Well... chatGPT, collab, automation, monolithic code and bad APIs

Let's just be honest about the state of things from an automation standpoint:

import pandas as pd

import re

# Variable Definitions

template_file_name = 'phonebuttontemplate.csv'

device_file_name = 'deviceprofile.csv'

modified_device_file_name = 'deviceprofile_modified.csv'

replacement_value = 'DELETED'

end_column_number = 89

print_line_counts = False  # Flag this if you encounter issues and want to print the Line count for each row in the template csv

first_column_name = 'Device Profile Name'

# Read phonebuttontemplate.csv

print("Reading phonebuttontemplate.csv...")

template_df = pd.read_csv(template_file_name)

# Store header row

header_row_template = list(template_df.columns)

# Initialize a dictionary to store the values

template_dict = {}

# Loop through the DataFrame rows

for _, row in template_df.iterrows():

    name = row.get('NAME', None)

    # Check if the row has a NAME and is not empty

    if pd.notna(name):

        # Check each column for "Line", "Speed Dial", or "None" under the "TYPE OF FEATURE \d{1,2}" pattern

        count = 0

        empty_value_encountered = False

        for col in header_row_template:

            if re.match(r'TYPE OF FEATURE \d{1,2}', col):

                value = row[col]

                if value == 'Line':

                    count += 1

                elif value == 'None':

                    empty_value_encountered = True

                    break

        # If an empty value was encountered, stop counting and break the loop

        if empty_value_encountered:

            break

        template_dict[name] = {'count': count + 1}  # Start the count from 1

        # If print_line_counts is True, print the name of the template and the count of its lines

        if print_line_counts:

            print(f"{name}: {count + 1} lines")

# Read deviceprofile.csv

print("Reading deviceprofile.csv...")

device_df = pd.read_csv(device_file_name)

# Store header row

header_row_device = list(device_df.columns)

# Iterate over the rows in deviceprofile.csv

for index, row in device_df.iterrows():

    template_name = row['Phone Button Template']

    device_profile_name = row[first_column_name]

    if pd.notna(template_name) and pd.notna(device_profile_name):

        # Check if the template name exists in the template_dict

        if template_name in template_dict:

            template_info = template_dict[template_name]

            count = template_info['count']

            directory_number_col = f'Directory Number {count}'

            call_id_presentation_col = f'Calling Line ID Presentation When Diverted {end_column_number}'

            device_df.loc[index, directory_number_col:call_id_presentation_col] = replacement_value

# Write the DataFrame to a new file

device_df.to_csv(modified_device_file_name, index=False)

print("Processing completed successfully.")

The prominent issue in terms of coding is chatGPT, which needs to be addressed when considering collaboration (collab).

To begin with, it would be beneficial to develop a universal UC API that can merge various methods and functions, enabling the automation of any task. Although this idea is intriguing, it necessitates the complete rewriting of these large-scale applications. The goal would be to leverage AI and prioritize an API-first approach.

Once this is accomplished, a standardized UC dashboard could be implemented. This would unify platforms like Webex and CUCM, allowing for seamless provisioning, integration, and communication without the need for intermediary components. These components were not specifically designed for the purpose and still rely on outdated Unix code, essentially being rooted in the Tandberg system.

I propose a significant transformation, a genuine movement empowered by AI, to bring UC up to date and in line with current advancements.

Anyhow, that's my hot-take.  I am working on automating all the provisioning in my lab, check back here in a couple months.  Maybe I will have a solid solution.  As it stands right now I just have a certificate generation, request and load API for various UC devices.  

That is the start of my ucEngineersToolKit API

Good day and may it be a great one!