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EDD Per Download License Calculations
# Script: EDD Per Download License Calculations
# Author: Frank Corso
# Date Created: 04/05/2020
# Last Modified: 07/16/2020
# Python Version: 3.6.5
# Takes exports of licenses from EDD and turns it into a CSV of totals and averages.
# To use, have CSVs of licenses for each download in EDD in a 'licenses' directory with each
# saved as edd-export-licenses-(download-slug).csv
# Put this script above that directory. In terminal, run python
from os import listdir
from os import path
import pandas as pd
import re
def calculate_license_stats():
"""Loads all license exports and generates simplified aggregated license CSV."""
# Edit this if you name your CSV files something different.
p = re.compile(r'edd-export-licenses-(.+).csv')
# Edit this to change input and output directories
in_dir = 'licenses'
out_dir = 'data-output'
# Begins creating our new dataframe for our new CSV.
totals = pd.DataFrame(columns=['Extension', 'Total Licences', 'Active/(Active+Inactive)', 'Active Licenses',
'Inactive Licenses', 'Expired Licenses', 'Total Activated Sites',
'AVG Site Per Licence', 'Total Active Activated Sites',
'AVG Active Site Per Active License'])
# Loop over all files in directory.
for file in listdir(in_dir):
print('Loading...', file)
# Checks filename for REGEX defined above. If matches, uses that as download name.
# If not matching, skips this file.
extension_search = p.findall(file)
if len(extension_search) > 0:
extension_name = extension_search[0]
print('Not using this file...')
df = pd.read_csv(path.join(in_dir, file))
# Make our calculations.
total_activated = df['Activation Count'].sum()
total_avg_activated = round(df['Activation Count'].mean(), 2)
active = df[df['License Status'] == 'active']
inactive = df[df['License Status'] == 'inactive']
expired = df[df['License Status'] == 'expired']
active_activated = active['Activation Count'].sum()
active_avg_activated = round(active['Activation Count'].mean(), 2)
active_percent = round(len(active) / (len(active) + len(inactive)), 3)
# Adds new row to dataframe.
totals.loc[len(totals)] = [extension_name, len(df), active_percent, len(active), len(inactive), len(expired),
total_activated, total_avg_activated, active_activated, active_avg_activated]
# Puts dataframe into our new CSV.
print('Writing results to file...')
totals.to_csv(path.join(out_dir, 'license-data.csv'))
if __name__ == '__main__':
print('Calculating license stats...')
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