tsbuddy 0.0.3

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Tech Support Buddy (tsbuddy)

Tech Support Buddy is a versatile Python module built to empower developers and IT professionals in resolving technical issues. It provides a suite of Python functions designed to efficiently diagnose and resolve technical issues by parsing raw text into structured data, enabling automation and data-driven decision-making.

Table of Contents

• Overview
• Key Features
• Installation
• Usage
  • Basic Example: Parsing Temperature Data
• Future Enhancements (Ideas)
• Contributing

Overview

Dealing with raw text output can be tedious and time-consuming. tsbuddy parsing aims to simplify this by providing tools to:

1. Extract relevant sections from log files or command output.
2. Parse this raw text into structured Python objects.
3. Enable programmatic analysis and decision-making based on the parsed data.

This allows you to quickly turn unstructured command output into actionable insights.

Key Features

• Log Section Extraction: Easily isolate specific command output or sections from larger support files.
• Structured Data Parsing: Convert unstructured command output into Python objects for easy manipulation. (Simple example below).
• Simplified Diagnostics: Build custom logic on top of parsed data to automate checks, generate reports, trigger alerts or actions.
• Developer-Friendly: Designed to be easily integrated into existing Python scripts and workflows.

Installation

You can install tsbuddy via pip:

pip install tsbuddy

Usage

tsbuddy can be run directly from your preferred terminal. Doing so will run the main() function where tsbuddy will search for tech_support.log in your working directory & output its contents to a CSV.

(venv) admin:~/tech_support_complete$ tsbuddy
✅ CSV exported to parsed_sections_2025-05-30_220933.csv

Here's a basic example demonstrating how to use tsbuddy within Python to parse temperature information from command output.

Basic Example: Parsing Temperature Data

For this example, we will use a file named tech_support.log in your working directory.

1. Import tsbuddy and pprint:

import tsbuddy as ts
from pprint import pprint

2. Read your log file:

(For this example, we'll simulate reading from the file. tsbuddy itself can work on any source of text.)

# Example content for 'tech_support.log' stored in the file_text variable
# This would typically be read from the actual file
file_text = """
Some initial lines...
show system, show chassis, etc

show temperature
Chassis/Device   Current Range      Danger Thresh Status
---------------- ------- ---------- ------ ------ ---------------
1/CMMA       47      15 to 60   68     60     UNDER THRESHOLD
3/CMMA       46      15 to 60   68     60     UNDER THRESHOLD
4/CMMA       46      15 to 60   68     60     UNDER THRESHOLD


Some other lines...
show ip interface, etc
...
"""

3. Extract the relevant section:

The extract_section function helps you get the raw text for a specific command or section.

# Extract the section containing "show temperature" output
temp_section_text = ts.extract_section(file_text, "show temperature")

# print("--- Raw Extracted Text ---")
# print(temp_section_text)
## Seen above, without other section output

4. Parse the raw text into a structured format:

tsbuddy provides parsers for specific commands. Here, we use parse_temperature.

# Parse the raw temperature text to structured data
parsed_temps = ts.parse_temperature(temp_section_text)

print("--- Parsed Temperature Data ---")
pprint(parsed_temps, sort_dicts=False)

This will output:

--- Parsed Temperature Data ---
[{'Chassis/Device': '1/CMMA',
  'Current': '47',
  'Range': '15 to 60',
  'Danger': '68',
  'Thresh': '60',
  'Status': 'UNDER THRESHOLD'},
 {'Chassis/Device': '3/CMMA',
  'Current': '46',
  'Range': '15 to 60',
  'Danger': '68',
  'Thresh': '60',
  'Status': 'UNDER THRESHOLD'},
 {'Chassis/Device': '4/CMMA',
  'Current': '46',
  'Range': '15 to 60',
  'Danger': '68',
  'Thresh': '60',
  'Status': 'UNDER THRESHOLD'}]

5. Work with the structured data:

Now that the data is structured, you can easily access and process specific fields.

# Request data from specific fields
print("\n--- Device Statuses ---")
for chassis in parsed_temps:
    print(chassis["Status"])

Output:

--- Device Statuses ---
UNDER THRESHOLD
UNDER THRESHOLD
UNDER THRESHOLD

6. Add custom logic:

You can build more complex logic based on the values of specific fields.

print("\n--- Devices with Current Temperature greater than 46°C ---")
for chassis in parsed_temps:
    if int(chassis["Current"]) > 46:
        print(chassis["Chassis/Device"] + " is greater than 46°C")

Output:

--- Devices with Current Temperature greater than 46°C ---
1/CMMA is greater than 46°C

Future Enhancements (Examples)

The tsbuddy module is designed to be extensible. Future development could include:

• More parsers for common log outputs (e.g., show fabric, vrf ... show ..., debug show ...).
• Functions to compare states (e.g., before/after changes).
• Integration with alerting systems.
• Parse configuration.
• Convert configurations.
• Auto-detect parsing function.
• Generate tech-support & validate generation.
• Support outputting to MS Excel.
• Support for different log formats & devices.
• More sophisticated section extraction logic.

Contributing

Contributions are welcome! If you have ideas for improvements or new features, or if you've found a bug, please feel free to:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/YourFeature or bugfix/YourBugfix).
3. Make your changes.
4. Commit your changes (git commit -m 'Add some feature').
5. Push to the branch (git push origin feature/YourFeature).
6. Open a Pull Request.

Please ensure your code adheres to any existing style guidelines and includes tests where appropriate.