PyPy VS Think Python

• Performance
  PyPy is known for its superior execution speed and performance, often outperforming the standard CPython interpreter for many workloads thanks to its Just-in-Time (JIT) compilation strategy.
• Compatibility
  PyPy aims to be compatible with standard Python, so many programs and libraries that run on CPython should work on PyPy without or with minimal changes.
• Memory Efficiency
  Due to its garbage collection mechanism, PyPy often results in lower memory usage as compared to CPython, which can be beneficial for memory-intensive applications.
• Concurrency
  PyPy provides better support for concurrency, including potentially avoiding some of the Global Interpreter Lock (GIL) performance issues present in CPython.

Possible disadvantages

• Compatibility Limitations
  Although PyPy aims to be compatible with Python, not all extensions and libraries available for CPython work flawlessly with PyPy, particularly those relying on C extensions.
• Startup Time
  PyPy has a slower startup time than CPython due to the JIT compilation overhead, which could be a downside for scripts primarily dealing with short-lived processes.
• Larger Memory Footprint
  While PyPy can be more memory efficient in the long term, the JIT compilation process can result in a larger initial memory footprint which could affect applications with limited memory resources.
• Platform Support
  PyPy might not support all platforms or the latest Python features immediately, potentially causing issues for users relying on cutting-edge Python developments or specific system architectures.

• Accessible for Beginners
  Think Python is written in a clear and approachable style, making it suitable for beginners with no prior programming experience. The author takes care to explain concepts thoroughly, making it easy to follow.
• Practical Examples
  The book is filled with practical examples that demonstrate how to use Python for various applications. This approach helps readers understand real-world usage of the language.
• Free Availability
  Think Python is openly accessible in digital format for free, making it easy for anyone to read without financial barriers, supporting open education.
• Emphasis on Problem Solving
  The book places strong emphasis on teaching readers how to think like programmers, encouraging problem-solving and logical thinking skills.

Possible disadvantages

• Limited Depth
  While suitable for beginners, the book doesn’t delve deeply into advanced features of Python, which might leave learners needing additional resources for more complex topics.
• Pacing
  Some readers might find the pacing of the book too slow, particularly if they have some prior programming experience, as it aims to accommodate complete beginners.
• Lack of Exercises
  There are fewer exercises compared to some other programming books, potentially providing less practice for readers to reinforce their learning.
• Outdated Information
  Depending on the edition, some information may be outdated due to the fast-evolving nature of programming languages. Readers may need to verify with more recent sources.

PyPy - the hero we all deserve. - Amit Ripshtos - PyCon Israel 2019

More videos

Thoughts on Think Python From a Beginner Programmer

More videos

• TurboPython – A Python-to-C++ Compiler

  It reminds me of PyPy (https://pypy.org/) It works as a pure Python runtime, but when comes with issues when integrating with existing libraries who have C/C++ extensions, which is a big one for modern use of Python (Numpy, pandas, you... - Source: Hacker News / 2 days ago

• CPython Internals Explained

  There are quite a few JITs: JIT-compiler for Python https://pypy.org/ Python enhancement proposal for JIT in CPython https://peps.python.org/pep-0744/ And there are several JIT-compilers for various subsets of Python, usually with focus... - Source: Hacker News / 8 months ago

• Pydrofoil: Accelerating Sail-based instruction set simulators

  Gains than using either compiler alone. This uses the PyPy JIT framework to speed up a RISC-V simulator. https://pypy.org/ https://github.com/pydrofoil/pydrofoil Pydrofoil: A fast... - Source: Hacker News / over 1 year ago

View more

• C949 help and Jay Wengrow's Guide to Data Structures

  This course actually starts with an introduction to Python. Since you don't have access yet, you can give Think Python a whirl - https://greenteapress.com/wp/think-python/ and for a more interactive experience, I really enjoyed this one... Source: over 3 years ago

• Best place to learn and practice python?

  Start with Think Python or learn x in y..both are free resources and good for basic understanding and practise. Source: over 3 years ago

• Good places to start learning python?

  This free book taught me Python many years ago https://greenteapress.com/wp/think-python/. Source: over 4 years ago

View more