fastcore
Python supercharged for fastai development
Decision gist · record as of 2026-08-14
Yes. fastcore is actively maintained, has zero known vulnerabilities, installs with no dependencies, and is widely used in production. It's worth installing if you want to reduce boilerplate, use functional programming patterns, or need simplified parallel execution. The v2 reorganization is a breaking change if you rely on old APIs, but most users importing via `from fastcore.utils import *` will see minimal disruption.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later
- Low friction installation as a pure Python wheel.
- Actively maintained with a recent release 2 days old and no known vulnerabilities.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in commercial and open-source projects with minimal restrictions.
last release 2026-08-12 (2 days) · last repo commit 2026-08-12 · 1,100 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 46,597,030 downloads/mo, #608 on PyPI
Alternatives
Verify before relying
pip install fastcore
from fastcore.foundation import L
x = L(1, 2, 3, 4)
result = x.map(lambda o: o * 2)- Whether the async module (fastcore.aio) is suitable for production high-concurrency workloads
- Performance characteristics of the enhanced ThreadPoolExecutor and ProcessPoolExecutor compared to stdlib equivalents
What it is and what it does
fastcore is a utility library that augments Python with patterns and conveniences borrowed from other languages—functional composition, mixins, currying, and enhanced data structures. It provides a drop-in replacement for `list` called `L` with method chaining and advanced indexing, decorators like `@patch` to extend existing classes and `@delegates` to replace `**kwargs` with explicit parameters, simplified parallel execution via enhanced thread and process pools, and testing utilities like `test_eq` and `test_close` for more readable assertions.
The library is designed for safe wildcard imports and is commonly used in data science workflows. Recent v2 changes reorganized APIs—moving async utilities to a dedicated `fastcore.aio` module, replacing some list methods with composable `star` and `rstar` adapters, and requiring Python 3.10 or later. It has no runtime dependencies, making it lightweight to integrate.
Use it for
- Replace `list` with `L` for chainable operations like filtering, mapping, and indexing in data processing pipelines.
- Use `@patch` decorator to add utility methods to built-in or third-party classes without subclassing.
- Simplify `__init__` methods with `store_attr()` to reduce boilerplate attribute assignment.
- Write more readable test assertions with `test_eq`, `test_ne`, and `test_close` instead of plain `assert` statements.
- Parallelize CPU-bound tasks with the enhanced `ThreadPoolExecutor` or `ProcessPoolExecutor` for concurrent work.
- Build command-line interfaces quickly using `fastcore.script` to convert Python functions into CLI tools.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
fastcore is actively maintained, has zero known vulnerabilities, installs with no dependencies, and is widely used in production. It's worth installing if you want to reduce boilerplate, use functional programming patterns, or need simplified parallel execution. The v2 reorganization is a breaking change if you rely on old APIs, but most users importing via `from fastcore.utils import *` will see minimal disruption.
Install
fastcore on PyPI
Before you install
Low friction installation as a pure Python wheel. Actively maintained with a recent release 2 days old and no known vulnerabilities. Requires Python 3.10 or later.
Requires Python 3.10 or later
License in practice
Apache-2.0 permissive license allows use in commercial and open-source projects with minimal restrictions.
Quickstart
pip install fastcore
from fastcore.foundation import L
x = L(1, 2, 3, 4)
result = x.map(lambda o: o * 2)Verify before relying
- Whether the async module (fastcore.aio) is suitable for production high-concurrency workloads
- Performance characteristics of the enhanced ThreadPoolExecutor and ProcessPoolExecutor compared to stdlib equivalents
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 46,597,030 / month, #608 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersNatural Language :: EnglishProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: Only |
Evidence: fastcore-2.2.12-py3-none-any.whl
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