Nicholas Winter
Yes, it's less portable. First of all, Python is not part of the Stata distribution (while Java is, and by the way it's currently a JRE from an OpenJDK 11 distribution, the current long term version, which is very good news). Stata relies on the installed Python, which leads to many questions:
* Is it even installed?
* Is it a Python2 or a Python3?
* Is it a Python 32 bits or a Python 64 bits? (I didn't check if 64-bit Stata requires 64-bit Python, it may)
* Which packages are installed, and which versions?
* Are extra binaries also required? (it happens with some packages)
However, IMHO:
It's not unreasonable to consider that people can install Python freely (less true in corporate/administration/university environments, but it should be doable), and can install necessary packages and keep them up to date.(*)
It's not unreasonable to consider only Python 3 as it has been here for more than a decade and all maintained data science/machine learning packages are available at least in Python 3.
There will possibly be some extra work to make Ado/Python packages run, but nothing insurmountable. For Stata it's usually as simple as ssc install, for Python it's usually just pip install.
(*) There are portable versions of Python, this can solve many issues. For instance IntelPython (based on Anaconda) which is free and comes with numpy/scipy linked with MKL.
Yes, it's less portable. First of all, Python is not part of the Stata distribution (while Java is, and by the way it's currently a JRE from an OpenJDK 11 distribution, the current long term version, which is very good news). Stata relies on the installed Python, which leads to many questions:
* Is it even installed?
* Is it a Python2 or a Python3?
* Is it a Python 32 bits or a Python 64 bits? (I didn't check if 64-bit Stata requires 64-bit Python, it may)
* Which packages are installed, and which versions?
* Are extra binaries also required? (it happens with some packages)
However, IMHO:
It's not unreasonable to consider that people can install Python freely (less true in corporate/administration/university environments, but it should be doable), and can install necessary packages and keep them up to date.(*)
It's not unreasonable to consider only Python 3 as it has been here for more than a decade and all maintained data science/machine learning packages are available at least in Python 3.
There will possibly be some extra work to make Ado/Python packages run, but nothing insurmountable. For Stata it's usually as simple as ssc install, for Python it's usually just pip install.
(*) There are portable versions of Python, this can solve many issues. For instance IntelPython (based on Anaconda) which is free and comes with numpy/scipy linked with MKL.
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