--- title: "What is (was?) GIL in Python?" url: https://daily.dev/posts/what-is-was-gil-in-python--texla9ifz source_url: https://blog.dailydoseofds.com/p/what-is-was-gil-in-python-d13 type: article source: "Daily Dose of Data Science | Avi Chawla | Substack" published: 2026-08-20T22:39:56.174Z updated: 2026-08-20T23:07:44.840Z tags: ["python", "rag"] reading_time: 10 upvotes: 0 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # What is (was?) GIL in Python? **[Daily Dose of Data Science \| Avi Chawla \| Substack](https://daily.dev/sources/dailydoseofds)** · 10 min read · 0 upvotes · 0 comments ## Summary A newsletter covering three separate topics: a visual explainer of combining RAG with Cache-Augmented Generation (CAG) using KV-memory caching and the CacheBlend technique from the open-source LMCache project; a deep dive into Python's Global Interpreter Lock (GIL), explaining why it exists, how it affects multi-threading versus multi-processing, and noting that Python 3.14 allows disabling the GIL for the first time; and an explainer of contrastive learning using Siamese networks illustrated through a face-unlock system example. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is the Global Interpreter Lock (GIL) in Python and why does it exist? The GIL is a mechanism in Python that restricts a process to running only one thread at a time, preventing multiple CPU cores from being used simultaneously by threads in the same process. It exists mainly for thread safety, since threads share memory and running them concurrently without a lock can cause race conditions when multiple threads modify the same data, producing different results depending on execution order. _Developers optimizing concurrent Python code can follow GIL-related changes and workarounds on daily.dev._ ### Can Python run without the GIL, and starting with which version? Yes, Python 3.14 allows disabling the GIL for the first time, letting a process fully utilize all CPU cores for multi-threaded workloads. Before this, multi-threaded CPU-bound Python code performed similarly to single-threaded code because only one thread could execute at a time, and multi-processing was the common workaround despite the added complexity of inter-process communication. _Teams planning to adopt free-threaded Python track version-specific changes like this via daily.dev._ ### Why doesn't multi-threading speed up CPU-bound Python code even with multiple threads? Multi-threading does not speed up CPU-bound Python code because the GIL only lets one thread run at a time within a process, so multiple threads executing a CPU-bound function take roughly the same time as running them sequentially, for example 0.432 seconds single-threaded versus 0.428 seconds multi-threaded. Multi-processing avoids this since each process gets its own interpreter and GIL, allowing true parallel execution across CPU cores. _Developers debugging slow multi-threaded Python performance can dig into concurrency explainers on daily.dev._ ## Similar posts on daily.dev - [What is \(was?\) GIL in Python?](https://daily.dev/posts/what-is-was-gil-in-python--nycowwdtu) · Daily Dose of Data Science \| Avi Chawla \| Substack · 2 upvotes · 0 comments - [What is \(was?\) GIL in Python?](https://daily.dev/posts/what-is-was-gil-in-python--t7r6chiip) · Daily Dose of Data Science \| Avi Chawla \| Substack · 2 upvotes · 0 comments - [Understanding Python’s Global Interpreter Lock \(GIL\): Explained Simply](https://daily.dev/posts/understanding-python-s-global-interpreter-lock-gil-explained-simply-zsdzigje6) · Medium · 0 upvotes · 0 comments --- Tags: [#python](https://daily.dev/tags/python), [#rag](https://daily.dev/tags/rag) [View this post on daily.dev](https://daily.dev/posts/what-is-was-gil-in-python--texla9ifz)