129 lines
3.9 KiB
Python
Executable File
129 lines
3.9 KiB
Python
Executable File
#!/usr/bin/env python
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# encoding: utf-8
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from notes_tools.tools import extract_flat_marks, get_class_ws, digest_flat_df, students_pov
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from .texenv import texenv
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import pandas as pd
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import numpy as np
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import xlrd
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from path import Path
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notStudent = ["Trimestre", "Nom", "Date", "Exercice", "Question", "Competence", "Domaine", "Commentaire", "Bareme", "Niveau"]
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def extract_students(df, notStudent = notStudent):
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""" Extract the list of students from df """
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students = df.columns.difference(notStudent)
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return students
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def build_students(df1, df2, notStudent = notStudent):
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""" Build students list """
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students_from_notes = extract_students(df1, notStudent)
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students_from_conn = extract_students(df2, notStudent)
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if students_from_conn.equals(students_from_notes):
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return students_from_conn
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else:
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raise ValueError("Not same list of students between df1 = {} ans df2 = {}".format(df1, df2))
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def flat_df_students(df, students):
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""" Flat the ws for students """
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flat_df = pd.DataFrame()
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flat_data = []
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dfT = df.T
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for n in dfT:
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pre_di = dfT[n][notStudent].to_dict()
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for e in students:
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data = pre_di.copy()
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data["Eleve"] = e
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data["Note"] = dfT[n].loc[e]
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flat_data.append(data)
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return pd.DataFrame.from_dict(flat_data)
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def select_ds(ds_name, flat_df):
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"""TODO: Docstring for select_ds.
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:param ds_name: TODO
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:param flat_df: TODO
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:returns: TODO
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"""
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ds = flat_df[flat_df["Nom"] == ds_name]
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if len(ds) == 0:
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raise ValueError("{} is not a registered evaluation".format(ds_name))
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return ds
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def build_ds_info(classe, ds_df):
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"""TODO: Docstring for build_ds_info.
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:param ds_df: TODO
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:returns: TODO
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# TODO: vérifier que toutes ces informations soient identiques sur les lignes |dim. nov. 6 16:06:58 EAT 2016
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"""
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ds_info = {}
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ds_info["Classe"] = classe
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ds_info["Nom"] = ds_df["Nom"].unique()[0]
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ds_info["Date"] = pd.to_datetime(ds_df["Date"].unique()[0]).strftime("%d-%m-%Y")
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ds_info["Trimestre"] = ds_df["Trimestre"].unique()[0]
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return ds_info
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def build_target_name(classe, ds_name, path = Path("./")):
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""" Build the path where the .tex will be sored
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>>> build_target_name("312", "DS1")
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Path('./312/bilan_DS1.tex')
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>>> build_target_name("312", "DS1", Path("plop/"))
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Path('plop/312/bilan_DS1.tex')
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"""
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return Path(path + classe + "/bilan_" + ds_name + ".tex")
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def feed_bilan(target, datas, template = "tpl_bilan.tex"):
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""" Get the template and feed it to create bilans
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:param target: path where the bilan will be saved
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:param datas: dictonnary to feed the template
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:param template: the template
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"""
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bilan = texenv.get_template(template)
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path_to_target = target.dirname()
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if not path_to_target.exists():
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path_to_target.mkdir()
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with open(target, "w") as f:
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f.write(bilan.render(**datas))
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print("{} est construit! Ya plus qu'à compiler!".format(target))
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def generate_bilan(classe, ds_name, path = Path('./'), template = "tpl_bilan.tex"):
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""" Generate the bilan of a evaluation for a class
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:param classe: the classe name
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:param ds_name: name of the evaluation
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:param path: path where xlsx are stored
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:param template: template for the bilan
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"""
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ws = get_class_ws(classe, path)
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flat_df = extract_flat_marks(ws)
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quest_df, exo_df, eval_df = digest_flat_df(flat_df)
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quest_df = select_ds(ds_name, quest_df)
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exo_df = select_ds(ds_name, exo_df)
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eval_df = select_ds(ds_name, eval_df)
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ds_info = build_ds_info(classe, eval_df)
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students_df = students_pov(quest_df, exo_df, eval_df)
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datas = {"ds_info": ds_info, "students":students_df}
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target = build_target_name(classe, ds_name, path)
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feed_bilan(target, datas, template)
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# -----------------------------
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# Reglages pour 'vim'
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# vim:set autoindent expandtab tabstop=4 shiftwidth=4:
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# cursor: 16 del
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