Python to be Language of 2018 According to TIOBE

According to experts, Python has become an integral part of many IT-spheres, including AI
09 January 2019   345

TIOBE experts called Python the programming language of 2018 - according to them, Python has become an integral part of many IT-spheres. It is leader of use at statistics, artificial intelligence systems development, scripts and system tests, and is still widely used in web development and scientific computing.

By the way, Python reached this peak for the third time - none of the languages ​​showed this result.

TIOBE Languages of the Year List
TIOBE Languages of the Year List

TIOBE experts summed up not only the whole year, but also the month. Returning to the top three in December, in January, Python continued to push C ++, although the last time it lost ground fairly quickly.

MATLAB changed places with Ruby: the first one rose to the 11th line, the second one dropped to 18. TypeScript took off as much as 118 points and took the 49th place. F # lost two dozen points, and Alice lost all four.

Tiobe Index Jan 2019 to Jan 2018 Compare
Tiobe Index Jan 2019 to Jan 2018 Compare

Kotlin started the year with a positive. The language has risen to 31st place, and experts believe that in 2019 it will enter the top 20.

Facebook to Release PyTorch 1.0

This release added support for large cloud platforms, a C ++ interface, a set of JIT compilers
10 December 2018   371

Facebook has released a stable version of the library for machine learning PyTorch 1.0. This iteration added support for large cloud platforms, a C ++ interface, a set of JIT compilers, and various improvements.

The stable version received a set of JIT compilers that eliminate the dependence of the code on the Python interpreter. The model code is transformed into Torch Script - a superstructure over Python. Keeping the opportunity to work with the model in the Python environment, the user can download it to other projects not related to this language. So, the PyTorch developers state that the code processed in this way can be used in the C ++ API.

The torch.distributed package and the torch.nn.parallel.DistributedDataParallel module are completely redesigned. torch.distributed now has better performance and works asynchronously with the Gloo, NCCL and MPI libraries.

The developers added a C ++ wrapper to PyTorch 1.0. It contains analogs of Python interface components, such astorch.nn,torch.optim, torch.data. According to the creators, the new interface should provide high performance for C ++ applications. True, the C ++ API is still experimental, but it can be used in projects now.

To improve the efficiency of working with PyTorch 1.0, a Torch Hub repository has been created, which stores pre-trained models of neural networks. You can publish your own development using the hubconf.py file, after which the model will be available for download by any user via the torch.hub.load API.

Support for C extensions and the module torch.utils.trainer were removed from the library.

Facebook released the preliminary version of PyTorch 1.0 at the beginning of October 2018, and in two months the developers brought the framework to a stable state.