Python has many string formatting styles which have been added to the language over the years. Early Python used the % operator to injected formatted values into strings. And we have string.format() which offers several powerful styles. Both were verbose and indirect, so f-strings were added in Python 3.6. But these f-strings lacked security features (think little bobby tables) and they manifested as fully-formed strings to runtime code. Today we talk about the next evolution of Python string formatting for advanced use-cases (SQL, HTML, DSLs, etc): t-strings. We have Paul Everitt, David Peck, and Jim Baker on the show to introduce this upcoming new language feature.
PEP 750 – Template Strings: peps.python.org tdom - Placeholder for future library on PyPI using PEP 750 t-strings: github.com PEP 750: Tag Strings For Writing Domain-Specific Languages: discuss.python.org How To Teach This: peps.python.org PEP 501 – General purpose template literal strings: peps.python.org Python's new t-strings: davepeck.org PyFormat: Using % and .format() for great good!: pyformat.info flynt: A tool to automatically convert old string literal formatting to f-strings: github.com Examples of using t-strings as defined in PEP 750: github.com htm.py issue: github.com Exploits of a Mom: xkcd.com pyparsing: github.com Watch this episode on YouTube: youtube.com Episode #505 deep-dive: talkpython.fm/505 Episode transcripts: talkpython.fm
Jay Shah, former Chief Operating Officer of Octo and now Strategic Advisor at Technomile joins the show to explore how small and mid-sized companies can scale effectively and thrive amid federal market shifts. We also unpack his personal journey from helping build Octo from the ground up to navigating multiple acquisitions and get his candid perspective on the evolving landscape of government contracting, particularly the increasing focus on performance-based acquisition, innovation, and the rising expectations for industry to deliver differentiated value. Finally we dive deep into how tools like Technomile’s platform are equipping businesses to capture growth opportunities with precision, optimize resource alignment, and meet the moment of generational disruption in federal procurement.
Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) OpenAI has another new top executive structure 2) What is Sam Altman's role now? 3) Who is Fidji Simo, OpenAI's new CEO of Applications 4) OpenAI abandons total for-profit conversion 5) Microsoft's demands on OpenAI 6) Could Apple replace Google as the default search with AI? 7) Is it an either or decision? 8) Could Apple make AI companies bid for the default search position? 9) Everyone is cheating using ChatGPT in college 10) Do people need to change or does the education system need to change?
---
Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice.
Alembic is an AI platform that helps organizations see how marketing spend connects to revenue so they can illuminate blind spots and make more informed business decisions.
In this episode of Leaders of Code, Dan Lines, cofounder and COO of LinearB; Ben Matthews, Senior Director of Engineering at Stack Overflow; and host Ben Popper talk about why velocity should be a diagnostic tool, not the primary goal of engineering teams. They also touch on the need for cross-disciplinary collaboration to align engineering with business objectives.
They also discuss:
AI's potential to automate repetitive tasks, allowing engineers to focus on more complex work.
The challenges of scaling organizations and the importance of centralized developer experience teams to improve productivity.
How non-technical staff can contribute to engineering tasks through the democratization of technology, enabling more innovation.
Gary Marcus is a cognitive scientist, author, and longtime AI skeptic. Marcus joins Big Technology to discuss whether large‑language‑model scaling is running into a wall. Tune in to hear a frank debate on the limits of “just add GPUs" and what that means for the next wave of AI. We also cover data‑privacy fallout from ad‑driven assistants, open‑source bio‑risk fears, and the quest for interpretability. Hit play for a reality check on AI’s future — and the insight you need to follow where the industry heads next.
---
Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice.
Anurag Goel grew up in New Delhi, but moved to Boston after college for his first job. He worked at Stripe, as the 8th employee, before eventually moving on and launching his current venture. Outside of tech, he is married, living in San Francisco. He likes to read science fiction, especially prior to bedtime. He also enjoys eating Thai food on the regular, though he mentioned he could eat pizza every day.
Post leaving Stripe, Anurag decided to work on an ambitious problem, and he started doing this by building a bunch of stuff in many different domains. After noticing a common problem in building out Kubernetes, he decided to start a new business to abstract these problems, and allow builders to focus on the differentiating factors to their solutions.
Janna Levin is a theoretical physicist and cosmologist specializing in black holes, cosmology of extra dimensions, topology of the universe, and gravitational waves.
Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep468-sc
See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc.
OUTLINE:
(00:00) – Introduction
(00:51) – Sponsors, Comments, and Reflections
(09:21) – Black holes
(16:55) – Formation of black holes
(27:45) – Oppenheimer and the Atomic Bomb
(34:08) – Inside the black hole
(47:10) – Supermassive black holes
(50:39) – Physics of spacetime
(53:42) – General relativity
(59:13) – Gravity
(1:15:47) – Information paradox
(1:24:17) – Fuzzballs & soft hair
(1:27:28) – ER = EPR
(1:34:07) – Firewall
(1:42:59) – Extra dimensions
(1:45:24) – Aliens
(2:01:00) – Wormholes
(2:11:57) – Dark matter and dark energy
(2:22:00) – Gravitational waves
(2:34:08) – Alan Turing and Kurt Godel
(2:46:23) – Grigori Perelman, Andrew Wiles, and Terence Tao
(2:52:58) – Art and science
(3:02:37) – The biggest mystery