This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
The SPARC Automated Development System (claude-sparc.sh) is a comprehensive, agentic workflow for automated software development using the SPARC methodology (Specification, Pseudocode, Architecture, Refinement, Completion). This system leverages Claude Code's built-in tools for parallel task orchestration, comprehensive research, and Test-Driven Development.
| import boto3 | |
| from botocore.config import Config | |
| ta_config = Config(s3={"use_accelerate_endpoint": True}) | |
| s3 = boto3.client("s3", config=ta_config) |
| import boto3 | |
| s3 = boto3.client("s3") | |
| response = s3.put_bucket_accelerate_configuration( | |
| Bucket="annageller", AccelerateConfiguration={"Status": "Enabled"}, | |
| ) |
| import boto3 | |
| s3_resource = boto3.resource("s3") | |
| list(i for i in s3_resource.Bucket("annageller").objects.all() | |
| if i.get()["ContentType"] == "text/csv") |
| import boto3 | |
| s3 = boto3.client("s3") | |
| bucket_name = "annageller" | |
| s3_object = "sales/customers.csv" | |
| local_file_path = f"/Users/annageller/Desktop/datasets/{s3_object}" | |
| # Uploading without specifying content type | |
| s3.upload_file( | |
| local_file_path, |
| import os | |
| import boto3 | |
| import tempfile | |
| S3_BUCKET = "annageller" | |
| S3_PREFIX = "sales/" | |
| with tempfile.TemporaryDirectory() as tempdir: | |
| s3 = boto3.client("s3") | |
| response = s3.list_objects_v2(Bucket=S3_BUCKET, Prefix=S3_PREFIX) |
| import boto3 | |
| bucket_name = "annageller" | |
| s3_object = "ted_lasso.txt" | |
| s3_object_body = "Be curious, not judgemental" | |
| s3_resource = boto3.resource("s3") | |
| upload_result = s3_resource.Object(bucket_name, s3_object).put(Body=s3_object_body) | |
| assert upload_result["ResponseMetadata"]["HTTPStatusCode"] == 200 |
| import boto3 | |
| import pandas as pd | |
| s3 = boto3.client("s3") | |
| bucket_name = "annageller" | |
| s3_object = "sales/customers.csv" | |
| obj = s3.get_object(Bucket=bucket_name, Key=s3_object) | |
| df = pd.read_csv(obj["Body"]) |
| import boto3 | |
| import pandas as pd | |
| s3_bucket = "annageller" | |
| html_file = "sales_report.html" | |
| df = pd.DataFrame([{'year': 2021, 'month': 8, 'order_status': 'unavailable', 'order_count': 48}, | |
| {'year': 2021, 'month': 8, 'order_status': 'delivered', 'order_count': 7069}, | |
| {'year': 2021, 'month': 8, 'order_status': 'invoiced', 'order_count': 15}, | |
| {'year': 2021, 'month': 8, 'order_status': 'shipped', 'order_count': 74}, |
| import boto3 | |
| import pandas as pd | |
| s3_bucket = "awebsite" | |
| html_file = "sales_report.html" | |
| df = pd.DataFrame([{'year': 2021, 'month': 8, 'order_status': 'unavailable', 'order_count': 48}, | |
| {'year': 2021, 'month': 8, 'order_status': 'delivered', 'order_count': 7069}, | |
| {'year': 2021, 'month': 8, 'order_status': 'invoiced', 'order_count': 15}, | |
| {'year': 2021, 'month': 8, 'order_status': 'shipped', 'order_count': 74}, |