otcharts

Market data from OTC broker books — Pocket Option, Quotex, IQ Option, BinoDex — and the real institutional FX market, as JSON. One dependency-free Python package.

pip install otcharts

from otcharts import Client

otc = Client()                                      # reads OTCHARTS_API_KEY
bars = otc.candles("iq", "EURUSD-OTC", tf=60, limit=300)
print(bars[-1].close)

for tick in otc.stream("quotex", "EURUSD_otc"):     # live, reconnects on drop
    print(tick.time, tick.price)

Read this before you install

This reads prices. It does not place trades. No orders, no positions, no account balance. If you came here looking for a way to automate trading on one of these platforms, this is the wrong package and you should stop here rather than pay for it.

You never give anyone your broker password. Unlike the community wrappers, this does not log in as you, drive a browser, or hold your broker session. It talks to an HTTP API with a key that is yours, and the connection to the venue is held on the server side.

Not affiliated with Pocket Option, Quotex, IQ Option, or BinoDex. Their names appear here to say which price feed the data comes from, nothing more.

Why this exists

None of these platforms publishes an official API. What exists is a handful of community wrappers that log in with your credentials, drive Selenium past a CAPTCHA, and break quietly when the platform changes its socket format. They are often good work, and if you need to place orders they are the only route there is.

But if all you wanted was the prices, that is a lot of moving parts — and a lot of risk to an account — to read a number. This package reads the number.

Install

pip install otcharts              # no dependencies
pip install 'otcharts[pandas]'    # adds .dataframe()

Requires Python 3.8+. The package imports nothing outside the standard library, so it cannot conflict with whatever you already have pinned.

Getting a key

1. Buy a data plan at otcharts.com/pricing
2. Create a key on your account page — it is shown once, and only a hash is stored, so nobody can recover it afterwards, including us
3. export OTCHARTS_API_KEY=otc_live_...

The books, and their symbol formats

Ids are not portable between books. This catches everyone once:

otc.venues()            # every book, and whether your plan opens it
otc.symbols("otc")      # every instrument in one, with the exact id to send

Do not keep your own list. A book drops instruments it stops quoting, and a hand-written list goes stale silently — the first thing you notice is an empty response for a pair delisted weeks ago. symbols() is the live catalogue; the cross-reference is the same thing for a human, all five books side by side.

Errors that tell you what to do

The API distinguishes its refusals, and so does this package. In particular 429 means two different things, and they have different fixes:

from otcharts import QuotaExceeded, TooManyStreams, HouseBusy, PlanError

try:
    ...
except QuotaExceeded:      # 429 on a request — daily request quota spent
    ...
except TooManyStreams:     # 429 on a stream — YOUR account's concurrent limit
    ...                    #   close one of your streams
except HouseBusy as e:     # 503 — the service as a whole is at its ceiling.
    time.sleep(e.retry_after)   # not your fault, not fixed by upgrading
except PlanError:          # 402 — key is fine, plan does not open this book
    ...

AuthError (401) is worth one note: a password reset revokes every API key on the account, so a key that worked yesterday may simply have been revoked.

Knowing where you stand

u = otc.usage()
print(u.used, "of", u.quota, "-", u.remaining, "left")
print("resets at", u.resets)                  # unix seconds, next midnight UTC
print(u.instruments_per_stream, "per stream") # None on Desk: the whole book

This call is free — it does not count against the quota it reports, so a loop may check it as often as it likes. Every figure is the account's, shared across all of its keys: a second key does not buy a second allowance.

if u.remaining < 500:
    time.sleep(u.resets - time.time())        # rather than find out by refusal

Streaming

One connection, and it can carry many instruments:

for tick in otc.stream("otc", ["EURUSD_otc", "GBPUSD_otc", "XAUUSD_otc"]):
    print(tick.symbol, tick.price)        # every tick names its own instrument

This is the difference between following a watchlist and exhausting a quota polling it. Fifty pairs asked for once a minute is 72,000 requests a day; fifty pairs on one stream is one, and holding it costs nothing further.

How many one stream may carry is a property of your plan — usage().instruments_per_stream, or None for no limit. Ask for more and the refusal names the number. Several instruments on one connection is a Pocket Option (otc) feature today; the other books take one symbol per stream, because there a second instrument really is a second connection.

A single symbol still works exactly as before:

for tick in otc.stream("quotex", "EURUSD_otc"):
    ...

The book subscribes you only to what is quoting right now, so a weekend list of forty may come back as twenty-seven. Nothing has failed; an instrument that is not trading is dropped rather than held open.

Reconnection is on by default and is deliberately selective. Dropped sockets and HouseBusy are retried — HouseBusy after the delay the server asks for. A revoked key or a plan that does not open the book is not retried, because it will fail identically forever and a client hammering a 402 in a loop is a client that gets limited. Pass reconnect=False to handle it yourself.

pandas

df = otc.dataframe("quotex", "EURUSD_otc", tf=60, limit=1000)

Optional on purpose — most callers want JSON, and a 60MB install to read five prices is rude.

One thing about this data

An instrument named after gold or EUR/USD on an OTC book is the venue's own price, not the underlying market, and it can drift from it. That is how these books work. If you are modelling this data, treat each series as its own thing rather than as a proxy for the market it is named after — and note that venue="forex" carries the real institutional feed, so the two can be compared directly.

Development

git clone https://github.com/otcharts/otcharts-python
cd otcharts-python
PYTHONPATH=src python3 -m unittest discover -s tests -v

The tests run against a real HTTP server on loopback rather than a mocked transport, so the headers, the status handling and the SSE parsing are genuinely exercised. No test touches the network.

Links

• API reference — one page, the whole contract
• Pocket Option API · Quotex API · IQ Option API · BinoDex API

Licence

MIT. Nothing here is financial advice and no result is promised.