xeus-cling
SHOGUN
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xeus-cling | SHOGUN | |
---|---|---|
15 | 1 | |
2,945 | 3,005 | |
1.8% | 0.5% | |
4.6 | 4.8 | |
8 days ago | 4 months ago | |
C++ | C++ | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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.
xeus-cling
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Interactive GCC (igcc) is a read-eval-print loop (REPL) for C/C++
More recent activity, but based on clang: https://github.com/jupyter-xeus/xeus-cling https://github.com/root-project/cling
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TermiC: Terminal C, Interactive C/C++ REPL shell created with BASH
If you like interactive c/c++, how a look at https://github.com/jupyter-xeus/xeus-cling, that allow you to run the c/c++ repl in Jupyter, either in web interface, and terminal interfaces.
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IDE for CPP(leetcode)
There are Cpp intepreters like Cling. There are even cpp notebooks like https://github.com/jupyter-xeus/xeus-cling. If that's an "IDE" it's questionable
- How does 3[a] gives the element at index 3 in an array?
- For those defending Python and citing Jupyter notebook scripting as the reason
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Why tho?
Holy shit, its actually a thing for C++ https://github.com/jupyter-xeus/xeus-cling. Now if only there was a C version...
- Changing std:sort at Google’s Scale and Beyond
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Jupyter refuses C++
Links I tried and failed:https://github.com/jupyter-xeus/xeus-cling
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How to write multiple programs in one c file? (like we can do for python files in jupyter notebook )
Are you talking about interpreted C++? Xeus-cling is your friend (i.e., C++ interpreter).
- Turns Jupyter notebooks into standalone web applications and dashboards
SHOGUN
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Changing std:sort at Google’s Scale and Beyond
The function is trying to get the median, which is not defined for an empty set. With this particular implementation, there is an assert for that:
https://github.com/shogun-toolbox/shogun/blob/9b8d85/src/sho...
Unrelatedly, but from the same section:
> Fixes are trivial, access the nth element only after the call being made. Be careful.
Wouldn't the proper fix to do the nth_element for the larget element first (for those cases that don't do that already) and then adjust the end to be the begin + larger_n for the second nth_element call? Otherwise the second call will check [begin + larger_n, end) again for no reason at all.
What are some alternatives?
pybind11 - Seamless operability between C++11 and Python
mlpack - mlpack: a fast, header-only C++ machine learning library
jupyterlite - Wasm powered Jupyter running in the browser 💡
Caffe - Caffe: a fast open framework for deep learning.
cling - The cling C++ interpreter
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
examples - Fully-working mlpack example programs
Dlib - A toolkit for making real world machine learning and data analysis applications in C++
Pluto.jl - 🎈 Simple reactive notebooks for Julia
vowpal_wabbit - Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
sanitizers - AddressSanitizer, ThreadSanitizer, MemorySanitizer
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow