Preprocessor to embed markdown images

Author: Jürgen Hasch

src/jupyter_contrib_nbextensions/nbconvert_support/pre_embedimages.py

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+"""Nbconvert preprocessor for the python-markdown nbextension."""
+
+from nbconvert.preprocessors import Preprocessor
+from traitlets import Bool, Float
+import re
+import os
+import base64
+from urllib.request import urlopen
+from io import StringIO
+from ipython_genutils.ipstruct import Struct
+
+
+class EmbedImagesPreprocessor(Preprocessor):
+    """
+    :mod:`nbconvert` Preprocessor to embed images in a markdown cell as attachment inside the notebook itself.
+
+    This :class:`~nbconvert.preprocessors.Preprocessor` replaces kernel code in
+    markdown cells with the results stored in the cell metadata.
+
+    The preprocessor is installed by default. To enable embedding images with
+    NbConvert, you need to set the configuration parameter
+    `EmbedImagesPreprocessor.embed_images=True`.
+    This can be done either in the `jupyter_nbconvert_config.py` file::
+
+        c.EmbedImagesPreprocessor.embed_images=True
+
+    or using a command line parameter when calling NbConvert::
+
+        $ jupyter nbconvert --to html --EmbedImagesPreprocessor.embed_images=True mynotebook.ipynb
+
+    Further options are
+
+        EmbedImagesPreprocessor.embed_remote_images=True
+
+    to additionally embeds all images referenced by an url (e.g. http://jupyter.org/assets/nav_logo.svg) instead
+    of a local file name. Also
+
+        EmbedImagesPreprocessor.dpi_scaling
+
+    Let's you scale the size of an image. This is interesting if you want to save space by not embedding large
+    images and instead use a smaller (scaled) version. Works only for raster images (i.e. png, jpg).
+
+    *Note:* To embed images after conversion to HTML you can also use the `html_embed` exporter
+    """
+
+    embed_images = Bool(False, help="Embed images as attachment").tag(config=True)
+    embed_remote_images = Bool(False, help="Embed images referenced by an url as attachment").tag(config=True)
+    dpi_scaling = Float(0, help="Resize images to a certain DPI number (reduce size)").tag(config=True)
+
+    def preprocess(self, nb, resources):
+        """Skip preprocessor if not enabled"""
+        if self.embed_images:
+            nb, resources = super(EmbedImagesPreprocessor, self).preprocess(nb, resources)
+        return nb, resources
+
+    def replfunc_md(self, match):
+        """Read image and store as base64 encoded attachment"""
+        url = match.group(2)
+        imgformat = url.split('.')[-1]
+        if url.startswith('http'):
+            if self.embed_remote_images:
+                data = urlopen(url).read()
+            else:
+                return match.string
+        elif url.startswith('attachment'):
+            return match.string
+        else:
+            filename = os.path.join(self.path, url)
+            with open(filename, 'rb') as f:
+                data = f.read()
+
+        # TODO: scale image...
+        if self.dpi_scaling > 0 and imgformat in ['png', 'jpg']:
+            try:
+                import pillow as PIL
+            except ImportError:
+                self.log.info("pillow library not available to scale images")
+            if PIL:
+                #im = PIL.Image.open(StringIO(data))
+                #size = 128, 128
+                #im.thumbnail(size, PIL.Image.ANTIALIAS)
+                #data = im.save()
+                self.log.info("Rescaled image %s to size %d x %d pixels" % (imgname, size) )
+
+        self.log.debug("embedding url: %s, format: %s" % (url, imgformat))
+        b64_data = base64.b64encode(data).decode("utf-8")
+        self.attachments[url] = { 'image/'+imgformat : b64_data }
+
+        newimg = '![' + match.group(1) + '](attachment:' + match.group(2) + ')'
+        return newimg
+
+    def preprocess_cell(self, cell, resources, index):
+        """
+        Preprocess cell
+
+        Parameters
+        ----------
+        cell : NotebookNode cell
+            Notebook cell being processed
+        resources : dictionary
+            Additional resources used in the conversion process.  Allows
+            preprocessors to pass variables into the Jinja engine.
+        cell_index : int
+            Index of the cell being processed (see base.py)
+        """
+        self.path = resources['metadata']['path']
+        self.attachments = Struct()
+
+        if cell.cell_type == "markdown":
+            regex = re.compile('!\[([^"]*)\]\(([^"]+)\)')
+            cell.source = regex.sub(self.replfunc_md, cell.source)
+            cell.attachments = self.attachments
+        return cell, resources