Metadata-Version: 2.1
Name: arxiv_latex_cleaner
Version: 0.1.8
Summary: Cleans the LaTeX code of your paper to submit to arXiv.
Home-page: https://github.com/google-research/arxiv-latex-cleaner
Author: Google Research Authors
Author-email: jponttuset@gmail.com
License: Apache License, Version 2.0
Description: # `arxiv_latex_cleaner`
        
        This tool allows you to easily clean the LaTeX code of your paper to submit to
        arXiv. From a folder containing all your code, e.g. `/path/to/latex/`, it
        creates a new folder `/path/to/latex_arXiv/`, that is ready to ZIP and upload to
        arXiv.
        
        ## Example call:
        
        ```console
        arxiv_latex_cleaner /path/to/latex --im_size 500 --images_whitelist='{"images/im.png":2000}'
        ```
        
        ## Installation:
        
        ```console
        pip install arxiv-latex-cleaner
        ```
        
        | :exclamation:  arxiv_latex_cleaner is only compatible with Python >=3  :exclamation: |
        |--------------------------------------------------------------------------------------|
        
        Alternatively, you can download the source code:
        
        ```console
        git clone https://github.com/google-research/arxiv-latex-cleaner
        cd arxiv-latex-cleaner/
        python -m arxiv_latex_cleaner --help
        ```
        
        And install as a command-line program directly from the source code:
        
        ```console
        python setup.py install
        ```
        
        ## Main features:
        
        #### Privacy-oriented
        
        *   Removes all auxiliary files (`.aux`, `.log`, `.out`, etc.).
        *   Removes all comments from your code (yes, those are visible on arXiv and you
            do not want them to be). These also include `\begin{comment}\end{comment}`
            and `\iffalse\fi` environments.
        *   Optionally removes user-defined commands entered with `commands_to_delete`
            (such as `\todo{}` that you redefine as the empty string at the end).
        
        #### Size-oriented
        
        There is a 50MB limit on arXiv submissions, so to make it fit:
        
        *   Removes all unused `.tex` files (those that are not in the root and not
            included in any other `.tex` file).
        *   Removes all unused images that take up space (those that are not actually
            included in any used `.tex` file).
        *   Optionally resizes all images to `im_size` pixels, to reduce the size of the
            submission. You can whitelist some images to skip the global size using
            `images_whitelist`.
        *   Optionally compresses `.pdf` files using ghostscript (Linux and Mac only).
            You can whitelist some PDFs to skip the global size using
            `images_whitelist`.
        
        #### TikZ picture source code concealment
        
        To prevent the upload of tikzpicture source code or raw simulation
        data, this feature:
        
        *   Replaces the tikzpicture environment `\begin{tikzpicture} ... \end{tikzpicture}`
            with the respective `\includegraphics{EXTERNAL_TIKZ_FOLDER/picture_name.pdf}`.
        *   Requires externally compiled TikZ pictures as `.pdf` files in folder `EXTERNAL_TIKZ_FOLDER`.
            See section 53 in the [PGF/TikZ manual](https://ctan.org/pkg/pgf?lang=en) on TikZ picture externalization.
        *   Only replaces environments with preceding `\tikzsetnextfilename{picture_name}` command
            (as in `\tikzsetnextfilename{picture_name}\begin{tikzpicture} ... \end{tikzpicture}`) where
            the externalized `picture_name.pdf` filename matches `picture_name`.
        
        ## Usage:
        
        ```
        usage: arxiv_latex_cleaner@v0.1.8 [-h] [--resize_images] [--im_size IM_SIZE]
                                          [--compress_pdf]
                                          [--pdf_im_resolution PDF_IM_RESOLUTION]
                                          [--images_whitelist IMAGES_WHITELIST]
                                          [--commands_to_delete COMMANDS_TO_DELETE [COMMANDS_TO_DELETE ...]]
                                          input_folder
        
        Clean the LaTeX code of your paper to submit to arXiv. Check the README for
        more information on the use.
        
        positional arguments:
          input_folder          Input folder containing the LaTeX code.
        
        optional arguments:
          -h, --help            show this help message and exit
          --resize_images       Resize images.
          --im_size IM_SIZE     Size of the output images (in pixels, longest side).
                                Fine tune this to get as close to 10MB as possible.
          --compress_pdf        Compress PDF images using ghostscript (Linux and Mac
                                only).
          --pdf_im_resolution PDF_IM_RESOLUTION
                                Resolution (in dpi) to which the tool resamples the
                                PDF images.
          --images_whitelist IMAGES_WHITELIST
                                Images (and PDFs) that won't be resized to the default
                                resolution,but the one provided here. Value is pixel
                                for images, and dpi forPDFs, as in --im_size and
                                --pdf_im_resolution, respectively. Format is a
                                dictionary as: '{"path/to/im.jpg": 1000}'
          --commands_to_delete COMMANDS_TO_DELETE [COMMANDS_TO_DELETE ...]
                                LaTeX commands that will be deleted. Useful for e.g.
                                user-defined \todo commands.
          --use_external_tikz EXTERNAL_TIKZ_FOLDER
                                Folder (relative to input folder) containing
                                externalized TikZ figures in PDF format.
        ```
        
        ## Note
        
        This is not an officially supported Google product.
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3
Description-Content-Type: text/markdown
