⚡ Optimize CADC client capability status checks with concurrent execution#158
⚡ Optimize CADC client capability status checks with concurrent execution#158tjzegmott wants to merge 1 commit into
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…oncurrently This replaces a sequential for-loop of HTTP GET requests with a ThreadPoolExecutor mapping over the URLs in `dtcli/utilities/cadcclient.py`. Co-authored-by: tjzegmott <20817254+tjzegmott@users.noreply.github.com>
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Pull request overview
This PR optimizes CANFAR service status checks by running the Minoc and Luskan /capabilities requests concurrently instead of sequentially, reducing latency for independent network calls.
Changes:
- Adds
ThreadPoolExecutorusage incadcclient.status(). - Extracts per-URL status logic into a nested
check_url()helper. - Preserves the existing
(minoc_status, luskan_status)return order.
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #158 +/- ##
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- Coverage 65.68% 65.57% -0.12%
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Files 15 15
Lines 1399 1400 +1
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- Hits 919 918 -1
- Misses 480 482 +2 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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💡 What: The optimization implemented
Replaced the sequential loop checking MINOC and Luskan capabilities in
dtcli/utilities/cadcclient.py::status()with aconcurrent.futures.ThreadPoolExecutor. A helper function processes the HTTP request and handles exceptions concurrently.🎯 Why: The performance problem it solves
The original code looped over an array of 2 URLs, executing an independent HTTP GET request synchronously for each iteration. In scenarios with any sort of network latency, these blocking operations compound. Running the requests in parallel mitigates the cumulative latency overhead of independent network calls, reducing the function execution time.
📊 Measured Improvement:
Using an injected
1.0ssleep mock representing network latency in a benchmark script simulatingstatus():max(t_1, t_2)rather thant_1 + t_2).PR created automatically by Jules for task 13064934752270288918 started by @tjzegmott