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A python package to easily make reports in LaTeX from Markdown.

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sdgniser/reportinator

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Aim of the Project:

To make LaTeX reports easily from markdowns, containing the section data, autoplotted graphs from CSV, . Please look at the example first, before doing anything. Please install Typora, a MarkDown reader (not necessary, but recommended) and the latest version of Python.

Installation:

Please ensure that you have atleast Python3.6+ Clone the repo:

git clone "https://github.com/sdgniser/reportinator"

or by just downloading and unzipping this in your own location. To build this package with pip, just:

python -m pip install -e path/to/the/clone/directory/

For windows, py may replace python. NOTE for Windows Users: You would have to logout and login once the program is installed. This will make sure that the PATH added is implemented. You might even want to use a more user-friendly interface. A python script gets made in the Desktop, which is named make-my-report.py. You can copy this script to your project directory, and just run it with python by using the terminal or by right clicking and then selecting open with python.

A thing to note here is that on first installation, reportinator will exit after collecting metadata. So you will need to run it again.

Dependencies:

You do not need to install these, pip does that by itself. But heres a list of what gets installed. We are not listing the things the dependencies install.

  • matplotlib
  • numpy
  • scipy
  • ruamel.yaml
  • doi2bib
  • pandas
  • pyyaml
  • configurator
  • xlrd

Basic Usage:

This needs python3.6+, nothing below is supported. After the pip installation, you can easily call this from anywhere using the terminal/powershell. Just go to the directory where you have the markdown files/source csv files and the images and:

reportinator

This should run configuration once its started for the first time. If at any point you want to reconfigure:

reportinator --reconfig

If you want to have your own script bring run in one of the sections, say you want some custom code to output something in Example section, you need to make an Example.py and run:

reportinator --install Example.py

You can tweak the scripts in the program in the clone directory or just run say,

reportinator --install Default.py

to replace the Default.py usage in the code. However for making your own scripts, you need to follow the format as shown in example/Template.py. A working example named example/Example.py has been placed for further reference. If you want to run this code from somewhere else, you can always do:

reportinator --source path/to/project/directory

If you are stuck, do:

reportinator --help

Input Markdown:

The name of the input markdown is the title of the report. Recommended use: Typora, as a markdown editor, otherwise:

For recognizing multiple subsections, or lists with a text above them, it is necessary that you leave a one line gap between each subsection, or before the list. There is an example loaded in the current repo, which may be referred to, initially. Tables and Graphs will only be plotted only if the program sees the appropriate section headings. If you are leaving some section like graphs blank, and want to only fill it up with python graphs, you need to leave one blank line in the section. That is, you must have atleast one line in each section, even if it is blank.

Equations:

For putting in equations, you must type:

$$ your-equation $$ #e:tag

For referencing them anywhere inside the text, you just need to type @e:tag at the appropriate place.

Images:

Just use the default markdown syntax for images. You can drag and drop images in typora. No need to type.

![This is the caption](image.png)

Refer to these images by saying @f:name in-text.

Tables:

All the csv files placed in the source folder will be converted to tables. For good looking reports, please make sure that there are a maximum of 4 columns, in double column. To refer to the table anywhere, you do @t:csvname. You can use excel too. Just keep the .xlsx in your project directory and have the names of the sheets, what you would want the caption of the table.

Graphs:

These are triggered by a graph statement at the end of the csvfile (Look at the example in example). So if the line contains graph(x,y), then a graph will be plotted. Writing fit(lin) next will fit the graph in the said format. Look at the example. You can fit polynomial functions till 4 order. To refer to a graph, you need to do @g:graphname. The graph name is y column name without \ and $ and the order number. So, it might be Potential1. Of course, this supports excel files. Just keep your data as sheets inside a excel file named data.xlsx. Just keep this inside your project directory.

Referencing:

You can add references by just adding a dois.txt file, containing the list of dois in your source directory. You might need to manually compile it to actually get the references printed. Please note that you can just not use the referencing schemes explained above with the @ and just type \ref{something} to use the default syntax.

Compiling:

Autocompile is toggled on if there is a compiler installation in the system.

Templates

This code supports templates. All the class files are to be stored in _layouts/. Please add these lines to your custom class file, after \NeedsTeXFormat{LaTeX2e}:

 \usepackage[utf8]{inputenc}
 \usepackage{times}
 \usepackage{graphicx}
 \usepackage{amssymb}
 \usepackage{textcomp}
 \usepackage{gensymb}
 \usepackage{amsmath}
 \usepackage{float}
 \usepackage{booktabs}
 \usepackage[table,xcdraw]{xcolor}
 \providecommand{\tightlist}{%
   \setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}

The graph python code uses seaborn, you may look at the different styles available in the internet for the same, and change it in share/figures.py

To do:

  • PyPi submission
  • Tightlist integration
  • Proper fitting in the graph (more functions)
  • Error analysis code
  • Auto break for equations
  • Consistent font size and column width in tables

Example:

One example has been given in the program at example

The Maintainers:

This project is being maintained by Spandan Anupam and Visnhu Namboodiri K S. Thank us by using this program.

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A python package to easily make reports in LaTeX from Markdown.

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