Feat: Eval with or without date

templates/tpl_evaluation.ipynb

@@ -2,18 +2,20 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
     "from IPython.display import Markdown as md\n",
+    "from IPython.display import DisplayHandle\n",
     "import pandas as pd\n",
-    "from pathlib import Path"
+    "from pathlib import Path\n",
+    "from datetime import datetime"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 8,
    "metadata": {
     "tags": [
      "parameters"
@@ -28,25 +30,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "split_ass = assessment.split(\"_\")\n",
+    "if len(split_ass) > 1:\n",
+    "    date, *assessment = assessment.split(\"_\")\n",
+    "    date = datetime.strptime(date, \"%y%m%d\")\n",
+    "    assessment = ' '.join(assessment)\n",
+    "else:\n",
+    "    date = None\n",
+    "    assessment = split_ass[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/markdown": [
-       "# Ds1 pour 308"
+       "# dm2 (14/11/2016) pour 308"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
       ]
      },
-     "execution_count": 39,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "md(f\"# {assessment} pour {tribe}\")"
+    "if date is None:\n",
+    "    display(md(f\"# {assessment} pour {tribe}\"))\n",
+    "else:\n",
+    "    display(md(f\"# {assessment} ({date:%d/%m/%Y}) pour {tribe}\"))"
    ]
   },
   {
@@ -74,7 +94,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,