Merge pull request #2 from cevoaustralia/feature/GenerateCommandAddition

info:added command for generate_excel file

Makefile

@@ -1,4 +1,13 @@
+AWS_REGION ?= ap-southeast-2
+AWS_ACCOUNT := cevo-dev
+
 setup:
 	pip install -r requirements.txt
 test:
-	bash tests/scripts/unit_tests.sh
+	bash tests/scripts/unit_tests.sh
+
+collect:
+	python cloudmapper.py collect --account ${AWS_ACCOUNT}
+
+generate-excel: collect
+	python cloudmapper.py generate_excel --account ${AWS_ACCOUNT}

Pipfile

@@ -0,0 +1,12 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+openpyxl = "*"
+
+[dev-packages]
+
+[requires]
+python_version = "3.9"

commands/generate_excel.py

@@ -0,0 +1,126 @@
+
+import os
+import argparse
+import json
+import pandas as pd
+from pandas import ExcelWriter
+import openpyxl
+import argparse
+from shared.common import get_account, parse_arguments
+from .collect import collect
+from .find_unused import find_unused_resources
+
+__description__ = "Run AWS API calls to collect data from the account and generates the excel sheet"
+
+MAX_RETRIES = 3
+
+def run(arguments):
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--config", help="Config file name", default="config.json", type=str
+    )
+    parser.add_argument(
+        "--account",
+        help="Account to collect from",
+        required=False,
+        type=str,
+        dest="account_name",
+    )
+    parser.add_argument(
+        "--profile",
+        help="AWS profile name",
+        required=False,
+        type=str,
+        dest="profile_name",
+    )
+    parser.add_argument(
+        "--clean",
+        help="Remove any existing local, previously collected data for the account before gathering",
+        action="store_true",
+    )
+    parser.add_argument(
+        "--max-attempts",
+        help="Override Botocore config max_attempts (default 4)",
+        required=False,
+        type=int,
+        dest="max_attempts",
+        default=4,
+    )
+    parser.add_argument(
+        "--regions",
+        help="Filter and query AWS only for the given regions (CSV)",
+        required=False,
+        type=str,
+        dest="regions_filter",
+        default="",
+    )
+
+    args = parser.parse_args(arguments)
+
+    if not args.account_name:
+        try:
+            config = json.load(open(args.config))
+        except IOError:
+            exit('ERROR: Unable to load config file "{}"'.format(args.config))
+        except ValueError as e:
+            exit(
+                'ERROR: Config file "{}" could not be loaded ({}), see config.json.demo for an example'.format(
+                    args.config, e
+                )
+            )
+        args.account_name = get_account(args.account_name, config, args.config)["name"]
+
+    _, accounts, config = parse_arguments(arguments)
+
+    data = find_unused_resources(accounts)
+
+    with open('unused_resources.json', 'w') as json_file:
+        json.dump(data, json_file, indent=4)
+
+    try:
+        json_to_excel(data, 'account-data/data/unused_resources.xlsx', args)
+    except:
+        print("Error: Unable to create Excel file.")
+
+def json_to_excel(json_data, output_path,args) -> None:
+    """
+    Converts a list of JSON-like objects to an Excel file.
+
+    Args:
+        json_data (list): List of JSON-like objects to convert.
+        output_path (str): Path to the output Excel file.
+
+    Returns:
+        None
+    """
+    # Prepare data for Excel
+    excel_data = []
+
+    def process_unused_resources(account_id, account_name, region, resources, resource_type):
+        for resource in resources:
+            entry = {
+                'Account ID': account_id,
+                'Account Name': account_name,
+                'Region': region,
+                'Resource Type': resource_type
+            }
+            entry.update(resource)
+            excel_data.append(entry)
+
+    for account in json_data:
+        account_id = account.get('account', {}).get('id')
+        account_name = account.get('account', {}).get('name')
+        for region_info in account.get('regions', []):
+            region = region_info.get('region')
+            unused_resources = region_info.get('unused_resources', {})
+            for resource_type, resources in unused_resources.items():
+                process_unused_resources(account_id, account_name, region, resources, resource_type)
+
+    # Convert to DataFrame
+    df = pd.DataFrame(excel_data)
+
+    # Save to Excel
+    with ExcelWriter(f'account-data/{args.account_name}/unused_resources.xlsx') as writer:
+        df.to_excel(writer, index=False)
+
+    print(f"Excel file has been created at {output_path}")