SOFTWARE-ARC-PYTHON.AJ1
Software Architecture with Python
A comprehensive training to design high-performance applications with Python.
- Practice in 27 Praktische Übungen — nothing to install
- 13 Interaktive Lektionen Und 83 topics mapped to the official exam objectives
- 128 Testfragen zur Praxis
Intermediate Selbstgesteuert · 1 Jahr Zugang 4.6/5 (193 Rezension)
27 Praktische LiveLabs
Practice real IT tasks in guided environments.
- Reale Umgebungen
- Automatisch bewertet
- Keine Installation
13Interaktive Lektionen
83Topics
27LiveLab
128Testfragen zur Praxis
174Karteikarten
174Glossar der Begriffe
01 / Fähigkeiten, die Sie erwerben
What you will be able to do
Try Free →
Keine Kreditkarte benötigt
Software Architecture with Python is an extensive training course that equips you with the skills to develop high-quality software applications using Python. The detailed course content covers everything from foundational concepts to advanced architectural patterns. You’ll begin with core fundamentals of software architecture like system and enterprise architecture, and design principles. By the end of this Python Architecture course, you’ll learn how to write clean, maintainable, and scalable codes.
- Understanding of the basic syntax and semantics: data types, operators, control flow statements, and more.
- Expertise with OOP concepts: classes, objects, inheritance, and more
- Organizing codes, working with file I/O & handling errors
- knowledge of Software Architecture fundamentals: modularity, cohesion, coupling, and more
- Ability to apply common design patterns & architectural patterns
- Optimize performance using profiling tools, algorithms & asynchronous programming
- Using multithreading and multiprocessing to optimize resources
- Knowledge of security best practices, cryptographic techniques & secure coding practices
- Conduct unit tests to verify the performance of individual codes
- Knowledge of debugging techniques to identity and fix errors
- Expertise with deployment strategies, deployment tools & DevOps practices
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Course Highlights
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13 Strukturierte Lektionen Umfassende Abdeckung der zentralen Kursziele
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27 Praktische LiveLabs Interaktive, geführte Szenarien mit sofortiger Auswertung
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128 Übungsfragen Bewertungstests mit ausführlichen Antwortbegründungen
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1 Jahr voller Zugang Selbstgesteuertes Lernen, jederzeit auf allen Geräten zugänglich
02 / Lektionen & Labore
See exactly what you will learn and practice
Unterrichtsplan
13 Interaktive Lektionen · 83 topics01 Preface 2 topics +
- What this course covers
- Conventions
02 Principles of Software Architecture 6 topics +
- Defining software architecture
- Characteristics of software architecture
- Importance of software architecture
- System versus enterprise architecture
- Architectural quality attributes
- Summary
03 Writing Modifiable and Readable Code 8 topics · 6 LiveLab +
- What is modifiability?
- Aspects related to modifiability
- Understanding readability
- Fundamentals of modifiability – cohesion and coupling
- Exploring strategies for modifiability
- Metrics – tools for static analysis
- Refactoring code
- Summary
6 LiveLab in this lesson — see the labs panel →
04 Testability – Writing Testable Code 3 topics · 4 LiveLab +
- Understanding testability
- White-box testing principles
- Summary
4 LiveLab in this lesson — see the labs panel →
05 Good Performance is Rewarding! 9 topics · 4 LiveLab +
- What is performance?
- Software performance engineering
- Performance testing and measurement tools
- Performance complexity
- Measuring performance
- Profiling
- Other tools
- Programming for performance – data structures
- Summary
4 LiveLab in this lesson — see the labs panel →
06 Writing Applications that Scale 13 topics · 5 LiveLab +
- Scalability and performance
- Concurrency
- Thumbnail generator
- Multithreading – Python and GIL
- Multithreading versus multiprocessing
- Pre-emptive versus cooperative multitasking
- The asyncio module in Python
- Waiting for a future – async and await
- Concurrent futures – high-level concurrent processing
- Scaling for the web
- Scaling workflows – message queues and task queues
- Celery – a distributed task queue
- Summary
5 LiveLab in this lesson — see the labs panel →
07 Security – Writing Secure Code 8 topics · 2 LiveLab +
- Information security architecture
- Secure coding
- Common security vulnerabilities
- Is Python secure?
- Security issues with web applications
- Strategies for security – Python
- Secure coding strategies
- Summary
2 LiveLab in this lesson — see the labs panel →
08 Design Patterns in Python 6 topics +
- Design patterns – elements
- Categories of design patterns
- Patterns in Python – creational
- Patterns in Python – structural
- Patterns in Python – behavioral
- Summary
09 Python – Architectural Patterns 5 topics +
- Introducing MVC
- Event-driven programming
- Microservice architecture
- Pipe and Filter architectures
- Summary
10 Deploying Python Applications 5 topics +
- Deployability
- Tiers of software deployment architecture
- Software deployment in Python
- Deployment – patterns and best practices
- Summary
11 Techniques for Debugging 6 topics · 6 LiveLab +
- Maximum subarray problem
- Simple debugging tricks and techniques
- Logging as a debugging technique
- Debugging tools – using debuggers
- Advanced debugging – tracing
- Summary
6 LiveLab in this lesson — see the labs panel →
12 Appendix - A 7 topics +
- Installing Python
- Running Python
- Basic syntax
- Conditional statements and loops
- Data structures
- Functions
- Summary
13 Appendix - B 5 topics +
- Object-oriented programming
- Modules and packages
- File operations
- Error and exception handling
- Summary
Praktische Übungen Our edge
27 LiveLabs- Documenting the Code
- Understanding the Concept of Cohesion
- Finding the McCabe Metric
- Running a Static Checker
- Fixing Code Smells by Refactoring the Code
- Fixing Code Complexity by Refactoring the Code
- Measuring Code Coverage
- Unit Testing a Module
- Using Test-Driven Development
- Unit Testing Using doctest
- Measuring the Performance of Code Using timeit
- Collecting and Reporting Statistics
- Profiling with cProfile
- Implementing an LRU Cache Dictionary
- Using the Multiprocessing Pool Object
- Creating a Co-operative Multitasking Scheduler Using Simple Python Generators
- Using the asyncio Module
- Using async and await
- Using the concurrent.futures Module
- Serializing an object using code jail
- Making the Code Secure for Input
- Debugging Maximum Subarray Problem
- Generating Random Patient Data Using the schematics Library
- Debugging the Word Searcher Program
- Creating a Log File Using Logger Objects
- Creating a Simple Log File
- Debugging with pdb
Labore laufen direkt im Browser — nichts zu installieren.
03 / FAQS
Fragen, bevor Sie beginnen
Do I need prior Python knowledge?+
No, you don’t necessarily need to have Python knowledge. However, it is recommended to have prior programming experience.
What advanced topics are covered here?+
This Python Architecture course covers several advanced topics like:
- Design patterns
- Architectural patterns
- Concurrency & parallelism
- Performance profiling & optimization
- Deployment strategies
- DevOps practices
Will I learn about cloud-based architecture?+
Yes, this course covers some topics of cloud-based development including:
- Microservices Architecture
- Deployment & DevOps
- Performance optimization
Do I need any specific skills in Software Engineering for this course?+
No, you don’t need any specific skills to start this course as it covers the fundamentals concepts of software engineering.
What are the career advantages of this Software Architecture training?+
Learning this course will give you a competitive edge by making you a highly-sought after professional. With the right knowledge and experience, you can progress towards leadership roles like technical lead or chief architect.
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- 1 Jahr voller Zugang
- 27 LiveLab enthalten
- Abschlusszertifikat
Keine Kreditkarte benötigt