Liberal Alpha Python SDK for interacting with gRPC-based backend
Project description
Liberal Alpha Python SDK (Historical HTTP APIs)
This SDK provides historical upload, historical download, and real-time subscription APIs (HTTP + WebSocket).
Install
pip install liberal_alpha
# Optional: override default API base (default is https://api.librealpha.com)
export LIBALPHA_API_BASE="https://api.librealpha.com"
# Upload auth (X-API-Key)
export LIBALPHA_API_KEY="YOUR_API_KEY"
# Download auth (used to obtain JWT via /api/users/auth)
export LIBALPHA_PRIVATE_KEY="0xYOUR_PRIVATE_KEY"
Optional upload tuning:
export LIBALPHA_UPLOAD_BATCH_ID="12345" # optional batch id (int)
export LIBALPHA_UPLOAD_CHUNK_SIZE="1048576" # default 1MB
export LIBALPHA_UPLOAD_RESUME="1" # 1=enable resume, 0=disable
Initialize Client
from liberal_alpha.client import LiberalAlphaClient
# api_base defaults to https://api.librealpha.com
# can be overridden by env LIBALPHA_API_BASE or by passing api_base=...
client = LiberalAlphaClient(
api_key="YOUR_API_KEY", # optional if using env LIBALPHA_API_KEY
private_key="0xYOUR_PRIVATE_KEY", # optional if using env LIBALPHA_PRIVATE_KEY
)
Historical Upload API (Python)
def upload_data(record_id: int, df: pandas.DataFrame) -> bool:
pass
DataFrame Format
Your DataFrame must contain these columns:
-record_id (int)
-symbol (str)
-data (dict) — e.g. {"open": 50000.0, "close": 51000.0}
-timestamp (int) — milliseconds since epoch
(seconds are also accepted and will be auto-converted to milliseconds)
Example
import pandas as pd
from liberal_alpha.client import LiberalAlphaClient
client = LiberalAlphaClient(
api_key="YOUR_API_KEY",
# api_base defaults to https://api.librealpha.com
)
sample_data = []
for i in range(1000):
sample_data.append({
"record_id": 4,
"symbol": "BNfBTC",
"data": {"open": 50000.0 + i, "close": 51000.0 + i},
"timestamp": 1733299200000 + i * 1000,
})
df = pd.DataFrame(sample_data)
# Optional batch_id: set via env because public API has only 2 args
# export LIBALPHA_UPLOAD_BATCH_ID=12345
ok = client.upload_data(record_id=4, df=df)
print("Upload ok:", ok)
Notes:
-Upload uses X-API-Key authentication.
-Upload is chunked and supports resume if enabled (default enabled).
Historical Download API (Python)
def download_data(
record_id: int,
symbols: list[str],
dates: list[int],
tz_info: datetime.tzinfo | str = "Asia/Singapore"
) -> pandas.DataFrame:
pass
## Historical File Download API (Python) - protobuf (length-prefixed)
```python
def download_history_data(
record_id: int,
symbol: str,
start: datetime | str | int,
end: datetime | str | int,
private_key: str | None = None,
) -> pandas.DataFrame:
pass
Parameters:
- record_id: the record id to download
- symbol: symbol string, e.g. "ADA", "BTCUSDT"
- start/end: datetime | ISO string | unix timestamp (sec/ms/us)
- private_key: optional, record private key for decrypting encrypted_payload when features are empty
Notes:
- Backend
/api/entries/download-linksenforcesend-start <= 24h(microseconds). The SDK automatically splits long ranges into multiple 24h windows and merges results locally. - Returned timestamps are in microseconds.
- DataEntry uses
repeated double features; each row hasfeaturesas a list of floats. - When data is encrypted (features empty, encrypted_payload present), pass
private_keyto decrypt. Plaintext format: uint32 count + float64[count] (AES-GCM, key = sha256(private_key)).
Example
from liberal_alpha.client import LiberalAlphaClient
import datetime as dt
client = LiberalAlphaClient(
private_key="0xYOUR_PRIVATE_KEY", # or api_key="YOUR_API_KEY"
api_base="https://api.librealpha.com",
)
start = dt.datetime(2026, 1, 1, 0, 0, 0, tzinfo=dt.timezone.utc)
end = dt.datetime(2026, 1, 3, 0, 0, 0, tzinfo=dt.timezone.utc) # >24h is OK (SDK will split)
df = client.download_history_data(
record_id=2,
symbol="ADA",
start=start,
end=end,
private_key="YOUR_RECORD_PRIVATE_KEY", # for decrypting encrypted data
)
print(df.head())
print("rows:", len(df))
Real-time Subscribe API (Python) - WebSocket ws/data
from typing import List, Callable
def subscribe_data(
record_id: int,
*,
symbols: List[str],
on_data_fn: Callable[[str, pd.DataFrame], None],
private_key: str | None = None,
) -> None:
"""Subscribes to live data for a record into a DataFrame (schema matches publish).
Args:
record_id: Backend record identifier.
symbols: Symbols to filter by (required).
on_data_fn: Callback function invoked upon receiving new data. The
function takes two arguments: the symbol (str) and a DataFrame
containing the new data for that symbol.
private_key: Optional, record private key for decrypting encrypted_payload.
"""
Parameters:
- record_id: must be in user's subscriptions (from /api/subscriptions)
- symbols: symbols to filter by (required). Only rows with symbol in this list are passed to on_data_fn.
- on_data_fn: callback invoked upon receiving new data. Takes (symbol: str, df: DataFrame).
- private_key: optional, record private key for decrypting encrypted_payload; required if data is encrypted.
Notes:
- Connects to ws/data, sends { wallet_address, record_id } on open.
- If data is encrypted (encrypted_payload has value), pass private_key or set LIBALPHA_RECORD_PRIVATE_KEY.
- DataFrame schema matches download_history_data (entry_id, record_id, symbol, features, timestamps).
- Blocking; run in a daemon thread for long-lived subscription.
Example
import threading
import pandas as pd
from liberal_alpha import LiberalAlphaClient
client = LiberalAlphaClient(api_key="YOUR_API_KEY", api_base="https://api.librealpha.com")
def on_data_fn(symbol: str, df: pd.DataFrame):
print(f"[{symbol}] entry_id={df['entry_id'].iloc[0]} features_len={len(df['features'].iloc[0])}")
t = threading.Thread(
target=client.subscribe_data,
kwargs={"record_id": 2, "symbols": ["YFI", "BTCUSDT"], "on_data_fn": on_data_fn, "private_key": "YOUR_RECORD_KEY"},
daemon=True,
)
t.start()
Historical Download API (download_data) Parameters
-record_id: the record id to download
-symbols: list of symbols, e.g. ["BTCUSDT", "ETHUSDT"]
If you pass [], the SDK will automatically fetch all symbols (if supported by backend).
-dates: list of local dates in YYYYMMDD format, e.g. [20251214, 20251215]
If you pass [], no date filter is applied.
-tz_info: controls how local_date is computed
"Asia/Singapore" (IANA tz string)
numeric offsets like 8, -4, or strings like "+8", "-4"
8 means UTC+8 (SGT/HKT)
-4 means UTC-4 (NYC during DST)
Example
from liberal_alpha.client import LiberalAlphaClient
client = LiberalAlphaClient( private_key="0xYOUR_PRIVATE_KEY", # api_base defaults to https://api.librealpha.com )
df = client.download_data( record_id=24, symbols=[], # empty => auto fetch all symbols dates=[], # empty => no date filter tz_info="Asia/Singapore" # or tz_info=8 )
print(df.head()) print("rows:", len(df))
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