mini conda vs anaconda - installing environments best practice question - anaconda

I'm new to miniconda and anaconda. I just wanted to get an opinion on anaconda vs miniconda in the hope of finding out what's better for my needs.
Currently i've got miniconda installed and everytime I want to work on a project I have to create a new environment inside a project folder.
Before I download and intall it I wanted to know whether if I install it, whether I would have to create an environment for each project, or will they all work at a system level.
If I have to create an environment even in anaconda, then there's no point me installing it as well.
Thanks.

Currently i've got miniconda installed and everytime I want to work on a project I have to create a new environment inside a project folder. Yes, that's basically one of the two functions of Conda, it's a good thing.
Before I download and intall it I wanted to know whether if I install it, whether I would have to create an environment for each project, or will they all work at a system level. That sounds like a bad idea!
If I have to create an environment even in anaconda, then there's no point me installing it as well. What is the point of using Conda, rather?
Take a look at some of the questions with the anaconda and conda tags, there are mountains of people encountering issues which stem from using a single environment for everything.
As for the question of Miniconda vs Anaconda, I stick to using the former, and get all my packages from the popular conda-forge channel.

Related

I have 2 versions of node installed on my coding environment and can't update the older version

I use vagrant and installed it first day of a bootcamp I took. I'm now trying to learn react but the installed version of node is too low to use npx/npm. I've tried a ton of different things, looked up different videos and I'm at a wall. I now have nodeJS version 12, and node v7 and my environment seems to just default to v7 and I can't sudo apt remove it
Well, I think there are 2 steps to resolve your issue, more or less it will help you in a long run.
Uninstall all the node installed
You can follow this guide on SO to do the removal steps: How do I completely uninstall Node.js, and reinstall from beginning (Mac OS X)
5 mentioned steps are enough to make sure your dev is clean of node.
This will revert your development back to default environment. After that, just dont install any new node like the old way you did.
Install nvm to manage node version management
Go to https://github.com/nvm-sh/nvm and follow their installation guide.
Basically this tool will help to manage your node version on your machine. You can install multi version and choose which one to work on, depend on your specific needs.
The installation guide is quite easy to follow, for some Mac OS user there might have some slight tweaks, but it's not that difficult.
Hope this help,
nvm 100% solved the issue. Was able to use it to update the one that wasnt updating, and i was able to uninstall the unused version. Unfortunately i could never get create-react-app to work. Its something to do with a node_module folder installed in my root files that i cant find and delete so it crashed every time i try to create react app. But i think i can just use cdn to create a react app so i guess its not that important, at least i have npm/npx if i need it

Install numpy in Python 2.7 without setting environment

I wanted to install numpy in python 2.7 without setting environment path. I do not know if that is possible or not but my Professor wants it like so please any advice would be appreciated.
I am not sure I understand your question correctly. You can simply delete python from your environment path. But normally this is not desirable since you then cannot call python from any directory. Better is to create a virtual environment. Or better use: anaconda. This will allow you to use various version of pythons in separate environments without any confusion or clashes between versions. You then install the respective numpy version within a specific environment. See: https://conda.io/docs/user-guide/tasks/manage-python.html
If you mean want to install numpy but you do not have the previleges then your answer can be found here: (Python) Use a library locally instead of installing it
I hope this helps. If not, then please clarify your question.

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.)
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.

Problems installing Flagmatic

I'm trying to install Flagmatic on Mac OS X Yosemite, a software package used to solve problems in extremal graph theory using the "flag algebras" developed by Razborov. I'd like to use Flagmatic to help with a research problem I'm working on, but I'm finding it very difficult to install. I'm a mathematician and while I've had some experience using Sage and Python through the Terminal I don't really know how to fix the sort of problems that I'm running into here. Here's the most up-to-date user guide so you can follow what I'm trying to do. I can broadly break down the problem as follows:
First, there is a link in the user guide to download the semidefinite programming package CSDP which Flagmatic needs in order to do some calculations. You then need to move CSDP to somewhere Flagmatic can find it, so I typed
sudo cp ~/Downloads/csdp/usr/local/bin/
into Terminal, which seemed to work. Then the user guide says by typing
csdp
into Terminal it should launch CSDP. This doesn't work - I get a permission denied message even though I typed sudo. Can anyone explain why this is happening and how to remedy it?
Secondly, when I run Sage (maths software) in the Terminal, I then want to be able to change directory to the pkg folder where there is a script called setup.py. When I run sage and type
python setup.py install
or
-python setup.py install
while in the pkg directory, I get an invalid syntax message with a pointer to the particular phrase setup.py. This is what the user guide tells you to do. If I instead try to install outside of Sage I get an error message The environment variable SAGE_ROOT must be defined. Can anyone provide some explanation and help with how to fix this?
Wow, this is somewhat dated information that they provide, since for well over a year csdp is an experimental Sage package. You should be able to just do
sage -i csdp
to install it (if you have compiler tools, which you probably do in this case). I guess the old instructions would still work but are a little brittle w.r.t. Sage.
Anyway, to the actual problem. You need to do the exact command given in the instructions:
sage -python setup.py install
However, this assumes (!) that you have a sage command in your PATH. Which you may not!
In this case, I recommend you use whatever command you use to run Sage, but instead of just typing /commmand/for/sage do /command/for/sage -python setup.py install in that directory. It will have all the right environment variables set up so that it installs in the right place, I am guessing.
Now, I'm not sure why flagmatic isn't just having themselves become an upstream package on the Sage servers, but that is a question that is harder to answer.
I might udpate the documentation in the near future. For now, however, you might want to visit this: https://github.com/jsliacan/flagmatic-2.0.git. I keep Emil's copy of Flagmatic 2.0 with updated install info. If you follow the README file, you should be fine.
I just built sage on Yosemite from source (worked fine) and then installed Flagmatic 2.0 (or Flagmatic-dev) without difficulties. It should work for you too.
I hope this helps.

Not able to install node module for SQLite 3 on Windows

Is someone aware of the steps that are necessary for installing node module for SQLite3?
Cannot see any posts/threads that clearly tell the steps.
I also need to do this without installing Visual Studio etc.
and old post, but still relevant. The sqlite3 module relies on the node-gyp module, which on windows is a pain to install. Its readme recently got updated to explain the steps required to make this work, see https://github.com/TooTallNate/node-gyp/blob/master/README.md

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