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Python 3 Performance
Dan Tofan
Dan Tofan
Python developers love Python's high productivity. Unfortunately, many
Python applications suffer from slow performance. This course is about
concrete approaches for improving the performance of your Python
applications.
Read more
Python developers love Python's high productivity. Unfortunately, many Python applications suffer from slow performance. This course is about concrete approaches for improving the performance of your Python applications.
Read more
Python developers love Python's high productivity. Unfortunately, many Python applications suffer from slow performance. This course is about concrete approaches for improving the performance of your Python applications.
Are your Python applications running slowly? If yes, this Python 3 Performance course is going to give you concrete approaches to increase the speed of your Python applications. First, you will learn how to measure the performance of Python applications. Next, you will discover how to write faster Python code by using the right data structures. Finally, you will learn how to speed up your applications using threads, asyncio, and more processes. Take this course and make your Python applications faster!
Register for this course and see more details by visiting:
OpenCourser.com/course/ee7q1d/python
What's inside
Syllabus
Course Overview
Measuring Performance
Using the Right Data Structures
Optimizing Python Code
Read more
Syllabus
Course Overview
Measuring Performance
Using the Right Data Structures
Optimizing Python Code
Read more
Using More Threads
Using Asynchronous Code
Using More Processes
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores concrete approaches to enhance the performance of your Python applications, a vital skill for developers
Led by Dan Tofan, a recognized expert in Python performance optimization
Covers crucial topics, including performance measurement, data structure optimization, and concurrency techniques
Provides hands-on practice with real-world examples, enhancing your understanding and practical implementation abilities
May require prior experience in Python programming for optimal comprehension
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Activities
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Python 3 Performance.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Python 3 Performance will develop knowledge and skills
that may be useful to these careers:
Python Developer
Python Developer
A Python Developer may be interested in the Python 3 Performance course because it can help them write faster and more efficient code. The course covers topics like writing optimized code, choosing the right data structures, and using threads and asynchronous programming. This knowledge can help Python Developers create more scalable and performant Python applications.
Performance Engineer
Performance Engineer
Performance Engineers will appreciate the Python 3 Performance course as it covers advanced topics such as using more threads, using asynchronous code, and using more processes, which are essential for writing performant systems. The course also covers measuring performance, which is crucial for identifying and fixing performance bottlenecks.
Software Developer
Software Developer
A Software Developer may wish to consider the Python 3 Performance course if they are interested in learning how to make their Python applications run faster. The course covers measuring application performance, and optimizing code using the right data structures, threads, and processes. This knowledge can help Software Developers create more efficient and performant Python applications.
Full-Stack Developer
Full-Stack Developer
The topics covered in the Python 3 Performance course, such as optimizing code for speed and using concurrency, are valuable for Full Stack Developers who want to create high-performance Python applications. The course can help Full Stack Developers write more efficient and scalable Python code, which can lead to improved performance for both the frontend and backend of their applications.
Backend Developer
Backend Developer
A Backend Developer may consider the Python 3 Performance course if they want to learn how to optimize the performance of their Python backend applications. The course covers topics like choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Backend Developers create more efficient and scalable Python backend applications.
Software Architect
Software Architect
Python 3 Performance is a great course for Software Architects who want to learn how to design and implement high-performance Python applications. The course covers topics such as choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Software Architects create scalable and efficient Python applications.
Web Developer
Web Developer
Python 3 Performance is a suitable course for Web Developers who want to learn how to optimize the performance of their Python web applications. The course covers topics such as choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Web Developers create more efficient and scalable Python web applications.
Data Analyst
Data Analyst
A Data Analyst may wish to consider the Python 3 Performance course if they are interested in learning how to measure and optimize the performance of their Python code. The course covers using the right data structures, threads, and processes to improve code speed. This can be valuable for Data Analysts who need to process large amounts of data efficiently and quickly.
DevOps Engineer
DevOps Engineer
For those working as a DevOps Engineer, the Python 3 Performance course may help build a foundation in Python performance optimization techniques. The course covers topics like measuring performance, optimizing code, and using threads and asynchronous programming. This knowledge can help DevOps Engineers identify and fix performance bottlenecks in Python applications.
Data Engineer
Data Engineer
For those working in the field of Data Engineering, the Python 3 Performance course may be helpful for learning how to optimize the performance of Python data engineering pipelines. The course covers topics like choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Data Engineers create more efficient and scalable Python data engineering pipelines.
Data Scientist
Data Scientist
A Data Scientist may wish to consider the Python 3 Performance course to learn how to make their Python code more efficient. The course covers topics such as choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Data Scientists create more efficient and scalable Python data science applications.
Mobile Developer
Mobile Developer
A Mobile Developer may find the Python 3 Performance course beneficial if they want to learn how to optimize the performance of their Python mobile applications. The course covers topics such as choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Mobile Developers create more efficient and scalable Python mobile applications.
Cloud Engineer
Cloud Engineer
Taking the Python 3 Performance course may be useful for Cloud Engineers who want to learn how to optimize the performance of Python applications running in the cloud. The course covers topics like choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Cloud Engineers create more efficient and scalable Python cloud applications.
Machine Learning Engineer
Machine Learning Engineer
The Python 3 Performance course can be useful for Machine Learning Engineers who want to learn how to optimize the performance of their Python machine learning models and applications. The course covers topics such as choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Machine Learning Engineers create more efficient and scalable Python machine learning applications.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst may wish to consider the Python 3 Performance course to learn how to optimize the performance of their Python quantitative finance models and applications. The course covers topics such as choosing the right data structures, optimizing code for speed, and using concurrency. This knowledge can help Quantitative Analysts create more efficient and scalable Python quantitative finance applications.
For more career information including salaries, visit:
OpenCourser.com/course/ee7q1d/python
Reading list
We've selected 15 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 3 Performance.
Covers advanced techniques for optimizing Python code, including techniques for profiling, memory management, and concurrency. It provides a deep dive into the Python interpreter and the underlying CPython implementation.
Provides a comprehensive overview of Python performance optimization techniques. It covers topics such as profiling, data structures, algorithms, and concurrency and includes practical examples and case studies.
Save
Covers data structures and algorithms in Python, which are essential for understanding Python performance optimization. It provides a comprehensive overview of the most common data structures and algorithms, with a focus on their performance characteristics.
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Provides a collection of practical tips and techniques for writing more effective Python code. Many of the tips can be applied to improve Python performance.
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Practical reference guide to solving common Python programming problems, including problems related to performance optimization. It provides concise and efficient solutions to a wide range of Python-related tasks.
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Provides a comprehensive overview of Python programming, from basic concepts to advanced topics such as data structures, algorithms, and object-oriented programming. It good general reference for Python programmers of all levels.
Provides a comprehensive overview of Python programming, from basic concepts to advanced topics such as data structures, algorithms, and object-oriented programming. It good general reference for Python programmers of all levels.
Save
Elucidates Pythonic idioms, design patterns, and best practices, providing a solid foundation for writing high-quality and efficient Python code. While not solely dedicated to performance optimization, its emphasis on code quality and maintainability indirectly contributes to improved performance.
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Provides a solid foundation in algorithms and data structures, which are fundamental to performance optimization. By understanding how algorithms and data structures affect code performance, developers can make informed decisions and write more efficient code.
Although primarily intended for beginners learning the Python language, this book covers essential programming concepts and introduces basic performance considerations. It can serve as a useful preparatory resource for those new to Python programming and performance optimization.
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Provides a beginner-friendly introduction to computer science and programming using Python. It covers basic concepts, data structures, algorithms, and object-oriented programming, which are important prerequisites for understanding Python performance optimization.
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Serves as a comprehensive reference for Python, covering essential language features, syntax, and standard library modules. While not explicitly focused on performance optimization, it provides a solid foundation for understanding Python's core concepts and their implications on code performance.
Save
Provides a beginner-friendly introduction to Python programming. It covers basic concepts, data structures, algorithms, and object-oriented programming, which are important prerequisites for understanding Python performance optimization.
Save
Covers advanced Python programming concepts and idioms, many of which can be used to improve code performance. It provides deep insights into the Python language and its underlying implementation.
Save
Offers a comprehensive introduction to Python 3. While not specifically tailored to performance optimization, it provides a thorough grounding in Python's fundamentals, which can benefit those new to the language or seeking to reinforce their understanding.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ee7q1d/python
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Time
178 hours
Level
Advanced
Via
Pluralsight
Instructor
Dan Tofan
Language
English
Good to know
Explores concrete approaches to enhance the performance of your Python applications, a vital skill for developers
Led by Dan Tofan, a recognized expert in Python performance optimization
Covers crucial topics, including performance measurement, data structure optimization, and concurrency techniques
Provides hands-on practice with real-world examples, enhancing your understanding and practical implementation abilities
May require prior experience in Python programming for optimal comprehension
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