2018-02-01 17:18:51 +00:00
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{
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"cells": [
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{
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"cell_type": "code",
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2018-04-21 15:30:09 +00:00
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"execution_count": 2,
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2018-02-09 03:02:48 +00:00
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"metadata": {
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"collapsed": true
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},
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2018-02-01 17:18:51 +00:00
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"outputs": [],
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"source": [
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"import xlsxwriter"
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]
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},
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{
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"cell_type": "code",
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2018-04-21 15:30:09 +00:00
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"execution_count": 39,
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"metadata": {},
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2018-02-01 17:18:51 +00:00
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"outputs": [],
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"source": [
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2018-04-21 15:30:09 +00:00
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"from repytex.worksheets.worksheet import pull_datas\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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2018-02-01 17:18:51 +00:00
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"import sqlite3"
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]
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},
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{
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"cell_type": "code",
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2018-04-21 15:30:09 +00:00
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"execution_count": 4,
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2018-02-01 17:18:51 +00:00
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"conn = sqlite3.connect('./recopytex.db')"
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]
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},
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{
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"cell_type": "code",
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2018-04-21 15:30:09 +00:00
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'evaluation': id name term t_id\n",
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" 0 1 DS1 mise en jambe 1 1,\n",
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" 'exercises': id name eval_id date comment\n",
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" 0 1 1 - Prendre la température 1 2017-09-05 00:00:00.000000 \n",
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" 1 2 2 - Maladroite! 1 2017-09-05 00:00:00.000000 ,\n",
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" 'question_scores': id question_id student_id value\n",
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" 0 1 1 1 1\n",
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" 1 2 2 1 2\n",
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" 2 3 3 1 .\n",
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" 3 4 1 2 2\n",
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" 4 5 2 2 2\n",
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" 5 6 3 2 1\n",
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" 6 7 1 3 3\n",
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" 7 8 2 3 0\n",
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" 8 9 3 3 0\n",
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" 9 10 1 4 3\n",
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" 10 11 2 4 3\n",
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" 11 12 3 4 0\n",
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" 12 13 1 5 1\n",
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" 13 14 2 5 2\n",
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" 14 15 3 5 .\n",
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" 15 16 1 6 3\n",
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" 26 27 3 8 .\n",
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" \n",
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" [200 rows x 4 columns],\n",
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" 'questions': id name score_rate is_leveled exercise_id competence domain \\\n",
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" 0 1 1 0 1 1 Cher Grandeurs \n",
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" 1 2 2 0 1 1 Cal Grandeurs \n",
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" 2 3 2.c 0 1 1 Cal Grandeurs \n",
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" 0 4 0 1 2 Cher 4opérations \n",
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" 1 5 0 1 2 Cher 4opérations \n",
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" 2 6 0 1 2 Rai 4opérations \n",
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" 3 7 0 1 2 Cal 4opérations \n",
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" 4 8 0 1 2 Com 4opérations \n",
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" \n",
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" comment \n",
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" 0 Lecture du thermomètre \n",
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" 1 Suivre programme de calculs \n",
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" 2 Renverser un programme de calculs \n",
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" 0 Lire le tableau et le graphique \n",
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" 1 Décomposer le problème \n",
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" 2 Manipuler les grandeurs \n",
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" 3 Mener à bien les calculs \n",
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" 4 Rédaction ,\n",
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" 'students': id name surname mail commment tribe_id\n",
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" 0 1 ABDALLAH ALLAOUI Taiassima None 1\n",
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" 1 2 ADANI Ismou None 1\n",
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" 2 3 AHAMADA Dhoulkamal None 1\n",
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" 3 4 AHAMADI Asbahati None 1\n",
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" 4 5 AHAMADI OUSSENI Ansufiddine None 1\n",
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" 5 6 AHAMED Fayadhi None 1\n",
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" 6 7 AHMED SAID Hadaïta None 1\n",
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" 7 8 ALI MADI Anissa None 1\n",
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" 8 9 ALI Raydel None 1\n",
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" 9 10 ATTOUMANE ALI Fatima None 1\n",
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" 10 11 BACHIROU Elzame None 1\n",
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" 11 12 BINALI Zalida None 1\n",
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" 12 13 BOINA Abdillah Mze Limassi None 1\n",
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" 13 14 BOUDRA Zaankidine None 1\n",
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" 14 15 BOURA Kayssoiria None 1\n",
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" 15 16 HALADI Asna None 1\n",
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" 16 17 HALIDI Soibrata None 1\n",
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" 17 18 HAMEDALY Doulkifly None 1\n",
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" 18 19 IBRAHIM Nassur None 1\n",
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" 19 20 INOUSSA Anchoura None 1\n",
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" 20 21 MOHAMED Nadia None 1\n",
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" 21 22 MOUHOUDHOIRE Izak None 1\n",
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" 22 23 MOUSSRI Bakari None 1\n",
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" 23 24 SAÏD Fatoumia None 1\n",
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" 24 25 SAKOTRA Claudiana None 1\n",
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" 25 26 TOUFAIL Salahou None 1\n",
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" 26 76 Ibrahim Chaharzade None 1,\n",
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" 'tribe': id name grade\n",
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" 0 1 302 3e}"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"datas = pull_datas(1, conn)\n",
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"datas"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'DS1 mise en jambe'"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"datas['evaluation'][\"name\"][0]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 64,
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"metadata": {},
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"outputs": [],
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"source": [
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"q_df = datas[\"questions\"]\n",
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"q_df = q_df.assign(\n",
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" Nom = q_df[[\"name\", \"comment\"]].apply(lambda x: \" \".join(x), 1)\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 65,
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2018-02-09 03:02:48 +00:00
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style>\n",
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" .dataframe thead tr:only-child th {\n",
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" text-align: right;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: left;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>id</th>\n",
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" <th>name</th>\n",
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2018-04-21 15:30:09 +00:00
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" <th>score_rate</th>\n",
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" <th>is_leveled</th>\n",
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" <th>exercise_id</th>\n",
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" <th>competence</th>\n",
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" <th>domain</th>\n",
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" <th>comment</th>\n",
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" <th>Nom</th>\n",
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2018-02-09 03:02:48 +00:00
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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2018-04-21 15:30:09 +00:00
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" <td>0</td>\n",
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2018-02-09 03:02:48 +00:00
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" <td>1</td>\n",
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2018-04-21 15:30:09 +00:00
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" <td>1</td>\n",
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" <td>Cher</td>\n",
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" <td>Grandeurs</td>\n",
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" <td>Lecture du thermomètre</td>\n",
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" <td>1 Lecture du thermomètre</td>\n",
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2018-02-09 03:02:48 +00:00
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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2018-04-21 15:30:09 +00:00
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" <td>0</td>\n",
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2018-02-09 03:02:48 +00:00
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" <td>1</td>\n",
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" <td>1</td>\n",
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2018-04-21 15:30:09 +00:00
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" <td>Cal</td>\n",
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" <td>Grandeurs</td>\n",
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" <td>Suivre programme de calculs</td>\n",
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" <td>2 Suivre programme de calculs</td>\n",
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2018-02-09 03:02:48 +00:00
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" </tr>\n",
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" <tr>\n",
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2018-04-21 15:30:09 +00:00
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" <th>2</th>\n",
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2018-02-09 03:02:48 +00:00
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" <td>3</td>\n",
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2018-04-21 15:30:09 +00:00
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" <td>2.c</td>\n",
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" <td>0</td>\n",
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2018-02-09 03:02:48 +00:00
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" <td>1</td>\n",
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" <td>1</td>\n",
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2018-04-21 15:30:09 +00:00
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" <td>Cal</td>\n",
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" <td>Grandeurs</td>\n",
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" <td>Renverser un programme de calculs</td>\n",
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" <td>2.c Renverser un programme de calculs</td>\n",
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2018-02-09 03:02:48 +00:00
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" </tr>\n",
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" <tr>\n",
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2018-04-21 15:30:09 +00:00
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" <th>0</th>\n",
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" <td>4</td>\n",
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" <td></td>\n",
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" <td>0</td>\n",
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2018-02-09 03:02:48 +00:00
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" <td>1</td>\n",
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" <td>2</td>\n",
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2018-04-21 15:30:09 +00:00
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" <td>Cher</td>\n",
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" <td>4opérations</td>\n",
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" <td>Lire le tableau et le graphique</td>\n",
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" <td>Lire le tableau et le graphique</td>\n",
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2018-02-09 03:02:48 +00:00
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" </tr>\n",
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" <tr>\n",
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2018-04-21 15:30:09 +00:00
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" <th>1</th>\n",
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" <td>5</td>\n",
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" <td></td>\n",
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" <td>0</td>\n",
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2018-02-09 03:02:48 +00:00
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" <td>1</td>\n",
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" <td>Cher</td>\n",
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" <td>Décomposer le problème</td>\n",
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" <td>Décomposer le problème</td>\n",
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" id name score_rate is_leveled exercise_id competence domain \\\n",
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"0 1 1 0 1 1 Cher Grandeurs \n",
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"1 2 2 0 1 1 Cal Grandeurs \n",
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"2 3 2.c 0 1 1 Cal Grandeurs \n",
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"1 5 0 1 2 Cher 4opérations \n",
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"\n",
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" comment Nom \n",
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"0 Lecture du thermomètre 1 Lecture du thermomètre \n",
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"1 Suivre programme de calculs 2 Suivre programme de calculs \n",
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"2 Renverser un programme de calculs 2.c Renverser un programme de calculs \n",
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"0 Lire le tableau et le graphique Lire le tableau et le graphique \n",
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"1 Décomposer le problème Décomposer le problème "
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" id name eval_id date comment\n",
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"0 1 1 - Prendre la température 1 2017-09-05 00:00:00.000000 \n",
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"1 2 2 - Maladroite! 1 2017-09-05 00:00:00.000000 "
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" <td></td>\n",
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" <td>Ex 1 - Prendre la température</td>\n",
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" <td>1</td>\n",
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" </tr>\n",
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" <td>2 - Maladroite!</td>\n",
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" <td>1</td>\n",
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" <td>2017-09-05 00:00:00.000000</td>\n",
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" <td></td>\n",
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" <td>Ex 2 - Maladroite!</td>\n",
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" score_rate competence id name eval_id \\\n",
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"0 0 Cher-Cal-Cal 1 1 - Prendre la température 1 \n",
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"1 0 Cher-Cher-Rai-Cal-Com 2 2 - Maladroite! 1 \n",
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"\n",
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" date comment Nom \\\n",
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"0 2017-09-05 00:00:00.000000 Ex 1 - Prendre la température \n",
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"1 2017-09-05 00:00:00.000000 Ex 2 - Maladroite! \n",
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"\n",
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" exercise_id \n",
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"0 1 \n",
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"1 2 "
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"source": [
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"ex_q = q_df.groupby(\"exercise_id\")\\\n",
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" .agg({\"score_rate\": np.sum, \"competence\": lambda x: '-'.join(list(x))}) \\\n",
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" <th>0</th>\n",
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" <td>1 Lecture du thermomètre</td>\n",
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" <td>Cher</td>\n",
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" <td>0</td>\n",
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" <td>2 Suivre programme de calculs</td>\n",
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2018-04-21 15:30:09 +00:00
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" <td>2.c Renverser un programme de calculs</td>\n",
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" <td>Ex 2 - Maladroite!</td>\n",
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" <th>0</th>\n",
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" <td>Lire le tableau et le graphique</td>\n",
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" <td>Cher</td>\n",
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" <td>0</td>\n",
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" <td>Décomposer le problème</td>\n",
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" <td>Cher</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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2018-04-21 15:30:09 +00:00
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" <th>2</th>\n",
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" <td>Manipuler les grandeurs</td>\n",
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" <td>Rai</td>\n",
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" <td>0</td>\n",
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" <td>2</td>\n",
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|
|
" <tr>\n",
|
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|
|
" <th>3</th>\n",
|
|
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|
|
" <td>Mener à bien les calculs</td>\n",
|
|
|
|
|
" <td>Cal</td>\n",
|
|
|
|
|
" <td>0</td>\n",
|
|
|
|
|
" <td>2</td>\n",
|
|
|
|
|
" </tr>\n",
|
|
|
|
|
" <tr>\n",
|
|
|
|
|
" <th>4</th>\n",
|
|
|
|
|
" <td>Rédaction</td>\n",
|
|
|
|
|
" <td>Com</td>\n",
|
|
|
|
|
" <td>0</td>\n",
|
|
|
|
|
" <td>2</td>\n",
|
2018-02-01 17:18:51 +00:00
|
|
|
" </tr>\n",
|
|
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|
|
" </tbody>\n",
|
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|
|
"</table>\n",
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"</div>"
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|
],
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|
"text/plain": [
|
2018-04-21 15:30:09 +00:00
|
|
|
" Nom competence score_rate \\\n",
|
|
|
|
|
"0 Ex 1 - Prendre la température Cher-Cal-Cal 0 \n",
|
|
|
|
|
"0 1 Lecture du thermomètre Cher 0 \n",
|
|
|
|
|
"1 2 Suivre programme de calculs Cal 0 \n",
|
|
|
|
|
"2 2.c Renverser un programme de calculs Cal 0 \n",
|
|
|
|
|
"1 Ex 2 - Maladroite! Cher-Cher-Rai-Cal-Com 0 \n",
|
|
|
|
|
"0 Lire le tableau et le graphique Cher 0 \n",
|
|
|
|
|
"1 Décomposer le problème Cher 0 \n",
|
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|
|
"2 Manipuler les grandeurs Rai 0 \n",
|
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|
"3 Mener à bien les calculs Cal 0 \n",
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|
"4 Rédaction Com 0 \n",
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|
"\n",
|
|
|
|
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" exercise_id \n",
|
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"0 1 \n",
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"0 1 \n",
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"1 1 \n",
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"2 1 \n",
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"1 2 \n",
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"0 2 \n",
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"1 2 \n",
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"2 2 \n",
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"3 2 \n",
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"4 2 "
|
2018-02-01 17:18:51 +00:00
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]
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},
|
2018-04-21 15:30:09 +00:00
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"execution_count": 85,
|
2018-02-01 17:18:51 +00:00
|
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"metadata": {},
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"output_type": "execute_result"
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}
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|
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|
|
],
|
|
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|
"source": [
|
2018-04-21 15:30:09 +00:00
|
|
|
"sel_fields = ['Nom', 'competence', 'score_rate', 'exercise_id']\n",
|
|
|
|
|
"xls_df = pd.concat([ex_q[sel_fields], q_df[sel_fields]]).sort_values(\"exercise_id\")\n",
|
|
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|
|
"xls_df"
|
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|
]
|
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|
},
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|
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{
|
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"cell_type": "code",
|
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|
"execution_count": 86,
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|
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"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"writer = pd.ExcelWriter(\"./test.xlsx\", engine=\"xlsxwriter\")\n",
|
|
|
|
|
"xls_df.to_excel(writer, index=False, sheet_name='DNB blanc 2')"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
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|
"cell_type": "code",
|
|
|
|
|
"execution_count": 87,
|
|
|
|
|
"metadata": {
|
|
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|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"workbook = writer.book\n",
|
|
|
|
|
"worksheet = writer.sheets['DNB blanc 2']"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
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|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 91,
|
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|
|
"metadata": {},
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|
|
|
|
"outputs": [
|
|
|
|
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{
|
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"data": {
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|
"text/plain": [
|
|
|
|
|
"0"
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|
]
|
|
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|
|
},
|
|
|
|
|
"execution_count": 91,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"first_line_format = workbook.add_format({\"align\": 'center', \"rotation\":90})\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"worksheet.set_column('A:D', 20)\n"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": null,
|
|
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": []
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": null,
|
|
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": []
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": null,
|
|
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": []
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 89,
|
|
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"writer.save()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"## Fait au DNB blanc 1"
|
2018-02-01 17:18:51 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 9,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
2018-02-09 03:02:48 +00:00
|
|
|
"wb = xlsxwriter.Workbook(\"DNB_BLANC_pro1.xlsx\")"
|
2018-02-01 17:18:51 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"Formatages"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 10,
|
|
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
2018-02-01 17:18:51 +00:00
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"eval_format = wb.add_format({'bold': True, 'font_color': 'red'})\n",
|
|
|
|
|
"eval_cell = wb.add_format()\n",
|
|
|
|
|
"eval_cell.set_bg_color(\"red\")\n",
|
|
|
|
|
"# exo_cell"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"La feuille de calcul"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 11,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"wb = xlsxwriter.Workbook(\"DS4_302.xlsx\")"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 12,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"ws = wb.add_worksheet()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"En tête du tableau"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 13,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"0"
|
|
|
|
|
]
|
|
|
|
|
},
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 13,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"ws.write(0,1,\"Competence\")\n",
|
|
|
|
|
"ws.write(0,2,\"Barème\")"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"Toutes les questions et exercices"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 14,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"def q_line(q, row, ws):\n",
|
|
|
|
|
" ws.write(row, 0, f\"{q.name} - {q.comment}\")\n",
|
|
|
|
|
" ws.write(row, 1, f\"{q.competence}\")\n",
|
|
|
|
|
" ws.write(row, 2, q.score_rate)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 15,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"def exo_block(exo, row, ws):\n",
|
|
|
|
|
" qrow = row\n",
|
|
|
|
|
" for q in exo[\"questions\"]:\n",
|
|
|
|
|
" qrow += 1\n",
|
|
|
|
|
" q_line(q, qrow, ws)\n",
|
|
|
|
|
" ws.write(row, 0, f\"Ex {exo['name']}\")\n",
|
|
|
|
|
" row_range = \", \".join([f\"C{i}\" for i in range(row+2, qrow+2)])\n",
|
|
|
|
|
" for i in range(30):\n",
|
|
|
|
|
" ws.write(row, i+2, f\"=SUM({row_range})\")\n",
|
|
|
|
|
" return qrow"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 16,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
2018-02-09 03:02:48 +00:00
|
|
|
"collapsed": true,
|
2018-02-01 17:18:51 +00:00
|
|
|
"scrolled": false
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"row = 2\n",
|
|
|
|
|
"exo_rows = []\n",
|
|
|
|
|
"for exo in ev.exercises:\n",
|
|
|
|
|
" exo_rows.append(row)\n",
|
|
|
|
|
" row = exo_block(exo, row, ws) + 1\n",
|
|
|
|
|
"ws.write(1,0, ev.name, eval_format)\n",
|
|
|
|
|
"exo_xls_range = \", \".join([f\"C{i+1}\" for i in exo_rows])\n",
|
|
|
|
|
"for i in range(30):\n",
|
|
|
|
|
" ws.write(1,i+2, f\"=SUM({exo_xls_range})\", eval_format)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 17,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"wb.close()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"# Avec openpyxl"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 13,
|
|
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
2018-02-01 17:18:51 +00:00
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"from openpyxl import Workbook\n",
|
|
|
|
|
"from openpyxl.styles import PatternFill, Border, Side, Alignment, Protection, Font, colors"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 14,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
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"'00FF0000'"
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]
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},
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2018-02-09 03:02:48 +00:00
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"execution_count": 14,
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2018-02-01 17:18:51 +00:00
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"colors.RED"
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|
|
]
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},
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{
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"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
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"execution_count": 15,
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2018-02-01 17:18:51 +00:00
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"wb = Workbook()"
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]
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},
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{
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"cell_type": "code",
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2018-02-09 03:02:48 +00:00
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"execution_count": 16,
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2018-02-01 17:18:51 +00:00
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"ws = wb.create_sheet(ev.name)"
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]
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},
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{
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"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
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"execution_count": 17,
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2018-02-01 17:18:51 +00:00
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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2018-02-09 03:02:48 +00:00
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"<Cell 'DNB blanc1'.C1>"
|
2018-02-01 17:18:51 +00:00
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]
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},
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2018-02-09 03:02:48 +00:00
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"execution_count": 17,
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2018-02-01 17:18:51 +00:00
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ws.cell(1,2,\"Competence\")\n",
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"ws.cell(1,3,\"Barème\")"
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]
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},
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{
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"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
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"execution_count": 18,
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"metadata": {
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"collapsed": true
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},
|
2018-02-01 17:18:51 +00:00
|
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"outputs": [],
|
|
|
|
|
"source": [
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|
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|
"def q_line(q, row, ws):\n",
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" ws.cell(row, 1, f\"{q.name} - {q.comment}\")\n",
|
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|
|
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" ws.cell(row, 2, f\"{q.competence}\")\n",
|
|
|
|
|
" ws.cell(row, 3, q.score_rate)"
|
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|
|
|
]
|
|
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|
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},
|
|
|
|
|
{
|
|
|
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|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 19,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
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},
|
|
|
|
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"outputs": [],
|
|
|
|
|
"source": [
|
|
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|
|
"def exo_block(exo, row, ws):\n",
|
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|
|
|
" qrow = row\n",
|
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|
|
" for q in exo[\"questions\"]:\n",
|
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|
" qrow += 1\n",
|
|
|
|
|
" q_line(q, qrow, ws)\n",
|
|
|
|
|
" ws.cell(row, 1, f\"Ex {exo['name']}\")\n",
|
|
|
|
|
" row_range = \", \".join([f\"C{i}\" for i in range(row+1, qrow+1)])\n",
|
|
|
|
|
" ws.cell(row, 3, f\"=SUM({row_range})\")\n",
|
|
|
|
|
" return qrow"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 20,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
2018-02-09 03:02:48 +00:00
|
|
|
"<Cell 'DNB blanc1'.C2>"
|
2018-02-01 17:18:51 +00:00
|
|
|
]
|
|
|
|
|
},
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 20,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"row = 3\n",
|
|
|
|
|
"exo_rows = []\n",
|
|
|
|
|
"for exo in ev.exercises:\n",
|
|
|
|
|
" exo_rows.append(row)\n",
|
|
|
|
|
" row = exo_block(exo, row, ws) + 1\n",
|
|
|
|
|
"eval_row = ws.row_dimensions[2]\n",
|
|
|
|
|
"eval_row.fill = PatternFill(bgColor=colors.RED)\n",
|
|
|
|
|
"ws.cell(2,1, ev.name)\n",
|
|
|
|
|
"exo_xls_range = \", \".join([f\"C{i}\" for i in exo_rows])\n",
|
|
|
|
|
"ws.cell(2,3, f\"=SUM({exo_xls_range})\")"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2018-02-09 03:02:48 +00:00
|
|
|
"execution_count": 21,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"'302'"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"execution_count": 21,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"ev.tribe"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 22,
|
2018-02-01 17:18:51 +00:00
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
2018-02-09 03:02:48 +00:00
|
|
|
"wb.save(f\"./{ev.name}-{ev.tribe}.xlsx\")"
|
2018-02-01 17:18:51 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": null,
|
|
|
|
|
"metadata": {
|
|
|
|
|
"collapsed": true
|
|
|
|
|
},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": []
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"metadata": {
|
|
|
|
|
"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": "3.6.4"
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
"nbformat": 4,
|
|
|
|
|
"nbformat_minor": 2
|
|
|
|
|
}
|
