Two decimal place formatting
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
Two decimal place formatting has 9 facts recorded in Dontopedia across 6 references, with 2 live disagreements.
Mostly:rdf:type(2), precision(2), specifies precision(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (1)
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.
uses-format-specifierUses Format Specifier(1)
- Print Statement
ex:print-statement
Other facts (8)
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 |
|---|---|---|
| Rdf:type | Formatting Operation | [1] |
| Rdf:type | Format Specification | [5] |
| Precision | 4-decimal-places | [2] |
| Precision | 2 | [3] |
| Specifies Precision | 2 | [5] |
| Specifies Precision | 2 | [6] |
| Used in | Score Print Loop | [1] |
| Applies to | latency-values | [4] |
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 (6)
ctx:claims/beam/eb7f55ff-6715-4dd8-81f8-023b5f9693f2- full textbeam-chunktext/plain1 KB
doc:beam/eb7f55ff-6715-4dd8-81f8-023b5f9693f2Show excerpt
retrieved_labels = relevant_labels[retrieved_indices] true_positives = np.sum(retrieved_labels) recall = true_positives / num_relevant return recall # Initialize the recall scores recall_scores = [] for tool in tools: …
ctx:claims/beam/a22fcd58-d4f0-414b-af57-b01230fea0e4- full textbeam-chunktext/plain1 KB
doc:beam/a22fcd58-d4f0-414b-af57-b01230fea0e4Show excerpt
logging.info(f"Response status: {response.status_code}") logging.info(f"Total request processing took {time.time() - start_time:.4f} seconds") return response # Example endpoint @app.get("/items") async def read_items(): re…
ctx:claims/beam/09328a61-37c3-4af1-a981-2afdd948ccb2- full textbeam-chunktext/plain1 KB
doc:beam/09328a61-37c3-4af1-a981-2afdd948ccb2Show excerpt
print(f"Processed {len(test_texts)} queries in {end_time - start_time:.2f} seconds") # Get the current memory snapshot snapshot = tracemalloc.take_snapshot() # Print the top 10 memory blocks top_stats = snapshot.statistics('lineno') for s…
ctx:claims/beam/2cfb7d2b-5bfb-4cc7-8380-035b7adbf5f7- full textbeam-chunktext/plain1 KB
doc:beam/2cfb7d2b-5bfb-4cc7-8380-035b7adbf5f7Show excerpt
# Simulate cache lookups start_time = time.time() latencies = [] for _ in range(14000): start_query_time = time.time() result = search_query("example") end_query_time = time.time() latencies.append(end_query_time - start_que…
ctx:claims/beam/7ba60581-efb1-48dc-ae4e-5da742180b42- full textbeam-chunktext/plain1 KB
doc:beam/7ba60581-efb1-48dc-ae4e-5da742180b42Show excerpt
queries = ["example query"] * 6000 # Measure the latency of processing multiple queries in parallel start_time = time.time() results = process_queries(queries) end_time = time.time() latency = end_time - start_time print(f"Total latency fo…
ctx:claims/beam/b681d85b-6c59-4977-9fea-11c8ba76b4ab
See also
Keep researching
Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.