Create simple_universe.py

This example aims to help users get familiar with catalyst API's to collect and handle data.

catalyst/examples/simple_universe.py

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+"""
+Requires Catalyst version 0.3.0 or above
+Tested on Catalyst version 0.3.2
+
+These example aims to provide and easy way for users to learn how to collect data from the different exchanges.
+You simply need to specify the exchange and the market that you want to focus on.
+You will all see how to create a universe and filter it base on the exchange and the market you desire.
+
+The example prints out the closing price of all the pairs for a given market-exchange every 30 minutes.
+The example also contains the ohlcv minute data for the past seven days which could be used to create indicators
+Use this as the backbone to create your own trading strategies.
+"""
+
+import pandas as pd
+from catalyst import run_algorithm
+from catalyst.exchange.exchange_utils import get_exchange_symbols
+
+from catalyst.api import (
+    symbols,
+)
+
+
+def initialize(context):
+    context.i = -1  # counts the minutes
+    context.exchange = 'poloniex'  # must match the exchange specified in run_algorithm
+    context.base_currency = 'btc'  # must match the base currency specified in run_algorithm
+
+
+def handle_data(context, data):
+    lookback = 60 * 24 * 7  # (minutes, hours, days) of how far to lookback in the data history
+    context.i += 1
+
+    # we must first wait until enough minutes, hours or days have passed for data history to work
+    if context.i < lookback:
+        return
+
+    # current date formatted into a string
+    today = context.blotter.current_dt.strftime('%Y-%m-%d %H:%M:%S')
+    date, time = str(today).split(' ')
+
+    # update universe everyday
+    new_day = 60 * 24
+    if not context.i % new_day:
+        context.universe = universe(context, date)
+
+    # get data every 30 minutes
+    minutes = 30
+    if not context.i % minutes and context.universe:
+        # we iterate for every pair in the current universe
+        for coin in context.coins:
+            pair = str(coin.symbol)
+
+            # ohlcv data (the standard data required for candlestick or indicators/signals)
+            open = data.history(coin, 'open', bar_count=lookback, frequency='1m').ffill().bfill()
+            high = data.history(coin, 'high', bar_count=lookback, frequency='1m').ffill().bfill()
+            low = data.history(coin, 'low', bar_count=lookback, frequency='1m').ffill().bfill()
+            close = data.history(coin, 'price', bar_count=lookback, frequency='1m').ffill().bfill()
+            volume = data.history(coin, 'volume', bar_count=lookback, frequency='1m').ffill().bfill()
+
+            # close[-1] is the equivalent to current price
+            # displays the minute price for each pair every 30 minutes
+            print(today, pair, close[-1])
+
+
+def analyze(context=None, results=None):
+    pass
+
+
+def universe(context, date):
+    # Get the universe for a given exchange and a given base_currency market
+    # Example: Poloniex BTC Market
+    json_symbols = get_exchange_symbols(context.exchange)  # get all the pairs for the exchange
+    poloniex_universe_df = pd.DataFrame.from_dict(json_symbols).transpose().astype(str)  # convert into a dataframe
+    poloniex_universe_df['base_currency'] = poloniex_universe_df.apply(lambda row: row.symbol.split('_')[1],
+                                                                       axis=1)
+    poloniex_universe_df['market_currency'] = poloniex_universe_df.apply(lambda row: row.symbol.split('_')[0],
+                                                                         axis=1)
+    # Filter all the exchange pairs to only the ones for a give base currency
+    poloniex_universe_df = poloniex_universe_df[poloniex_universe_df['base_currency'] == context.base_currency]
+
+    # Filter all the pairs to ensure that pair existed in the current date
+    poloniex_universe_df = poloniex_universe_df[poloniex_universe_df.start_date < date]
+    context.coins = symbols(*poloniex_universe_df.symbol)  # convert all the pairs to symbols
+    return poloniex_universe_df.symbol.tolist()
+
+
+if __name__ == '__main__':
+    start_date = pd.to_datetime('2017-01-01', utc=True)
+    end_date = pd.to_datetime('2017-10-15', utc=True)
+
+    performance = run_algorithm(start=start_date, end=end_date,
+                                capital_base=10000.0,
+                                initialize=initialize,
+                                handle_data=handle_data,
+                                analyze=analyze,
+                                exchange_name='poloniex',
+                                bundle='poloniex',
+                                data_frequency='minute',
+                                base_currency='btc',
+                                live=False,
+                                live_graph=False,
+                                algo_namespace='simple_universe')
+
+"""
+Run in Terminal (inside catalyst environment):
+python simple_universe.py
+"""