tanlermin
Distributed scikit-learn and pandas
It can handle parallel and distributed parts for you.
I think its already a Killer general-purpose language (except for the module system).
I'm just not sure if it is good enough to unseat incumbents when there are things like rust with its deterministic memory management or python with all its momentum and compiler technology coming along.
Not sure whether to bet on it at this point.
Also apparently stackoverflow julia questions have clear exponential growth.
IronPython 3 (python for .net) development restarted
Moore Foundation provides grant for Contiuum's Python Numba and Dask Compilers
Escher: An Elm-like web framework for Julia
https://docs.continuum.io/anaconda-cluster/index https://www.continuum.io/blog/developer-blog/getting-most-ou...
Coconut: Simple, elegant, Pythonic functional programming (compiles to python)
Julia is gaining marketshare and mindshare among grad student not just due to its speed, but because it is a more fun and intuitive environment in which to code mathy stuff.
These people will in turn filter into industry and if not them, then atleast their code.
Also macros. As Julia gains more utility for run of the mill data science, Its Dplyr like DSL abilities will be very attractive.
Do you see this type system and generic function library as useful for general purpose programming as well? How would that play with mypy and type hints?
Yattag: Generate HTML and XML in a readable, concise and pythonic way
Genie: High-performance high-productivity Julia web framework
I wish we could just use mypy when we feel like making our code faster :/