CODEWITHSUNDEEP
pipanacondapython-3.5condaminiconda
Chill
Chill

Reputation: 87

Scientific Python installation recommendations

I am new to Python and starting work on a large project that will be distributed to users. I am also the first in my company to be using, and I wanted to get recommendations on the best way to install Python & packages, so that I don't head off in the wrong direction.

I require data analysis frameworks (pandas, numpy, scipy, matplotlib, statsmodels, pymongo) and my initial approach was to install Python 3.5 directly, and then use pip install on each package.

I ran into similar problems that others have found [Unable to find vcvarsall], and resolved. Next problem was with BLAS and LAPACK missing when installing scipy. At this point I decided Anaconda was the way to go, rather than individual pip installs, and was easily able to set everything up.

One problem with Anaconda is that it installs a lot of packages which I will never use, and may not have some which I would like to use in future, e.g. TensorFlow (presumably can do pip install to get extra ones that are not included?).

An in-between solution seems to be Miniconda, which I believe would have fixed the BLAS/LAPACK problem with scipy.

So my question is: can someone with experience of developing data analysis projects in Python, that will be deployed to users' Windows desktops, and with server-side components running on Linux, provide recommendation of what they would do if starting from scratch at new organization?

(I'm currently in favour of heading down the Anaconda route.)

Upvotes: 1

Views: 468

Answers (1)

Tian Zhang
Tian Zhang

Reputation: 351

Personally, I think Anaconda(conda) is better. First of all, conda is cross-platform package manager, and it is easy to install and use. Second, conda has functionality of virtualenv, and you can use conda create to create environment. Finally, there is Anaconda cloud and condo-forge, those community can help you solve conda issue, build packages, and share ideas.

Moreover, Anaconda(conda) indeed install a lot of packages, but those are all dependencies. For example, when you "conda install scikit-learn", conda will automatically help you install the dependency, numpy and spicy.

Upvotes: 1

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