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@codeflash-ai codeflash-ai bot commented Nov 9, 2025

📄 18% (0.18x) speedup for JiraDataSource.delete_issue_type_property in backend/python/app/sources/external/jira/jira.py

⏱️ Runtime : 2.42 milliseconds 2.05 milliseconds (best of 40 runs)

📝 Explanation and details

The optimized code achieves a 17% runtime improvement through strategic reduction of dictionary operations and type checking overhead:

Key Optimizations:

  1. Smart Header Processing: Instead of always calling dict(headers or {}), the code now checks if headers are None (common case) or already a Dict[str, str] and avoids unnecessary conversion. This eliminates redundant dict allocations for the majority of calls.

  2. Optimized String Dictionary Conversion: The new _fast_as_str_dict() function checks if a dictionary is already Dict[str, str] before performing expensive string conversions. Since _path parameters are typically already strings, this avoids the costly _serialize_value() calls seen in the profiler.

  3. Query Parameter Bypass: Since _query is always empty in this method, the optimization directly passes an empty dict {} instead of processing it through _fast_as_str_dict(), eliminating unnecessary function calls.

  4. HTTP Client Path Optimization: The HTTPClient now avoids string formatting when path_params is empty and optimizes header merging by checking if request headers are empty before creating a new merged dictionary.

Performance Impact:
The line profiler shows significant reductions in time spent on dictionary operations - _as_str_dict() calls dropped from 2.94ms total time in the original to much faster _fast_as_str_dict() calls. The optimization is particularly effective for typical API calls with string parameters and minimal headers.

Test Case Performance:
The optimizations excel in high-throughput scenarios (100-200 concurrent calls) and basic use cases with simple string parameters, making this ideal for bulk API operations common in JIRA integrations.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 642 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 90.9%
🌀 Generated Regression Tests and Runtime

import asyncio

import pytest
from app.sources.external.jira.jira import JiraDataSource

---- Minimal stubs for HTTPRequest, HTTPResponse, and JiraClient ----

class HTTPRequest:
def init(self, method, url, headers, path_params, query_params, body):
self.method = method
self.url = url
self.headers = headers
self.path_params = path_params
self.query_params = query_params
self.body = body

class HTTPResponse:
def init(self, status_code, content=None):
self.status_code = status_code
self.content = content

Minimal stub for HTTP client used by JiraDataSource

class DummyAsyncHTTPClient:
def init(self, base_url, should_raise=False, delay=0):
self._base_url = base_url
self.should_raise = should_raise
self.delay = delay
self.executed_requests = []

def get_base_url(self):
    return self._base_url

async def execute(self, req):
    self.executed_requests.append(req)
    if self.should_raise:
        raise RuntimeError("Simulated client error")
    if self.delay > 0:
        await asyncio.sleep(self.delay)
    # Simulate a successful HTTP DELETE with 204 No Content
    return HTTPResponse(status_code=204, content=None)

Minimal JiraClient wrapper

class JiraClient:
def init(self, client):
self.client = client
def get_client(self):
return self.client
from app.sources.external.jira.jira import JiraDataSource

---- TESTS ----

1. BASIC TEST CASES

@pytest.mark.asyncio
async def test_delete_issue_type_property_basic_success():
"""Test basic successful async delete with normal parameters."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
resp = await ds.delete_issue_type_property("10001", "customKey")
# The request should have correct URL and method
req = dummy_client.executed_requests[0]

@pytest.mark.asyncio
async def test_delete_issue_type_property_with_headers():
"""Test passing custom headers and ensure they are set correctly."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
headers = {"X-Test-Header": "Value"}
await ds.delete_issue_type_property("10001", "customKey", headers=headers)
req = dummy_client.executed_requests[0]

@pytest.mark.asyncio
async def test_delete_issue_type_property_empty_headers():
"""Test that passing headers=None works and does not raise."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
resp = await ds.delete_issue_type_property("10001", "customKey", headers=None)

@pytest.mark.asyncio
async def test_delete_issue_type_property_url_formatting():
"""Test that URL is formatted safely even with special characters."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
resp = await ds.delete_issue_type_property("ID-!@#", "prop/with/slash")
req = dummy_client.executed_requests[0]

2. EDGE TEST CASES

@pytest.mark.asyncio
async def test_delete_issue_type_property_client_not_initialized():
"""Test that ValueError is raised if the HTTP client is None."""
class NoneClient:
def get_client(self):
return None
with pytest.raises(ValueError, match="HTTP client is not initialized"):
JiraDataSource(NoneClient())

@pytest.mark.asyncio
async def test_delete_issue_type_property_client_missing_base_url():
"""Test that ValueError is raised if get_base_url is missing."""
class BadClient:
def get_client(self):
class NoBaseUrl:
pass
return NoBaseUrl()
with pytest.raises(ValueError, match="HTTP client does not have get_base_url method"):
JiraDataSource(BadClient())

@pytest.mark.asyncio
async def test_delete_issue_type_property_execute_raises():
"""Test that exceptions from client.execute are propagated."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com", should_raise=True)
ds = JiraDataSource(JiraClient(dummy_client))
with pytest.raises(RuntimeError, match="Simulated client error"):
await ds.delete_issue_type_property("10001", "customKey")

@pytest.mark.asyncio

async def test_delete_issue_type_property_special_characters():
"""Test special characters in issueTypeId and propertyKey."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
issue_type_id = "特殊字符"
property_key = "ключ"
resp = await ds.delete_issue_type_property(issue_type_id, property_key)
req = dummy_client.executed_requests[0]

3. LARGE SCALE TEST CASES

@pytest.mark.asyncio

async def test_delete_issue_type_property_long_strings():
"""Test with very long issueTypeId and propertyKey."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
long_id = "A" * 200
long_key = "B" * 200
resp = await ds.delete_issue_type_property(long_id, long_key)
req = dummy_client.executed_requests[0]

4. THROUGHPUT TEST CASES

@pytest.mark.asyncio
async def test_delete_issue_type_property_throughput_small_load():
"""Throughput test: 10 concurrent calls, should all succeed quickly."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
tasks = [
ds.delete_issue_type_property("10001", f"key{i}")
for i in range(10)
]
results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_delete_issue_type_property_throughput_medium_load():
"""Throughput test: 100 concurrent calls."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
tasks = [
ds.delete_issue_type_property("10001", f"key{i}")
for i in range(100)
]
results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_delete_issue_type_property_throughput_sustained_pattern():
"""Throughput test: 10 rounds of 10 concurrent calls (sustained execution)."""
dummy_client = DummyAsyncHTTPClient(base_url="https://jira.example.com")
ds = JiraDataSource(JiraClient(dummy_client))
for round in range(10):
tasks = [
ds.delete_issue_type_property("10001", f"key{round}_{i}")
for i in range(10)
]
results = await asyncio.gather(*tasks)

codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

#------------------------------------------------
import asyncio
from typing import Any, Dict, Optional

import pytest
from app.sources.external.jira.jira import JiraDataSource

---- Minimal stubs for dependencies to allow testing ----

class HTTPRequest:
def init(self, method, url, headers, path_params, query_params, body):
self.method = method
self.url = url
self.headers = headers
self.path_params = path_params
self.query_params = query_params
self.body = body

class HTTPResponse:
def init(self, status_code: int, content: Any = None, headers: Optional[Dict[str, Any]] = None):
self.status_code = status_code
self.content = content
self.headers = headers or {}

class FakeHTTPClient:
"""A fake async HTTP client for unit testing."""
def init(self, base_url="https://jira.example.com", should_raise=False, response_status=204, response_content=None):
self._base_url = base_url
self.should_raise = should_raise
self.response_status = response_status
self.response_content = response_content

def get_base_url(self):
    return self._base_url

async def execute(self, request: HTTPRequest):
    # Simulate error if requested
    if self.should_raise:
        raise RuntimeError("Simulated client error")
    # Simulate a successful HTTPResponse
    return HTTPResponse(
        status_code=self.response_status,
        content=self.response_content,
        headers={"X-Fake": "yes"}
    )

class JiraClient:
"""Fake JiraClient for testing."""
def init(self, client):
self.client = client

def get_client(self):
    return self.client

from app.sources.external.jira.jira import JiraDataSource

---- TESTS ----

1. BASIC TEST CASES

@pytest.mark.asyncio
async def test_delete_issue_type_property_basic_success():
"""Test basic successful async call returns expected HTTPResponse."""
client = FakeHTTPClient()
jira_client = JiraClient(client)
ds = JiraDataSource(jira_client)
resp = await ds.delete_issue_type_property("123", "mykey")

@pytest.mark.asyncio
async def test_delete_issue_type_property_custom_headers():
"""Test passing custom headers are included in the HTTPRequest."""
class HeaderCheckClient(FakeHTTPClient):
async def execute(self, request: HTTPRequest):
return await super().execute(request)
client = HeaderCheckClient()
ds = JiraDataSource(JiraClient(client))
resp = await ds.delete_issue_type_property("321", "customkey", headers={"X-Test": "abc"})

@pytest.mark.asyncio
async def test_delete_issue_type_property_returns_content():
"""Test that response content is returned as expected."""
client = FakeHTTPClient(response_status=200, response_content={"deleted": True})
ds = JiraDataSource(JiraClient(client))
resp = await ds.delete_issue_type_property("555", "prop")

2. EDGE TEST CASES

@pytest.mark.asyncio
async def test_delete_issue_type_property_invalid_client_raises():
"""Test that ValueError is raised if JiraClient returns None client."""
class NullJiraClient:
def get_client(self):
return None
with pytest.raises(ValueError, match="HTTP client is not initialized"):
JiraDataSource(NullJiraClient())

@pytest.mark.asyncio
async def test_delete_issue_type_property_client_missing_base_url():
"""Test that ValueError is raised if client has no get_base_url method."""
class NoBaseUrlClient:
pass
class Wrapper:
def get_client(self):
return NoBaseUrlClient()
with pytest.raises(ValueError, match="does not have get_base_url method"):
JiraDataSource(Wrapper())

@pytest.mark.asyncio
async def test_delete_issue_type_property_execute_raises():
"""Test that exceptions in execute are propagated."""
client = FakeHTTPClient(should_raise=True)
ds = JiraDataSource(JiraClient(client))
with pytest.raises(RuntimeError, match="Simulated client error"):
await ds.delete_issue_type_property("x", "y")

@pytest.mark.asyncio

async def test_delete_issue_type_property_url_formatting():
"""Test that the URL is formatted correctly with path params."""
class URLCheckClient(FakeHTTPClient):
async def execute(self, request: HTTPRequest):
return await super().execute(request)
client = URLCheckClient()
ds = JiraDataSource(JiraClient(client))
resp = await ds.delete_issue_type_property("ISSUE-42", "my.property")

@pytest.mark.asyncio
async def test_delete_issue_type_property_empty_headers_and_params():
"""Test with empty strings and no headers."""
client = FakeHTTPClient()
ds = JiraDataSource(JiraClient(client))
resp = await ds.delete_issue_type_property("", "")

3. LARGE SCALE TEST CASES

@pytest.mark.asyncio

async def test_delete_issue_type_property_throughput_small_load():
"""Throughput: Test 10 concurrent calls complete successfully."""
client = FakeHTTPClient()
ds = JiraDataSource(JiraClient(client))
tasks = [
ds.delete_issue_type_property(f"small{i}", f"prop{i}")
for i in range(10)
]
results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_delete_issue_type_property_throughput_medium_load():
"""Throughput: Test 100 concurrent calls."""
client = FakeHTTPClient()
ds = JiraDataSource(JiraClient(client))
tasks = [
ds.delete_issue_type_property(f"mid{i}", f"prop{i}")
for i in range(100)
]
results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_delete_issue_type_property_throughput_varied_headers():
"""Throughput: Test 30 concurrent calls with unique headers."""
client = FakeHTTPClient()
ds = JiraDataSource(JiraClient(client))
tasks = [
ds.delete_issue_type_property(
f"hid{i}", f"key{i}", headers={"X-Req": str(i)}
)
for i in range(30)
]
results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_delete_issue_type_property_throughput_high_volume():
"""Throughput: Test 200 concurrent calls for high load (under 1000)."""
client = FakeHTTPClient()
ds = JiraDataSource(JiraClient(client))
tasks = [
ds.delete_issue_type_property(f"bulk{i}", f"prop{i}")
for i in range(200)
]
results = await asyncio.gather(*tasks)

codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-JiraDataSource.delete_issue_type_property-mhs3dz4y and push.

Codeflash Static Badge

The optimized code achieves a **17% runtime improvement** through strategic reduction of dictionary operations and type checking overhead:

**Key Optimizations:**

1. **Smart Header Processing**: Instead of always calling `dict(headers or {})`, the code now checks if headers are `None` (common case) or already a `Dict[str, str]` and avoids unnecessary conversion. This eliminates redundant dict allocations for the majority of calls.

2. **Optimized String Dictionary Conversion**: The new `_fast_as_str_dict()` function checks if a dictionary is already `Dict[str, str]` before performing expensive string conversions. Since `_path` parameters are typically already strings, this avoids the costly `_serialize_value()` calls seen in the profiler.

3. **Query Parameter Bypass**: Since `_query` is always empty in this method, the optimization directly passes an empty dict `{}` instead of processing it through `_fast_as_str_dict()`, eliminating unnecessary function calls.

4. **HTTP Client Path Optimization**: The HTTPClient now avoids string formatting when `path_params` is empty and optimizes header merging by checking if request headers are empty before creating a new merged dictionary.

**Performance Impact**: 
The line profiler shows significant reductions in time spent on dictionary operations - `_as_str_dict()` calls dropped from 2.94ms total time in the original to much faster `_fast_as_str_dict()` calls. The optimization is particularly effective for typical API calls with string parameters and minimal headers.

**Test Case Performance**: 
The optimizations excel in high-throughput scenarios (100-200 concurrent calls) and basic use cases with simple string parameters, making this ideal for bulk API operations common in JIRA integrations.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 November 9, 2025 19:14
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: Medium Optimization Quality according to Codeflash labels Nov 9, 2025
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