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--- scripts:index [2024/10/08 10:15] – created antonio.andriychuk
+++ scripts:index [2024/10/08 10:50] (current) – added CDRs antonio.andriychuk
@@ Line 1: / Line 1: @@
-====== Concurrent Usage Script ======
+====== Scripts ======
-<code python>
-import pandas as pd
-import datetime
-import json
-# Creating the Dates used to rename the files at the end of the process
-today = datetime.date.today()
-first = today.replace(day=1)
-last_month = first - datetime.timedelta(days=1)
-year = last_month.strftime("%Y")
-month = last_month.strftime("%m")
-# Dictionary to map month numbers to month names
-months_dict = {
-    '01': 'jan',
-    '02': 'feb',
-    '03': 'mar',
-    '04': 'apr',
-    '05': 'may',
-    '06': 'jun',
-    '07': 'jul',
-    '08': 'aug',
-    '09': 'sep',
-    '10': 'oct',
-    '11': 'nov',
-    '12': 'dec'
-}
-# Update month name using the dictionary
-month_name = months_dict.get(month)
-# Retrieving DataFrame
-df = pd.read_csv('license_usage_report.csv')
-# Dropping last 5 rows
-df.drop(df.tail(5).index, inplace=True)
-# Convert "Time" column to datetime format with specified format
-df['Time'] = pd.to_datetime(df['Time'], format='%Y-%m-%d %H:%M:%S (%Z)')
-# Filter DataFrame based on year and month
-filtered_df = df[(df['Time'].dt.year == int(year)) & (df['Time'].dt.month == int(month))]
-# Initialize an empty list to store the formatted rows
-formatted_rows = []
-# filtered_df.to_csv("license_usage_report_08_2024.csv", index=False)
-# Iterate over each row in the filtered DataFrame
-for index, row in filtered_df.iterrows():
-    # Extract the values from the columns
-    time = row['Time']
-    user = row['Number of Users']
-    tenant = row['Tenant Name']
-    # Format the row as a JSON object with a comma at the end
-    formatted_row = '\n{"time":"' + str(time) + '", "users":' + str(user) + ', "tenant_name":"' + str(tenant) + '"},'
-    formatted_rows.append(formatted_row)
-# Remove the comma and newline from the last row
-if formatted_rows:
-    formatted_rows[-1] = formatted_rows[-1][:-2]  # Remove the last two characters, which are the comma and newline
-# Construct the JSON array
-json_data = '[' + ''.join(formatted_rows) + '}\n]'
-# Request user whether it's FK or SYD
-region = input('Is the region FK or SYD? ')
-list_region = ['FK', 'fk', 'SYD', 'syd']
-if region not in list_region:
-    print('Error ecountered, check script and fix the issue...')
-    exit()
-else:
-    match region:
-        case 'FK':
-            region = 'fk'
-        case 'SYD':
-            region = 'syd'
-        case 'fk':
-            region = 'fk'
-        case 'syd':
-            region = 'syd'
-# Save the .csv file
-filtered_df.to_csv('usage_' + month_name + '_' + year + '_' + region + '.csv', index=False)
-# Write the JSON data to a file
-with open('usage_' + month_name + '_' + year + '_' + region + '.json', 'w') as json_file:
-    json_file.write(json_data)
-# Re-loads the file
-array = json.loads(json_data)
-# Setting variables
-t = ''
-sum = 0
-max = []
-# Saves a list of UNIQUE tenant names
-ten = [{"tenant": array[0]["tenant_name"], "check": False}]
-b = False
-for i in range(len(array)):
-    for j in range(len(ten)):
-        if ten[j]["tenant"] == array[i]["tenant_name"]:
-            b = True
-    if not b:
-        tmp = {"tenant": array[i]["tenant_name"], "check": False}
-        ten.append(tmp)
-    b = False
-# Sums of the concurrent tenants per each timeframe, used for the next step to find the maximum licence usage
-for i in range(len(array)):
-    if t == array[i]["time"]:
-        for j in range(len(ten)):
-            if ten[j]["tenant"] == array[i]["tenant_name"]:
-                if not ten[j]["check"]:
-                    sum += array[i]["users"]
-                    ten[j]["check"] = True
-    else:
-        t = array[i]["time"]
-        temp = {"users": sum, "time": array[i]["time"]}
-        max.append(temp)
-        for j in range(len(ten)):
-            ten[j]["check"] = False
-        for j in range(len(ten)):
-            if ten[j]["tenant"] == array[i]["tenant_name"]:
-                if not ten[j]["check"]:
-                    sum = array[i]["users"]
-                    ten[j]["check"] = True
-# This line will just find the maximum licence usage
-res = None
-tmp = 0
-for i in range(len(max)):
-    if tmp < max[i]["users"]:
-        res = max[i]
-        tmp = max[i]["users"]
-# Prints the maximum of connected licence on the platform
-print("This is the max --> ", res['users'])
-filtered_df.to_csv("usage.csv", index=False)
-</code>
+[[ConcurrentUsage:index|Concurrent Usage]]\\
+[[CDRs:index|CDRs]]\\