will add a preprocessor here (ready to merge)

README.md

@@ -113,6 +113,13 @@ If successful, a message will be printed with the URL to your post.  Additionall
 
 Currently, this package only works for the "classic" Jupyter Notebook and is not available in Jupyter Lab. If you have experience making Jupyter Lab extensions, please let me know.
 
+## Removing cells
+The code cells are removed by default. A cell tag ```show``` can supress this behaviour for a specific cell where the code should be included in the medium post.
+
+### Removing pieces of cells using cell tags
+You can remove pieces of cells using [cell tags](https://nbconvert.readthedocs.io/en/latest/removing_cells.html#removing-pieces-of-cells-using-cell-tags). You can use the tags: ```remove_cell```, ```remove_output```, ```remove_input```.
+
+
 ## Troubleshooting
 
 If your post is unsuccessful, a message with the error will be printed to the screen with information that might help you solve the issue.

jupyter_to_medium/_preprocesors.py

@@ -150,3 +150,14 @@ def preprocess_cell(self, cell, resources, index):
                             # TODO: Necessary when images from IPython.display module used
                             pass
         return cell, resources 
+
+# Remove code cells if a cell tag 'show' has not been defined.
+class RemoveCodeCellPreprocessor(Preprocessor):
+
+    def preprocess_cell(self, cell, resources, cell_index):
+        if cell['cell_type'] == 'code':
+            tags=cell['metadata'].get('tags',[])
+            if not 'show' in tags:
+                cell['source'] = ''  # remove the code it cell tag is not == 'show'
+
+        return cell, resources

jupyter_to_medium/_publish_to_medium.py

@@ -5,9 +5,11 @@
 import requests
 import nbformat
 from nbconvert.exporters import MarkdownExporter
+from nbconvert.preprocessors import TagRemovePreprocessor
 
-from ._preprocesors import MarkdownPreprocessor, NoExecuteDataFramePreprocessor
+from ._preprocesors import MarkdownPreprocessor, NoExecuteDataFramePreprocessor, RemoveCodeCellPreprocessor
 from ._screenshot import Screenshot
+from traitlets.config import Config
 
 
 class Publish:
@@ -20,9 +22,10 @@ class Publish:
     IMAGE_TYPES = {'png', 'gif', 'jpeg', 'jpg', 'tiff'}
 
 
-    def __init__(self, filename, integration_token, pub_name, title, tags, 
-                 publish_status, notify_followers, license, canonical_url,
-                 chrome_path, save_markdown, table_conversion):
+    def __init__(self, filename:str, integration_token=None, pub_name=None, title=None, 
+            tags=None, publish_status='draft', notify_followers=False, 
+            license='all-rights-reserved', canonical_url=None, chrome_path=None,
+            save_markdown=False, table_conversion='chrome'):
         self.filename = Path(filename)
         self.img_data_json = self.filename.stem + '_image_data.json'
         self.integration_token = self.get_integration_token(integration_token)
@@ -114,17 +117,38 @@ def get_pub_id(self):
                          f'Here is the publication data returned from Medium\n\n{data}')
 
     def create_markdown(self):
+        """[summary]
+
+        Returns:
+            md : str 
+                markdown
+            image_data_dict : dict
+        """        
+
+        # Adding a preprocessor here...
+
         mp = MarkdownPreprocessor()
         mp.preprocess(self.nb, self.resources)
 
         no_ex_pp = NoExecuteDataFramePreprocessor()
         no_ex_pp.preprocess(self.nb, self.resources)
 
+        remove_code_cells_preprocess = RemoveCodeCellPreprocessor()
+        remove_code_cells_preprocess.preprocess(self.nb, self.resources)
+
         # MarkdownExporter converts images to base64 bytes automatically
         # MarkdownExporter deep copies resources and fails when matplotlib
         # must remove converter key to not error
         self.resources.pop('converter') 
-        me = MarkdownExporter()
+
+        # Configure our tag removal
+        c = Config()
+        c.TagRemovePreprocessor.remove_cell_tags.add("remove_cell")
+        c.TagRemovePreprocessor.remove_all_outputs_tags.add('remove_output')
+        c.TagRemovePreprocessor.remove_input_tags.add('remove_input',)
+
+        me = MarkdownExporter(config=c)
+
         md, self.resources = me.from_notebook_node(self.nb, self.resources)
 
         image_data_dict = {**self.resources['image_data_dict'], **self.resources['outputs']}

tests/notebooks/Test Medium Blog Post.ipynb

@@ -3613,7 +3613,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.6.5"
   }
  },
  "nbformat": 4,

tests/notebooks/latex_to_medium.ipynb

@@ -0,0 +1,151 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# LaTeX to medium\n",
+    "As being a dedicated user of jupyter notebooks in my research I was very pleased to hear about the \n",
+    "[jupyter_to_medium](https://github.com/dexplo/jupyter_to_medium) package, also introduced in this [post](https://medium.com/dunder-data/jupyter-to-medium-initial-post-ecd140d339f0).\n",
+    "I tried this package and was very impressed by how easy my work in jupyter could be converted into a medium post. One pretty essential part missing however, was the LaTeX equations from my notebooks...\n",
+    "\n",
+    "This was a known issue, but someone proposed that matplotlib could be used to render the equations into images stored in the notebooks, which would be converted to medium. Here is my attempt to do so..."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I wrote a simple method that uses matplotlib to render the equations:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "tags": [
+     "show"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import sympy as sp\n",
+    "\n",
+    "def display(eq:sp.Eq, size=20):\n",
+    "    \"\"\"\n",
+    "    Use matplotlib to render LaTeX equations to figure within notebook.\n",
+    "    \n",
+    "    ----------\n",
+    "    eq : str or sympy.Eq\n",
+    "    LaTeX equation to render\n",
+    "    \n",
+    "    size : int\n",
+    "    size of the equation\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    if isinstance(eq, str):\n",
+    "        eq_latex = eq\n",
+    "    else:\n",
+    "        eq_latex = sp.latex(eq)\n",
+    "\n",
+    "    fig,ax=plt.subplots()\n",
+    "    fig.set_size_inches(0.01, 0.01)\n",
+    "    ax.axis(\"off\")\n",
+    "    plt.title(r'$' + eq_latex + r'$' , size=size);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As I'm also a big fan of the SymPy package, this method accepts equations both as pure LaTeX string or a SymPy expression. So it is either possible to write the LaTeX:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": [
+     "show"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 0.72x0.72 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "eq = r'E = m*c^2'\n",
+    "display(eq)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": [
+     "show"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAF0AAAAmCAYAAACmlJfBAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAADe0lEQVR4nO2Z24sURxTGf5+Jl5B18UKCAVEJ6oMIshdEREUNMYII+xQQb3+CvuZBEMGnBI0PCiKKJhBQkCyaENQFfRAironrihcWFRFF0KzGjYGIWY8PVYPD2jNdszvbpUx9UDQ93+lzvv66OFXdIzMjoViMiS2gEZFMj4BkegQk0yMgmR4ByfQIaBjTJX0jqVvSgKTHkk5Kmh9DS8OYDiwH9gGLgZXA/0CXpClFC1GjvhxJagKeAR1mdrLI2jXNdEmnJVnO2DZaYuuMibj7f1p04ZpmuqR+oBnYWSXsmJldH6mw0YakY8AcoN3MBous/WFooKTPgSnAZTPbPmqKCoCkXcASYEnRhkNt7aXdH7tHQ8hIIGm5pKOS7kt6IemhpFOSOjJidwPrgJVmdieDX+Hb5HeSWiV1Snoi6ZmknyVN83HzJP0k6ZHnfpE0I0Tve226HL4HzuJ2JF3ALn/ehtuplMfv4Y3hNyukbfXHucB5YBA4CNwDOoBDktYCF4Em4AjQB6wBfgjRHdxeeGP6YknTK8R8a2b/ZhGStgKTaqjXY2adOTE7gS3AcWBzeW2/O5ladr4X2Igz7mlpxgLPzex5Wc6S6QuBRWbW66/fgTN+FdACfGlmv3tuHHALWCZpgpn9V1W1meUOQMDfgFUZ/Tk57uZcP3QczsnXipuF3cC4gHuoVGf7kLgb/vfVGTkue25DBnfGc1NztQSaPtcnPB8SX8QAfvSavqhjzo/9g7xdgX8C9ANjM7g+YCCkTmhPL7WWnsD4IvAVbo99to45F+DWua6hhKRZwGTgnJm9HMI1AbMJ9Ce0p5dMvxIY/xbq2dMlTQA+8TGvhqspA6V+/kcG11aFa8G14D9DihRmOrAVmFlD/BGgswInf/x0BHqyUDL9UgbXVoVr8ccg00P63BjgH9wHoo9i9/IyXVdxPf3rCmvQB8PI2QO8IGNhBk5RYaEEDntufkid3M8AkuYB14ABYHeV0ANm9iDoSdcBktYAJ3Cz/jecxkm4WTfdzD6rMd943OTqNbP2DP4v3PZyVgbXi+vpEy3kDTfg6W8if3s3CDRHmO1LgV9xu4qXwEPgNLB+GLna/L3sz+Bmeu54Bjfe174QWqthP+3GRCP9ifHOIJkeAcn0CEimR0AyPQKS6RGQTI+AZHoEJNMjIJkeAcn0CEimR0AyPQJeA9tcMksNMo7bAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 0.72x0.72 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "E,m,c = sp.symbols('E m c')\n",
+    "eq2 = sp.Eq(E,m*c**2)\n",
+    "display(eq2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusions\n",
+    "Eventhough this requires that you rewrite your notebooks using the display method, I think that this is still much more convenient than having to create these LaTeX equations as images in some other (more manual way). I will now definatelly used the [jupyter_to_medium](https://github.com/dexplo/jupyter_to_medium) package for my next post. "
+   ]
+  }
+ ],
+ "metadata": {
+  "celltoolbar": "Tags",
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

tests/test_create_markdown.py

@@ -0,0 +1,14 @@
+import pytest
+import os.path
+from jupyter_to_medium._publish_to_medium import Publish
+
+@pytest.fixture
+def file_name():
+    path = os.path.dirname(__file__)
+    yield os.path.join(path,'notebooks','latex_to_medium.ipynb')
+
+
+def test_create_markdown(file_name):
+    publish = Publish(filename=file_name)
+    md, image_data_dict = publish.create_markdown()
+    a = 1