High performance asyncio REST client for polygon.io
Project description
Upoly
An Asyncio based, high performance, REST client libary for interacting with the polygon REST api.
Abstract
The two main python rest-client libs for polygon.io(alpaca-trade-api, polygonio) do not provide an effective means to gather more than 50,000 trade bars at once. This library aims to address that by providing an easy and performant solution to getting results from timespans where the resultset exceeds 50,000 trade bars.
Installation
This library makes use of some high performance packages written in C
/Rust
(uvloop, orjson) so it may require python-dev
on Ubuntu or similar on
other OS's. It is compatible with Python 3.8.x and aims to be compatible with
all future CPython versions moving forward.
pip/poetry w/ venv
#!/bin/env bash
python3.8 -m venv .venv && source .venv/bin/activate
poetry add upoly
# or
pip install upoly
Usage
Reccomend to create a copy of ./env.sample
as ./env
. Make sure .env
is listed
in .gitignore
.
# ./.env
POLYGON_KEY_ID=REPACEWITHPOLYGONORALPACAKEYHERE
Many alternatives to .env
exist. One such alternative is exporting
like so:
#!/bin/env bash
export POLYGON_KEY_ID=REPACEWITHPOLYGONORALPACAKEYHERE
# ./yourscript.py
import pytz
from dotenv import load_dotenv
import pandas as pd
# load Polygon key from .env file
load_dotenv()
# alternatively run from cli with:
# POLYGON_KEY_ID=@#*$sdfasd python yourscript.py
# Not recommend but can be set with os.environ["POLYGON_KEY_ID"] as well
from upoly import async_polygon_aggs
NY = pytz.timezone("America/New_York")
# Must be a NY, pandas Timestamp
start = pd.Timestamp("2015-01-01", tz=NY)
end = pd.Timestamp("2020-01-01", tz=NY)
df = async_polygon_aggs("AAPL", "minute", 1, start, end)
TODO
- unit tests
- regression tests
- integration tests
-
/trade
endpoint functionality for tick data
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