DEV Community: DollarPixel

Why I Ditched Polygon.io and What I Found Instead

DollarPixel — Thu, 22 May 2025 08:04:15 +0000

Let’s be real for a second. I used to be a big fan of Polygon.io. For a while, it felt like the right tool—decent docs, fair pricing, enough endpoints to get moving. But as my work evolved and my expectations (read: patience) dropped, I started noticing some cracks in the façade.

Some missing candles here, latency weirdness there, and then—the killer—a couple of wildly inaccurate ticks that threw off a backtest enough to make me question everything. If you've ever spent hours tuning a signal only to realize the data was the issue... yeah. You get it.

So, I did what any slightly masochistic quant would do: I went shopping for pain.
Here’s what I found.

Alpha Vantage

I wanted to like Alpha Vantage. It’s one of those platforms that looks clean, feels nice at first glance, and has an API that doesn’t make you scream into a pillow.

But oh boy—the data.

The tick data (or what passes for it) just wasn’t what I needed. Latency on responses was all over the place, and even basic intraday price series sometimes had suspicious gaps. I know some people say “it’s good enough for retail,” but let’s be honest—"good enough" doesn’t cut it when you're pushing signal edges measured in basis points.

Also, their rate limits felt a bit too tight unless you upgrade, and even then, I wasn’t blown away. End of story: I wanted clean, granular, fast data. Alpha Vantage gave me decent-ish data wrapped in a SaaS smile, but it just wasn’t enough.

Alpaca

I’ve got a soft spot for Alpaca. I really do. They make it stupidly easy to open an account, paper trade, and even integrate with some neat tools.

But as a data provider? Not my jam.

Alpaca’s market data API feels like a bonus feature rather than a primary offering—and it shows. Historical data access is okay at best, but granularity is lacking, and the depth isn’t there for serious research. The real dealbreaker, though, was quality: a few inconsistent ticks, and some missing volume data on lower liquidity names.

To be fair, if you're trading through them and want basic context—sure, it's fine. But I’m not using a broker’s side hustle for signal development. That just feels like asking your Uber driver for career advice. Sometimes you get a gem. Most times, you don't.

Alltick.co

Now this one surprised me.

I stumbled across Alltick.co almost by accident. The site didn’t scream “next-gen quant infra” or anything flashy. But something about the positioning made me curious. So I tried it. And… I kept using it.

First of all, their tick-level data is clean. Like, scarily clean. I threw my usual tests at it—backfill consistency, timestamp precision, cross-checking with exchange prints—and it passed better than anything else I’d tried.

Latency? Low.

Missing data? Practically none that I could find.

Historical depth? Solid.

API experience? Surprisingly smooth.

The pricing was reasonable, and I didn’t feel like I had to play some weird freemium upgrade game to get actual value. It just worked—and in this world, that's rarer than it should be.

Final Thoughts

Switching data providers isn’t fun. It’s like switching therapists: time-consuming, awkward, and you always wonder if you're just being too picky.

But trust me—your models are only as good as the stuff you feed them. Garbage in, garbage out, etc. We all know it, but it’s easy to forget when the APIs are "good enough."

I’m still kicking the tires on Alltick.co, but so far, they’ve earned their spot. If you’re frustrated with your current feed—or worse, you’re ignoring your data quality issues—maybe it’s time for your own little search party.

Let me know if you've found something better. Or if you've been burned by any of these too. Misery loves company, right?

A Better Yahoo Finance API Alternative for Developers in 2025

DollarPixel — Thu, 15 May 2025 07:44:23 +0000

For years, developers have relied on Yahoo Finance for quick access to market data. It was free, easy to use, and worked well for prototypes. I’ve used it myself in side projects, backtesting tools, and even dashboards.

But let’s be honest — Yahoo Finance API isn’t what it used to be. It’s unofficial, unstable, and limited in scope. At some point, you realize it’s time to move on.

That’s when I started looking for a better option. Something reliable. Something real-time. Something that works across markets — not just U.S. stocks.

I eventually landed on AllTick API, and I think it’s worth sharing why it has become my go-to alternative.

Why Yahoo Finance Isn’t Enough Anymore

First, the obvious: Yahoo’s public API has long been shut down. What you’re using today — if you’re still using it — is a workaround. It can break anytime. And even when it works, you’re limited to delayed quotes and U.S. stock data.

There’s no real support. No guarantees. And certainly not something I’d build a production system on.

What Developers Actually Need

If you're building any serious trading tool, portfolio tracker, or signal engine, here’s what you probably care about:

Real-time market data (not 15 minutes delayed)
Support for multiple markets: not just U.S. stocks, but also China A-shares, Hong Kong stocks, forex, crypto, and maybe even commodities
Reliable and fast APIs — ideally both HTTP and WebSocket
Clear docs and easy integration
Commercial usage without worrying about licensing
Yahoo can’t do that. That’s where AllTick comes in.

Meet AllTick API

AllTick is a real-time market data provider designed for developers. It gives you fast, stable access to financial markets across the globe.

Here’s what it covers:
China A-shares

Hong Kong stocks
U.S. stocks
Forex
Cryptocurrencies
Commodity futures

You can query data using HTTP RESTful API, or set up WebSocket streams for real-time updates. It’s straightforward to integrate, and the latency is low enough for serious use cases — like algo trading or high-frequency analytics.

One thing to note: AllTick focuses on market quotes. You won’t find financial statements or fundamentals here — it’s purely market data. That’s exactly what I wanted, so no complaints.

AllTick vs Yahoo Finance API — A Quick Look

Example Use Cases

To give you an idea, here’s how I’ve been using AllTick:

Real-time stock price alerts via WebSocket
Forex market dashboard with streaming quotes
Backtesting strategies on U.S. and Hong Kong stocks using tick data

Setting up the API was quick. The docs are clear. You get an API key, make a few HTTP calls, and you’re in.

Here’s a super basic example in Python:

import time

import requests # pip3 install requests
import json

# Extra headers
test_headers = {
    'Content-Type' : 'application/json'
}

'''
Encode the following JSON with URL encoding and copy it to the "query" field in the query string of an HTTP request.
{"trace" : "python_http_test1","data" : {"code" : "700.HK","kline_type" : 1,"kline_timestamp_end" : 0,"query_kline_num" : 2,"adjust_type": 0}}
{"trace" : "python_http_test2","data" : {"symbol_list": [{"code": "700.HK"},{"code": "UNH.US"}]}}
{"trace" : "python_http_test3","data" : {"symbol_list": [{"code": "700.HK"},{"code": "UNH.US"}]}}
'''
test_url1 = 'http://quote.aatest.online/quote-stock-b-api/kline?token=e945d7d9-9e6e-4721-922a-7251a9d311d0-1678159756806&query=%7B%22trace%22%20%3A%20%22python_http_test1%22%2C%22data%22%20%3A%20%7B%22code%22%20%3A%20%22700.HK%22%2C%22kline_type%22%20%3A%201%2C%22kline_timestamp_end%22%20%3A%200%2C%22query_kline_num%22%20%3A%202%2C%22adjust_type%22%3A%200%7D%7D'
test_url2 = 'http://quote.aatest.online/quote-stock-b-api/depth-tick?token=e945d7d9-9e6e-4721-922a-7251a9d311d0-1678159756806&query=%7B%22trace%22%20%3A%20%22python_http_test2%22%2C%22data%22%20%3A%20%7B%22symbol_list%22%3A%20%5B%7B%22code%22%3A%20%22700.HK%22%7D%2C%7B%22code%22%3A%20%22UNH.US%22%7D%5D%7D%7D'
test_url3 = 'http://quote.aatest.online/quote-stock-b-api/trade-tick?token=e945d7d9-9e6e-4721-922a-7251a9d311d0-1678159756806&query=%7B%22trace%22%20%3A%20%22python_http_test3%22%2C%22data%22%20%3A%20%7B%22symbol_list%22%3A%20%5B%7B%22code%22%3A%20%22700.HK%22%7D%2C%7B%22code%22%3A%20%22UNH.US%22%7D%5D%7D%7D'

resp1 = requests.get(url=test_url1, headers=test_headers)
time.sleep(1)
resp2 = requests.get(url=test_url2, headers=test_headers)
time.sleep(1)
resp3 = requests.get(url=test_url3, headers=test_headers)

# Decoded text returned by the request
text1 = resp1.text
print(text1)

text2 = resp2.text
print(text2)

text3 = resp3.text
print(text3)

And if you’re into WebSockets:

import json
import websocket    # pip install websocket-client

class Feed(object):

    def __init__(self):
        self.url = 'wss://quote.aatest.online/quote-stock-b-ws-api?token=e945d7d9-9e6e-4721-922a-7251a9d311d0-1678159756806'
        self.ws = None

    def on_open(self, ws):
        """
        Callback object which is called at opening websocket.
        1 argument:
        @ ws: the WebSocketApp object
        """
        print('A new WebSocketApp is opened!')

        sub_param = {
            "cmd_id": 22002, 
            "seq_id": 123,
            "trace":"3baaa938-f92c-4a74-a228-fd49d5e2f8bc-1678419657806",
            "data":{
                "symbol_list":[
                    {
                        "code": "700.HK",
                        "depth_level": 5,
                    },
                    {
                        "code": "UNH.US",
                        "depth_level": 5,
                    }
                ]
            }
        }

        sub_str = json.dumps(sub_param)
        ws.send(sub_str)
        print("depth quote are subscribed!")

    def on_data(self, ws, string, type, continue_flag):
        """
        4 argument.
        The 1st argument is this class object.
        The 2nd argument is utf-8 string which we get from the server.
        The 3rd argument is data type. ABNF.OPCODE_TEXT or ABNF.OPCODE_BINARY will be came.
        The 4th argument is continue flag. If 0, the data continue
        """

    def on_message(self, ws, message):
        """
        Callback object which is called when received data.
        2 arguments:
        @ ws: the WebSocketApp object
        @ message: utf-8 data received from the server
        """

        result = eval(message)
        print(result)

    def on_error(self, ws, error):
        """
        Callback object which is called when got an error.
        2 arguments:
        @ ws: the WebSocketApp object
        @ error: exception object
        """
        print(error)

    def on_close(self, ws, close_status_code, close_msg):
        """
        Callback object which is called when the connection is closed.
        2 arguments:
        @ ws: the WebSocketApp object
        @ close_status_code
        @ close_msg
        """
        print('The connection is closed!')

    def start(self):
        self.ws = websocket.WebSocketApp(
            self.url,
            on_open=self.on_open,
            on_message=self.on_message,
            on_data=self.on_data,
            on_error=self.on_error,
            on_close=self.on_close,
        )
        self.ws.run_forever()


if __name__ == "__main__":
    feed = Feed()
    feed.start()

Getting Started

You can sign up and get an API key right away. There’s a free trial tier if you just want to try it out. The docs cover everything — HTTP endpoints, WebSocket structure, market codes, etc.

They also support Python and JavaScript pretty well, so you won’t be fighting the API like some of the older data providers.

Final Thoughts

If you’ve outgrown Yahoo Finance — or just want something faster, more stable, and developer-friendly — give AllTick a try.

It won’t give you financial statements or dividend history, but for real-time quotes across multiple markets, it’s a solid upgrade.

And most importantly, it feels like an API built for developers, not just something bolted onto a website.