Dontopedia

sort_stats

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

sort_stats has 8 facts recorded in Dontopedia across 3 references, with 2 live disagreements.

8 facts·4 predicates·3 sources·2 in dispute

Mostly:rdf:type(3), has argument(1), sorts by(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (2)

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.

callsCalls(1)

hasMethodHas Method(1)

Other facts (6)

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.

6 facts
PredicateValueRef
Rdf:typeMethod Call[1]
Rdf:typePython Method[2]
Rdf:typeStats Method[3]
Has Argument'cumulative'[1]
Sorts by'cumulative'[1]
Accepts Parameter'cumulative' String[2]

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.

typebeam/9c3b099c-2326-4d01-9fe2-f042149661ca
ex:Method-Call
labelbeam/9c3b099c-2326-4d01-9fe2-f042149661ca
sort_stats('cumulative')
hasArgumentbeam/9c3b099c-2326-4d01-9fe2-f042149661ca
ex:'cumulative'
sortsBybeam/9c3b099c-2326-4d01-9fe2-f042149661ca
ex:'cumulative'
typebeam/660e3995-1e13-46bd-ac9f-742b3e9f7c2b
ex:PythonMethod
acceptsParameterbeam/660e3995-1e13-46bd-ac9f-742b3e9f7c2b
ex:'cumulative'-string
typebeam/65957df4-b73b-432a-9942-de8252cc92e4
ex:Stats-method
labelbeam/65957df4-b73b-432a-9942-de8252cc92e4
sort_stats

References (3)

3 references
  1. ctx:claims/beam/9c3b099c-2326-4d01-9fe2-f042149661ca
  2. ctx:claims/beam/660e3995-1e13-46bd-ac9f-742b3e9f7c2b
    • full textbeam-chunk
      text/plain1 KBdoc:beam/660e3995-1e13-46bd-ac9f-742b3e9f7c2b
      Show excerpt
      time.sleep(10) # Simulating a time-consuming task def main(): start_time = datetime.datetime.now() # Profile the critical assignment code profiler = cProfile.Profile() profiler.enable() critical_assignmen
  3. ctx:claims/beam/65957df4-b73b-432a-9942-de8252cc92e4
    • full textbeam-chunk
      text/plain957 Bdoc:beam/65957df4-b73b-432a-9942-de8252cc92e4
      Show excerpt
      - **Optimization**: Use the timing information to identify bottlenecks and optimize the query rewriting logic. ### Example with Profiling You can use `cProfile` to profile the entire process: ```python import cProfile import pstats def

See also

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