mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-18 12:20:12 +08:00
Housekeeping and documentation
This commit is contained in:
Frederic Fortier
@@ -274,16 +274,13 @@ class Bitfinex(Exchange):
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def subscribe_to_market_data(self, symbol):
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pass
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def get_candles(self, data_frequency, assets,
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end_dt=None, bar_count=None, limit=None):
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def get_candles(self, data_frequency, assets, bar_count=None):
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"""
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Retrieve OHLVC candles from Bitfinex
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:param data_frequency:
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:param assets:
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:param end_dt:
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:param bar_count:
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:param limit:
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:return:
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Available Frequencies
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@@ -596,7 +593,7 @@ class Bitfinex(Exchange):
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"""
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Fetch ticket data for assets
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https://docs.bitfinex.com/v2/reference#rest-public-tickers
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:param date:
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:param assets:
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:return:
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"""
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@@ -610,16 +607,17 @@ class Bitfinex(Exchange):
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symbols=','.join(symbols),
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)
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)
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tickers = response.json()
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except Exception as e:
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raise ExchangeRequestError(error=e)
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if 'message' in tickers:
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if 'error' in response.content:
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raise ExchangeRequestError(
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error='Unable to retrieve tickers: {}'.format(
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tickers['message'])
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response.content)
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)
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tickers = response.json()
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formatted_tickers = []
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for index, ticker in enumerate(tickers):
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if not len(ticker) == 11:
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+286
-250
@@ -26,95 +26,6 @@ class Exchange:
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self.assets = {}
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self._portfolio = None
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def get_trading_pairs(self, pairs):
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return [pair for pair in pairs if pair in self.trading_pairs]
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def get_symbol(self, asset):
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symbol = None
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for key in self.assets:
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if not symbol and self.assets[key].symbol == asset.symbol:
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symbol = key
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if not symbol:
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raise ValueError('Currency %s not supported by exchange %s' %
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(asset['symbol'], self.name))
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return symbol
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def get_asset(self, symbol):
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"""
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Find an Asset on the current exchange based on its Catalyst symbol
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:param symbol: the [target]_[base] currency pair symbol
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:return: Asset
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"""
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asset = None
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for key in self.assets:
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if not asset and self.assets[key].symbol.lower() == symbol.lower():
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asset = self.assets[key]
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if not asset:
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raise SymbolNotFound('Asset not found: %s' % symbol)
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return asset
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def get_symbols(self, assets):
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symbols = []
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for asset in assets:
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symbols.append(self.get_symbol(asset))
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return symbols
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@staticmethod
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def asset_parser(asset):
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for key in asset:
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if key == 'start_date':
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asset[key] = pd.to_datetime(asset[key], utc=True)
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return asset
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def load_assets(self, symbol_map):
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for exchange_symbol in symbol_map:
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asset_obj = Asset(
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sid=abs(hash(symbol_map[exchange_symbol]['symbol']))
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% (10 ** 4),
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exchange=self.name,
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end_date=pd.Timestamp.utcnow() + timedelta(minutes=300000),
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**symbol_map[exchange_symbol]
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)
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self.assets[exchange_symbol] = asset_obj
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def check_open_orders(self):
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transactions = list()
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if self.portfolio.open_orders:
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for order_id in list(self.portfolio.open_orders):
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log.debug('found open order: {}'.format(order_id))
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order, executed_price = self.get_order(order_id)
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log.debug('got updated order {}'.format(order))
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if order.status == ORDER_STATUS.FILLED:
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transaction = Transaction(
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asset=order.asset,
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amount=order.amount,
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dt=pd.Timestamp.utcnow(),
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price=executed_price,
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order_id=order.id,
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commission=order.commission
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)
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transactions.append(transaction)
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self.portfolio.execute_order(order, transaction)
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elif order.status == ORDER_STATUS.CANCELLED:
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self.portfolio.remove_order(order)
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else:
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delta = pd.Timestamp.utcnow() - order.dt
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log.info(
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'order {order_id} still open after {delta}'.format(
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order_id=order_id,
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delta=delta
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)
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)
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return transactions
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@abstractmethod
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def subscribe_to_market_data(self, symbol):
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pass
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@@ -139,6 +50,277 @@ class Exchange:
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def time_skew(self):
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pass
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def get_symbol(self, asset):
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"""
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Get the exchange specific symbol of the given asset.
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:param asset: Asset
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:return: symbol: str
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"""
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symbol = None
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for key in self.assets:
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if not symbol and self.assets[key].symbol == asset.symbol:
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symbol = key
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if not symbol:
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raise ValueError('Currency %s not supported by exchange %s' %
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(asset['symbol'], self.name))
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return symbol
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def get_symbols(self, assets):
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"""
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Get a list of symbols corresponding to each given asset.
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:param assets: Asset[]
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:return:
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"""
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symbols = []
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for asset in assets:
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symbols.append(self.get_symbol(asset))
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return symbols
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def get_asset(self, symbol):
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"""
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Find an Asset on the current exchange based on its Catalyst symbol
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:param symbol: the [target]_[base] currency pair symbol
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:return: Asset
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"""
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asset = None
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for key in self.assets:
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if not asset and self.assets[key].symbol.lower() == symbol.lower():
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asset = self.assets[key]
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if not asset:
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raise SymbolNotFound('Asset not found: %s' % symbol)
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return asset
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@staticmethod
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def asset_parser(asset):
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"""
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Helper method to de-serialize Asset objects correctly.
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:param asset:
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:return:
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"""
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for key in asset:
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if key == 'start_date':
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asset[key] = pd.to_datetime(asset[key], utc=True)
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return asset
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def load_assets(self, symbol_map):
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"""
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Populate the 'assets' attribute with a dictionary of Assets.
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The key of the resulting dictionary is the exchange specific
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currency pair symbol. The universal symbol is contained in the
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'symbol' attribute of each asset.
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Note
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----
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The sid of each asset is calculated based on a numeric hash of the
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universal symbol. This simple approach avoids maintaining a mapping
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of sids.
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:param symbol_map:
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:return:
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"""
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for exchange_symbol in symbol_map:
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asset_obj = Asset(
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sid=abs(hash(symbol_map[exchange_symbol]['symbol']))
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% (10 ** 4),
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exchange=self.name,
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end_date=pd.Timestamp.utcnow() + timedelta(minutes=300000),
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**symbol_map[exchange_symbol]
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)
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self.assets[exchange_symbol] = asset_obj
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def check_open_orders(self):
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"""
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Loop through the list of open orders in the Portfolio object.
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For each executed order found, create a transaction and apply to the
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Portfolio.
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:return:
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transactions: Transaction[]
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"""
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transactions = list()
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if self.portfolio.open_orders:
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for order_id in list(self.portfolio.open_orders):
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log.debug('found open order: {}'.format(order_id))
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order, executed_price = self.get_order(order_id)
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log.debug('got updated order {} {}'.format(
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order, executed_price))
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if order.status == ORDER_STATUS.FILLED:
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transaction = Transaction(
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asset=order.asset,
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amount=order.amount,
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dt=pd.Timestamp.utcnow(),
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price=executed_price,
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order_id=order.id,
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commission=order.commission
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)
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transactions.append(transaction)
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self.portfolio.execute_order(order, transaction)
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elif order.status == ORDER_STATUS.CANCELLED:
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self.portfolio.remove_order(order)
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else:
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delta = pd.Timestamp.utcnow() - order.dt
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log.info(
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'order {order_id} still open after {delta}'.format(
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order_id=order_id,
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delta=delta
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)
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)
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return transactions
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def get_spot_value(self, assets, field, dt=None, data_frequency='minute'):
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"""
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Public API method that returns a scalar value representing the value
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of the desired asset's field at either the given dt.
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Parameters
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----------
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assets : Asset, ContinuousFuture, or iterable of same.
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The asset or assets whose data is desired.
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field : {'open', 'high', 'low', 'close', 'volume',
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'price', 'last_traded'}
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The desired field of the asset.
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dt : pd.Timestamp
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The timestamp for the desired value.
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data_frequency : str
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The frequency of the data to query; i.e. whether the data is
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'daily' or 'minute' bars
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Returns
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-------
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value : float, int, or pd.Timestamp
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The spot value of ``field`` for ``asset`` The return type is based
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on the ``field`` requested. If the field is one of 'open', 'high',
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'low', 'close', or 'price', the value will be a float. If the
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``field`` is 'volume' the value will be a int. If the ``field`` is
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'last_traded' the value will be a Timestamp.
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Bitfinex timeframes
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-------------------
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Available values: '1m', '5m', '15m', '30m', '1h', '3h', '6h', '12h',
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'1D', '7D', '14D', '1M'
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"""
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if field not in BASE_FIELDS:
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raise KeyError('Invalid column: ' + str(field))
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if isinstance(assets, collections.Iterable):
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values = list()
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for asset in assets:
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value = self.get_single_spot_value(
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asset, field, data_frequency)
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values.append(value)
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return values
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else:
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return self.get_single_spot_value(
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assets, field, data_frequency)
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def get_single_spot_value(self, asset, field, data_frequency):
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"""
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Similar to 'get_spot_value' but for a single asset
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:param asset:
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:param field:
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:param data_frequency:
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:return value: The spot value of the given asset / field
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"""
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log.debug(
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'fetching spot value {field} for symbol {symbol}'.format(
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symbol=asset.symbol,
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field=field
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)
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)
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ohlc = self.get_candles(data_frequency, asset)
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if field not in ohlc:
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raise KeyError('Invalid column: %s' % field)
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value = ohlc[field]
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log.debug('got spot value: {}'.format(value))
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return value
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def get_history_window(self,
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assets,
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end_dt,
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bar_count,
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frequency,
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field,
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data_frequency,
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ffill=True):
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"""
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Public API method that returns a dataframe containing the requested
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history window. Data is fully adjusted.
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Parameters
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----------
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assets : list of catalyst.data.Asset objects
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The assets whose data is desired.
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end_dt: not applicable to cryptocurrencies
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bar_count: int
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The number of bars desired.
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frequency: string
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"1d" or "1m"
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field: string
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The desired field of the asset.
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data_frequency: string
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The frequency of the data to query; i.e. whether the data is
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'daily' or 'minute' bars.
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# TODO: fill how?
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ffill: boolean
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Forward-fill missing values. Only has effect if field
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is 'price'.
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Returns
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-------
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A dataframe containing the requested data.
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"""
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candles = self.get_candles(
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data_frequency=frequency,
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assets=assets,
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bar_count=bar_count,
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)
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frames = []
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for asset in assets:
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asset_candles = candles[asset]
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asset_data = dict()
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asset_data[asset] = map(lambda candle: candle[field],
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asset_candles)
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dates = map(lambda candle: candle['last_traded'],
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asset_candles)
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df = pd.DataFrame(asset_data, index=dates)
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frames.append(df)
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return pd.concat(frames)
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@abstractmethod
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def order(self, asset, amount, limit_price, stop_price, style):
|
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"""Place an order.
|
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@@ -233,171 +415,25 @@ class Exchange:
|
||||
pass
|
||||
|
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@abstractmethod
|
||||
def get_spot_value(self, assets, field, dt, data_frequency):
|
||||
def get_candles(self, data_frequency, assets, bar_count=None):
|
||||
"""
|
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Public API method that returns a scalar value representing the value
|
||||
of the desired asset's field at either the given dt.
|
||||
Retrieve OHLCV candles for the given assets
|
||||
|
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Parameters
|
||||
----------
|
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assets : Asset, ContinuousFuture, or iterable of same.
|
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The asset or assets whose data is desired.
|
||||
field : {'open', 'high', 'low', 'close', 'volume',
|
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'price', 'last_traded'}
|
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The desired field of the asset.
|
||||
dt : pd.Timestamp
|
||||
The timestamp for the desired value.
|
||||
data_frequency : str
|
||||
The frequency of the data to query; i.e. whether the data is
|
||||
'daily' or 'minute' bars
|
||||
|
||||
Returns
|
||||
-------
|
||||
value : float, int, or pd.Timestamp
|
||||
The spot value of ``field`` for ``asset`` The return type is based
|
||||
on the ``field`` requested. If the field is one of 'open', 'high',
|
||||
'low', 'close', or 'price', the value will be a float. If the
|
||||
``field`` is 'volume' the value will be a int. If the ``field`` is
|
||||
'last_traded' the value will be a Timestamp.
|
||||
:param data_frequency:
|
||||
:param assets:
|
||||
:param end_dt:
|
||||
:param bar_count:
|
||||
:param limit:
|
||||
:return:
|
||||
"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
def get_candles(self, data_frequency, assets,
|
||||
end_dt=None, bar_count=None, limit=None):
|
||||
"""
|
||||
Retrieve OHLC candles
|
||||
"""
|
||||
pass
|
||||
|
||||
def get_spot_value(self, assets, field, dt=None, data_frequency='minute'):
|
||||
"""
|
||||
Public API method that returns a scalar value representing the value
|
||||
of the desired asset's field at either the given dt.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
assets : Asset, ContinuousFuture, or iterable of same.
|
||||
The asset or assets whose data is desired.
|
||||
field : {'open', 'high', 'low', 'close', 'volume',
|
||||
'price', 'last_traded'}
|
||||
The desired field of the asset.
|
||||
dt : pd.Timestamp
|
||||
The timestamp for the desired value.
|
||||
data_frequency : str
|
||||
The frequency of the data to query; i.e. whether the data is
|
||||
'daily' or 'minute' bars
|
||||
|
||||
Returns
|
||||
-------
|
||||
value : float, int, or pd.Timestamp
|
||||
The spot value of ``field`` for ``asset`` The return type is based
|
||||
on the ``field`` requested. If the field is one of 'open', 'high',
|
||||
'low', 'close', or 'price', the value will be a float. If the
|
||||
``field`` is 'volume' the value will be a int. If the ``field`` is
|
||||
'last_traded' the value will be a Timestamp.
|
||||
|
||||
Bitfinex timeframes
|
||||
-------------------
|
||||
Available values: '1m', '5m', '15m', '30m', '1h', '3h', '6h', '12h',
|
||||
'1D', '7D', '14D', '1M'
|
||||
"""
|
||||
if field not in BASE_FIELDS:
|
||||
raise KeyError('Invalid column: ' + str(field))
|
||||
|
||||
if isinstance(assets, collections.Iterable):
|
||||
values = list()
|
||||
for asset in assets:
|
||||
value = self.get_single_spot_value(
|
||||
asset, field, data_frequency)
|
||||
values.append(value)
|
||||
|
||||
return values
|
||||
else:
|
||||
return self.get_single_spot_value(
|
||||
assets, field, data_frequency)
|
||||
|
||||
def get_single_spot_value(self, asset, field, data_frequency):
|
||||
log.debug(
|
||||
'fetching spot value {field} for symbol {symbol}'.format(
|
||||
symbol=asset.symbol,
|
||||
field=field
|
||||
)
|
||||
)
|
||||
|
||||
ohlc = self.get_candles(data_frequency, asset)
|
||||
if field not in ohlc:
|
||||
raise KeyError('Invalid column: %s' % field)
|
||||
|
||||
value = ohlc[field]
|
||||
log.debug('got spot value: {}'.format(value))
|
||||
|
||||
return value
|
||||
|
||||
def get_history_window(self,
|
||||
assets,
|
||||
end_dt,
|
||||
bar_count,
|
||||
frequency,
|
||||
field,
|
||||
data_frequency,
|
||||
ffill=True):
|
||||
|
||||
"""
|
||||
Public API method that returns a dataframe containing the requested
|
||||
history window. Data is fully adjusted.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
assets : list of catalyst.data.Asset objects
|
||||
The assets whose data is desired.
|
||||
|
||||
bar_count: int
|
||||
The number of bars desired.
|
||||
|
||||
frequency: string
|
||||
"1d" or "1m"
|
||||
|
||||
field: string
|
||||
The desired field of the asset.
|
||||
|
||||
data_frequency: string
|
||||
The frequency of the data to query; i.e. whether the data is
|
||||
'daily' or 'minute' bars.
|
||||
|
||||
# TODO: fill how?
|
||||
ffill: boolean
|
||||
Forward-fill missing values. Only has effect if field
|
||||
is 'price'.
|
||||
|
||||
Returns
|
||||
-------
|
||||
A dataframe containing the requested data.
|
||||
"""
|
||||
|
||||
candles = self.get_candles(
|
||||
data_frequency=frequency,
|
||||
assets=assets,
|
||||
bar_count=bar_count,
|
||||
end_dt=end_dt
|
||||
)
|
||||
|
||||
frames = []
|
||||
for asset in assets:
|
||||
asset_candles = candles[asset]
|
||||
|
||||
asset_data = dict()
|
||||
asset_data[asset] = map(lambda candle: candle[field],
|
||||
asset_candles)
|
||||
|
||||
dates = map(lambda candle: candle['last_traded'],
|
||||
asset_candles)
|
||||
|
||||
df = pd.DataFrame(asset_data, index=dates)
|
||||
frames.append(df)
|
||||
|
||||
return pd.concat(frames)
|
||||
|
||||
@abc.abstractmethod
|
||||
def tickers(self, date, pairs):
|
||||
def tickers(self, assets):
|
||||
"""
|
||||
Retrieve current tick data for the given assets
|
||||
|
||||
:param assets:
|
||||
:return:
|
||||
"""
|
||||
return
|
||||
|
||||
Reference in New Issue
Block a user