Tips

Tip! Validate your env vars from your .env files before they hit your application by using Pydantic. This also eliminates the need to call python-dotenv manually. Here's an example: # uv add pydantic pydantic-settings python-dotenv from pydantic import Field, AnyHttpUrl, ValidationError from pydantic_settings import BaseSettings, SettingsConfigDict # Define settings

For those still working with Excel spreadsheets, here's a quick tip ... To easily work with data from an Excel spreadsheet in Python, use the Pandas library. First, import the spreadsheet, then iterate over the data, using itertuples, like so: # Install - pip install pandas import pandas as pd

🐍 Python Tip: Improve code readability by enforcing named arguments. To enforce all arguments to be named, start your parameter list with *. Here’s an example: def add_vlan(*, vlan_id, name): print(f"VLAN ID: {vlan_id}") print(f"Name: {name}") add_vlan(vlan_id=10,

pyATS Tip! By default, pyATS runs several exec/config commands and logs to stdout when connecting. You can disable these using the parameters in the example below: device.connect( init_exec_commands=[], # Disable default exec commands init_config_commands=[], # Disable default config commands log_stdout=False # Disable logging to stdout

Jinja Tip: Validate and check your Jinja templates for syntax errors with j2lint. Ideal for integrating into a CI pipeline. ➜ https://github.com/aristanetworks/j2lint Here is an example below 👇 $ uv tool install j2lint $ cat config.j2 hostname {%for int in interfaces%} interface ip address {{int.ip}} {{int.NetMask}} {%endfor

PySentry - Scan your Python dependencies for known vulnerabilities. Built in Rust for performance, PySentry is fast, easy to use, and supports flexible output formats (Markdown, JSON, etc.). Here are some examples 👇 # Install pysentry-rs using uv (or use pip install pysentry-rs) $ uv add pysentry-rs # Run a security scan on the

A quick Panda tip for you... Import nested data into a DataFrame using json_normalize with record_path and meta. Here’s an example 👇 import pandas as pd data = [ { "network_device": { "hostname": "spine1-nxos", "os_version": "9.3.7", "interface&

Ansible Tip: Use the dict2items filter to loop over dictionaries in Ansible. Here's an example: --- - name: Example of dict2items filter hosts: localhost gather_facts: false vars: interfaces: eth0: ip: "192.168.1.1/24" eth1: ip: "192.168.2.1/24" tasks:

NetBox Query Tip! If you need to search for a cable by its ID, use GraphQL by visiting: https://your_nb_instance/graphql/ Then run the following query, replacing YOUR_CABLE_ID with the actual cable ID: query { cable(id: YOUR_CABLE_ID) { id label type status color length length_