4.3 OML User Tasks for Downloading and Using an Available Conda Environment
Once user ADMIN installs the environment in Object Storage, as an OML user, you can download, activate, and use it in R paragraphs in notebooks and with embedded execution.
List all environments persisted in Object Storage
Get the list of environments saved in Object Storage using the
list-saved-envs command.
%conda
list-saved-envs Get information on a named environment persisted in Object Storage
Provide the environment name as an argument to the -e
parameter and request information on the environment.
%conda
list-saved-envs -e myrenvThe output is similar to the following:
{
"name": "myrenv",
"size": "831.5 MiB",
"description": "Install R forecast and ggplot2 packages",
"tags": {
"application": "OML4R",
"user": "OMLUSER"
},
"number_of_installed_packages": 121
}Download and activate the environment
Use the download command to download an
environment from Object Storage. To activate the downloaded
environment, use the activate command.
Note:
The paragraph that contains the download command must be the first paragraph in the notebook.%conda
download myrenv
activate myrenvDownloading conda environment myrenv
Download successful for conda environment myrenvList the packages available in the environment
Get the list of all the packages in an active environment using the
list command.
%conda
listThe output is similar to the following:
# packages in environment at /u01/.conda/envs/myrenv:
#
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_gnu conda-forge
_r-mutex 1.0.1 anacondar_1 conda-forge
binutils_impl_linux-64 2.39 h6ceecb4_0 conda-forge
bwidget 1.9.14 ha770c72_1 conda-forge
bzip2 1.0.8 h7f98852_4 conda-forge
c-ares 1.18.1 h7f98852_0 conda-forge
ca-certificates 2022.9.24 ha878542_0 conda-forge
cairo 1.16.0 ha61ee94_1014 conda-forge
curl 7.86.0 h2283fc2_1 conda-forge
expat 2.5.0 h27087fc_0 conda-forge
font-ttf-dejavu-sans-mono 2.37 hab24e00_0 conda-forge
font-ttf-inconsolata 3.000 h77eed37_0 conda-forge
font-ttf-source-code-pro 2.038 h77eed37_0 conda-forge
font-ttf-ubuntu 0.83 hab24e00_0 conda-forge
fontconfig 2.14.1 hc2a2eb6_0 conda-forge
fonts-conda-ecosystem 1 0 conda-forge
fonts-conda-forge 1 0 conda-forge
freetype 2.12.1 hca18f0e_0 conda-forge
fribidi 1.0.10 h36c2ea0_0 conda-forge
gcc_impl_linux-64 12.2.0 hcc96c02_19 conda-forge
gettext 0.21.1 h27087fc_0 conda-forge
gfortran_impl_linux-64 12.2.0 h55be85b_19 conda-forge
graphite2 1.3.13 h58526e2_1001 conda-forge
gsl 2.7 he838d99_0 conda-forge
gxx_impl_linux-64 12.2.0 hcc96c02_19 conda-forge
harfbuzz 5.3.0 h418a68e_0 conda-forge
icu 70.1 h27087fc_0 conda-forge
jpeg 9e h166bdaf_2 conda-forge
kernel-headers_linux-64 2.6.32 he073ed8_15 conda-forge
keyutils 1.6.1 h166bdaf_0 conda-forge
krb5 1.19.3 h08a2579_0 conda-forge
ld_impl_linux-64 2.39 hc81fddc_0 conda-forge
lerc 4.0.0 h27087fc_0 conda-forge
libblas 3.9.0 16_linux64_openblas conda-forge
libcblas 3.9.0 16_linux64_openblas conda-forge
libcurl 7.86.0 h2283fc2_1 conda-forge
libdeflate 1.14 h166bdaf_0 conda-forge
libedit 3.1.20191231 he28a2e2_2 conda-forge
libev 4.33 h516909a_1 conda-forge
libffi 3.4.2 h7f98852_5 conda-forge
libgcc-devel_linux-64 12.2.0 h3b97bd3_19 conda-forge
libgcc-ng 12.2.0 h65d4601_19 conda-forge
libgfortran-ng 12.2.0 h69a702a_19 conda-forge
libgfortran5 12.2.0 h337968e_19 conda-forge
libglib 2.74.1 h7a41b64_0 conda-forge
libgomp 12.2.0 h65d4601_19 conda-forge
libiconv 1.17 h166bdaf_0 conda-forge
liblapack 3.9.0 16_linux64_openblas conda-forge
libnghttp2 1.47.0 hff17c54_1 conda-forge
libopenblas 0.3.21 pthreads_h78a6416_3 conda-forge
libpng 1.6.38 h753d276_0 conda-forge
libsanitizer 12.2.0 h46fd767_19 conda-forge
libssh2 1.10.0 hf14f497_3 conda-forge
libstdcxx-devel_linux-64 12.2.0 h3b97bd3_19 conda-forge
libstdcxx-ng 12.2.0 h46fd767_19 conda-forge
libtiff 4.4.0 h55922b4_4 conda-forge
libuuid 2.32.1 h7f98852_1000 conda-forge
libwebp-base 1.2.4 h166bdaf_0 conda-forge
libxcb 1.13 h7f98852_1004 conda-forge
libxml2 2.10.3 h7463322_0 conda-forge
libzlib 1.2.13 h166bdaf_4 conda-forge
make 4.3 hd18ef5c_1 conda-forge
ncurses 6.3 h27087fc_1 conda-forge
openssl 3.0.7 h166bdaf_0 conda-forge
pango 1.50.11 h382ae3d_0 conda-forge
pcre2 10.37 hc3806b6_1 conda-forge
pixman 0.40.0 h36c2ea0_0 conda-forge
pthread-stubs 0.4 h36c2ea0_1001 conda-forge
r-backports 1.4.1 r41h06615bd_1 conda-forge
r-base 4.1.3 h7880091_3 conda-forge
r-brio 1.1.3 r41h06615bd_1 conda-forge
r-callr 3.7.3 r41hc72bb7e_0 conda-forge
r-cli 3.4.1 r41h7525677_1 conda-forge
r-colorspace 2.0_3 r41h06615bd_1 conda-forge
r-crayon 1.5.2 r41hc72bb7e_1 conda-forge
r-curl 4.3.3 r41h06615bd_1 conda-forge
r-desc 1.4.2 r41hc72bb7e_1 conda-forge
r-diffobj 0.3.5 r41h06615bd_1 conda-forge
r-digest 0.6.30 r41h7525677_0 conda-forge
r-ellipsis 0.3.2 r41h06615bd_1 conda-forge
r-evaluate 0.18 r41hc72bb7e_0 conda-forge
r-fansi 1.0.3 r41h06615bd_1 conda-forge
r-farver 2.1.1 r41h7525677_1 conda-forge
r-forecast 8.18 r41h37cf8d7_0 conda-forge
r-fracdiff 1.5_2 r41h64d53c3_0 conda-forge
r-fs 1.5.2 r41h7525677_2 conda-forge
r-generics 0.1.3 r41hc72bb7e_1 conda-forge
r-ggplot2 3.4.0 r41hc72bb7e_0 conda-forge
r-glue 1.6.2 r41h06615bd_1 conda-forge
r-gtable 0.3.1 r41hc72bb7e_1 conda-forge
r-isoband 0.2.6 r41h7525677_1 conda-forge
r-jsonlite 1.8.3 r41h06615bd_0 conda-forge
r-labeling 0.4.2 r41hc72bb7e_2 conda-forge
r-lattice 0.20_45 r41h06615bd_1 conda-forge
r-lifecycle 1.0.3 r41hc72bb7e_1 conda-forge
r-lmtest 0.9_40 r41h8da6f51_1 conda-forge
r-magrittr 2.0.3 r41h06615bd_1 conda-forge
r-mass 7.3_58.1 r41h06615bd_1 conda-forge
r-matrix 1.5_1 r41h5f7b363_0 conda-forge
r-mgcv 1.8_41 r41h5f7b363_0 conda-forge
r-munsell 0.5.0 r41hc72bb7e_1005 conda-forge
r-nlme 3.1_160 r41h8da6f51_0 conda-forge
r-nnet 7.3_18 r41h06615bd_1 conda-forge
r-pillar 1.8.1 r41hc72bb7e_1 conda-forge
r-pkgconfig 2.0.3 r41hc72bb7e_2 conda-forge
r-pkgload 1.3.1 r41hc72bb7e_0 conda-forge
r-praise 1.0.0 r41hc72bb7e_1006 conda-forge
r-processx 3.8.0 r41h06615bd_0 conda-forge
r-ps 1.7.2 r41h06615bd_0 conda-forge
r-quadprog 1.5_8 r41hd009a43_4 conda-forge
r-quantmod 0.4.20 r41hc72bb7e_1 conda-forge
r-r6 2.5.1 r41hc72bb7e_1 conda-forge
r-rcolorbrewer 1.1_3 r41h785f33e_1 conda-forge
r-rcpp 1.0.9 r41h7525677_0 conda-forge
r-rcpparmadillo 0.11.4.2.1 r41h9f5de39_0 conda-forge
r-rematch2 2.1.2 r41hc72bb7e_2 conda-forge
r-rlang 1.0.6 r41h7525677_1 conda-forge
r-rprojroot 2.0.3 r41hc72bb7e_1 conda-forge
r-scales 1.2.1 r41hc72bb7e_1 conda-forge
r-testthat 3.1.5 r41h7525677_1 conda-forge
r-tibble 3.1.8 r41h06615bd_1 conda-forge
r-timedate 4021.106 r41hc72bb7e_1 conda-forge
r-tseries 0.10_52 r41hd009a43_0 conda-forge
r-ttr 0.24.3 r41h06615bd_1 conda-forge
r-urca 1.3_3 r41h8da6f51_0 conda-forge
r-utf8 1.2.2 r41h06615bd_1 conda-forge
r-vctrs 0.5.0 r41h7525677_0 conda-forge
r-viridislite 0.4.1 r41hc72bb7e_1 conda-forge
r-waldo 0.4.0 r41hc72bb7e_1 conda-forge
r-withr 2.5.0 r41hc72bb7e_1 conda-forge
r-xts 0.12.2 r41h06615bd_0 conda-forge
r-zoo 1.8_11 r41h06615bd_1 conda-forge
readline 8.1.2 h0f457ee_0 conda-forge
sed 4.8 he412f7d_0 conda-forge
sysroot_linux-64 2.12 he073ed8_15 conda-forge
tk 8.6.12 h27826a3_0 conda-forge
tktable 2.10 hb7b940f_3 conda-forge
xorg-kbproto 1.0.7 h7f98852_1002 conda-forge
xorg-libice 1.0.10 h7f98852_0 conda-forge
xorg-libsm 1.2.3 hd9c2040_1000 conda-forge
xorg-libx11 1.7.2 h7f98852_0 conda-forge
xorg-libxau 1.0.9 h7f98852_0 conda-forge
xorg-libxdmcp 1.1.3 h7f98852_0 conda-forge
xorg-libxext 1.3.4 h7f98852_1 conda-forge
xorg-libxrender 0.9.10 h7f98852_1003 conda-forge
xorg-libxt 1.2.1 h7f98852_2 conda-forge
xorg-renderproto 0.11.1 h7f98852_1002 conda-forge
xorg-xextproto 7.3.0 h7f98852_1002 conda-forge
xorg-xproto 7.0.31 h7f98852_1007 conda-forge
xz 5.2.6 h166bdaf_0 conda-forge
zlib 1.2.13 h166bdaf_4 conda-forge
zstd 1.5.2 h6239696_4 conda-forgeExample 4-1 Use the packages in the Conda environment
The following example shows the use of the available packages in the installed and activated environment.
-
Load libraries and suppress warnings.
%r library(ggplot2) library(forecast) -
Load and prepare data.
%r data("AirPassengers") # Through the end of 1956, no months in 1957 air.train <- window(AirPassengers, end = 1956+11/12) # everything in 1957 and beyond air.test <- window(AirPassengers, start = 1957) n.test <- length(air.test) -
Fit an arima model to the data and compute performance.
%r air.model <- auto.arima(air.train) -
Create multi-step forecasts for each day
%r accuracy(air.model) air.multi.forecast <- air.model %>% forecast(h = n.test) air.multi.forecast %>% autoplot()The output is similar to the following:
Figure 4-1 Multi-step Forecasts for each Day
-
Compare performance to the test data.
%r accuracy(air.multi.forecast, x = air.test) air.multi.forecast %>% autoplot() + geom_line( aes( x = as.numeric(time(air.test)), y = as.numeric(air.test) ), col = "red" )The output of the example is the following.
Figure 4-2 Performance of Test and Training Data Set
Example 4-2 Create a function and save it to the OML4R script repository
With OML4R, functions are saved to the script repository as
strings so they can be run in embedded R execution. Create a
function multi.forecast, after verifying the
function behaves as expected, save it to the OML4R script
repository.
%r
multi.forecast <- function() {
library(forecast)
library(ggplot2)
data("AirPassengers")
air.train <- window(AirPassengers, end = 1956+11/12)
air.test <- window(AirPassengers, start = 1957)
n.test <- length(air.test)
air.model <- auto.arima(air.train)
accuracy(air.model)
air.multi.forecast <- air.model %>% forecast(h = n.test)
air.multi.forecast %>% autoplot()
res <- accuracy(air.multi.forecast, x = air.test)
print(air.multi.forecast %>%
autoplot() + geom_line(
aes(x = as.numeric(time(air.test)), y = as.numeric(air.test)), col = "red"))
return(res)}Run the user-defined function in R.
%r
multi.forecast()The output of the example is the following.
Figure 4-3 Performance of Test and Training Data Set
Run the user-defined function using the R API for embedded R execution.
%r
ore.doEval(FUN=multi.forecast, ore.graphics=TRUE)The output of the example is the following:
Figure 4-4 Performance of Test and Training Data Set
Use the ore.scriptCreate function to store a
single user-defined R function in the OML4R script repository. The
parameter "multi.forecast" is a string that
specifies the name of the user-defined function. The parameter
multi.forecast is the R function to
run.
%r
ore.scriptCreate("multi.forecast", multi.forecast, overwrite=TRUE)Use the R API for embedded R execution to run the user-defined R function you saved in the script repository. Run the user-defined function by referencing it as a named script
%r
ore.doEval(FUN.NAME="multi.forecast", ore.graphics=TRUE)The output of the example is the following:
Figure 4-5 Performance of Test and Training Data Set
Deactivate the current environment
Use the deactivate command to deactivate an
enviroment.
Note:
At a given time, only one active environment is supported. So, a newly activated environment would replace an old environment. As a best practice, deactivate an environment before logging off.%conda
deactivateConda environment deactivatedParent topic: Install third-party packages