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In this episode of the Python Show Podcast, David Mertz is our guest. David is a prolific writer about the Python programming language. From his extremely popular IPM Developerworks articles to his multiple books on the Python language, David has been a part of the Python community for decades.

We ended up chatting about:

• The history of Python

• Book writing

• Conference speaking

• The PSF

• and more!

Show Links

• David Mertz’s website

• PyDev of the Week: David Mertz on Mouse vs Python

• David Mertz on InformIT / Pearson

Python threading allows you to run parts of your code concurrently, making the code more efficient. However, when you introduce threading to your code without knowing about thread safety, you may run into issues such as race conditions. You solve these with tools like locks, semaphores, events, conditions, and barriers.

By the end of this tutorial, you’ll be able to identify safety issues and prevent them by using the synchronization primitives in Python’s threading module to make your code thread-safe.

In this tutorial, you’ll learn:

• What thread safety is
• What race conditions are and how to avoid them
• How to identify thread safety issues in your code
• What different synchronization primitives exist in the threading module
• How to use synchronization primitives to make your code thread-safe

To get the most out of this tutorial, you’ll need to have basic experience working with multithreaded code using Python’s threading module and ThreadPoolExecutor.

Get Your Code: Click here to download the free sample code that you’ll use to learn about thread safety techniques in Python.

Take the Quiz: Test your knowledge with our interactive “Python Thread Safety: Using a Lock and Other Techniques” quiz. You’ll receive a score upon completion to help you track your learning progress:

Interactive Quiz

Python Thread Safety: Using a Lock and Other Techniques

In this quiz, you'll test your understanding of Python thread safety. You'll revisit the concepts of race conditions, locks, and other synchronization primitives in the threading module. By working through this quiz, you'll reinforce your knowledge about how to make your Python code thread-safe.

Threading in Python

In this section, you’ll get a general overview of how Python handles threading. Before discussing threading in Python, it’s important to revisit two related terms that you may have heard about in this context:

• Concurrency: The ability of a system to handle multiple tasks by allowing their execution to overlap in time but not necessarily happen simultaneously.
• Parallelism: The simultaneous execution of multiple tasks that run at the same time to leverage multiple processing units, typically multiple CPU cores.

Python’s threading is a concurrency framework that allows you to spin up multiple threads that run concurrently, each executing pieces of code. This improves the efficiency and responsiveness of your application. When running multiple threads, the Python interpreter switches between them, handing the control of execution over to each thread.

By running the script below, you can observe the creation of four threads:

Python threading_example.py import threading import time from concurrent.futures import ThreadPoolExecutor def threaded_function(): for number in range(3): print(f"Printing from {threading.current_thread().name}. {number=}") time.sleep(0.1) with ThreadPoolExecutor(max_workers=4, thread_name_prefix="Worker") as executor: for _ in range(4): executor.submit(threaded_function) Copied!

In this example, threaded_function prints the values zero to two that your for loop assigns to the loop variable number. Using a ThreadPoolExecutor, four threads are created to execute the threaded function. ThreadPoolExecutor is configured to run a maximum of four threads concurrently with max_workers=4, and each worker thread is named with a “Worker” prefix, as in thread_name_prefix="Worker".

In print(), the .name attribute on threading.current_thread() is used to get the name of the current thread. This will help you identify which thread is executed each time. A call to sleep() is added inside the threaded function to increase the likelihood of a context switch.

You’ll learn what a context switch is in just a moment. First, run the script and take a look at the output:

Shell $ python threading_example.py Printing from Worker_0. number=0 Printing from Worker_1. number=0 Printing from Worker_2. number=0 Printing from Worker_3. number=0 Printing from Worker_0. number=1 Printing from Worker_2. number=1 Printing from Worker_1. number=1 Printing from Worker_3. number=1 Printing from Worker_0. number=2 Printing from Worker_2. number=2 Printing from Worker_1. number=2 Printing from Worker_3. number=2 Copied!

Each line in the output represents a print() call from a worker thread, identified by Worker_0, Worker_1, Worker_2, and Worker_3. The number that follows the worker thread name shows the current iteration of the loop each thread is executing. Each thread takes turns executing the threaded_function, and the execution happens in a concurrent rather than sequential manner.

For example, after Worker_0 prints number=0, it’s not immediately followed by Worker_0 printing number=1. Instead, you see outputs from Worker_1, Worker_2, and Worker_3 printing number=0 before Worker_0 proceeds to number=1. You’ll notice from these interleaved outputs that multiple threads are running at the same time, taking turns to execute their part of the code.

This happens because the Python interpreter performs a context switch. This means that Python pauses the execution state of the current thread and passes control to another thread. When the context switches, Python saves the current execution state so that it can resume later. By switching the control of execution at specific intervals, multiple threads can execute code concurrently.

You can check the context switch interval of your Python interpreter by typing the following in the REPL:

Python >>> import sys >>> sys.getswitchinterval() 0.005 Copied!

The output of calling the getswitchinterval() is a number in seconds that represents the context switch interval of your Python interpreter. In this case, it’s 0.005 seconds or five milliseconds. You can think of the switch interval as how often the Python interpreter checks if it should switch to another thread.

An interval of five milliseconds doesn’t mean that threads switch exactly every five milliseconds, but rather that the interpreter considers switching to another thread at these intervals.

The switch interval is defined in the Python docs as follows:

Read the full article at https://realpython.com/python-thread-lock/ »

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Компьютеры и сети содействуют нам в борьбе за свободу: они помогают посвятить время и силы важным общественным инициативам, организовывать протесты, защищаться от цензуры.

Но свободны ли наши компьютеры?  И свободны ли мы как пользователи?

Обсудим эти вопросы в Открытом пространстве с Глебом Ерофеевым — активистом движения за свободные программы и волонтёром проекта "ГНУ", который в 1983 году запустил философ и активист Ричард Столлман.

Команда проекта "ГНУ" занимается разработкой свободного софта и техноэтическим активизмом, чтобы дать пользователям контроль над их компьютерами и искоренить несправедливость, которую приносят в общество собственнические программы.

Адрес: Плетешковский пер., 8с1 (м. "Бауманская").

Участие бесплатно.  Приветствуются пожертвования в пользу пространства.

The navigation menu is a crucial element of any website, guiding users through content, enhancing their experience, and playing a vital role in the site's overall usability and success.

Creating a menu that's accessible, responsive, and easy to navigate is a non-trivial task, no matter how simple or complex your navigation is. However, people usually underestimate the efforts required to create a navigation menu that provides a good user experience, and that it can take several iterations to do it right.

In this quiz, you’ll test your understanding of Python Class Constructors.

By working through this quiz, you’ll revisit the internal instantiation process, object initialization using .__init__(), and fine-tuning object creation by overriding .__new__().

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

Web accessibility is crucial for ensuring people of all abilities can engage with digital content without barriers. With the European Accessibility Act approaching, both the public and private sector must comply with its requirements. Learn how!

Drupal needs no introduction! It is a robust content management system (CMS) widely used for developing powerful, scalable, and secure websites. However, like any web platform, optimizing for speed and security is essential to ensure smooth performance, protect data, and improve user experience.Drupal 11 is all about enhanced scalability and security, which makes this version more dynamic and…

The companies are using the newest technologies to improve their e-commerce websites customer service and outreach. With e-commerce websites, you can offer better features to the audience that enhance the overall experience of the visitors on the website. 

And what better CMS of choice than Drupal for your large-scale websites? Drupal offers fresh features for e-commerce businesses that help their customers to have a better experience shopping online. On top of that, there is also a Drupal e-commerce module that allows you to help you engage more with the audience that visits the websites and converts them. 

In this blog, you will learn more about why you should use Drupal For your e-commerce websites and how it can be the best decision for your business. 

Russell wrote a great comment on my last post (thanks!):

What benefits do these things offer when a general purpose computer can do so many things nowadays? Is there a USB keyboard that you can connect to a laptop or phone to do these things? I presume that all recent phones have the compute power to do all the synthesis you need if you have the right software. Is it just a lack of software and infrastructure for doing it on laptops/phones that makes synthesisers still viable?

I've decided to turn my response into a post of its own.

The issue is definitely not compute power. You can indeed attach a USB keyboard to a computer and use a plethora of software synthesisers, including very faithful emulations of all the popular classics. The raw compute power of modern hardware synths is comparatively small: I’ve been told the modern Korg digital synths are on a par with a raspberry pi. I’ve seen some DSPs which are 32 bit ARMs, and other tools which are roughly equivalent to arduinos.

I can think of four reasons hardware synths remain popular with some despite the above:

1. As I touched on in my original synth post, computing dominates my life outside of music already. I really wanted something separate from that to keep mental distance from work.

2. Synths have hard real-time requirements. They don't have raw power in compute terms, but they absolutely have to do their job within microseconds of being instructed to, with no exceptions. Linux still has a long way to go for hard real-time.

3. The Linux audio ecosystem is… complex. Dealing with pipewire, pulseaudio, jack, alsa, oss, and anything else I've forgotten, as well as their failure modes, is too time consuming.

4. The last point is to do with creativity and inspiration. A good synth is more than the sum of its parts: it's an instrument, carefully designed and its components integrated by musically-minded people who have set out to create something to inspire. There are plenty of synths which aren't good instruments, but have loads of features: they’re boxes of "stuff". Good synths can't do it all: they often have limitations which you have to respond to, work around or with, creatively. This was expressed better than I could by Trent Reznor in the video archetype of a synthesiser:

In recent years, a lot has been happening to improve performance, maintainability and tooling of QML. Some of those improvements can only take full effect when your code follows modern best practices. Here are 10 things you can do in order to modernize your QML code and take full advantage of QML’s capabilities.

1. Use qt_add_qml_module CMake API

Qt6 introduced a new CMake API to create QML modules. Not only is this more convenient than what previously had to be done manually, but it is also a prerequisite for being able to exploit most of the following tips.

By using the qt_add_qml_module, your QML code is automatically processed by qmlcachegen, which not only creates QML byte code ahead of time, but also converts parts of your QML code to C++ code, improving performance. How much of your code can be compiled to C++ depends on the quality of the input code. The following tips are all about improving your code in that regard.

add_executable(myapp main.cpp) qt_add_qml_module(myapp URI "org.kde.myapp" QML_FILES Main.qml ) 2. Use declarative type registration

When creating custom types in C++ and registering them with qmlRegisterType and friends, they are not visible to the tooling at the compile time. qmlcachegen doesn’t know which types exist and which properties they have. Hence, it cannot translate to C++ the code that’s using them. Your experience with the QML Language Server will also suffer since it cannot autocomplete types and property names.

To fix this, your types should be registered declaratively using the QML_ELEMENT (and its friends, QML_NAMED_ELEMENT, QML_SINGLETON, etc) macros.

qmlRegisterType("org.kde.myapp", 1, 0, "MyThing");

becomes

class MyThing : public QObject { Q_OBJECT QML_ELEMENT };

The URL and version information are inferred from the qt_add_qml_module call.

3. Declare module dependencies

Sometimes your QML module depends on other modules. This can be due to importing it in the QML code, or more subtly by using types from another module in your QML-exposed C++ code. In the latter case, the dependency needs to be declared in the qt_add_qml_module call.

For example, exposing a QAbstractItemModel subclass to QML adds a dependency to the QtCore (that’s where QAbstractItemModel is registered) to your module. This does not only happen when subclassing a type but also when using it as a parameter type in properties or invokables.

Another example is creating a custom QQuickItem-derived type in C++, which adds a dependency on the Qt Quick module.

To fix this, add the DEPENDENCIES declaration to qt_add_qml_module:

qt_add_qml_module(myapp URI "org.kde.myapp" QML_FILES Main.qml DEPENDENCIES QtCore ) 4. Qualify property types fully

MOC needs types in C++ property definitions to be fully qualified, i.e. include the full namespace, even when inside that namespace. Not doing this will cause issues for the QML tooling.

namespace MyApp { class MyHelper : public QObject { Q_OBJECT }; class MyThing : public QObject { Q_OBJECT QML_ELEMENT Q_PROPERTY(MyHelper *helper READ helper CONSTANT) // bad Q_PROPERTY(MyApp::MyHelper *helper READ helper CONSTANT) // good ... }; } 5. Use types

In order for qmlcachegen to generate efficient code for your bindings, it needs to know the type for properties. Avoid using ‘property var’ wherever possible and use concrete types. This may be built-in types like int, double, or string, or any declaratively-defined custom type. Sometimes you want to be able to use a type as a property type in QML but don’t want the type to be creatable from QML directly. For this, you can register them using the QML_UNCREATABLE macro.

property var size: 10 // bad property int size: 10 // good property var thing // bad property MyThing thing // good 6. Avoid parent and other generic properties

qmlcachegen can only work with the property types it knows at compile time. It cannot make any assumptions about which concrete subtype a property will hold at runtime. This means that, if a property is defined with type Item, it can only compile bindings using properties defined on Item, not any of its subtypes. This is particularly relevant for properties like ‘parent’ or ‘contentItem’. For this reason, avoid using properties like these to look up items when not using properties defined on Item (properties like width, height, or visible are okay) and use look-ups via IDs instead.

Item { id: thing property int size: 10 Rectangle { width: parent.size // bad, Item has no 'size' property height: thing.height // good, lookup via id color: parent.enabled ? "red" : "black" // good, Item has 'enabled' property } } 7. Annotate function parameters with types

In order for qmlcachegen to compile JavaScript functions, it needs to know the function’s parameter and return type. For that, you need to add type annotations to the function:

function calculateArea(width: double, height: double) : double { return width * height }

When using signal handlers with parameters, you should explicitly specify the signal parameters by supplying a JS function or an arrow expression:

MouseArea { onClicked: event => console.log("clicked at", event.x, event.y) }

Not only does this make qmlcachegen happy, it also makes your code far more readable.

8. Use qualified property lookup

QML allows you to access properties from objects several times up in the parent hierarchy without explicitly specifying which object is being referenced. This is called an unqualified property look-up and generally considered bad practice since it leads to brittle and hard to reason about code. qmlcachegen also cannot properly reason about such code. So, it cannot properly compile it. You should only use qualified property lookups

Item { id: root property int size: 10 Rectangle { width: size // bad, unqualified lookup height: root.size // good, qualified lookup } }

Another area that needs attention is accessing model roles in a delegate. Views like ListView inject their model data as properties into the context of the delegate where they can be accessed with expressions like ‘foo’, ‘model.foo’, or ‘modelData.foo’. This way, qmlcachegen has no information about the types of the roles and cannot do its job properly. To fix this, you should use required properties to fetch the model data:

ListView { model: MyModel delegate: ItemDelegate { text: name // bad, lookup from context icon.name: model.iconName // more readable, but still bad required property bool active // good, using required property checked: active } } 9. Use pragma ComponentBehavior: Bound

When defining components, either explicitly via Component {} or implicitly when using delegates, it is common to want to refer to IDs outside of that component, and this generally works. However, theoretically any component can be used outside of the context it is defined in and, when doing that, IDs might refer to another object entirely. For this reason, qmlcachegen cannot properly compile such code.

To address this, we need to learn about pragma ComponentBehavior. Pragmas are file-wide switches that influence the behavior of QML. By specifying pragma ComponentBehavior: Bound at the top of the QML file, we can bind any components defined in this file to their surroundings. As a result, we cannot use the component in another place anymore but can now safely access IDs outside of it.

pragma ComponentBehavior: Bound import QtQuick Item { id: root property int delegateHeight: 10 ListView { model: MyModel delegate: Rectangle { height: root.delegateHeight // good with ComponentBehavior: Bound, bad otherwise } } }

A side effect of this is that accessing model data now must happen using required properties, as described in the previous point. Learn more about ComponentBehavior here.

10. Know your tools

A lot of these pitfalls are not obvious, even to seasoned QML programmers, especially when working with existing codebases. Fortunately, qmllint helps you find most of these issues and avoids introducing them. By using the QML Language Server, you can incorporate qmllint directly into your preferred IDE/editor such as Kate or Visual Studio Code.

While qmlcachegen can help boost your QML application’s performance, there are performance problems it cannot help with, such as scenes that are too complex, slow C++ code, or inefficient rendering. To investigate such problems, tools like the QML profiler, Hotspot for CPU profiling, Heaptrack for memory profiling, and GammaRay for analyzing QML scenes are very helpful.

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The post 10 Tips to Make Your QML Code Faster and More Maintainable appeared first on KDAB.

In the last weeks qmpbackup has seen a bit more improvements.

• Adds support for CEPH/RBD backed devices.
• Allows to use unique bitmaps for having multiple, separate backup chains.
• Adds support for jsonified filename configurations like often used on proxmox systems.
• Adds support for saving attached pflash/nvram devices (storing UEFI related settings)
• qmprestore can now merge the backup chain into a new image file and the new snapshotrebase command can rebase the images and after committing, creates an internal qcow snapshot, so one can easily switch between different vm states in the backup.

Ive been running it lately to backup Virtual machines on proxmox systems, where the proxmox backup server is not an option.

BOSTON (October 22, 2024) -- The Free Software Foundation (FSF) has announced today that it is working on a statement of criteria for free machine learning applications, which will require the software, as well as the raw training data and associated scripts, to grant users the four freedoms.

#652 – OCTOBER 22, 2024
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Structural Pattern Matching in Python

In this tutorial, you’ll learn how to harness the power of structural pattern matching in Python. You’ll explore the new syntax, delve into various pattern types, and find appropriate applications for pattern matching, all while identifying common pitfalls.
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Combinatoric Iterators From itertools

The itertools module offers four combinatoric iterators that generate different combined outputs from one or more iterable. This post covers all of them: product, permutations, combinations, and combinations_with_replacement.
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Scrape Web Data at Scale with a 98.7% Success Rate

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CPython Internals: Your Guide to the Python 3 Interpreter

Unlock the inner workings of the Python language, compile the Python interpreter from source code, and participate in the development of CPython. Guido van Rossum, the creator of Python, says: “I can recommend CPython Internals to anyone who wants to get going with hacking on CPython” →
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SSH Scripting With Fabric and Python

Reading and writing files is a basic task that most software applications need to do, but what if you need to do that on remote machines? This tutorial introduces you to Fabric and how to connect over SSH in Python.
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Python 3.14.0 Alpha 1 Released

CPYTHON DEV BLOG

Quiz: Structural Pattern Matching

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Quiz: Iterators and Iterables in Python

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Quiz: Python import: Advanced Techniques and Tips

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Articles & Tutorials Mind Your Image Metadata

Most devices record a variety of metadata when generating images. While some of that information may be innocuous, you could end up exposing the GPS coordinates to your home if you aren’t careful. In this article, Stefanie provides a brief introduction to image metadata, and then shows you how to remove it with exif-stripper.
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Open Source in Python and JavaScript 2024

Python vs. JavaScript: Which open-source community is leading the way? This analysis of 36,000 GitHub repositories explores the evolution of Python and JavaScript ecosystems, highlighting key trends and popular topics. Discover how open-source communities of Python and JavaScript have shaped the tech landscape.
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Accelerate Edge Devices with High-Performance AI Power

Experience the power of Edge AI—delivering lightning-fast, real-time processing where it matters. Optimize your applications to push performance and accuracy beyond limits with Intel’s OpenVINO toolkit.
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Using Type Hints for Multiple Return Types in Python

In this video course, you’ll learn how to define multiple return types using type hints in Python. This course covers working with single or multiple pieces of data, defining type aliases, and performing type checking using a third-party static type checker tool.
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Narwhals: Expanding DataFrame Compatibility

How does a Python tool support all types of DataFrames and their various features? Could a lightweight library be used to add compatibility for newer formats like Polars or PyArrow? This week on the show, we speak with Marco Gorelli about his project, Narwhals.
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Syntactic Sugar: Why Python Is Sweet and Pythonic

In this tutorial, you’ll learn what syntactic sugar is and how Python uses it to help you create more readable, descriptive, clean, and Pythonic code. You’ll also learn how to replace a given piece of syntactic sugar with another syntax construct.
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Entering Text in the Terminal Is Complicated

Julia asked some folks on Mastodon what they found confusing about working in a terminal. It turns out that entering text in the terminal is complicated. This post talks about why that is and how to understand it better.
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4 Lessons From Small Teams That Ship Fast

Software engineering provides a lot of leverage and small teams can do a large amount of work. This post talks about several common examples in the industry where a small group created a big product.
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Perks of Being a Python Core Developer

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How to Use Lambda Functions in Python

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Projects & Code ryp: R Inside Python

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pyglove: Symbolic OO for Python

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pipreqs: Generate requirements.txt Based on Imports

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Bowler: Safe Code Refactoring for Modern Python

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nanodjango: Full Django in a Single File

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Events Weekly Real Python Office Hours Q&A (Virtual)

October 23, 2024
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October Oslo Python Meetup

October 24, 2024
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PyCon APAC 2024

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PyCon Korea 2024

October 25 to October 28, 2024
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October 27, 2024
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PyCon FR 2024

October 31 to November 3, 2024
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PyCon Zimbabwe

October 31 to November 3, 2024
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Happy Pythoning!
This was PyCoder’s Weekly Issue #652.
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The Python Global Interpreter Lock or GIL, in simple words, is a mutex (or a lock) that allows only one thread to hold the control of the Python interpreter.

This means that only one thread can be in a state of execution at any point in time. The impact of the GIL isn’t visible to developers who execute single-threaded programs, but it can be a performance bottleneck in CPU-bound and multi-threaded code.

Since the GIL allows only one thread to execute at a time even in a multi-threaded architecture with more than one CPU core, the GIL has gained a reputation as an “infamous” feature of Python.

In this video course you’ll learn how the GIL affects the performance of your Python programs, and how you can mitigate the impact it might have on your code.

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

In this quiz, you’ll test your understanding of how to define your own Python function.

You’ll revisit theoretical knowledge about passing values to functions, when to divide your program into separate user-defined functions, and all the tools you’ll need to define complex and powerful functions in Python.

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

With PHP attributes, your Drupal development process can be simplified, more performant, and easier to read. Learn the difference between PHP Attributes and Annotations and discover why attributes are the future of efficient coding.

Takeaway: With Drupal 7's end-of-life date set for January 5, 2025, public sector institutions face critical decisions about their web infrastructure. While migration to Drupal 10 offers clear advantages, organizations unable to migrate immediately need robust security measures to protect their sites.

PythonAnywhere has been around for over 10 years, and as our platform continues to grow with thousands of users, we’re committed to keeping it in top shape. Part of this involves upgrading some of the older parts of our infrastructure, with a special focus on our file storage servers—some of the oldest systems we have.

As we continue to evolve and adapt the Qt Framework to the needs of our users and upcoming regulation changes, we are excited to announce some significant changes to our Long-Term Support (LTS) policy from Qt 6.8 onwards. The changes are designed to provide a more robust and predictable support strategy, ensuring your projects remain secure and stable over their entire lifecycle. 

Today's exercice is just about turning a very nice example of the python soundevice module into something that works for me© to help me tune my bass.

Long story short, I suck at tuning my instrument and just lost my tuner...

This will require the python module soundevice and matplotlib.

So in order to tune my guitar I indeed need a spectrosonogram that displays the frequencies captured in real time by an audio device with an output readable enough I can actually know if I am nearing a legit frequency called a Note.

The frequencies for the notes are pretty arbitrary and I chose to only show the frequency for E, A , D, G, B since I have a 5 strings bass.
I chose the frequency between 100 and 2000 knowing that anyway any frequency below will trigger harmonics and above will trigger reasonance in the right frequency frame.

Plotting a spectrogram is done by tweaking the eponym matplotlib grapher with values chosen to fit my need and show me a laser thin beam around the right frequency. #!/usr/bin/env python3 """Show a text-mode spectrogram using live microphone data.""" import argparse import math import shutil import matplotlib.pyplot as plt from multiprocessing import Process, Queue import matplotlib.animation as animation import numpy as np import sounddevice as sd usage_line = ' press enter to quit,' def int_or_str(text): """Helper function for argument parsing.""" try: return int(text) except ValueError: return text try: columns, _ = shutil.get_terminal_size() except AttributeError: columns = 80 parser = argparse.ArgumentParser(add_help=False) parser.add_argument( '-l', '--list-devices', action='store_true', help='show list of audio devices and exit') args, remaining = parser.parse_known_args() if args.list_devices: print(sd.query_devices()) parser.exit(0) parser = argparse.ArgumentParser( description=__doc__ + '\n\nSupported keys:' + usage_line, formatter_class=argparse.RawDescriptionHelpFormatter, parents=[parser]) parser.add_argument( '-b', '--block-duration', type=float, metavar='DURATION', default=50, help='block size (default %(default)s milliseconds)') parser.add_argument( '-d', '--device', type=int_or_str, help='input device (numeric ID or substring)') parser.add_argument( '-g', '--gain', type=float, default=10, help='initial gain factor (default %(default)s)') parser.add_argument( '-r', '--range', type=float, nargs=2, metavar=('LOW', 'HIGH'), default=[50, 4000], help='frequency range (default %(default)s Hz)') args = parser.parse_args(remaining) low, high = args.range if high <= low: parser.error('HIGH must be greater than LOW') q = Queue() try: samplerate = sd.query_devices(args.device, 'input')['default_samplerate'] def plot(q): global samplerate fig, ( ax,axs) = plt.subplots(nrows=2) plt.ioff() def animate(i,q): data = q.get() ax.clear() axs.clear() axs.plot(data) ax.set_yticks([ 41.20, 82.41, 164.8, 329.6, 659.3, # E 55.00, 110.0, 220.0, 440.0, 880.0, # A 73.42, 146.8, 293.7, 587.3, # D 49.00, 98.00, 196.0, 392.0, 784.0, #G 61.74, 123.5, 246.9, 493.9, 987.8 ])#B ax.specgram(data[:,-1],mode="magnitude", Fs=samplerate*2, scale="linear",NFFT=9002) ax.set_ylim(150,1000) ani = animation.FuncAnimation(fig, animate,fargs=(q,), interval=500) plt.show() plotrt = Process(target=plot, args=(q,)) plotrt.start() def callback(indata, frames, time, status): if any(indata): q.put(indata) else: print('no input') with sd.InputStream(device=args.device, channels=1, callback=callback, blocksize=int(samplerate * args.block_duration /50 ), samplerate=samplerate) as sound: while True: response = input() if response in ('', 'q', 'Q'): break for ch in response: if ch == '+': args.gain *= 2 elif ch == '-': args.gain /= 2 else: print('\x1b[31;40m', usage_line.center(args.columns, '#'), '\x1b[0m', sep='') break except KeyboardInterrupt: parser.exit('Interrupted by user') except Exception as e: parser.exit(type(e).__name__ + ': ' + str(e))