#!/usr/bin/env python
# encoding: utf-8

import pandas as pd
import numpy as np

class Student(object):

    """ 
    Informations on a student which can be use inside template.
    
    Those informations should not be modify or use for compute analysis otherwise they won't be spread over other POV.
    """

    def __init__(self, quest_df, exo_df, eval_df):
        """ 
        Description of a student from quest, exo and eval

        """

        name = {*quest_df["Eleve"].unique(),
                *exo_df["Eleve"].unique(),
                *eval_df["Eleve"].unique(),
                }

        if len(name) != 1:
            raise ValueError("Can't initiate Student: dfs contains different student names")

        self.name = name.pop()

        evalname = {*quest_df["Nom"].unique(),
                *exo_df["Nom"].unique(),
                *eval_df["Nom"].unique(),
                }

        if len(evalname) != 1:
            raise ValueError(f"Can't initiate Student: dfs contains different evaluation names ({'-'.join(evalname)})")

        self.quest_df = quest_df
        self.exo_df = exo_df
        self.eval = eval_df.to_dict('records')[0]

    @property
    def latex_exo_tabulars(self):
        """ Return list of latex tabulars. One by exercise of the evaluation """
        try:
            self._latex_exo_tabulars
        except AttributeError:
            self._latex_exo_tabulars = self.build_latex_exo_tabulars()
        return self._latex_exo_tabulars

    def build_latex_exo_tabulars(self):
        tabulars = []
        for t in self.exo_df["Exercice"]:
            tabulars.append(self.build_latex_exo_tabular(t))

        return tabulars

    def build_latex_exo_tabular(self, exo_name):
        exo = self.exo_df[self.exo_df["Exercice"] == exo_name]
        quest = self.quest_df[self.quest_df["Exercice"] == exo_name]

        tabular = [r"\begin{tabular}{|p{2cm}|c|}"]
        tabular.append(r"\hline")

        if type(exo_name) == int:
            tabular.append(f"Exercice {exo_name} & {exo['Mark_barem'].all()} \\\\")
        else:
            tabular.append(f"{exo_name} & {exo['Mark_barem'].all()} \\\\")
        tabular.append(r"\hline")

        if len(quest) > 1:
            for _, q in quest.iterrows():
                line = ""
                if not pd.isnull(q["Question"]):
                    line += str(q['Question'])
                if not pd.isnull(q["Commentaire"]):
                    line += str(q['Commentaire'])

                line += " & "
                if q["Niveau"] == 1:
                    line += q['Latex_rep']
                else:
                    line += str(q['Mark'])
                line += r"\\"
                tabular.append(line)
                tabular.append(r"\hline")

        tabular.append(r"\end{tabular}")
        return '\n'.join(tabular)

class Classe(object):

    """ 
    Informations on a class which can be use inside template.
    
    Those informations should not be modify or use for compute analysis otherwise they won't be spread over other POV.
    """
    pass

# TODO: à factoriser Il y a la même dans term.py |jeu. mars 23 19:36:28 EAT 2017
def select(quest_df, exo_df, eval_df, index, value):
    """ Return quest, exo and eval rows which correspond index == value

    :param quest_df: TODO
    :param exo_df: TODO
    :param eval_df: TODO

    """
    qu = quest_df[quest_df[index] == value]
    exo = exo_df[exo_df[index] == value]
    ev = eval_df[eval_df[index] == value]
    return qu, exo, ev

def select_contains(quest_df, exo_df, eval_df, index, name_part):
    """ Return quest, exo and eval rows which contains name_part

    :param quest_df: TODO
    :param exo_df: TODO
    :param eval_df: TODO

    """
    qu = quest_df[quest_df[index].str.contains(name_part)]
    exo = exo_df[exo_df[index].str.contains(name_part)]
    ev = eval_df[eval_df[index].str.contains(name_part)]
    return qu, exo, ev

def students_pov(quest_df, exo_df, eval_df):
    es = []
    for e in eval_df["Eleve"].unique():
        d = select(quest_df, exo_df, eval_df, "Eleve", e)
        eleve = Student(*d)
        es.append(eleve)
    return es

def class_pov(quest_df, exo_df, eval_df):
    return Classe(quest_df, exo_df, eval_df)



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