Category: 3-SometimeTechTalk

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David Asamu grew up in Nigeria and got into technology early, through serving his community. He attended University, and continued his community efforts there, and was introduced to the joys of Python programming. Outside of tech, he spends time with his significant other and family. He enjoys soccer, whether it is watching over playing. When asked about food, he mentioned loving Nigerian delicacies, such as Jollof rice.

Previously, David was working at a fintech company. While he was there, he and his friends were observing the trends around AI - and they wanted to get more involved. So they got together and built something over the weekend... and eventually decided to advance AI through research.

This is the creation story of Nesla.

Sponsors

• Paddle.com
• Sema Software
• PropelAuth
• Postman
• Meilisearch

Links

• https://nesla.co/
• https://www.linkedin.com/in/david-asamu/

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Anthony Scaramucci is the founder and managing partner at SkyBridge Capital, and host of The Rest Is Politics US. Scaramucci joins Big Technology Podcast to talk about his brief experience as Trump's communication director, what derailed Elon Musk’s White House stint, the problems with Trump’s 'Big Beautiful Bill,' the state of the trade war, Tim Cook’s tariff troubles, bitcoin, and more. We also cover Long Island culture at the top of the show, if you’re into that. Tune in for a fast paced, fascinating look into the state of the global economy and the tech titans trying to ride it to results.

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Clément "Kero" Renault wanted to be an architect when he was younger. During that time, he also learned about computers and built his first website - and he never stopped building. Funny story, he lost that first website cause it wasn't on Git. Outside of his professional life, he likes to draw, craft and to cook. He also enjoys video games, and mentioned Hidden Reign was his favorite game of all time, alongside the likes of Cyberpunk.

Seven years ago, Kero was in school, and he wanted to build a solid search experience, but not just a general search - one that indexed your data, and allowed you to have a "Google" just for your info. After winning a school hackathon, Kero and his mates wanted to take it to the next level.

This is the creation story of Meilisearch.

Sponsors

• Paddle.com
• Sema Software
• PropelAuth
• Postman
• Meilisearch

Links

• https://www.meilisearch.com/
• https://www.linkedin.com/in/kerollmops/

Our Sponsors:
* Check out Vanta: https://vanta.com/CODESTORY


Support this podcast at — https://redcircle.com/code-story/donations

Advertising Inquiries: https://redcircle.com/brands

Privacy & Opt-Out: https://redcircle.com/privacy

Antithesis is an autonomous testing platform that finds bugs in your software with perfect reproducibility.

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Topics covered in this episode:

• Making PyPI’s test suite 81% faster
• People aren’t talking enough about how most of OpenAI’s tech stack runs on Python
• PyCon Talks on YouTube
• Optimizing Python Import Performance
• Extras
• Joke

Watch on YouTube

About the show

Sponsored by Digital Ocean: pythonbytes.fm/digitalocean-gen-ai Use code DO4BYTES and get $200 in free credit

Connect with the hosts

• Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky)
• Brian: @brianokken@fosstodon.org / @brianokken.bsky.social
• Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky)

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Brian #1: Making PyPI’s test suite 81% faster

• Alexis Challande
• The PyPI backend is a project called Warehouse
• It’s tested with pytest, and it’s a large project, thousands of tests.
• Steps for speedup
  • Parallelizing test execution with pytest-xdist
    • 67% time reduction
    • --numprocesses=auto allows for using all cores
    • DB isolation - cool example of how to config postgress to give each test worker it’s on db
    • They used pytest-sugar to help with visualization, as xdist defaults to quite terse output
  • Use Python 3.12’s sys.monitoring to speed up coverage instrumentation
    • 53% time reduction
    • Nice example of using COVERAGE_CORE=sysmon
  • Optimize test discovery
    • Always use testpaths
    • Sped up collection time. 66% reduction (collection was 10% of time)
    • Not a huge savings, but it’s 1 line of config
  • Eliminate unnecessary imports
    • Use python -X importtime
    • Examine dependencies not used in testing.
    • Their example: ddtrace
      • A tool they use in production, but it also has a couple pytest plugins included
      • Those plugins caused ddtrace to get imported
      • Using -p:no ddtrace turns off the plugin bits
• Notes from Brian:
  • I often get questions about if pytest is useful for large projects.
  • Short answer: Yes!
  • Longer answer: But you’ll probably want to speed it up
  • I need to extend this article with a general purpose “speeding up pytest” post or series.
  • -p:no can also be used to turn off any plugin, even builtin ones.
    • Examples include
      • nice to have developer focused pytest plugins that may not be necessary in CI
      • CI reporting plugins that aren’t needed by devs running tests locally

Michael #2: People aren’t talking enough about how most of OpenAI’s tech stack runs on Python

• Original article: Building, launching, and scaling ChatGPT Images
• Tech stack: The technology choices behind the product are surprisingly simple; dare I say, pragmatic!
  • Python: most of the product’s code is written in this language.
  • FastAPI: the Python framework used for building APIs quickly, using standard Python type hints. As the name suggests, FastAPI’s strength is that it takes less effort to create functional, production-ready APIs to be consumed by other services.
  • C: for parts of the code that need to be highly optimized, the team uses the lower-level C programming language
  • Temporal: used for asynchronous workflows and operations inside OpenAI. Temporal is a neat workflow solution that makes multi-step workflows reliable even when individual steps crash, without much effort by developers. It’s particularly useful for longer-running workflows like image generation at scale

Michael #3: PyCon Talks on YouTube

• Some talks that jumped out to me:
  • Keynote by Cory Doctorow
  • 503 days working full-time on FOSS: lessons learned
  • Going From Notebooks to Scalable Systems
    • And my Talk Python conversation around it. (edited episode pending)
  • Unlearning SQL
  • The Most Bizarre Software Bugs in History
  • The PyArrow revolution in Pandas
    • And my Talk Python episode about it.
  • What they don't tell you about building a JIT compiler for CPython
    • And my Talk Python conversation around it (edited episode pending)
  • Design Pressure: The Invisible Hand That Shapes Your Code
  • Marimo: A Notebook that "Compiles" Python for Reproducibility and Reusability
    • And my Talk Python episode about it.
  • GPU Programming in Pure Python
    • And my Talk Python conversation around it (edited episode pending)
  • Scaling the Mountain: A Framework for Tackling Large-Scale Tech Debt

Brian #4: Optimizing Python Import Performance

• Mostly pay attention to #'s 1-3
• This is related to speeding up a test suite, speeding up necessary imports.
• Finding what’s slow
  • Use python -X importtime <the reset of the command
  • Ex: python -X importtime ptyest
• Techniques
  • Lazy imports
    • move slow-to-import imports into functions/methods
  • Avoiding circular imports
    • hopefully you’re doing that already
  • Optimize __init__.py files
    • Avoid unnecessary imports, heavy computations, complex logic
• Notes from Brian
  • Some questions remain open for me
    • Does module aliasing really help much?
  • This applies to testing in a big way
    • Test collection imports your test suite, so anything imported at the top level of a file gets imported at test collection time, even if you only are running a subset of tests using filtering like -x or -m or other filter methods.
    • Run -X importtime on test collection.
    • Move slow imports into fixtures, so they get imported when needed, but NOT at collection.
• See also:
  • option -X in the standard docs
  • Consider using import_profile

Extras

Brian:

• PEPs & Co.
  • PEP is a ‘backronym”, an acronym where the words it stands for are filled in after the acronym is chosen. Barry Warsaw made this one up.
  • There are a lot of “enhancement proposal” and “improvement proposal” acronyms now from other communities
• pythontest.com has a new theme
  • More colorful. Neat search feature
  • Now it’s excruciatingly obvious that I haven’t blogged regularly in a while
    • I gotta get on that
  • Code highlighting might need tweaked for dark mode

Michael:

• git-bug
• Pyrefly follow up

Joke: There is hope.

Jim Richberg, Head of Cyber Policy and Global Field CISO at Fortinet rejoins the show for a timely discussion on the fast-evolving landscape of artificial intelligence and we unpack AI’s unprecedented energy demands, its implications on national infrastructure, and the critical cybersecurity considerations government agencies must navigate in this new era. Jim also shares his "Three Rules for Government Technology Transformation," and we explore why education and clear procurement strategies are vital to responsible AI rollout in public sector programs.

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Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) Anthropic CEO Dario Amodei's prophesy that 50% of entry level work will disappear 2) Hype or true: Is mass AI-driven unemployment just marketing? 3) How Amodei's prediction could come true 4) How work might shift even before job loss, as in the case of Amazon's engineers 5) NVIDIA's business is booming 6) Are export restrictions on China working? 7) DeepSeek's updated R1 model is here 8) Meta's AI problems 9) Meta teams up with Anduril 10) Did Mark call Palmer? 11) Grammarly's unique funding model 12) Elon Musk gets out of DOGE 13) CEOs using AI avatars on earnings calls

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Episode overview: In this conversation, South African strategist Wabo Majavu, executive strategy and business operations leader at Africa Data Centres, unpacks how technical expertise at organisations like MTN and Intelsat laid the foundation for her distinctive approach to strategic leadership and digital activism. From building radar applications at the CSIR to optimising cellular networks through late-night, township-sourced sheep's head dinners with seasoned veteran technicians, Majavu's journey illustrates how hands-on technical experience and savvy adaptation becomes the bedrock of strategic thinking. She discusses navigating workplace discrimination, helping transform organisational culture at state-owned Sentech, and her prescient work in AI before it became a global phenomenon. Andile Masuku explores with Majavu how strategists shape a company's future direction, the delicate balance between commercial viability and digital inclusion, and her current mission to democratise coding through native African languages. Key topics: - From radar systems at CSIR to RF optimisation at MTN: building the technical foundation for strategic leadership - How experiences at Intelsat shaped her understanding of managed services and market transformation - The Sentech years: leading digital transformation while learning that culture can eat even the best strategy for breakfast - Studying AI and signal processing before the global AI boom, and formative educational experiences in Malaysia that shaped future vision - Strategic stakeholder management: converting union leaders into product managers and building collaborative ecosystems - Balancing commercial imperatives with digital inclusion through long-term strategic thinking - Where to start learning AI: practical advice for breaking into the field Notable points: 1. Majavu's radar applications work at CSIR and cellular network optimisation at MTN provided the technical depth that informs her strategic decision-making today 2. At MTN, she overcame racial barriers by building relationships with Network Operations Centre (NOC) technicians through after-hours learning sessions, bringing sheep's head delicacies from Mamelodi township to earn their trust and knowledge 3. At Sentech, she learned firsthand that "culture can eat strategy for breakfast," successfully converting a well-respected, highly influential union leader into a turnkey product manager spearheading the roll-out of new digital services 4. Majavu studied signal processing and then AI before it became mainstream, building web crawlers and predictive systems 5. Her approach to change management involves understanding each stakeholder's agenda and finding areas of alignment, demonstrated through her successful transformation of adversaries into collaborators Listen for Majavu's insights on how strategists inform a company's trajectory, why patient capital and technical depth are essential for Africa's digital transformation, and how past experiences become the lens through which strategic leaders view future possibilities. Image credit: Konecta