⚡️ Speed up function `_encode_error_event` by 20% by codeflash-ai[bot] · Pull Request #26 · aseembits93/deepgram-python-sdk

codeflash-ai · 2025-10-17T10:30:23Z

📄 20% (0.20x) speedup for `_encode_error_event` in `src/deepgram/extensions/telemetry/proto_encoder.py`

⏱️ Runtime : 17.0 milliseconds → 14.1 milliseconds (best of 171 runs)

📝 Explanation and details

Impact: high
Impact_explanation: Looking at this optimization report, I need to assess the impact based on the provided rubric and data.

Analysis of Runtime Performance:

Overall runtime: 17.0ms → 14.1ms (20.31% speedup)
This exceeds the 100 microsecond threshold significantly, indicating substantial work
The 20% speedup exceeds the 15% threshold for high impact

Analysis of Generated Test Results:

Small/basic tests: 2-14% faster (mostly above 5%)
Large attribute maps (500 entries): 25-27% faster - this is excellent
Bulk operations (1000 events): 19% faster - very good
Empty/minimal data: 12-20% faster - good across the board

The test results show consistent improvements across all test cases, with particularly strong performance on larger workloads (25-27% for large maps, 19% for bulk operations).

Analysis of Hot Path Usage:
The calling_fn_details shows _encode_error_event is called in a loop within _normalize_events() for multiple event types:

http_error events
ws_error events
uncaught_error events
error_event events

This means the optimization effect is multiplicative - each improvement gets applied many times in typical telemetry workloads.

Key Optimization Quality:
The optimizations are well-designed:

Fast path for small varints (common case optimization)
Elimination of intermediate allocations via b"".join()
Localized attribute lookups in tight loops
Pre-allocated lists for better memory efficiency

These target fundamental performance bottlenecks in Python bytecode and memory allocation.

Assessment:

Runtime exceeds 100μs threshold ✓
Speedup exceeds 15% threshold ✓
Function is in hot path (called in loops) ✓
Consistent improvements across all test cases ✓
Large workload improvements are substantial (25-27%) ✓

END OF IMPACT EXPLANATION

The optimization achieves a 20% speedup through several key improvements targeting Python's bytecode efficiency and memory allocation patterns:

Key Optimizations:

Fast path for small varints: Added an early return if value <= 0x7F: return bytes([value]) in _varint(), avoiding loop overhead for small values (common in protobuf encoding).
Localized attribute lookups: In tight loops, cached method references like append = out.append to avoid repeated attribute resolution overhead.
Eliminated intermediate concatenations: Replaced multiple + operations with b"".join() in functions like _len_delimited(), _string(), and _timestamp_message(). This avoids creating temporary byte objects that get immediately discarded.
Pre-allocated lists for joins: Changed from progressive bytearray concatenation to collecting parts in lists, then joining once. This is more efficient because b"".join(list) pre-allocates the final buffer size.
Direct byte literals: Replaced _varint(1 if value else 0) with b'\x01' if value else b'\x00' in _bool(), eliminating function call overhead for this common case.

Performance Impact by Test Type:

Small/simple events (basic tests): 2-14% faster due to fast-path varints and reduced allocations
Large attribute maps (500 entries): 25-27% faster due to pre-allocated lists and localized lookups
Bulk operations (1000 events): 19% faster from cumulative micro-optimizations
Empty/minimal data: 12-20% faster from avoiding unnecessary work

The optimizations are particularly effective for telemetry use cases with many small integer fields and moderate-sized attribute maps, which are common in error event encoding.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 1024 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	✅ 2 Passed
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from __future__ import annotations

import struct
import sys
import typing
from typing import Dict

# imports
import pytest  # used for our unit tests
from src.deepgram.extensions.telemetry.proto_encoder import _encode_error_event

# unit tests

# --- Helper functions for test decoding ---
def decode_varint(data, offset=0):
    """Decode a varint from data[offset:]"""
    shift = 0
    result = 0
    while True:
        b = data[offset]
        result |= (b & 0x7f) << shift
        offset += 1
        if not (b & 0x80):
            break
        shift += 7
    return result, offset

def decode_key(data, offset):
    """Decode a protobuf key (field_number, wire_type) from data[offset:]"""
    key, offset2 = decode_varint(data, offset)
    field_number = key >> 3
    wire_type = key & 0x07
    return field_number, wire_type, offset2

def decode_len_delimited(data, offset):
    """Decode length-delimited field from data[offset:]"""
    length, offset2 = decode_varint(data, offset)
    return data[offset2:offset2+length], offset2+length

def decode_string_field(data, offset, expected_field_number):
    """Decode a string field and check field number"""
    field_number, wire_type, offset2 = decode_key(data, offset)
    s, offset3 = decode_len_delimited(data, offset2)
    return s.decode('utf-8'), offset3

def decode_bool_field(data, offset, expected_field_number):
    field_number, wire_type, offset2 = decode_key(data, offset)
    value, offset3 = decode_varint(data, offset2)
    return bool(value), offset3

def decode_int_field(data, offset, expected_field_number):
    field_number, wire_type, offset2 = decode_key(data, offset)
    value, offset3 = decode_varint(data, offset2)
    return value, offset3

def decode_timestamp_field(data, offset, expected_field_number):
    field_number, wire_type, offset2 = decode_key(data, offset)
    ts_bytes, offset3 = decode_len_delimited(data, offset2)
    # decode seconds (field 1) and nanos (field 2)
    sec, off = decode_int_field(ts_bytes, 0, 1)
    nanos = 0
    if off < len(ts_bytes):
        nanos, _ = decode_int_field(ts_bytes, off, 2)
    return sec, nanos, offset3

def decode_map_str_str(data, offset, expected_field_number):
    """Decode map<string,string> field from data[offset:]"""
    out = {}
    while offset < len(data):
        field_number, wire_type, offset2 = decode_key(data, offset)
        if field_number != expected_field_number or wire_type != 2:
            break
        entry_bytes, offset3 = decode_len_delimited(data, offset2)
        # entry: key (field 1), value (field 2)
        k, off = decode_string_field(entry_bytes, 0, 1)
        v, off2 = decode_string_field(entry_bytes, off, 2)
        out[k] = v
        offset = offset3
    return out, offset

# --- Basic Test Cases ---

def test_basic_minimal_required_fields():
    # Only required fields, all optionals omitted
    codeflash_output = _encode_error_event(
        err_type="TypeError",
        message="Division by zero",
        severity=3,
        handled=True,
        ts=1680000000.0,
        attributes=None,
    ); result = codeflash_output # 17.6μs -> 17.2μs (2.51% faster)
    offset = 0
    # err_type (field 1)
    s, offset = decode_string_field(result, offset, 1)
    # message (field 2)
    s, offset = decode_string_field(result, offset, 2)
    # severity (field 7)
    sev, offset = decode_int_field(result, offset, 7)
    # handled (field 8)
    handled, offset = decode_bool_field(result, offset, 8)
    # timestamp (field 9)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)

def test_basic_all_fields_present():
    # All fields present
    codeflash_output = _encode_error_event(
        err_type="ValueError",
        message="Invalid value",
        severity=2,
        handled=False,
        ts=1680000000.123456789,
        attributes={"foo": "bar", "baz": "qux"},
        stack_trace="Traceback...",
        file="main.py",
        line=42,
        column=7,
    ); result = codeflash_output # 30.1μs -> 28.3μs (6.37% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    s, offset = decode_string_field(result, offset, 3)
    s, offset = decode_string_field(result, offset, 4)
    value, offset = decode_int_field(result, offset, 5)
    value, offset = decode_int_field(result, offset, 6)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)
    attributes, offset = decode_map_str_str(result, offset, 10)

def test_basic_empty_strings_and_zeroes():
    # Empty strings, zero severity, handled False, zero timestamp
    codeflash_output = _encode_error_event(
        err_type="",
        message="",
        severity=0,
        handled=False,
        ts=0.0,
        attributes={},
        stack_trace="",
        file="",
        line=0,
        column=0,
    ); result = codeflash_output # 13.0μs -> 12.0μs (8.89% faster)
    offset = 0
    # err_type not present
    # message not present
    # stack_trace not present
    # file not present
    value, offset = decode_int_field(result, offset, 5)
    value, offset = decode_int_field(result, offset, 6)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)

# --- Edge Test Cases ---

def test_edge_long_strings_and_unicode():
    # Very long string and unicode
    long_str = "𝄞" * 200  # 200 unicode chars
    codeflash_output = _encode_error_event(
        err_type=long_str,
        message="测试",  # Chinese
        severity=1,
        handled=True,
        ts=1.5,
        attributes={"emoji": "😀", "long": long_str},
        stack_trace=None,
        file=None,
        line=None,
        column=None,
    ); result = codeflash_output # 30.3μs -> 29.7μs (2.05% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)
    attributes, offset = decode_map_str_str(result, offset, 10)

def test_edge_negative_and_large_numbers():
    # Negative and large numbers for line/column
    codeflash_output = _encode_error_event(
        err_type="Err",
        message="msg",
        severity=4,
        handled=False,
        ts=0.0,
        attributes=None,
        stack_trace=None,
        file=None,
        line=-1,
        column=2**31-1,
    ); result = codeflash_output # 20.5μs -> 20.3μs (0.644% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    value, offset = decode_int_field(result, offset, 5)
    value, offset = decode_int_field(result, offset, 6)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)

def test_edge_empty_attributes():
    # attributes is empty dict
    codeflash_output = _encode_error_event(
        err_type="E",
        message="M",
        severity=1,
        handled=True,
        ts=1.0,
        attributes={},
    ); result = codeflash_output # 14.5μs -> 12.7μs (14.2% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)

def test_edge_none_attributes():
    # attributes is None
    codeflash_output = _encode_error_event(
        err_type="E",
        message="M",
        severity=1,
        handled=True,
        ts=1.0,
        attributes=None,
    ); result = codeflash_output # 14.4μs -> 12.7μs (13.3% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)

def test_edge_zero_and_negative_severity():
    # severity zero and negative
    codeflash_output = _encode_error_event(
        err_type="E",
        message="M",
        severity=-5,
        handled=False,
        ts=2.0,
        attributes=None,
    ); result = codeflash_output # 17.7μs -> 17.2μs (2.81% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)

# --- Large Scale Test Cases ---

def test_large_attributes_map():
    # Large attributes dict
    large_attrs = {f"key{i}": f"value{i}" for i in range(500)}
    codeflash_output = _encode_error_event(
        err_type="LargeMap",
        message="Test",
        severity=1,
        handled=True,
        ts=12345678.0,
        attributes=large_attrs,
    ); result = codeflash_output # 1.45ms -> 1.15ms (25.7% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)
    attributes, offset = decode_map_str_str(result, offset, 10)

def test_large_long_strings():
    # Large strings for err_type, message, stack_trace
    big_string = "A" * 1000
    codeflash_output = _encode_error_event(
        err_type=big_string,
        message=big_string,
        severity=1,
        handled=True,
        ts=0.0,
        attributes=None,
        stack_trace=big_string,
    ); result = codeflash_output # 19.4μs -> 18.8μs (3.02% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    s, offset = decode_string_field(result, offset, 3)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)

def test_large_all_fields_maximum():
    # All fields, maximum values within reasonable limits
    attrs = {f"k{i}": f"v{i}" for i in range(100)}
    codeflash_output = _encode_error_event(
        err_type="E"*100,
        message="M"*200,
        severity=4,
        handled=True,
        ts=9999999999.999999999,
        attributes=attrs,
        stack_trace="S"*500,
        file="F"*50,
        line=2**31-1,
        column=2**31-1,
    ); result = codeflash_output # 309μs -> 248μs (24.7% faster)
    offset = 0
    s, offset = decode_string_field(result, offset, 1)
    s, offset = decode_string_field(result, offset, 2)
    s, offset = decode_string_field(result, offset, 3)
    s, offset = decode_string_field(result, offset, 4)
    value, offset = decode_int_field(result, offset, 5)
    value, offset = decode_int_field(result, offset, 6)
    sev, offset = decode_int_field(result, offset, 7)
    handled, offset = decode_bool_field(result, offset, 8)
    sec, nanos, offset = decode_timestamp_field(result, offset, 9)
    attributes, offset = decode_map_str_str(result, offset, 10)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import struct  # for decoding varints in binary
from typing import Dict

# imports
import pytest  # used for our unit tests
from src.deepgram.extensions.telemetry.proto_encoder import _encode_error_event

# --- Helper functions for decoding for test assertions ---

def decode_varint(data: bytes, offset: int = 0):
    """Decode a varint from data[offset:]. Returns (value, new_offset)."""
    shift = 0
    result = 0
    while True:
        if offset >= len(data):
            raise ValueError("Unexpected end of data")
        b = data[offset]
        result |= ((b & 0x7F) << shift)
        offset += 1
        if not (b & 0x80):
            break
        shift += 7
    return result, offset

def decode_key(data: bytes, offset: int = 0):
    """Decode a protobuf key (field_number, wire_type, new_offset)."""
    key, offset = decode_varint(data, offset)
    field_number = key >> 3
    wire_type = key & 0x7
    return field_number, wire_type, offset

def decode_len_delimited(data: bytes, offset: int = 0):
    """Decode a length-delimited field. Returns (field_number, payload, new_offset)."""
    field_number, wire_type, offset = decode_key(data, offset)
    length, offset = decode_varint(data, offset)
    payload = data[offset:offset+length]
    offset += length
    return field_number, payload, offset

def decode_bool(data: bytes, offset: int = 0):
    """Decode a boolean field. Returns (field_number, value, new_offset)."""
    field_number, wire_type, offset = decode_key(data, offset)
    value, offset = decode_varint(data, offset)
    return field_number, bool(value), offset

def decode_int(data: bytes, offset: int = 0):
    """Decode an int field. Returns (field_number, value, new_offset)."""
    field_number, wire_type, offset = decode_key(data, offset)
    value, offset = decode_varint(data, offset)
    return field_number, value, offset

def decode_string(data: bytes, offset: int = 0):
    """Decode a string field. Returns (field_number, value, new_offset)."""
    field_number, payload, offset = decode_len_delimited(data, offset)
    return field_number, payload.decode('utf-8'), offset

def decode_map_str_str(data: bytes, offset: int = 0):
    """Decode map<string,string> field. Returns (field_number, dict, new_offset)."""
    items = {}
    while offset < len(data):
        field_number, payload, offset = decode_len_delimited(data, offset)
        # decode entry: two strings
        entry_offset = 0
        fn1, key, entry_offset = decode_string(payload, entry_offset)
        fn2, value, entry_offset = decode_string(payload, entry_offset)
        items[key] = value
    return field_number, items, offset

def decode_timestamp_message(payload: bytes):
    """Decode a google.protobuf.Timestamp message."""
    offset = 0
    field_number, seconds, offset = decode_int(payload, offset)
    nanos = 0
    if offset < len(payload):
        field_number, nanos_val, offset = decode_int(payload, offset)
        nanos = nanos_val
    return seconds, nanos

# --- Unit tests ---

# 1. Basic Test Cases

def test_basic_minimal_required_fields():
    # Only required fields, no optionals, attributes=None
    codeflash_output = _encode_error_event(
        err_type="TypeError",
        message="Something went wrong",
        severity=3,
        handled=True,
        ts=1710000000.0,
        attributes=None,
    ); result = codeflash_output # 17.0μs -> 16.7μs (1.75% faster)
    offset = 0
    # err_type
    fn, val, offset = decode_string(result, offset)
    # message
    fn, val, offset = decode_string(result, offset)
    # severity
    fn, val, offset = decode_int(result, offset)
    # handled
    fn, val, offset = decode_bool(result, offset)
    # timestamp
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)

def test_basic_all_fields_present():
    # All fields present, attributes non-empty
    codeflash_output = _encode_error_event(
        err_type="ValueError",
        message="Invalid value",
        severity=2,
        handled=False,
        ts=1710000123.456,
        attributes={"foo": "bar", "baz": "qux"},
        stack_trace="Traceback (most recent call last): ...",
        file="main.py",
        line=42,
        column=7,
    ); result = codeflash_output # 30.1μs -> 28.9μs (4.32% faster)
    offset = 0
    # err_type
    fn, val, offset = decode_string(result, offset)
    # message
    fn, val, offset = decode_string(result, offset)
    # stack_trace
    fn, val, offset = decode_string(result, offset)
    # file
    fn, val, offset = decode_string(result, offset)
    # line
    fn, val, offset = decode_int(result, offset)
    # column
    fn, val, offset = decode_int(result, offset)
    # severity
    fn, val, offset = decode_int(result, offset)
    # handled
    fn, val, offset = decode_bool(result, offset)
    # timestamp
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)
    # attributes
    fn, items, offset = decode_map_str_str(result[offset:], 0)

def test_basic_empty_strings_and_zeroes():
    # Empty strings, zero severity, handled False, zero timestamp, empty attributes
    codeflash_output = _encode_error_event(
        err_type="",
        message="",
        severity=0,
        handled=False,
        ts=0.0,
        attributes={},
        stack_trace="",
        file="",
        line=0,
        column=0,
    ); result = codeflash_output # 13.4μs -> 11.9μs (12.5% faster)
    offset = 0
    # err_type and message skipped (empty)
    # stack_trace and file skipped (empty)
    # line
    fn, val, offset = decode_int(result, offset)
    # column
    fn, val, offset = decode_int(result, offset)
    # severity
    fn, val, offset = decode_int(result, offset)
    # handled
    fn, val, offset = decode_bool(result, offset)
    # timestamp
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)

# 2. Edge Test Cases

def test_edge_negative_line_and_column():
    # Negative line and column numbers should be encoded as unsigned varint
    codeflash_output = _encode_error_event(
        err_type="Error",
        message="msg",
        severity=1,
        handled=True,
        ts=1.0,
        attributes=None,
        line=-1,
        column=-123,
    ); result = codeflash_output # 21.7μs -> 21.2μs (2.19% faster)
    offset = 0
    # err_type
    fn, val, offset = decode_string(result, offset)
    # message
    fn, val, offset = decode_string(result, offset)
    # line
    fn, val, offset = decode_int(result, offset)
    # column
    fn, val, offset = decode_int(result, offset)
    # severity
    fn, val, offset = decode_int(result, offset)
    # handled
    fn, val, offset = decode_bool(result, offset)
    # timestamp
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)

def test_edge_large_severity_and_timestamp():
    # Large severity value, large timestamp (far future)
    codeflash_output = _encode_error_event(
        err_type="Overflow",
        message="Big severity",
        severity=2**31,
        handled=False,
        ts=9999999999.999999,
        attributes=None,
    ); result = codeflash_output # 19.7μs -> 19.7μs (0.395% slower)
    offset = 0
    # err_type
    fn, val, offset = decode_string(result, offset)
    # message
    fn, val, offset = decode_string(result, offset)
    # severity
    fn, val, offset = decode_int(result, offset)
    # handled
    fn, val, offset = decode_bool(result, offset)
    # timestamp
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)

def test_edge_attributes_none_and_empty():
    # attributes=None and attributes={} should both result in no map field
    codeflash_output = _encode_error_event(
        err_type="A",
        message="B",
        severity=1,
        handled=True,
        ts=1.0,
        attributes=None,
    ); result_none = codeflash_output # 14.2μs -> 12.7μs (12.2% faster)
    codeflash_output = _encode_error_event(
        err_type="A",
        message="B",
        severity=1,
        handled=True,
        ts=1.0,
        attributes={},
    ); result_empty = codeflash_output # 8.86μs -> 7.36μs (20.3% faster)
    # Both should lack field 10
    # We'll decode all fields and ensure no field 10
    def no_field_10(data):
        offset = 0
        while offset < len(data):
            field_number, wire_type, new_offset = decode_key(data, offset)
            if field_number == 10:
                return False
            if wire_type == 2:
                _, payload, offset = decode_len_delimited(data, offset)
            elif wire_type == 0:
                _, _, offset = decode_int(data, offset)
            else:
                raise AssertionError("Unexpected wire type")
        return True

def test_edge_utf8_strings():
    # Unicode/UTF-8 strings in err_type, message, stack_trace, file, attributes
    codeflash_output = _encode_error_event(
        err_type="Ошибка",
        message="Ошибка: значение неверно",
        severity=4,
        handled=False,
        ts=100.5,
        attributes={"ключ": "значение", "emoji": "😀"},
        stack_trace="Трассировка (последний вызов): ...",
        file="файл.py",
        line=1,
        column=2,
    ); result = codeflash_output # 29.5μs -> 27.8μs (6.18% faster)
    offset = 0
    fn, val, offset = decode_string(result, offset)
    fn, val, offset = decode_string(result, offset)
    fn, val, offset = decode_string(result, offset)
    fn, val, offset = decode_string(result, offset)
    fn, val, offset = decode_int(result, offset)
    fn, val, offset = decode_int(result, offset)
    fn, val, offset = decode_int(result, offset)
    fn, val, offset = decode_bool(result, offset)
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)
    fn, items, offset = decode_map_str_str(result[offset:], 0)

def test_edge_stack_trace_none_and_empty():
    # stack_trace=None (should not be present), stack_trace="" (should not be present)
    codeflash_output = _encode_error_event(
        err_type="err",
        message="msg",
        severity=1,
        handled=True,
        ts=1.0,
        attributes=None,
        stack_trace=None,
    ); result_none = codeflash_output # 14.3μs -> 12.7μs (12.7% faster)
    codeflash_output = _encode_error_event(
        err_type="err",
        message="msg",
        severity=1,
        handled=True,
        ts=1.0,
        attributes=None,
        stack_trace="",
    ); result_empty = codeflash_output # 8.48μs -> 7.11μs (19.4% faster)
    # Both should lack field 3
    def no_field_3(data):
        offset = 0
        while offset < len(data):
            field_number, wire_type, new_offset = decode_key(data, offset)
            if field_number == 3:
                return False
            if wire_type == 2:
                _, payload, offset = decode_len_delimited(data, offset)
            elif wire_type == 0:
                _, _, offset = decode_int(data, offset)
            else:
                raise AssertionError("Unexpected wire type")
        return True

def test_edge_timestamp_rounding_and_overflow():
    # Test nanos rounding and overflow (should increment seconds)
    ts = 123.9999999995  # nanos > 1_000_000_000
    codeflash_output = _encode_error_event(
        err_type="err",
        message="msg",
        severity=1,
        handled=True,
        ts=ts,
        attributes=None,
    ); result = codeflash_output # 14.6μs -> 12.8μs (14.0% faster)
    offset = 0
    # Skip err_type & message
    fn, _, offset = decode_string(result, offset)
    fn, _, offset = decode_string(result, offset)
    # severity
    fn, _, offset = decode_int(result, offset)
    # handled
    fn, _, offset = decode_bool(result, offset)
    # timestamp
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)

# 3. Large Scale Test Cases

def test_large_scale_attributes_map():
    # Large attributes map (500 entries)
    attributes = {f"key{i}": f"value{i}" for i in range(500)}
    codeflash_output = _encode_error_event(
        err_type="LargeMap",
        message="Many attributes",
        severity=2,
        handled=True,
        ts=42.42,
        attributes=attributes,
    ); result = codeflash_output # 1.46ms -> 1.15ms (27.2% faster)
    offset = 0
    # err_type
    fn, val, offset = decode_string(result, offset)
    # message
    fn, val, offset = decode_string(result, offset)
    # severity
    fn, val, offset = decode_int(result, offset)
    # handled
    fn, val, offset = decode_bool(result, offset)
    # timestamp
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)
    # attributes
    fn, items, offset2 = decode_map_str_str(result[offset:], 0)
    for i in range(500):
        pass

def test_large_scale_long_strings():
    # Large strings for err_type, message, stack_trace, file
    big_str = "A" * 1000
    codeflash_output = _encode_error_event(
        err_type=big_str,
        message=big_str,
        severity=3,
        handled=False,
        ts=123456789.123456,
        attributes={"big": big_str},
        stack_trace=big_str,
        file=big_str,
        line=123456,
        column=654321,
    ); result = codeflash_output # 31.6μs -> 31.1μs (1.59% faster)
    offset = 0
    for fn_expected in [1, 2, 3, 4]:
        fn, val, offset = decode_string(result, offset)
    fn, val, offset = decode_int(result, offset)
    fn, val, offset = decode_int(result, offset)
    fn, val, offset = decode_int(result, offset)
    fn, val, offset = decode_bool(result, offset)
    fn, payload, offset = decode_len_delimited(result, offset)
    sec, nanos = decode_timestamp_message(payload)
    # attributes
    fn, items, offset2 = decode_map_str_str(result[offset:], 0)

def test_large_scale_many_events():
    # Encode 1000 events, ensure all are unique and correct
    for i in range(1000):
        codeflash_output = _encode_error_event(
            err_type=f"Type{i}",
            message=f"Msg{i}",
            severity=i % 5,
            handled=(i % 2 == 0),
            ts=i * 1.5,
            attributes={"k": f"v{i}"},
            line=i,
            column=i+1,
        ); result = codeflash_output # 13.3ms -> 11.1ms (19.5% faster)
        offset = 0
        fn, val, offset = decode_string(result, offset)
        fn, val, offset = decode_string(result, offset)
        fn, val, offset = decode_int(result, offset)
        fn, val, offset = decode_int(result, offset)
        fn, val, offset = decode_int(result, offset)
        fn, val, offset = decode_bool(result, offset)
        fn, payload, offset = decode_len_delimited(result, offset)
        sec, nanos = decode_timestamp_message(payload)
        fn, items, offset2 = decode_map_str_str(result[offset:], 0)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from src.deepgram.extensions.telemetry.proto_encoder import _encode_error_event

def test__encode_error_event():
    _encode_error_event(err_type='\x00', message='\x00', severity=0, handled=True, ts=0.0, attributes={'\U00040000\x00': ''}, stack_trace=None, file='\U00040000', line=0, column=128)

def test__encode_error_event_2():
    _encode_error_event(err_type='', message='', severity=0, handled=False, ts=0.0, attributes={}, stack_trace='𐀀𐀀𐀀', file='', line=None, column=0)

🔎 Concolic Coverage Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
`codeflash_concolic_5p92pe1r/tmpd0ni74mh/test_concolic_coverage.py::test__encode_error_event`	22.9μs	21.8μs	4.85%✅
`codeflash_concolic_5p92pe1r/tmpd0ni74mh/test_concolic_coverage.py::test__encode_error_event_2`	14.3μs	12.7μs	13.0%✅

To edit these changes git checkout codeflash/optimize-_encode_error_event-mgupjlsp and push.

Impact: high Impact_explanation: Looking at this optimization report, I need to assess the impact based on the provided rubric and data. **Analysis of Runtime Performance:** - Overall runtime: 17.0ms → 14.1ms (20.31% speedup) - This exceeds the 100 microsecond threshold significantly, indicating substantial work - The 20% speedup exceeds the 15% threshold for high impact **Analysis of Generated Test Results:** - Small/basic tests: 2-14% faster (mostly above 5%) - Large attribute maps (500 entries): 25-27% faster - this is excellent - Bulk operations (1000 events): 19% faster - very good - Empty/minimal data: 12-20% faster - good across the board The test results show consistent improvements across all test cases, with particularly strong performance on larger workloads (25-27% for large maps, 19% for bulk operations). **Analysis of Hot Path Usage:** The `calling_fn_details` shows `_encode_error_event` is called in a loop within `_normalize_events()` for multiple event types: - `http_error` events - `ws_error` events - `uncaught_error` events - `error_event` events This means the optimization effect is multiplicative - each improvement gets applied many times in typical telemetry workloads. **Key Optimization Quality:** The optimizations are well-designed: - Fast path for small varints (common case optimization) - Elimination of intermediate allocations via `b"".join()` - Localized attribute lookups in tight loops - Pre-allocated lists for better memory efficiency These target fundamental performance bottlenecks in Python bytecode and memory allocation. **Assessment:** - Runtime exceeds 100μs threshold ✓ - Speedup exceeds 15% threshold ✓ - Function is in hot path (called in loops) ✓ - Consistent improvements across all test cases ✓ - Large workload improvements are substantial (25-27%) ✓ END OF IMPACT EXPLANATION The optimization achieves a 20% speedup through several key improvements targeting Python's bytecode efficiency and memory allocation patterns: **Key Optimizations:** 1. **Fast path for small varints**: Added an early return `if value <= 0x7F: return bytes([value])` in `_varint()`, avoiding loop overhead for small values (common in protobuf encoding). 2. **Localized attribute lookups**: In tight loops, cached method references like `append = out.append` to avoid repeated attribute resolution overhead. 3. **Eliminated intermediate concatenations**: Replaced multiple `+` operations with `b"".join()` in functions like `_len_delimited()`, `_string()`, and `_timestamp_message()`. This avoids creating temporary byte objects that get immediately discarded. 4. **Pre-allocated lists for joins**: Changed from progressive `bytearray` concatenation to collecting parts in lists, then joining once. This is more efficient because `b"".join(list)` pre-allocates the final buffer size. 5. **Direct byte literals**: Replaced `_varint(1 if value else 0)` with `b'\x01' if value else b'\x00'` in `_bool()`, eliminating function call overhead for this common case. **Performance Impact by Test Type:** - **Small/simple events** (basic tests): 2-14% faster due to fast-path varints and reduced allocations - **Large attribute maps** (500 entries): 25-27% faster due to pre-allocated lists and localized lookups - **Bulk operations** (1000 events): 19% faster from cumulative micro-optimizations - **Empty/minimal data**: 12-20% faster from avoiding unnecessary work The optimizations are particularly effective for telemetry use cases with many small integer fields and moderate-sized attribute maps, which are common in error event encoding.

codeflash-ai bot requested a review from aseembits93 October 17, 2025 10:30

codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Oct 17, 2025

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⚡️ Speed up function `_encode_error_event` by 20%#26

⚡️ Speed up function `_encode_error_event` by 20%#26
codeflash-ai[bot] wants to merge 1 commit intomainfrom
codeflash/optimize-_encode_error_event-mgupjlsp

codeflash-ai bot commented Oct 17, 2025

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codeflash-ai bot commented Oct 17, 2025

📄 20% (0.20x) speedup for _encode_error_event in src/deepgram/extensions/telemetry/proto_encoder.py

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📄 20% (0.20x) speedup for `_encode_error_event` in `src/deepgram/extensions/telemetry/proto_encoder.py`