before claude
This commit is contained in:
Gilles Soulier
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"""Ajout champs Amazon produit
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Revision ID: 0014e51c4927
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Revises: 20260115_02_product_details
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Create Date: 2026-01-17 19:23:01.866891
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"""
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from alembic import op
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import sqlalchemy as sa
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from sqlalchemy.dialects import postgresql
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# Revision identifiers, used by Alembic.
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revision = '0014e51c4927'
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down_revision = '20260115_02_product_details'
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branch_labels = None
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depends_on = None
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def upgrade() -> None:
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# ### commands auto generated by Alembic - please adjust! ###
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op.alter_column('price_history', 'price',
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existing_type=sa.NUMERIC(precision=10, scale=2),
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comment='Product price',
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existing_nullable=True)
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op.alter_column('price_history', 'shipping_cost',
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existing_type=sa.NUMERIC(precision=10, scale=2),
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comment='Shipping cost',
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existing_nullable=True)
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op.alter_column('price_history', 'stock_status',
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existing_type=sa.VARCHAR(length=20),
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comment='Stock status (in_stock, out_of_stock, unknown)',
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existing_nullable=True)
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op.alter_column('price_history', 'fetch_method',
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existing_type=sa.VARCHAR(length=20),
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comment='Fetch method (http, playwright)',
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existing_nullable=False)
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op.alter_column('price_history', 'fetch_status',
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existing_type=sa.VARCHAR(length=20),
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comment='Fetch status (success, partial, failed)',
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existing_nullable=False)
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op.alter_column('price_history', 'fetched_at',
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existing_type=postgresql.TIMESTAMP(),
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comment='Scraping timestamp',
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existing_nullable=False)
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op.alter_column('product_images', 'image_url',
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existing_type=sa.TEXT(),
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comment='Image URL',
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existing_nullable=False)
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op.alter_column('product_images', 'position',
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existing_type=sa.INTEGER(),
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comment='Image position (0=main)',
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existing_nullable=False)
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op.alter_column('product_specs', 'spec_key',
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existing_type=sa.VARCHAR(length=200),
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comment="Specification key (e.g., 'Brand', 'Color')",
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existing_nullable=False)
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op.alter_column('product_specs', 'spec_value',
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existing_type=sa.TEXT(),
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comment='Specification value',
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existing_nullable=False)
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op.add_column('products', sa.Column('rating_value', sa.Numeric(precision=3, scale=2), nullable=True, comment='Note moyenne'))
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op.add_column('products', sa.Column('rating_count', sa.Integer(), nullable=True, comment="Nombre d'evaluations"))
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op.add_column('products', sa.Column('amazon_choice', sa.Boolean(), nullable=True, comment="Badge Choix d'Amazon"))
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op.add_column('products', sa.Column('amazon_choice_label', sa.Text(), nullable=True, comment="Libelle Choix d'Amazon"))
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op.add_column('products', sa.Column('discount_text', sa.Text(), nullable=True, comment='Texte de reduction affiche'))
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op.add_column('products', sa.Column('stock_text', sa.Text(), nullable=True, comment='Texte brut du stock'))
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op.add_column('products', sa.Column('in_stock', sa.Boolean(), nullable=True, comment='Disponibilite derivee'))
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op.add_column('products', sa.Column('model_number', sa.Text(), nullable=True, comment='Numero du modele'))
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op.add_column('products', sa.Column('model_name', sa.Text(), nullable=True, comment='Nom du modele'))
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op.alter_column('products', 'source',
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existing_type=sa.VARCHAR(length=50),
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comment='Store ID (amazon, cdiscount, etc.)',
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existing_nullable=False)
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op.alter_column('products', 'reference',
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existing_type=sa.VARCHAR(length=100),
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comment='Product reference (ASIN, SKU, etc.)',
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existing_nullable=False)
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op.alter_column('products', 'url',
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existing_type=sa.TEXT(),
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comment='Canonical product URL',
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existing_nullable=False)
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op.alter_column('products', 'title',
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existing_type=sa.TEXT(),
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comment='Product title',
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existing_nullable=True)
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op.alter_column('products', 'category',
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existing_type=sa.TEXT(),
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comment='Product category (breadcrumb)',
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existing_nullable=True)
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op.alter_column('products', 'description',
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existing_type=sa.TEXT(),
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comment='Product description',
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existing_nullable=True)
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op.alter_column('products', 'currency',
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existing_type=sa.VARCHAR(length=3),
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comment='Currency code (EUR, USD, GBP)',
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existing_nullable=True)
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op.alter_column('products', 'msrp',
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existing_type=sa.NUMERIC(precision=10, scale=2),
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comment='Recommended price',
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existing_nullable=True)
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op.alter_column('products', 'first_seen_at',
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existing_type=postgresql.TIMESTAMP(),
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comment='First scraping timestamp',
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existing_nullable=False)
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op.alter_column('products', 'last_updated_at',
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existing_type=postgresql.TIMESTAMP(),
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comment='Last metadata update',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'url',
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existing_type=sa.TEXT(),
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comment='Scraped URL',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'source',
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existing_type=sa.VARCHAR(length=50),
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comment='Store ID (amazon, cdiscount, etc.)',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'reference',
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existing_type=sa.VARCHAR(length=100),
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comment='Product reference (if extracted)',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'fetch_method',
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existing_type=sa.VARCHAR(length=20),
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comment='Fetch method (http, playwright)',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'fetch_status',
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existing_type=sa.VARCHAR(length=20),
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comment='Fetch status (success, partial, failed)',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'fetched_at',
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existing_type=postgresql.TIMESTAMP(),
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comment='Scraping timestamp',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'duration_ms',
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existing_type=sa.INTEGER(),
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comment='Fetch duration in milliseconds',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'html_size_bytes',
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existing_type=sa.INTEGER(),
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comment='HTML response size in bytes',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'errors',
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existing_type=postgresql.JSONB(astext_type=sa.Text()),
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comment='Error messages (list of strings)',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'notes',
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existing_type=postgresql.JSONB(astext_type=sa.Text()),
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comment='Debug notes (list of strings)',
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existing_nullable=True)
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op.alter_column('webhooks', 'event',
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existing_type=sa.VARCHAR(length=50),
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comment='Event name',
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existing_nullable=False)
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op.alter_column('webhooks', 'url',
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existing_type=sa.TEXT(),
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comment='Webhook URL',
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existing_nullable=False)
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op.alter_column('webhooks', 'secret',
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existing_type=sa.VARCHAR(length=200),
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comment='Secret optionnel',
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existing_nullable=True)
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op.alter_column('webhooks', 'created_at',
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existing_type=postgresql.TIMESTAMP(),
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comment='Creation timestamp',
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existing_nullable=False)
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# ### end Alembic commands ###
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def downgrade() -> None:
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# ### commands auto generated by Alembic - please adjust! ###
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op.alter_column('webhooks', 'created_at',
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existing_type=postgresql.TIMESTAMP(),
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comment=None,
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existing_comment='Creation timestamp',
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existing_nullable=False)
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op.alter_column('webhooks', 'secret',
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existing_type=sa.VARCHAR(length=200),
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comment=None,
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existing_comment='Secret optionnel',
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existing_nullable=True)
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op.alter_column('webhooks', 'url',
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existing_type=sa.TEXT(),
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comment=None,
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existing_comment='Webhook URL',
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existing_nullable=False)
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op.alter_column('webhooks', 'event',
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existing_type=sa.VARCHAR(length=50),
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comment=None,
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existing_comment='Event name',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'notes',
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existing_type=postgresql.JSONB(astext_type=sa.Text()),
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comment=None,
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existing_comment='Debug notes (list of strings)',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'errors',
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existing_type=postgresql.JSONB(astext_type=sa.Text()),
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comment=None,
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existing_comment='Error messages (list of strings)',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'html_size_bytes',
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existing_type=sa.INTEGER(),
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comment=None,
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existing_comment='HTML response size in bytes',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'duration_ms',
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existing_type=sa.INTEGER(),
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comment=None,
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existing_comment='Fetch duration in milliseconds',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'fetched_at',
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existing_type=postgresql.TIMESTAMP(),
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comment=None,
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existing_comment='Scraping timestamp',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'fetch_status',
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existing_type=sa.VARCHAR(length=20),
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comment=None,
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existing_comment='Fetch status (success, partial, failed)',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'fetch_method',
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existing_type=sa.VARCHAR(length=20),
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comment=None,
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existing_comment='Fetch method (http, playwright)',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'reference',
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existing_type=sa.VARCHAR(length=100),
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comment=None,
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existing_comment='Product reference (if extracted)',
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existing_nullable=True)
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op.alter_column('scraping_logs', 'source',
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existing_type=sa.VARCHAR(length=50),
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comment=None,
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existing_comment='Store ID (amazon, cdiscount, etc.)',
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existing_nullable=False)
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op.alter_column('scraping_logs', 'url',
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existing_type=sa.TEXT(),
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comment=None,
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existing_comment='Scraped URL',
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existing_nullable=False)
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op.alter_column('products', 'last_updated_at',
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existing_type=postgresql.TIMESTAMP(),
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comment=None,
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existing_comment='Last metadata update',
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existing_nullable=False)
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op.alter_column('products', 'first_seen_at',
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existing_type=postgresql.TIMESTAMP(),
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comment=None,
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existing_comment='First scraping timestamp',
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existing_nullable=False)
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op.alter_column('products', 'msrp',
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existing_type=sa.NUMERIC(precision=10, scale=2),
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comment=None,
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existing_comment='Recommended price',
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existing_nullable=True)
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op.alter_column('products', 'currency',
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existing_type=sa.VARCHAR(length=3),
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comment=None,
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existing_comment='Currency code (EUR, USD, GBP)',
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existing_nullable=True)
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op.alter_column('products', 'description',
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existing_type=sa.TEXT(),
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comment=None,
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existing_comment='Product description',
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existing_nullable=True)
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op.alter_column('products', 'category',
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existing_type=sa.TEXT(),
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comment=None,
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existing_comment='Product category (breadcrumb)',
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existing_nullable=True)
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op.alter_column('products', 'title',
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existing_type=sa.TEXT(),
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comment=None,
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existing_comment='Product title',
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existing_nullable=True)
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op.alter_column('products', 'url',
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existing_type=sa.TEXT(),
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comment=None,
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existing_comment='Canonical product URL',
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existing_nullable=False)
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op.alter_column('products', 'reference',
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existing_type=sa.VARCHAR(length=100),
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comment=None,
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existing_comment='Product reference (ASIN, SKU, etc.)',
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existing_nullable=False)
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op.alter_column('products', 'source',
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existing_type=sa.VARCHAR(length=50),
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comment=None,
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existing_comment='Store ID (amazon, cdiscount, etc.)',
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existing_nullable=False)
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op.drop_column('products', 'model_name')
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op.drop_column('products', 'model_number')
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op.drop_column('products', 'in_stock')
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op.drop_column('products', 'stock_text')
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op.drop_column('products', 'discount_text')
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op.drop_column('products', 'amazon_choice_label')
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op.drop_column('products', 'amazon_choice')
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op.drop_column('products', 'rating_count')
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op.drop_column('products', 'rating_value')
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op.alter_column('product_specs', 'spec_value',
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existing_type=sa.TEXT(),
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comment=None,
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existing_comment='Specification value',
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existing_nullable=False)
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op.alter_column('product_specs', 'spec_key',
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existing_type=sa.VARCHAR(length=200),
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comment=None,
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existing_comment="Specification key (e.g., 'Brand', 'Color')",
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existing_nullable=False)
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op.alter_column('product_images', 'position',
|
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existing_type=sa.INTEGER(),
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comment=None,
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existing_comment='Image position (0=main)',
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existing_nullable=False)
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op.alter_column('product_images', 'image_url',
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existing_type=sa.TEXT(),
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comment=None,
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existing_comment='Image URL',
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existing_nullable=False)
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op.alter_column('price_history', 'fetched_at',
|
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existing_type=postgresql.TIMESTAMP(),
|
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comment=None,
|
||||
existing_comment='Scraping timestamp',
|
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existing_nullable=False)
|
||||
op.alter_column('price_history', 'fetch_status',
|
||||
existing_type=sa.VARCHAR(length=20),
|
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comment=None,
|
||||
existing_comment='Fetch status (success, partial, failed)',
|
||||
existing_nullable=False)
|
||||
op.alter_column('price_history', 'fetch_method',
|
||||
existing_type=sa.VARCHAR(length=20),
|
||||
comment=None,
|
||||
existing_comment='Fetch method (http, playwright)',
|
||||
existing_nullable=False)
|
||||
op.alter_column('price_history', 'stock_status',
|
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existing_type=sa.VARCHAR(length=20),
|
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comment=None,
|
||||
existing_comment='Stock status (in_stock, out_of_stock, unknown)',
|
||||
existing_nullable=True)
|
||||
op.alter_column('price_history', 'shipping_cost',
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existing_type=sa.NUMERIC(precision=10, scale=2),
|
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comment=None,
|
||||
existing_comment='Shipping cost',
|
||||
existing_nullable=True)
|
||||
op.alter_column('price_history', 'price',
|
||||
existing_type=sa.NUMERIC(precision=10, scale=2),
|
||||
comment=None,
|
||||
existing_comment='Product price',
|
||||
existing_nullable=True)
|
||||
# ### end Alembic commands ###
|
||||
@@ -0,0 +1,28 @@
|
||||
"""Ajout champs Amazon produit
|
||||
|
||||
Revision ID: 1467e98fcbea
|
||||
Revises: 3e68b0f0c9e4
|
||||
Create Date: 2026-01-17 20:08:32.991650
|
||||
"""
|
||||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
|
||||
|
||||
# Revision identifiers, used by Alembic.
|
||||
revision = '1467e98fcbea'
|
||||
down_revision = '3e68b0f0c9e4'
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
@@ -0,0 +1,114 @@
|
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"""Ajout classification rules et type produit
|
||||
|
||||
Revision ID: 20260117_03_classification_rules
|
||||
Revises: 3e68b0f0c9e4
|
||||
Create Date: 2026-01-17 20:05:00.000000
|
||||
"""
|
||||
|
||||
from datetime import datetime, timezone
|
||||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
from sqlalchemy.dialects import postgresql
|
||||
|
||||
|
||||
# Revision identifiers, used by Alembic.
|
||||
revision = "20260117_03_classification_rules"
|
||||
down_revision = "3e68b0f0c9e4"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
op.add_column(
|
||||
"products",
|
||||
sa.Column("type", sa.Text(), nullable=True, comment="Product type"),
|
||||
)
|
||||
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||||
op.create_table(
|
||||
"classification_rules",
|
||||
sa.Column("id", sa.Integer(), primary_key=True, autoincrement=True),
|
||||
sa.Column("category", sa.String(length=80), nullable=True, comment="Categorie cible"),
|
||||
sa.Column("type", sa.String(length=80), nullable=True, comment="Type cible"),
|
||||
sa.Column(
|
||||
"keywords",
|
||||
postgresql.JSONB(astext_type=sa.Text()),
|
||||
nullable=False,
|
||||
comment="Mots-cles de matching",
|
||||
),
|
||||
sa.Column("sort_order", sa.Integer(), nullable=False, server_default="0"),
|
||||
sa.Column("is_active", sa.Boolean(), nullable=False, server_default=sa.text("true")),
|
||||
sa.Column(
|
||||
"created_at",
|
||||
sa.TIMESTAMP(),
|
||||
nullable=False,
|
||||
server_default=sa.text("CURRENT_TIMESTAMP"),
|
||||
comment="Creation timestamp",
|
||||
),
|
||||
)
|
||||
op.create_index("ix_classification_rule_order", "classification_rules", ["sort_order"])
|
||||
op.create_index("ix_classification_rule_active", "classification_rules", ["is_active"])
|
||||
|
||||
rules_table = sa.table(
|
||||
"classification_rules",
|
||||
sa.column("category", sa.String),
|
||||
sa.column("type", sa.String),
|
||||
sa.column("keywords", postgresql.JSONB),
|
||||
sa.column("sort_order", sa.Integer),
|
||||
sa.column("is_active", sa.Boolean),
|
||||
sa.column("created_at", sa.TIMESTAMP),
|
||||
)
|
||||
|
||||
now = datetime.now(timezone.utc)
|
||||
op.bulk_insert(
|
||||
rules_table,
|
||||
[
|
||||
{
|
||||
"category": "Informatique",
|
||||
"type": "Ecran",
|
||||
"keywords": ["ecran", "moniteur", "display"],
|
||||
"sort_order": 0,
|
||||
"is_active": True,
|
||||
"created_at": now,
|
||||
},
|
||||
{
|
||||
"category": "Informatique",
|
||||
"type": "PC portable",
|
||||
"keywords": ["pc portable", "ordinateur portable", "laptop", "notebook"],
|
||||
"sort_order": 1,
|
||||
"is_active": True,
|
||||
"created_at": now,
|
||||
},
|
||||
{
|
||||
"category": "Informatique",
|
||||
"type": "Unite centrale",
|
||||
"keywords": ["unite centrale", "tour", "desktop", "pc fixe"],
|
||||
"sort_order": 2,
|
||||
"is_active": True,
|
||||
"created_at": now,
|
||||
},
|
||||
{
|
||||
"category": "Informatique",
|
||||
"type": "Clavier",
|
||||
"keywords": ["clavier", "keyboard"],
|
||||
"sort_order": 3,
|
||||
"is_active": True,
|
||||
"created_at": now,
|
||||
},
|
||||
{
|
||||
"category": "Informatique",
|
||||
"type": "Souris",
|
||||
"keywords": ["souris", "mouse"],
|
||||
"sort_order": 4,
|
||||
"is_active": True,
|
||||
"created_at": now,
|
||||
},
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
op.drop_index("ix_classification_rule_active", table_name="classification_rules")
|
||||
op.drop_index("ix_classification_rule_order", table_name="classification_rules")
|
||||
op.drop_table("classification_rules")
|
||||
op.drop_column("products", "type")
|
||||
@@ -0,0 +1,28 @@
|
||||
"""Ajout champs Amazon produit
|
||||
|
||||
Revision ID: 3e68b0f0c9e4
|
||||
Revises: 0014e51c4927
|
||||
Create Date: 2026-01-17 19:45:03.730218
|
||||
"""
|
||||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
|
||||
|
||||
# Revision identifiers, used by Alembic.
|
||||
revision = '3e68b0f0c9e4'
|
||||
down_revision = '0014e51c4927'
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
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Binary file not shown.
@@ -84,6 +84,36 @@ class Product(Base):
|
||||
msrp: Mapped[Optional[Decimal]] = mapped_column(
|
||||
Numeric(10, 2), nullable=True, comment="Recommended price"
|
||||
)
|
||||
type: Mapped[Optional[str]] = mapped_column(
|
||||
Text, nullable=True, comment="Product type"
|
||||
)
|
||||
rating_value: Mapped[Optional[Decimal]] = mapped_column(
|
||||
Numeric(3, 2), nullable=True, comment="Note moyenne"
|
||||
)
|
||||
rating_count: Mapped[Optional[int]] = mapped_column(
|
||||
Integer, nullable=True, comment="Nombre d'evaluations"
|
||||
)
|
||||
amazon_choice: Mapped[Optional[bool]] = mapped_column(
|
||||
Boolean, nullable=True, comment="Badge Choix d'Amazon"
|
||||
)
|
||||
amazon_choice_label: Mapped[Optional[str]] = mapped_column(
|
||||
Text, nullable=True, comment="Libelle Choix d'Amazon"
|
||||
)
|
||||
discount_text: Mapped[Optional[str]] = mapped_column(
|
||||
Text, nullable=True, comment="Texte de reduction affiche"
|
||||
)
|
||||
stock_text: Mapped[Optional[str]] = mapped_column(
|
||||
Text, nullable=True, comment="Texte brut du stock"
|
||||
)
|
||||
in_stock: Mapped[Optional[bool]] = mapped_column(
|
||||
Boolean, nullable=True, comment="Disponibilite derivee"
|
||||
)
|
||||
model_number: Mapped[Optional[str]] = mapped_column(
|
||||
Text, nullable=True, comment="Numero du modele"
|
||||
)
|
||||
model_name: Mapped[Optional[str]] = mapped_column(
|
||||
Text, nullable=True, comment="Nom du modele"
|
||||
)
|
||||
|
||||
# Timestamps
|
||||
first_seen_at: Mapped[datetime] = mapped_column(
|
||||
@@ -331,6 +361,45 @@ class ScrapingLog(Base):
|
||||
return f"<ScrapingLog(id={self.id}, url={self.url}, status={self.fetch_status}, fetched_at={self.fetched_at})>"
|
||||
|
||||
|
||||
class ClassificationRule(Base):
|
||||
"""
|
||||
Regles de classification categorie/type basees sur des mots-cles.
|
||||
"""
|
||||
|
||||
__tablename__ = "classification_rules"
|
||||
|
||||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||||
category: Mapped[Optional[str]] = mapped_column(
|
||||
String(80), nullable=True, comment="Categorie cible"
|
||||
)
|
||||
type: Mapped[Optional[str]] = mapped_column(
|
||||
String(80), nullable=True, comment="Type cible"
|
||||
)
|
||||
keywords: Mapped[list[str]] = mapped_column(
|
||||
JSON().with_variant(JSONB, "postgresql"),
|
||||
nullable=False,
|
||||
default=list,
|
||||
comment="Mots-cles de matching",
|
||||
)
|
||||
sort_order: Mapped[int] = mapped_column(
|
||||
Integer, nullable=False, default=0, comment="Ordre de priorite (0=haut)"
|
||||
)
|
||||
is_active: Mapped[bool] = mapped_column(
|
||||
Boolean, nullable=False, default=True, comment="Regle active"
|
||||
)
|
||||
created_at: Mapped[datetime] = mapped_column(
|
||||
TIMESTAMP, nullable=False, default=utcnow, comment="Creation timestamp"
|
||||
)
|
||||
|
||||
__table_args__ = (
|
||||
Index("ix_classification_rule_order", "sort_order"),
|
||||
Index("ix_classification_rule_active", "is_active"),
|
||||
)
|
||||
|
||||
def __repr__(self) -> str:
|
||||
return f"<ClassificationRule(id={self.id}, category={self.category}, type={self.type})>"
|
||||
|
||||
|
||||
class Webhook(Base):
|
||||
"""
|
||||
Webhooks pour notifications externes.
|
||||
|
||||
@@ -13,7 +13,14 @@ from sqlalchemy.orm import Session
|
||||
|
||||
from pricewatch.app.core.logging import get_logger
|
||||
from pricewatch.app.core.schema import ProductSnapshot
|
||||
from pricewatch.app.db.models import PriceHistory, Product, ProductImage, ProductSpec, ScrapingLog
|
||||
from pricewatch.app.db.models import (
|
||||
ClassificationRule,
|
||||
PriceHistory,
|
||||
Product,
|
||||
ProductImage,
|
||||
ProductSpec,
|
||||
ScrapingLog,
|
||||
)
|
||||
|
||||
logger = get_logger("db.repository")
|
||||
|
||||
@@ -49,12 +56,58 @@ class ProductRepository:
|
||||
product.title = snapshot.title
|
||||
if snapshot.category:
|
||||
product.category = snapshot.category
|
||||
if snapshot.type:
|
||||
product.type = snapshot.type
|
||||
if snapshot.description:
|
||||
product.description = snapshot.description
|
||||
if snapshot.currency:
|
||||
product.currency = snapshot.currency
|
||||
if snapshot.msrp is not None:
|
||||
product.msrp = snapshot.msrp
|
||||
if snapshot.rating_value is not None:
|
||||
product.rating_value = snapshot.rating_value
|
||||
if snapshot.rating_count is not None:
|
||||
product.rating_count = snapshot.rating_count
|
||||
if snapshot.amazon_choice is not None:
|
||||
product.amazon_choice = snapshot.amazon_choice
|
||||
if snapshot.amazon_choice_label:
|
||||
product.amazon_choice_label = snapshot.amazon_choice_label
|
||||
if snapshot.discount_text:
|
||||
product.discount_text = snapshot.discount_text
|
||||
if snapshot.stock_text:
|
||||
product.stock_text = snapshot.stock_text
|
||||
if snapshot.in_stock is not None:
|
||||
product.in_stock = snapshot.in_stock
|
||||
if snapshot.model_number:
|
||||
product.model_number = snapshot.model_number
|
||||
if snapshot.model_name:
|
||||
product.model_name = snapshot.model_name
|
||||
|
||||
def apply_classification(self, snapshot: ProductSnapshot) -> None:
|
||||
"""Applique les regles de classification au snapshot."""
|
||||
if not snapshot.title:
|
||||
return
|
||||
|
||||
rules = (
|
||||
self.session.query(ClassificationRule)
|
||||
.filter(ClassificationRule.is_active == True)
|
||||
.order_by(ClassificationRule.sort_order, ClassificationRule.id)
|
||||
.all()
|
||||
)
|
||||
if not rules:
|
||||
return
|
||||
|
||||
title = snapshot.title.lower()
|
||||
for rule in rules:
|
||||
keywords = rule.keywords or []
|
||||
if isinstance(keywords, str):
|
||||
keywords = [keywords]
|
||||
if any(keyword and keyword.lower() in title for keyword in keywords):
|
||||
if rule.category:
|
||||
snapshot.category = rule.category
|
||||
if rule.type:
|
||||
snapshot.type = rule.type
|
||||
return
|
||||
|
||||
def add_price_history(self, product: Product, snapshot: ProductSnapshot) -> Optional[PriceHistory]:
|
||||
"""Ajoute une entree d'historique de prix si inexistante."""
|
||||
|
||||
Reference in New Issue
Block a user