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May 8, 2026May 8, 2026

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

April 26, 2026May 8, 2026

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

April 24, 2026

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

April 23, 2026May 8, 2026

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

April 20, 2026April 26, 2026

Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

April 20, 2026

Inside CPython’s obmalloc: How the Small Object Allocator Avoids the System Heap

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Understand pydantic core schema compilation, the main trade-offs, and the practical checks to use before relying on it in practice.
  • API Development
May 8, 2026May 8, 2026
Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

By Riko Ishikawa When Hypothesis catches a property violation, the failing input you eventually see in the traceback is almost never the input the.
  • Automation
April 26, 2026May 8, 2026
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

If you search polars streaming engine spill today, the top result is a benchmark that OOM'd on Polars 1.6.0 in September 2024.
  • Data Engineering
April 24, 2026
Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

The pola.rs blog has a headline number that every Polars tutorial copies: the optimized lazy plan runs roughly 4x faster than the naive one on the NYC.
  • Data Engineering
April 23, 2026May 8, 2026
Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

The technical barrier that kept Python's sub-interpreter feature from being genuinely useful for a decade wasn't parallelism — it was reference counting.
  • AI/ML
April 20, 2026April 26, 2026
Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL
Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

  • API Development
Mateo Vargas
May 8, 2026May 8, 2026
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

  • Automation
Riko Ishikawa
April 26, 2026May 8, 2026
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Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

  • API Development
Mateo Vargas
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

  • Automation
Riko Ishikawa
Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

  • Data Engineering
Riko Ishikawa
Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

  • Data Engineering
Priya Sharma
Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

  • Data Engineering
Priya Sharma
Master Python: Amazing Systematic Guide

Master Python: Amazing Systematic Guide

  • Data Science
Riko Ishikawa
Advanced Python Async Programming: Complete Guide to Concurrency

Advanced Python Async Programming: Complete Guide to Concurrency

  • Data Science
Riko Ishikawa
Advanced Python Async Programming: Complete Guide to Concurrency

Advanced Python Async Programming: Complete Guide to Concurrency

  • Data Science
Riko Ishikawa
Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

  • API Development
Mateo Vargas
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

  • Automation
Riko Ishikawa
Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

  • Data Engineering
Riko Ishikawa
Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

  • Data Engineering
Priya Sharma

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Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

  • API Development
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Mateo VargasMay 8, 2026May 8, 2026
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

  • Automation
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Riko IshikawaApril 26, 2026May 8, 2026
Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

  • Data Engineering
  • Data Science
Riko IshikawaApril 24, 2026
Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

  • Data Engineering
  • Data Science
Priya SharmaApril 23, 2026May 8, 2026
Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

  • AI/ML
  • Concurrency
Priya SharmaApril 20, 2026April 26, 2026
Inside CPython’s obmalloc: How the Small Object Allocator Avoids the System Heap

Inside CPython’s obmalloc: How the Small Object Allocator Avoids the System Heap

  • CPython Internals
  • Memory Management
Mateo VargasApril 20, 2026

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Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

  • API Development
  • CPython Internals
Mateo Vargas
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

  • Automation
  • Development Tools
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Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

  • Data Engineering
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Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

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Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

  • AI/ML
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Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

  • API Development
May 8, 2026May 8, 2026
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

  • Automation
April 26, 2026May 8, 2026
Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

  • Data Engineering
April 24, 2026
Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

  • Data Engineering
April 23, 2026May 8, 2026
Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

  • AI/ML
April 20, 2026April 26, 2026
Inside CPython’s obmalloc: How the Small Object Allocator Avoids the System Heap

Inside CPython’s obmalloc: How the Small Object Allocator Avoids the System Heap

  • CPython Internals
April 20, 2026

Popular News

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Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

  • API Development
  • CPython Internals
Mateo Vargas
Understand pydantic core schema compilation, the main trade-offs, and the practical checks to use before…
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

  • Automation
  • Development Tools
Riko Ishikawa
Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

  • Data Engineering
  • Data Science
Riko Ishikawa
Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

  • Data Engineering
  • Data Science
Priya Sharma
Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

  • AI/ML
  • Concurrency
Priya Sharma
Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to
17 mins read

Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to

  • API Development
May 8, 2026May 8, 2026 Mateo VargasTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

Understand pydantic core schema compilation, the main trade-offs, and the practical checks to use before relying on it in practice.

Read More
Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples
16 mins read

Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples

  • Automation
April 26, 2026May 8, 2026 Riko IshikawaTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

By Riko Ishikawa When Hypothesis catches a property violation, the failing input you eventually see in the traceback is almost never the input the.

Read More
Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins
18 mins read

Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins

  • Data Engineering
April 24, 2026 Riko IshikawaTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

If you search polars streaming engine spill today, the top result is a benchmark that OOM’d on Polars 1.6.0 in September 2024.

Read More
Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas
14 mins read

Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas

  • Data Engineering
April 23, 2026May 8, 2026 Priya SharmaTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

The pola.rs blog has a headline number that every Polars tutorial copies: the optimized lazy plan runs roughly 4x faster than the naive one on the NYC.

Read More
Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL
13 mins read

Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

  • AI/ML
April 20, 2026April 26, 2026 Priya SharmaTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

The technical barrier that kept Python’s sub-interpreter feature from being genuinely useful for a decade wasn’t parallelism — it was reference counting.

Read More
Inside CPython’s obmalloc: How the Small Object Allocator Avoids the System Heap
14 mins read

Inside CPython’s obmalloc: How the Small Object Allocator Avoids the System Heap

  • CPython Internals
April 20, 2026 Mateo VargasTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

Jump to: What exactly does obmalloc manage, and what falls through to system malloc? · How are arenas, pools, and blocks structured inside CPython?

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Django 5.2 async ORM aprefetch_related() Hit N+1 With select_related
13 mins read

Django 5.2 async ORM aprefetch_related() Hit N+1 With select_related

  • Async Programming
April 19, 2026 Priya SharmaTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

Event date: April 1, 2026 — django 5.2 Jump to Why does aprefetch_related() still fire N+1 queries under the async ORM?

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Free-Threaded Python 3.13t: Measuring Contention With perf c2c
15 mins read

Free-Threaded Python 3.13t: Measuring Contention With perf c2c

  • Concurrency
April 17, 2026April 19, 2026 Priya SharmaTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

The first time you run a threaded dict.get loop on python3.13t and watch it scale at 1.3x on 8 cores instead of 7x, the instinct is to blame Python.

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Litestar Cut Our P99 Latency 40% After Migrating From FastAPI
16 mins read

Litestar Cut Our P99 Latency 40% After Migrating From FastAPI

  • API Development
April 13, 2026April 19, 2026 Silas MontgomeryTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

In this article Why does Litestar handle tail latency better than FastAPI? What makes serialization the biggest bottleneck?

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Ruff 0.8 Replaced Black, isort, and Flake8 in Our Monorepo
14 mins read

Ruff 0.8 Replaced Black, isort, and Flake8 in Our Monorepo

  • Automation
April 11, 2026April 19, 2026 Nia OkoroTagged CPython internals, DuckDB python, Free threading, GIL removal, Ibis framework, Marimo notebooks, Mojo language, Polars dataframe, Python JIT, Rust Python

A single ruff check –fix and ruff format pair now covers what used to be three separate pre-commit hooks: Black for formatting, isort for import.

Read More

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Recent Posts

  • Inside Pydantic v2’s Core: How pydantic-core Compiles Schemas to
  • Inside Hypothesis’s Shrinker: How Pareto Minimization Finds Smaller Failing Examples
  • Inside Polars’ Streaming Engine: How Spillable Sinks Handle Larger-Than-RAM Joins
  • Inside Polars’ Lazy Query Engine: How Predicate Pushdown Beats Pandas
  • Inside CPython Sub-Interpreters: How Immortal Objects Share Memory Without the GIL

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