Production-Ready
SDKs
Capabilities
Financial data SDKs that fit your needs
High Performance
Optimized market data clients with efficient serialization, connection reuse, and minimal overhead for demanding research workloads.
Authentication & Security
Built-in API key management, secure request handling, and enterprise-ready authentication workflows for your financial data API.
Type Safety
Strongly typed SDKs with autocomplete, request validation, and generated models, ideal for TypeScript financial API development.
Quick Integration
Install the financial data SDK, authenticate, and make your first request in minutes with concise APIs and practical examples.
Developer Experience
Clear documentation, comprehensive examples, and predictable interfaces designed for productivity.
Consistent APIs
Unified request patterns and data structures across the Python finance library, TypeScript clients, endpoints, and datasets.
An All-in-one Financial Data API For Building Alpha
Native Python libraries, JavaScript and TypeScript SDKs, C bindings, and AI agents plus a REST API for everything else.
Fetch, Frame,
Graph
Pull historical market data through the Python financial data API, transform it into a dataframe, and generate visualizations with a few lines of code. Spend less time wiring tools together and more time analyzing markets.
from axion import Axion, utils, visualize
client = Axion(api_key="your_api_key")
df = utils.df(
client.stocks.prices(
"NVDA",
from_date=utils.d(utils.yearago),
frame="daily",
)
)
visualize.candles(df)
from axion import Axion, utils, visualize, ta
client = Axion(api_key="your_api_key")
df = utils.df(
client.forex.prices(
"EURUSD",
from_date=utils.d(utils.yearago),
frame="daily",
)
)
df["ema_21"] = ta.ema(df, period=21)
df["ema_50"] = ta.ema(df, period=50)
df["rsi"] = ta.rsi(df, period=14)
visualize.graph(
df,
x="date",
lines=["close", "ema_21", "ema_50"],
title="EUR/USD - Spot Direction",
)
from axion import Axion
client = Axion(api_key="your_api_key")
ticker = "NVDA"
profile = client.profiles.profile(ticker)
info = client.profiles.info(ticker)
summary = client.profiles.summary(ticker)
calendar = client.profiles.calendar(ticker)
sector = profile["sector"]
industry = profile["industry"]
price = summary["regularMarketPrice"]
high_52w = summary["fiftyTwoWeekHigh"]
earnings = calendar["earnings"]["earningsDate"]
from axion import Axion, utils, models, visualize
client = Axion(api_key="your_api_key")
cpi_id = client.econ.search("CPI all items")[0]["id"]
cpi = utils.df(client.econ.dataset(cpi_id))
# Convert price levels to a monthly inflation rate
cpi = utils.relativity(cpi, cols=["value"])
# Project inflation six months forward
forecast = models.linearRegression(
cpi,
x="date",
target="relative_value",
n_preds=6,
scale="M"
)
visualize.line(cpi, x="date", y="relative_value")from axion import Axion, utils
client = Axion(api_key="your_api_key")
watchlist = ["AAPL", "MSFT", "GOOGL", "TSLA", "META"]
def fetch_filings(row):
t = row["ticker"]
return (t, {
"ticker": t,
"last_10k": client.filings.recent(t, form="10-K", limit=1)[0]["date"],
"last_10q": client.filings.recent(t, form="10-Q", limit=1)[0]["date"],
"recent_8k": client.filings.recent(t, form="8-K", limit=1)[0]["title"],
})
filings_map = {}
utils.work(utils.df([{"ticker": t} for t in watchlist]), fetch_filings, filings_map)
df_filings = utils.df(list(filings_map.values()))
Enterprise-grade financial data SDK clients, ready to deploy
Secure, Enterprise Vault
Connect using scoped API keys that are safe for both client and server contexts.
Deep historical search and knowledge
Connect your external applications and integrate financial intelligence across your entire stack with one financial data SDK.
Slides, spreadsheets, and documents
Produce polished financial analytics in slides, spreadsheets, and documents.
| A | B | C | |
|---|---|---|---|
| Revenue | $1.2M | $1.5M | $1.8M |
| COGS | $520K | $610K | $720K |
| OpEx | $180K | $210K | $240K |
| Gross Profit | $680K | $890K | $1.08M |
| Marketing | $90K | $110K | $135K |
| R&D | $120K | $145K | $170K |
| Headcount | 42 | 48 | 56 |
| EBITDA | $470K | $635K | $775K |
| Margin | 39.2% | 42.3% | 43.1% |
And much more
Everything you need in one package - from quant research to algorithmic trading.
Daily and hourly market data
Query daily and hourly equities, crypto, forex, and alternative data with responses in milliseconds
Decades of historical depth
Retrieve full daily and hourly price history back to 1987, ready for backtesting and long-horizon research
Data-driven analytics
Build quantitative trading strategies and models using structured financial and historical datasets
Multi-source aggregation
Combine multiple data providers into a single unified API interface
Developer-first SDKs
Clean, typed SDKs for Python, TypeScript, and more with consistent APIs
Data visualization support
Power dashboards and charts using structured market and alternative datasets
Market replay tools
Reconstruct historical market movements for simulation and backtesting
Alerting & notifications
Trigger alerts for price movements, thresholds, and events across daily and hourly data
Structured data access
Retrieve normalized financial data across all supported asset classes
Alternative data insights
Analyze non-traditional datasets to uncover market signals and trends
Global market coverage
Access international exchanges and multi-region financial data seamlessly
Historical data access
Query deep historical datasets for research, modeling, and backtesting
Strategy development workflow
Build, test, and iterate on algorithmic trading strategies using clean API primitives
Flexible API configuration
Customize endpoints, filters, and data granularity per use case
Export & integration ready
Easily pipe data into your existing trading systems and analytics tools
Cloud-native infrastructure
Reliable, scalable APIs designed for production financial systems
Consistent developer experience
Unified behavior across SDKs and REST interfaces
Pricing That Scales With You
Flexible plans for developers, startups, and enterprises. Access comprehensive market data, fundamental data, and alternative data through a single financial data API.
Billed annually
Billed annually
Start Building with the AxionQuant Financial Data API
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