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        "author": "Angus Hollands",
        "author_email": "goosey15@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Framework :: Jupyter",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Text Processing :: Markup :: LaTeX"
        ],
        "description": "# JupyTeX\nProvides Jupyter-backed execution of LaTeX `code` environments, and embeds the results. Similar in concept to [PythonTex](https://github.com/gpoore/PythonTex), but focuses on code _execution_, and avoids any language specific features.\n\n## How to use\n1. Install JupyTeX with `pip install git+https://github.com/agoose77/jupytex.git#egg=jupytex`\n2. Run `jupytex install` in LaTeX project directory (or provide an install directory with `-d DIR`) to create the necessary `.latexmkrc` and `jupytex.sty` files\n3. Add `\\usepackage{jupytex}` to the document header\n4. Declare code environments with\n    ```latex\n    \\begin{code}{language}[opts]\n        Some source code\n    \\end{code}\n    ```\n    See the configuration section for valid options in `opts`.\n5. Run `jupytex make` (which is a pass-through to `latexmk --shell-escape`) to invoke `latexmk`.\n### Example Python Script\n```latex\n\\begin{code}{python}[kernel=python3]\n    print(\"$x + y = z$\")\n\\end{code}\n```\n## Uninstallation\nRun `jupytex uninstall` in LaTeX project directory (or provide an install directory with `-d DIR`) to remove the installed `.latexmkrc` and `jupytex.sty` files\n## Cleaning\nRun `jupytex clean` (which is a pass-through to `latexmk -c` or `latexmk -C`) to remove both LaTeX and JupyTex-related run files.\n## JupyTeX flow control\n1. `jupytex.sty` declares dependency upon `\\jobname.timestamp`\n1. `jupytex.sty` macro writes code blocks to numbered `.code` files and attempts to include results\n1. Code 'blocks' are written to a `\\jobname.blocks` csv file\n1. `jupytex hash` is invoked to calculate the md5 hash for all of the blocks, which is written to `\\jobname.hash`. In future this should only be performed per-kernel-session.\n1. If `\\jobname.hash` has been modified, `jupytex execute` is invoked for the corresponding job, the code blocks executed, and results written to `.result` files, and errors to `.traceback` files. Code blocks which do not write to stdout write an empty results file. `\\jobname.timestamp` is updated with new timestamp.\n1. `latexmk` performs a new pass for the dependencies upon `\\jobname.timestamp`\n\n## Configuration\n* Each code block must be given a language. \n* One can specify the Jupyter kernel name with a `kernel` key parameter, which will be used instead of the language if present. One can also access an existing kernel, by passing the name of a connection file. \n* A `session` key parameter may be passed to create a new kernel associated with the kernel-session pair.  If the `kernel` parameter is set to a connection file, then *this will create a new client to the same kernel*.\n\n\n",
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        "name": "jupytex",
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