pybind11
Cap'n Proto
pybind11 | Cap'n Proto | |
---|---|---|
42 | 66 | |
14,800 | 11,201 | |
1.2% | 1.0% | |
8.6 | 9.2 | |
11 days ago | 3 days ago | |
C++ | C++ | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
pybind11
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Experience using crow as web server
I'm investigating using C++ to build a REST server, and would love to know of people's experiences with Crow-- or whether they would recommend something else as a "medium-level" abstraction C++ web server. As background, I started off experimenting with Python/FastAPI, which is great, but there is too much friction to translate from pybind11-exported C++ objects to the format that FastAPI expects, and, of course, there are inherent performance limitations using Python, which could impact scaling up if the project were to be successful.
- Swig – Connect C/C++ programs with high-level programming languages
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returning numpy arrays via pybind11
I have a C++ function computing a large tensor which I would like to return to Python as a NumPy array via pybind11.
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I created smooth_lines python module, great for drawing software
This is based on the Google Ink Stroke Modeler C++ library, and using pybind11 to make it available on python.
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Facial Landmark Detection with C++
pybind11 makes it easy to call C++ from Python if you want to mix.
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Python’s Multiprocessing Performance Problem
If you've never used Pybind before these pybind tests[1] and this repo[2] have good examples you can crib to get started (in addition to the docs). Once you handle passing/returning/creating the main data types (list, tuple, dict, set, numpy array) the first time, then it's mostly smooth sailing.
Pybind offers a lot of functionality, but core "good parts" I've found useful are (a) use a numpy array in Python and pass it to a C++ method to work on, (b) pass your python data structure to pybind and then do work on it in C++ (some copy overhead), and (c) Make a class/struct in C++ and expose it to Python (so no copying overhead and you can create nice cache-aware structs, etc.).
[1] https://github.com/pybind/pybind11/blob/master/tests/test_py...
- Making Python Web Application with C++ Backend
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Using pybind11 with minGW to cross compile pyhton module for Windows
I have a python module for which the logic is written in C++ and I use pybind11 to expose the objects and functions to Python.
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IPC communication between rust, c++, and python
Reading from Python requires a wrapper, using pybind11 this is fairly done.
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[ADVICE] Python to C++
Also I can highly recommend starting using C++ to augment your Python code, i.e. find the parts that are slow or undoable in Python and write those in C++ then expose them as Python functions. You can use https://github.com/pybind/pybind11 to call C++ code from Python.
Cap'n Proto
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Mysterious Moving Pointers
Yeah I pretty much only use my own alternate container implementations (from KJ[0]), which avoid these footguns, but the result is everyone complains our project is written in Kenton-Language rather than C++ and there's no Stack Overflow for it and we can't hire engineers who know how to write it... oops.
[0] https://github.com/capnproto/capnproto/blob/v2/kjdoc/tour.md
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Show HN: Comprehensive inter-process communication (IPC) toolkit in modern C++
- may massively reduce the latency involved.
Those sharing Cap'n Proto-encoded data may have particular interest. Cap'n Proto (https://capnproto.org) is fantastic at its core task - in-place serialization with zero-copy - and we wanted to make the IPC (inter-process communication) involving capnp-serialized messages be zero-copy, end-to-end.
That said, we paid equal attention to other varieties of payload; it's not limited to capnp-encoded messages. For example there is painless (<-- I hope!) zero-copy transmission of arbitrary combinations of STL-compliant native C++ data structures.
To help determine whether Flow-IPC is relevant to you we wrote an intro blog post. It works through an example, summarizes the available features, and has some performance results. https://www.linode.com/blog/open-source/flow-ipc-introductio...
Of course there's nothing wrong with going straight to the GitHub link and getting into the README and docs.
Currently Flow-IPC is for Linux. (macOS/ARM64 and Windows support could follow soon, depending on demand/contributions.)
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Condvars and atomics do not mix
FWIW, my C++ toolkit library, KJ, does the same thing.[0]
But presumably you could still write a condition predicate which looks at things which aren't actually part of the mutex-wrapped structure? Or does is the Rust type system able to enforce that the callback can only consider the mutex-wrapped value and values that are constant over the lifetime of the wait? (You need the latter e.g. if you are waiting for the mutex-wrapped value to compare equal to some local variable...)
[0] https://github.com/capnproto/capnproto/blob/e6ad6f919aeb381b...
- Cap'n'Proto: infinitely faster than Protobuf
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I don’t understand zero copy
The second one is to encode data in such a way that you can read it and operate on it directly from the buffer. You write data in a layout that is the same, or easily transformed as types in memory. To do that you usually need to encode with a known schema, only Sized types to efficiently compute fields locations as offsets in the buffer, and you usually represent pointers as offset into the encode. You can look at capnproto protocol for instance https://capnproto.org/
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OpenTF Renames Itself to OpenTofu
Worked well for Cap'n Proto (the cerealization protocol)! https://capnproto.org/
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A Critique of the Cap'n Proto Schema Language
With all due respect, you read completely wrong.
* The very first use case for which Cap'n Proto was designed was to be the protocol that Sandstorm.io used to talk between sandbox and supervisor -- an explicitly adversarial security scenario.
* The documentation explicitly calls out how implementations should manage resource exhaustion problems like deep recursion depth (stack overflow risk).
* The implementation has been fuzz-tested multiple ways, including as part of Google's oss-fuzz.
* When there are security bugs, I issue advisories like this:
https://github.com/capnproto/capnproto/tree/v2/security-advi...
* The primary aim of the entire project is to be a Capability-Based Security RPC protocol.
- Cap'n Proto: serialization/RPC system – core tools and C++ library
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Sandstorm: Open-source platform for self-hosting web app
I like how they use capability-based security [0] and use Cap'n Proto protocol. This is another technology that is slow to get broad adoption, but has many things going for when compared to e.g. Protocol Buffers (Cap'n Proto is created by the primary author of Protobuf v2, Kenton Varda).
[0] https://sandstorm.io/how-it-works#capabilities
[1] https://capnproto.org
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Flatty - flat message buffers with direct mapping to Rust types without packing/unpacking
Related but not Rust-specific: FlatBuffers, Cap'n Proto.
What are some alternatives?
PyO3 - Rust bindings for the Python interpreter
gRPC - The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
nanobind - nanobind: tiny and efficient C++/Python bindings
Protobuf - Protocol Buffers - Google's data interchange format
Optional Argument in C++ - Named Optional Arguments in C++17
FlatBuffers - FlatBuffers: Memory Efficient Serialization Library
setuptools-rust - Setuptools plugin for Rust support
ZeroMQ - ZeroMQ core engine in C++, implements ZMTP/3.1
sol2 - Sol3 (sol2 v3.0) - a C++ <-> Lua API wrapper with advanced features and top notch performance - is here, and it's great! Documentation:
Apache Thrift - Apache Thrift
PEGTL - Parsing Expression Grammar Template Library
MessagePack - MessagePack serializer implementation for Java / msgpack.org[Java]