60 Unit Testing courses

This Python BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career. -------------------------------------------------------------------------------- PYTHON BOOTCAMP: This 12-week Python Boot Camp is a practical, instructor-lead program, covering Python from start to in-depth. You will be fully fluent and confident as a Python programmer. If you have more questions goto https://pcworkshopslondon.co.uk/contact.html  [http://pcworkshopslondon.co.uk/contact.html], Or contact us on training@pcworkshopslondon.co.uk [https://pcworkshopslondon.co.uk/] Customise dates, course outline, arrange installments [https://pcworkshopslondon.co.uk/contact.htm] This course will give you enough practical experience and practical projects to code, to give you full confidence to enter into the coding profession.    Duration: 3 months: * 1 Python class per week, * Plus pratical work, * Plus personal trainer-mentor for 1-1 training, * Plus e-learning materials. Final project : Practical to upload to GitHub and show-case Date and times, choose: * Fridays in London or Online , 10am - 5pm, * or Saturdays in London or Online , 12noon-6pm, * or negotiate your date Study level: Start from beginners level to in-depth, ready to work professionally. Virtual attendance:  online instructor-led  Download: Anaconda.com Pre-requisites: General computer literacy. Oracle Qualification: PCWorkshops Python Programmer Certificate Payments:  You may apply to pay in installments for this Python Training course COURSE OUTLINE Week 1 - 4: Essentials 1. Python Coding Basics 2. Object Oriented programming: Python Object Orientated programming (OOP) 3. UX Principles: UX Principles and applying it on Front-ends with TKinter 4. Specialised topics: Dates, Localization, Strings, Maths Operation , Random Number, Lambdas Week 5 - 10 : All about data 1. Python Data Structures: Lists, Tuples, Sets, Exceptions, I/O Fundamentals , Reading and Writing file 2. Database: Database principles and SQL. Database Project: Python database connections and creating a database driven project 3. Data Analytics: Numpy. Pandas for data analytics and data queries. 4. Data Analytics: Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc. 5. Data visualisation: MatPlotLib 6. Prediction: Machine Learning Basics Week 11 and 12: The final touch 1. Python Concurrency and Multi-threading: Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks 2. Python Unit Testing 3. Optional : Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends INCLUDED: * PCWorkshops Python Course Certificate on completion. * Python Course notes. * Practical Course exercises, Code Examples, Online Materials. * After the course, continuous assistance with practical and preparation for exams * Max group size on this is 4. * Portfolio: Post your Python project online. * Exam preparation and interview questions MORE ABOUT THE ONLINE CLASSROOM *  Attend from your internet connection *  Instructor-led, get instant answers to your questions *  Fully interactive *  Work clearly explained with demonstrations and examples *  Practical exercises to be tried out by delegate WHAT YOU WILL GAIN: * Skills & knowledge: Python coding knowledge and understanding with good practical application   * Certification: Internal PCWorkshops Python certificate * Portfolio: You will have an online portfolio of Python projects  * Experience: Our comprehensive practical makes you job ready -------------------------------------------------------------------------------- REFUND POLICY No Refunds

From installation and project creation to writing tests with JUnit, Mockito, and Hamcrest, this course will cover all the important concepts that you need to get up and running with unit testing.

Why should I learn unit testing? Why spend extra time writing code to test? Is manual testing not sufficient? Well, if you have these questions, then you are on the right course. Unit testing is a very valuable skill in the current development cycle. The purpose is to validate that each unit of the software code performs as expected. So, let's dive into it!

This is a very comprehensive introduction to Spring Boot Test, which includes Mockito, JUnit, JSONassert, Spring Data JPA, REST, design pattern, and many more. You will learn to write JUnit tests with Spring Boot and Mockito for RESTful services.

This course delves into the rudiments of unit testing, including the red-green-refactor cycle, and provides in-depth knowledge on testing and implementing business logic in a .NET Core application, Develop the ability to design, write, and execute unit tests using xUnit and Moq for robust and scalable .NET Core applications.

Master Go programming with an in-depth course covering advanced topics such as authentication, authorization, JWT tokens, and refresh tokens. Learn how to write reliable code with effective unit testing techniques, while exploring concepts such as logging, error handling, and modularization. Build secure and scalable web applications with Go to take your coding expertise to the next level.

This course will help you master Spring, Spring Boot, Spring Modules - JDBC, AOP, and Data JPA through a hands-on, step-by-step approach. You will also be introduced to unit testing with JUnit and Mockito and learn how to communicate with the database using the Spring framework.

Learn BDD with SpecFlow (based on Gherkin) and Selenium WebDriver with C# alongwith an Intro to UnitTesting and TDD with TestStack.White

NETWORK AUTOMATION TRAINING COURSE DESCRIPTION This course concentrates on the technical side of tools and languages for network DevOps rather than the soft skills. These tools include Python, Ansible, Git and NAPALM By the end of the course delegates should be able to recognise the tools that they can use to automate their networks and be able to use the knowledge gained to feel confident approaching network automation. WHAT WILL YOU LEARN * Describe network DevOps. * Choose network automation tools. * Explain the role of various network automation technologies including: Python Ansible Git NAPALM NETWORK AUTOMATION TRAINING COURSE DETAILS * Who will benefit: Those wishing to learn about the tools of network automation. * Prerequisites: Introduction to data communications. * Duration 1 day NETWORK AUTOMATION TRAINING COURSE CONTENTS * What is DevOps and network automation Programming and automating networks, networks and clouds, AWS, OpenStack, SDN, DevOps for network operations. Unit testing. Hype vs reality. Benefits and features. * Network monitoring and troubleshooting Traditional methods, SNMP. Netflow and xflow. Traditional automation. Streaming telemetry. Event driven automation. gRPC, Protocol buffers. * Configuration management Catch 22 and initial configuration. ZTP, POAP. Traditional automation. TFTP. Ansible vs the rest (chef, salt, puppet). Jinja2 and templating. How ansible works. * Network programmability Programming languages. Linux, shell scripting. Python vs the rest. Off box vs on box automation. * Python network libraries Sockets pysnmp, ncclient, paramiko, netmiko, pyez, NAPALM. * APIs Proprietary APIs, CLI, NETCONF, RETCONF. YANG, XML, YAML, JSON. * Other tools Git, GitHub, Jenkins, JIRA and others.

ADVANCED PYTHON TRAINING COURSE DESCRIPTION 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. 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. ADVANCED PYTHON TRAINING COURSE DETAILS * Who will benefit: Network engineers. * Prerequisites: Python for network engineers * Duration 5 days ADVANCED PYTHON TRAINING COURSE CONTENTS * 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.