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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.

28 facts·21 predicates·13 sources·5 in dispute

Mostly:has argument(4), called on(2), returns(2)

Maturity scale raw canonical shape-checked rule-derived certified

Has 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

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

  • Sort Key[2]sourceall time · Bb0c421a Abf6 4f60 A2a9 6428edaf8c0a

Parameterparameter

  • cumtime[6]sourceall time · Aedb6d8a 8822 4467 A7a5 Cfff18551c49

Argumentargument

  • cumtime[3]all time · C4d9d47f 41fb 4e74 Bbca E6bdc41cabac

Sorts bysortsBy

  • Cumtime[5]sourceall time · 5e9afeda 9bb9 4fc2 B6c2 8be60e02ac6e

Accepts ArgumentacceptsArgument

  • Cumtime[1]all time · 51125ee6 B618 48ae 8493 828d91a10410

Method ParametermethodParameter

  • cumtime[7]sourceall time · 9fcfc92c 57a9 467e 86b3 63dd7ea33dbe

Used forusedFor

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)

callsMethodCalls Method(3)

callsCalls(1)

hasMethodCallHas Method Call(1)

isSortingCriterionOfIs Sorting Criterion of(1)

methodMethod(1)

methodCallMethod Call(1)

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.

9 facts
PredicateValueRef
Method ofStats[7]
DescriptionSort profiling statistics by criterion[7]
Called Withcumtime[7]
Takes ArgumentCumulative[12]
ProducesSorted Stats[4]
Uses Sorting CriterionCumulative[4]
Called byStats[4]
Rdfs:labelsort_stats[8]
Uses ParameterSortby[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.

acceptsArgumentbeam/51125ee6-b618-48ae-8493-828d91a10410
ex:cumtime
acceptsParameterbeam/bb0c421a-abf6-4f60-a2a9-6428edaf8c0a
ex:sort-key
argumentbeam/c4d9d47f-41fb-4e74-bbca-e6bdc41cabac
cumtime
calledBybeam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51
ex:stats
calledOnbeam/5e9afeda-9bb9-4fc2-b6c2-8be60e02ac6e
ex:ps
calledOnbeam/aedb6d8a-8822-4467-a7a5-cfff18551c49
ex:Stats-object
calledWithbeam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbe
cumtime
descriptionbeam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbe
Sort profiling statistics by criterion
hasArgumentbeam/20342d06-a832-4fa0-8eda-34243774ac2e
ex:'cumulative'
hasArgumentbeam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51
ex:cumulative
hasArgumentbeam/1649add7-5446-4cf1-9934-90116d9362c7
cumulative
hasArgumentbeam/7b17d450-1e6b-4a8d-aeee-b2acb55eb0f2
cumulative
hasParameterbeam/a3257e5e-b867-40a8-a44a-3456d9c9c0b8
ex:cumtime
hasParameterbeam/20342d06-a832-4fa0-8eda-34243774ac2e
ex:cumulative
methodOfbeam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbe
ex:Stats
methodParameterbeam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbe
cumtime
parameterbeam/aedb6d8a-8822-4467-a7a5-cfff18551c49
cumtime
producesbeam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51
ex:sorted-stats
labelbeam/20342d06-a832-4fa0-8eda-34243774ac2e
sort_stats
typebeam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51
ex:Method
typebeam/20342d06-a832-4fa0-8eda-34243774ac2e
ex:PythonMethod
returnsbeam/aedb6d8a-8822-4467-a7a5-cfff18551c49
ex:Stats-object
returnsbeam/c4d9d47f-41fb-4e74-bbca-e6bdc41cabac
ex:Stats_Object
sortsBybeam/5e9afeda-9bb9-4fc2-b6c2-8be60e02ac6e
ex:cumtime
takesArgumentbeam/5825331f-9249-40f8-9c37-fa519c74bcc1
ex:cumulative
usedForbeam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbe
ex:data-sorting
usesParameterbeam/bd01edbd-14a6-4066-9451-f8bdb9efdc3d
ex:sortby
usesSortingCriterionbeam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51
ex:cumulative

References (13)

13 references
  1. customctx:claims/beam/51125ee6-b618-48ae-8493-828d91a10410
  2. [2]beam-chunk1 fact
    customctx:claims/beam/bb0c421a-abf6-4f60-a2a9-6428edaf8c0a
    • full textbeam-chunk
      text/plain1 KBdoc:beam/bb0c421a-abf6-4f60-a2a9-6428edaf8c0a
      Show 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
  3. customctx:claims/beam/c4d9d47f-41fb-4e74-bbca-e6bdc41cabac
  4. [4]beam-chunk5 facts
    customctx:claims/beam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51
    • full textbeam-chunk
      text/plain1 KBdoc:beam/b9406b81-4fc1-45b7-ad2a-ee6dd1ca1b51
      Show 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:
  5. [5]beam-chunk2 facts
    customctx:claims/beam/5e9afeda-9bb9-4fc2-b6c2-8be60e02ac6e
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5e9afeda-9bb9-4fc2-b6c2-8be60e02ac6e
      Show 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
  6. [6]beam-chunk3 facts
    customctx:claims/beam/aedb6d8a-8822-4467-a7a5-cfff18551c49
    • full textbeam-chunk
      text/plain1 KBdoc:beam/aedb6d8a-8822-4467-a7a5-cfff18551c49
      Show 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
  7. [7]beam-chunk5 facts
    customctx:claims/beam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbe
    • full textbeam-chunk
      text/plain1 KBdoc:beam/9fcfc92c-57a9-467e-86b3-63dd7ea33dbe
      Show 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
  8. customctx:claims/beam/20342d06-a832-4fa0-8eda-34243774ac2e
  9. [9]beam-chunk1 fact
    customctx:claims/beam/1649add7-5446-4cf1-9934-90116d9362c7
    • full textbeam-chunk
      text/plain1 KBdoc:beam/1649add7-5446-4cf1-9934-90116d9362c7
      Show 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
  10. [10]beam-chunk1 fact
    customctx:claims/beam/7b17d450-1e6b-4a8d-aeee-b2acb55eb0f2
    • full textbeam-chunk
      text/plain1 KBdoc:beam/7b17d450-1e6b-4a8d-aeee-b2acb55eb0f2
      Show 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
  11. [11]beam-chunk1 fact
    customctx:claims/beam/a3257e5e-b867-40a8-a44a-3456d9c9c0b8
    • full textbeam-chunk
      text/plain1 KBdoc:beam/a3257e5e-b867-40a8-a44a-3456d9c9c0b8
      Show 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. *
  12. [12]beam-chunk1 fact
    customctx:claims/beam/5825331f-9249-40f8-9c37-fa519c74bcc1
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5825331f-9249-40f8-9c37-fa519c74bcc1
      Show 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
  13. [13]beam-chunk1 fact
    customctx:claims/beam/bd01edbd-14a6-4066-9451-f8bdb9efdc3d
    • full textbeam-chunk
      text/plain1 KBdoc:beam/bd01edbd-14a6-4066-9451-f8bdb9efdc3d
      Show 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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