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Load DataFrames and Arrow tables directly; to_polars() on results - #390
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…lars() on results (#387) Database.insert_dataframe and insert_arrow load a DataFrame or Arrow table in batches: documents through the existing insert_columns typed-array path, vertices through GraphBatch, no new Java. The Arrow type mapping (ints, floats, bool, string, timestamps with and without zone, date, decimal, list, struct, nulls) is documented and tested, and a declared property converts or the load is refused before a row is written. ResultSet.to_polars() reads through Arrow. polars joins the test extras and the CI test requirements, and a polars extra is added. Docs, java-api-coverage, testing rows and example 27 are in the same change. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
… comes through the bindings' test extra and the CI test requirements (#387) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
…ataframe_arrow_ingest.py (#387) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
…cs, whose leg is disabled; it breaks pyarrow on 3.14) (#387) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Two CI changes added after review: the examples' environment now has pandas, polars and pyarrow (example 27 imports them), and the macOS |
…our transaction, not committed' inside the caller's transaction; docs: undeclared nanosecond timestamps are stored, the readers return milliseconds and get() microseconds (#387) Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
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…r-call figure in the examples README (#386) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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…allbacks (#391) * Python functions callable from SQL and openCypher, and record event callbacks (#386) Database.register_function() / unregister_function() register a Python callable as an engine SQLFunction (bridge class PythonFunctions): SELECT and WHERE in SQL, and openCypher through a namespaced name such as py.slugify (its validator rejects an unknown bare name). An exception in the function is an ArcadeDBError naming the function, never a JVM crash. Database.on() / EventHandle.remove() run Python callbacks on before/after create, update and delete (bridge class PythonRecordEvents), database-wide or per type; a before callback that returns False vetoes the change, and an exception fails the operation. Tests, API and guide docs, coverage, bridge and testing docs, and example 27 in the same change. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * Renumber the Python functions example to 28 (27 is the DataFrame ingest example of #387) (#386) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * callbacks: the function registry holds its Database weakly, so a Database is released with its last result (#386) The registry, the function proxies and the event proxies hold the Database through a weak reference: the engine holds the proxies, so a strong reference would keep the Database alive until a gc pass. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * docs: no per-call figure for Python functions until it is measured with tools/ab.py; Example 28 prints the cost on the reader's machine (#386) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * callbacks: one JPype proxy class per interface (no per-registration leak), readable error for an unconvertible return, Ctrl-C always a KeyboardInterrupt, Document.save()/delete() raise ArcadeDBError; docs: read-only begin(), the ~30 bytes per numeric argument JPype note (#386) Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * docs: examples 27 and 28 side by side after the rebase on #390; no per-call figure in the examples README (#386) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
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…ow on Apple Silicon) The cap was for Intel Macs, whose leg (darwin/amd64) is disabled. pyarrow 26 requires NumPy 2, so example 27 failed on darwin/arm64 with 'pyarrow requires NumPy 2.0 or newer, found 1.26.4'. Same change as humemai/arcadedb-embedded-python#390. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Closes #387.
A bulk data path is one of the things an embedded database's Python API owns (DuckDB reads DataFrames in place), so this adds one, built on the existing glue (no new Java): documents go through
DocumentBatcher.insertColumns, vertices throughGraphBatch; the Arrow-to-column conversion and the declared-type check are new Python indataframe.py.Database.insert_dataframe(type_name, df, *, batch_size=10_000, parallel=False) -> int: pandas, Polars, or any Arrow PyCapsule object. A separate function frominsert_arrowbecause the frame libraries' missing values differ (pandas NaN becomes null, Polars NaN stays NaN).Database.insert_arrow(type_name, table, *, batch_size=10_000, parallel=False) -> int: Table, RecordBatch, RecordBatchReader or capsule object.ResultSet.to_polars(batch_size=25_000, columns=None)viato_arrow().api/database.md): integers to LONG (uint64 above 2^63-1 refused), floats to DOUBLE, bool, strings, dictionary as its value type, binary, timestamps (no zone: wall clock kept; with zone: UTC; precision from the declared type, read from the integer epoch so nanoseconds survive), date, decimal, list (ARRAY_OF_* if declared), struct to MAP, null as no value; time, duration and map columns raiseTypeError. A declared property converts along an allowlist and refuses the rest before any row is written. Each batch commits on its own; on a failure the batch in flight rolls back and the error says how many rows were committed before it.graph_batch().new_edges()),parallel=Truefor vertex types.api/database.md,api/results.md,guide/import.md,java-api-coverage.md,bridge.md,architecture.md,testing.md,docs/index.md; example 27 (script, page, README, nav). Packaging: apolarsextra; polars in thetestextra and in the CI test requirements.test_dataframe_ingest.py, 68 cases (every mapping written and read back, nulls, declared-type conversions and refusals, a 100k-row frame across batches, Polars and Arrow inputs, theto_polars()round trip); no skips.Checked locally against the 26.10.2 engine: the new tests with the insert_columns, resultset_arrow, columnar_readers and graph_batch tests (179 passed), bandit (low/low), pre-commit, the strict docs build.
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