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"""initial
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Revision ID: 3c651a0d1fe0
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Revises:
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Create Date: 2023-10-27 18:19:47.402501
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"""
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import random
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import time
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from datetime import datetime, timedelta
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from alembic import op
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import sqlalchemy as sa
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# revision identifiers, used by Alembic.
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revision = '3c651a0d1fe0'
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down_revision = None
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branch_labels = None
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depends_on = None
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def generate_normal_random(mean, std_dev):
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return int(random.gauss(mean, std_dev))
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def upgrade():
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# ### commands auto generated by Alembic - please adjust! ###
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op.create_table('camera',
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sa.Column('camera_type', sa.String(), nullable=False),
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sa.Column('order_numb', sa.Integer(), nullable=True),
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sa.Column('id', sa.Integer(), autoincrement=True, nullable=False),
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sa.Column('created_at', sa.TIMESTAMP(), server_default=sa.text('CURRENT_TIMESTAMP'),
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nullable=False),
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sa.Column('updated_at', sa.TIMESTAMP(), server_default=sa.text('CURRENT_TIMESTAMP'),
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nullable=False),
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sa.PrimaryKeyConstraint('id', name=op.f('pk_camera')),
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sa.UniqueConstraint('id', name=op.f('uq_camera_id')),
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sa.UniqueConstraint('order_numb', name=op.f('uq_camera_order_numb'))
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)
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op.create_table('conveer',
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sa.Column('wood', sa.Integer(), nullable=True),
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sa.Column('metal', sa.Integer(), nullable=True),
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sa.Column('glass', sa.Integer(), nullable=True),
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sa.Column('plastic', sa.Integer(), nullable=True),
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sa.Column('camera_id', sa.Integer(), nullable=False),
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sa.Column('id', sa.Integer(), autoincrement=True, nullable=False),
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sa.Column('created_at', sa.TIMESTAMP(), server_default=sa.text('CURRENT_TIMESTAMP'),
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nullable=False),
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sa.Column('updated_at', sa.TIMESTAMP(), server_default=sa.text('CURRENT_TIMESTAMP'),
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nullable=False),
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sa.ForeignKeyConstraint(['camera_id'], ['camera.id'], name=op.f('fk_conveer_camera_id_camera')),
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sa.PrimaryKeyConstraint('id', name=op.f('pk_conveer')),
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sa.UniqueConstraint('id', name=op.f('uq_conveer_id'))
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)
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op.execute('''INSERT INTO camera(id,order_numb, camera_type) VALUES (1,1, 'По умолчанию')''')
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import random
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from datetime import datetime, timedelta
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# Устанавливаем параметры нормального распределения
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mean_metal = 10 # Среднее значение для металла
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std_dev_metal = 3 # Стандартное отклонение для металла
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mean_glass = 5 # Среднее значение для стекла
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std_dev_glass = 2 # Стандартное отклонение для стекла
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mean_plastic = 7.5 # Среднее значение для пластика
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std_dev_plastic = 2.5 # Стандартное отклонение для пластика
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mean_wood = 15 # Среднее значение для дерева
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std_dev_wood = 5 # Стандартное отклонение для дерева
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for _ in range(0, 10):
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random_date = datetime.now() - timedelta(days=random.randint(1, 365))
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# Генерируем случайные значения, следующие нормальному распределению
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metal = generate_normal_random(mean_metal, std_dev_metal)
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glass = generate_normal_random(mean_glass, std_dev_glass)
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plastic = generate_normal_random(mean_plastic, std_dev_plastic)
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wood = generate_normal_random(mean_wood, std_dev_wood)
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# Далее вы можете выполнить ваш SQL-запрос с этими случайными значениями
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op.execute(f'''INSERT INTO conveer (metal, glass, plastic, wood, camera_id, created_at)
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VALUES ({metal}, {glass}, {plastic}, {wood}, 1, '{random_date}');''')
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def downgrade():
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# ### commands auto generated by Alembic - please adjust! ###
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op.drop_table('conveer')
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op.drop_table('camera')
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# ### end Alembic commands ###
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