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Fetching Real Time Data using Python | Interactive Brokers | Quantra Free Course - YouTube
Channel: Quantra
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In this video,
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we will learn how to fetch real-time
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data for the given securities
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from the Interactive Brokers server.
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Fetching Real-time Data
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The IBridgePy package contains two
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methods namely data.current and
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show_real_time_price method
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to fetch real-time data.
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Let us see how to
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use each of these methods.
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data.current method
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The data.current method returns
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the real-time data for the
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given securities for
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the specified fields.
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The slide shows the syntax
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of the data.current method.
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The security argument in the
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data.current method signifies
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the security object, created by
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either using the symbol, symbols
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or the superSymbol functions.
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The fields argument can take
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values like the ask price,
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bid price, ask size, bid
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size, last traded price etc.
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Let us take some examples
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and see how the method in used.
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Let us see how to
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pull real-time data for a
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single security with a single
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field passed to it.
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First, we create a security
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object using the AAPL stock.
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This security object is used
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as the argument to the
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data.current method.
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We specify the field for
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which we want to pull
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the data as the second
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argument to the
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data.current method.
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The method will return a
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scalar value of the selected
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field which can be seen
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in the Python console.
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Let us now see how
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to pull data for a
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single security with a list of fields.
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In this case, we specify
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a list of fields instead
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of a single field as
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the second argument to the
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data.current method.
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A pandas series is returned
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whose indices are the fields,
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and whose values are scalar
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values for this asset for each field.
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In the third example,
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let us pass a list of
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securities and a list of fields.
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First, we create a security
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object which contains a list of securities.
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This security object is passed
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to the data.current
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method along with the list
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of fields for which we
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want to pull the data.
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In this case, a pandas
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data frame is returned, which
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is indexed by securities.
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The columns represent the requested
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fields, filled with the scalar
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values for each security for
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each field.
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To pull real-time data for
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a futures contract we use
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the superSymbol function and
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specify the relevant fields of
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the futures contract as arguments
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to the function.
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This security object is passed
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to the data.current
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method to fetch the
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real-time data.
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We can use the same
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superSymbol function to fetch
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data for an options contract
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as illustrated in this example.
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Another way to fetch
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real-time data is using
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show_real_time_price method.
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show_real_time_price method
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The show_real_time_price
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method is used to request
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real-time quotes of the
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specified security from Interactive
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Brokers server.
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The real-time prices are received
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automatically until the request is cancelled.
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In case the user has not subscribed to
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the real-time quotes of the
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requested security, an error
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message is thrown.
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The slide shows the syntax
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of the show_real_time_price method.
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The method takes a security
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object which is created using
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the symbol function.
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The version argument takes valid
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values like bid price, ask
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price and last price.
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Let us
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see how this is done in Python.
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As can be seen, the
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method pulls real-time values for
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the specified field.
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That is all for this video lecture.
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In this video, we saw
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how to fetch real-time data
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from Interactive Brokers server.
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In the next video, we
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will learn how to fetch
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historical data using IBridgePy.
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