Output Message

# Define the storage pricing for each option aws_storage_price = 0.023 # per GB-month azure_storage_price = 0.019 # per GB-month # Define the amount of storage to calculate the cost for storage_gb = 1000 # 1 TB # Calculate the cost for…

action=action_attribute, effect="allow", context=Context(attributes=context_attributes) ) # Store the policy in memory storage = MemoryStorage() storage.add_policy(policy) # Create an engine to evaluate policies engine = Engin…

return [1.0, 2.0, 3.0] def process_documents(documents): vectors = [] with ThreadPoolExecutor(max_workers=10) as executor: futures = [executor.submit(vectorize_document, document) for document in documents] for …

# Adjust rate limit based on average response time if len(response_times) > 10: avg_response_time = sum(response_times[-10:]) / 10 if avg_response_time > 0.1: # Threshold for high loa…

transition_id = transition['id'] break if transition_id: jira.transition_issue(task, transition_id) print(f"Task {task_key} has been updated to {desired_status}.") else: print(f"No transition found for status {d…

# Convert columns to appropriate data types datasets['some_column'] = pd.to_numeric(datasets['some_column'], errors='coerce') # Define secure tuning function def secure_tuning(row): # Implement secure tuning logic here # Example: C…

# Gradually update references to use the new key # After ensuring all data is encrypted with the new key, remove the old key client.secrets.kv.v2.delete_metadata_and_all_versions( path=current_key_name, mount_poi…

queries = ["query1", "query2", "query3"] * 500 # 1500 queries start_time = time.time() rewritten_queries = rewriter.batch_process_queries(queries) end_time = time.time() print(f"Processed {len(rewritten_queries)} queries in {end_time - st…

eval_dataset=eval_dataset, ) trainer.train() ``` ### Evaluation Metrics To evaluate the quality of reformulated queries, you can use metrics like BLEU or ROUGE: ```python from nltk.translate.bleu_score import sentence_bleu def eval…