Version bump

FlorianWilhelm · Dec 4, 2023 · 21af049 · 21af049
1 parent aa5dbda
commit 21af049
Show file tree

Hide file tree

Showing 2 changed files with 79 additions and 41 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,5 +1,10 @@
 # Changelog
 
+## Version 0.6 (2023-04-10)
+
+- Migrate to Pydantic v2
+- Require mininum Python version of 3.10
+
 ## Version 0.5 (2023-04-10)
 
 - Change the start/end time of a slot to a datetime

diff --git a/notebooks/pyconde-pydata-berlin-2024/10_selection_v1.ipynb b/notebooks/pyconde-pydata-berlin-2024/10_selection_v1.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -37,7 +37,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,21 +46,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
     "import pytanis\n",
     "from pytanis import GSheetClient, PretalxClient\n",
-    "from pytanis.google import Scope, mark_rows\n",
+    "from pytanis.google import Scope, mark_rows, gsheet_col\n",
     "from pytanis.review import read_assignment_as_df, save_assignments_as_json, Col\n",
     "from pytanis.pretalx import subs_as_df, reviews_as_df, speakers_as_df\n",
     "from pytanis.utils import implode"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -69,7 +69,7 @@
        "'0.5.post1.dev1+gaff63da.d20231129'"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -81,7 +81,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -99,18 +99,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7ac26907e83b45068145ccc60fbc9db8",
+       "model_id": "b47dcae516f0411fb92af233fb3b105c",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "  0%|          | 0/11 [00:00<?, ?it/s]"
+       "  0%|          | 0/20 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -119,12 +119,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "699c5b0c8c364d8b948630e5087b9ab2",
+       "model_id": "0a1526f4e5464407ade1e171aeb60f7e",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "  0%|          | 0/7 [00:00<?, ?it/s]"
+       "  0%|          | 0/15 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -133,7 +133,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c3d8a3de5c2b4de4b033ab7863a3ef24",
+       "model_id": "e0a02540f98b4947b2cec13bee707dc1",
        "version_major": 2,
        "version_minor": 0
       },
@@ -155,7 +155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -173,7 +173,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -192,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -210,7 +210,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -224,7 +224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -242,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -253,7 +253,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -265,7 +265,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -281,7 +281,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -299,12 +299,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
     "subs_df.rename(columns={'Q: Expected audience expertise: Python': 'Python expertise',\n",
-    "                        'Q: Expected audience expertise: Domain': 'Domain expetise',\n",
+    "                        'Q: Expected audience expertise: Domain': 'Domain expertise',\n",
     "                        'Q: I identify as a member of an underrepresented group': 'Underrepresented',\n",
     "                        'Q: Country of residence': 'Country',\n",
     "                        'Q: Github': 'Github',\n",
@@ -313,13 +313,18 @@
     "                        'Q: Company / Institute': 'Affiliation',\n",
     "                        'Q: Position / Job': 'Position',\n",
     "                        'Q: I will present my talk on site': 'Onsite talk',\n",
-    "                        'Q: Notes for reviewers only': 'Reviewer notes'},\n",
+    "                        'Q: Notes for reviewers only': 'Reviewer notes',\n",
+    "                        'Q: I hereby declare that this proposal is my own original work': 'Original work',\n",
+    "                        'Q: Did you use an LLM, e.g. ChatGPT, to help you with this proposal?': 'ChatGPT used',\n",
+    "                        'Q: How should we address you?': 'Pronouns',\n",
+    "                        'Q: I am open to receiving invitations from meet-up organizers to showcase my work at local meet-ups.': 'Meetup interested',\n",
+    "                        'Q: City of residence': 'City'},\n",
     "              inplace=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -330,7 +335,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -344,7 +349,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -354,7 +359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -371,7 +376,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -381,7 +386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -390,7 +395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -399,7 +404,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -412,7 +417,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "set_row_height(worksheet, \"1:100\", 50);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for idx, col in enumerate(subs_df.columns):\n",
+    "    if col not in {'Title', 'Track', 'Speaker name', 'ChatGPT used', 'Reviewer notes', 'Biography', 'Position', 'LinkedIn', 'Github', 'Affiliation', 'Homepage'}:\n",
+    "        continue\n",
+    "    col_id = gsheet_col(idx)\n",
+    "\n",
+    "    fmt = cellFormat(\n",
+    "        horizontalAlignment='LEFT',\n",
+    "        wrapStrategy='WRAP'\n",
+    "        )\n",
+    "\n",
+    "    format_cell_range(worksheet, col_id, fmt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -424,7 +457,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -436,7 +469,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -448,7 +481,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -460,7 +493,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -479,7 +512,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -488,7 +521,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -497,7 +530,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [