ロードマップ4: Djangoで作る競馬予想AIモデル分析ソフト part2

from django.db import models
############# ここから下を追加 ###############
from datetime import datetime

# Create your models here.


class ModelList(models.Model):
    model_id = models.CharField(
        verbose_name="モデルID", max_length=64)
    model_name = models.CharField(
        verbose_name="モデル名", max_length=64, null=False, blank=False, default="No model name")
    model_type = models.CharField(
        verbose_name="モデル種別", max_length=64, null=False, blank=False)
    model_dir = models.CharField(
        verbose_name="モデルパス", max_length=256, null=False, blank=False)
    model_analyze_dir = models.CharField(verbose_name="分析結果パス",
                                         max_length=256, null=False, blank=False)
    model_predict_dir = models.CharField(verbose_name="推論結果パス",
                                         max_length=256, null=False, blank=False)
    bet_columns_map = models.JSONField(
        verbose_name="馬券カラムマップ", null=False, blank=False)
    pl_column_map = models.JSONField(
        verbose_name="収支カラムマップ", null=False, blank=False)
    return_hit_rate_file = models.JSONField(
        verbose_name="馬券別回収率と的中率マップ", null=False, blank=False)
    fav_bet_num_dir = models.JSONField(
        verbose_name="馬券別人気ごとベット回数マップ", null=False, blank=False)
    profit_loss_dir = models.JSONField(
        verbose_name="馬券別収支データマップ", null=False, blank=False)
    odds_graph_file = models.JSONField(
        verbose_name="馬券別オッズグラフマップ", null=False, blank=False)
    confidence_column = models.CharField(verbose_name="確信度カラム",
                                         max_length=64, null=False, blank=False)
    confidence_rank_column = models.CharField(verbose_name="確信度ランクカラム",
                                              max_length=64, null=False, blank=False)
    motivate = models.TextField(
        verbose_name="モデル説明", max_length=1024, blank=False)
    memo = models.TextField(verbose_name="備考", max_length=1024, blank=True)
    regist_date = models.DateTimeField(
        verbose_name="登録日", default=datetime.now)

    @staticmethod
    def get_serializer_field_list(exclude=["regist_date"]):
        fields_meta = ModelList._meta.get_fields()

        serialize_field_list = []
        for i, meta_field in enumerate(fields_meta):
            if i > 0 and meta_field.name not in exclude:
                serialize_field_list.append(meta_field.name)
        return serialize_field_list

    @staticmethod
    def get_forms_field_list(include=["model_name", "motivate", "memo"]):
        fields_meta = ModelList._meta.get_fields()

        forms_field_list = []
        for i, meta_field in enumerate(fields_meta):
            if i > 0 and meta_field.name in include:
                forms_field_list.append(meta_field.name)
        return forms_field_list

# 新規作成
from django import forms
from django.core.validators import FileExtensionValidator
from .models import ModelList


class ModelImportForms(forms.Form):
    model_name = forms.CharField(
        label="モデル名",
        required=True
    )
    motivate = forms.CharField(
        widget=forms.Textarea,
        label="モデルの説明",
        required=True
    )
    memo = forms.CharField(widget=forms.Textarea, label="備考")
    model_info_json = forms.FileField(
        label="モデル情報ファイル",
        required=True,
        validators=[FileExtensionValidator(['json', ])]
    )


class ModelListForms(forms.ModelForm):
    class Meta:
        model = ModelList
        fields = ModelList.get_serializer_field_list()

from django.shortcuts import render
from django.views import View
from django.views.generic import FormView # 追加
from .models import ModelList # 追加
from .forms import ModelImportForms, ModelListForms # 追加
import json # 追加

# Create your views here.
～～～省略～～～

class ModelManageView(View):
　　 # 追加
    nav_params = {
        "model_analyze": True,
        "model_manage": False
    }

    def get(self, request):
        # print(ModelList.get_serializer_field_list())
        form = ModelImportForms()　 # 追加
        self.nav_params |= {"form": form}　 # 追加
        return render(request, 'model_manage.html', self.nav_params)　 # 追加

　　 # 以下を追加
    def post(self, request):
        form = ModelImportForms(request.POST, request.FILES)
        if form.is_valid():
            model_info = json.loads(
                form.cleaned_data.pop("model_info_json").read())
            form.cleaned_data |= model_info
            model_form = ModelListForms(form.cleaned_data)
            if model_form.is_valid():
                model_form.save()
            else:
                print(model_form.errors)
                self.nav_params |= {"model_form": model_form, "form": form}
        else:
            self.nav_params |= {"form": form}

        return render(request, 'model_manage.html', self.nav_params)

{% extends "base_layout.html" %}
{% block content %}
<div class="list-item">
    <h3>モデルインポート</h3>
    {% if form.errors %}
    <ul>
        {% for error in form.errors %}
        <li>{{ error }}</li><!--form内にエラーがある際に表示させる-->
        {% endfor %}
    </ul>
    {% endif %}
    {% if model_form.errors %}
    <h4>Upload Json File Error!!</h4>
    {{ model_form.errors }}
    {% endif %}
    <form class="" action="" method="post" enctype="multipart/form-data">
        {% csrf_token %}
        <table>{{ form.as_table }}</table>
        <button type="submit" class="btn btn-primary">送信</button>
    </form>
</div>
{% endblock %}

{
  "model_id": "first_model",
  "model_type": "lightGBM",
  "model_dir": "E:\\keiba_dev\\keiba_ai\\models\\first_model",
  "model_analyze_dir": "E:\\keiba_dev\\keiba_ai\\models\\first_model\\analyze",
  "model_predict_dir": "E:\\keiba_dev\\keiba_ai\\models\\first_model\\analyze\\00_predict",
  "bet_columns_map": {
    "tan": "bet_tan"
  },
  "pl_column_map": {
    "tan": "pl_tan"
  },
  "return_hit_rate_file": {
    "tan": "E:\\keiba_dev\\keiba_ai\\models\\first_model\\analyze\\tan\\hit_and_return_rate.csv"
  },
  "fav_bet_num_dir": {
    "tan": "E:\\keiba_dev\\keiba_ai\\models\\first_model\\analyze\\tan\\fav_bet_num"
  },
  "profit_loss_dir": {
    "tan": "E:\\keiba_dev\\keiba_ai\\models\\first_model\\analyze\\tan\\profit_loss"
  },
  "odds_graph_file": {
    "tan": "E:\\keiba_dev\\keiba_ai\\models\\first_model\\analyze\\tan\\odds_graph"
  },
  "confidence_column": "pred_prob",
  "confidence_rank_column": "pred_rank"
}