Stock Screener

class ScannerResult:
    def __init__(self, page, page_size, total_page, total_count, items, cursor_id):
        # Current page number, starting from 0
        self.page = page
        # Total number of pages
        self.total_page = total_page
        # Total number of data items
        self.total_count = total_count
        # Page size
        self.page_size = page_size
        # Next page cursor ID
        self.cursor_id = cursor_id
        # Result data list
        self.items: ScannerResultItem = list()
        # Summary of filtered stock symbol list
        self.symbols = list()

# Each item in items is:
class ScannerResultItem:
    def __init__(self, symbol, market, base_data_list=None, accumulate_data_list=None, financial_data_list=None,
                 multi_tag_data_list=None):
        self.symbol = symbol
        self.market = market
        self.field_data = dict()

# You can use filter as key to get the corresponding filter field value, see example below

import time
from datetime import datetime
from tigeropen.quote.quote_client import QuoteClient
from tigeropen.tiger_open_config import get_client_config
from tigeropen.common.consts import TradingSession, Market
from tigeropen.quote.domain.filter import OptionFilter, StockFilter, SortFilterData
from tigeropen.common.consts.filter_fields import StockField, AccumulateField, FinancialField, MultiTagField, \
    FinancialPeriod, AccumulatePeriod

from tigeropen.tiger_open_config import TigerOpenClientConfig
client_config = TigerOpenClientConfig(props_path='/path/to/your/properties/file/')

quote_client = QuoteClient(client_config)

def test_market_scanner():
    # Stock basic data filter (is_no_filter=True means this filter is not enabled)
    base_filter1 = StockFilter(StockField.FloatShare, filter_min=1e7, filter_max=1e13, is_no_filter=True)
    base_filter2 = StockFilter(StockField.MarketValue, filter_min=1e8, filter_max=1e14, is_no_filter=False)
    # Filter by earnings date
    base_filter3 = StockFilter(StockField.EarningDate, filter_min=int(datetime.strptime('2021-01-01', '%Y-%m-%d').timestamp() * 1000),
                                   filter_max=int(datetime.strptime('2023-12-31', '%Y-%m-%d').timestamp() * 1000)
                                   , is_no_filter=False)
    # Periodic cumulative data filter
    accumulate_filter = StockFilter(AccumulateField.ChangeRate, filter_min=0.01, filter_max=1, is_no_filter=False,
                                    accumulate_period=AccumulatePeriod.Last_Year)
    # Financial data filter
    financial_filter = StockFilter(FinancialField.LYR_PE, filter_min=1, filter_max=100, is_no_filter=False,
                                   financial_period=FinancialPeriod.LTM)
    # Multi-tag data filter, need to get tag_list first. If there are values, pass them according to the situation. If no values, don't pass tag_list parameter; For boolean fields, tag_list is generally empty and no value needs to be passed
    tags = quote_client.get_market_scanner_tags(market=Market.US, tag_fields=[MultiTagField.OptionsAvailable])
    if not tags:
        tag_list = []
    else:
        # Need to replace with the desired tag based on actual situation, e.g., when field is MultiTagField.Industry, tag_list = ['BK4209']
        tag_list = ['BK4209']
    multi_tag_filter = StockFilter(MultiTagField.isOTC, tag_list=tag_list)


    # Sort field
    sort_field_data = SortFilterData(StockField.FloatShare, sort_dir=SortDirection.ASC)

    cursor_id = None
    page_size = 50
    # Whether it's the last page of data
    is_last_page = False
    # Symbol list after filtering
    scanner_result_symbols = set()

    while not is_last_page:
        # Put the filters you want to use in the filters parameter
        result = quote_client.market_scanner(market=Market.US,
                                             filters=[base_filter1, base_filter2, 
                                                      # base_filter3,
                                                      accumulate_filter,
                                                      financial_filter,
                                                      multi_tag_filter],
                                             sort_field_data=sort_field_data,
                                             cursor_id=cursor_id,
                                             page_size=page_size)
        print(result)
        if result.total_page:
            for item in result.items:
                # item type is ScannerResultItem 
                symbol = item.symbol
                market = item.market
                # You can get the value of a certain filter field in dictionary form
                base_filter1_value = item[base_filter1]
                accumulate_filter_value = item[accumulate_filter]
                print(
                    f'page:{result.page}, symbol:{symbol}, base_filter1 value:{base_filter1_value}, accumulate_filter value:{accumulate_filter_value}')
            print(f'current page symbols:{result.symbols}')
            scanner_result_symbols.update(result.symbols)
        time.sleep(10)
        # Handle pagination
        if not result.cursor_id:
            is_last_page = True
        else:
            cursor_id = result.cursor_id

    print(f'scanned symbols:{scanner_result_symbols}')

from tigeropen.quote.quote_client import QuoteClient
from tigeropen.common.consts import TradingSession
from tigeropen.quote.domain.filter import OptionFilter, StockFilter, SortFilterData
from tigeropen.common.consts.filter_fields import StockField, AccumulateField, FinancialField, MultiTagField, \
    FinancialPeriod, AccumulatePeriod

from tigeropen.tiger_open_config import TigerOpenClientConfig
client_config = TigerOpenClientConfig(props_path='/path/to/your/properties/file/')

quote_client = QuoteClient(client_config)

def test_market_scanner1():

    # Dividend yield greater than 5%
    base_filter = StockFilter(StockField.DivideRate, filter_min=0.05)
    # Total revenue 3-year growth rate or revenue 3-year compound annual growth rate
    financial_filter = StockFilter(FinancialField.TotalRevenues3YrCagr, filter_min=0.1)
    
    cursor_id = None
    page_size = 50
    # Whether it's the last page of data
    is_last_page = False
    # Symbol list after filtering
    scanner_result_symbols = set()

    while not is_last_page:
        # Put the filters you want to use in the filters parameter
        result = quote_client.market_scanner(market=Market.US,
                                             filters=[
                                                 base_filter,
                                                 financial_filter,
                                             ],
                                             cursor_id=cursor_id,
                                             page_size=page_size)
        print(result)
        if result.total_page:
            for item in result.items:
                symbol = item.symbol
                market = item.market
                # You can get the value of a certain filter field in dictionary form
                base_filter_value = item[base_filter]
                financial_filter_value = item[financial_filter]
                print(
                    f'page:{result.page}, symbol:{symbol}, base_filter value:{base_filter_value}, financial_filter value:{financial_filter_value}')
            print(f'current page symbols:{result.symbols}')
            scanner_result_symbols.update(result.symbols)
        time.sleep(10)
        # Handle pagination
        if result.cursor_id is None:
            is_last_page = True
        else:
            cursor_id = result.cursor_id

    print(f'scanned symbols:{scanner_result_symbols}')

Hot ETFs: package_us_v1_etf_hot
Bank ETF: package_us_v1_etf_bank
Bond ETF: package_us_v1_etf_bond
Buffer ETF: package_us_v1_etf_buffer
Broad Index ETF: package_us_v1_etf_index
Leveraged & Inverse ETF: package_us_v1_etf_leverage
Sector ETF: package_us_v1_etf_sector
Single Stock Leveraged ETF: package_us_v1_etf_single_stock
Market Cap ETF: package_us_v1_etf_market_cap
Thematic ETF: package_us_v1_etf_thematic
International ETF: package_us_v1_etf_international
Growth & Value ETF: package_us_v1_etf_growth
Commodity ETF: package_us_v1_etf_commodity
ARK ETF: package_us_v1_etf_ark
Volatility ETF: package_us_v1_etf_volatility
Currency ETF: package_us_v1_etf_currency
Alternative Investment ETF: package_us_v1_etf_alternative

from tigeropen.quote.quote_client import QuoteClient
from tigeropen.tiger_open_config import get_client_config
from tigeropen.common.consts import Market
from tigeropen.quote.domain.filter import StockFilter
from tigeropen.common.consts.filter_fields import MultiTagField

client_config = get_client_config(private_key_path='private_key_path', tiger_id='your tiger id', account='your account')
quote_client = QuoteClient(client_config)

def test_market_scanner_etf():
    # Filter by ETF type, here we filter growth and alternative investment ETFs
    multi_tag_filter_etftype = StockFilter(MultiTagField.ETF_TYPE, tag_list=["package_us_v1_etf_growth", "package_us_v1_etf_alternative"])
    
    cursor_id = None
    page_size = 50
    # Whether it's the last page of data
    is_last_page = False
    # Symbol list after filtering
    scanner_result_symbols = set()

    while not is_last_page:
        result = quote_client.market_scanner(market=Market.US,
                                          filters=[multi_tag_filter_etftype],
                                          cursor_id=cursor_id,
                                          page_size=page_size)
        
        if result.total_page:
            for item in result.items:
                symbol = item.symbol
                market = item.market
                etf_type_value = item[multi_tag_filter_etftype]
                print(f'page:{result.page}, symbol:{symbol}, etf_type:{etf_type_value}')
            print(f'current page symbols:{result.symbols}')
            scanner_result_symbols.update(result.symbols)
            
        time.sleep(10)
        # Handle pagination
        if result.cursor_id is None:
            is_last_page = True
        else:
            cursor_id = result.cursor_id

    print(f'scanned symbols:{scanner_result_symbols}')

from tigeropen.quote.quote_client import QuoteClient
from tigeropen.common.consts import TradingSession, Market
from tigeropen.common.consts.filter_fields import MultiTagField

from tigeropen.tiger_open_config import TigerOpenClientConfig
client_config = TigerOpenClientConfig(props_path='/path/to/your/properties/file/')

quote_client = QuoteClient(client_config)

field_list = [ MultiTagField.Concept, MultiTagField.Industry]
result = quote_client.get_market_scanner_tags(market=Market.US, fields=field_list)
print(result)

[
    {
        "market": "US",
        "multi_tag_field": "MultiTagField_Concept",
        "tag_list": [
            {
                "tag": "BK4565",
                "value": "NFT Concept"
            },
            {
                "tag": "BK4564",
                "value": "Space Concept"
            },
            {
                "tag": "BK4567",
                "value": "ESG Concept"
            },
            {
                "tag": "BK4566",
                "value": "Capital Group"
            },
            {
                "tag": "BK4568",
                "value": "US Anti-Pandemic Concept"
            },
            {
                "tag": "BK4561",
                "value": "Soros Holdings"
            },
            {
                "tag": "BK4560",
                "value": "Cybersecurity Concept"
            }
        ]
    }
]