iturri
Python client for the Iturri verified market-data API —
historical market data for trading bots, backtests, and AI agents where
every bar carries a quality flag (verified · raw · reconciled · interpolated · disputed · outage) and every candle is traceable to a
checksummed primary source.
- 380M+ quality-flagged OHLCV bars: 102 crypto symbols (1m/5m/15m/1h/1d since 2015) + 106 US stocks & ETFs incl. 20 delisted (consolidated-tape EOD since 2016, as-traded and split-adjusted bases)
- Funding rates, open interest, taker order flow, curated events, market context (Fear & Greed, VIX, DXY…)
- Leakage-safe feature matrices, multi-timeframe aligned bundles, BSQ token sequences, training packs
- Agent-native: 11 MCP tools and x402 micropayments (USDC on Base) — no account, no API key
Zero hard dependencies. With pandas installed you get DataFrames; without it, columnar dicts.
Install
pip install iturri # or: pip install "iturri[pandas]"
Quickstart
import iturri
iturri.catalog() # free discovery — symbols, ranges, pricing
iturri.token = "…" # membership token from iturri.ai/subscribe
# (or: export ITURRI_TOKEN)
df = iturri.bars("BTC", "1h", start="2024-01-01", end="2024-02-01")
df = df[df.quality == "verified"] # the whole point
feats = iturri.features("SPY", "1d_split", start="2026-06-01")
iturri.bundle("crypto") # signed training-pack URLs
Without a token, priced endpoints return HTTP 402 with an x402 quote — payment-capable agents settle per call ($0.001 per 1,000 candles) with no human in the loop.
Full surface
catalog · bars · features · funding · open_interest · orderflow ·
context · events · regime · validate · bundle — mirroring the
11 MCP tools at https://iturri.ai/mcp.
validate(symbol, tf, start=…, end=…) returns a data-quality report
(coverage, gaps, flag distribution) so you can audit a range before
backtesting on it.
For AI agents (MCP)
{ "mcpServers": { "iturri": { "type": "http", "url": "https://iturri.ai/mcp" } } }
describe_catalog is free forever. See the
MCP tutorial.
Links
Docs: https://iturri.ai/#docs · OpenAPI: https://iturri.ai/openapi.json ·
llms.txt: https://iturri.ai/llms.txt · JS SDK + CLI: npm i iturri ·
Sourcing & verification policy: https://iturri.ai/sourcing
Iturri sells data and tooling only. Nothing in any dataset, feature, label, or tool is a trading signal, a prediction, or financial advice.
Metadata
Release files for iturri 0.2.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| iturri-0.2.4.tar.gz | 5.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| iturri-0.2.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.6 kB
Release files / iturri-0.2.4.tar.gz
| Download URL | iturri-0.2.4.tar.gz |
|---|---|
| Size | 5.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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Release files / iturri-0.2.4-py3-none-any.whl
| Download URL | iturri-0.2.4-py3-none-any.whl |
|---|---|
| Size | 5.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.11.2 {"installer":{"name":"uv","version":"0.11.2","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
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