Advanced Python for network engineers Training

  • Learn via: Online Instructor-Led / Classroom Based / Onsite
  • Duration: 5 Days
  • Level: Expert
  • Price: Please contact for booking options
  • UK Based Global Training Provider

This course caters to network engineers aiming to enhance both their Python proficiency and network automation skills. Delving deeper into key areas such as netmiko, Nornir, and ncclient, we also focus on automating network testing and validation. Participants gain greater confidence working with Python functions, classes, objects, and error handling. The course additionally introduces more libraries like Scrapli, TTP, pyATS, Genie, pybatfish, and Suzieq, which cover parsing strategies, automation testing, validation, network analysis, observability, and telemetry. The curriculum also encompasses concurrency techniques. Save time automating network tasks with python. Postman, automating validation, automating testing.

We can organize this training at your preferred date and location. Contact Us!

Prerequisites

There are no formal prerequisite courses, however delegates are advised to know all of the knowledge in our Python for network engineers .

What You Will Learn

What will you learn

  • Write Python modules and functions.
  • Evaluate techniques to parse unstructured data.
  • Use NETCONF filters.
  • Handle Python errors effectively (try, assert…).
  • Use postman.
  • Automate testing and validation of the network.
  • Use scrapli, Genie, batfish and Suzieq.

Training Outline

Review

CLI, NETCONF, RESTCONF, structured versus unstructured data, gNMI and when to use which. PEP 8. Naming conventions. Packages, modules, Classes and methods. The scrapli library. Netmiko versus scrapli.

Hands on: scrapli, Dictionaries versus Regular Expressions.

Modules and Functions

Writing your own modules, containers versus packages, virtual environments. Best practices, calling functions, writing your own functions. Parameters, arguments. Named arguments, dictionaries as arguments. Builtins. Docstrings. Main. __name__, __main__ . Program arguments.

Hands on: Getting interfaces, showing interface status using Netmiko and functions. Using dictionaries as arguments. Writing your own modules.

Parsing strategies

Turning unstructured data into structured data. textfsm, PyATS Genie parser, NAPALM getters, Template Text Parser.

Hands on: Genie parser, TTP. Accessing structured data with lists and dictionaries.

Classes, objects and Python

Python classes in Genie, PyEZ and others .

Hands on: studying network automation classes, objects, methods and attributes.

Configuration management – more nornir, ncclient, requests

Nornir tasks. Nornir results, Nornir functions, Nornir plugins. Nornir processors. YANG, YANG models, pyang. NETCONF hello. Capabilities. Schemas. Filters. Subtrees. XPATH. Exploring available YANG data models. NETCONF and network wide transactions. Asserting NETCONF capabilities. Configuration types. Locking configurations, commits. NETCONF data stores. Netconf-console. RESTCONF differences from NETCONF. URI construction. Postman. More XML and JSON. Git and configuration versions.

Hands on: Nornir and Jinja2. Exploring available models, NETCONF filters. Using postman.

Python error handling and debugging

Context handlers, try, assert, logging, pdb, pytest, unit testing, chatgpt.

Hands on: Writing code with each of the error handling methods, investigating what happens on an error. Use chatgpt to debug your code.

Python Automation Testing

Testing and validation. pyATS, Genie. Testbed file. Genie parse, genie learn, genie diff. Genie conf, Genie ops, Genie SDK, Genie harness. Xpresso.

Hands on: Using Genie for state comparisons of the network.

Network analysis

Batfish, pybatfish, configuration analysis, analysing routing, analysing ACLs. Pandas. Pandas dataframe. Filtering and selecting values of interest.

Hands on: Use Batfish to analyse network snapshots, find network adjacencies, flow path analysis.

Network observability

Suzieq, using docker, using as a package. Sqpoller, suzieq-gui, suzieq-cli, sq-rest-server. Namespaces and seeing devices, network state and Asserts. Time based analysis, snapshots and changes.

Hands on: Suzieq: Gathering data from the network, analysing data from the network. Network state assertion.

Telemetry

gRPC, gNMI. CAP, GET, SET. Subscriptions. Model Driven telemetry.

Hands on: Analysing telemetry data with Python.

Concurrency

asyncio, threads, processes. Nornir concurrency. Scrapli and netmiko concurrency.

Hands on: Multiple SSH connections to devices at same time. Scarpli asyncio.

Why Choose Us

Experience Advanced Python for network engineers through Bilginç IT Academy's live and interactive virtual classroom environment, accessible from your home, office, or any location. Connect with expert trainers in real time and bring the energy of classroom learning into the digital experience.

  • Live Instructor-Led Sessions: Join scheduled training sessions with your instructor and fellow delegates in real time.
  • Interactive Learning Experience: Take part in discussions, practical exercises, group activities, and Q&A sessions throughout the course.
  • Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
  • Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's long-standing experience in delivering professional training since 1995.
  • Flexible and Scalable Delivery: Access live virtual classrooms worldwide with flexible planning options for individual and corporate training needs.

Experience Advanced Python for network engineers in a focused classroom environment designed for high engagement and effective learning. Bilginç IT Academy's carefully selected training venues provide a professional setting where delegates can interact directly with expert trainers and peers.

  • Experienced Trainers: Learn from specialists with extensive field experience and real-world knowledge.
  • Professional Training Venues: Attend courses in comfortable, well-equipped classrooms designed to support effective learning.
  • Focused Classroom Experience: Benefit from limited class sizes that encourage discussion, interaction, and personalized support.
  • Quality-Driven Learning: Develop practical skills through structured, up-to-date, and professionally designed training content.

Meet your team's training needs with Bilginç IT Academy's onsite Advanced Python for network engineers solution, delivered at your office or preferred location. Align your team's development with your business goals through a training experience tailored to your organization.

  • Tailored Course Content: Adapt the training program to your organization's projects, team structure, and specific business requirements.
  • Time and Cost Efficiency: Reduce travel, accommodation, and operational costs while maximizing the value of your training investment.
  • Team-Focused Learning: Help your employees develop around the same knowledge base and strengthen collaboration across your organization.
  • Simplified Planning and Tracking: Manage the training process, participant development, and organizational requirements with greater control.


Contact us for more detail about our trainings and for all other enquiries!

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