Feeds

For the fifth year in a row, I've asked Société de Transport de Montréal, Montreal's transit agency, for the foot traffic data of Montreal's subway.

By clicking on a subway station, you'll be redirected to a graph of the station's foot traffic.

• Orange line (top10)
• Green line (top10)
• Blue line
• Yellow line
• Global Top 10

Licences

• The subway map displayed on this page, the original dataset and my modified dataset are licenced under CCO 1.0: they are in the public domain.

• The R code I wrote is licensed under the GPLv3+. It's pretty much the same code as last year. I tweaked last's year converter script and although I had to clean some of the data by hand, it worked pretty well.

GNU Parallel 20240122 ('Frederik X') has been released. It is available for download at: lbry://@GnuParallel:4

Quote of the month:

  GNU Parallel alone provides more value than moreutils
    -- Ferret7446@news.ycombinator.com
 
New in this release:

• --sshlogin supports ranges: server[01-12,15] 10.0.[1-10].[2-254]
• --plus enables {slot-1} and {seq-1} = {%}-1 and {#}-1 to count from 0.
• env_parallel.{sh,ash,dash,bash,ksh,zsh} are now the same script.
• Bug fixes and man page updates.

GNU Parallel - For people who live life in the parallel lane.

If you like GNU Parallel record a video testimonial: Say who you are, what you use GNU Parallel for, how it helps you, and what you like most about it. Include a command that uses GNU Parallel if you feel like it.

About GNU Parallel

GNU Parallel is a shell tool for executing jobs in parallel using one or more computers. A job can be a single command or a small script that has to be run for each of the lines in the input. The typical input is a list of files, a list of hosts, a list of users, a list of URLs, or a list of tables. A job can also be a command that reads from a pipe. GNU Parallel can then split the input and pipe it into commands in parallel.

If you use xargs and tee today you will find GNU Parallel very easy to use as GNU Parallel is written to have the same options as xargs. If you write loops in shell, you will find GNU Parallel may be able to replace most of the loops and make them run faster by running several jobs in parallel. GNU Parallel can even replace nested loops.

GNU Parallel makes sure output from the commands is the same output as you would get had you run the commands sequentially. This makes it possible to use output from GNU Parallel as input for other programs.

For example you can run this to convert all jpeg files into png and gif files and have a progress bar:

  parallel --bar convert {1} {1.}.{2} ::: *.jpg ::: png gif

Or you can generate big, medium, and small thumbnails of all jpeg files in sub dirs:

  find . -name '*.jpg' |
    parallel convert -geometry {2} {1} {1//}/thumb{2}_{1/} :::: - ::: 50 100 200

You can find more about GNU Parallel at: http://www.gnu.org/s/parallel/

You can install GNU Parallel in just 10 seconds with:

    $ (wget -O - pi.dk/3 || lynx -source pi.dk/3 || curl pi.dk/3/ || \
       fetch -o - http://pi.dk/3 ) > install.sh
    $ sha1sum install.sh | grep 883c667e01eed62f975ad28b6d50e22a
    12345678 883c667e 01eed62f 975ad28b 6d50e22a
    $ md5sum install.sh | grep cc21b4c943fd03e93ae1ae49e28573c0
    cc21b4c9 43fd03e9 3ae1ae49 e28573c0
    $ sha512sum install.sh | grep ec113b49a54e705f86d51e784ebced224fdff3f52
    79945d9d 250b42a4 2067bb00 99da012e c113b49a 54e705f8 6d51e784 ebced224
    fdff3f52 ca588d64 e75f6033 61bd543f d631f592 2f87ceb2 ab034149 6df84a35
    $ bash install.sh

Watch the intro video on http://www.youtube.com/playlist?list=PL284C9FF2488BC6D1

Walk through the tutorial (man parallel_tutorial). Your command line will love you for it.

When using programs that use GNU Parallel to process data for publication please cite:

O. Tange (2018): GNU Parallel 2018, March 2018, https://doi.org/10.5281/zenodo.1146014.

If you like GNU Parallel:

• Give a demo at your local user group/team/colleagues
• Post the intro videos on Reddit/Diaspora*/forums/blogs/ Identi.ca/Google+/Twitter/Facebook/Linkedin/mailing lists
• Get the merchandise https://gnuparallel.threadless.com/designs/gnu-parallel
• Request or write a review for your favourite blog or magazine
• Request or build a package for your favourite distribution (if it is not already there)
• Invite me for your next conference

If you use programs that use GNU Parallel for research:

• Please cite GNU Parallel in you publications (use --citation)

If GNU Parallel saves you money:

• (Have your company) donate to FSF https://my.fsf.org/donate/

About GNU SQL

GNU sql aims to give a simple, unified interface for accessing databases through all the different databases' command line clients. So far the focus has been on giving a common way to specify login information (protocol, username, password, hostname, and port number), size (database and table size), and running queries.

The database is addressed using a DBURL. If commands are left out you will get that database's interactive shell.

When using GNU SQL for a publication please cite:

O. Tange (2011): GNU SQL - A Command Line Tool for Accessing Different Databases Using DBURLs, ;login: The USENIX Magazine, April 2011:29-32.

About GNU Niceload

GNU niceload slows down a program when the computer load average (or other system activity) is above a certain limit. When the limit is reached the program will be suspended for some time. If the limit is a soft limit the program will be allowed to run for short amounts of time before being suspended again. If the limit is a hard limit the program will only be allowed to run when the system is below the limit.

This Wing Tip introduces Wing Pro's AI assisted software development capabilities. Starting with Wing Pro version 10, you can use generative AI to write new code at the current editor insertion point, or you can use the AI tool to refactor, redesign, or extend existing code.

Generative AI is astonishingly capable as a programmer's assistant. As long as you provide it with sufficient context and clear instructions, it can cleanly and correctly execute a wide variety of programming tasks.

AI Code Suggestion

Here is an example where Wing Pro's AI code suggestion capability is used to write a missing method for an existing class. The AI knows what to add because it can see what precedes and follows the insertion point in the editor. It infers from that context what code you would like it to produce:

Shown above: Typing 'def get_full_name' followed by Ctrl-? to initiate AI suggestion mode. The suggested code is accepted by pressing Enter.

AI Refactoring

AI refactoring is even more powerful. You can request changes to existing code according to written instructions. For example, you might ask it to "convert this threaded implementation to run asynchronously instead":

Shown above: Running the highlighted request in the AI tool to convert multithreaded code to run asynchronously instead.

Description-Driven Development

Wing Pro's AI refactoring tool can also be used to write new code at the current insertion point, according to written instructions. For example, you might ask it to "add client and server classes that expose all the public methods of FileManager to a client process using sockets and JSON":

Shown above: Using the AI tool to request implementation of client/server classes for remote access to an existing class.

Simpler and perhaps more common requests like "write documentation strings for these methods" and "create unit tests for class Person" of course also work. In general, Wing Pro's AI assistant can do any reasonably sized chunk of work for which you can clearly state instructions.

Used correctly, this capability will have a significant impact on your productivity as a programmer. Instead of typing out code manually, your role changes to one of directing an intelligent assistant capable of completing a wide range of programming tasks very quickly. You will still need to review and accept or reject the AI's work. Generative AI can't replace you, but it allows you to concentrate much more on higher-level design and much less on implementation details.

Getting Started

Wing Pro uses OpenAI as its AI provider, and you will need to create and pay for your own OpenAI account before you can use this feature. You may need to pay up to US $50 up front to be given computational rate limits that are high enough to use AI for your software development. However, individual requests often cost less than a US$ 0.01. More complex tasks may cost up to 30 cents, if you provide a lot of context with them. This is still far less than the paid programmer time the AI is replacing.

To use AI assisted development effectively, and you will need to learn how to create well-designed requests that provide the AI both with the necessary relevant context and clear and specific instructions. Please read all of the AI Assisted Development documentation for details on setup, framing requests, and monitoring costs. It takes a bit of time to get started, but it is well worth the effort incorporate generative AI into your tool chain.

That's it for now! We'll be back soon with more Wing Tips for Wing Python IDE.

As always, please don't hesitate to email support@wingware.com if you run into problems or have any questions.

A very minor maintenance release, now at version 0.0.22, of RcppAnnoy has arrived on CRAN.

RcppAnnoy is the Rcpp-based R integration of the nifty Annoy library by Erik Bernhardsson. Annoy is a small and lightweight C++ template header library for very fast approximate nearest neighbours—originally developed to drive the Spotify music discovery algorithm. It had all the buzzwords already a decade ago: it is one of the algorithms behind (drum roll …) vector search as it finds approximate matches very quickly and also allows to persist the data.

This release responds to a CRAN request to clean up empty macros and sections in Rd files.

Details of the release follow based on the NEWS file.

Changes in version 0.0.22 (2024-01-23)

• Replace empty examples macro to satisfy CRAN request.

Courtesy of my CRANberries, there is also a diffstat report for this release.

If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

You are probably interested in setting up a workign environment for Drupal-based projects or maybe you have new members in your development team, so the configuration of the correct development environment is a fundamental part of the process of working with Drupal, you are right. By reading this how-to guide, you will implement a complete and ready-to-go Drupal working environment ready for versions 8, 9, and 10 of our favorite CMS/framework. Do you want to start?…

Picture from Unsplash, user Mathyas Kurmann, @mathyaskurmann.

This content has been constructed as a …

Releases on the Python Package Index are never “done” About • Blog • Newsletter • Links Releases on the Python Package Index are never “done”

Published 2024-01-24 by Seth Larson
Reading time: minutes

This critical role would not be possible without funding from the OpenSSF Alpha-Omega project. Massive thank-you to Alpha-Omega for investing in the security of the Python ecosystem! PEP 740 and open-ended PyPI releases

PEP 740 is a proposal to add support for digital attestations to PyPI artifacts, for example publish provenance attestations, which can be verified and used by tooling.

William Woodruff has been working on PEP 740 which is in draft on GitHub, William addressed my feedback this week. During this work the open-endedness of PyPI releases came up during our discussion, specifically how it is a common gotcha for folks designing tools and policy for multiple software ecosystems difficult.

What does it mean for PyPI releases to be open-ended? It means that you can always upload new files to an existing release on PyPI even if the release has been created for years. This is because a PyPI “release” is only a thin layer aggregating a bunch of files on PyPI that happen to share the same version.

This discussion between us was opened up as a wider discussion on discuss.python.org about this property. Summarizing this discussion:

• New Python releases mean new wheels need to be built for non-ABI3 compatible projects. IMO this is the most compelling reason to keep this property.
• Draft releases seem semi-related, being able to put artifacts into a "queue" before making them public.
• Ordering of which wheel gets evaluated as an installation candidate isn't defined well. Up to installers, tends to be more specific -> less specific.
• PyPI doesn't allow single files to be yanked even though PEP 592 allows for yanking at the file level instead of only the release level.
• The "attack" vector is fairly small, this property would mostly only provide additional secrecy for attackers by blending into existing releases.

CPython Software Bill-of-Materials update

CPython 3.13.0a3 was released, this is the very first CPython release that contains any SBOM metadata at all, and thus we can create an initial draft SBOM document.

Much of the work on CPython's SBOMs was done to fix issues related to pip's vendored dependencies and issues found by downstream distributors of CPython builds like Red Hat. The issues were as follows:

• Don't require internet access to run the SBOM script. We use internet access to automatically generate metadata for pip, but if the internet isn't available we should continue using the metadata that we already have (assuming the file hasn't changed) and then rely on CI which should always have internet access (the script fails in CI) to verify the values.
• If pip wheel is removed, don't raise an unskippable error. Redistributors will typically remove the wheel in favor of their own distribution of pip for ensurepip.
• Enumerate pip's vendored dependencies in the SBOM. This requires parsing the vendor.txt script inside of pip's vendor directory.

All of these issues are mostly related and touch the same place in the codebase, so resulted in a medium-sized pull request to fix all the issues together.

On the release side, I've addressed feedback from the first round of reviews for generating SBOMs for source code artifacts and uploading them during the release. Once those SBOMs start being generated they'll automatically begin being added to python.org/downloads.

Other items

• Two new Developer-in-Residence roles have been filled at the Python Software Foundation. Welcome, Petr Viktorin as the Deputy Developer-in-Residence and Serhiy Storchaka as the Supporting Developer-in-Residence. We've already gotten a chance to collaborate and I look forward to even more.
• scikit-learn is considering build reproducibility.
• Wrote my piece for the Python Software Foundation Annual Impact report.
• Submitted to the OpenSSF SOSS Community Day Call for Proposals (see you in Washington!)
• Reviewed a fix by Erlend Aasland for the SBOM generation script.
• I published a blog post which provides guidance on how to remove a maintainer from an open source project to reduce the attack surface of an open source project.

That's all for this week! 👋 If you're interested in more you can read last week's report.

Thanks for reading! ♡ Did you find this article helpful and want more content like it? Get notified of new posts by subscribing to the RSS feed or the email newsletter.

This work is licensed under CC BY-SA 4.0

This is the third part of a post series under the tag package_config that explains the Nuitka package configuration in more detail. To recap, Nuitka package configuration is the way Nuitka learns about hidden dependencies, needed DLLs, data files, and just generally avoids bloat in the compilation. The details are here on a dedicate page on the web site in Nuitka Package Configuration but reading on will be just fine.

Problem Package

Each post will feature one package that caused a particular problem. In this case, we are talking about the package toga.

Problems like with this package are typically encountered in standalone mode only, but they also affect accelerated mode, since it doesn’t compile all the things desired in that case. Some packages, and in this instance look at what OS they are running on, environment variables, etc. and then in a relatively static fashion, but one that Nuitka cannot see through, loads a what it calls “backend” module.

We are going to look at that in some detail, and will see a workaround applied with the anti-bloat engine doing code modification on the fly that make the choice determined at compile time, and visible to Nuitka is this way.

Initial Symptom

The initial symptom reported was that toga did suffer from broken version lookups and therefor did not work, and we encountered even two things, that prevented it, one was about the version number. It was trying to do int after resolving the version of toga by itself to None.

Traceback (most recent call last): File "C:\py\dist\toga1.py", line 1, in <module> File "<frozen importlib._bootstrap>", line 1176, in _find_and_load File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 690, in _load_unlocked File "C:\py\dist\toga\__init__.py", line 1, in <module toga> File "<frozen importlib._bootstrap>", line 1176, in _find_and_load File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 690, in _load_unlocked File "C:\py\dist\toga\app.py", line 20, in <module toga.app> File "<frozen importlib._bootstrap>", line 1176, in _find_and_load File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 690, in _load_unlocked File "C:\py\dist\toga\widgets\base.py", line 7, in <module toga.widgets.base> File "<frozen importlib._bootstrap>", line 1176, in _find_and_load File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 690, in _load_unlocked File "C:\py\dist\travertino\__init__.py", line 4, in <module travertino> File "<frozen importlib._bootstrap>", line 1176, in _find_and_load File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 690, in _load_unlocked File "C:\py\dist\setuptools_scm\__init__.py", line 7, in <module setuptools_scm> File "<frozen importlib._bootstrap>", line 1176, in _find_and_load File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 690, in _load_unlocked File "C:\py\dist\setuptools_scm\_config.py", line 15, in <module setuptools_scm._config> File "<frozen importlib._bootstrap>", line 1176, in _find_and_load File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 690, in _load_unlocked File "C:\py\dist\setuptools_scm\_integration\pyproject_reading.py", line 8, in <module setuptools_scm._integration.pyproject_reading> File "<frozen importlib._bootstrap>", line 1176, in _find_and_load File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 690, in _load_unlocked File "C:\py\dist\setuptools_scm\_integration\setuptools.py", line 62, in <module setuptools_scm._integration.setuptools> File "C:\py\dist\setuptools_scm\_integration\setuptools.py", line 29, in _warn_on_old_setuptools ValueError: invalid literal for int() with base 10: 'unknown'

So, this is clearly something that we consider bloat in the first place, to runtime lookup your own version number. The use of setuptools_scm is implying the use of setuptools, for which the version cannot be determined, and that’s crashing.

Step 1 - Analysis of initial crashing

So first thing, we did was to repair setuptools, to know its version. It is doing it a bit different, because it cannot use itself. Our compile time optimization failed there, but also would be overkill. We never came across this, since we avoid setuptools very hard normally, but it’s not good to be incompatible.

- module-name: 'setuptools.version' anti-bloat: - description: 'workaround for metadata version of setuptools' replacements: "pkg_resources.get_distribution('setuptools').version": "repr(__import__('setuptools.version').version.__version__)"

We do not have to include all metadata for setuptools here, just to get that one item, so we chose to make a simple string replacement here, that just looks the value up at compile time and puts it into the source code automatically. That removes the pkg_resources.get_distribution() call entirely.

With that, setuptools_scm was not crashing anymore. That’s good. But we don’t really want it to be included, since it’s good for dynamically detecting the version from git, and what not, but including the framework for building C extensions, not a good idea in the general case. Nuitka therefore said this:

Nuitka-Plugins:WARNING: anti-bloat: Undesirable import of 'setuptools_scm' (intending to Nuitka-Plugins:WARNING: avoid 'setuptools') in 'toga' (at Nuitka-Plugins:WARNING: 'c:\3\Lib\site-packages\toga\__init__.py:99') encountered. It may Nuitka-Plugins:WARNING: slow down compilation. Nuitka-Plugins:WARNING: Complex topic! More information can be found at Nuitka-Plugins:WARNING: https://nuitka.net/info/unwanted-module.html

So that’s informing the user to take action. And in the case of optional imports, i.e. ones where using code will handle the ImportError just fine and work without it, we can use do this.

- module-name: 'toga' anti-bloat: - description: 'remove setuptools usage' no-auto-follow: 'setuptools_scm': '' when: 'not use_setuptools'

He we say, no not automatically follow setuptools_scm reports, unless there is other code that still does it. In that way, the import still happens if some other part of the code imports the module, but only then. We no longer enforce the non-usage of a module here, we just make that decision based on other uses being present.

With this the bloat warning, and the inclusion of setuptools_scm into the compilation is removed, and you always want to make as small as possible and remove those packages that do not contribute anything but overhead, aka bloat.

The next thing discovered was that toga needs the toga-core distribution to version check. For that, we use the common solution, and tell that we want to include the metadata of it, for when toga is part of a compilation.

- module-name: 'toga' data-files: include-metadata: - 'toga-core'

So that moved the entire issue of version looks to resolved.

Step 2 - Dynamic Backend dependency

Now on to the backend issue. What remained was a need for including the platform specific backend. One that can even be overridden by an environment variable. For full compatibility, we invented something new. Typically what we would have done is to create a toga plugin for the following snippet.

- module-name: 'toga.platform' variables: setup_code: 'import toga.platform' declarations: 'toga_backend_module_name': 'toga.platform.get_platform_factory().__name__' anti-bloat: - change_function: 'get_platform_factory': "'importlib.import_module(%r)' % get_variable('toga_backend_module_name')"

There is a whole new thing here, a new feature that was added specifically for this to be easy to do. And with the backend selection being complex and partially dynamic code, we didn’t want to hard code that. So we added support for variables and their use in Nuitka Package Configuration.

The first block variables defines a mapping of expressions in declarations that will be evaluated at compile time given the setup code under setup_code.

This then allows us to have a variable with the name of the backend that toga decides to use. We then change the very complex function get_platform_factory that we used used, for compilation, to be replacement that Nuitka will be able to statically optimize and see the backend as a dependency and use it directly at run time, which is what we want.

Final remarks

I am hoping you will find this very helpful information and will join the effort to make packaging for Python work out of the box. Adding support for toga was a bit more complex, but with the new tool, once identified to be that kind of backend issue, it might have become a lot more easy.

Lessons learned. We should cover packages that we routinely remove from compilation, like setuptools, but e.g. also IPython. This will have to added, such that setuptools_scm cannot cloud the vision to actual issues.

What are those words on the bottom of your video screen and where do they come from? Captioning’s normalization in the past several decades may seem like it would render those questions moot, but understanding more about captions means making more informed decisions about when, how, and why we make sure information is accessible.

Join Fran Garcia, Senior Drupal Developer at the Drupal Association, as he unveils the driving forces behind Drupal's evolution. Fran shares exclusive insights with Kazima Abbas, Sub Editor at The DropTimes (TDT), exploring strategic projects, global hiring initiatives, and the transformative impact of GitLab CI on Drupal's development process. Discover the symbiotic relationship between Fran's role, the Drupal community, and his unique journey from teaching to web development.

#613 – JANUARY 23, 2024
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Python Packaging, One Year Later: A Look Back at 2023

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Running Python on Air-Gapped Systems

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Elevate Your Web Development with MongoDB’s Full Stack FastAPI App Generator

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Articles & Tutorials Bias, Toxicity, and Truthfulness in LLMs With Python

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Postgres vs. DynamoDB: Which Database to Choose

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January 24, 2024
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Happy Pythoning!
This was PyCoder’s Weekly Issue #613.
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In this tutorial, we’ll explain the difference between Python map vs list comprehension. Both map and list comprehensions are powerful tools in Python for applying functions to each element of a sequence. However, they have different strengths and weaknesses, making them suitable for different situations. Here’s a breakdown: What is the Difference Between the Python […]

The post Python Map vs List Comprehension – The Difference Between the Two appeared first on TechBeamers.

In this post, we explain to all novice Drupal developers and Drupal site owners how to develop a page layout for a Drupal-based site using the Layout Builder.

This is part 2 of the series on the Layout Builder. You can find the first post here: Layout Builder | The power module in a nutshell.

With Composer and several useful modules, your Drupal 9 site can be upgraded to Drupal 10 as quickly as possible. Here is a step-by-step guide on how to do this and save you time.

Python lists are similar to real-life lists. You can use them to store and organize a collection of objects, which can be of any data type. Instead of just storing one item, a list can hold multiple items while allowing manipulation and retrieval of those items. Because lists are mutable, you can think of them as being written in pencil. In other words, you can make changes.

Tuples, on the other hand, are written in ink. They’re similar to lists in that they can hold multiple items, but unlike lists, tuples are immutable, meaning you can’t modify them after you’ve created them.

In this video course, you’ll learn:

• What lists and tuples are and how they’re structured
• How lists and tuples differ from other data structures
• How to define and manipulate lists and tuples in your Python code

By the end of this course, you’ll have a solid understanding of Python lists and tuples, and you’ll be able to use them effectively in your own programming projects.

This video course is part of the Python Basics series, which accompanies Python Basics: A Practical Introduction to Python 3. You can also check out the other Python Basics courses.

Note that you’ll be using IDLE to interact with Python throughout this course.

[ 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 ]

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Drupal voice search has evolved from being a mere trend to becoming a standard feature for websites today. If you find yourself wondering, 'How do I enable search based on voice recognition on my Drupal website?' — you're in the right place. 

Integrating voice search functionality into your Drupal site is not only modern but also enhances user experience and is extremely important for SEO ranking. In this blog post, we'll walk you through the steps to set up search based on voice recognition, making your Drupal site more accessible and user-friendly. But before we dive into the steps, let’s understand…

<strong>Topics covered in this episode:</strong><br> <ul> <li><a href="https://www.syntaxerror.tech/syntax-error-11-debugging-python/"><strong>Syntax Error #11: Debugging Python</strong></a></li> <li><a href="https://umami.is">umami</a> and <a href="https://pypi.org/project/umami-analytics/">umami-analytics</a></li> <li><a href="https://github.com/okken/pytest-suite-timeout"><strong>pytest-suite-timeout</strong></a></li> <li><a href="https://listmonk.app">Listmonk</a> and <a href="https://pypi.org/project/listmonk/">(py) listmonk</a></li> <li><strong>Extras</strong></li> <li><strong>Joke</strong></li> </ul><a href='https://www.youtube.com/watch?v=Tac5MS__IBA' style='font-weight: bold;'data-umami-event="Livestream-Past" data-umami-event-episode="368">Watch on YouTube</a><br> <p><strong>About the show</strong></p> <p>Sponsored by us! Support our work through:</p> <ul> <li>Our <a href="https://training.talkpython.fm/"><strong>courses at Talk Python Training</strong></a></li> <li><a href="https://courses.pythontest.com/p/the-complete-pytest-course"><strong>The Complete pytest Course</strong></a></li> <li><a href="https://www.patreon.com/pythonbytes"><strong>Patreon Supporters</strong></a></li> </ul> <p><strong>Connect with the hosts</strong></p> <ul> <li>Michael: <a href="https://fosstodon.org/@mkennedy"><strong>@mkennedy@fosstodon.org</strong></a></li> <li>Brian: <a href="https://fosstodon.org/@brianokken"><strong>@brianokken@fosstodon.org</strong></a></li> <li>Show: <a href="https://fosstodon.org/@pythonbytes"><strong>@pythonbytes@fosstodon.org</strong></a></li> </ul> <p>Join us on YouTube at <a href="https://pythonbytes.fm/stream/live"><strong>pythonbytes.fm/live</strong></a> to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too.</p> <p><strong>Brian #1:</strong> <a href="https://www.syntaxerror.tech/syntax-error-11-debugging-python/"><strong>Syntax Error #11: Debugging Python</strong></a></p> <ul> <li>Juhis</li> <li>Issue 11 of a fun debugging newsletter from Juhis</li> <li>Debugging advice <ul> <li>mindeset <ul> <li>take a break</li> <li>adopt a process</li> <li>talk to a duck</li> </ul></li> <li>tools &amp; techniques <ul> <li>print</li> <li>snoop</li> <li>debuggers</li> <li>Django debug toolbar &amp; Kolo for VS Code</li> </ul></li> </ul></li> </ul> <p><strong>Michael #2:</strong> <a href="https://umami.is">umami</a> and <a href="https://pypi.org/project/umami-analytics/">umami-analytics</a></p> <ul> <li>Umami makes it easy to collect, analyze, and understand your web data — while maintaining <strong>visitor privacy</strong> and <strong>data ownership</strong>.</li> <li><a href="https://pypi.org/project/umami-analytics/">umami-analytics</a> is a client for privacy-preserving, open source <a href="https://umami.is/">Umami analytics platform</a> based on <code>httpx</code> and <code>pydantic</code>.</li> <li>Core features</li> <li>➕ <strong>Add a custom event</strong> to your Umami analytics dashboard.</li> <li>🌐 List all websites with details that you have registered at Umami.</li> <li>🔀 Both <strong>sync</strong> and <strong>async</strong> programming models.</li> <li>⚒️ <strong>Structured data with Pydantic</strong> models for API responses.</li> <li>👩‍💻 <strong>Login / authenticate</strong> for either a self-hosted or SaaS hosted instance of Umami.</li> <li>🥇Set a <strong>default website</strong> for a <strong>simplified API</strong> going forward.</li> </ul> <p><strong>Brian #3:</strong> <a href="https://github.com/okken/pytest-suite-timeout"><strong>pytest-suite-timeout</strong></a></p> <ul> <li>While recording <a href="https://podcast.pythontest.com/episodes/213-repeating-tests">Python Test 213 : Repeating Tests</a> <ul> <li>I noted that pytest-repeat doesn’t have a timeout, but pytest-flakefinder does.</li> <li>And perhaps I should add a timeout to pytest-repeat</li> </ul></li> <li>But also, maybe there’s other places I’d like a timeout, not just with repeat, but often with other parametrizations and even parametrize matrices. </li> <li>So, <a href="https://github.com/okken/pytest-suite-timeout"><strong>pytest-suite-timeout</strong></a> is born</li> <li>But <a href="https://hachyderm.io/@miketheman/111799555975904630">Why not pytest-timeout? asks Mike Felder</a> <ul> <li>timeout is only timeouts per test, and it isn’t always graceful</li> <li>suite-timeout is for the full suite, and only times out between tests.</li> <li>so, you could use both</li> </ul></li> </ul> <p><strong>Michael #4:</strong> <a href="https://listmonk.app">Listmonk</a> and <a href="https://pypi.org/project/listmonk/">(py) listmonk</a></p> <ul> <li><a href="https://listmonk.app">Listmonk</a> <ul> <li>Self-hosted newsletter and mailing list manager (think mailchimp)</li> <li>Built on Go and Vue</li> <li>Backed by a company charing for this service as SaaS</li> <li>Still requires a mail infrastructure backend (I’m using <a href="https://sendgrid.com">Sendgrid</a>)</li> </ul></li> <li><a href="https://pypi.org/project/listmonk/">listmonk</a> (on PyPI) <ul> <li>API Client for Python</li> <li>Created by Yours Truly</li> <li>I tried 4 other options first, they were all bad in their own way.</li> <li>Features:</li> <li>➕<strong>Add a subscriber</strong> to your subscribed users.</li> <li>🙎 Get <strong>subscriber details</strong> by email, ID, UUID, and more.</li> <li>📝 <strong>Modify subscriber details</strong> (including custom attribute collection).</li> <li>🔍 <strong>Search</strong> your users based on app and custom attributes.</li> <li>🏥 Check the <strong>health and connectivity</strong> of your instance.</li> <li>👥 Retrieve your <strong>segmentation lists</strong>, list details, and subscribers.</li> <li>🙅 Unsubscribe and block users who don't want to be contacted further.</li> <li>💥 Completely delete a subscriber from your instance.</li> <li>📧 Send transactional email with template data (e.g. password reset emails).</li> </ul></li> <li>These pair well in my new <a href="https://www.docker.com">docker</a> cluster infrastructure <ul> <li>Calls to the API from a client app (e.g. <a href="https://training.talkpython.fm">Talk Python Training</a>) are basically loopback on the local docker bridge network.</li> </ul></li> </ul> <p><strong>Extras</strong> </p> <p>Michael:</p> <ul> <li>Every github repo that has “releases” has a releases RSS feed, e.g. <a href="https://github.com/umami-software/umami/releases.atom">Umami</a></li> <li><a href="https://kolo.app">Kolo Django + VS Code</a></li> <li><a href="https://www.warp.dev/linux-terminal">Warp Terminal</a> on linux</li> <li><a href="https://fosstodon.org/@mkennedy/111787125592445700">bpytop and btop</a> - live server monitoring</li> </ul> <p><strong>Joke:</strong> <a href="https://infosec.exchange/@jbhall56/111178034352233910">The cloud, visualized</a></p>