Improved CSV generator and performance test (#109)

Signed-off-by: Justin Ohrenberger <justinohrenberger@gmail.com>

tests/samples/csv_random_data_generate_at_scale.py

@@ -0,0 +1,250 @@
+from concurrent.futures import ThreadPoolExecutor
+import csv
+import functools
+import io
+import logging
+import random
+import time
+import pytz
+from datetime import datetime, timedelta
+from faker import Faker
+
+fake = Faker()
+
+def log_execution_time(func):
+    """Decorator to log the execution time of a function."""
+
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        start_time = time.time()
+        result = func(*args, **kwargs)
+        end_time = time.time()
+        logging.info(f"{func.__name__} executed in {end_time - start_time:.2f} seconds")
+        return result
+
+    return wrapper
+
+class FakeFocus:
+
+    def __init__(self):
+        self._cache = {}
+
+    # Current time in UTC
+    now = datetime.now(pytz.utc)
+
+    # 30 days ago from now
+    thirty_days_ago = now - timedelta(days=30)
+
+    @property
+    def InvoiceIssuer(self):
+        return self._cached_property('InvoiceIssuer', self.get_aws_invoice_issuer)
+
+    @property
+    def ResourceID(self):
+        return self._cached_property('ResourceID', fake.uuid4)
+
+    @property
+    def ChargeType(self):
+        return self._cached_property('ChargeType', self.get_charge_type)
+
+    @property
+    def Provider(self):
+        return self._cached_property('Provider', fake.company)
+
+    @property
+    def BillingAccountName(self):
+        return self._cached_property('BillingAccountName', fake.company)
+
+    @property
+    def SubAccountName(self):
+        # Only generate a new datetime when it's not in cache
+        if 'SubAccountName' not in self._cache:
+            # Generate a random datetime object within the last 30 days
+            random_datetime = fake.date_time_between(start_date=self.thirty_days_ago, end_date=self.now, tzinfo=pytz.utc)
+            formatted_date = datetime.strftime(random_datetime, '%Y-%m-%dT%H:%M:%SZ')
+            self._cache['SubAccountName'] = formatted_date
+
+        return self._cache['SubAccountName']
+
+    @property
+    def BillingAccountId(self):
+        return self._cached_property('BillingAccountId', fake.uuid4)
+
+    @property
+    def Publisher(self):
+        return self._cached_property('Publisher', self.get_aws_publisher)
+
+    @property
+    def ResourceName(self):
+        return self._cached_property('ResourceName', self.get_aws_resource_name)
+
+    @property
+    def ServiceName(self):
+        return self._cached_property('ServiceName', self.get_aws_service_name)
+
+    @property
+    def BilledCurrency(self):
+        return self._cached_property('BilledCurrency', lambda: 'USD')
+
+    @property
+    def BillingPeriodEnd(self):
+        # Only generate a new datetime when it's not in cache
+        if 'BillingPeriodEnd' not in self._cache:
+            # Generate a random datetime object within the last 30 days
+            random_datetime = fake.date_time_between(start_date=self.thirty_days_ago, end_date=self.now, tzinfo=pytz.utc)
+            formatted_date = datetime.strftime(random_datetime, '%Y-%m-%dT%H:%M:%SZ')
+            self._cache['BillingPeriodEnd'] = formatted_date
+
+        return self._cache['BillingPeriodEnd']
+
+    @property
+    def BillingPeriodStart(self):
+        # Only generate a new datetime when it's not in cache
+        if 'BillingPeriodStart' not in self._cache:
+            # Generate a random datetime object within the last 30 days
+            random_datetime = fake.date_time_between(start_date=self.thirty_days_ago, end_date=self.now, tzinfo=pytz.utc)
+            formatted_date = datetime.strftime(random_datetime, '%Y-%m-%dT%H:%M:%SZ')
+            self._cache['BillingPeriodStart'] = formatted_date
+
+        return self._cache['BillingPeriodStart']
+
+    @property
+    def Region(self):
+        return self._cached_property('Region', self.get_aws_region)
+
+    @property
+    def ServiceCategory(self):
+        return self._cached_property('ServiceCategory', self.get_aws_service_category)
+
+    @property
+    def ChargePeriodStart(self):
+        # Only generate a new datetime when it's not in cache
+        if 'ChargePeriodStart' not in self._cache:
+            # Generate a random datetime object within the last 30 days
+            random_datetime = fake.date_time_between(start_date=self.thirty_days_ago, end_date=self.now, tzinfo=pytz.utc)
+            formatted_date = datetime.strftime(random_datetime, '%Y-%m-%dT%H:%M:%SZ')
+            self._cache['ChargePeriodStart'] = formatted_date
+
+        return self._cache['ChargePeriodStart']
+
+    @property
+    def ChargePeriodEnd(self):
+        # Only generate a new datetime when it's not in cache
+        if 'ChargePeriodEnd' not in self._cache:
+            # Generate a random datetime object within the last 30 days
+            random_datetime = fake.date_time_between(start_date=self.thirty_days_ago, end_date=self.now, tzinfo=pytz.utc)
+            formatted_date = datetime.strftime(random_datetime, '%Y-%m-%dT%H:%M:%SZ')
+            self._cache['ChargePeriodEnd'] = formatted_date
+
+        return self._cache['ChargePeriodEnd']
+
+    @property
+    def BilledCost(self):
+        return self._cached_property('BilledCost', lambda: fake.pyfloat(left_digits=3, right_digits=2, positive=True))
+
+    @property
+    def AmortizedCost(self):
+        return self._cached_property('AmortizedCost', lambda: fake.pyfloat(left_digits=3, right_digits=2, positive=True))
+
+    def _cached_property(self, prop_name, generator_func):
+        if prop_name not in self._cache:
+            self._cache[prop_name] = generator_func()
+        return self._cache[prop_name]
+
+    def to_dict(self):
+        return {
+            'InvoiceIssuer': self.InvoiceIssuer,
+            'ResourceID': self.ResourceID,
+            'ChargeType': self.ChargeType,
+            'Provider': self.Provider,
+            'BillingAccountName': self.BillingAccountName,
+            'SubAccountName': self.SubAccountName,
+            'BillingAccountId': self.BillingAccountId,
+            'Publisher': self.Publisher,
+            'ResourceName': self.ResourceName,
+            'ServiceName': self.ServiceName,
+            'BilledCurrency': self.BilledCurrency,
+            'BillingPeriodEnd': self.BillingPeriodEnd,
+            'BillingPeriodStart': self.BillingPeriodStart,
+            'Region': self.Region,
+            'ServiceCategory': self.ServiceCategory,
+            'ChargePeriodStart': self.ChargePeriodStart,
+            'ChargePeriodEnd': self.ChargePeriodEnd,
+            'BilledCost': self.BilledCost,
+            'AmortizedCost': self.AmortizedCost
+        }
+
+
+    def get_aws_invoice_issuer(self):
+            aws_entities = [
+                'AWS Inc.', 'Amazon Web Services', 'AWS Marketplace', 
+                'Amazon Data Services', 'AWS CloudFront', 'Amazon S3 Billing', 
+                'Amazon EC2 Billing', 'AWS Lambda Billing'
+            ]
+            return str(random.choice(aws_entities))
+
+    def get_charge_type(self):
+            aws_entities = [
+                'Adjustment', 'Purchase', 'Tax', 
+                'Usage'
+            ]
+            return str(random.choice(aws_entities))
+
+    def get_aws_publisher(self):
+            publisher_types = ['Software', 'Service', 'Platform']
+            publisher_suffix = random.choice(['Inc.', 'LLC', 'Ltd.', 'Group', 'Technologies', 'Solutions'])
+            return f"{fake.company()} {random.choice(publisher_types)} {publisher_suffix}"
+
+    def get_aws_resource_name(self):
+            resource_types = ['i-', 'vol-', 'snap-', 'ami-', 'bucket-', 'db-']
+            resource_prefix = random.choice(resource_types)
+            resource_id = fake.hexify(text='^^^^^^^^', upper=False)
+            return f'{resource_prefix}{resource_id}'
+
+    def get_aws_service_category(self):
+            aws_service_categories = [
+                'AI and Machine Learning', 'Analytics', 'Business Applications', 'Compute', 'Databases', 'Developer Tools', 'Multicloud',
+                'Identity', 'Integration', 'Internet of Things', 'Management and Governance', 'Media', 'Migration', 'Mobile', 'Networking',
+                'Security', 'Storage', 'Web', 'Other'
+            ]
+            return random.choice(aws_service_categories)
+
+    def get_aws_service_name(self):
+            aws_services = [
+                'Amazon EC2', 'Amazon S3', 'AWS Lambda', 'Amazon RDS', 
+                'Amazon DynamoDB', 'Amazon VPC', 'Amazon Route 53', 
+                'Amazon CloudFront', 'AWS Elastic Beanstalk', 'Amazon SNS', 
+                'Amazon SQS', 'Amazon Redshift', 'AWS CloudFormation', 
+                'AWS IAM', 'Amazon EBS', 'Amazon ECS', 'Amazon EKS', 
+                'Amazon ElastiCache', 'AWS Fargate', 'AWS Glue'
+            ]
+            return random.choice(aws_services)
+
+    def get_aws_region(self):
+            aws_regions = [
+                'us-east-1', 'us-west-1', 'us-west-2', 'eu-west-1', 'eu-central-1',
+                'ap-southeast-1', 'ap-southeast-2', 'ap-northeast-1', 'ap-northeast-2',
+                'ap-south-1', 'sa-east-1', 'ca-central-1', 'eu-north-1', 'eu-west-2',
+                'eu-west-3', 'ap-east-1', 'me-south-1', 'af-south-1', 'eu-south-1'
+            ]
+            return random.choice(aws_regions)
+
+def generate_fake_focus():
+    return FakeFocus()
+
+def write_focus_to_csv(focus, csv_writer):
+    csv_writer.writerow(focus.to_dict())
+
+@log_execution_time
+def generate_and_write_fake_focuses(csv_filename, num_records):
+    headers = FakeFocus().to_dict().keys()
+
+    with open(csv_filename, 'w', newline='') as csvfile:
+        csv_writer = csv.DictWriter(csvfile, fieldnames=headers)
+        csv_writer.writeheader()
+
+        with ThreadPoolExecutor() as executor:
+            futures = [executor.submit(generate_fake_focus) for _ in range(num_records)]
+            for future in futures:
+                focus = future.result()
+                write_focus_to_csv(focus, csv_writer)

tests/test_progressive_performance.py

@@ -0,0 +1,126 @@
+import logging
+import os
+import subprocess
+import time
+import unittest
+
+from tests.samples.csv_random_data_generate_at_scale import generate_and_write_fake_focuses
+
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - [%(funcName)s] - %(message)s')
+
+
+class TestProgressivePerformance(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        #Generate 1000 fake focuses to a CSV file
+        cls.csv_filename_1000 = 'fake_focuses1000.csv'
+        cls.csv_filename_10000 = 'fake_focuses10000.csv'
+        cls.csv_filename_50000 = 'fake_focuses50000.csv'
+        cls.csv_filename_100000 = 'fake_focuses100000.csv'
+        cls.csv_filename_250000 = 'fake_focuses250000.csv'
+        cls.csv_filename_500000 = 'fake_focuses500000.csv'
+
+        logging.info("Generating file with 1,000 records")
+        cls.generate_test_file(str(cls.csv_filename_1000), 1000)
+
+        # logging.info("Generating file with 10,0000 records")
+        # cls.generate_test_file(str(cls.csv_filename_10000), 10000)
+
+        # logging.info("Generating file with 50,0000 records")
+        # cls.generate_test_file(str(cls.csv_filename_50000), 50000)
+
+        # logging.info("Generating file with 100,0000 records")
+        # cls.generate_test_file(str(cls.csv_filename_100000), 100000)
+
+        # logging.info("Generating file with 250,0000 records")
+        # cls.generate_test_file(str(cls.csv_filename_250000), 250000)
+
+        # logging.info("Generating file with 500,0000 records")
+        # cls.generate_test_file(str(cls.csv_filename_500000), 500000)
+
+    @classmethod
+    def tearDownClass(cls):
+        base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+
+        if os.path.exists(os.path.join(base_dir, 'fake_focuses.csv')):
+            os.remove(os.path.join(base_dir, 'fake_focuses.csv'))
+
+        if os.path.exists(os.path.join(base_dir, str(cls.csv_filename_1000))):
+            os.remove(os.path.join(base_dir, str(cls.csv_filename_1000)))
+
+        if os.path.exists(os.path.join(base_dir, str(cls.csv_filename_10000))):
+            os.remove(os.path.join(base_dir, str(cls.csv_filename_10000)))
+
+        if os.path.exists(os.path.join(base_dir, str(cls.csv_filename_50000))):
+            os.remove(os.path.join(base_dir, str(cls.csv_filename_50000)))
+
+        if os.path.exists(os.path.join(base_dir, str(cls.csv_filename_100000))):
+            os.remove(os.path.join(base_dir, str(cls.csv_filename_100000)))
+
+        if os.path.exists(os.path.join(base_dir, str(cls.csv_filename_250000))):
+            os.remove(os.path.join(base_dir, str(cls.csv_filename_250000)))
+
+        if os.path.exists(os.path.join(base_dir, str(cls.csv_filename_500000))):
+            os.remove(os.path.join(base_dir, str(cls.csv_filename_500000)))
+
+    @classmethod
+    def generate_test_file(cls, csv_filename, number_of_records):
+        #Generate fake focuses to a CSV file
+        # fake_focuses = generate_fake_focus(number_of_records)
+
+        # write_fake_focuses_to_csv(fake_focuses, csv_filename)
+        generate_and_write_fake_focuses(csv_filename, number_of_records)
+
+
+    def run_validator(self, args):
+        # Get the current directory of this test file
+        test_dir = os.path.dirname(os.path.abspath(__file__))
+
+        # Construct the path to the application directory
+        app_dir = os.path.join(test_dir, '../focus_validator')
+        # Set the environment variable for logging level
+        env = os.environ.copy()
+        env["LOG_LEVEL"] = "INFO"
+
+        command = ['poetry', 'run', 'python', os.path.join(app_dir, 'main.py')] + args
+        return subprocess.run(command, env=env, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, check=True)
+
+    def test_1000_record_csv_performance(self):
+        self.execute_performance(str(self.csv_filename_1000), 25.0)
+
+    # def test_10000_record_csv_performance(self):
+    #     self.execute_performance(str(self.csv_filename_10000), 25.0)
+
+    # def test_50000_record_csv_performance(self):
+    #     self.execute_performance(str(self.csv_filename_50000), 150.0)
+
+    # def test_100000_record_csv_performance(self):
+    #     self.execute_performance(str(self.csv_filename_100000), 300.0)
+
+    # def test_250000_record_csv_performance(self):
+    #     self.execute_performance(str(self.csv_filename_250000), 300.0)
+
+    # def test_500000_record_csv_performance(self):
+    #     self.execute_performance(str(self.csv_filename_500000), 300.0)
+
+    def execute_performance(self, file_name, performance_threshold):
+        # Get the current directory of this test file
+        test_dir = os.path.dirname(os.path.abspath(__file__))
+
+        start_time = time.time()
+
+        # Command to execute the focus_validator tool
+        result = self.run_validator(['--data-file', os.path.join(test_dir, '../' + file_name)])
+        print(result.stdout)
+
+        end_time = time.time()
+        duration = end_time - start_time
+        logging.info(f"File: {file_name} Duration: {duration} seconds")
+
+        self.assertLess(duration, performance_threshold, f"Performance test exceeded threshold. Duration: {duration} seconds")
+        self.assertEqual(result.returncode, 0, "Focus Validator did not exit cleanly.")
+
+
+if __name__ == '__main__':
+    unittest.main()