--- title: "JSON Format Example" description: "This page explains how to import custom data of a single security sourced in JSON format." canonical: https://www.quantconnect.com/docs/v2/writing-algorithms/importing-data/streaming-data/custom-securities/json-format-example markdown: https://www.quantconnect.com/docs/v2/writing-algorithms/importing-data/streaming-data/custom-securities/json-format-example.md language: python source: https://github.com/QuantConnect/Documentation/tree/master/03%20Writing%20Algorithms/16%20Importing%20Data/02%20Streaming%20Data/02%20Custom%20Securities/03%20JSON%20Format%20Example modified: 2026-10-29 index: https://www.quantconnect.com/llms.txt --- # JSON Format Example [Documentation](https://www.quantconnect.com/docs/v2.md) > [Writing Algorithms](https://www.quantconnect.com/docs/v2/writing-algorithms.md) > Importing Data > Streaming Data > Custom Securities > JSON Format Example > Code examples are shown in Python. Append `?lang=csharp` to this URL for the C# version of this page. ## Introduction This page explains how to import custom data of a single security sourced in `JSON` format. ## Data Format The following code snippet shows an example `JSON` file ``` [ { "Date": "1997-01-01", "Open": 905.2, "High": 941.4, "Low": 905.2, "Close": 939.55, "SharesTraded": 38948210, "Tur11er(Rs.Cr)": 978.21 }, { "Date": "1997-01-02", "Open": 941.95, "High": 944, "Low": 925.05, "Close": 927.05, "SharesTraded": 49118380, "Tur11er(Rs.Cr)": 1150.42 }, ... { "Date": "2014-07-25", "Open": 7828.2, "High": 7840.95, "Low": 7748.6, "Close": 7790.45, "SharesTraded": 153936037, "Tur11er(Rs.Cr)": 7827.61 }, { "Date": "2014-07-28", "Open": 7792.9, "High": 7799.9, "Low": 7722.65, "Close": 7748.7, "SharesTraded": 116534670, "Tur11er(Rs.Cr)": 6107.78 } ] ``` The data in the file must be in chronological order. ## Define Custom Types To define a custom data type, inherit the `PythonData` class and override the [GetSource](https://www.quantconnect.com/docs/v2/writing-algorithms/importing-data/streaming-data/key-concepts.md#04-Set-Data-Sources) and [Reader](https://www.quantconnect.com/docs/v2/writing-algorithms/importing-data/streaming-data/key-concepts.md#05-Parse-Custom-Data) methods. If you need to create multiple objects in your `reader` method from a single `line`, follow these steps: 1. In the `get_source` method, pass `FileFormat.UNFOLDING_COLLECTION` as the third argument to the `SubscriptionDataSource` constructor. 2. In the `reader` method, order the objects by their timestamp and then return a `BaseDataCollection(end_time, config.symbol, objects)` where `objects` is a list of your custom data objects. ```python class MyCustomDataType(PythonData): def get_source(self, config: SubscriptionDataConfig, date: datetime, is_live: bool) -> SubscriptionDataSource: if not is_live: return SubscriptionDataSource("", SubscriptionTransportMedium.OBJECT_STORE, FileFormat.UNFOLDING_COLLECTION) return SubscriptionDataSource("https://raw.githubusercontent.com/QuantConnect/Documentation/master/Resources/datasets/custom-data/unfolding-collection-example.json", SubscriptionTransportMedium.REMOTE_FILE, FileFormat.UNFOLDING_COLLECTION) def reader(self, config: SubscriptionDataConfig, line: str, date: datetime, is_live: bool) -> BaseData: if not (line.strip()): return None objects = [] data = json.loads(line) for datum in data: index = MyCustomDataType() index.symbol = config.symbol index.time = datetime.strptime(datum["Date"], "%Y-%m-%d") index.end_time = index.time + timedelta(1) index["Open"] = float(datum["Open"]) index["High"] = float(datum["High"]) index["Low"] = float(datum["Low"]) index["Close"] = float(datum["Close"]) index.value = index["Close"] objects.append(index) return BaseDataCollection(objects[-1].end_time, config.symbol, objects) ``` ## Create Subscriptions To create a subscription for the custom type, in the `initialize` method, call the `add_data` method. The `add_data` method returns a `Security` object, which contains a `Symbol`. Save a reference to the `symbol` so you can use it in `on_data` to access the security data in the `Slice`. ```python class MyAlgorithm(QCAlgorithm): def initialize(self) -> None: self._symbol = self.add_data(MyCustomDataType, "MyCustomDataType", Resolution.DAILY).symbol ``` The `add_data` method creates a subscription for a single custom data asset and adds it to your **user-defined** universe. ## Receive Custom Data As your data reader reads your custom data file, LEAN adds the data points in the `Slice` it passes to your algorithm's `on_data` method. To collect the custom data, use the `symbol` or name of your custom data subscription. You can access the `value` and custom properties of your custom data class from the `Slice`. To access the custom properties, pass the property name to the `get_property` method. ```python class MyAlgorithm(QCAlgorithm): def on_data(self, slice: Slice) -> None: if slice.contains_key(self._symbol): custom_data = slice[self._symbol] close = custom_data.close ``` If you add custom properties to your data object in the `reader` method, LEAN adds them as members to the data object in the `Slice`. To ensure the property names you add in the `reader` method follow the convention of member names, LEAN applies the following changes to the property names you provide in the `reader` method: 1. `-` and `.` characters are replaced with whitespace. 2. The first letter is capitalized. 3. Whitespace characters are removed. For example, if you set a property name in the `reader` method to `['some-property.name']`, you can access it in the `on_data` method through the `Somepropertyname` member of your data object. ## Demonstration Algorithms - [CustomDataBitcoinAlgorithm.py](https://github.com/QuantConnect/Lean/blob/master/Algorithm.Python/CustomDataBitcoinAlgorithm.py) (Python)