⚡ Bolt: [performance improvement] O(1) memory usage for IP generation

.jules/bolt.md

@@ -16,3 +16,7 @@
 ## 2024-05-09 - Redundant attributes in Python ipaddress
 **Learning:** By definition in Python's `ipaddress` module, `is_private`, `is_loopback`, `is_link_local`, `is_unspecified`, and `is_reserved` inherently evaluate as `is_global = False`. Evaluating them sequentially in an SSRF blocklist is highly redundant and slow.
 **Action:** When validating IPs for global routability, replace long chains like `ip.is_private or ip.is_loopback or ...` with a significantly faster logical reduction: `not ip.is_global or ip.is_multicast or (type(ip) is ipaddress.IPv6Address and ip.is_site_local)`. This reduces 8 checks down to 3 and yields massive performance gains on public IPs.
+
+## 2024-05-09 - Optimize Memory Usage with Generator Expressions
+**Learning:** When queueing a large sequence of tasks into a `ThreadPoolExecutor` or creating a dictionary of futures from a sequence, using a list comprehension pre-allocates all objects in memory. For large lists, this creates an O(N) memory spike.
+**Action:** Use a generator expression instead of a list comprehension to feed the initial data into the executor submission loop. This changes the intermediate storage memory complexity from O(N) to O(1) by avoiding the allocation of an intermediate list in memory.

testping1.py

@@ -285,7 +285,7 @@ def is_reachable(ip, timeout=1):
     base_int = int(start_obj)
     ip_class = type(start_obj)
     # ⚡ Bolt: Pass pre-instantiated IP objects to worker threads to avoid string parsing overhead
-    ips_to_scan = [ip_class(base_int + i) for i in range(total_ips)]
+    ips_to_scan = (ip_class(base_int + i) for i in range(total_ips))
 
     # ⚡ Bolt: Parallelize network scanning using ThreadPoolExecutor
     # Reduces scan time significantly by performing pings concurrently instead of sequentially.