc)
        by using `sources-stats`,
        the number of packages that changed over time (0 if only
        one file is given, since it will only include the package list
        of a single execution) by using `pkg-changes`,
        the number of packages per container by specifying `pkgs-per-container`.
        """,
        choices = ["sources-stats", "pkgs-changes", "pkgs-per-container"],
        required = True
    )
    parser.add_argument(
        "-i", "--input",
        action = "append",
        help =
        """
        The CSV file used as input for the analysis function. Multiple files
        can be specified by repeating this argument with different paths.
        All the input files must be package lists generated by ECG.
        """,
        required = True
    )
    parser.add_argument(
        "-o", "--output",
        help =
        """
        Path to the output CSV file that will be created by the analysis function.
        """,
        required = True
    )
    args = parser.parse_args()
    input_paths = args.input
    output_path = args.output
    analysis_type = args.analysis_type

    # Parsing the input files:
    input_table = []
    for path in input_paths:
        input_file = open(path)
        input_table += list(csv.reader(input_file))
        input_file.close()

    # Analyzing the inputs:
    if analysis_type == "sources-stats":
        output_dict = sources_stats(input_table)
    elif analysis_type == "pkgs-changes":
        output_dict = pkgs_changes(input_table)
    elif analysis_type == "pkgs-per-container":
        output_dict = pkgs_per_container(input_table)

    # Writing analysis to output file:
    output_file = open(output_path, "w+")
    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()