Welcome to the official Python client library for the Polygon REST and WebSocket API. To get started, please see the Getting Started section in our documentation, view the examples directory for code snippets, or the blog post with video tutorials to learn more.
Before installing the Polygon Python client, ensure your environment has Python 3.8 or higher.
Please use pip to install or update to the latest stable version.
pip install -U polygon-api-client
To get started, please see the Getting Started section in our docs, view the examples directory for code snippets, or view the blog post with videos to learn more.
The free tier of our API comes with usage limitations, potentially leading to rate limit errors if these are exceeded. For uninterrupted access and to support larger data requirements, we recommend reviewing our subscription plans, which are tailored for a wide range of needs from development to high-demand applications. Refer to our pricing page for detailed information on limits and features to ensure a seamless experience, especially for real-time data processing.
Import the RESTClient.
from polygon import RESTClientCreate a new client with your API key
client = RESTClient(api_key="<API_KEY>")Request data using client methods.
ticker = "AAPL"
# List Aggregates (Bars)
aggs = []
for a in client.list_aggs(ticker=ticker, multiplier=1, timespan="minute", from_="2023-01-01", to="2023-06-13", limit=50000):
aggs.append(a)
print(aggs)
# Get Last Trade
trade = client.get_last_trade(ticker=ticker)
print(trade)
# List Trades
trades = client.list_trades(ticker=ticker, timestamp="2022-01-04")
for trade in trades:
print(trade)
# Get Last Quote
quote = client.get_last_quote(ticker=ticker)
print(quote)
# List Quotes
quotes = client.list_quotes(ticker=ticker, timestamp="2022-01-04")
for quote in quotes:
print(quote)By default, the client paginates results for endpoints like list_trades and list_quotes behind the scenes for you. Understanding how pagination interacts with the limit parameter is key.
Pagination is enabled by default (pagination=True):
limitcontrols the page size, not the total number of results.- The client automatically fetches all pages, yielding results until none remain.
Here's an example:
client = RESTClient(api_key="<API_KEY>")
trades = [t for t in client.list_trades(ticker="TSLA", limit=100)]This fetches all TSLA trades, 100 per page.
To return a fixed number of results and stop, disable pagination:
client = RESTClient(api_key="<API_KEY>", pagination=False)
trades = [t for t in client.list_trades(ticker="TSLA", limit=100)]This returns at most 100 total trades, no additional pages.
If you're fetching large datasets, always use the maximum supported limit for the API endpoint. This reduces the number of API calls and improves overall performance.
Many of the APIs in this client library support the use of additional filter parameters to refine your queries. Please refer to the specific API documentation for details on which filter parameters are supported for each endpoint. These filters can be applied using the following operators:
.gt: greater than.gte: greater than or equal to.lt: less than.lte: less than or equal to
Here's a sample code snippet that demonstrates how to use these filter parameters when requesting an Options Chain using the list_snapshot_options_chain method. In this example, the filter parameters ensure that the returned options chain data will only include options with an expiration date that is greater than or equal to "2024-03-16" and a strike price that falls between 29 and 30 (inclusive).
options_chain = []
for o in client.list_snapshot_options_chain(
"HCP",
params={
"expiration_date.gte": "2024-03-16",
"strike_price.gte": 29,
"strike_price.lte": 30,
},
):
options_chain.append(o)
print(options_chain)
print(len(options_chain))Also, please refer to the API documentation to get a full understanding of how the API works and the supported arguments. All required arguments are annotated with red asterisks " * " and argument examples are set.
Sometimes you may find it useful to see the actual request and response details while working with the API. The RESTClient allows for this through its trace=True option.
You can activate the debug mode as follows:
client = RESTClient(trace=True)When debug mode is enabled, the client will print out useful debugging information for each API request. This includes: the request URL, the headers sent in the request, and the headers received in the response.
For instance, if you made a request for TSLA data for the date 2023-08-01, you would see debug output similar to the following:
Request URL: https://api.polygon.io/v2/aggs/ticker/TSLA/range/1/minute/2023-08-01/2023-08-01?limit=50000
Request Headers: {'Authorization': 'Bearer REDACTED', 'Accept-Encoding': 'gzip', 'User-Agent': 'Polygon.io PythonClient/1.12.4'}
Response Headers: {'Server': 'nginx/1.19.2', 'Date': 'Tue, 05 Sep 2023 23:07:02 GMT', 'Content-Type': 'application/json', 'Transfer-Encoding': 'chunked', 'Connection': 'keep-alive', 'Content-Encoding': 'gzip', 'Vary': 'Accept-Encoding', 'X-Request-Id': '727c82feed3790b44084c3f4cae1d7d4', 'Strict-Transport-Security': 'max-age=15724800; includeSubDomains'}
This can be an invaluable tool for debugging issues or understanding how the client interacts with the API.
Import classes
from polygon import WebSocketClient
from polygon.websocket.models import WebSocketMessage
from typing import ListCreate a new client with your API key and subscription options.
# Note: Multiple subscriptions can be added to the array
# For example, if you want to subscribe to AAPL and META,
# you can do so by adding "T.META" to the subscriptions array. ["T.AAPL", "T.META"]
# If you want to subscribe to all tickers, place an asterisk in place of the symbol. ["T.*"]
ws = WebSocketClient(api_key=<API_KEY>, subscriptions=["T.AAPL"])Create a handler function and run the WebSocket.
def handle_msg(msg: List[WebSocketMessage]):
for m in msg:
print(m)
ws.run(handle_msg=handle_msg)Check out more detailed examples here.
If you found a bug or have an idea for a new feature, please first discuss it with us by submitting a new issue. We will respond to issues within at most 3 weeks. We're also open to volunteers if you want to submit a PR for any open issues but please discuss it with us beforehand. PRs that aren't linked to an existing issue or discussed with us ahead of time will generally be declined. If you have more general feedback or want to discuss using this client with other users, feel free to reach out on our Slack channel.
If you plan to contribute by developing new features then you will need to install certain dependencies.
Poetry is a packaging and dependency manager for Python.
Installation instructions can be found on their website.
Once installed run poetry install to install the required dependencies. This step should be run after incorporating new upstream changes.
Our Makefile has the common operations needed when developing on this repo. Running tests and linting can both be
run through our Makefile. Just run make help to see the list of available commands.
If you're using pyenv to manage active Python versions then you might need to launch a Poetry shell before running
Make commands in order to actually use your chosen Python version. This is because Poetry uses the system Python version
by default.
poetry shell # start shell
poetry install # install deps
make test # run your make commandsThis client will attempt to follow the release cadence of our API.
When endpoints are deprecated and newer versions are added, the client will
maintain two methods in a backwards compatible way
(e.g. list_trades and list_trades_v4(...)).
When deprecated endpoints are removed from the API, we'll rename the versioned
method (e.g. list_trades_v4(...) -> list_trades(...)), remove the old method,
and release a new major version of the client.
The goal is to give users ample time to upgrade to newer versions of our API before we bump the major version of the client, and in general, we'll try to bundle breaking changes like this to avoid frequent major version bumps.
Exceptions to this are:
- Methods under
client.vx. These are expiremental. - Methods that start with
_*. We use these internally. - Type annotations. We may modify these based on our JSON responses.
- We may add model fields.