292 lines
10 KiB
Python
292 lines
10 KiB
Python
""" Modelisation des gymnastes """
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from datetime import date
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from django.contrib.auth import get_user_model
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from django.db.models import Count
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from django.db import models
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import pendulum
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from jarvis.core.global_vars import GENDER_CHOICES, ORIENTATION_CHOICES
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from jarvis.objective.models import Skill
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# from jarvis.profiles.models import TrainerGymnast
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from jarvis.tools.models import Markdownizable
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from jarvis.objective.tools import (
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nb_skill_by_type,
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nb_skill_lte_type,
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compute_completude,
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compute_statistics_by_type,
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)
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from jarvis.tools.clean_name import clean_name
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User = get_user_model()
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class Gymnast(Markdownizable):
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"""Représente un gymnaste.
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Un gymnaste peut être actif ou inactif.
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"""
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class Meta:
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verbose_name = "Gymnast"
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verbose_name_plural = "Gymnasts"
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ordering = ["first_name", "last_name"]
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user = models.OneToOneField(
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User, on_delete=models.SET_NULL, related_name="gymnast", blank=True, null=True
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)
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last_name = models.CharField(max_length=40, null=False, blank=False)
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cleaned_last_name = models.CharField(max_length=40, null=False, blank=False)
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first_name = models.CharField(max_length=25, null=False, blank=False)
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cleaned_first_name = models.CharField(max_length=25, null=False, blank=False)
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birthdate = models.DateField(verbose_name="Birth date")
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gender = models.PositiveSmallIntegerField(
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choices=GENDER_CHOICES, verbose_name="Sexe"
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)
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is_active = models.BooleanField(default=1, verbose_name="Active")
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year_of_practice = models.PositiveSmallIntegerField(default=0)
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orientation = models.PositiveSmallIntegerField(
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choices=ORIENTATION_CHOICES,
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null=True,
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blank=True,
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verbose_name="Twist side",
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)
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email_trainer = models.EmailField(
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max_length=254, null=True, blank=True, verbose_name="Trainer's email"
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)
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created_at = models.DateTimeField(auto_now_add=True)
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trainers = models.ManyToManyField(
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User,
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through="profiles.TrainerGymnast",
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through_fields=("gymnast", "user"),
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related_name="gymnasts",
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)
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def save(self, *args, **kwargs):
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"""Sauve les informations de la personne et initialise les champs nettoyés."""
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self.cleaned_last_name = clean_name(self.last_name)
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self.cleaned_first_name = clean_name(self.first_name)
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super().save(*args, **kwargs)
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def __str__(self):
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return f"{self.first_name} {self.last_name}"
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@property
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def next_birthday(self):
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"""Définit la prochaine date (de fête) d'anniversaire pour cette personne.
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Returns:
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Soit le jour/mois pour cette année
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Soit le jour/mois pour l'année prochaine.
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Example: (en supposant qu'on soit le 23/05/2019)
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>>> from datetime import date
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>>> gymnast = Gymnast(name='Tru', firstname='Gregg', birthdate=date(1982, 2, 5))
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>>> gymnast.next_birthday()
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Date(2020, 2, 5)
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"""
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now = pendulum.now()
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this_year_birthday = pendulum.date(
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now.year, self.birthdate.month, self.birthdate.day
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)
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if this_year_birthday.is_past():
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return pendulum.date(now.year + 1, self.birthdate.month, self.birthdate.day)
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return this_year_birthday
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@property
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def next_birthday_in_days(self):
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now = pendulum.now()
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return self.next_birthday.diff(now).in_days()
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@property
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def age(self):
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"""Renvoie l'âge d'un gymnaste."""
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# TODO: utiliser pendulum.age : age = pendulum.datetime(1985, 7, 3).age
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today = date.today()
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return (
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today.year
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- self.birthdate.year
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- ((today.month, today.day) < (self.birthdate.month, self.birthdate.day))
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)
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@property
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def next_age(self):
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"""Renvoie l'âge prochain du gymnaste."""
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return (self.age) + 1
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def skill_max_for_type(self, desired_type="level"):
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"""
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Renvoie le niveau/rank maximum des skill que le gymnaste sait faire suivant le type passé
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en paramètre.
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Args:
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desired_type (string): type ("level" ou "rank") des Skills désirés.
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Returns:
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int
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Examples:
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>>> from jarvis.people.models import Gymnast
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>>> gymnast = Gymnast.objects.get(pk=1)
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>>> gymnast.skill_max_for_type("level")
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1
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>>> gymnast.skill_max_for_type("rank")
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19
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"""
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if desired_type not in ("level", "rank"):
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return None
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tmp = (
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Skill.objects.filter(known_by__gymnast=self.id)
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.order_by("-" + desired_type)
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.values(desired_type)[:1]
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)
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if tmp:
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skill_max = tmp[0][desired_type]
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else:
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skill_max = 0
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return skill_max
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def nb_known_skill_by_type(self, desired_type="level"):
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"""
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Renvoie le nombre de Skill qu'un gymnast sait faire par niveau/rang suivant le type passé
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en paramètre
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Args:
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desired_type (string): type ("level" ou "rank") des Skills désirés.
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Returns:
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QuerySet
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Examples:
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>>> from jarvis.people.models import Gymnast
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>>> gymnast = Gymnast.objects.get(pk=1)
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>>> gymnast.nb_known_skill_by_type("level")
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<QuerySet [{'level': 0, 'nb_known_skill': 15}, {'level': 1, 'nb_known_skill': 5}]>
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>>> gymnast.nb_known_skill_by_type("rank")
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<QuerySet [{'rank': 1, 'nb_known_skill': 2}, {'rank': 2, 'nb_known_skill': 4}, …]>
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"""
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if desired_type not in ("level", "rank"):
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return None
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nb_known_skill_by_type = (
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Skill.objects.values(desired_type)
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.filter(known_by__gymnast=self.id)
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.order_by(desired_type)
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.annotate(nb_known_skill=Count("id"))
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)
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return nb_known_skill_by_type
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def unknown_skill_lte_level(self, max_level_skill):
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"""
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Liste des Skill que le gymnaste ne sait PAS faire/
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Ces skills sont classé par niveau.
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"""
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return Skill.objects.filter(level__lte=max_level_skill).exclude(
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known_by__gymnast=self.id
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)
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def unknown_skill_gt_level(self, max_level_skill):
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"""
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Liste des Skill que le gymnaste ne sait PAS faire,
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classé par niveau (ayant un niveau inférieur ou égal au niveau max du gym)
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"""
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return Skill.objects.filter(level__gt=max_level_skill).exclude(
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known_by__gymnast=self.id
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)
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def unknown_skill_lte_rank(self, max_rank_skill):
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# Liste des Skill que le gymnaste ne sait PAS faire, classé par niveau
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# (ayant un niveau inférieur ou égal au niveau max du gym)
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return Skill.objects.filter(level__lte=max_rank_skill).exclude(
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known_by__gymnast=self.id
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)
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def unknown_skill_gt_rank(self, max_rank_skill):
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"""
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Liste des Skill que le gymnaste ne sais PAS faire
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(ayant un niveau plus grand que le niveau max du gym)
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"""
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return Skill.objects.filter(level__gt=max_rank_skill).exclude(
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known_by__gymnast=self.id
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)
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def get_informations_from_type(self, desired_type="level"):
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"""
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Calcule toutes les statistiques par rapport au niveau/rang suivant le paramètre transmis.
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1. On va chercher le type (niveau ou rang) maximum de skill que le gymnast sait faire
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2. 0n va chercher le nombre de skill par niveau/rang que le gymnast sait faire
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nb_known_skill_by_type = [
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{
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'level': 1,
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'nb_known_skill': 1
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},
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{
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'level': 2,
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'nb_known_skill': 2
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}
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]
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3. Si le niveau/rang maximum est supérieur à 0:
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a. on va chercher le nombre de skill qu'il y a par niveau/rang :
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[
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{
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'level': 1, 'nb_skill': 1
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},
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{
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'level': 2, 'nb_skill': 1
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}
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]
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b. on va chercher le nombre total des skills dont le niveau/rang est inférieur ou
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égale au niveau max.
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c. on calcule les statistiques du gymnaste par rapport aux skill
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SINON:
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on va chercher tous les Skill qui existent et on les compte.
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"""
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if desired_type not in ("level", "rank"):
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return None
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context = {}
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skill_max = self.skill_max_for_type(desired_type)
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gymnast_nb_known_skills = self.known_skills.distinct("skill").count()
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context["gymnast_nb_known_skills"] = gymnast_nb_known_skills
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if skill_max > 0:
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cpt_known_skill_by_type = self.nb_known_skill_by_type(
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desired_type
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) # à remonter ???
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cpt_skill_by_type = nb_skill_by_type(skill_max, desired_type)
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context["total_skill"] = nb_skill_lte_type(skill_max, desired_type)
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context["percentages"] = compute_statistics_by_type(
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cpt_skill_by_type, cpt_known_skill_by_type, desired_type
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)
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context["skill_by_level"] = self.unknown_skill_lte_level(skill_max)
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context["unknown_skill"] = self.unknown_skill_gt_level(skill_max)
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else:
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tmp = Skill.objects.all()
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context["total_skill"] = tmp.count()
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context["unknown_skill"] = tmp
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context["percentages"] = 0
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context["completude"], context["estimated_level"], context["percentage_known_skill"] = compute_completude(
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context["total_skill"], gymnast_nb_known_skills, skill_max
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)
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# print(context["percentage_known_skill"])
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# print(context["gymnast_nb_known_skills"])
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# print(context["completude"])
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# print(context["estimated_level"])
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context["max_" + desired_type + "_skill"] = skill_max
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return context
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