jupyterlab_email's Introduction

jupyterlab_email

A jupyterlab extension to email notebooks from the browser.

Options

Inline notebook as email, with code
Inline notebook as email, without code
Send notebook as HTML attachment, with code
Send notebook as HTML attachment, without code
Send notebook as PDF attachment, with code
Send notebook as PDF attachment, without code
Attach output data as CSV, TSV, PDF, PNG, or Excel Spreadsheet

Install

pip install jupyterlab_email
jupyter labextension install jupyterlab_email
jupyter serverextension enable --py jupyterlab_email

Adding templates

install the server extension, and add the following to jupyter_notebook_config.py

c.JupyterLabEmail.smtp_servers = [{'name': 'gmail',
                                   'domain': 'gmail.com',
                                   'username': '<YOUR USERNAME>',
                                   'smtp': 'smtp.gmail.com',
                                   'port': 465}]

Create email from notebook:

Use the function in jupyterlab_email._email

def make_email(path, model, from_, type='email', template='', code=False, subject='',
               also_attach='none', also_attach_pdf_template='', also_attach_html_template=''):
    '''
        path        : path to notebook
        model       : notebook itself (in case deployment strips outputs or
                      notebook not available except through ContentsManager)
        from_       : address to send the email from
        type        : type to convert notebook to
        template    : template to use when converting notebook
        code        : include input cells in notebook
        subject     : subject of email
        also_attach : also attach pdf/html/both
    '''

Attach dataframe as csv or spreadsheet

In jupyterlab_email.attachments

def attach(data, filename, type):

Modify jupyterlab_email.attachments.EXCEL_ENGINE to use a different excel writer (defaults to xlsxwriter)

Inline LaTeX

In jupyterlab_email.attachments

def latex(expression):
    import matplotlib.pyplot as plt
    fig, ax = plt.subplots(figsize=(10, 1))
    ax.xaxis.set_visible(False)
    ax.yaxis.set_visible(False)
    ax.axis('off')
    plt.text(0, 0.6, r'$%s$' % expression, fontsize=25)
    plt.show()

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