Feature flags Pt 1: Faster feature development with flags. đ
The greatest accelerator of my team's work last year was adopting feature flags. With flags we ship features faster, more confidently and with less stress. We have fewer merge conflicts despite frequently working together on the same part of the code base.
Result pattern - An exceptional way to handle errors đ
People often say that in Python you should use exceptions - "Easier to Ask Forgiveness than Permission" (EAFP) over guard clauses - "Look Before You Leap" (LBYL), but the Result design pattern - returning an object which explicitly states whether the operation succeeded is a useful alternative where error handling is required and, as I learned by exploring in more depth, it can be compatible with both approaches.
As my design patterns repo approaches 100â on GitHub I decided to add the Result design pattern to the mix
EAFP vs LBYL
or Graham plays with GitHub Code Search
Prompted by a post on Mastodon I looked a bit more into which patterns people are using for error handling specifically for attribute lookup: I'm surprised to see twice as many references to hasattr as for "except AttributeError"
and not only for dynamic lookups but also for general attribute search, so a win for LBYL vs EAFP style with Python, despite the latter often being recommended ?
City Modelling with Generative AI: Tool or toy? đ
AI tools such as Chat-Gpt (text generation) and Dall-E (image generation) are making impressive leaps, allowing people to rapidly generate text, code and images from simple input prompts. The next frontier in generative AI may be 3D modelling, and OpenAI recently released the open source 3D modelling software Point·E. Could computer games, films and even architecture use these techniques to replace or improve manual city modelling?
33 3D mesh models, each generated from the text prompt "a buildng"â
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đŒTrouver un musicothĂ©rapeuteđŒ đ
Ma femme est non seulement une superbe musicienne mais aussi une musicothĂ©rapeute : elle soigne les gens, ou les aide Ă se soigner eux-mĂȘmes, avec de la musique!
J'ai crée cette carte des musicothérapeutes français avec la méthode suivante:
- Scrape le site web de la Fédération Française de Musicothérapie avec Requests et Beautiful Soup
- Géocoder les addresses de tous les musicothérapeutes via OSM (cette partie prend plusieurs minutes)
- Créer une carte avec un marqueur par musicothérapeute avec Folium.
- Enregistrer la carte sous format html
J'utilise la fonction suivantes pour générer mes tags HTML pour les marqueurs:
def tagged(txt:str, tag:str): str = txt.strip() if str: return f"<{tag}>{txt}</{tag}>\n" else: return ""
Fail fast - coder sereinement : Tests dans Jupyter đ
Following the "fail fast" principal I have found it really useful when coding engineering and data science code in Jupyter to follow this pattern:
- Write the code in a Jupyter notebook - this is a great option for scientific and technical computing as it lets you combine code, visualisation and documentation all in the same place.
- Find independent sample calculations from text books or other commonly used tools - the key is that the examples should not be generated from your own code.
- Add sample calculations with assert statements in the same cell as the function definition to demonstrate that the function works.
This last point is the key to the method I suggest here - the tests are run every time you update your definition but if the test is slow it will only be run the first time you reopen the notebook, once you are happy with the function you can reuse it without re-running the tests
Aerodynamic Behaviour and Structural Safety of Tower Cranes đ
Upon moving to work at the French national scientific research organisation for the built environment, CSTB, I was surprised to see the attention to detail in tower crane studies - looking at the risk of strong winds, construction site exposure and swirling winds potentially setting tower cranes rotating.
Following some LinkedIn posts and academic articles on the subject I was invited by the UK Wind Engineering Society to give an online talk. I gave some of the history of the subject, the key factors influencing risk levels and the methods used by the CSTB and by French insurers to assess and reduce risk levels.
En attendant la PyConFr (02/2021) â Traitement des rĂ©sultats dâessai en soufflerie đ
Un résumé de mes expériences de l'utilisation de Python en équipe d'ingénierie du vent https://pyvideo.org/en-attendant-la-pyconfr-2020-2021/traitement-des-resultats-dessai-en-soufflerie.html
Game of life in Rhino 3D đ
Hello.
Prompted by this yearâs Advent Of Code challenge I have implemented a 3D version of the game of life in Python in Rhino 7.
Here are some images renders from individual steps in my solution, followed by the code I used to generate them.
RhinoPython: may the source be with you! đ
Hello everyone,
I wrote a script to help me code in python and learn RhinoCommon and decided to share it with you đ
As you may know, the rhinoscriptsyntax library is written in Python and uses rhinocommon functions, also in Python, under the hood. In order to look up the underlying code you can open up the full python file, you can use the inspect module or you can save the script below to your computer and run it each time you want to look up a particular function. For instance if you search for âboundingâ you get the following options:
Here comes the sun đ
I spend too much of my life sitting alone in an office working on my conputer or looking at my smartphone. My regular dose of fresh air comes from my bike - I ride to work and back regularly - but I also enjoy getting out into the garden when I can. Trouble is, I dont really enjoy gardening! I do get a lot of satisfaction from pruning the trees and shrubs, especially if it involves some climbing and as a result we now have an enormous pile of branches, leaves and twigs in the bottom of the garden. I recently found a new activity which satisfies my creative side and starts to diminish the stack o' cuttings : building 'dead hedge' style walls and fences.
