## Table of Contents

- Getting information about your Git repository
- Getting information about Python(3) libraries
  - Getting the list of installed packages and their version
  - How to list imported modules?
  - Setting up an environment with pip
- Getting information about R libraries

## Getting information about your Git repository

When taking notes, it may be difficult to remember which version of the code or of a file was used. This is what version control is useful for. Here are a few useful commands that we typically insert at the top of our notebooks in shell cells

    git log -1

    commit 741b0088af5b40588493c23c46d6bab5d0adeb33
    Author: Arnaud Legrand <arnaud.legrand@imag.fr>
    Date:   Tue Sep 4 12:45:43 2018 +0200

        Fix a few typos and provide information on jupyter-git plugins.

    git status

    On branch master
    Your branch is ahead of 'origin/master' by 4 commits.
      (use "git push" to publish your local commits)

    Changes not staged for commit:
      (use "git add <file>..." to update what will be committed)
      (use "git checkout -- <file>..." to discard changes in working directory)

    	modified:   resources.org

    Untracked files:
      (use "git add <file>..." to include in what will be committed)

    	../../module2/ressources/replicable_article/IEEEtran.bst
    	../../module2/ressources/replicable_article/IEEEtran.cls
    	../../module2/ressources/replicable_article/article.bbl
    	../../module2/ressources/replicable_article/article.tex
    	../../module2/ressources/replicable_article/data.csv
    	../../module2/ressources/replicable_article/figure.pdf
    	../../module2/ressources/replicable_article/logo.png
    	.#resources.org

    no changes added to commit (use "git add" and/or "git commit -a")

Then, I often include commands at the end of my notebook indicating how to commit the results (adding the new files, committing with a clear message and pushing). E.g.,

    git add resources.org;
    git commit -m "Completing the section on getting Git information"
    git push

    [master 514fe2c1 ] Completing the section on getting Git information
     1 file changed, 61 insertions(+)
    Counting objects: 25, done.
    Delta compression using up to 4 threads.
    Compressing objects: 100% (20/20), done.
    Writing objects: 100% (25/25), 7.31 KiB | 499.00 KiB/s, done.
    Total 25 (delta 11), reused 0 (delta 0)
    To ssh://app-learninglab.inria.fr:9418/learning-lab/mooc-rr-ressources.git
       6359f8c..1f8a567  master -> master

Obviously, in this case you need to save the notebook before running this cell, hence the output of this final command (with the new git hash) will not be stored in the cell. This is not really a problem and is the price to pay for running git from within the notebook itself.

## 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

    pip3 freeze

    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

    pip3 show pandas
    echo "            "
    pip3 show statsmodels

    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

### How to list imported modules?

Inspiring from StackOverflow, here is a simple function that lists loaded package (that have a `__version__` attribute, which is unfortunately not completely standard).

    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()

    **** 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

### Setting up an environment with pip

The easiest way to go is as follows:

    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

If you want to have several installed python environments, you may want to use 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.

    sessionInfo()
    devtools::session_info()

    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)

Some actually advocate that 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 Packrat.