A Python SDK for accessing the Historical Market Data API and Smart Order Router API of Bjarkan
Project description
Bjarkan SDK
A Python SDK for accessing both the Smart Order Router (SOR) API and Historical Market Data services of Bjarkan.
Installation
You can install the Bjarkan SDK using pip:
pip install bjarkan-sdk
Usage
The SDK provides two main client classes:
BjarkanDataClient
: For interacting with the Historical Market Data API (data.bjarkan.io)BjarkanSORClient
: For interacting with the Smart Order Router API (api.bjarkan.io)
Here's a quick example of how to use both clients:
from bjarkan_sdk import BjarkanDataClient, BjarkanSORClient
from datetime import datetime, timedelta
# Initialize the clients
data_client = BjarkanDataClient()
sor_client = BjarkanSORClient()
# Authenticate
data_client.authenticate("your_username", "your_password")
sor_client.authenticate("your_username", "your_password")
# Using the SOR API
orderbook_config = {
"aggregated": True,
"exchanges": ["binance", "okx", "htx"],
"symbols": ["BTC/USDT", "ETH/USDT"],
"depth": 10
}
result = sor_client.set_orderbook_config(orderbook_config)
print("Orderbook config set:", result)
latest_orderbook = sor_client.get_latest_orderbook()
print("Latest orderbook:", latest_orderbook)
# Using the Data API
tables = data_client.get_tables()
print("Available tables:", tables)
result = data_client.get_history(
table_name="example_table",
start_time=datetime.now() - timedelta(hours=1),
end_time=datetime.now(),
exchange='binance',
symbol="BTC/USDT",
bucket_period="1 minute",
sort_descending=False,
limit=100
)
print("Historical data:", result['data'][:5]) # Print first 5 entries
print(f"Query performance: {result['query_performance_seconds']:.4f} seconds")
API Reference
BjarkanDataClient
The BjarkanDataClient
class is used for interacting with the Bjarkan Historical Market Data service.
__init__(base_url: str = 'https://data.bjarkan.io')
Initialize the client with the base URL of the Bjarkan Data service.
authenticate(username: str, password: str)
Authenticate with the Data service using your username and password. This method must be called before making any other API calls.
Methods
get_tables() -> List[Dict[str, any]]
get_history(table_name: str, start_time: datetime, end_time: datetime, ...) -> Dict[str, any]
get_paginated_history(table_name: str, start_time: datetime, end_time: datetime, ...) -> Iterator[Dict[str, any]]
validate_bucket_period(bucket_period: str) -> bool
BjarkanSORClient
The BjarkanSORClient
class is used for interacting with the Bjarkan Smart Order Router API.
__init__(base_url: str = 'https://api.bjarkan.io')
Initialize the client with the base URL of the Bjarkan SOR API service.
authenticate(username: str, password: str)
Authenticate with the SOR API service using your username and password. This method must be called before making any other API calls.
Methods
set_orderbook_config(config: Dict) -> Dict
get_orderbook_config() -> Dict
set_trades_config(config: Dict) -> Dict
get_trades_config() -> Dict
set_api_keys(api_configs: List[Dict]) -> Dict
get_api_keys() -> Dict
get_latest_orderbook() -> Dict
execute_order(order: Dict) -> Dict
get_balances() -> Dict
For detailed information on each method, please refer to the docstrings in the source code.
Examples
Setting Orderbook Configuration (SOR API)
sor_client = BjarkanSORClient()
sor_client.authenticate("your_username", "your_password")
orderbook_config = {
"aggregated": True,
"exchanges": ["binance", "okx", "htx"],
"symbols": ["BTC/USDT", "ETH/USDT"],
"depth": 10
}
result = sor_client.set_orderbook_config(orderbook_config)
print("Orderbook config set:", result)
Fetching Historical Data with Pagination (Data API)
from datetime import datetime, timedelta
data_client = BjarkanDataClient()
data_client.authenticate("your_username", "your_password")
start_time = datetime.now() - timedelta(days=1)
end_time = datetime.now()
for page in data_client.get_paginated_history(
table_name="example_table",
start_time=start_time,
end_time=end_time,
exchange="binance",
symbol="BTC/USDT",
bucket_period="5 minutes",
page_size=500
):
print(f"Retrieved {len(page['data'])} records")
print(f"Query performance: {page['query_performance_seconds']:.4f} seconds")
# Process the data in the current page
for record in page['data']:
# Do something with each record
pass
License
This project is licensed under the MIT License - see the LICENSE file for details.
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