pytype
Folly
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pytype | Folly | |
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20 | 88 | |
4,520 | 26,949 | |
1.0% | 1.0% | |
9.7 | 9.8 | |
about 21 hours ago | about 8 hours ago | |
Python | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pytype
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Enhance Your Project Quality with These Top Python Libraries
Pytype checks and infers types for your Python code - without requiring type annotations. Pytype can catch type errors in your Python code before you even run it.
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
Pyre from Meta, pyright from Microsoft and PyType from Google provide additional assistance. They can 'infer' types based on code flow and existing types within the code.
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Mypy 1.6 Released
we've written a little bit about what pytype does differently here: https://google.github.io/pytype/
our main focus is to be able to work with unannotated and partially-annotated code, and treat it on par with fully annotated code.
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Writing Python like it's Rust
What is the smart money doing for type checking in Python? I've used mypy which seems to work well but is incredibly slow (3-4s to update linting after I change code). I've tried pylance type checking in VS Code, which seems to work well + fast but is less clear and comprehensive than mypy. I've also seen projects like pytype [1] and pyre [2] used by Google/Meta, but people say those tools don't really make sense to use unless you're an engineer for those companies.
Am just curious if mypy is really the best option right now?
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The Python Paradox
Check out https://github.com/google/pytype
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Forma: An efficient vector-graphics renderer
i work on https://github.com/google/pytype which is largely developed internally and then pushed to github every few days. the github commits are associated with the team's personal github accounts. pytype is not an "official google product" insofar as the open source version is presented as is without official google support, but it is "production code" in the sense that it is very much used extensively within google.
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Ruff – an fast Python Linter written in Rust
pytype dev here - thanks for the kind words :) whole-program analysis on unannotated or partially-annotated code is our particular focus, but there's surprisingly little dark PLT magic involved; in particular you don't need to be an academic type theory wizard to understand how it works. our developer docs[1] have more info, but at a high level we have an interpreter that virtually executes python bytecode, tracking types where the cpython interpreter would have tracked values.
it's worth exploring some of the other type checkers as well, since they make different tradeoffs - in particular, microsoft's pyright[2] (written in typescript!) can run incrementally within vscode, and tends to add new and experimentally proposed typing PEPs faster than we do.
[1] https://github.com/google/pytype/blob/main/docs/developers/i...
- A Python-compatible statically typed language erg-lang/erg
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mypy alternatives - pytype and pyright
3 projects | 30 Oct 2021
another library to check typing in python code (by google)
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Type Checkers: which one you use and why?
The main ones I can think about are: * mypy * pytype * pyright
Folly
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A lock-free ring-buffer with contiguous reservations (2019)
My interpretation is that with release semantics for the store, the 2nd read (load) in Thread 1 is actually allowed to be reordered before the release store to the hazard pointer. But they are not very explicit about it.
> So if thread 2 removing the pointer happens first, thread 1 will see a different value on its second read and not attempt to dereference it.
Thread 1 will see thread 2's remove even with release semantics for that store -- the store has a data dependency on the first load; they cannot be reordered.
> If thread 1 writes to its hazard pointer first, the garbage collector is guaranteed to see that value and not delete the node.
Yeah, this must be it. Thread 1 fails to notice the GC happened while it was writing its HP because its second load actually happened before the HP store.
Folly's hazard pointer implementation uses a release store to update the hazard pointer (here: reset_protection()), but uses some sort of SeqCst barrier between the store and the 2nd load (with acquire semantics): https://github.com/facebook/folly/blob/main/folly/synchroniz...
To set a HP on Linux, Folly just does a relaxed load of the src pointer, release store of the HP, compiler-only barrier, and acquire load. (This prevents the compiler from reordering the 2nd load before the store, right? But to my understanding does not prevent a hypothetical CPU reordering of the 2nd load before the store, which seems potentially problematic!)
Then on the GC/reclaim side of things, after protected object pointers are stored, it does a more expensive barrier[0] before acquire-loading the HPs.
I'll admit, I am not confident I understand why this works. I mean, even on x86, loads can be reordered before earlier program-order stores. So it seems like the 2nd check on the protection side could be ineffective. (The non-Linux portable version just uses an atomic_thread_fence SeqCst on both sides, which seems more obviously correct.) And if they don't need the 2nd load on Linux, I'm unclear on why they do it.
[0]: https://github.com/facebook/folly/blob/main/folly/synchroniz...
(This uses either mprotect to force a TLB flush in process-relevant CPUs, or the newer Linux membarrier syscall if available.)
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Appending to an std:string character-by-character: how does the capacity grow?
folly provides functions to resize std::string & std::vector without initialization [0].
[0] https://github.com/facebook/folly/blob/3c8829785e3ce86cb821c...
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A Compressed Indexable Bitset
> How is that relevant?
Roaring bitmaps and similar data structures get their speed from decoding together consecutive groups of elements, so if you do sequential decoding or decode a large fraction of the list you get excellent performance.
EF instead excels at random skipping, so if you visit a small fraction of the list you generally get better performance. This is why it works so well for inverted indexes, as generally the queries are very selective (otherwise why do you need an index?) and if you have good intersection algorithms you can skip a large fraction of documents.
I didn't follow the rest of your comment, select is what EF is good at, every other data structure needs a lot more scanning once you land on the right chunk. With BMI2 you can also use the PDEP instruction to accelerate the final select on a 64-bit block: https://github.com/facebook/folly/blob/main/folly/experiment...
The EF core algorithm implemented in folly [3] may be a bit faster, and implementing partitioning on top of that is relatively easy.
It would definitely compress much better than roaring bitmaps. In terms of performance, it depends on the access patterns. If very sparse (large jumps) PEF would likely be faster, if dense (visit a large fraction of the bitmap) it'd be slower.
It is possible to squeeze a bit more compression out of PEF by introducing a chunk type for Elias-Fano of the chunk complement (for very dense chunks), but you lose the operation of skipping to a given position, which is however not needed in inverted indexes (you only need to skip past a given id, and that can be supported efficiently). That is not mentioned in the paper because at the time I thought the skip-to-position operation was a non-negotiable.
[1] https://github.com/ot/ds2i/
[2] https://github.com/pisa-engine/pisa
[3] https://github.com/facebook/folly/blob/main/folly/experiment...
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How a Single Line of Code Made a 24-Core Server Slower Than a Laptop
Can't speak for abseil and tbb, but in folly there are a few solutions for the common problem of sharing state between a writer that updates it very infrequently and concurrent readers that read it very frequently (typical use case is configs).
The most performant solutions are RCU (https://github.com/facebook/folly/blob/main/folly/synchroniz...) and hazard pointers (https://github.com/facebook/folly/blob/main/folly/synchroniz...), but they're not quite as easy to use as a shared_ptr [1].
Then there is simil-shared_ptr implemented with thread-local counters (https://github.com/facebook/folly/blob/main/folly/experiment...).
If you absolutely need a std::shared_ptr (which can be the case if you're working with pre-existing interfaces) there is CoreCachedSharedPtr (https://github.com/facebook/folly/blob/main/folly/concurrenc...), which uses an aliasing trick to transparently maintain per-core reference counts, and scales linearly, but it works only when acquiring the shared_ptr, any subsequent copies of that would still cause contention if passed around in threads.
[1] Google has a proposal to make a smart pointer based on RCU/hazptr, but I'm not a fan of it because generally RCU/hazptr guards need to be released in the same thread that acquired them, and hiding them in a freely movable object looks like a recipe for disaster to me, especially if paired with coroutines https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p05...
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Ask HN: What are some of the most elegant codebases in your favorite language?
Not sure if it's still the case but about 6 years ago Facebook's folly C++ library was something I'd point to for my junior engineers to get a sense of "good" C++ https://github.com/facebook/folly
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DynaMix 2.0.0 Released
https://github.com/facebook/folly/blob/master/folly/docs/Poly.md Folly.Poly
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Deduplicating a Slice in Go
Most modern hash map designs don't do this weird shuffle with buckets and linked lists because pointer chasing is super expensive.
https://doc.rust-lang.org/std/collections/struct.HashMap.htm...
Because it's documenting the actual API in the standard this even spells out that the result has "at least the specified capacity"
https://github.com/facebook/folly/blob/main/folly/container/...
F14 is a linear map but I couldn't immediately find actual API documentation, however it should have the same property where if you ask for an F14 with specific capacity or you reserve enough capacity, that's an "at least" promise not an approximate one.
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rust-like traits on plain C++ with short macro (type erasure actually)
Or dyno or Poly or Not-Actually-Boost.TE or ...
What are some alternatives?
abseil-cpp - Abseil Common Libraries (C++)
Boost - Super-project for modularized Boost
mypy - Optional static typing for Python
Seastar - High performance server-side application framework
pyright - Static Type Checker for Python
parallel-hashmap - A family of header-only, very fast and memory-friendly hashmap and btree containers.
EASTL - Obsolete repo, please go to: https://github.com/electronicarts/EASTL
pyre-check - Performant type-checking for python.
Qt - Qt Base (Core, Gui, Widgets, Network, ...)
OpenFrameworks - openFrameworks is a community-developed cross platform toolkit for creative coding in C++.
cppcoro - A library of C++ coroutine abstractions for the coroutines TS
pyannotate - Auto-generate PEP-484 annotations