Exemple #1
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def df():
    user_id = os.environ.get("FINMIND_USER", "")
    password = os.environ.get("FINMIND_PASSWORD", "")
    data_loader = DataLoader()
    data_loader.login(user_id, password)
    df = data_loader.taiwan_stock_holding_shares_per(stock_id="2890",
                                                     start_date="2021-06-01",
                                                     end_date="2021-07-03")
    df["labels"] = df["HoldingSharesLevel"]
    df["series"] = df["percent"]
    return df
Exemple #2
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def test_bar_success(stock_id, start_date, end_date):
    user_id = os.environ.get("FINMIND_USER", "")
    password = os.environ.get("FINMIND_PASSWORD", "")
    data_loader = DataLoader()
    data_loader.login(user_id, password)
    df = data_loader.taiwan_stock_month_revenue(stock_id=stock_id,
                                                start_date=start_date,
                                                end_date=end_date)
    df["labels"] = (df[["revenue_year", "revenue_month"]].astype(str).apply(
        lambda date: f"{date[0]}-{date[1]}M", axis=1))
    df["series"] = df["revenue"].map(lambda value: round(value * 1e-8, 2))
    assert plotting.bar(labels=df["labels"], series=df["series"])
Exemple #3
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def df():
    user_id = os.environ.get("FINMIND_USER", "")
    password = os.environ.get("FINMIND_PASSWORD", "")
    data_loader = DataLoader()
    data_loader.login(user_id, password)
    df = data_loader.taiwan_stock_month_revenue(stock_id="2890",
                                                start_date="2018-1M",
                                                end_date="2021-7M")
    df["labels"] = (df[["revenue_year", "revenue_month"]].astype(str).apply(
        lambda date: f"{date[0]}-{date[1]}M", axis=1))
    df["series"] = df["revenue"].map(lambda value: round(value * 1e-8, 2))
    return df
Exemple #4
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def test_pie_failed():
    user_id = os.environ.get("FINMIND_USER", "")
    password = os.environ.get("FINMIND_PASSWORD", "")
    data_loader = DataLoader()
    data_loader.login(user_id, password)
    df = data_loader.taiwan_stock_month_revenue(stock_id="2330",
                                                start_date="2018-01-01",
                                                end_date="2021-03-03")
    df["series"] = (df[["revenue_year", "revenue_month"]].astype(str).apply(
        lambda date: f"{date[0]}-{date[1]}M", axis=1))
    df["labels"] = df["revenue"].map(lambda value: round(value * 1e-8, 2))
    with (pytest.raises(Exception)):
        plotting.pie(labels=df["labels"], series=df["series"])
Exemple #5
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def test_pie(stock_id, start_date, end_date):
    user_id = os.environ.get("FINMIND_USER", "")
    password = os.environ.get("FINMIND_PASSWORD", "")
    data_loader = DataLoader()
    data_loader.login(user_id, password)
    df = data_loader.taiwan_stock_holding_shares_per(stock_id=stock_id,
                                                     start_date=start_date,
                                                     end_date=end_date)
    df = df[df["date"] == max(df["date"])]
    df = df[df["HoldingSharesLevel"] != "total"]
    df["labels"] = df["HoldingSharesLevel"]
    df["series"] = df["percent"]
    assert plotting.pie(labels=df["labels"], series=df["series"])
Exemple #6
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def test_kline(stock_id, start_date, end_date):
    user_id = os.environ.get("FINMIND_USER", "")
    password = os.environ.get("FINMIND_PASSWORD", "")
    data_loader = DataLoader()
    data_loader.login(user_id, password)
    stock_data = data_loader.taiwan_stock_daily_adj(stock_id=stock_id,
                                                    start_date=start_date,
                                                    end_date=end_date)
    assert plotting.kline(stock_data)
    stock_data = data_loader.feature.add_kline_institutional_investors(
        stock_data)
    assert plotting.kline(stock_data)
    stock_data = data_loader.feature.add_kline_margin_purchase_short_sale(
        stock_data)
    assert plotting.kline(stock_data)
Exemple #7
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def data_loader():
    data_loader = DataLoader()
    data_loader.login(user_id, password)
    return data_loader