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BLD: misc housekeeping

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This commit is contained in:
fredfortier
2017-11-16 16:55:40 -05:00
parent e087e48088
commit 3fa88a3e56
7 changed files with 129 additions and 66 deletions
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catalyst/support/issue_47.py
+13 -14
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@@ -1,6 +1,6 @@
"""
Requires Catalyst version 0.3.0 or above
Tested on Catalyst version 0.3.2
Tested on Catalyst version 0.3.3
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.
@@ -27,7 +27,7 @@ from catalyst.api import (
def initialize(context):
context.i = -1 # counts the minutes
context.exchange = 'poloniex' # must match the exchange specified in run_algorithm
context.base_currency = 'eth' # must match the base currency specified in run_algorithm
context.base_currency = 'btc' # must match the base currency specified in run_algorithm
def handle_data(context, data):
@@ -56,21 +56,21 @@ def handle_data(context, data):
# 30 minute interval ohlcv data (the standard data required for candlestick or indicators/signals)
# 30T means 30 minutes re-sampling of one minute data. change to your desire time interval.
open = fill(data.history(coin, 'open', bar_count=lookback,
frequency='1m')).resample('30T').first()
opened = fill(data.history(coin, 'open', bar_count=lookback,
frequency='30T')).values
high = fill(data.history(coin, 'high', bar_count=lookback,
frequency='1m')).resample('30T').max()
frequency='30T')).values
low = fill(data.history(coin, 'low', bar_count=lookback,
frequency='1m')).resample('30T').min()
frequency='30T')).values
close = fill(data.history(coin, 'price', bar_count=lookback,
frequency='1m')).resample('30T').last()
frequency='30T')).values
volume = fill(data.history(coin, 'volume', bar_count=lookback,
frequency='1m')).resample('30T').sum()
frequency='30T')).values
# close[-1] is the equivalent to current price
# displays the minute price for each pair every 30 minutes
print(
today, pair, open[-1], high[-1], low[-1], close[-1], volume[-1])
today, pair, opened[-1], high[-1], low[-1], close[-1], volume[-1])
# ----------------------------------------------------------------------------------------------------------
# -------------------------------------- Insert Your Strategy Here -----------------------------------------
@@ -82,7 +82,7 @@ def analyze(context=None, results=None):
# Get the universe for a given exchange and a given base_currency market
# Example: Poloniex BTC Market
# Example: Poloniex btc Market
def universe(context, lookback_date, current_date):
json_symbols = get_exchange_symbols(
context.exchange) # get all the pairs for the exchange
@@ -103,7 +103,6 @@ def universe(context, lookback_date, current_date):
universe_df = universe_df[universe_df.end_daily >= current_date]
context.coins = symbols(
*universe_df.symbol) # convert all the pairs to symbols
print(universe_df.head(), len(universe_df))
return universe_df.symbol.tolist()
@@ -119,8 +118,8 @@ def fill(series):
if __name__ == '__main__':
start_date = pd.to_datetime('2017-01-01', utc=True)
end_date = pd.to_datetime('2017-10-15', utc=True)
start_date = pd.to_datetime('2017-01-08', utc=True)
end_date = pd.to_datetime('2017-11-13', utc=True)
performance = run_algorithm(start=start_date, end=end_date,
capital_base=10000.0,
@@ -129,7 +128,7 @@ if __name__ == '__main__':
analyze=analyze,
exchange_name='poloniex',
data_frequency='minute',
base_currency='eth',
base_currency='btc',
live=False,
live_graph=False,
algo_namespace='simple_universe')