Choose names that clearly convey their purpose, role, and meaning while maintaining consistency with established patterns in the codebase. Names should be self-documenting and unambiguous to future maintainers.

Key principles:

Semantic clarity: Names should reflect their actual purpose and role in the system architecture. For example, use receiver_host instead of peer_host_name when the architecture has a clear receiver-sender relationship, or num_skip_prefix_chunk instead of num_skip_chunk when the meaning is “number of prefix chunks to skip”.
Consistency with patterns: Follow established naming conventions in the codebase. If other batch operations use batched_xxx pattern, use batched_contains instead of batch_contains. Similarly, maintain consistency between related functions like using batched instead of mixing layerwise and batched.
Avoid ambiguous abbreviations: Use clear variable names instead of cryptic abbreviations. Replace unclear names like anw and anws with descriptive names like cache_exists_results.
Distinguish similar entities: When multiple files or classes serve similar but distinct purposes, use names that clearly differentiate them. Instead of disagg_proxy_server.py and disagg_proxy_server_original.py, use names that describe their specific roles.

Example of good naming:

# Instead of:
def batch_contains(self, keys): pass
anws = self.engine_.batched_contains(keys)
for anw in anws:
    if not anw:

# Use:
def batched_contains(self, keys): pass  # Consistent with other batched_xxx methods
cache_exists_results = self.engine_.batched_contains(keys)
for cache_exists in cache_exists_results:
    if not cache_exists:

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