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Explore the Frontend Editing module, a new release from 1xINTERNET that transforms the Drupal editor experience. Industry leaders discuss its impact and compatibility with current web technologies.

Discover insights from leading Drupal professionals on the challenges and solutions for creating a module that notifies users when new content is posted, as discussed by Jeff Geerling and other community members on LinkedIn.

Series Overview & ToC | Next Article (coming Apr 24th) ### SERIES INTRODUCTION Today, we are excited to launch a detailed blog series that serves as an in-depth guide on utilizing the Drupal 10 Migrate API. This series is designed to equip you with thorough explanations and step-by-step guidance for migrating all your data from a Drupal 7 site to Drupal 10, facilitating a smooth upgrade to the most current version of the platform. As we progress, we will introduce a DDEV-based development environment, complete with instructions to set it up. This environment is prepared with a Drupal 7 site already installed and a Drupal 10 site set as the migration target. Through the course of this series, we will walk you through the entire data migration process, covering a wide range of topics along the way, empowering you to migrate your own sites confidently. Contact Our Solutions Experts Helping you navigate the next steps on your Drupal Migration Journey Want to learn more? The Migrate API, created and co-maintained by Tag1 team members, is a flexible and powerful system that can be used to collect data from multiple sources and import it into Drupal. While migrating...

Read more mauricio Thu, 04/18/2024 - 13:23

Explore Purple A11y, an advanced open-source accessibility tool from Singapore Government Digital Services, aimed at improving web usability for individuals with disabilities. This tool facilitates comprehensive website scanning and offers a user-friendly interface for all users.

Join Bryan Gruneberg at LagoonCon on May 6 to explore the benefits of open-source hosting for the Open Website Alliance's CMS platforms. Discover how Lagoon's Kubernetes-based solutions can enhance your open-source strategy and streamline web development.

Nicole is a software engineer and writer, and recently wrote about the trade-offs we make when deciding which tests to write and how much testing is enough.

We talk about:

• Balancing schedule vs testing
• How much testing is the right about of testing
• Should code coverage be measured and tracked
• Good refactoring can reduce code coverage
• Is it worth testing error conditions?
• Are rare error codes ok to just monitor?
• API drift and autospec
• Mitigating risk
• Deciding what to test and what not to test
• Focus testing on key money-making features 
• If there's a bug in this part of the code, how much business impact is there?
• Performance testing needs to approximately match real world workloads
• Cost of a service breaking vs the cost of creating, maintaining, and running tests
• Keeping test suites quick to minimize getting distracted

Links:

• Too much of a good thing: the trade-off we make with tests 
• Load testing is hard, and the tools are... not great. But why?
• Yet Another Rust Resource (YARR!)
• Goodhart's law - "When a measure becomes a target, it ceases to be a good measure"

Sponsored by Mailtrap.io

• An Email Delivery Platform that developers love. 
• An email-sending solution with industry-best analytics, SMTP, and email API, SDKs for major programming languages, and 24/7 human support. 
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Sponsored by PyCharm Pro

• Use code PYTEST for 20% off PyCharm Professional at jetbrains.com/pycharm
• Now with Full Line Code Completion
• See how easy it is to run pytest from PyCharm at pythontest.com/pycharm

The Complete pytest Course

• For the fastest way to learn pytest, go to courses.pythontest.com
• Whether your new to testing or pytest, or just want to maximize your efficiency and effectiveness when testing.

<p>Nicole is a software engineer and writer, and recently wrote about the trade-offs we make when deciding which tests to write and how much testing is enough.</p><p>We talk about:</p><ul><li>Balancing schedule vs testing</li><li>How much testing is the right about of testing</li><li>Should code coverage be measured and tracked</li><li>Good refactoring can reduce code coverage</li><li>Is it worth testing error conditions?</li><li>Are rare error codes ok to just monitor?</li><li>API drift and autospec</li><li>Mitigating risk</li><li>Deciding what to test and what not to test</li><li>Focus testing on key money-making features </li><li>If there's a bug in this part of the code, how much business impact is there?</li><li>Performance testing needs to approximately match real world workloads</li><li>Cost of a service breaking vs the cost of creating, maintaining, and running tests</li><li>Keeping test suites quick to minimize getting distracted</li></ul><p><br></p><p>Links:</p><ul><li><a href="https://ntietz.com/blog/too-much-of-a-good-thing-the-cost-of-excess-testing/">Too much of a good thing: the trade-off we make with tests</a> </li><li><a href="https://ntietz.com/blog/load-testing-is-hard-but-why/">Load testing is hard, and the tools are... not great. But why?</a></li><li><a href="https://yarr.fyi">Yet Another Rust Resource (YARR!)</a></li><li><a href="https://en.wikipedia.org/wiki/Goodhart%27s_law">Goodhart's law</a> - "When a measure becomes a target, it ceases to be a good measure"</li></ul> <br><p><strong>Sponsored by Mailtrap.io</strong></p><ul><li>An Email Delivery Platform that developers love. </li><li>An email-sending solution with industry-best analytics, SMTP, and email API, SDKs for major programming languages, and 24/7 human support. </li><li>Try for Free at <a href="https://l.rw.rw/pythontest">MAILTRAP.IO</a></li></ul><p><strong>Sponsored by PyCharm Pro</strong></p><ul><li>Use code PYTEST for 20% off PyCharm Professional at <a href="https://www.jetbrains.com/pycharm/">jetbrains.com/pycharm</a></li><li>Now with Full Line Code Completion</li><li>See how easy it is to run pytest from PyCharm at <a href="https://pythontest.com/pycharm/">pythontest.com/pycharm</a></li></ul><p><strong>The Complete pytest Course</strong></p><ul><li>For the fastest way to learn pytest, go to <a href="https://courses.pythontest.com/p/complete-pytest-course">courses.pythontest.com</a></li><li>Whether your new to testing or pytest, or just want to maximize your efficiency and effectiveness when testing.</li></ul>

Review: Unseen Academicals, by Terry Pratchett

Series: Discworld #37 Publisher: Harper Copyright: October 2009 Printing: November 2014 ISBN: 0-06-233500-6 Format: Mass market Pages: 517

Unseen Academicals is the 37th Discworld novel and includes many of the long-standing Ankh-Morpork cast, but mostly as supporting characters. The main characters are a new (and delightful) bunch with their own concerns. You arguably could start reading here if you really wanted to, although you would risk spoiling several previous books (most notably Thud!) and will miss some references that depend on familiarity with the cast.

The Unseen University is, like most institutions of its sort, funded by an endowment that allows the wizards to focus on the pure life of the mind (or the stomach). Much to their dismay, they have just discovered that an endowment that amounts to most of their food budget requires that they field a football team.

Glenda runs the night kitchen at the Unseen University. Given the deep and abiding love that wizards have for food, there is both a main kitchen and a night kitchen. The main kitchen is more prestigious, but the night kitchen is responsible for making pies, something that Glenda is quietly but exceptionally good at.

Juliet is Glenda's new employee. She is exceptionally beautiful, not very bright, and a working class girl of the Ankh-Morpork streets down to her bones. Trevor Likely is a candle dribbler, responsible for assisting the Candle Knave in refreshing the endless university candles and ensuring that their wax is properly dribbled, although he pushes most of that work off onto the infallibly polite and oddly intelligent Mr. Nutt.

Glenda, Trev, and Juliet are the sort of people who populate the great city of Ankh-Morpork. While the people everyone has heard of have political crises, adventures, and book plots, they keep institutions like the Unseen University running. They read romance novels, go to the football games, and nurse long-standing rivalries. They do not expect the high mucky-mucks to enter their world, let alone mess with their game.

I approached Unseen Academicals with trepidation because I normally don't get along as well with the Discworld wizard books. I need not have worried; Pratchett realized that the wizards would work better as supporting characters and instead turns the main plot (or at least most of it; more on that later) over to the servants. This was a brilliant decision. The setup of this book is some of the best of Discworld up to this point.

Trev is a streetwise rogue with an uncanny knack for kicking around a can that he developed after being forbidden to play football by his dear old mum. He falls for Juliet even though their families support different football teams, so you may think that a Romeo and Juliet spoof is coming. There are a few gestures of one, but Pratchett deftly avoids the pitfalls and predictability and instead makes Juliet one of the best characters in the book by playing directly against type. She is one of the characters that Pratchett is so astonishingly good at, the ones that are so thoroughly themselves that they transcend the stories they're put into.

The heart of this book, though, is Glenda.

Glenda enjoyed her job. She didn't have a career; they were for people who could not hold down jobs.

She is the kind of person who knows where she fits in the world and likes what she does and is happy to stay there until she decides something isn't right, and then she changes the world through the power of common sense morality, righteous indignation, and sheer stubborn persistence. Discworld is full of complex and subtle characters fencing with each other, but there are few things I have enjoyed more than Glenda being a determinedly good person. Vetinari of course recognizes and respects (and uses) that inner core immediately.

Unfortunately, as great as the setup and characters are, Unseen Academicals falls apart a bit at the end. I was eagerly reading the story, wondering what Pratchett was going to weave out of the stories of these individuals, and then it partly turned into yet another wizard book. Pratchett pulled another of his deus ex machina tricks for the climax in a way that I found unsatisfying and contrary to the tone of the rest of the story, and while the characters do get reasonable endings, it lacked the oomph I was hoping for. Rincewind is as determinedly one-note as ever, the wizards do all the standard wizard things, and the plot just isn't that interesting.

I liked Mr. Nutt a great deal in the first part of the book, and I wish he could have kept that edge of enigmatic competence and unflappableness. Pratchett wanted to tell a different story that involved more angst and self-doubt, and while I appreciate that story, I found it less engaging and a bit more melodramatic than I was hoping for. Mr. Nutt's reactions in the last half of the book were believable and fit his background, but that was part of the problem: he slotted back into an archetype that I thought Pratchett was going to twist and upend.

Mr. Nutt does, at least, get a fantastic closing line, and as usual there are a lot of great asides and quotes along the way, including possibly the sharpest and most biting Vetinari speech of the entire series.

The Patrician took a sip of his beer. "I have told this to few people, gentlemen, and I suspect never will again, but one day when I was a young boy on holiday in Uberwald I was walking along the bank of a stream when I saw a mother otter with her cubs. A very endearing sight, I'm sure you will agree, and even as I watched, the mother otter dived into the water and came up with a plump salmon, which she subdued and dragged on to a half-submerged log. As she ate it, while of course it was still alive, the body split and I remember to this day the sweet pinkness of its roes as they spilled out, much to the delight of the baby otters who scrambled over themselves to feed on the delicacy. One of nature's wonders, gentlemen: mother and children dining on mother and children. And that's when I first learned about evil. It is built into the very nature of the universe. Every world spins in pain. If there is any kind of supreme being, I told myself, it is up to all of us to become his moral superior."

My dissatisfaction with the ending prevents Unseen Academicals from rising to the level of Night Watch, and it's a bit more uneven than the best books of the series. Still, though, this is great stuff; recommended to anyone who is reading the series.

Followed in publication order by I Shall Wear Midnight.

Rating: 8 out of 10

Hey everyone! Here is a new video explanation of the changes we have done. This time we tackled Labplot, maps, and media icons! Can you believe it? We are now officially past the mid-way for the icons. So exciting!

In this episode, I built the import view that is needed to allow users to add their own journal entries to JourneyInbox. After completing that, I handled the pull requests from dependabot, then I worked on some quality of life to do better handling with beta user trials.

Why would someone pick Django over Flask? That’s the question that I got on stream and here is my answer.

This is my very first post, just to make sure everything is working as expected.

Made with Zola and the Abridge theme.

I will be delivering my talk, "It is easy to contribute to GNU," Saturday, May 4, 2024, 12:15--13:00 EDT (16:00 UTC), at the LibrePlanet 2024 conference, and I hope you’ll check it out!

LibrePlanet is a conference about software freedom, happening on May 4 & 5, 2024. The event is hosted by the Free Software Foundation (FSF), and brings together software developers, law and policy experts, activists, students, and computer users to learn skills, celebrate free software accomplishments, and face upcoming challenges. Newcomers are always welcome, and LibrePlanet 2024 will feature programming for all ages and experience levels.

*Please register in advance at <https://libreplanet.org/2024/>.*

wxie

Join us THURSDAY, April 18 at 1pm ET / 10am PT, for our regularly scheduled call to chat about all things Drupal and nonprofits. (Convert to your local time zone.)

This month we'll be preparing for DrupalCon Portland, which features the return of the Nonprofit Summit!

And we'll of course also have time to discuss anything else that's on our minds at the intersection of Drupal and nonprofits.  Got something specific you want to talk about? Feel free to share ahead of time in our collaborative Google doc: https://nten.org/drupal/notes!

All nonprofit Drupal devs and users, regardless of experience level, are always welcome on this call.

This free call is sponsored by NTEN.org and open to everyone. 

• Join the call: https://us02web.zoom.us/j/81817469653

  • Meeting ID: 818 1746 9653
    Passcode: 551681

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  • Find your local number: https://us02web.zoom.us/u/kpV1o65N

• Follow along on Google Docs: https://nten.org/drupal/notes

View notes of previous months' calls.

Cédric Krier has found that trytond accepts compressed content from unauthenticated requests which makes it vulnerable to zip bomb attacks.

Impact

CVSS v3.0 Base Score: 5.3

• Attack Vector: Network
• Attack Complexity: Low
• Privileges Required: None
• User Interaction: None
• Scope: Unchanged
• Confidentiality: None
• Integrity: None
• Availability: Low

Workaround

A proxy can be deployed in front of the trytond server to forbid this kind of request.

Resolution

All affected users should upgrade trytond to the latest version.

Affected versions per series:

• trytond:
  • 7.0: <= 7.0.9
  • 6.8: <= 6.8.14
  • 6.0: <= 6.0.44

Non affected versions per series:

• trytond:
  • 7.0: >= 7.0.10
  • 6.8: >= 6.8.15
  • 6.0: >= 6.0.45

Reference

• Accept request with gzip content encoding may make server vulnerable to zip bomb (#13142) · Issues · Tryton / Tryton · GitLab

Concerns?

Any security concerns should be reported on the bug-tracker at https://bugs.tryton.org/ with the confidential checkbox checked.

1 post - 1 participant

Read full topic

Experience the ultimate Drupal getaway at DrupalCamping 2024 in Wolfsburg! Tickets are now on sale for four days of camping, chilling, swimming, barbecue, and Drupal excitement. Don't miss out – secure your spot today.

Drupal Developer Days announces featured speakers Gábor Hojtsy and Cristina Chumillas for their upcoming event in Burgas, Bulgaria. Get ready to dive deep into Drupal 11 updates and Admin UI changes. Don't miss out on this opportunity to learn from industry experts and connect with the Drupal community!

I am happy to report that the megactl package, useful to fetch RAID status when using the LSI Megaraid controller, now is available in Debian. It passed NEW a few days ago, and is now available in unstable, and probably showing up in testing in a weeks time. The new version should provide Appstream hardware mapping and should integrate nicely with isenkram.

As usual, if you use Bitcoin and want to show your support of my activities, please send Bitcoin donations to my address 15oWEoG9dUPovwmUL9KWAnYRtNJEkP1u1b.

What does every new developer do when they are first learning to program? They print out strings to their terminal. It’s how we learn! But printing out to the terminal isn’t what you do with most professional applications.

Support on Kickstarter 

In those cases, you log into files. Sometimes, you log into multiple locations at once. These logs may serve as an audit trail for compliance purposes or help the engineers debug what went wrong.

Python Logging teaches you how to log in the Python programming language. Python is one of the most popular programming languages in the world. Python comes with a logging module that makes logging easy.

What You’ll Learn

In this book, you will learn how about the following:

• Logger objects
• Log levels
• Log handlers
• Formatting your logs
• Log configuration
• Logging decorators
• Rotating logs
• Logging and concurrency
• and more!

Book formats

The finished book will be made available in the following formats:

• paperback (at the appropriate reward level)
• PDF
• epub

The paperback is a 6″ x 9″ book and is approximately 150 pages long.

 

You can support the book by clicking the button below:

Support on Kickstarter

The post Announcing The Python Logging Book & Course Kickstarter appeared first on Mouse Vs Python.

You’ll often need to format and round a Python float to display the results of your calculations neatly within strings. In earlier versions of Python, this was a messy thing to do because you needed to round your numbers first and then use either string concatenation or the old string formatting technique to do this for you.

Since Python 3.6, the literal string interpolation, more commonly known as a formatted string literal or f-string, allows you to customize the content of your strings in a more readable way.

An f-string is a literal string prefixed with a lowercase or uppercase letter f and contains zero or more replacement fields enclosed within a pair of curly braces {...}. Each field contains an expression that produces a value. You can calculate the field’s content, but you can also use function calls or even variables.

While most strings have a constant value, f-strings are evaluated at runtime. This makes it possible for you to pass different data into the replacement fields of the same f-string and produce different output. This extensibility of f-strings makes them a great way to embed dynamic content neatly inside strings. However, even though f-strings have largely replaced the earlier methods, they do have their short-comings.

For example, one of the most common attacks performed on a relational database is a SQL injection attack. Often, users provide parameters to SQL queries, and if the query is formed within an f-string, it may be possible to damage a database by passing in rogue commands. F-strings can also be used in a denial-of-service attack by attacking Python’s logging module code.

In older versions of Python, f-strings had a number of other limitations that were only fixed with Python version 3.12. This version is used throughout this tutorial.

Take a look at the example below. It shows you how to embed the result of a calculation within an f-string:

Python >>> f"One third, expressed as a float is: {1 / 3}" 'One third, expressed as a float is: 0.3333333333333333' Copied!

Without any explicit rounding, once an expression has produced its value it’ll be inserted into the string using a default number of decimal places. Here, the result is shown to sixteen decimal places, which, in most cases, is more precision than you’ll ever need. So you’ll likely want to round your final answer to a more practical number of digits.

In this tutorial, you’ll learn how to use a Python f-string to format floats to meet your requirements.

Get Your Code: Click here to download the free sample code and exercise solutions you’ll use for learning how to format floats within f-strings in Python.

Take the Quiz: Test your knowledge with our interactive “Format Floats Within F-Strings” quiz. Upon completion you will receive a score so you can track your learning progress over time:

Interactive Quiz

Format Floats Within F-Strings

In this quiz, you'll test your understanding of how to format floats within f-strings in Python. This knowledge will let you control the precision and appearance of floating-point numbers when you incorporate them into formatted strings.

How to Format and Round a Float Within a Python F-String

To format a float for neat display within a Python f-string, you can use a format specifier. In its most basic form, this allows you to define the precision, or number of decimal places, the float will be displayed with.

The code below displays the same calculation as before, only it’s displayed more neatly:

Python >>> f"One third, rounded to two decimal places is: {1 / 3:.2f}" 'One third, rounded to two decimal places is: 0.33' Copied!

To use Python’s format specifiers in a replacement field, you separate them from the expression with a colon (:). As you can see, your float has been rounded to two decimal places. You achieved this by adding the format specifier .2f into the replacement field. The 2 is the precision, while the lowercase f is an example of a presentation type. You’ll see more of these later.

Note: When you use a format specifier, you don’t actually change the underlying number. You only improve its display.

Python’s f-strings also have their own mini-language that allows you to format your output in a variety of different ways. Although this tutorial will focus on rounding, this is certainly not the only thing you can use them for. As you’ll see later, their mini-language is also used in other string formatting techniques.

In addition to displaying the result of calculations, the precision part of a format specifier can also be applied directly to variables and the return values of function calls:

Python >>> def total_price(cost): ... return cost * 1.2 ... >>> cost_price = 1000 >>> tax = 0.2 >>> f"£{1000:,.2f} + £{cost_price * tax:,.2f} = £{total_price(cost_price):,.2f}" '£1,000.00 + £200.00 = £1,200.00' Copied!

This time, you’ve used multiple replacement fields in the same string. The first one formats a literal number, the second formats the result of a calculation, while the third formats the return value from a function call. Also, by inserting a comma (,) before the decimal point (.) in the format specifier, you add a thousands separator to your final output.

In everyday use, you display numbers with a fixed amount of decimals, but when performing scientific or engineering calculations, you may prefer to format them using significant figures. Your results are then assumed to be accurate to the number of significant figures you display them with.

If you want to round numbers to significant figures, you use the lowercase letter g in the format specifier. You can also use an uppercase G, but this automatically switches the format to scientific notation for large numbers.

Suppose you have a circle with a radius of 10.203 meters. To work out the area, you could use this code:

Read the full article at https://realpython.com/how-to-python-f-string-format-float/ »

[ 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 ]

OpenStreetMaps (OSM) is known for being an open source project that allows people to browse the world map and to plan routes. However it is more than that. Among others it provides a read-only API that allows users to query for very diverse map data: Overpass API

Data structure of OSM

To understand the structure of the queries, we first need to understand how OSM saves its data. OSM uses basic data structures: node, way, and relation. Each element can have multiple tags, which consist of a key-value pair and they help specify the features of each element.

Nodes also save a latitude and longitude, indicating where the node is located on the world. Ways contain a list of the nodes contained in the way. Finally, relations are groups of nodes, ways and relations defining a logical relationship for this elements, for example being part of the same street, neighbourhood, city, postal code area, etc.

If we go to https://www.openstreetmap.org/, right-click on some point of the map and then click on Query Features, we get a list of the elements of the area. By clicking on one of them, we can explore it’s characteristics. As an example, we can explore the node 1918872432, which we can see on the left picture. Looking at the data we can see that it is located at longitude 52.5024783 and latitude 13.4155630. On the tags we can see it has the name Oranienplatz and among others it contains a bench and a bin. The key highway contains the value bus_stop, which tells us it is a bus stop.

If we explore the way 1228261444 (right picture) we can see a list of all the nodes it contains. In addition on the key highway we can see it’s of the type footway, telling us it’s a way intended for pedestrians. In addition we can see that it is a lit way.

Many keywords like highway are normalized. As an example, we can find a list of standardized values for highway here.

Overpass Queries Querying a single element

We can query the previous information using Overpass QL. For the query to get the information about the way 1228261444 we use way(1228261444). The default output format is in xml, so if we want to have it in json, we need to add [out:json] in front of it. Other possible formats are csv, for which we need to define the list of columns for it to work. We mark the end of the query with an out, so the complete query is:

[out:json]; way(1228261444); out;

To execute the query we need to run it against an instance, thus the complete URL looks like this:

https://overpass-api.de/api/interpreter?data=[out:json];way(1228261444);out;

We can copy the URL directly on the browser, or we can use wget to see the result:

wget -O my_file_name.osm "https://overpass-api.de/api/interpreter?data=[out:json];way(1228261444);out;"

To query a single node or relation works in a parallel way.

Output format { "version": 0.6, "generator": "Overpass API 0.7.61.5 4133829e", "osm3s": { "timestamp_osm_base": "2024-03-06T20:54:14Z", "copyright": "The data included in this document is from www.openstreetmap.org. The data is made available under ODbL." }, "elements": [ { "type": "way", "id": 1228261444, "nodes": [ 9010521154, 9010521155, 11390038869, 11390038870, 9394918823, 9394918824, 4613855449, 11390038871, 11390038872, 11390038873, 9394918822 ], "tags": { "footway": "sidewalk", "highway": "footway", "lit": "yes", "surface": "paving_stones" } } ] }

Here we can see two main blocks: the first with metadata like the version or the timestamp, and the second one with a list of the elements found with the query. Even if we queried for one specific element of type way, we still get it as a set formatted as list with length 1.

Querying many elements

If we don’t want the information of one singe way, but the information of all ways in an area, we need to change the query a little bit:

[out:json]; way(52.49505089381484,13.401961459729343,52.509912981033516,13.411502705004548); out;

Here, instead of requesting one single way, we put 4 coordinates in the parenthesis: boundaries in the south, west, north and east.

This returns a set of all the ways contained in the bounding box defined by the given coordinates.

It is not always needed to know the coordinates to get information for an area. With the query

[out:json]; area[name="Zürich"]; out;

we get all areas called Zürich. In this example we can see that we can use special characters without problem. Most interestingly are both square parentheses behind area [name=”Zürich”]. This is a filter where we only get the areas that contain a tag with key name and value Zürich.

We can use more than one filter, for example to get only the element representing the city Zürich, in contrast to the canton Zürich. In that case we can just place them one after another like this:

[out:json]; area[name=”Zürich”][place=”city”]; out;

We can filter by elements containing a certain tag independently from it’s value.

[out:json]; area[name=”Zürich”][place]; out;

This returns a set of all areas containing the tag place, which in this case contains the same element as above.

Subqueries

We can use the area we got in the previous query to get a set of certain elements inside said area. For example, if we want to get all public toilets in Zürich, we can use the following query:

[out:json]; area[name="Zürich"][place="city"]; node[amenity="toilets"](area); out;

First we get the area corresponding to the city Zürich, and then we get all nodes whose tag key amenity contains the value toilets. By passing the area between the round parenthesis we limit the set of nodes to the previous area.

The tag amenity describes a large number of important facilities from cafés, public bookcases, benches, vending machines, ATMs, etc.

Other useful tag names to find interesting places are tourism and historic.

TIL: there is also a value for public baking ovens, baking_oven. Apparently there are 2 of those which Zürich, which looks to me like a good reason to visit that city again. Seriously, how awesome is that?

Using overpass in Python

There are two ways to execute overpass queries with python that we will explore. One possibility is using the library and the other the library overpass-api-python-wrapper.

Requests

Example:

import requests overpass_url = 'https://overpass-api.de/api/interpreter' overpass_query = ''' [out:json]; area[name="Zürich"][place="city"]; node[amenity="toilets"](area); out; ''' response = requests.get(overpass_url, params={'data': overpass_query})

This way we send to the overpass interpreter the query in overpass_query and save the result in the variable response. If no error happened, response.text contains the data as string so we can decode it with:

decoded_data =json.loads(response.text)

If we had requested the information in xml or csv format, we would decode it accordingly.

Overpass-api-python-wrapper

The overpass-api-python-wrapper allows us to execute queries in a more concise and elegant way. First we need to initialize an overpass object.

import overpass api = overpass.API(endpoint="https://overpass.myserver/interpreter", timeout=25)

All parameters are optional and the default values are the ones shown here.

query = 'area[name="Zürich"][place="city"];node[amenity="toilets"](area);' response = api.get(query, responseformat='json')

By default, response contains a dictionary representing the returned json object, however we can define the output format with the parameter responseformat. With this query, the response is

{ "features": [ { "geometry": { "coordinates": [ 8.534562, 47.350221 ], "type": "Point" }, "id": 75743585, "properties": { "amenity": "toilets", "capacity": "4", "check_date:wheelchair": "2022-06-06", "fee": "no", "name": "Landiwiese", "opening_hours": "24/7", "operator": "Z\u00fcriWC", "unisex": "yes", "wheelchair": "no" }, "type": "Feature" }, etc }

If we use xml as format, response will be a string, and with csv it will be a list.

Other Useful tools:

We can find a complete manual on Overpass QL here, where we can read about more awesome possibilities that Overpass has to offer to us.

You can also try out queries with overpass-turbo. However it will only display the returned nodes on the map, but you can also get the returned response as text in the tab Data.

Finally, you can find another cool tutorial for using overpass with python here. In this case, the author shows us new possibilities with overpass, including how to plot the queried data in plots.

I hope you could awake your curiosity about the potential that OpenStreetMaps and Overpass offers. For me in meant not only to learn about a powerful tool, but while exploring it and playing with it it allowed me to learn more about the possibilities our cities and towns have to offer to us. Did you know that there are public showers, including in some train stations? Or that there are public ovens?

What I finally have to say is: keep calm and keep building cool stuff!