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Dive deep into the realm of asynchronous programming in Python with our comprehensive course on the high-level API of Asyncio. Asynchronous programming is crucial for building efficient, concurrent, and scalable applications, and this course equips you with the knowledge and skills to leverage Asyncio effectively.

You'll start by exploring the fundamentals of asynchronous programming, including coroutines and tasks. Learn how coroutines enable non-blocking operations and how tasks help manage concurrent operations efficiently.

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Dive deep into the realm of asynchronous programming in Python with our comprehensive course on the high-level API of Asyncio. Asynchronous programming is crucial for building efficient, concurrent, and scalable applications, and this course equips you with the knowledge and skills to leverage Asyncio effectively.

You'll start by exploring the fundamentals of asynchronous programming, including coroutines and tasks. Learn how coroutines enable non-blocking operations and how tasks help manage concurrent operations efficiently.

Next, discover the power of asynchronous context managers and the async with syntax for resource management in asynchronous code. Understand how to handle groups of tasks seamlessly using the TaskGroup() class and the gather() function, enabling you to coordinate and execute multiple asynchronous operations concurrently.

Gain proficiency in working with asynchronous iterators and the async for syntax, allowing you to iterate over asynchronous sequences effortlessly. Explore the capabilities of asynchronous comprehensions for creating asynchronous sequences efficiently.

Delve into asynchronous generators to create asynchronous context managers easily. Learn how to utilize asynchronous queues for communication and data exchange between asynchronous tasks in a thread-safe manner.

Finally, understand the importance of synchronization mechanisms such as Lock, Semaphore, Event, and Condition for coordinating access to shared resources and ensuring thread-safe execution of coroutines.

By the end of this course, you'll be equipped with the expertise to design and implement robust, concurrent Python applications using the high-level API of Asyncio. Take your asynchronous programming skills to the next level and unlock new possibilities in Python development.

Topics

- what are coroutines and tasks

- asynchronous context managers, async with syntax

- groups of tasks using TaskGroup() class and gather() function.

- asynchronous iterators and async for syntax

- asynchronous comprehensions

- asynchronous generators

- asynchronous queues

- synchronization of coroutines using Lock, Semaphore, Event, Condition

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What's inside

Syllabus

Basics and Further Steps

What is asynchronous programming and what issues it solves. What is async/await keywords.

What are coroutines, how to create, and call them

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What are tasks, how to create, use, and cancel them

Demonstration of some non-obvious issues of how the run() function works.

We will look at implementation of context managers, and we will write an Asynchronous Context manager

How to use the gather() to run coroutines, and gather their results

Demonstration of non-obvious issues when using await keyword.

The TaskGroup() class was introduced in Python 3.11 how to use it, and its features.

In this video, we'll explore the differences in task cancellation when using the gather() function versus the TaskGroup() class.

How to create a class which implements the iteration protocol to use with async for syntax.

How to use asynchronous comprehensions to generate lists, dicts, sets

Main use case of generators is creating of context managers using the contextlib module, and @contexmanager decorator. In this video we'll look at creating of async context managers using the @asynccontexmanager decorator

What is Queue as a data structure, how to use queues, and what is the Producer-Consumer pattern

In this video we will write an asynchronous crawler that will download images.
This crawler will use 3 different queues to store intermediate results.

What is the synchronization of coroutines and why do we need sometimes to use it.
The first synchronization primitive - Lock() class

The second synchronization primitive in AsyncIO - Semaphore() class.
In this video we will write a requests rate limiting decorator function.

Event() - the way to build a notification system for your app, if you need to notify some part of your program about some events.

The last synchronization class - Condition() class, and how to use it

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores asynchronous programming, which is essential for building scalable and concurrent applications, allowing developers to optimize performance and handle more requests efficiently
Covers coroutines and tasks, which are fundamental concepts in asynchronous programming, enabling developers to write non-blocking code and manage concurrent operations effectively
Discusses asynchronous context managers and the 'async with' syntax, providing developers with tools for managing resources efficiently in asynchronous code, ensuring proper cleanup and preventing resource leaks
Examines the TaskGroup() class and gather() function, which are useful for coordinating and executing multiple asynchronous operations concurrently, allowing developers to improve application responsiveness
Teaches asynchronous queues, which are valuable for communication and data exchange between asynchronous tasks in a thread-safe manner, facilitating the development of robust concurrent applications
Requires Python 3.11 to use the TaskGroup() class, so learners using older versions of Python may need to upgrade their environment to fully benefit from the course

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Reviews summary

Deep dive into python asyncio

According to learners, this course provides a solid foundation and comprehensive coverage of the high-level Asyncio API in Python. Students particularly praise the clear explanations of core concepts like coroutines, tasks, and synchronization primitives. The course includes practical examples and demos, such as building a web crawler, which help solidify understanding. While students say it's largely positive, some note it assumes a basic understanding of Python and isn't for absolute beginners, but it's an excellent starting point for asynchronous programming.
Good for understanding Asyncio fundamentals.
"Excellent foundation for anyone starting with Asyncio development."
"Helps build a strong understanding of how async works under the hood."
"Perfect course to get started with asynchronous Python programming."
Comprehensive coverage of key Asyncio features.
"Covers TaskGroup, gather, async context managers, and async iterators."
"Synchronization primitives like Lock and Semaphore are explained thoroughly."
"Gets into the high-level API details effectively for practical use."
Includes helpful code examples and demos.
"Loved the web crawler demo, showed how queues work in a real scenario."
"Code examples provided are very useful for practice alongside lectures."
"Hands-on examples solidify the theory discussed in the videos."
Explains core Asyncio ideas well.
"The course really helped clarify what coroutines and tasks are."
"Concepts like async/await and event loops were explained simply."
"Instructor makes complex ideas easy to grasp, especially synchronization."
Assumes prior Python knowledge is necessary.
"This course isn't for absolute beginners to Python programming."
"You need a solid grasp of Python fundamentals before taking this course."
"Having some prior experience with threading or concurrency helps but isn't strictly required."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python Asyncio: High-level API with these activities:
Review Python Concurrency
Refresh your understanding of Python's concurrency model to better grasp Asyncio's role and benefits.
Browse courses on Concurrency
Show steps
  • Review the differences between threads and processes.
  • Study the Global Interpreter Lock (GIL) and its implications.
  • Practice writing basic multithreaded programs in Python.
Read 'Concurrency with Modern C++'
Gain a deeper understanding of concurrency concepts by exploring how they are implemented in C++.
Show steps
  • Read the chapters on threads and tasks.
  • Study the sections on mutexes and condition variables.
  • Compare C++'s concurrency features to Python's Asyncio.
Implement Producer-Consumer with Asyncio Queues
Reinforce your understanding of Asyncio queues by implementing the classic producer-consumer pattern.
Show steps
  • Create an Asyncio queue.
  • Write asynchronous producer coroutines to add items to the queue.
  • Write asynchronous consumer coroutines to process items from the queue.
  • Test the implementation with multiple producers and consumers.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Blog Post: Asyncio Task Cancellation
Solidify your knowledge of task cancellation by writing a blog post explaining the nuances of using gather() versus TaskGroup().
Show steps
  • Research the differences in task cancellation behavior.
  • Write example code demonstrating each scenario.
  • Explain the implications for error handling.
  • Publish the blog post on a platform like Medium or Dev.to.
Build an Asynchronous Web Scraper
Apply your Asyncio skills to build a practical web scraper that can efficiently fetch data from multiple websites concurrently.
Show steps
  • Choose a website to scrape.
  • Use an asynchronous HTTP client library like aiohttp.
  • Implement coroutines to fetch and parse web pages concurrently.
  • Store the scraped data in a database or file.
  • Add error handling and logging.
Asyncio Performance Comparison Report
Create a report comparing the performance of synchronous vs. asynchronous code for a specific task, highlighting the benefits of Asyncio.
Show steps
  • Choose a task suitable for asynchronous execution (e.g., network requests).
  • Implement both synchronous and asynchronous versions of the task.
  • Measure the execution time of each version with varying workloads.
  • Analyze the results and create a report with graphs and charts.
  • Summarize the findings and draw conclusions about Asyncio's performance benefits.
Contribute to an Asyncio Library
Deepen your understanding of Asyncio by contributing to an open-source library that uses it.
Show steps
  • Find an Asyncio-based open-source project on GitHub.
  • Identify a bug or feature request to work on.
  • Implement the fix or feature, following the project's coding style.
  • Submit a pull request with your changes.
  • Respond to feedback from the project maintainers.

Career center

Learners who complete Python Asyncio: High-level API will develop knowledge and skills that may be useful to these careers:
Python Developer
A Python developer specializes in developing applications using the Python programming language. The Python Asyncio course is specifically designed to enhance a Python developer's skills in asynchronous programming. The course helps Python developers understand the nuances of coroutines, tasks, and asynchronous generators, empowering them to build more efficient and responsive applications. Understanding asynchronous comprehensions will assist the developer as well. The course's coverage of asynchronous queues is also useful for managing data flow between different parts of an application. A Python developer who wants to improve their concurrency skills should enroll in this course.
Software Engineer
A software engineer designs, develops, and tests software applications. This course, focusing on the high-level API of Asyncio in Python, directly applies to the work of a software engineer, especially those involved in building concurrent and scalable applications. The course helps engineers understand and implement asynchronous programming concepts such as coroutines, tasks, asynchronous context managers, and asynchronous iterators. Furthermore, the course's coverage of synchronization mechanisms like Lock, Semaphore, Event, and Condition provide a strong foundation for building thread-safe and efficient applications. A software engineer seeking to enhance their skills in asynchronous Python development should take this course. This is especially useful when they need to use the TaskGroup() class.
Backend Developer
A backend developer focuses on the server-side logic and databases that power applications. This course on Python's Asyncio is highly relevant to backend development, as it provides the tools and knowledge to build efficient and scalable server-side applications. A backend developer can use the concepts taught in this course, such as asynchronous context managers and iterators, to optimize resource management and data processing. The study of asynchronous queues for communication between tasks will also assist the developer. This course's exploration of synchronization primitives is useful for managing concurrent access to databases and ensuring data integrity. This course may be helpful for a backend developer by helping them learn to write efficient code.
Full-Stack Developer
A full stack developer works on both the front-end and back-end of applications. This course on Python's Asyncio can benefit full stack developers by enhancing their ability to build efficient and scalable backends using asynchronous programming. By learning about coroutines and tasks, a full stack developer writing the backend can improve the performance of their APIs and server-side logic. Asyncio can create context managers as well. The course's exploration of asynchronous queues is useful for managing data flow between different parts of the application, while knowledge of synchronization primitives improves the handling of concurrent requests. This course may be helpful for a full stack developer to gain better understanding of asynchronous programming.
DevOps Engineer
A DevOps engineer bridges the gap between development and operations, focusing on automating and streamlining the software development lifecycle. This course on Python's Asyncio is valuable for DevOps engineers who need to manage and optimize the performance of Python-based applications in production environments. A DevOps engineer can use the knowledge gained from this course to implement asynchronous task execution and resource management, improving the scalability and resilience of applications. The course's coverage of synchronization primitives can assist in ensuring the stability of deployments. This course may be useful for a DevOps engineer to help them manage asynchronous applications.
Cloud Engineer
A cloud engineer is responsible for designing, building, and maintaining cloud infrastructure and applications. This course on Python's Asyncio is relevant to cloud engineers because asynchronous programming is crucial for building scalable and resilient cloud-native applications. Cloud engineers can use the concepts taught in this course, such as coroutines and asynchronous context managers, to optimize resource utilization and improve the performance of cloud services. This exploration of synchronization primitives assists in managing concurrent access to cloud resources. A cloud engineer may find this course helpful for ensuring high performance.
Machine Learning Engineer
A machine learning engineer develops and deploys machine learning models and systems. This course on Python's Asyncio can be valuable for machine learning engineers in various ways. It can help them build efficient data pipelines for training models, optimize the deployment of models for real-time inference, and manage concurrent access to machine learning resources. Machine learning engineers benefit from the understanding of coroutines and asynchronous context managers. Asynchronous queues are useful for managing tasks, and knowledge of the synchronization primitives is useful managing data access. This course may be useful to machine learning engineers.
Data Engineer
A data engineer builds and maintains the infrastructure for data storage, processing, and analysis. This course on Python's Asyncio can benefit data engineers by improving their ability to build efficient data pipelines and processing systems using asynchronous programming. Data engineers can use the concepts taught in this course—such as asynchronous iterators and queues—to optimize data ingestion, transformation, and loading processes. Also, the knowledge of synchronization primitives helps with the handling of concurrent data access. Data engineers may find this course helpful for enhancing their skillset.
Software Architect
A software architect is responsible for designing the overall structure and architecture of software systems. This course on Python's Asyncio can be valuable for software architects who need to design scalable and concurrent applications. By understanding the principles of asynchronous programming and the capabilities of Asyncio, software architects can make informed decisions about how to structure their systems to achieve high performance and responsiveness. Also, Asynchronous queues may be helpful here. This course may be useful for a software architect seeking familiarity with Asyncio specifics.
Technical Lead
A technical lead is responsible for guiding and mentoring a team of developers, as well as making technical decisions about the direction of a project. This course on Python's Asyncio can benefit technical leads by providing them with a deeper understanding of asynchronous programming concepts and best practices. A technical lead can use this knowledge to guide their team in building efficient and scalable Python applications. The technical lead gains an understanding of asyncio concepts such as how to use TaskGroup() class features, async queues and iterators, and ways to implement context managers. This course may be useful for a technical lead.
Database Administrator
A database administrator manages and maintains databases, ensuring their availability, performance, and security. Understanding asynchronous programming can be beneficial when dealing with Python applications interacting with databases. They may find this course helpful in understanding how asynchronous operations can improve database performance and concurrency. The course's coverage of synchronization mechanisms helps with managing concurrent access to databases. This course may be useful to a database administrator.
Network Engineer
A network engineer designs, implements, and manages computer networks. While this course focuses on Python asynchronous programming, it may be relevant to network engineers who use Python for network automation and management tasks. Understanding asynchronous programming can help them build efficient and responsive network management tools. A network engineer gains an understanding of asyncio iterators, context managers, and other features. This course may be useful to a network engineer.
Security Engineer
A security engineer is responsible for protecting computer systems and networks from security threats. While this course primarily focuses on asynchronous programming in Python, a security engineer may find it useful to understand how asynchronous operations can impact security, especially in concurrent systems. Learning about synchronization primitives can help in understanding how to prevent race conditions and other concurrency-related security vulnerabilities, such as use of the Semaphore() class. This course may be useful to a security engineer.
Data Analyst
A data analyst collects, processes, and analyzes data to provide insights and support decision-making. While this course focuses on asynchronous programming, data analysts often use Python for data processing and analysis tasks. An understanding of asynchronous iterators and comprehensions as taught in this course, can help them optimize data processing pipelines and improve the performance of their analysis scripts. This course may be useful to a data analyst.
Technical Writer
A technical writer creates documentation for software and hardware products. While this course dives into asynchronous programming, a technical writer with programming experience may find it useful for documenting Python libraries or systems that use asynchronous constructs. The concepts presented, such as coroutines and asynchronous generators, can help improve documentation. A technical writer may find this course useful.

Reading list

We've selected one books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Python Asyncio: High-level API.
Provides a comprehensive overview of concurrency concepts, which are transferable to Python's Asyncio. While focused on C++, it offers valuable insights into managing threads, tasks, and synchronization primitives. It is particularly helpful for understanding the underlying principles behind asynchronous programming. This book is more valuable as additional reading than it is as a current reference.

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