Samuel Colvin ✓

@samuelcolvin · London/San Francisco · joined 06 Jan 2013

Founder @pydantic.

21 918Followers

920Following

5 746Posts total

80.8KViews on collected posts

Neueste Beiträge

Samuel Colvin ✓@samuelcolvin14 Sep

Some ideas are too good to not to steal. PyScript's antigravity example ported to Monty. https://t.co/G8RhnUBtNZ 1.8K views · 15 likes · 0 reposts · 2 replies Open on X →

Samuel Colvin ✓@samuelcolvin14 Sep

@samuelcolvin Writing this for the PyScript launch is still one of my favorite demo ideas: https://t.co/sTMh0XVnmW https://t.co/KGz0tvNjtH

GIF

5.3K views · 10 likes · 1 reposts · 1 replies Open on X →

Samuel Colvin ✓@samuelcolvin14 Sep

@samuelcolvin See also: import this from __future__ import braces 𝜋thon (added executable in python 3.14 virtualenvs) 1.7K views · 4 likes · 0 reposts · 0 replies Open on X →

Samuel Colvin ✓@samuelcolvin14 Sep

@samuelcolvin Not surprised when the name of the language was from the best sketch show ever. I'm also glad that the team keep the tradition alive 3K views · 4 likes · 0 reposts · 0 replies Open on X →

Samuel Colvin ✓@samuelcolvin14 Sep

This is kind of nuts. I'm amazed Python let something so playful into the standard library. https://t.co/LQO6h6M5mt 36.1K views · 135 likes · 3 reposts · 16 replies Open on X →

Samuel Colvin ✓@samuelcolvin13 Sep

There is currently a nasty bug in @github where diffs display wrong when you switch to the "Files changed" tab. It goes away if you reload the page, but it's confused me about 10times this weekend. https://t.co/PEkN06oN8W

2.6K views · 31 likes · 0 reposts · 1 replies Open on X →

Samuel Colvin ✓@samuelcolvin12 Sep

Significant `jiter` release, in particular this includes SIMD support for x86, which should give up to 7x performance improvement for parsing long strings. There are also significant improvements for tape reuse, arm64 string SIMD, float parsing and more. jiter is the most used 5.5K views · 28 likes · 3 reposts · 5 replies Open on X →

Samuel Colvin ✓@samuelcolvin11 Sep

@samuelcolvin @pydantic I've been waiting for the "not ready for prime time" language to be removed, looks like that finally happened on September 4th: https://t.co/AUA12haXqI 5.3K views · 7 likes · 0 reposts · 3 replies Open on X →

Samuel Colvin ✓@samuelcolvin11 Sep

@samuelcolvin @pydantic Using Monty to run Agentic workflows (generating python control-flow for agents orchestration), including running workflows on Claude as a replacement for JS. Maybe "Agents orchestration" could be a good selling point additionally to tools orchestration 305 views · 4 likes · 0 reposts · 1 replies Open on X →

Samuel Colvin ✓@samuelcolvin11 Sep

@samuelcolvin @pydantic Hehehe “Full Monty” 502 views · 7 likes · 0 reposts · 0 replies Open on X →

Samuel Colvin ✓@samuelcolvin11 Sep

I go to New York to sell @pydantic Logfire. Easy - it's the best. Pydantic team wonder how long it'll take for enterprise to even think about Pydantic Monty (it's Samuel's crazy side project, brand new, is it even useful?), so I ask: ALL the financial institutions we speak to 18.6K views · 114 likes · 3 reposts · 18 replies Open on X →

Im Vergleich zu Konten gleicher Größe

11 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 10K–100K Follower. wird weit gezeigt, aber nur wenige dieser Zuschauer reagieren.

Medianaufrufe3 028dieses Konto924Median für 10K–100K

Reichweite, %13.82%dieses Konto3.62%Median für 10K–100K

Interaktion, %0.65%dieses Konto1.52%Median für 10K–100K

Kennzahl	Dieses Konto	Median für 10K–100K	Verhältnis
Medianaufrufe pro Beitrag	3 028	924	3.28×
Reichweite (Aufrufe ÷ Follower)	13.82%	3.62%	3.82×
Interaktionsrate	0.65%	1.52%	0.43×

Weitere Konten dieser Größe → Mit einem anderen Konto vergleichen → Wie diese Vergleichswerte entstehen →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

18.6K11 Sep

502

305

5.3K

5.5K12 Sep

2.6K13 Sep

36.1K14 Sep

1.7K

5.3K

1.8K

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.73%11 Sep

1.39%

1.64%

0.19%

0.65%12 Sep

1.21%13 Sep

0.43%14 Sep

0.13%

0.23%

0.95%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes70.1%359 in total

Reposts2.0%10 in total

Replies9.2%47 in total

Bookmarks18.8%96 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

Followers by day

14 Sep

Daily snapshots since 14 Sep 2026; the dashed line is the starting count.

Neueste Beiträge

Im Vergleich zu Konten gleicher Größe

Growth & engagement

Views per post

Engagement rate per post

What the audience does

Followers by day

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