pylcg/unit_test.py

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#!/usr/bin/env python
# PyLCG - Linear Congruential Generator for IP Sharding - Developed by acidvegas ib Python (https://github.com/acidvegas/pylcg)
# unit_test.py
import ipaddress
import time
import unittest
from pylcg import IPRange, ip_stream, LCG
class Colors:
BLUE = '\033[94m'
GREEN = '\033[92m'
YELLOW = '\033[93m'
CYAN = '\033[96m'
RED = '\033[91m'
ENDC = '\033[0m'
def print_header(message: str) -> None:
print(f'\n\n{Colors.BLUE}{"="*80}')
print(f'TEST: {message}')
print(f'{"="*80}{Colors.ENDC}\n')
def print_success(message: str) -> None:
print(f'{Colors.GREEN}{message}{Colors.ENDC}')
def print_info(message: str) -> None:
print(f"{Colors.CYAN} {message}{Colors.ENDC}")
def print_warning(message: str) -> None:
print(f"{Colors.YELLOW}! {message}{Colors.ENDC}")
class TestIPSharder(unittest.TestCase):
@classmethod
def setUpClass(cls):
print_header('Setting up test environment')
cls.test_cidr = '192.0.0.0/16' # 65,536 IPs
cls.test_seed = 12345
cls.total_shards = 4
# Calculate expected IPs
network = ipaddress.ip_network(cls.test_cidr)
cls.all_ips = {str(ip) for ip in network}
print_success(f"Initialized test environment with {len(cls.all_ips):,} IPs")
def test_ip_range_initialization(self):
print_header('Testing IPRange initialization')
start_time = time.perf_counter()
ip_range = IPRange(self.test_cidr)
self.assertEqual(ip_range.total, 65536)
first_ip = ip_range.get_ip_at_index(0)
last_ip = ip_range.get_ip_at_index(ip_range.total - 1)
elapsed = time.perf_counter() - start_time
print_success(f'IP range initialization completed in {elapsed:.6f}s')
print_info(f'IP range spans from {first_ip} to {last_ip}')
print_info(f'Total IPs in range: {ip_range.total:,}')
def test_lcg_sequence(self):
print_header('Testing LCG sequence generation')
# Test sequence generation speed
lcg = LCG(seed=self.test_seed)
iterations = 1_000_000
start_time = time.perf_counter()
for _ in range(iterations):
lcg.next()
elapsed = time.perf_counter() - start_time
print_success(f'Generated {iterations:,} random numbers in {elapsed:.6f}s')
print_info(f'Average time per number: {(elapsed/iterations)*1000000:.2f} microseconds')
# Test deterministic behavior
lcg1 = LCG(seed=self.test_seed)
lcg2 = LCG(seed=self.test_seed)
start_time = time.perf_counter()
for _ in range(1000):
self.assertEqual(lcg1.next(), lcg2.next())
elapsed = time.perf_counter() - start_time
print_success(f'Verified LCG determinism in {elapsed:.6f}s')
def test_shard_distribution(self):
print_header('Testing shard distribution and randomness')
# Test distribution across shards
sample_size = 65_536 # Full size for /16
shard_counts = {i: 0 for i in range(1, self.total_shards + 1)} # 1-based sharding
unique_ips = set()
duplicate_count = 0
start_time = time.perf_counter()
# Collect IPs from each shard
for shard in range(1, self.total_shards + 1): # 1-based sharding
ip_gen = ip_stream(self.test_cidr, shard, self.total_shards, self.test_seed)
shard_unique = set()
# Get all IPs from this shard
for ip in ip_gen:
if ip in unique_ips:
duplicate_count += 1
else:
unique_ips.add(ip)
shard_unique.add(ip)
shard_counts[shard] = len(shard_unique)
elapsed = time.perf_counter() - start_time
# Print distribution statistics
print_success(f'Generated {len(unique_ips):,} IPs in {elapsed:.6f}s')
print_info(f'Average time per IP: {(elapsed/len(unique_ips))*1000000:.2f} microseconds')
print_info(f'Unique IPs generated: {len(unique_ips):,}')
if duplicate_count > 0:
print_warning(f'Duplicates found: {duplicate_count:,} ({(duplicate_count/len(unique_ips))*100:.2f}%)')
expected_per_shard = sample_size // self.total_shards
for shard, count in shard_counts.items():
deviation = abs(count - expected_per_shard) / expected_per_shard * 100
print_info(f'Shard {shard}: {count:,} unique IPs ({deviation:.2f}% deviation from expected)')
# Test randomness by checking sequential patterns
ips_list = sorted([int(ipaddress.ip_address(ip)) for ip in list(unique_ips)[:1000]])
sequential_count = sum(1 for i in range(len(ips_list)-1) if ips_list[i] + 1 == ips_list[i+1])
sequential_percentage = (sequential_count / (len(ips_list)-1)) * 100
print_info(f'Sequential IP pairs in first 1000: {sequential_percentage:.2f}% (lower is more random)')
if __name__ == '__main__':
print(f"\n{Colors.CYAN}{'='*80}")
print(f"Starting IP Sharder Tests - Testing with 65,536 IPs (/16 network)")
print(f"{'='*80}{Colors.ENDC}\n")
unittest.main(verbosity=2)