越南股市数据服务

version : 1.0.0

list_all_icb_industries

List all ICB industries from stock market Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

output_format(string)

结果（Result）

list_all_companies_with_details

List all companies from stock market with details Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

output_format(string)

结果（Result）

get_company_overview

Get company overview from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_company_news

Get company news from stock market Args: symbol: str page_size: int = 10 page: int = 0 output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

page_size(integer)

page(integer)

output_format(string)

结果（Result）

get_company_events

Get company events from stock market Args: symbol: str page_size: int = 10 page: int = 0 output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

page_size(integer)

page(integer)

output_format(string)

结果（Result）

get_company_shareholders

Get company shareholders from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_company_officers

Get company officers from stock market Args: symbol: str filter_by: Literal['working', "all", 'resigned'] = 'working' output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

filter_by(string)

output_format(string)

结果（Result）

get_company_subsidiaries

Get company subsidiaries from stock market Args: symbol: str filter_by: Literal["all", "subsidiary"] = "all" output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

filter_by(string)

output_format(string)

结果（Result）

get_company_reports

Get company reports from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_company_dividends

Get company dividends from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_company_insider_deals

Get company insider deals from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_company_ratio_summary

Get company ratio summary from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_company_trading_stats

Get company trading stats from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_all_symbol_groups

Get all symbol groups from stock market Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

output_format(string)

结果（Result）

get_all_symbols_by_group

Get all symbols from stock market Args: group: str (group name to get symbols) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*group(string)

output_format(string)

结果（Result）

get_all_symbols_by_industry

Get all symbols from stock market Args: industry: str = None (if None, return all symbols) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame or json

industry(string)

output_format(string)

结果（Result）

get_all_symbols

Get all symbols from stock market Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame or json

output_format(string)

结果（Result）

get_all_symbols_detailed

Get all symbols detailed from stock market Args: output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

output_format(string)

结果（Result）

get_income_statements

Get income statements of a company from stock market Args: symbol: str (symbol of the company to get income statements) period: Literal['quarter', 'year'] = 'year' (period to get income statements) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

period(string)

output_format(string)

结果（Result）

get_balance_sheets

Get balance sheets of a company from stock market Args: symbol: str (symbol of the company to get balance sheets) period: Literal['quarter', 'year'] = 'year' (period to get balance sheets) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

period(string)

output_format(string)

结果（Result）

get_cash_flows

Get cash flows of a company from stock market Args: symbol: str (symbol of the company to get cash flows) period: Literal['quarter', 'year'] = 'year' (period to get cash flows) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

period(string)

output_format(string)

结果（Result）

get_finance_ratios

Get finance ratios of a company from stock market Args: symbol: str (symbol of the company to get finance ratios) period: Literal['quarter', 'year'] = 'year' (period to get finance ratios) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

period(string)

output_format(string)

结果（Result）

get_raw_report

Get raw report of a company from stock market Args: symbol: str (symbol of the company to get raw report) period: Literal['quarter', 'year'] = 'year' (period to get raw report) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

period(string)

output_format(string)

结果（Result）

list_all_funds

List all funds from stock market Args: fund_type: Literal['BALANCED', 'BOND', 'STOCK', None ] = None (if None, return funds in all types) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

fund_type(null)

output_format(string)

结果（Result）

search_fund

Search fund by name from stock market Args: keyword: str (partial match for fund name to search) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*keyword(string)

output_format(string)

结果（Result）

get_fund_nav_report

Get nav report of a fund from stock market Args: symbol: str (symbol of the fund to get nav report) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_fund_top_holding

Get top holding of a fund from stock market Args: symbol: str (symbol of the fund to get top holding) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_fund_industry_holding

Get industry holding of a fund from stock market Args: symbol: str (symbol of the fund to get industry holding) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_fund_asset_holding

Get asset holding of a fund from stock market Args: symbol: str (symbol of the fund to get asset holding) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_gold_price

Get gold price from stock market Args: date: str = None (if None, return today's price. Format: YYYY-MM-DD) source: Literal['SJC', 'BTMC'] = 'SJC' (source to get gold price) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

date(string)

source(string)

output_format(string)

结果（Result）

get_exchange_rate

Get exchange rate of all currency pairs from stock market Args: date: str = None (if None, return today's price. Format: YYYY-MM-DD) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

date(string)

output_format(string)

结果（Result）

get_quote_price_with_indicators

Get quote price with indicators of a symbol from stock market. Indicators can be specified with or without parameters: - Simple: "rsi", "macd", "stochastic" - With params: "rsi(window=21)", "macd(fast=12, slow=26, signal=9)" Args: symbol: str (symbol to get price) indicators: list[str] (list of indicators with optional parameters) Examples: - ["rsi", "macd"] - use default parameters - ["rsi(window=21)", "macd(fast=12, slow=26)"] - custom parameters - ["stochastic(k=14, d=3)", "cci(window=20)"] - mixed start_date: str (format: YYYY-MM-DD) end_date: str = None (end date to get price. None means today) interval: Literal['1m', '5m', '15m', '30m', '1H', '1D', '1W', '1M'] = '1D' (interval to get price) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame with OHLCV data and requested indicator columns

*symbol(string)

*indicators(array)

*start_date(string)

end_date(string)

interval(string)

drop_market_close(boolean)

output_format(string)

结果（Result）

get_quote_history_price

Get quote price history of a symbol from stock market Args: symbol: str (symbol to get history price) start_date: str (format: YYYY-MM-DD) end_date: str = None (end date to get history price. None means today) interval: Literal['1m', '5m', '15m', '30m', '1H', '1D', '1W', '1M'] = '1D' (interval to get history price) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

*start_date(string)

end_date(string)

interval(string)

drop_market_close(boolean)

output_format(string)

结果（Result）

get_quote_intraday_price

Get quote intraday price from stock market Args: symbol: str (symbol to get intraday price) page_size: int = 500 (max: 100000) (number of rows to return) page: int = 1 (page number to get intraday price from) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

page_size(integer)

page(integer)

output_format(string)

结果（Result）

get_quote_price_depth

Get quote price depth from stock market Args: symbol: str (symbol to get price depth) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbol(string)

output_format(string)

结果（Result）

get_price_board

Get price board from stock market Args: symbols: list[str] (list of symbols to get price board) output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

*symbols(array)

output_format(string)

结果（Result）