Nasdaq Data Link

Nasdaq Data Link provides a modern and efficient method of delivery for realtime exchange data and other financial information. Data is made available through a suite of APIs, allowing for effortless integration of data from disparate sources, and a dramatic reduction in time to market for customer-designed applications. The API is highly scalable, and robust enough to support the delivery of real-time exchange data.

Products Currently Available

Equities

The Nasdaq Stock Market

• Nasdaq Basic (real-time & delayed)
• Nasdaq Last Sale+ (real-time & delayed)
• Nasdaq TotalView
• Nasdaq Consolidated Quotes and Trades (real-time & delayed)

Nasdaq BX

• BX BBO
• BX Last Sale

Nasdaq PSX

• PSX BBO
• PSX Last Sale

Nasdaq Canada

• Nasdaq Canada Basic

OTC Markets

• OTC Markets (real-time & delayed)

Indexes & ETPs

• Global Index Data Service

Options

Nasdaq U.S. Derivatives

• Nasdaq Smart Options
• Nasdaq Options Greeks and Implied Volatility

Mutual Funds

• Nasdaq Fund Network

News

• Financial News

Items To Note

• Connecting to the API requires credentials, which are provided by the Nasdaq Data Operations team during an on-boarding process
• This sample code only connects to one topic (NLSCTA); during on-boarding process, you will receive a topic list that you're entitled to.
• See https://github.com/Nasdaq/NasdaqCloudDataService-SDK-Java for our officially support Java-based SDK.

Table of Contents

• Getting Started
• Using the SDK

Getting Started

Python version support

The SDK currently supports Python 3.9 and above

Get the SDK

The source code is currently hosted on GitHub at: https://github.com/Nasdaq/NasdaqCloudDataService-SDK-Python

• Clone the repository: git clone https://github.com/Nasdaq/NasdaqCloudDataService-SDK-Python.git
• Move into the directory cd NasdaqCloudDataService-SDK-Python
• Install the library and its dependencies from local source with pip install -e .

Optional: to use the Jupyter notebook provided,

• Download Jupyter notebook using either pip pip3 install notebook or conda conda install -c conda-forge notebook
• To run the notebook, use the command jupyter notebook and the Notebook Dashboard will open in your browser
• Select the file python_sdk_examples.ipynb

Stream configuration

Replace example stream properties in the file kafka-config.json (https://github.com/Nasdaq/NasdaqCloudDataService-SDK-Python/blob/master/ncdssdk_client/src/main/python/resources/kafka-config.json) with provided values during on-boarding.

Required kafka configuration

"bootstrap.servers": {streams_endpoint_url}:9094

For optional consumer configurations see: https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md

Client Authentication configuration

Replace example client authentication properties in the file client-authentication-config.json (https://github.com/Nasdaq/NasdaqCloudDataService-SDK-Python/blob/master/ncdssdk_client/src/main/python/resources/client-authentication-config.json) with valid credentials provided during on-boarding.

oauth.token.endpoint.uri: "https://{auth_endpoint_url}/auth/realms/pro-realm/protocol/openid-connect/token"
oauth.client.id: "client_id"
oauth.client.secret: "client_secret"

Logging Configuration

To enable debug logging, edit the file (https://github.com/Nasdaq/NasdaqCloudDataService-SDK-Python/blob/master/ncdssdk/src/main/resources/logging.json) and change the logging levels in whichever handler you would like output to go to.

For example, to enable debug logging to a file:

"file_handler": {
      "class": "logging.handlers.RotatingFileHandler",
      "level": "DEBUG",
      "formatter": "simple",
      "filename": "logging.log",
      "maxBytes": 10485760,
      "backupCount": 20,
      "encoding": "utf8"
    }
  },

  "loggers": {
    "": {
      "level": "DEBUG",
      "handlers": ["console", "file_handler"],
      "propogate": false
    }
  }
}

Next, add a debug option to your kafka configurations:

kafka_cfg = {
    "bootstrap.servers": "{streams_endpoint_url}:9094",
    "auto.offset.reset": "earliest",
    "debug": "all"
}

Create NCDS Session Client

How to run:

-opt -- Provide the operation you want to perform \n" +
  "        * TOP - View the top nnn records in the Topic/Stream\n" +
  "        * SCHEMA - Display the Schema for the topic\n" +
  "        * METRICS - Display the Metrics for the topic\n" +
  "        * TOPICS - List of streams available on Nasdaq Cloud DataService\n" +
  "        * GETMSG - Get one example message for the given message name\n" +
  "        * CONTSTREAM   - Retrieve continuous stream  \n" +
  "        * FILTERSTREAM  - Retrieve continuous stream filtered by symbols and/or msgtypes \n" +
  "        * HELP - help \n" +
"-topic -- Provide topic for selected option         --- REQUIRED for TOP,SCHEMA,METRICS,GETMSG,CONTSTREAM and FILTERSTREAM \n" +
"-symbols -- Provide symbols comma separated list    --- OPTIONAL for FILTERSTREAM" +
"-msgnames -- Provide msgnames comma separated list  --- OPTIONAL for FILTERSTREAM" +
"-authprops -- Provide Client Properties File path   --- For using different set of Client Authentication Properties \n" +
"-kafkaprops -- Provide Kafka Properties File path   --- For using different set of Kafka Properties \n" +
"-n -- Provide number of messages to retrieve        --- REQUIRED for TOP \n" +
"-msgName -- Provide name of message based on schema --- REQUIRED for GETMSG \n" +
"-timestamp -- Provide timestamp in milliseconds     --- OPTIONAL for TOP, CONTSTREAM and FILTERSTREAM\n"

A few examples:

Get first 100 records for given stream

python3.9 ncdssdk_client/src/main/python/ncdsclient/NCDSSession.py -opt TOP -n 100 -topic NLSCTA

Get all available streams

python3.9 ncdssdk_client/src/main/python/ncdsclient/NCDSSession.py -opt TOPICS

Using the SDK

Below are several examples for how to access data using the SDK. A Jupyter notebook with this same code and information is provided in the file python_sdk_examples.ipnyb

To run these examples, you will need the import and configuration dictionaries below. Replace the config information with your credentials.

from ncdssdk import NCDSClient

security_cfg = {
    "oauth.token.endpoint.uri": "https://{auth_endpoint_url}/auth/realms/demo/protocol/openid-connect/token",
    "oauth.client.id": "client",
    "oauth.client.secret": "client-secret"
}
kafka_cfg = {
    "bootstrap.servers": "{streams_endpoint_url}:9094",
    "auto.offset.reset": "earliest"
}

Getting list of data stream available

List all available data stream for the user

ncds_client = NCDSClient(security_cfg, kafka_cfg)
topics = ncds_client.list_topics_for_client()
print("Data set topics:")
for topic_entry in topics:
print(topic_entry)

Example output:

List of streams available on Nasdaq Cloud Data Service:
GIDS
NLSUTP
NLSCTA

Getting schema for the stream

This method returns the schema for the stream in Apache Avro format (https://avro.apache.org/docs/current/spec.html)

ncds_client = NCDSClient(security_cfg, kafka_cfg)
topic = "NLSCTA"
schema = ncds_client.get_schema_for_topic(topic)
print(schema)

Example output:

[ {
"type" : "record",
"name" : "SeqAdjClosingPrice",
"namespace" : "com.nasdaq.equities.trades.applications.nls.messaging.binary21",
"fields" : [ {
  "name" : "SoupPartition",
  "type" : "int"
}, {
  "name" : "SoupSequence",
  "type" : "long"
}, {
  "name" : "trackingID",
  "type" : "long"
}, {
  "name" : "msgType",
  "type" : "string"
}, {
  "name" : "symbol",
  "type" : "string"
}, {
  "name" : "securityClass",
  "type" : "string"
}, {
  "name" : "adjClosingPrice",
  "type" : "int"
} ],
"version" : "1"
}, {...
} .......
.... ]

Get first 10 messages of the stream

ncds_client = NCDSClient(security_cfg, kafka_cfg)
topic = "NLSCTA"
records = ncds_client.top_messages(topic)
for i in range(0, 10):
    print("key: ", records[i].key())
    print("value: ", str(records[i].value()))

Example output:

Top 10 Records for the Topic: NLSCTA
key: 14600739
value: {"SoupPartition": 0, "SoupSequence": 14600739, "trackingID": 72000000024569, "msgType": "S", "event": "E", "schema_name": "SeqSystemEventMessage"}
key: 14600740
value: {"SoupPartition": 0, "SoupSequence": 14600740, "trackingID": 72900000006514, "msgType": "J", "symbol": "A", "securityClass": "N", "consHigh": 1487799, "consLow": 1466600, "consClose": 1478100, "cosolidatedVolume": 1259303, "consOpen": 1486800, "schema_name": "SeqEndOfDayTradeSummary"}
key: 14600741
value: {"SoupPartition": 0, "SoupSequence": 14600741, "trackingID": 72900000006514, "msgType": "J", "symbol": "AA", "securityClass": "N", "consHigh": 378039, "consLow": 366800, "consClose": 368400, "cosolidatedVolume": 6047752, "consOpen": 372000, "schema_name": "SeqEndOfDayTradeSummary"}
key: 14600742
value: {"SoupPartition": 0, "SoupSequence": 14600742, "trackingID": 72900000006514, "msgType": "J", "symbol": "AAA", "securityClass": "P", "consHigh": 250400, "consLow": 250101, "consClose": 250250, "cosolidatedVolume": 3121, "consOpen": 250400, "schema_name": "SeqEndOfDayTradeSummary"}
key: 14600743
value: {"SoupPartition": 0, "SoupSequence": 14600743, "trackingID": 72900000006514, "msgType": "J", "symbol": "AAAU", "securityClass": "P", "consHigh": 176500, "consLow": 174700, "consClose": 176000, "cosolidatedVolume": 303143, "consOpen": 175000, "schema_name": "SeqEndOfDayTradeSummary"}
key: 14600744
value: {"SoupPartition": 0, "SoupSequence": 14600744, "trackingID": 72900000006514, "msgType": "J", "symbol": "AAC", "securityClass": "N", "consHigh": 97900, "consLow": 97500, "consClose": 97500, "cosolidatedVolume": 19787, "consOpen": 97600, "schema_name": "SeqEndOfDayTradeSummary"}
key: 14600745
value: {"SoupPartition": 0, "SoupSequence": 14600745, "trackingID": 72900000006514, "msgType": "J", "symbol": "AAC+", "securityClass": "N", "consHigh": 12800, "consLow": 12000, "consClose": 12500, "cosolidatedVolume": 85652, "consOpen": 12300, "schema_name": "SeqEndOfDayTradeSummary"}
key: 14600746
value: {"SoupPartition": 0, "SoupSequence": 14600746, "trackingID": 72900000006514, "msgType": "J", "symbol": "AAC=", "securityClass": "N", "consHigh": 100500, "consLow": 99500, "consClose": 100000, "cosolidatedVolume": 74060, "consOpen": 99500, "schema_name": "SeqEndOfDayTradeSummary"}
key: 14600747
value: {"SoupPartition": 0, "SoupSequence": 14600747, "trackingID": 72900000006514, "msgType": "J", "symbol": "AAIC", "securityClass": "N", "consHigh": 41850, "consLow": 40600, "consClose": 40600, "cosolidatedVolume": 241597, "consOpen": 41800, "schema_name": "SeqEndOfDayTradeSummary"}
key: 14600748
value: {"SoupPartition": 0, "SoupSequence": 14600748, "trackingID": 72900000006514, "msgType": "J", "symbol": "AAIC-B", "securityClass": "N", "consHigh": 249700, "consLow": 249700, "consClose": 249700, "cosolidatedVolume": 238, "consOpen": 249700, "schema_name": "SeqEndOfDayTradeSummary"}

Get first 10 messages of the stream from given timestamp

This returns the first 10 available messages of the stream given timestamp in milliseconds since the UNIX epoch.

ncds_client = NCDSClient(security_cfg, kafka_cfg)
topic="NLSCTA"
timestamp = 1590084446510
records = ncds_client.top_messages(topic, timestamp)
for i in range(0, 10):
    print("key: ", records[i].key())
    print("value: ", str(records[i].value()))

Example output:

Offset: 105834100
Top 10 Records for the Topic:NLSCTA
key:9362630
value :{"SoupPartition": 0, "SoupSequence": 9362630, "trackingID": 50845551492208, "msgType": "T", "marketCenter": "L", "symbol": "SIVR    ", "securityClass": "P", "controlNumber": "0000A2MLOB", "price": 164797, "size": 1, "saleCondition": "@  o", "cosolidatedVolume": 520174}
key:9362631
value :{"SoupPartition": 0, "SoupSequence": 9362631, "trackingID": 50845557908136, "msgType": "T", "marketCenter": "Q", "symbol": "TJX     ", "securityClass": "N", "controlNumber": "   8358213", "price": 540300, "size": 100, "saleCondition": "@   ", "cosolidatedVolume": 16278768}
key:9362632
value :{"SoupPartition": 0, "SoupSequence": 9362632, "trackingID": 50845565203932, "msgType": "T", "marketCenter": "L", "symbol": "CMI     ", "securityClass": "N", "controlNumber": "0000A2MLOC", "price": 1579900, "size": 100, "saleCondition": "@   ", "cosolidatedVolume": 568622}
key:9362633
value :{"SoupPartition": 0, "SoupSequence": 9362633, "trackingID": 50845565791061, "msgType": "T", "marketCenter": "L", "symbol": "UTI     ", "securityClass": "N", "controlNumber": "0000A2MLOD", "price": 70150, "size": 64, "saleCondition": "@  o", "cosolidatedVolume": 151359}
key:9362634
value :{"SoupPartition": 0, "SoupSequence": 9362634, "trackingID": 50845566628604, "msgType": "T", "marketCenter": "L", "symbol": "UFS     ", "securityClass": "N", "controlNumber": "0000A2MLOE", "price": 203660, "size": 24, "saleCondition": "@  o", "cosolidatedVolume": 664962}
key:9362635
value :{"SoupPartition": 0, "SoupSequence": 9362635, "trackingID": 50845569154140, "msgType": "T", "marketCenter": "L", "symbol": "KR      ", "securityClass": "N", "controlNumber": "0000A2MLOF", "price": 320350, "size": 100, "saleCondition": "@   ", "cosolidatedVolume": 4054473}
key:9362636
value :{"SoupPartition": 0, "SoupSequence": 9362636, "trackingID": 50845577944984, "msgType": "T", "marketCenter": "L", "symbol": "PAGP    ", "securityClass": "N", "controlNumber": "0000A2MLOG", "price": 98350, "size": 100, "saleCondition": "@   ", "cosolidatedVolume": 1557084}
key:9362637
value :{"SoupPartition": 0, "SoupSequence": 9362637, "trackingID": 50845588007117, "msgType": "T", "marketCenter": "L", "symbol": "LUV     ", "securityClass": "N", "controlNumber": "0000A2MLOH", "price": 297413, "size": 4, "saleCondition": "@  o", "cosolidatedVolume": 16791899}
key:9362638
value :{"SoupPartition": 0, "SoupSequence": 9362638, "trackingID": 50845596356365, "msgType": "T", "marketCenter": "L", "symbol": "M       ", "securityClass": "N", "controlNumber": "0000A2MLOI", "price": 54000, "size": 10, "saleCondition": "@  o", "cosolidatedVolume": 39273663}
key:9362639
value :{"SoupPartition": 0, "SoupSequence": 9362639, "trackingID": 50845600594567, "msgType": "T", "marketCenter": "L", "symbol": "TTM     ", "securityClass": "N", "controlNumber": "0000A2MLOJ", "price": 56000, "size": 400, "saleCondition": "@   ", "cosolidatedVolume": 1293244}

Get example message from stream

Print message to the console for given message name.

ncds_client = NCDSClient(security_cfg, kafka_cfg)
topic = "NLSCTA"
print(ncds_client.get_sample_messages(topic, "SeqDirectoryMessage", all_messages=False))

Example output:

{'SoupPartition': 0, 'SoupSequence': 500, 'trackingID': 11578737109589, 'msgType': 'R', 'symbol': 'AMN', 'marketClass': 'N', 'fsi': '', 'roundLotSize': 100, 'roundLotOnly': 'N', 'issueClass': 'C', 'issueSubtype': 'Z', 'authenticity': 'P', 'shortThreshold': 'N', 'ipo': '', 'luldTier': '2', 'etf': 'N', 'etfFactor': 0, 'inverseETF': 'N', 'compositeId': 'BBG000BCT197', 'schema_name': 'SeqDirectoryMessage'}

Get continuous stream

ncds_client = NCDSClient(security_cfg, kafka_cfg)
topic = "NLSCTA"
consumer = ncds_client.ncds_kafka_consumer(topic)
while True:
    messages = consumer.consume(num_messages=1, timeout=5)
    if len(messages) == 0:
        print(f"No Records Found for the Topic: {topic}")
              
    for message in messages:
        print(f"value :" + str(message.value()))

Example output: note that only the first ten messages of the stream are shown in this example

value :{"SoupPartition": 0, "SoupSequence": 1, "trackingID": 7233292771056, "msgType": "S", "event": "O", "schema_name": "SeqSystemEventMessage"}
value :{"SoupPartition": 0, "SoupSequence": 2, "trackingID": 11578719526113, "msgType": "R", "symbol": "A", "marketClass": "N", "fsi": "", "roundLotSize": 100, "roundLotOnly": "N", "issueClass": "C", "issueSubtype": "Z", "authenticity": "P", "shortThreshold": "N", "ipo": "", "luldTier": "1", "etf": "N", "etfFactor": 0, "inverseETF": "N", "compositeId": "BBG000C2V3D6", "schema_name": "SeqDirectoryMessage"}
value :{"SoupPartition": 0, "SoupSequence": 3, "trackingID": 11578719526113, "msgType": "G", "symbol": "A", "securityClass": "N", "adjClosingPrice": 1500300, "schema_name": "SeqAdjClosingPrice"}
value :{"SoupPartition": 0, "SoupSequence": 4, "trackingID": 11578719831656, "msgType": "R", "symbol": "AA", "marketClass": "N", "fsi": "", "roundLotSize": 100, "roundLotOnly": "N", "issueClass": "C", "issueSubtype": "Z", "authenticity": "P", "shortThreshold": "N", "ipo": "", "luldTier": "1", "etf": "N", "etfFactor": 1, "inverseETF": "N", "compositeId": "BBG00B3T3HD3", "schema_name": "SeqDirectoryMessage"}
value :{"SoupPartition": 0, "SoupSequence": 5, "trackingID": 11578719831656, "msgType": "G", "symbol": "AA", "securityClass": "N", "adjClosingPrice": 374400, "schema_name": "SeqAdjClosingPrice"}
value :{"SoupPartition": 0, "SoupSequence": 6, "trackingID": 11578719879872, "msgType": "R", "symbol": "AAA", "marketClass": "P", "fsi": "", "roundLotSize": 100, "roundLotOnly": "N", "issueClass": "Q", "issueSubtype": "I", "authenticity": "P", "shortThreshold": "N", "ipo": "", "luldTier": "2", "etf": "Y", "etfFactor": 1, "inverseETF": "N", "compositeId": "BBG00X5FSP48", "schema_name": "SeqDirectoryMessage"}
value :{"SoupPartition": 0, "SoupSequence": 7, "trackingID": 11578719879872, "msgType": "G", "symbol": "AAA", "securityClass": "P", "adjClosingPrice": 250050, "schema_name": "SeqAdjClosingPrice"}
value :{"SoupPartition": 0, "SoupSequence": 8, "trackingID": 11578719916519, "msgType": "R", "symbol": "AAAU", "marketClass": "P", "fsi": "", "roundLotSize": 100, "roundLotOnly": "N", "issueClass": "Q", "issueSubtype": "I", "authenticity": "P", "shortThreshold": "N", "ipo": "", "luldTier": "1", "etf": "Y", "etfFactor": 1, "inverseETF": "N", "compositeId": "BBG00LPXX872", "schema_name": "SeqDirectoryMessage"}
value :{"SoupPartition": 0, "SoupSequence": 9, "trackingID": 11578719916519, "msgType": "G", "symbol": "AAAU", "securityClass": "P", "adjClosingPrice": 179850, "schema_name": "SeqAdjClosingPrice"}
value :{"SoupPartition": 0, "SoupSequence": 10, "trackingID": 11578719950254, "msgType": "R", "symbol": "AAC", "marketClass": "N", "fsi": "", "roundLotSize": 100, "roundLotOnly": "N", "issueClass": "O", "issueSubtype": "Z", "authenticity": "P", "shortThreshold": "N", "ipo": "", "luldTier": "2", "etf": "N", "etfFactor": 1, "inverseETF": "N", "compositeId": "BBG00YZC2Z91", "schema_name": "SeqDirectoryMessage"}

Example syntax to run the client based on this SDK

1. To list streams available on Nasdaq Cloud Data Service

python3.9 NCDSSession.py -opt TOPICS

2. To display the schema for the given topic

python3.9 NCDSSession.py -opt SCHEMA -topic NLSCTA

3. To dump top n records from the given topic

python3.9 NCDSSession.py -opt TOP -n 10 -topic NLSCTA

4. To use client based specific authorization file instead of using from the resources of client code base

python3.9 NCDSSession.py -opt TOP -n 10 -topic NLSCTA -authprops client-authentication-config.json

5. To use the specific kafka properties instead of using the kafka properties from the resources of the client base code

python3.9 NCDSSession.py -opt TOP -n 10 -topic NLSCTA -kafkaprops kafka-config.json

6. To use the specific client based authorization file and specific kafka properties file

python3.9 NCDSSession.py -opt TOP -n 10 -topic NLSCTA -authprops client-authentication-config.json -kafkaprops kafka-config.json

7. To display a specific message type

python3.9 NCDSSession.py -opt GETMSG -topic NLSCTA -msgname SeqDirectoryMessage

8. To dump top n records from the given topic from given timestamp in milliseconds since the UNIX epoch

python3.9 NCDSSession.py -opt TOP -n 10 -topic NLSCTA -timestamp 1590084445610

9. To retrieve a continuous stream of messages from the given topic

python3.9 NCDSSession.py -opt CONTSTREAM -topic NLSCTA

10. To retrieve a stream of messages from the given topic, filtered by symbols or message names

python3.9 NCDSSession.py -opt FILTERSTREAM -topic NLSCTA -symbols SPCE

Documentation

An addition to the example application, there is extra documentation at the package and class level, which are located in project https://github.com/Nasdaq/NasdaqCloudDataService-SDK-Python​/tree/master/ncdssdk/docs

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

Code and documentation released under the Apache License, Version 2.0