# -*- mode: org -*-
#+TITLE:     
#+AUTHOR:    Arnaud Legrand
#+DATE: June, 2018
#+STARTUP: overview indent
#+OPTIONS: num:nil toc:t
#+PROPERTY: header-args :eval never-export

* Getting information about Python(3) libraries 
** Getting the list of installed packages and their version
https://stackoverflow.com/questions/20180543/how-to-check-version-of-python-modules
#+begin_src shell :results output :exports both
pip3 freeze
#+end_src

#+RESULTS:
#+begin_example
asn1crypto==0.24.0
attrs==17.4.0
bcrypt==3.1.4
beautifulsoup4==4.6.0
bleach==2.1.3
...
pandas==0.22.0
pandocfilters==1.4.2
paramiko==2.4.0
patsy==0.5.0
pexpect==4.2.1
...
traitlets==4.3.2
tzlocal==1.5.1
urllib3==1.22
wcwidth==0.1.7
webencodings==0.5
#+end_example

#+begin_src shell :results output :exports both
pip3 show pandas
echo "            "
pip3 show statsmodels
#+end_src

#+RESULTS:
#+begin_example
Name: pandas
Version: 0.22.0
Summary: Powerful data structures for data analysis, time series,and statistics
Home-page: http://pandas.pydata.org
Author: None
Author-email: None
License: BSD
Location: /usr/lib/python3/dist-packages
Requires: 
            
Name: statsmodels
Version: 0.9.0
Summary: Statistical computations and models for Python
Home-page: http://www.statsmodels.org/
Author: None
Author-email: None
License: BSD License
Location: /home/alegrand/.local/lib/python3.6/site-packages
Requires: patsy, pandas
#+end_example

#+begin_src python :results output :exports both

#+end_src

** How to list imported modules?
Inspiring from [[https://stackoverflow.com/questions/4858100/how-to-list-imported-modules][StackOverflow]], here is a simple function that lists
loaded package (that have a =__version__= attribute, which is
unfortunately not completely standard).

#+begin_src python :results output :exports both
def print_imported_modules():
    import sys
    for name,val in sorted(sys.modules.items()):
        if(hasattr(val, '__version__')): 
            print(val.__name__, val.__version__)

print("**** Package list in the beginning ****");
print_imported_modules()
print("**** Package list after loading pandas ****");
import pandas
print_imported_modules()

#+end_src

#+RESULTS:
#+begin_example
,**** Package list in the beginning ****
,**** Package list after loading pandas ****
_csv 1.0
_ctypes 1.1.0
decimal 1.70
argparse 1.1
csv 1.0
ctypes 1.1.0
cycler 0.10.0
dateutil 2.7.3
decimal 1.70
distutils 3.6.5rc1
ipaddress 1.0
json 2.0.9
logging 0.5.1.2
matplotlib 2.1.1
numpy 1.14.5
numpy.core 1.14.5
numpy.core.multiarray 3.1
numpy.core.umath b'0.4.0'
numpy.lib 1.14.5
numpy.linalg._umath_linalg b'0.1.5'
pandas 0.22.0
_libjson 1.33
platform 1.0.8
pyparsing 2.2.0
pytz 2018.5
re 2.2.1
six 1.11.0
urllib.request 3.6
zlib 1.0
#+end_example

** Setting up an environment with pip
The easiest way to go is as follows:
#+begin_src shell :results output :exports both
pip3 freeze > requirements.txt # to obtain the list of packages with their version
pip3 install -r requirements.txt # to install the previous list of packages, possibly on an other machine
#+end_src

If you want to have several installed python environments, you may
want to use [[https://docs.pipenv.org/][Pipenv]]. I doubt it allows to track correctly FORTRAN or C
dynamic libraries that are wrapped by Python.
* Getting information about R libraries
The best way seems to be to rely on the =devtools= package.

#+begin_src R :results output :session *R* :exports both
sessionInfo()
devtools::session_info()
#+end_src

#+RESULTS:
#+begin_example
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux buster/sid

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.8.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.8.0

locale:
 [1] LC_CTYPE=fr_FR.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=fr_FR.UTF-8        LC_COLLATE=fr_FR.UTF-8    
 [5] LC_MONETARY=fr_FR.UTF-8    LC_MESSAGES=fr_FR.UTF-8   
 [7] LC_PAPER=fr_FR.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C       

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

loaded via a namespace (and not attached):
[1] compiler_3.5.1
Session info ------------------------------------------------------------------
 setting  value                       
 version  R version 3.5.1 (2018-07-02)
 system   x86_64, linux-gnu           
 ui       X11                         
 language (EN)                        
 collate  fr_FR.UTF-8                 
 tz       Europe/Paris                
 date     2018-08-01                  

Packages ----------------------------------------------------------------------
 package   * version date       source        
 base      * 3.5.1   2018-07-02 local         
 compiler    3.5.1   2018-07-02 local         
 datasets  * 3.5.1   2018-07-02 local         
 devtools    1.13.6  2018-06-27 CRAN (R 3.5.1)
 digest      0.6.15  2018-01-28 CRAN (R 3.5.0)
 graphics  * 3.5.1   2018-07-02 local         
 grDevices * 3.5.1   2018-07-02 local         
 memoise     1.1.0   2017-04-21 CRAN (R 3.5.1)
 methods   * 3.5.1   2018-07-02 local         
 stats     * 3.5.1   2018-07-02 local         
 utils     * 3.5.1   2018-07-02 local         
 withr       2.1.2   2018-03-15 CRAN (R 3.5.0)
#+end_example

Some actually advocate that [[https://github.com/ropensci/rrrpkg][writing a reproducible research compendium
can be done by writing an R package]]. Those of you willing to have a
clean R dependency management should thus have a look at [[https://rstudio.github.io/packrat/][Packrat]].