What's the difference between conda skeleton and conda install? - python

Following this tutorial conda skeleton should be used for installing non r-essential R packages. however this hasn't worked for me. However after searching online this post suggests to use conda install -c r r-packagename which worked for me. So what is the difference between conda skeketon and conda install?

The skeleton command is used to jump-start the building of your own package. The install command is for installing someone else's package (or one that you previously finished.)

Related

Current working method to install zipline? tried everything

Hey im trying to install zipline on Python but nothing works
I already tried it with Python 3.7 but it fails at the following libaries bcolz
lru dict
bottleneck
cyordereddict
(and zipline itself)
I tried it with Python 3.5 as recommended in this guide (https://pythonprogramming.net/zipline-local-install-python-programming-for-finance/)
same results.
I tried it creating an anaconda environment with pyhton 3.5 ... again same results.
the only thing that "worked was installing it without dependencies, but then i would have to install trading-calendars and some other libaries (which also didnt work to install):
pip install --no-deps zipline-1.3.0-cp37-cp37m-win_amd64.whl
Could somebody tell me a current working method on installing zipline?
zipline is as of now, not compatible with python version > 3.5 and is very specific to versions of dependent packages. Most of these packages has new versions.
https://github.com/quantopian/zipline/issues/2514
Best method would be to install with conda.
Once you had installed Anaconda/Miniconda you need to downgrade it to 4.6.11, below commands may help.
conda config --set allow_conda_downgrades true
conda install conda=4.6.11
conda create -n env_zipline python=3.5
activate env_zipline
conda install -c Quantopian zipline
To install zipline simply run in your new virtual env:
pip install -e git://github.com/shlomikushchi/zipline-trader.git#egg=zipline-trader
For more info:
Check Docs
Edit on GitHub
Lear from video tutorial
Read blog - Linear Regression For a Momentum Based Trading Strategy Using Zipline Trader
Chat on Slack

Conda create is stuck at "solving package specifications"

I'm trying to create a Python 2.7 virtual environment with Anaconda so I can download some packages that are not compatible with Python 3.4. I'm working in Conda version 4.2.13.
When I type the command conda create -n chemistry python=2.7 anaconda the whole thing freezes at the solving package specifications stage.
Does anyone know what causes this or how I can go about fixing it?
Today I faced the same snag. It got fixed after updating my Anaconda Navigator.
Updating your Anaconda Navigator may fix your issue, too.
Try this:
conda create -n chemistry python=2.7
The initial command you use will try to install a package named anaconda. If you want to specify the channel when installing packages,you can add -c <channel>.For example:
conda install -c conda-forge tqdm
Had same issue while I was trying to install some packages. I tried updating python then all seemed working. Try it out
conda install python

How do I go about installing packages into Anaconda?

I've been looking everywhere and cannot find a robust explanation.
I'm brand new to Python, coming from R. I had no issues installing packages there but I'm finding it to be rather confusing in Python.
So, I'm using Anaconda and I want to install this package into Python. It mentions using the conda install -c https://conda.anaconda.org/amueller wordcloud command but I have no idea where I'm supposed to run it.
Any advice would be much appreciated.
If you can't find a package with a simple conda search from the command line, run a search on the Anaconda website.
In your case, you'll find that the contributor amueller has his own channel and the package wordcloud is available.
Just run conda install -c amueller wordcloud=1.2.1 to install it.
You might want to create a separate environment using conda create first.
Run it from command line. You can directly install using pip as mentioned in the link. Don't forget to install the pre-requisite packages.
pip install wordcloud
If you are using windows, make sure your environmental path is set so that you can use the pip command directly from windows command prompt. Usually the environmental variable is updated when you install Anaconda distribution.
Conda is just another command which you can use to install packages. Procedure is exactly the same.
You may install packages from interface
Interface

How to install R packages that are not available in "R-essentials"?

I use an out-of-the-box Anaconda installation to work with Python. Now I have read that it is possible to also "include" the R world within this installation and to use the IR kernel within the Jupyter/Ipython notebook.
I found the command to install a number of famous R packages:
conda install -c r r-essentials
My beginner's question:
How do I install R packages that are not included in the R-essential package? For example R packages that are available on CRAN. "pip" works only for PyPI Python packages, doesn't it?
Now I have found the documentation:
This is the documentation that explains how to generate R packages that are only available in the CRAN repository:
https://www.continuum.io/content/conda-data-science
Go to the section "Building a conda R package".
(Hint: As long as the R package is available under anaconda.org use this resource. See here: https://www.continuum.io/blog/developer/jupyter-and-conda-r)
alistaire's answer is another possibility to add R packages:
If you install packages from inside of R via the regular install.packages (from CRAN mirrors), or devtools::install_github (from GitHub), they work fine. #alistaire
How to do this:
Open your (independent) R installation, then run the following command:
install.packages("png", "/home/user/anaconda3/lib/R/library")
to add new package to the correct R library used by Jupyter, otherwise the package will be installed in /home/user/R/i686-pc-linux-gnu-library/3.2/png/libs mentioned in .libPaths() .
To install other R Packages on Jupyter beyond R-essentials
install.packages('readr', repos='http://cran.us.r-project.org')
One issue is that the specific repository is the US.R-Project (as below). I tried others and it did not work.
N.B. Replace readr with any desired package name to install.
Here's a conda-centric answer. It builds on Frank's answer and the continuum website: https://www.continuum.io/content/conda-data-science with a bit more detail.
Some packages not available in r-essentials are still available on conda channels, in that case, it's simple:
conda config --add channels r
conda install r-readxl
If you need to build a package and install using conda:
conda skeleton cran r-xgboost
conda build r-xgboost
conda install --use-local r-xgboost
that last line is absent in the continuum website because they assume it gets published to anaconda repository first. Without it, nothing will be put in the envs/ directory and the package won't be accessible to commandline R or Jupyter.
On a mac, I found it important to install the Clang compiler for package builds:
conda install clangxx_oxs-64
I found an easy workaround. I suppose that you have an RStudio IDE for you R. It is weird to use RStudio for that, but I tried straight from R in my terminal and it didn't work. So, in RStudio console, just do the usual adding the path to your anaconda directory (in OSX,'/Users/yourusernamehere/anaconda/lib/R/library')
So, for example,
install.packages('package','/Users/yourusernamehere/anaconda/lib/R/library')
I feel ashamed to post such a non-fancy answer, but that is the only one that worked for me.
Adding it here so other beginners already working with Jupyter notebooks with Python and interested in using it with R: additional packages available for Anaconda can be installed via terminal using the same command used to instal the essential packages.
Install r-essentials
conda install -c r r-essentials
Install microbenchmark (infrastructure to accurately measure and compare the execution time of R expressions)
conda install -c r r-microbenchmark
To install a CRAN package from the command line:
R --slave -e "install.packages('missing-package', repos='http://cran.us.r-project.org')"
I had a problem when trying to install package from github using install_github("user/package") in conda with r-essentials. Errors were multiple and not descriptive.
Was able to resolve a problem using these steps:
download and unzip the package locally
activate correct conda environment (if required)
run R from command line
library(devtools)
install('/path/to/unzipped-package')
Command failed due to missing dependancies, but now I know what's missing!
run install.packages('missing-package', repos='http://cran.us.r-project.org') for all dependancies
run install('/path/to/unzipped-package') again. Now it should work!
Use Conda Forge
Five years out from the original question, I'd assert that a more contemporary solution would simply be: use Conda Forge. The Conda Forge channel not only provides broader coverage of CRAN, but also has a simple procedure and great turnaround time (typically under 24 hours) for adding a missing CRAN package to the channel.
Start from Conda Forge
I'd recommend using Conda Forge for the full stack, and use a dedicated environment for each R version you require.
conda create -n r41 -c conda-forge r-base=4.1 r-irkernel ...
where ... is whatever additional packages you require (like r-tidyverse). The r-irkernel package is optional, but included here because OP mentions using R in Jupyter.
If your environment with Jupyter (which should be in a separate environment) also has nb_conda_kernels installed, then this environment will automatically be discovered by Jupyter.
Install from Conda Forge
Generally, all R packages on CRAN have a r- prefix to the package name on Conda Forge. So, if your package of interest is pkgname, first try
conda install -n r41 -c conda-forge r-pkgname
If the package is not available, then proceed to either add it or request it.
Submit a CRAN package with Conda R Skeleton Helper
There is a helpful script collection, called conda_r_skeleton_helper for creating new Conda Forge recipes for CRAN packages. There are clear directions in the README.
In broad strokes, one will
clone the conda_r_skeleton_helper repository
edit the packages.txt file to include r-pkgname
run the script to generate the recipe
fork and clone the conda-forge/staged-recipes
copy the new recipe folder to the stage-recipes/recipes folder
commit changes, push to the fork, then submit a Pull Request back to Conda Forge
This takes maybe ~15 mins of work. Once submitted, most packages take under 24 hours to get accepted, feedstocked, and deployed to the Conda Forge channel. Once the feedstock is up and running, the Conda Forge infrastructure uses a bot to auto-detect version updates, generate new pull requests, and even auto-merge Pull Requests that successfully build. That is, maintainers have a very minimal workload, and if there are issues, a team is available to help out.
File a Package Request
For users uncomfortable with creating and maintaining a Conda Forge build, packages can be requested on Conda Forge's staged-recipes repository by filing a new Issue. There is a template for Package Request, that includes some information fields to be filled in.
Install rpy2 with conda and add following line in your Jupyter notebook.
%load_ext rpy2.ipython
In next chunks, you can simply run any r code by specifying %R
Below is my favorite method to install and/or load r package
%R if (!require("pacman")) install.packages("pacman")
%R pacman::p_load(dplyr, data.table, package3, package4)
p_load argument will install + load the package if it's not in your lib else it will simply load it.
Someone suggested a not so elegant way around it, but actually it doesn't matter as long as it works fine.
install.packages('package','/Users/yourusernamehere/anaconda/lib/R/library')
I spent almost an entire morning looking for an answer to this problem. I was able to install the libraries on RStudio but not on Jupyter Notebook (they have different versions of R) The above solution "almost" worked, it's just that I found the Jupyter Notebook was trying to install in a different directory, and it will report what directory. So I only changed that and it worked as a charm... thanks to Dninhos
What worked for me is install.packages("package_name", type="binary").
None of the other answers have worked.

How can I add a repository to conda

I am trying to install python-qutip to run on IPython notebook, which I have configured to run using the conda path variables . Qutip is an extremely popular (and useful) open-source package to simulate open quantum suystems.
With
conda install python-qutip
or
pip-install python-qutip
I get Error: No packages found matching: python-qutip (as expected). Same thing with
pip install python-qutip
As a quick 'n dirty solution, Is there some way to add the jrjohansson/qutip-releases repository to my conda library?
Alternatively, is it possible to install manually as in: sudo python setup.py install and add the installation directory to the conda path?
I figure you've probably solved this at this point but for any wandering search-engine travelers:
In addition to specifying a channel for a singular install, anaconda's docs give this method for adding a channel to your user's conda config(with conda>=4.1):
conda config --add channels new_channel
You can also see the channels you currently have added in ~/.condarc or by running conda config --show
For this particular case, you might do something like:
conda config --add channels jrjohansson
conda install python-qutip
If you're installing packages from a particular channel frequently(e.g. from conda-forge), this can be pretty useful.
Hope it helps :)
If you search anaconda.com you find the following:
Using binstar api site https://api.anaconda.org
Name: qutip
Summary: QuTiP: The Quantum Toolbox in Python
Access: public
Package Types: conda
Versions:
+ 3.0.1
+ 3.0.0
+ 3.1.0
To install this package with conda run:
conda install --channel https://conda.anaconda.org/jrjohansson qutip
The last line works for me (OpenSuse 13.1, miniconda).
I think the easiest way to install qutip is the following
pip install qutip
This worked for me.
(It could be pip3 install qutip instead.)
Assuming you have conda-build installed, you can try building the conda recipe (currently on a fork):
git clone https://github.com/jrjohansson/conda-recipes.git
cd conda-recipes
conda build qutip
conda install --use-local qutip
Didn't work for my env (ubuntu saucy) but I didn't try too hard. Maybe it will work for you!

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