import tvscreener as tvs

# Stock Screener
ss = tvs.StockScreener()
df = ss.get()  # returns a dataframe with 150 rows by default

# Forex Screener
fs = tvs.ForexScreener()
df = fs.get()

# Crypto Screener
cs = tvs.CryptoScreener()
df = cs.get()

# Bond Screener (NEW)
bs = tvs.BondScreener()
df = bs.get()

# Futures Screener (NEW)
futs = tvs.FuturesScreener()
df = futs.get()

# Coin Screener (NEW) - CEX and DEX coins
coins = tvs.CoinScreener()
df = coins.get()

# Option Screener - option chains with greeks and IV (underlying required)
opts = tvs.OptionScreener("NASDAQ:AAPL")
opts.where(tvs.OptionField.DELTA.between(0.4, 0.6))
df = opts.get()

# Implied volatility term structure
df = tvs.get_iv_term_structure("NASDAQ:AAPL")

# ETF Screener - ETFs sorted by assets under management
etfs = tvs.ETFScreener()
etfs.where(tvs.StockField.EXPENSE_RATIO < 0.1)
df = etfs.get()

# Index Screener - indices, CFDs, crypto market caps
df = tvs.IndexScreener().main_indices().get()

# Economics Screener - 15,000+ economic indicators
es = tvs.EconomicsScreener()
es.where(tvs.EconomicsField.COUNTRY_CODE == 'US')
df = es.get()

# Government bond yield curve
df = tvs.get_yield_curve("US")

ss = tvs.StockScreener()
ss.where((tvs.StockField.SECTOR == 'Finance') | (tvs.StockField.SECTOR == 'Utilities'))
ss.where(tvs.StockField.PRICE.above_pct(tvs.StockField.SIMPLE_MOVING_AVERAGE_50, 5))
df = ss.get()

# TradingView's own screens
df = tvs.StockScreener().set_preset(tvs.Preset.GAINERS).get()

earnings = tvs.get_earnings_calendar("2026-10-12", "2026-10-18")
dividends = tvs.get_dividends_calendar("2026-10-12", "2026-10-18")
ipos = tvs.get_ipo_calendar("2026-10-01", "2026-10-31", markets=tvs.Market.ALL)
macro = tvs.get_economic_calendar("2026-10-12", "2026-10-18", countries=["US", "EU"], importance="high")

income = tvs.get_financials("NASDAQ:AAPL", "income", "FY")       # ~20 fiscal years
balance = tvs.get_financials("NASDAQ:AAPL", "balance_sheet", "FQ")
events = tvs.get_corporate_events("NASDAQ:AAPL")                  # dividends, earnings, splits
seasonals = tvs.get_seasonals("NASDAQ:AAPL")                      # monthly returns by year

for quote in tvs.stream_quotes(["NASDAQ:AAPL", "BINANCE:BTCUSDT"], duration=60):
    print(quote["symbol"], quote.get("price"))

news = tvs.get_news("NASDAQ:AAPL", corp_activity="insider_trading")
text = tvs.get_article(news["id"].iloc[0])
docs = tvs.get_documents("NASDAQ:AAPL", category="call_transcript")
transcript = tvs.get_document(docs["transcript_id"].iloc[0])

tvs.search_symbols("US0378331005")             # ISIN -> NASDAQ:AAPL and other listings
tvs.get_peers("NASDAQ:AAPL")
tvs.get_forward_curve("NYMEX:CL")
tvs.get_yield_matrix(["US", "DE", "JP"])
tvs.get_volatility_smile("NASDAQ:AAPL", "2026-11-13")

from tvscreener import StockScreener, StockField

ss = StockScreener()
ss.select(
    StockField.NAME,
    StockField.PRICE,
    StockField.CHANGE_PERCENT,
    StockField.VOLUME,
    StockField.MARKET_CAPITALIZATION
)
ss.where(StockField.MARKET_CAPITALIZATION > 1e9)
ss.where(StockField.CHANGE_PERCENT > 5)
df = ss.get()

from tvscreener import StockField

# Search fields by name or label
rsi_fields = StockField.search("rsi")
print(f"Found {len(rsi_fields)} RSI-related fields")

# Get all technical indicator fields
technicals = StockField.technicals()
print(f"Found {len(technicals)} technical fields")

# Get recommendation fields
recommendations = StockField.recommendations()

from tvscreener import (
    StockScreener, get_preset, list_presets,
    STOCK_PRICE_FIELDS, STOCK_VALUATION_FIELDS, STOCK_DIVIDEND_FIELDS,
    STOCK_PERFORMANCE_FIELDS, STOCK_OSCILLATOR_FIELDS
)

# See all available presets
print(list_presets())
# ['stock_price', 'stock_volume', 'stock_valuation', 'stock_dividend', ...]

# Use presets directly
ss = StockScreener()
ss.specific_fields = STOCK_VALUATION_FIELDS + STOCK_DIVIDEND_FIELDS
df = ss.get()

# Or get preset by name
fields = get_preset('stock_performance')

from tvscreener import StockScreener, StockField

ss = StockScreener()

# Get RSI with 1-hour interval
rsi_1h = StockField.RELATIVE_STRENGTH_INDEX_14.with_interval("60")

# Available intervals: 1, 5, 15, 30, 60, 120, 240, 1D, 1W, 1M
ss.specific_fields = [
    StockField.NAME,
    StockField.PRICE,
    rsi_1h,
    StockField.MACD_LEVEL_12_26.with_interval("240"),  # 4-hour MACD
]
df = ss.get()

import tvscreener as tvs

# Get raw data
ss = tvs.StockScreener()
df = ss.get()

# Apply TradingView styling
styled = tvs.beautify(df, tvs.StockField)

# Display in Jupyter/IPython (shows colored output)
styled

import tvscreener as tvs

# Basic streaming with iteration limit
ss = tvs.StockScreener()
for df in ss.stream(interval=10, max_iterations=5):
    print(f"Got {len(df)} rows")

# Streaming with callback
from datetime import datetime

def on_update(df):
    print(f"Updated at {datetime.now()}: {len(df)} rows")

ss = tvs.StockScreener()
try:
    for df in ss.stream(interval=5, on_update=on_update):
        # Process data
        pass
except KeyboardInterrupt:
    print("Stopped streaming")

# Stream with filters
ss = tvs.StockScreener()
ss.set_markets(tvs.Market.AMERICA)
for df in ss.stream(interval=30, max_iterations=10):
    print(df.head())