python

# Optional: custom error handlers
handler404 = 'myapp.views.custom_404'
handler500 = 'myapp.views.custom_500'


# In views.py

from django.contrib import admin
from django.utils.html import format_html
from .models import Post, Comment


class CommentInline(admin.TabularInline):

from sklearn.linear_model import LinearRegression, Ridge, Lasso, ElasticNet
from sklearn.metrics import mean_absolute_error, root_mean_squared_error

models = {
    'linear': LinearRegression(),
    'ridge': Ridge(alpha=1.0),

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

train_df = pd.read_parquet('train_features.parquet')
prod_df = pd.read_parquet('production_features.parquet')

from datasets import Dataset
from transformers import AutoTokenizer, AutoModelForSequenceClassification, TrainingArguments, Trainer

model_name = 'distilbert-base-uncased'
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name, num_labels=3)

from django import template
from django.utils.safestring import mark_safe
import markdown

register = template.Library()

import time
import logging

logger = logging.getLogger(__name__)

import pandas as pd
from sklearn.compose import ColumnTransformer
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import OneHotEncoder, StandardScaler

import numpy as np
from sklearn.metrics import confusion_matrix

probabilities = model.predict_proba(X_valid)[:, 1]
thresholds = np.linspace(0.1, 0.9, 9)

INSTALLED_APPS += ['tenant_schemas']

DATABASE_ROUTERS = ['tenant_schemas.routers.TenantSyncRouter']

MIDDLEWARE = [
    'tenant_schemas.middleware.TenantMiddleware',

import numpy as np
from scipy import stats

control = np.array([21.1, 20.5, 19.9, 22.0, 20.8, 21.4])
treatment = np.array([22.8, 23.0, 22.2, 24.1, 23.5, 22.9])

from django.db.models import Q
from django.views.generic import ListView
from .models import Product


class ProductSearchView(ListView):