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467 lines
18 KiB
Python
467 lines
18 KiB
Python
"""Global configurations and definitions for pytest."""
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import datetime
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from collections.abc import Generator
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from inspect import getmembers, isfunction
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from typing import Any
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import pytest
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from sqlalchemy.orm import Session, sessionmaker
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from aki_prj23_transparenzregister.config.config_template import SQLiteConnectionString
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from aki_prj23_transparenzregister.models.company import CapitalTypeEnum
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from aki_prj23_transparenzregister.utils import data_transfer
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from aki_prj23_transparenzregister.utils.enum_types import SentimentLabel
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from aki_prj23_transparenzregister.utils.sql import entities
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from aki_prj23_transparenzregister.utils.sql.connector import (
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get_engine,
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init_db,
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)
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@pytest.fixture(autouse=True)
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def _clear_caches() -> Generator[None, None, None]:
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"""A function that clears all caches after each test.
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All the modules containing the cached functions need to be listed in the modules tuple.
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"""
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yield
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# https://stackoverflow.com/a/139198/11003343
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modules = (data_transfer,)
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functions = [
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function
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for module in modules
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for name, function in getmembers(module, isfunction)
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if function.__dict__.get("cache") is not None
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]
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# https://cachetools.readthedocs.io/en/stable/?highlight=clear#memoizing-decorators
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for function in functions:
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function.cache.clear() # type: ignore
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@pytest.fixture()
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def empty_db() -> Generator[Session, None, None]:
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"""Generates a db Session to a sql_lite db."""
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engine = get_engine(SQLiteConnectionString(":memory:"))
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db = sessionmaker(autocommit=False, autoflush=False, bind=engine)()
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init_db(db)
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yield db
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db.close()
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engine.dispose()
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@pytest.fixture()
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def finance_statements() -> list[dict[str, Any]]:
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"""Creates a list of finance statements."""
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return [
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{
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"id": 1,
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"company_id": 1,
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"date": datetime.date.fromisoformat("2023-01-01"),
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"ebit": 1000.0,
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"ebitda": 1000.0,
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"gross_profit": 1000.0,
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"equity": 1000.0,
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"current_liabilities": 1000.0,
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"assets": 1000.0,
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"net_income": 100.0,
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"long_term_debt": 1000.0,
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"short_term_debt": 1000.0,
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"revenue": 1000.0,
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"cash_flow": 1000.0,
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"current_assets": 1000.0,
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"liabilities": 0.0,
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"cash_and_cash_equivalents": 1.0,
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"dividends": 0.0,
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},
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{
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"id": 2,
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"company_id": 1,
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"date": datetime.date.fromisoformat("2022-01-01"),
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"revenue": 1100.0,
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"net_income": float("NaN"),
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"ebit": 1100.0,
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"ebitda": 1100.0,
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"gross_profit": 1100.0,
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"equity": 1100.0,
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"current_liabilities": 1100.0,
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"dividends": float("NaN"),
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"assets": 1100.0,
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"long_term_debt": 1100.0,
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"short_term_debt": 1100.0,
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"cash_flow": 1100.0,
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"current_assets": 1100.0,
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"operating_profit": 1.0,
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},
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]
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@pytest.fixture()
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def full_db(empty_db: Session, finance_statements: list[dict[str, Any]]) -> Session:
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"""Fills a db with some test data."""
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empty_db.add_all(
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[
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entities.DistrictCourt(name="Amtsgericht Bochum", city="Bochum"),
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entities.DistrictCourt(name="Amtsgericht Dortmund", city="Dortmund"),
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entities.Person(
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firstname="Max",
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lastname="Mustermann",
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date_of_birth=datetime.date(2023, 1, 1),
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),
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entities.Person(
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firstname="Sabine",
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lastname="Mustermann",
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date_of_birth=datetime.date(2023, 1, 1),
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),
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entities.Person(
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firstname="Some Firstname",
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lastname="Some Surname",
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date_of_birth=datetime.date(2023, 1, 1),
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),
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entities.Person(
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firstname="Some Firstname",
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lastname="Some Surname",
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date_of_birth=datetime.date(2023, 1, 2),
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),
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entities.Person(
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firstname="Other Firstname",
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lastname="Other Surname",
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date_of_birth=datetime.date(2023, 1, 2),
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),
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]
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)
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empty_db.commit()
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empty_db.add_all(
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[
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entities.Company(
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hr="HRB 123",
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court_id=2,
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name="Some Company GmbH",
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street="Sesamstr.",
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house_number="1",
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zip_code="58644",
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city="TV City",
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last_update=datetime.date.fromisoformat("2023-01-01"),
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latitude=51.3246,
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longitude=7.6968,
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pos_accuracy=4.0,
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founding_date=datetime.date(2010, 8, 7),
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capital_value=1000000,
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original_currency="DM",
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capital_type=CapitalTypeEnum.HAFTEINLAGE,
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business_purpose='Say "Hello World"',
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),
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entities.Company(
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hr="HRB 123",
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court_id=1,
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name="Other Company GmbH",
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street="Sesamstr.",
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house_number="2",
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zip_code="58636",
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city="TV City",
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last_update=datetime.date.fromisoformat("2023-01-01"),
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latitude=51.38,
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longitude=7.7032,
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pos_accuracy=4.0,
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business_purpose="Some purpose",
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),
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entities.Company(
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hr="HRB 12",
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court_id=2,
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name="Third Company GmbH",
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last_update=datetime.date.fromisoformat("2023-01-01"),
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sector="Electronic",
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capital_value=10000,
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original_currency="EUR",
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capital_type=CapitalTypeEnum.GRUNDKAPITAL,
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),
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]
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)
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empty_db.commit()
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empty_db.add_all(
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[
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entities.AnnualFinanceStatement(**finance_statement)
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for finance_statement in finance_statements
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]
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)
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empty_db.add(
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entities.MissingCompany(name="Some company missing", zip_code="", city="")
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)
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empty_db.commit()
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# print(pd.read_sql_table("company", empty_db.bind).to_string())
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return empty_db
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@pytest.fixture()
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def news_db(full_db: Session) -> Session:
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news_example = entities.News(
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title="AI Revolution in Tech",
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timestamp=datetime.datetime(2023, 11, 1, 15, 30),
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text="The latest advancements in AI are transforming the tech industry.",
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source_url="http://example-news.com/ai-revolution",
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source_domain="example-news.com",
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overall_sentiment_label=SentimentLabel.POSITIVE, # type: ignore
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overall_sentiment_certainty=0.95,
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number_of_companies=2,
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sum_of_times_named=5,
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)
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full_db.add(news_example)
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full_db.commit()
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# Print to see the object representation
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# Example instances of Sentiment for different company IDs
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sentiment_examples = [
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entities.Sentiment(
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company_id=1,
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article_id=news_example.id, # This should be the actual ID after insertion into the database
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times_named=3,
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specific_sentiment_label=SentimentLabel.NEUTRAL, # type: ignore
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specific_sentiment_score=0.5,
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),
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entities.Sentiment(
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company_id=2,
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article_id=news_example.id, # This should be the actual ID after insertion into the database
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times_named=2,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.2,
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),
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entities.Sentiment(
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company_id=3,
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article_id=news_example.id, # This should be the actual ID after insertion into the database
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times_named=1,
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specific_sentiment_label=SentimentLabel.POSITIVE, # type: ignore
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specific_sentiment_score=0.8,
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),
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]
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full_db.add_all(sentiment_examples)
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add_news_examples = [
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entities.News(
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title="Breakthrough in Renewable Energy",
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timestamp=datetime.datetime(2023, 11, 1, 15, 30),
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text="Innovative solar panels are expected to revolutionize the energy sector.",
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source_url="http://example-news.com/renewable-breakthrough",
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source_domain="eco-news.com",
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overall_sentiment_label=SentimentLabel.POSITIVE, # type: ignore
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overall_sentiment_certainty=0.9,
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number_of_companies=1,
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sum_of_times_named=3,
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),
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entities.News(
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title="Global Economic Outlook",
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timestamp=datetime.datetime(2023, 11, 2, 10, 0),
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text="Economists predict a challenging year ahead for global markets.",
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source_url="http://example-news.com/economic-outlook",
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source_domain="finance-world.com",
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overall_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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overall_sentiment_certainty=0.95,
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number_of_companies=3,
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sum_of_times_named=7,
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),
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entities.News(
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title="Tech Giants Merge",
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timestamp=datetime.datetime(2023, 11, 3, 12, 45),
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text="Two leading tech companies have announced a merger, sparking industry-wide discussions.",
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source_url="http://example-news.com/tech-merger",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.NEUTRAL, # type: ignore
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overall_sentiment_certainty=0.91,
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number_of_companies=2,
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sum_of_times_named=10,
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),
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entities.News(
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title="Deutsche Bank announces huge job loss plan",
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timestamp=datetime.datetime(2023, 11, 5, 12, 45),
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text="Deutsche Bank has announced plans for major job losses and will also scale down massively its operations worldwide, as part of a major shake-up of.",
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source_url="http://example-news.com/deutsche-bank",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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overall_sentiment_certainty=0.9,
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number_of_companies=1,
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sum_of_times_named=8,
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),
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entities.News(
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title="Germany approves reforms to help its tech industry compete with Silicon Valley",
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timestamp=datetime.datetime(2023, 11, 6, 9, 45),
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text="Germany on Friday approved a litany of changes to its rules for stock-based compensation at tech startups, listing of companies and taxation.",
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source_url="http://example-news.com/german-tech-industry",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.POSITIVE, # type: ignore
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overall_sentiment_certainty=0.97,
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number_of_companies=3,
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sum_of_times_named=5,
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),
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entities.News(
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title="German housebuilding is collapsing ",
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timestamp=datetime.datetime(2023, 11, 8, 12, 30),
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text="German housebuilding is on the brink of collapse as construction projects are being canceled and orders are slowing.",
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source_url="http://example-news.com/german-housing",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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overall_sentiment_certainty=0.96,
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number_of_companies=3,
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sum_of_times_named=2,
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),
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entities.News(
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title="The Berlin start-ups tearing up capitalism and putting workers first",
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timestamp=datetime.datetime(2023, 11, 10, 12, 45),
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text="Berlin is one of Europe's hottest start-up hubs. But companies setting up there are doing things differently and it starts with where the power lies.",
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source_url="http://example-news.com/tech-merger",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.POSITIVE, # type: ignore
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overall_sentiment_certainty=0.91,
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number_of_companies=2,
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sum_of_times_named=10,
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),
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entities.News(
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title="Air traffic across Germany disrupted due to mass walkouts",
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timestamp=datetime.datetime(2023, 11, 3, 12, 45),
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text="Security workers are staging a full-day walkout at airports across Germany over pay disputes.",
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source_url="http://example-news.com/tech-merger",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.NEUTRAL, # type: ignore
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overall_sentiment_certainty=0.95,
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number_of_companies=3,
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sum_of_times_named=17,
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),
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entities.News(
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title="Car makers face fraud claims",
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timestamp=datetime.datetime(2023, 11, 12, 12, 45),
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text="The German economy grew 0.6 percent in Q1, quarter on quarter, helped by strong exports, booming construction and higher household and state spending.",
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source_url="http://example-news.com/tech-merger",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.NEUTRAL, # type: ignore
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overall_sentiment_certainty=0.9,
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number_of_companies=2,
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sum_of_times_named=10,
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),
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entities.News(
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title="Inflation rises, unemployment falls",
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timestamp=datetime.datetime(2023, 11, 15, 12, 45),
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text="German inflation rose in February, reaching its highest level in four-and-a-half years, while unemployment fell more than expected.",
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source_url="http://example-news.com/inflation",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.POSITIVE, # type: ignore
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overall_sentiment_certainty=0.98,
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number_of_companies=2,
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sum_of_times_named=10,
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),
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entities.News(
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title="Exports struggle on slow factory output",
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timestamp=datetime.datetime(2023, 11, 16, 12, 45),
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text="Exports rebounded by less than expected in October, according to latest official figures.",
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source_url="http://example-news.com/exports",
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source_domain="tech-news.com",
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overall_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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overall_sentiment_certainty=0.98,
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number_of_companies=3,
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sum_of_times_named=4,
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),
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]
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full_db.add_all(add_news_examples)
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full_db.commit()
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# Additional examples for the Sentiment entity
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sentiment_more_examples = [
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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2
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].id, # Placeholder ID, replace with actual after insertion
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times_named=1,
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specific_sentiment_label=SentimentLabel.NEUTRAL, # type: ignore
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specific_sentiment_score=0.5,
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),
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entities.Sentiment(
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company_id=3,
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article_id=add_news_examples[
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1
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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1
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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3
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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4
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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5
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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6
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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7
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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8
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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9
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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entities.Sentiment(
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company_id=1,
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article_id=add_news_examples[
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10
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].id, # Placeholder ID, replace with actual after insertion
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times_named=4,
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specific_sentiment_label=SentimentLabel.NEGATIVE, # type: ignore
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specific_sentiment_score=0.3,
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),
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]
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full_db.add_all(sentiment_more_examples)
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full_db.commit()
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return full_db
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