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()