I am following the instructions here to install packages (I'm looking at the "Simple Installation") section: https://rstudio.github.io/reticulate/articles/python_packages.html
Here is my R code:
library(reticulate)
use_python(python="C:\\Users\\...\\AppData\\Local\\Programs\\Python\\Python39\\python.exe")
py_install("pandas")
However, I'm getting the following error:
Error: could not find a Python environment for
C:/Users/.../AppData/Local/Programs/Python/Python39/python.exe
How do I resolve this? I have used py_install() this way on another computer before, so I know it's possible and I would like to use it. However, I can't understand what I'm missing.
You might respond that I need to specify an environment when using py_install(), but the instructions in the link don't require that, and I know it can be done without specifying an environment every time. Do I need to somehow set a "default"?
EDIT: Just to clarify, I am on Windows.
You may not be connected to the proper environment. Depending on your OS, you will likely have to create a .Renviron file and direct R to look for it.
This post here, should help you diagnose the issue:
Unable to change Python path in reticulate
Related
I am a beginner with using Julia and I am trying to use the packages. However, when I try to use the packagegs Excelfiles, plots and JuMP. I use this code for the packages:
Pkg.add("JuMP")
using JuMP
I get the error: ERROR: Failed to precompile JuMP [4076af6c-e467-56ae-b986-b466b2749572] to C:\Users\yobbi.julia\compiled\v1.7\JuMP\jl_39BC.tmp. I already updated the packages, restarted my laptop, and downloaded Julia again but I keep getting this error. Can someone help me out? Thanks!
Try:
using Pkg
pkg"build JuMP"
This will either resolve your problem or show you errors in the package build process.
Please also note that "reinstalling" Julia usually not helps as Julia is keeping its files in the .julia folder.
Finally, your folder C:\Users\yobbi.julia looks fishy to me. Maybe it is a typo and it should be C:\Users\yobbi\.julia or you managed to misconfigure something with the JULIA_DEPOT_PATH variable.
I've searched for tutorials to help configure the package in my PC, and I've found this one: https://www.youtube.com/watch?v=_fDhRL_LBdQ
I executed every part of the code interactively with the tutorial, but when I run ee_install() (after installing miniconda with py_discover_config() and other packages previously, such as reticulate), but it keeps me returning an error saying that anaconda is mandatory for the package since I'm a windows user.
Here is the error I get:
Error in ee_install_set_pyenv_env(py_env = py_env, py_path = python_path, : Windows users must install miniconda/anaconda to use rgee. The use of a Python environment is mandatory.
I've just installed Anaconda (full version with navigator) and I set a new python environment called "py2r" and tried to use the function ee_install_set_pyenv(), passing the path to the environment created through Anaconda Navigator (which has a python.exe) as paremeter to py_path and the name "py2r" as paremeter for py_env arg. And yet, it didn't work.
What am I missing?
In case you want to take a look at the code, I can provide it, but I don't think it's necessary because is a simple test script that follows as I described.
Thanks for your attention and congratulations for the library, it will be very usefull for me at work!
I fixed the ee_install() problems bypassing them and doing every passage manually. It will require no more then 10 mins and you will probably fix the installation problems. You can find and follow the manual installation with this tutorial:
https://www.youtube.com/watch?v=1-k6wNL2hlo
I tried to run a Python script from R with:
system('python script.py arg1 arg2')
And got an error:
ImportError: No module named pandas
This was a bit of a surprise since the script was working from the terminal as expected. Having encountered this type of issue before (with knitr, whence the engine.path chunk option), I know to check:
Sys.which('python')
# python
# "/usr/bin/python"
And compare it to the command line:
$ which python
# /Users/michael.chirico/anaconda2/bin/python
(i.e., the error arises because I have pandas installed for the anaconda distribution, though TBH I don't know why I have a different distribution)
Hence I can fix my issue by running:
system('/Users/michael.chirico/anaconda2/bin/python script.py arg1 arg2')
My question is two-fold:
How does R's system/Sys.which find a different python than my terminal?
How can I fix this besides writing out the full binary path each time?
I read ?Sys.which for some hints, but to no avail. In particular, ?Sys.which suggests Sys.which is using which:
This is an interface to the system command which
This is clearly (?) untrue; to be sure, I checked Sys.which('which') and which which to confirm both are pointing to /usr/bin/which (goaded on by this tidbit):
On a Unix-alike the full path to which (usually /usr/bin/which) is found when R is installed.
To the latter, on a whim I tried Sys.setenv(python = '/Users/michael.chirico/anaconda2/bin/python') to no avail.
As some of the comments hint, this is a problem that arises because the PATH environment variable is different for programs launched by Finder (or the Dock) than it is in the Terminal. There are ways to set the PATH for Dock-launched applications, but they aren't pretty. Here's a place to start looking if you want to go that route:
https://apple.stackexchange.com/questions/51677/how-to-set-path-for-finder-launched-applications
The other thing you can do, which is probably more straightforward, is tell R to set the PATH variable when it starts up, using Sys.setenv to add the path to your desired Python instance. You can do that for just one project, for your whole user account, or for the whole system, by placing the command in a .Rprofile file in the corresponding location. More information on how to do this here:
https://stat.ethz.ch/R-manual/R-devel/library/base/html/Startup.html
I have installed an R package but, in order to load it via library, the LD_LIBRARY_PATH needs to be set to the path where one of the libraries, called libhts.so.2 is located. The loading only works when editing the LD_LIBRARY_PATH before going into R, not after.
I have tried several different methods in solving this:
exporting a modified LD_LIBRARY_PATH from the configure script located in the R package.
Creating a soft link to the shared library within the same configure script.
Both have not worked and it seems to me that there is a variable that stores the results of the LD_LIBRARY_PATH once R is started. Maybe the solution is editing that variable.
With help from Hans Lub, the way to solve the problem is by using the dyn.load() function and supplying the full path to the library:
dyn.load('path_to_library')
and then, loading via library should work.
I'd like to profile functions in an installed R package (data.table) using Rprof() with line.profiling=TRUE. Normally, installed package are byte compiled, and line numbers are not available for byte compiled packages. The usual instructions for line profiling with Rprof() require using source() or eval(parse()) so that srcref attributes are present.
How can I load data.table so that line numbers are active? My naive attempts to first load the package with library(data.table) and then source('data.table.R') fails because some of the compiled C functions are not found when I attempt to use the package, presumably because library() is using a different namespace. Maybe there is some way to source() into the correct namespace?
Alternatively, perhaps I can build a modified version of data.table that is not byte compiled, and then load that in a way that keeps line numbers? What alterations would I have to make, and how would I then load it? I started by setting ByteCompile: FALSE and then trying R CMD INSTALL -l ~/R/lib --build data.table, but this still seems to be byte compiled.
I'm eager to make this work and will pursue any suggestions. I'm running R 3.2.1 on Linux, have full control over the machine, and can install anything else that is required.
Edit:
A more complete description of the problem I was trying to solve (and the solution for it) is here: https://github.com/Rdatatable/data.table/issues/1249
I ended up doing essentially what Joshua suggested: recompile the package with "KeepSource: TRUE" in the DESCRIPTION. For my purposes, I also found "ByteCompile: FALSE" to be helpful, although this might not apply generally. I also changed the version number so I could see that I was using my modified version.
Then I installed to a different location with "R CMD INSTALL data.table -l ~/R/lib", and loaded with "library(data.table, lib='~/R/lib')". When used with the patches given in the link, I got the line numbers of the allocations as I desired. But if anyone knows a solution that doesn't require recompilation, I'm sure that others would appreciate if you shared.
You should be able to get line numbers even if the package is byte-compiled. But, as it says in ?Rprof (emphasis added):
Individual statements will be recorded in the profile log if
line.profiling is TRUE, and if the code being executed was
parsed with source references. See parse for a discussion of
source references. By default the statement locations are not
shown in summaryRprof, but see that help page for options to
enable the display.
That means you need to set KeepSource: TRUE either in the DESCRIPTION file or via the --with-keep.source argument to R CMD INSTALL.