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How to Send Your Data

PreviousPlatform Architecture OverviewNextVisualizing Trade Insights: Pre & Post-Trade Dashboards

Last updated 1 month ago

The first step in leveraging our platform is connecting your data. Once your data is securely ingested, you gain access to powerful tools for analysis, reporting, execution algorithms, and real-time insights. Whether you’re tracking market movements, optimizing execution strategies, or automating trading workflows, our SDK ensures a seamless, secure, and efficient data transfer process. For specific data schemas visit the "" section of the documentation.

Why Connect Your Trade Data?

Centralized Data Management – Store and process trade data efficiently in one place.

Advanced Analytics – Unlock dashboards and reports for better decision-making.

Automated Execution – Use execution algorithms to optimize trading strategies.

Real-time Monitoring – Gain insights into market trends and trade performance.

Step-by-step Guide

Sending Trade Data

Step 1: Install the SDK

First, ensure you have the Blockhouse SDK installed in your Python environment. If you haven’t installed it yet, you can do so using:

pip install blockhouse

This package provides a simple interface for securely transmitting trade data.

Step 2: Authenticate and Connect

Before sending data, authenticate using your unique . You will need this key to access our data ingestion service.

from blockhouse import Transfer  

# Initialize the SDK with your unique API key
client= Transfer("YOUR_API_KEY")

Note: Your API key is unique to your account. Keep it secure and do not share it.

Step 3: Prepare Your Trade Data File

Our system supports multiple file formats including:

• CSV (Comma-Separated Values)

• Parquet (Optimized for big data processing)

• JSON (Lightweight, flexible data format)

• Other structured data formats

File Formatting Guidelines

• Ensure that your trade data file contains well-structured columns (e.g., trade_id, timestamp, symbol, price, volume, etc.).

• File naming conventions are flexible, but using timestamped filenames can help with tracking.

• For CSV files, use UTF-8 encoding to avoid formatting issues.

Step 4: Send Trade Data

Once your trade data file is ready, send it to our platform using the following code:

result = client.process_data(
    trade_data_path='trade_data.csv',
    bucket_name="blockhouse-sdk"
)
print(result)

Sending Market Data

In addition to trade data, our SDK also supports the ingestion of market data, allowing you to consolidate your internal and external market sources for richer analytics and strategy development. The process is identical to sending trade data—simply specify the market_data_path.

Example:

result = client.process_data(      
    market_data_path='market_data.csv',
    bucket_name="blockhouse-sdk"
)

Market Data Guidelines

• Supported formats: CSV, Parquet, JSON, and others.

• Recommended columns: symbol, timestamp, bid_price, ask_price, volume, etc.

• Use consistent timestamps and symbol naming to ensure alignment with your trade data.

Sending Market Data and Trade Data

Example:

result = client.process_data(    
    trade_data_path='trade_data.csv',  
    market_data_path='market_data.csv',
    bucket_name="blockhouse-sdk"
)

What happens next?

• The SDK securely transfers your data to our servers.

• You receive an acknowledgment response upon a successful upload.

• Your data becomes accessible for further processing, analytics, and execution.

Connecting your trade data is the first step to unlocking powerful insights, automation, and execution capabilities on our platform. With just a few lines of code, you can seamlessly transmit trade data, setting the foundation for smarter trading decisions.

For further assistance, refer to our or reach out to our support team.

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