Codon: high-performance Python compiler

Codon is a high-performance Python implementation that compiles to native machine code without any runtime overhead. Typical speedups over vanilla Python are on the order of 10-100x or more, on a single thread. Codon’s performance is typically on par with (and sometimes better than) that of C/C++. Unlike Python, Codon supports native multithreading, which can lead to speedups many times higher still.

Think of Codon as Python reimagined for static, ahead-of-time compilation, built from the ground up with best possible performance in mind.

How to connect Python to WordPress – Call Me Fred

np_array's size=220.0MB
With SharedMemory: ...
Current memory usage 0.11283MB; Peak: 0.156706MB
Time elapsed: 0.99s
No SharedMemory: ...
Current memory usage 0.026587MB; Peak: 467.558995MB
Time elapsed: 5.48s

I think I shall go for shared memory! My Amiga formation years requires it!

Risky Implementations: If the pattern is not implemented carefully, there are huge chances that you will end up with large complexity code.

From https://www.geeksforgeeks.org/observer-method-python-design-patterns/

With all the complex code out there having “risky implementations” the observer pattern is one of the mildest.

# eg. f’{x=}’ returns ‘x=’

n = 5
print(f'{n+1=}')    # n+1=6

n = 5
print(f'{n+10=}')    # n+10=15

Textual is a TUI framework for Python, inspired by modern web development.

Textual is a Rapid Application Development framework for Python, built by Textualize.io.

Build sophisticated user interfaces with a simple Python API. Run your apps in the terminal or a web browser!

Well, I just wish I could have it in EIffel….

You can use “CSV” table storage in (at least) these database backends:

• SQLite: https://www.sqlite.org/csv.html 42
• MySQL/MariaDB via the “CSV” storage engine: https://dev.mysql.com/doc/refman/8.0/en/csv-storage-engine.html 15 . Or MariaDB via the CONNECT storage engine: https://mariadb.com/kb/en/connect/ 1

However these will be slow though. Changes to CSV based tables require a lot of parsing and re-saving.

It’s probably better to import the CSV into a table with an optimized storage engine, and export it again later. django-import-export can help with that: https://pypi.org/project/django-import-export/

Source: Using CSV File as data storage and access

In fact Anmol Tomar wrote on medium.com “9 Python Mistakes That Reveal You’re a Nooby! Move away from noob status!”. Too bad he want to be read only by people in medium walled garden. The fist is readable:

1. Neglecting Pythonic Idioms

Python has its own set of idioms and best practices that make your code more elegant and readable. A common mistake among newcomers is writing code in a non-Pythonic way.

For example, using excessive loops when list comprehensions or generator expressions could provide a more concise solution. Embrace Pythonic idioms to improve the readability and maintainability of your code.

Wrong

# Non-Pythonic way
squared_numbers = []
for i in range(1, 6):
    squared_numbers.append(i ** 2)

In this example, using a list comprehension provides a more concise and readable solution compared to the traditional loop and append approach.

Correct

# Pythonic way
squared_numbers = [i ** 2 for i in range(1, 6)]

Young Jedi, your pythoninc knowledge lacks historical viewpoint. The “non python way” was the only pythonic way back in the 1.5.x days.