wehub-resource-sync
55 lines
2.0 KiB
Python
55 lines
2.0 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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from custom_data import *
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class Test_CustomDataAlgorithm(QCAlgorithm):
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def initialize(self):
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self.add_data(Nifty, "NIFTY")
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self.add_data(CustomPythonData, "IBM", Resolution.DAILY)
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class Nifty(PythonData):
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'''NIFTY Custom Data Class'''
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def get_source(self, config, date, is_live_mode):
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return SubscriptionDataSource("https://www.dropbox.com/s/rsmg44jr6wexn2h/CNXNIFTY.csv?dl=1", SubscriptionTransportMedium.REMOTE_FILE)
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def reader(self, config, line, date, is_live_mode):
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if not (line.strip() and line[0].isdigit()): return None
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# New Nifty object
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index = Nifty()
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index.symbol = config.symbol
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try:
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# Example File Format:
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# Date, Open High Low Close Volume Turnover
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# 2011-09-13 7792.9 7799.9 7722.65 7748.7 116534670 6107.78
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data = line.split(',')
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index.time = datetime.strptime(data[0], "%Y-%m-%d")
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index.value = decimal.decimal(data[4])
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index["Open"] = float(data[1])
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index["High"] = float(data[2])
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index["Low"] = float(data[3])
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index["Close"] = float(data[4])
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except ValueError:
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# Do nothing
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return None
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return index
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