## Get Instrument Income Statements `v1.instrument_data.get_instrument_income_statements(InstrumentIDOrSymbolinstrument_id, InstrumentDataGetInstrumentIncomeStatementsParams**kwargs) -> InstrumentDataGetInstrumentIncomeStatementsResponse` **get** `/v1/instruments/{instrument_id}/income-statements` Retrieves quarterly income statements for a specific instrument, sorted by fiscal period (most recent first). Date range defaults: - `from_date`: None (no lower bound) - `to_date`: None (no upper bound) ### Parameters - `instrument_id: InstrumentIDOrSymbol` OEMS instrument UUID - `from_date: Optional[str]` The start date for the query range, inclusive (YYYY-MM-DD). - `page_size: Optional[int]` The number of items to return per page. Only used when page_token is not provided. - `page_token: Optional[Union[str, Base64FileInput]]` Token for retrieving the next or previous page of results. Contains encoded pagination state; when provided, page_size is ignored. - `to_date: Optional[str]` The end date for the query range, inclusive (YYYY-MM-DD). ### Returns - `class InstrumentDataGetInstrumentIncomeStatementsResponse: …` - `data: InstrumentIncomeStatementList` - `accepted_date: datetime` The date and time when the filing was accepted by the SEC - `filing_date: date` The date the financial statement was filed - `period: str` The fiscal period identifier (e.g., "Q1", "Q2", "Q3", "Q4") - `period_type: FiscalPeriodType` The type of fiscal period - `"QUARTERLY"` - `"ANNUAL"` - `"TTM"` - `"BIANNUAL"` - `reported_currency: str` The currency in which the statement is reported (ISO 4217) - `year: int` The fiscal year of the statement - `bottom_line_net_income: Optional[str]` Bottom line net income after all adjustments - `cost_and_expenses: Optional[str]` Total costs and expenses - `cost_of_revenue: Optional[str]` Direct costs attributable to producing goods sold - `depreciation_and_amortization: Optional[str]` Depreciation and amortization expenses - `ebit: Optional[str]` Earnings before interest and taxes - `ebitda: Optional[str]` Earnings before interest, taxes, depreciation, and amortization - `eps: Optional[str]` Basic earnings per share - `eps_diluted: Optional[str]` Diluted earnings per share - `general_and_administrative_expenses: Optional[str]` General administrative overhead expenses - `gross_profit: Optional[str]` Revenue minus cost of revenue - `income_before_tax: Optional[str]` Income before income tax expense - `income_tax_expense: Optional[str]` Income tax expense for the period - `interest_expense: Optional[str]` Interest paid on debt - `interest_income: Optional[str]` Interest earned on investments and cash - `net_income: Optional[str]` Total net income for the period - `net_income_deductions: Optional[str]` Deductions from net income - `net_income_from_continuing_operations: Optional[str]` Net income from continuing operations - `net_income_from_discontinued_operations: Optional[str]` Net income from discontinued operations - `net_interest_income: Optional[str]` Net interest income (interest income minus interest expense) - `non_operating_income_excluding_interest: Optional[str]` Non-operating income excluding interest - `operating_expenses: Optional[str]` Total operating expenses - `operating_income: Optional[str]` Income from core business operations - `other_adjustments_to_net_income: Optional[str]` Other adjustments to net income - `other_expenses: Optional[str]` Other miscellaneous expenses - `research_and_development_expenses: Optional[str]` Expenditure on research and development activities - `revenue: Optional[str]` Total revenue from sales of goods and services - `selling_and_marketing_expenses: Optional[str]` Expenditure on marketing and sales activities - `selling_general_and_administrative_expenses: Optional[str]` Combined selling, general, and administrative expenses - `total_other_income_expenses_net: Optional[str]` Net of other income and expenses - `weighted_average_shs_out: Optional[str]` Weighted average shares outstanding (basic) - `weighted_average_shs_out_dil: Optional[str]` Weighted average shares outstanding (diluted) ### Example ```python from clear_street import ClearStreet client = ClearStreet( api_key="My API Key", ) response = client.v1.instrument_data.get_instrument_income_statements( instrument_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", ) print(response) ``` #### Response ```json { "data": [ { "accepted_date": "2025-05-02T14:30:00Z", "cost_of_revenue": "52080000000", "eps": "1.40", "eps_diluted": "1.38", "filing_date": "2025-05-01", "gross_profit": "42850000000", "net_income": "22200000000", "operating_income": "26550000000", "period": "Q1", "period_type": "QUARTERLY", "reported_currency": "USD", "revenue": "94930000000", "year": 2025 } ], "error": null, "metadata": { "next_page_token": "AAAAAAAAAGQAAAAAAAAAZQ==", "page_number": 1, "request_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890", "total_items": 20, "total_pages": 2 } } ```