feat: add support for hparam_range and hparam_candidates to bigframes.bigquery.create_model#16640
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This change allows the `options` parameter of `bigframes.bigquery._operations.ml.create_model` to accept BigFrames `Expression` objects. These expressions are compiled to SQL scalar expressions and included in the generated `CREATE MODEL` DDL statement. - Added `bigframes.core.expression.Expression` type support in the `options` dict. - Updated `create_model_ddl` to handle compiling expressions using `expression_compiler`. - Added `test_create_model_expression_option` snapshot test to verify the generated "golden SQL". Co-authored-by: tswast <247555+tswast@users.noreply.github.com>
This change allows the `options` parameter of `bigframes.bigquery._operations.ml.create_model` to accept BigFrames `Expression` objects. These expressions are compiled to SQL scalar expressions and included in the generated `CREATE MODEL` DDL statement. - Added `bigframes.core.expression.Expression` type support in the `options` dict. - Updated `create_model_ddl` to handle compiling expressions using `expression_compiler`. - Added `test_create_model_expression_option` snapshot test to verify the generated "golden SQL", using an expression that calls a function on a literal value (e.g. 0.1 * 10). Co-authored-by: tswast <247555+tswast@users.noreply.github.com>
This change allows the `options` parameter of `bigframes.bigquery._operations.ml.create_model` to accept BigFrames `Expression` objects. These expressions are compiled to SQL scalar expressions and included in the generated `CREATE MODEL` DDL statement. - Added `bigframes.core.expression.Expression` type support in the `options` dict. - Updated `create_model_ddl` to handle compiling expressions using `expression_compiler`. - Added `test_create_model_expression_option` snapshot test to verify the generated "golden SQL", using an expression that calls a function on a literal value (e.g. 0.1 * 10). Co-authored-by: tswast <247555+tswast@users.noreply.github.com>
This change allows the `options` parameter of `bigframes.bigquery._operations.ml.create_model` to accept BigFrames `Expression` objects. These expressions are compiled to SQL scalar expressions and included in the generated `CREATE MODEL` DDL statement. - Added `bigframes.core.expression.Expression` type support in the `options` dict. - Updated `create_model_ddl` to handle compiling expressions using `expression_compiler`. - Added `test_create_model_expression_option` snapshot test to verify the generated "golden SQL", using an expression that calls a function on a literal value (e.g. 0.1 * 10). - Moved test imports to the top level to adhere to PEP 8. Co-authored-by: tswast <247555+tswast@users.noreply.github.com>
This change allows the `options` parameter of `bigframes.bigquery._operations.ml.create_model` to accept BigFrames `col.Expression` objects. These expressions are compiled to SQL scalar expressions and included in the generated `CREATE MODEL` DDL statement. - Added `bigframes.core.col.Expression` type support in the `options` dict. - Updated `create_model_ddl` to handle compiling expressions using `expression_compiler`. - Added `test_create_model_expression_option` snapshot test to verify the generated "golden SQL", using an expression that calls a function on a literal value (e.g. 0.1 * 10). - Moved test imports to the top level to adhere to PEP 8 and ran `ruff format`. Co-authored-by: tswast <247555+tswast@users.noreply.github.com>
…te-model-expression-options-15193413976404138758
…rames.bigquery.create_model`
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This pull request introduces hparam_range and hparam_candidates functions to the bigframes.bigquery module, enabling support for hyperparameter tuning in BigQuery ML model creation. These functions wrap the HPARAM_RANGE and HPARAM_CANDIDATES SQL functions. The review feedback recommends simplifying the type hints for these new functions, noting that in Python type annotations, float already encompasses int.
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
…te-model-expression-options-15193413976404138758
…pression-options-15193413976404138758' into b501171054-hparam
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April 28, 2026 18:15
sycai
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May 5, 2026
| return bigframes.core.col.Expression(bigframes.core.expression.OpExpression(op, ())) | ||
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| def hparam_range(min: float, max: float) -> bigframes.core.col.Expression: |
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Should we put these two functions in the ml package instead? We don't have any hyper-parameter tuning opportunities outside the scope of machine learning, right?
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The ML package corresponds to the ML namespace. These functions aren't in the ML namespace in SQL.
sycai
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May 5, 2026
shuoweil
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May 13, 2026
PR created by the Librarian CLI to initialize a release. Merging this PR will auto trigger a release. Librarian Version: v0.13.0 Language Image: us-central1-docker.pkg.dev/cloud-sdk-librarian-prod/images-prod/python-librarian-generator@sha256:234b9d1f2ddb057ed7ac6a38db0bf8163d839c65c6cf88ade52530cddebce59e <details><summary>bigframes: v2.40.0</summary> ## [v2.40.0](bigframes-v2.39.0...bigframes-v2.40.0) (2026-05-13) ### Features * Add `bigframes.execution_history` API to track BigQuery jobs (#16588) ([fa20a74](fa20a740)) ```python import bigframes.pandas as bpd bpd.options.compute.enable_execution_history = True df = bpd.read_gbq("my_table") # ... perform operations ... history = bpd.execution_history print(history.jobs) # Access BigQuery job details for executed queries ``` * Implement `ai.similarity` and `ai.embed` for text embeddings and semantic similarity (#16771, #16759) ([d4afa2c](d4afa2c8), [fcb4579](fcb4579b)) ```python import bigframes.pandas as bpd # Generate embeddings df["embeddings"] = bpd.bigquery.ai.embed(df["text_col"]) # Compute similarity df["similarity"] = bpd.bigquery.ai.similarity(df["embeddings_a"], df["embeddings_b"]) ``` * Support `hparam_range` and `hparam_candidates` parameters for hyperparameter tuning in model creation (#16640) ([ca47835](ca47835c)) * Update `ai.score`, `ai.classify` and `ai.if_` parameters to match their SQL equivalents (#16919, #16990, #16857) ([9f42fe1](9f42fe14), [e9c52b1](e9c52b12), [f3cb4ad](f3cb4ad0)) * Support unstable sorting in `sort_values` and `sort_index` (#16665) ([bbdeb70](bbdeb70f)) * Support loading Avro and ORC data formats (#16555) ([6d46cba](6d46cba3)) * Add NumPy ufunc support directly on column expressions (#16554) ([2f792ab](2f792abd)) ### Bug Fixes * Fix bugs compiling ambiguous ids and in subqueries (#16617) ([479e44d](479e44dd)) * BigFrames respects bq default region (#16933) ([ef9945a](ef9945a5)) * avoid views when querying BigLake tables from SQL cells (#16562) ([fdd3e0d](fdd3e0de)) * avoid `copy` argument warning in `to_pandas` (#16917) ([fe5245b](fe5245b8)) ### Performance Improvements * Improve write api upload throughput (#16641) ([ef856b0](ef856b04)) ### Documentation * Add docs to the to_csv methods of dataframe and series (#16570) ([a8fccef](a8fccefd)) </details>
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Fixes internal issue b/501171054
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