Run Python in RMarkdown

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Knitr setting for rmarkdown export

library(reticulate)
py_config: see current python version
use_virtualenv(“py39bert”)
Enable knit_engine to use python for rmarkdown export purpose
knitr::knit_engines$set(python = reticulate::eng_python)

library(reticulate)
py_home <- py_config()
use_virtualenv(py_home$virtualenv)
knitr::knit_engines$set(python = reticulate::eng_python)

library(reticulate)
py_home <- py_config()
use_virtualenv(py_home$virtualenv)
knitr::knit_engines$set(python = reticulate::eng_python)

Install Python 3.9 on Ubuntu

Check Ubuntu version
```
lsb_release -a
```
Update packages
```
sudo apt update
sudo apt -y upgrade
```

Install python 3.9

sudo apt install python3.9
python3 -V
python3.9 -V

Install pip
```
python3.9 -m pip install --upgrade pip
```

Install virtualenv

pip3 install virtualenv
which virtualenv

Create a virtualenv using Python 3.9 named as py39bert

which python3.9
virtualenv -p /usr/bin/python3.9 py39bert

Activate the virtualenv
```
source ~/py39bert/bin/activate
```

Install ipython and jupyter notebook within virtualenv

pip3 install ipython
pip3 install jupyter notebook
jupyter notebook to start jupyter notebook

Install python packages within the virtualenv
```
pip3 install numpy
```

Install Python packages within R

Run python module within R

library(reticulate)
py_home <- py_config()
use_virtualenv(py_home$virtualenv)
## virtualenv_install(py_home$virtualenv, "feather")

os <- import("os")
os$environ['HOME']

[1] “/home/ghowoo”

os$listdir()[1:2]

[1] “flowchart.Rmd” “data_manipulation.Rmd”

Install Python packages within Python


import subprocess

def install(package):
    subprocess.check_call([sys.executable, "-m", "pip", "install", package])

# install("tabulate")

Save Data in R

library(feather)
library(data.table)
dt <- data.table(v1=1:6, v2=rep("A", 6))
write_feather(dt, "dt.feather")
list.files(pattern = "*.feather")

[1] “dt.feather”

Read feather in Python

import os
#print(os.getcwd())
path = os.getcwd()
os.chdir(path)
print(os.listdir()[0:4])
#print(os.getcwd())

[‘flowchart.Rmd’, ‘data_manipulation.Rmd’, ‘discretization.Rmd’, ‘graph.Rmd’]

import pandas as pd
# import feather
path = "dt.feather"


df = pd.read_feather(path)

from tabulate import tabulate
print(tabulate(df, tablefmt='html'))

0	1	A
1	2	A
2	3	A
3	4	A
4	5	A
5	6	A

reticulate

virtualenv_list() lists virtual environment
use_virtualenv(“virtual-environment-name”): initiate python from virtual-environment, required = TRUE check if there is the version, otherwise may search for other versions
use_python(“python path”): initiated python from path
py_config() to see version

## library(reticulate)


## Sys.setenv(RETICULATE_PYTHON = "/home/gongw/.virtualenvs/pybert/bin/python3.9")
## Sys.setenv(LD_LIBRARY_PATH = paste(
##              "/home/gongw/.virtualenvs/pybert/lib"
##            , Sys.getenv("LD_LIBRARY_PATH")
##            , sep = ":"))
## use_python("/home/gongw/.virtualenvs/pybert/bin/python3.9")

library(reticulate)
## use_python("/home/gongw/.virtualenvs/py39bert/bin/python3.9")
## use_python("/usr/bin/python3")

use_virtualenv("py39bert")

py_config()
py_discover_config()
## py_install()


## reticulate::py_config()


virtualenv_list()
## reticulate::use_python("/usr/bin/python3")
## use_virtualenv("py39bert", required = TRUE)
## py_available()

## reticulate::use_python("~/venv/pybert/bin/python3")

os <- import("os")
os$listdir(".")
sys <- import("sys")
sys$version


## py_install("pandas")
#py_install("pandas", method = "auto", conda = "auto")

python matplotlib


import sys
print(sys.version)

3.9.12 (main, Mar 24 2022, 16:20:11) [GCC 9.4.0]

import seaborn as sns
pr = sns.load_dataset("fmri")
import matplotlib as plt
sns.lmplot("timepoint", "signal", data = pr)

plt.pyplot.show()

Python print table



x = 'hello, python world!'
print(x)

hello, python world!

import numpy as np
# a = np.arange(5)

table = [['one','two','three'],['four','five','six'],['seven','eight','nine']]
from tabulate import tabulate
print(tabulate(table, tablefmt = 'html', headers = ["Column I", "Column II", "Column III"]))

Column I	Column II	Column III
one	two	three
four	five	six
seven	eight	nine

Save Python plot

To show plot in rmarkdown
```
![matplot](pythton_pyplot.png)
```


import matplotlib.pyplot as plt
fig, ax = plt.subplots( nrows=1, ncols=1 )
ax.plot([0,1,2], [10,20,3])
#ax.show()
# plt.plot([1,2,3],[3,4,5])
# plt.show()

fig.savefig("pythton_pyplot.png")
plt.close(fig)

matplot

Python Version

import sys
print(sys.version_info)

sys.version_info(major=3, minor=9, micro=12, releaselevel=‘final’, serial=0)

R sessionInfo()

sessionInfo()

R version 4.1.2 (2021-11-01) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 20.04.3 LTS

Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale: [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C

attached base packages: [1] stats graphics grDevices utils datasets methods base

other attached packages: [1] feather_0.3.5 reticulate_1.24 Wu_0.0.0.9000
[4] flexdashboard_0.5.2 lme4_1.1-27.1 Matrix_1.4-0
[7] mgcv_1.8-38 nlme_3.1-152 png_0.1-7
[10] scales_1.1.1 nnet_7.3-16 labelled_2.8.0
[13] kableExtra_1.3.4 plotly_4.9.4.1 gridExtra_2.3
[16] ggplot2_3.3.5 DT_0.18 tableone_0.13.0
[19] magrittr_2.0.1 lubridate_1.7.10 dplyr_1.0.7
[22] plyr_1.8.6 data.table_1.14.0 rmdformats_1.0.2
[25] knitr_1.36

loaded via a namespace (and not attached): [1] httr_1.4.2 sass_0.4.0 tidyr_1.1.3 jsonlite_1.7.2
[5] viridisLite_0.4.0 splines_4.1.2 here_1.0.1 bslib_0.2.5.1
[9] highr_0.9 yaml_2.2.1 pillar_1.6.4 lattice_0.20-45
[13] glue_1.5.1 digest_0.6.29 rvest_1.0.0 minqa_1.2.4
[17] colorspace_2.0-2 htmltools_0.5.2 survey_4.0 pkgconfig_2.0.3
[21] haven_2.4.1 bookdown_0.22 purrr_0.3.4 webshot_0.5.2
[25] svglite_2.0.0 tibble_3.1.6 generics_0.1.0 ellipsis_0.3.2
[29] withr_2.4.3 lazyeval_0.2.2 survival_3.2-13 crayon_1.4.2
[33] evaluate_0.14 fansi_0.5.0 MASS_7.3-54 forcats_0.5.1
[37] xml2_1.3.3 tools_4.1.2 hms_1.1.0 mitools_2.4
[41] lifecycle_1.0.1 stringr_1.4.0 munsell_0.5.0 compiler_4.1.2
[45] jquerylib_0.1.4 systemfonts_1.0.2 rlang_0.4.12 grid_4.1.2
[49] nloptr_1.2.2.2 rstudioapi_0.13 rappdirs_0.3.3 htmlwidgets_1.5.4 [53] rmarkdown_2.10 boot_1.3-28 gtable_0.3.0 DBI_1.1.1
[57] R6_2.5.0 fastmap_1.1.0 utf8_1.2.2 rprojroot_2.0.2
[61] stringi_1.7.6 Rcpp_1.0.7 vctrs_0.3.8 tidyselect_1.1.1 [65] xfun_0.28