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Python SDK Advanced Features

Data Neuron's Python SDK offers several advanced features to enhance your data querying and management capabilities.

Custom Query Execution​

Execute custom SQL queries while still benefiting from Data Neuron's context awareness:

custom_sql = "SELECT * FROM users WHERE signup_date > :date"
params = {"date": "2023-01-01"}
result = dn.execute_custom_query(custom_sql, params)

Batch Processing​

Efficiently process multiple queries in a single batch:

queries = [
    "How many active users do we have?",
    "What was our revenue last month?",
    "Who are our top 5 customers by sales?"
]
results = dn.batch_query(queries)

Query Explanation​

Get detailed explanations of how Data Neuron interprets and executes queries:

query = "What is our user retention rate?"
result = dn.explain_query(query)
print(result['explanation'])

Context Management​

Dynamically switch between different semantic contexts:

dn.set_context("sales_analytics")
sales_result = dn.query("What were our top-selling products?")

dn.set_context("user_engagement")
engagement_result = dn.query("What is our daily active user count?")

Error Handling and Logging​

Implement advanced error handling and logging:

import logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

try:
    result = dn.query("Complex query that might fail")
except DataNeuronQueryError as e:
    logger.error(f"Query failed: {e}")
    # Implement fallback or retry logic

These advanced features allow you to leverage the full power of Data Neuron in your Python applications, enabling more complex and flexible data operations.