Metadata-Version: 2.1
Name: nbless
Version: 0.1.2
Summary: Create Jupyter notebooks from Markdown and Python scripts.
Home-page: https://github.com/marskar/nbless
Author: Martin Skarzynski
Author-email: marskar@gmail.com
License: UNKNOWN
Description: # The `nbless` python package
        
        Using `nbless` you can create and execute [Jupyter Notebooks](http://jupyter-notebook.readthedocs.io/en/latest/examples/Notebook/What%20is%20the%20Jupyter%20Notebook.html) in
        - your terminal or
        - your favorite Python environment (e.g. [PyCharm](https://www.jetbrains.com/pycharm/) or [Visual Studio Code](https://code.visualstudio.com/docs/python/python-tutorial)).
        
        The `nbless` python package consists of 5 functions:
        - `nbuild`, which creates a notebook from python scripts and plain text files, e.g. markdown (`.md`) and text (`.txt`) files.
        - `nbexec`, which runs a notebook from top to bottom and saves an executed version, leaving the source notebook untouched.
        - `nbcode`, which converts a notebook into a code file.  Markdown content is discarded.
        - `nbless`, which calls `nbuild`, `nbcode`, and `nbexec` to create and execute a notebook.
        - `nbhtml`, which converts a notebook into an HTML document.
        
        All of the above function work for Python _and_ R code, with the caveat that nbexec and nbless require the kernel argument to be set to `ir` if R code files (`.R`) are included.
        
        If you want to execute a Jupyter notebook that contains both R and Python code, you will have to put the R code in Python scripts (`.py`) and use [rpy2](https://rpy2.readthedocs.io/) with the default kernel (`python3`).
        
        To run Rmd files that include R and Python code, you will need the `reticulate` R package.
        
        The `nb` functions rely on the `nbconvert` and `nbformat` modules that are included with `jupyter`. The `catrmd` function has no dependencies beyond Python.
        
        ## Installation
        
        ```sh
        pip install nbless
        ```
        
        or clone the [repo](https://github.com/marskar/nbless), e.g. `git clone https://github.com/marskar/nbless` and either use locally, e.g. `python nbless.py README.md plot.py notes.txt` or install using setup.py, e.g. `python setup.py install`.
        
        ## Basic usage: terminal
        
        ### Creating a Jupyter notebook with `nbuild` in the terminal
        
        ```sh
        nbuild README.md plot.py notes.txt
        ```  
        
        The `nbuild` function takes the contents of Python code files (`.py`) stores them as [Jupyter Notebook code cells](https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Running%20Code.html). The contents of all other files are stored in [markdown cells](https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Working%20With%20Markdown%20Cells.html).
        
        The default output filename for `nbuild` is `unexecuted.ipynb`. By default, input and output files are located in the current directory (`'./'`).
        
        You can provide a more descriptive name for the unexecuted notebook (`-n`) and set different input (`-i`) and output (`-o`) filepaths:
        
        ```sh
        nbuild README.md plot.py notes.txt --input_path input_files --output_name raw.ipynb --output_path notebooks/
        # Or
        nbuild README.md plot.py notes.txt -i input_files -n raw.ipynb -o notebooks/
        ```
        
        If you only want to execute a notebook, run `nbexec`.
        
        ### Executing a notebook with `nbexec` in the terminal
        
        
        ```sh
        nbexec raw.ipynb
        ```
        
        The `nbexec` command creates a copy of the input notebook, runs it from top to bottom and saves it. The default name of the executed notebook is `executed.ipynb`. The default filepath where the notebook is saved is the current directory (`'./'`).
        
        You can provide a more descriptive name for the executed notebook (`-n`) and set different input (`-i`) and output (`-o`) filepaths:
        
        
        ```sh
        nbexec raw.ipynb --input_path input_files --output_name out.ipynb --output_path notebooks/
        # Or
        nbexec raw.ipynb -i input_files -n out.ipynb -o notebooks/
        ```
        
        If you want to combine `nbuild` and `nbexec` in one step, use `nbless`.
        
        ### Creating and executing a Jupyter notebook with `nbless` in the terminal
        
        Run `nbless` in your terminal, providing all of the names of the source files as arguments, e.g.
        
        ```sh
        nbless README.md plot.py notes.txt
        ```
        The default name of the first notebook is `unexecuted.ipynb` while the executed notebook is called `executed.ipynb` by default. The default filepath where the notebooks are saved is the current directory (`'./'`).
        
        You can provide more descriptive names for the notebooks and set a different output path:
        
        ```sh
        nbless README.md plot.py notes.txt --input_path input_files --nbuild raw.ipynb --nbexec out.ipynb --nbcode code.py --output_path output_files/
        # Or
        nbless README.md plot.py notes.txt --i input_files -u raw.ipynb -e out.ipynb -c code.py -o output_files/
        ```  
        
        If you do not want an executed version of the notebook, run `nbuild` instead of `nbless`.
        
        ### Creating a code file with `nbcode` in the terminal
        
        
        ```sh
        nbcode out.ipynb
        ```
        
        The `nbcode` command extracts the content from code cells, discarding all output and markdown content.
        
        The default name of the code file is `code.py`. The default filepath where the code file is saved is the current directory (`'./'`).
        
        You can provide a more descriptive name for the code file (`-n`) and set different input (`-i`) and output (`-o`) filepaths:
        
        
        ```sh
        nbcode out.ipynb --input_path input_files --output_name out.ipynb --output_path notebooks/
        # Or
        nbcode out.ipynb -i input_files -n out.ipynb -o notebooks/
        ```
        
        
        ### Creating an HTML file with `nbhtml` in the terminal
        
        The `nbhtml` command works like `nbcode`, except it creates an HTML document, which includes output and the content of markdown and code cells.
        
        ```sh
        nbhtml out.ipynb
        ```
        
        The default name of the HTML file is `nb.html`. The default filepath where the HTML file is saved is the current directory (`'./'`).
        
        You can provide a more descriptive name for the executed notebook (`-n`) and set different input (`-i`) and output (`-o`) filepaths:
        
        
        ```sh
        nbhtml out.ipynb --input_path input_files --output_name out.ipynb --output_path notebooks/
        # Or
        nbhtml out.ipynb -i input_files -n out.ipynb -o notebooks/
        ```
        
        ## Basic usage: Python environment
        
        ```python
        # You can import any or all of the functions from the nbless package.
        
        # You can also import each function individually
        from nbless import nbuild
        from nbless import nbexec
        from nbless import nbless
        from nbless import nbcode
        
        # The above imports all 4 functions
        # This can also be done with either of the two lines below.
        from nbless import nbuild, nbexec, nbless, nbcode
        from nbless import *
        
        # Another alternative is to import the package and use it as a namespace.
        import nbless
        
        #Use individually
        nbuild(["plot.py", "notes.txt"], input_path='input_files', output_path="notebooks/")
        nbexec("notebooks/raw.ipynb", output_path="notebooks/")
        nbcode("out.ipynb", input_path="notebooks/", output_path='output_files')
        nbhtml("out.ipynb", input_path="notebooks/", output_path='output_files')
        
        # Or to run both nbuild and nbexec at once, use nbless
        nbless(["index.md", "plot.py", "notes.txt"], input_path="input_files/", nbexec_path="notebooks/")
        
        # Use nbless as a namespace
        nbless.nbuild(["index.md", "plot.py", "notes.txt"], input_path="input_files/", output_path="notebooks/")
        nbless.nbexec("out.ipynb", input_path="notebooks/", output_path="notebooks/")
        nbless.nbcode("out.ipynb", input_path="notebooks/", output_path='output_files')
        nbless.nbhtml("out.ipynb", input_path="notebooks/", output_path='output_files')
        nbless.nbless(["index.md", "plot.py", "notes.txt"], input_path="input_files/", nbexec_path="notebooks/")
        ```
        
        You can also run the `nbless` functions in an R environment using the `reticulate` R package.
        
        ### Missing a dependency?
        
        If you installed [Anaconda](https://www.anaconda.com/download/), you should already have all of the dependencies (`python`, `nbformat`, and `nbconvert`).
        
        If not, or if you have [Miniconda](https://conda.io/miniconda.html) installed, run
        
        ```sh
        conda install -yc conda-forge jupyter
        ```
        
        If you have any other Python installation, run
        
        ```sh
        pip install jupyter
        ```
        
        ## Too many file names to type out?
        
        You can use the `ls` command to assign all of the relevant names in the current directory to a variable and pass this variable as an argument to `nbconvert.py`.
        
        To preserve the order and differentiate files that should be incorporated into the notebook, I recommend left padding your file names with zeros (e.g. 01_intro.md, 02_figure1.py).
        
        Consider the example below:
        
        ```sh
        touch {01..09}.py
        name_list=`ls 0*.py`
        python nbuild.py `echo $name_list`
        ```
        
        In a python environment, I recommend `os.listdir` to obtain a list of all files:
        ```python
        from os import listdir
        from os.path import isfile, join
        onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
