Sort Stats
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Sort Stats has 28 facts recorded in Dontopedia across 13 references, with 5 live disagreements.
Mostly:has argument(4), called on(2), returns(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedHas Argumentin disputehasArgument
- 'cumulative'[8]all time · 20342d06 A832 4fa0 8eda 34243774ac2e
- Cumulative[4]sourceall time · B9406b81 4fc1 45b7 Ad2a Ee6dd1ca1b51
- cumulative[9]sourceall time · 1649add7 5446 4cf1 9934 90116d9362c7
- cumulative[10]sourceall time · 7b17d450 1e6b 4a8d Aeee B2acb55eb0f2
Called onin disputecalledOn
- Ps[5]sourceall time · 5e9afeda 9bb9 4fc2 B6c2 8be60e02ac6e
- Stats Object[6]all time · Aedb6d8a 8822 4467 A7a5 Cfff18551c49
Returnsin disputereturns
- Stats Object[6]all time · Aedb6d8a 8822 4467 A7a5 Cfff18551c49
- Stats Object[3]all time · C4d9d47f 41fb 4e74 Bbca E6bdc41cabac
Has Parameterin disputehasParameter
- Cumtime[11]all time · A3257e5e B867 40a8 A44a 3456d9c9c0b8
- Cumulative[8]all time · 20342d06 A832 4fa0 8eda 34243774ac2e
Rdf:typein disputerdf:type
- Method[4]sourceall time · B9406b81 4fc1 45b7 Ad2a Ee6dd1ca1b51
- Python Method[8]all time · 20342d06 A832 4fa0 8eda 34243774ac2e
Accepts ParameteracceptsParameter
Parameterparameter
- cumtime[6]sourceall time · Aedb6d8a 8822 4467 A7a5 Cfff18551c49
Argumentargument
- cumtime[3]all time · C4d9d47f 41fb 4e74 Bbca E6bdc41cabac
Sorts bysortsBy
Accepts ArgumentacceptsArgument
Method ParametermethodParameter
- cumtime[7]sourceall time · 9fcfc92c 57a9 467e 86b3 63dd7ea33dbe
Used forusedFor
- Data Sorting[7]all time · 9fcfc92c 57a9 467e 86b3 63dd7ea33dbe
Inbound mentions (12)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
hasMethodHas Method(4)
- Pstats.stats
ex:pstats.Stats - Stats
ex:stats - Stats Object
ex:Stats-object - Stats
Stats
callsMethodCalls Method(3)
- Profile Function
ex:profile_function - Stats
ex:stats - Stats Object
ex:stats_object
callsCalls(1)
- Profile Function
ex:profile_function
hasMethodCallHas Method Call(1)
- Ps
ex:ps
isSortingCriterionOfIs Sorting Criterion of(1)
- Cumtime
ex:cumtime
methodMethod(1)
- Stats
ex:Stats
methodCallMethod Call(1)
- Stats
ex:stats
Other facts (9)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Method of | Stats | [7] |
| Description | Sort profiling statistics by criterion | [7] |
| Called With | cumtime | [7] |
| Takes Argument | Cumulative | [12] |
| Produces | Sorted Stats | [4] |
| Uses Sorting Criterion | Cumulative | [4] |
| Called by | Stats | [4] |
| Rdfs:label | sort_stats | [8] |
| Uses Parameter | Sortby | [13] |
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (13)
- custom
ctx:claims/beam/51125ee6-b618-48ae-8493-828d91a10410 - custom
ctx:claims/beam/bb0c421a-abf6-4f60-a2a9-6428edaf8c0a- full textbeam-chunktext/plain1 KB
doc:beam/bb0c421a-abf6-4f60-a2a9-6428edaf8c0aShow excerpt
def tokenize_text(text): normalized_text = normalize_unicode(text) doc = nlp(normalized_text) return [token.text for token in doc] # Profile the tokenization process def profile_tokenization(texts): profiler = cProfile.Prof…
- custom
ctx:claims/beam/c4d9d47f-41fb-4e74-bbca-e6bdc41cabac - custom
ctx:claims/beam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51- full textbeam-chunktext/plain1 KB
doc:beam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51Show excerpt
[Turn 7217] Assistant: Great job on improving the API throughput by 10% for 25,000 queries! To further refine your endpoints and achieve better performance, you can consider several additional strategies. Here are some steps you can take: …
- custom
ctx:claims/beam/5e9afeda-9bb9-4fc2-b6c2-8be60e02ac6e- full textbeam-chunktext/plain1 KB
doc:beam/5e9afeda-9bb9-4fc2-b6c2-8be60e02ac6eShow excerpt
def profile_function(func, *args, **kwargs): pr = cProfile.Profile() pr.enable() result = func(*args, **kwargs) pr.disable() s = io.StringIO() ps = Stats(pr, stream=s).sort_stats('cumtime') ps.print_stats() p…
- custom
ctx:claims/beam/aedb6d8a-8822-4467-a7a5-cfff18551c49- full textbeam-chunktext/plain1 KB
doc:beam/aedb6d8a-8822-4467-a7a5-cfff18551c49Show excerpt
Test the reformulation function with a subset of your queries to identify and fix specific issues. Gradually increase the test set size until you are confident in the performance. ```python import pandas as pd # Load the query data querie…
- custom
ctx:claims/beam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbe- full textbeam-chunktext/plain1 KB
doc:beam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbeShow excerpt
inputs = tokenizer(query, return_tensors="pt") # Get the reformulated query start_time = time.time() outputs = model.generate(**inputs) end_time = time.time() # Return the reformulated query return toke…
- custom
ctx:claims/beam/20342d06-a832-4fa0-8eda-34243774ac2e - custom
ctx:claims/beam/1649add7-5446-4cf1-9934-90116d9362c7- full textbeam-chunktext/plain1 KB
doc:beam/1649add7-5446-4cf1-9934-90116d9362c7Show excerpt
[Turn 3240] User: Sure, let's start with profiling the code to identify bottlenecks. I'll add the `cProfile` part to my script and run it to see where the time is being spent. Once I have that info, I can focus on optimizing those parts. So…
- custom
ctx:claims/beam/7b17d450-1e6b-4a8d-aeee-b2acb55eb0f2- full textbeam-chunktext/plain1 KB
doc:beam/7b17d450-1e6b-4a8d-aeee-b2acb55eb0f2Show excerpt
def profile_function(func, *args, **kwargs): profiler = cProfile.Profile() result = profiler.runcall(func, *args, **kwargs) stats = pstats.Stats(profiler) stats.sort_stats('cumulative').print_stats(2…
- custom
ctx:claims/beam/a3257e5e-b867-40a8-a44a-3456d9c9c0b8- full textbeam-chunktext/plain1 KB
doc:beam/a3257e5e-b867-40a8-a44a-3456d9c9c0b8Show excerpt
reformulated_query, latency = reformulate_query(query) pr.disable() s = io.StringIO() ps = pstats.Stats(pr, stream=s).sort_stats('cumtime') ps.print_stats() print(s.getvalue()) print(reformulated_query, latency) ``` ### Explanation 1. *…
- custom
ctx:claims/beam/5825331f-9249-40f8-9c37-fa519c74bcc1- full textbeam-chunktext/plain1 KB
doc:beam/5825331f-9249-40f8-9c37-fa519c74bcc1Show excerpt
result = profiler.runcall(func, *args, **kwargs) stats = pstats.Stats(profiler) stats.strip_dirs().sort_stats('cumulative').print_stats(10) return result test_id = 123 profile_function(get_test_results, te…
- custom
ctx:claims/beam/bd01edbd-14a6-4066-9451-f8bdb9efdc3d- full textbeam-chunktext/plain1 KB
doc:beam/bd01edbd-14a6-4066-9451-f8bdb9efdc3dShow excerpt
pr.disable() s = io.StringIO() sortby = 'cumulative' ps = pstats.Stats(pr, stream=s).sort_stats(sortby) ps.print_stats() print(s.getvalue()) return result # Example function to profile def example_function(): …
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