type stringclasses 5
values | name stringlengths 1 55 | qualified_name stringlengths 5 130 | docstring stringlengths 15 3.11k ⌀ | filepath stringclasses 90
values | is_public bool 2
classes | is_private bool 2
classes | line_start int64 0 1.44k ⌀ | line_end int64 0 1.51k ⌀ | annotation stringclasses 2
values | returns stringclasses 82
values | value stringclasses 66
values | parameters listlengths 0 10 ⌀ | bases listlengths 0 2 ⌀ | parent_class stringclasses 193
values | api_element_summary stringlengths 199 3.43k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
method | __gt__ | fenic.api.column.Column.__gt__ | Greater than comparison. | null | true | false | 784 | 786 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __gt__
Qualified Name: fenic.api.column.Column.__gt__
Docstring: Greater than comparison.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __ge__ | fenic.api.column.Column.__ge__ | Greater than or equal comparison. | null | true | false | 788 | 790 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __ge__
Qualified Name: fenic.api.column.Column.__ge__
Docstring: Greater than or equal comparison.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __lt__ | fenic.api.column.Column.__lt__ | Less than comparison. | null | true | false | 792 | 794 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __lt__
Qualified Name: fenic.api.column.Column.__lt__
Docstring: Less than comparison.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __le__ | fenic.api.column.Column.__le__ | Less than or equal comparison. | null | true | false | 796 | 798 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __le__
Qualified Name: fenic.api.column.Column.__le__
Docstring: Less than or equal comparison.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __eq__ | fenic.api.column.Column.__eq__ | Equality comparison. | null | true | false | 800 | 802 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __eq__
Qualified Name: fenic.api.column.Column.__eq__
Docstring: Equality comparison.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __ne__ | fenic.api.column.Column.__ne__ | Not equal comparison. | null | true | false | 804 | 806 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __ne__
Qualified Name: fenic.api.column.Column.__ne__
Docstring: Not equal comparison.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __and__ | fenic.api.column.Column.__and__ | Logical AND operation. | null | true | false | 808 | 810 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __and__
Qualified Name: fenic.api.column.Column.__and__
Docstring: Logical AND operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __rand__ | fenic.api.column.Column.__rand__ | Reverse logical AND operation. | null | true | false | 812 | 814 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __rand__
Qualified Name: fenic.api.column.Column.__rand__
Docstring: Reverse logical AND operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __or__ | fenic.api.column.Column.__or__ | Logical OR operation. | null | true | false | 816 | 818 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __or__
Qualified Name: fenic.api.column.Column.__or__
Docstring: Logical OR operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __ror__ | fenic.api.column.Column.__ror__ | Reverse logical OR operation. | null | true | false | 820 | 822 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __ror__
Qualified Name: fenic.api.column.Column.__ror__
Docstring: Reverse logical OR operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __add__ | fenic.api.column.Column.__add__ | Addition operation. | null | true | false | 824 | 826 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __add__
Qualified Name: fenic.api.column.Column.__add__
Docstring: Addition operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __radd__ | fenic.api.column.Column.__radd__ | Reverse addition operation. | null | true | false | 828 | 832 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __radd__
Qualified Name: fenic.api.column.Column.__radd__
Docstring: Reverse addition operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __sub__ | fenic.api.column.Column.__sub__ | Subtraction operation. | null | true | false | 834 | 836 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __sub__
Qualified Name: fenic.api.column.Column.__sub__
Docstring: Subtraction operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __rsub__ | fenic.api.column.Column.__rsub__ | Reverse subtraction operation. | null | true | false | 838 | 842 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __rsub__
Qualified Name: fenic.api.column.Column.__rsub__
Docstring: Reverse subtraction operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __mul__ | fenic.api.column.Column.__mul__ | Multiplication operation. | null | true | false | 844 | 846 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __mul__
Qualified Name: fenic.api.column.Column.__mul__
Docstring: Multiplication operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __rmul__ | fenic.api.column.Column.__rmul__ | Reverse multiplication operation. | null | true | false | 848 | 850 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __rmul__
Qualified Name: fenic.api.column.Column.__rmul__
Docstring: Reverse multiplication operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __truediv__ | fenic.api.column.Column.__truediv__ | Division operation. | null | true | false | 852 | 854 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __truediv__
Qualified Name: fenic.api.column.Column.__truediv__
Docstring: Division operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __rtruediv__ | fenic.api.column.Column.__rtruediv__ | Reverse division operation. | null | true | false | 856 | 860 | null | Column | null | [
"self",
"other"
] | null | Column | Type: method
Member Name: __rtruediv__
Qualified Name: fenic.api.column.Column.__rtruediv__
Docstring: Reverse division operation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: Column
Parent Class: Column |
method | __bool__ | fenic.api.column.Column.__bool__ | Prevent boolean conversion of Column objects. | null | true | false | 862 | 866 | null | null | null | [
"self"
] | null | Column | Type: method
Member Name: __bool__
Qualified Name: fenic.api.column.Column.__bool__
Docstring: Prevent boolean conversion of Column objects.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: Column |
attribute | ColumnOrName | fenic.api.column.ColumnOrName | null | null | true | false | 868 | 868 | null | null | Union[Column, str] | null | null | null | Type: attribute
Member Name: ColumnOrName
Qualified Name: fenic.api.column.ColumnOrName
Docstring: none
Value: Union[Column, str]
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
module | dataframe | fenic.api.dataframe | DataFrame API for Fenic - provides DataFrame and grouped data operations. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/dataframe/__init__.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: dataframe
Qualified Name: fenic.api.dataframe
Docstring: DataFrame API for Fenic - provides DataFrame and grouped data operations.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | __all__ | fenic.api.dataframe.__all__ | null | null | false | false | 10 | 10 | null | null | ['DataFrame', 'GroupedData', 'SemGroupedData', 'SemanticExtensions'] | null | null | null | Type: attribute
Member Name: __all__
Qualified Name: fenic.api.dataframe.__all__
Docstring: none
Value: ['DataFrame', 'GroupedData', 'SemGroupedData', 'SemanticExtensions']
Annotation: none
is Public? : false
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
module | _base_grouped_data | fenic.api.dataframe._base_grouped_data | null | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/dataframe/_base_grouped_data.py | false | true | null | null | null | null | null | null | null | null | Type: module
Member Name: _base_grouped_data
Qualified Name: fenic.api.dataframe._base_grouped_data
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none |
class | BaseGroupedData | fenic.api.dataframe._base_grouped_data.BaseGroupedData | Base class for aggregation methods shared between GroupedData and SemanticallyGroupedData. | null | true | false | 13 | 82 | null | null | null | null | [] | null | Type: class
Member Name: BaseGroupedData
Qualified Name: fenic.api.dataframe._base_grouped_data.BaseGroupedData
Docstring: Base class for aggregation methods shared between GroupedData and SemanticallyGroupedData.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent C... |
method | __init__ | fenic.api.dataframe._base_grouped_data.BaseGroupedData.__init__ | null | null | true | false | 16 | 17 | null | null | null | [
"self",
"df"
] | null | BaseGroupedData | Type: method
Member Name: __init__
Qualified Name: fenic.api.dataframe._base_grouped_data.BaseGroupedData.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "df"]
Returns: none
Parent Class: BaseGroupedData |
method | _process_agg_dict | fenic.api.dataframe._base_grouped_data.BaseGroupedData._process_agg_dict | Process dictionary-style aggregation specifications. | null | false | true | 19 | 39 | null | List[Column] | null | [
"self",
"agg_dict"
] | null | BaseGroupedData | Type: method
Member Name: _process_agg_dict
Qualified Name: fenic.api.dataframe._base_grouped_data.BaseGroupedData._process_agg_dict
Docstring: Process dictionary-style aggregation specifications.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "agg_dict"]
Returns: List[Column]
P... |
method | _process_agg_exprs | fenic.api.dataframe._base_grouped_data.BaseGroupedData._process_agg_exprs | Process Column-style aggregation expressions. | null | false | true | 41 | 58 | null | List[AliasExpr] | null | [
"self",
"cols"
] | null | BaseGroupedData | Type: method
Member Name: _process_agg_exprs
Qualified Name: fenic.api.dataframe._base_grouped_data.BaseGroupedData._process_agg_exprs
Docstring: Process Column-style aggregation expressions.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "cols"]
Returns: List[AliasExpr]
Parent ... |
method | _validate_agg_exprs | fenic.api.dataframe._base_grouped_data.BaseGroupedData._validate_agg_exprs | Validate aggregation expressions. | null | false | true | 60 | 82 | null | None | null | [
"self",
"exprs"
] | null | BaseGroupedData | Type: method
Member Name: _validate_agg_exprs
Qualified Name: fenic.api.dataframe._base_grouped_data.BaseGroupedData._validate_agg_exprs
Docstring: Validate aggregation expressions.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self", "exprs"]
Returns: None
Parent Class: BaseGroupedDa... |
module | dataframe | fenic.api.dataframe.dataframe | DataFrame class providing PySpark-inspired API for data manipulation. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/dataframe/dataframe.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: dataframe
Qualified Name: fenic.api.dataframe.dataframe
Docstring: DataFrame class providing PySpark-inspired API for data manipulation.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | logger | fenic.api.dataframe.dataframe.logger | null | null | true | false | 53 | 53 | null | null | logging.getLogger(__name__) | null | null | null | Type: attribute
Member Name: logger
Qualified Name: fenic.api.dataframe.dataframe.logger
Docstring: none
Value: logging.getLogger(__name__)
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | DataFrame | fenic.api.dataframe.dataframe.DataFrame | A data collection organized into named columns.
The DataFrame class represents a lazily evaluated computation on data. Operations on
DataFrame build up a logical query plan that is only executed when an action like
show(), to_polars(), to_pandas(), to_arrow(), to_pydict(), to_pylist(), or count() is called.
The DataF... | null | true | false | 56 | 1,512 | null | null | null | null | [] | null | Type: class
Member Name: DataFrame
Qualified Name: fenic.api.dataframe.dataframe.DataFrame
Docstring: A data collection organized into named columns.
The DataFrame class represents a lazily evaluated computation on data. Operations on
DataFrame build up a logical query plan that is only executed when an action like
sh... |
method | __new__ | fenic.api.dataframe.dataframe.DataFrame.__new__ | Prevent direct DataFrame construction.
DataFrames must be created through Session.create_dataframe(). | null | true | false | 87 | 96 | null | null | null | [
"cls"
] | null | DataFrame | Type: method
Member Name: __new__
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.__new__
Docstring: Prevent direct DataFrame construction.
DataFrames must be created through Session.create_dataframe().
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["cls"]
Returns: none
Parent ... |
method | _from_logical_plan | fenic.api.dataframe.dataframe.DataFrame._from_logical_plan | Factory method to create DataFrame instances.
This method is intended for internal use by the Session class and other
DataFrame methods that need to create new DataFrame instances.
Args:
logical_plan: The logical plan for this DataFrame
Returns:
A new DataFrame instance | null | false | true | 98 | 117 | null | DataFrame | null | [
"cls",
"logical_plan"
] | null | DataFrame | Type: method
Member Name: _from_logical_plan
Qualified Name: fenic.api.dataframe.dataframe.DataFrame._from_logical_plan
Docstring: Factory method to create DataFrame instances.
This method is intended for internal use by the Session class and other
DataFrame methods that need to create new DataFrame instances.
Args:
... |
method | __getitem__ | fenic.api.dataframe.dataframe.DataFrame.__getitem__ | Enable DataFrame[column_name] syntax for column access.
Args:
col_name: Name of the column to access
Returns:
Column: Column object for the specified column
Raises:
TypeError: If item is not a string
Examples:
>>> df[col("age")] # Returns Column object for "age"
>>> df.filter(df[col("age")] > 2... | null | true | false | 162 | 190 | null | Column | null | [
"self",
"col_name"
] | null | DataFrame | Type: method
Member Name: __getitem__
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.__getitem__
Docstring: Enable DataFrame[column_name] syntax for column access.
Args:
col_name: Name of the column to access
Returns:
Column: Column object for the specified column
Raises:
TypeError: If item is n... |
method | __getattr__ | fenic.api.dataframe.dataframe.DataFrame.__getattr__ | Enable DataFrame.column_name syntax for column access.
Args:
col_name: Name of the column to access
Returns:
Column: Column object for the specified column
Raises:
TypeError: If col_name is not a string
Examples:
>>> df.age # Returns Column object for "age"
>>> df.filter(col("age") > 25) # Use... | null | true | false | 192 | 219 | null | Column | null | [
"self",
"col_name"
] | null | DataFrame | Type: method
Member Name: __getattr__
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.__getattr__
Docstring: Enable DataFrame.column_name syntax for column access.
Args:
col_name: Name of the column to access
Returns:
Column: Column object for the specified column
Raises:
TypeError: If col_name i... |
method | explain | fenic.api.dataframe.dataframe.DataFrame.explain | Display the logical plan of the DataFrame. | null | true | false | 221 | 223 | null | None | null | [
"self"
] | null | DataFrame | Type: method
Member Name: explain
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.explain
Docstring: Display the logical plan of the DataFrame.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: None
Parent Class: DataFrame |
method | show | fenic.api.dataframe.dataframe.DataFrame.show | Display the DataFrame content in a tabular form.
This is an action that triggers computation of the DataFrame.
The output is printed to stdout in a formatted table.
Args:
n: Number of rows to display
explain_analyze: Whether to print the explain analyze plan | null | true | false | 225 | 239 | null | None | null | [
"self",
"n",
"explain_analyze"
] | null | DataFrame | Type: method
Member Name: show
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.show
Docstring: Display the DataFrame content in a tabular form.
This is an action that triggers computation of the DataFrame.
The output is printed to stdout in a formatted table.
Args:
n: Number of rows to display
explain... |
method | collect | fenic.api.dataframe.dataframe.DataFrame.collect | Execute the DataFrame computation and return the result as a QueryResult.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the results are
materialized into a QueryResult, which contains both the result data and the query metrics.
Args:
... | null | true | false | 241 | 269 | null | QueryResult | null | [
"self",
"data_type"
] | null | DataFrame | Type: method
Member Name: collect
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.collect
Docstring: Execute the DataFrame computation and return the result as a QueryResult.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the result... |
method | to_polars | fenic.api.dataframe.dataframe.DataFrame.to_polars | Execute the DataFrame computation and return the result as a Polars DataFrame.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the results are
materialized into a Polars DataFrame.
Returns:
pl.DataFrame: A Polars DataFrame with material... | null | true | false | 271 | 281 | null | pl.DataFrame | null | [
"self"
] | null | DataFrame | Type: method
Member Name: to_polars
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.to_polars
Docstring: Execute the DataFrame computation and return the result as a Polars DataFrame.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and t... |
method | to_pandas | fenic.api.dataframe.dataframe.DataFrame.to_pandas | Execute the DataFrame computation and return a Pandas DataFrame.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the results are
materialized into a Pandas DataFrame.
Returns:
pd.DataFrame: A Pandas DataFrame containing the computed res... | null | true | false | 283 | 293 | null | pd.DataFrame | null | [
"self"
] | null | DataFrame | Type: method
Member Name: to_pandas
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.to_pandas
Docstring: Execute the DataFrame computation and return a Pandas DataFrame.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the results are... |
method | to_arrow | fenic.api.dataframe.dataframe.DataFrame.to_arrow | Execute the DataFrame computation and return an Apache Arrow Table.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the results are
materialized into an Apache Arrow Table with columnar memory layout
optimized for analytics and zero-copy dat... | null | true | false | 295 | 306 | null | pa.Table | null | [
"self"
] | null | DataFrame | Type: method
Member Name: to_arrow
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.to_arrow
Docstring: Execute the DataFrame computation and return an Apache Arrow Table.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the results ar... |
method | to_pydict | fenic.api.dataframe.dataframe.DataFrame.to_pydict | Execute the DataFrame computation and return a dictionary of column arrays.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the results are
materialized into a Python dictionary where each column becomes a list of values.
Returns:
Dict[... | null | true | false | 308 | 320 | null | Dict[str, List[Any]] | null | [
"self"
] | null | DataFrame | Type: method
Member Name: to_pydict
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.to_pydict
Docstring: Execute the DataFrame computation and return a dictionary of column arrays.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the ... |
method | to_pylist | fenic.api.dataframe.dataframe.DataFrame.to_pylist | Execute the DataFrame computation and return a list of row dictionaries.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the results are
materialized into a Python list where each element is a dictionary
representing one row with column name... | null | true | false | 322 | 337 | null | List[Dict[str, Any]] | null | [
"self"
] | null | DataFrame | Type: method
Member Name: to_pylist
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.to_pylist
Docstring: Execute the DataFrame computation and return a list of row dictionaries.
This is an action that triggers computation of the DataFrame query plan.
All transformations and operations are executed, and the res... |
method | count | fenic.api.dataframe.dataframe.DataFrame.count | Count the number of rows in the DataFrame.
This is an action that triggers computation of the DataFrame.
The output is an integer representing the number of rows.
Returns:
int: The number of rows in the DataFrame | null | true | false | 339 | 348 | null | int | null | [
"self"
] | null | DataFrame | Type: method
Member Name: count
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.count
Docstring: Count the number of rows in the DataFrame.
This is an action that triggers computation of the DataFrame.
The output is an integer representing the number of rows.
Returns:
int: The number of rows in the DataFr... |
method | lineage | fenic.api.dataframe.dataframe.DataFrame.lineage | Create a Lineage object to trace data through transformations.
The Lineage interface allows you to trace how specific rows are transformed
through your DataFrame operations, both forwards and backwards through the
computation graph.
Returns:
Lineage: Interface for querying data lineage
Example:
```python
... | null | true | false | 350 | 375 | null | Lineage | null | [
"self"
] | null | DataFrame | Type: method
Member Name: lineage
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.lineage
Docstring: Create a Lineage object to trace data through transformations.
The Lineage interface allows you to trace how specific rows are transformed
through your DataFrame operations, both forwards and backwards through ... |
method | persist | fenic.api.dataframe.dataframe.DataFrame.persist | Mark this DataFrame to be persisted after first computation.
The persisted DataFrame will be cached after its first computation,
avoiding recomputation in subsequent operations. This is useful for DataFrames
that are reused multiple times in your workflow.
Returns:
DataFrame: Same DataFrame, but marked for persis... | null | true | false | 377 | 403 | null | DataFrame | null | [
"self"
] | null | DataFrame | Type: method
Member Name: persist
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.persist
Docstring: Mark this DataFrame to be persisted after first computation.
The persisted DataFrame will be cached after its first computation,
avoiding recomputation in subsequent operations. This is useful for DataFrames
th... |
method | cache | fenic.api.dataframe.dataframe.DataFrame.cache | Alias for persist(). Mark DataFrame for caching after first computation.
Returns:
DataFrame: Same DataFrame, but marked for caching
See Also:
persist(): Full documentation of caching behavior | null | true | false | 405 | 414 | null | DataFrame | null | [
"self"
] | null | DataFrame | Type: method
Member Name: cache
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.cache
Docstring: Alias for persist(). Mark DataFrame for caching after first computation.
Returns:
DataFrame: Same DataFrame, but marked for caching
See Also:
persist(): Full documentation of caching behavior
Value: none
A... |
method | select | fenic.api.dataframe.dataframe.DataFrame.select | Projects a set of Column expressions or column names.
Args:
*cols: Column expressions to select. Can be:
- String column names (e.g., "id", "name")
- Column objects (e.g., col("id"), col("age") + 1)
Returns:
DataFrame: A new DataFrame with selected columns
Example: Select by column names
... | null | true | false | 416 | 483 | null | DataFrame | null | [
"self",
"cols"
] | null | DataFrame | Type: method
Member Name: select
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.select
Docstring: Projects a set of Column expressions or column names.
Args:
*cols: Column expressions to select. Can be:
- String column names (e.g., "id", "name")
- Column objects (e.g., col("id"), col("age"... |
method | where | fenic.api.dataframe.dataframe.DataFrame.where | Filters rows using the given condition (alias for filter()).
Args:
condition: A Column expression that evaluates to a boolean
Returns:
DataFrame: Filtered DataFrame
See Also:
filter(): Full documentation of filtering behavior | null | true | false | 485 | 497 | null | DataFrame | null | [
"self",
"condition"
] | null | DataFrame | Type: method
Member Name: where
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.where
Docstring: Filters rows using the given condition (alias for filter()).
Args:
condition: A Column expression that evaluates to a boolean
Returns:
DataFrame: Filtered DataFrame
See Also:
filter(): Full documentat... |
method | filter | fenic.api.dataframe.dataframe.DataFrame.filter | Filters rows using the given condition.
Args:
condition: A Column expression that evaluates to a boolean
Returns:
DataFrame: Filtered DataFrame
Example: Filter with numeric comparison
```python
# Create a DataFrame
df = session.create_dataframe({"age": [25, 30, 35], "name": ["Alice", "Bob", "Char... | null | true | false | 499 | 552 | null | DataFrame | null | [
"self",
"condition"
] | null | DataFrame | Type: method
Member Name: filter
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.filter
Docstring: Filters rows using the given condition.
Args:
condition: A Column expression that evaluates to a boolean
Returns:
DataFrame: Filtered DataFrame
Example: Filter with numeric comparison
```python
... |
method | with_column | fenic.api.dataframe.dataframe.DataFrame.with_column | Add a new column or replace an existing column.
Args:
col_name: Name of the new column
col: Column expression or value to assign to the column. If not a Column,
it will be treated as a literal value.
Returns:
DataFrame: New DataFrame with added/replaced column
Example: Add literal column
```p... | null | true | false | 554 | 638 | null | DataFrame | null | [
"self",
"col_name",
"col"
] | null | DataFrame | Type: method
Member Name: with_column
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.with_column
Docstring: Add a new column or replace an existing column.
Args:
col_name: Name of the new column
col: Column expression or value to assign to the column. If not a Column,
it will be treated as a l... |
method | with_column_renamed | fenic.api.dataframe.dataframe.DataFrame.with_column_renamed | Rename a column. No-op if the column does not exist.
Args:
col_name: Name of the column to rename.
new_col_name: New name for the column.
Returns:
DataFrame: New DataFrame with the column renamed.
Example: Rename a column
```python
# Create sample DataFrame
df = session.create_dataframe({
... | null | true | false | 640 | 703 | null | DataFrame | null | [
"self",
"col_name",
"new_col_name"
] | null | DataFrame | Type: method
Member Name: with_column_renamed
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.with_column_renamed
Docstring: Rename a column. No-op if the column does not exist.
Args:
col_name: Name of the column to rename.
new_col_name: New name for the column.
Returns:
DataFrame: New DataFrame w... |
method | drop | fenic.api.dataframe.dataframe.DataFrame.drop | Remove one or more columns from this DataFrame.
Args:
*col_names: Names of columns to drop.
Returns:
DataFrame: New DataFrame without specified columns.
Raises:
ValueError: If any specified column doesn't exist in the DataFrame.
ValueError: If dropping the columns would result in an empty DataFrame.
... | null | true | false | 705 | 784 | null | DataFrame | null | [
"self",
"col_names"
] | null | DataFrame | Type: method
Member Name: drop
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.drop
Docstring: Remove one or more columns from this DataFrame.
Args:
*col_names: Names of columns to drop.
Returns:
DataFrame: New DataFrame without specified columns.
Raises:
ValueError: If any specified column doesn... |
method | union | fenic.api.dataframe.dataframe.DataFrame.union | Return a new DataFrame containing the union of rows in this and another DataFrame.
This is equivalent to UNION ALL in SQL. To remove duplicates, use drop_duplicates() after union().
Args:
other: Another DataFrame with the same schema.
Returns:
DataFrame: A new DataFrame containing rows from both DataFrames.
... | null | true | false | 786 | 864 | null | DataFrame | null | [
"self",
"other"
] | null | DataFrame | Type: method
Member Name: union
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.union
Docstring: Return a new DataFrame containing the union of rows in this and another DataFrame.
This is equivalent to UNION ALL in SQL. To remove duplicates, use drop_duplicates() after union().
Args:
other: Another DataFr... |
method | limit | fenic.api.dataframe.dataframe.DataFrame.limit | Limits the number of rows to the specified number.
Args:
n: Maximum number of rows to return.
Returns:
DataFrame: DataFrame with at most n rows.
Raises:
TypeError: If n is not an integer.
Example: Limit rows
```python
# Create sample DataFrame
df = session.create_dataframe({
"id": [1... | null | true | false | 866 | 911 | null | DataFrame | null | [
"self",
"n"
] | null | DataFrame | Type: method
Member Name: limit
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.limit
Docstring: Limits the number of rows to the specified number.
Args:
n: Maximum number of rows to return.
Returns:
DataFrame: DataFrame with at most n rows.
Raises:
TypeError: If n is not an integer.
Example: Li... |
method | join | fenic.api.dataframe.dataframe.DataFrame.join | Joins this DataFrame with another DataFrame.
The Dataframes must have no duplicate column names between them. This API only supports equi-joins.
For non-equi-joins, use session.sql().
Args:
other: DataFrame to join with.
on: Join condition(s). Can be:
- A column name (str)
- A list of column n... | null | true | false | 932 | 1,041 | null | DataFrame | null | [
"self",
"other",
"on",
"left_on",
"right_on",
"how"
] | null | DataFrame | Type: method
Member Name: join
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.join
Docstring: Joins this DataFrame with another DataFrame.
The Dataframes must have no duplicate column names between them. This API only supports equi-joins.
For non-equi-joins, use session.sql().
Args:
other: DataFrame to j... |
method | explode | fenic.api.dataframe.dataframe.DataFrame.explode | Create a new row for each element in an array column.
This operation is useful for flattening nested data structures. For each row in the
input DataFrame that contains an array/list in the specified column, this method will:
1. Create N new rows, where N is the length of the array
2. Each new row will be identical to ... | null | true | false | 1,043 | 1,099 | null | DataFrame | null | [
"self",
"column"
] | null | DataFrame | Type: method
Member Name: explode
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.explode
Docstring: Create a new row for each element in an array column.
This operation is useful for flattening nested data structures. For each row in the
input DataFrame that contains an array/list in the specified column, thi... |
method | group_by | fenic.api.dataframe.dataframe.DataFrame.group_by | Groups the DataFrame using the specified columns.
Args:
*cols: Columns to group by. Can be column names as strings or Column expressions.
Returns:
GroupedData: Object for performing aggregations on the grouped data.
Example: Group by single column
```python
# Create sample DataFrame
df = session.... | null | true | false | 1,101 | 1,156 | null | GroupedData | null | [
"self",
"cols"
] | null | DataFrame | Type: method
Member Name: group_by
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.group_by
Docstring: Groups the DataFrame using the specified columns.
Args:
*cols: Columns to group by. Can be column names as strings or Column expressions.
Returns:
GroupedData: Object for performing aggregations on t... |
method | agg | fenic.api.dataframe.dataframe.DataFrame.agg | Aggregate on the entire DataFrame without groups.
This is equivalent to group_by() without any grouping columns.
Args:
*exprs: Aggregation expressions or dictionary of aggregations.
Returns:
DataFrame: Aggregation results.
Example: Multiple aggregations
```python
# Create sample DataFrame
df = s... | null | true | false | 1,158 | 1,202 | null | DataFrame | null | [
"self",
"exprs"
] | null | DataFrame | Type: method
Member Name: agg
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.agg
Docstring: Aggregate on the entire DataFrame without groups.
This is equivalent to group_by() without any grouping columns.
Args:
*exprs: Aggregation expressions or dictionary of aggregations.
Returns:
DataFrame: Aggreg... |
method | drop_duplicates | fenic.api.dataframe.dataframe.DataFrame.drop_duplicates | Return a DataFrame with duplicate rows removed.
Args:
subset: Column names to consider when identifying duplicates. If not provided, all columns are considered.
Returns:
DataFrame: A new DataFrame with duplicate rows removed.
Raises:
ValueError: If a specified column is not present in the current DataFra... | null | true | false | 1,204 | 1,260 | null | DataFrame | null | [
"self",
"subset"
] | null | DataFrame | Type: method
Member Name: drop_duplicates
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.drop_duplicates
Docstring: Return a DataFrame with duplicate rows removed.
Args:
subset: Column names to consider when identifying duplicates. If not provided, all columns are considered.
Returns:
DataFrame: A ne... |
method | sort | fenic.api.dataframe.dataframe.DataFrame.sort | Sort the DataFrame by the specified columns.
Args:
cols: Columns to sort by. This can be:
- A single column name (str)
- A Column expression (e.g., `col("name")`)
- A list of column names or Column expressions
- Column expressions may include sorting directives such as `asc("col")`,... | null | true | false | 1,262 | 1,422 | null | DataFrame | null | [
"self",
"cols",
"ascending"
] | null | DataFrame | Type: method
Member Name: sort
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.sort
Docstring: Sort the DataFrame by the specified columns.
Args:
cols: Columns to sort by. This can be:
- A single column name (str)
- A Column expression (e.g., `col("name")`)
- A list of column names ... |
method | order_by | fenic.api.dataframe.dataframe.DataFrame.order_by | Sort the DataFrame by the specified columns. Alias for sort().
Returns:
DataFrame: sorted Dataframe.
See Also:
sort(): Full documentation of sorting behavior and parameters. | null | true | false | 1,424 | 1,437 | null | 'DataFrame' | null | [
"self",
"cols",
"ascending"
] | null | DataFrame | Type: method
Member Name: order_by
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.order_by
Docstring: Sort the DataFrame by the specified columns. Alias for sort().
Returns:
DataFrame: sorted Dataframe.
See Also:
sort(): Full documentation of sorting behavior and parameters.
Value: none
Annotation: n... |
method | unnest | fenic.api.dataframe.dataframe.DataFrame.unnest | Unnest the specified struct columns into separate columns.
This operation flattens nested struct data by expanding each field of a struct
into its own top-level column.
For each specified column containing a struct:
1. Each field in the struct becomes a separate column.
2. New columns are named after the correspondin... | null | true | false | 1,439 | 1,512 | null | DataFrame | null | [
"self",
"col_names"
] | null | DataFrame | Type: method
Member Name: unnest
Qualified Name: fenic.api.dataframe.dataframe.DataFrame.unnest
Docstring: Unnest the specified struct columns into separate columns.
This operation flattens nested struct data by expanding each field of a struct
into its own top-level column.
For each specified column containing a str... |
module | grouped_data | fenic.api.dataframe.grouped_data | GroupedData class for aggregations on grouped DataFrames. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/dataframe/grouped_data.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: grouped_data
Qualified Name: fenic.api.dataframe.grouped_data
Docstring: GroupedData class for aggregations on grouped DataFrames.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | GroupedData | fenic.api.dataframe.grouped_data.GroupedData | Methods for aggregations on a grouped DataFrame. | null | true | false | 19 | 93 | null | null | null | null | [
"BaseGroupedData"
] | null | Type: class
Member Name: GroupedData
Qualified Name: fenic.api.dataframe.grouped_data.GroupedData
Docstring: Methods for aggregations on a grouped DataFrame.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic.api.dataframe.grouped_data.GroupedData.__init__ | Initialize grouped data.
Args:
df: The DataFrame to group.
by: Optional list of columns to group by. | null | true | false | 22 | 43 | null | null | null | [
"self",
"df",
"by"
] | null | GroupedData | Type: method
Member Name: __init__
Qualified Name: fenic.api.dataframe.grouped_data.GroupedData.__init__
Docstring: Initialize grouped data.
Args:
df: The DataFrame to group.
by: Optional list of columns to group by.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "df", ... |
method | agg | fenic.api.dataframe.grouped_data.GroupedData.agg | Compute aggregations on grouped data and return the result as a DataFrame.
This method applies aggregate functions to the grouped data.
Args:
*exprs: Aggregation expressions. Can be:
- Column expressions with aggregate functions (e.g., `count("*")`, `sum("amount")`)
- A dictionary mapping column ... | null | true | false | 45 | 93 | null | DataFrame | null | [
"self",
"exprs"
] | null | GroupedData | Type: method
Member Name: agg
Qualified Name: fenic.api.dataframe.grouped_data.GroupedData.agg
Docstring: Compute aggregations on grouped data and return the result as a DataFrame.
This method applies aggregate functions to the grouped data.
Args:
*exprs: Aggregation expressions. Can be:
- Column express... |
module | _join_utils | fenic.api.dataframe._join_utils | Utility functions for DataFrame join operations. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/dataframe/_join_utils.py | false | true | null | null | null | null | null | null | null | null | Type: module
Member Name: _join_utils
Qualified Name: fenic.api.dataframe._join_utils
Docstring: Utility functions for DataFrame join operations.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none |
function | validate_join_parameters | fenic.api.dataframe._join_utils.validate_join_parameters | Validate join parameter combinations. | null | true | false | 10 | 51 | null | None | null | [
"self",
"on",
"left_on",
"right_on",
"how"
] | null | null | Type: function
Member Name: validate_join_parameters
Qualified Name: fenic.api.dataframe._join_utils.validate_join_parameters
Docstring: Validate join parameter combinations.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "on", "left_on", "right_on", "how"]
Returns: None
Parent ... |
function | build_join_conditions | fenic.api.dataframe._join_utils.build_join_conditions | Build left and right join condition lists. | null | true | false | 53 | 82 | null | Tuple[List, List] | null | [
"on",
"left_on",
"right_on"
] | null | null | Type: function
Member Name: build_join_conditions
Qualified Name: fenic.api.dataframe._join_utils.build_join_conditions
Docstring: Build left and right join condition lists.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["on", "left_on", "right_on"]
Returns: Tuple[List, List]
Parent Cla... |
function | _has_join_conditions | fenic.api.dataframe._join_utils._has_join_conditions | Check if any join conditions are specified. | null | false | true | 84 | 94 | null | bool | null | [
"on",
"left_on",
"right_on"
] | null | null | Type: function
Member Name: _has_join_conditions
Qualified Name: fenic.api.dataframe._join_utils._has_join_conditions
Docstring: Check if any join conditions are specified.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["on", "left_on", "right_on"]
Returns: bool
Parent Class: none |
function | _validate_join_condition_lengths | fenic.api.dataframe._join_utils._validate_join_condition_lengths | Validate that left_on and right_on have matching lengths. | null | false | true | 96 | 108 | null | None | null | [
"left_on",
"right_on"
] | null | null | Type: function
Member Name: _validate_join_condition_lengths
Qualified Name: fenic.api.dataframe._join_utils._validate_join_condition_lengths
Docstring: Validate that left_on and right_on have matching lengths.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["left_on", "right_on"]
Return... |
module | semantic_extensions | fenic.api.dataframe.semantic_extensions | Semantic extensions for DataFrames providing clustering and semantic join operations. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/dataframe/semantic_extensions.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: semantic_extensions
Qualified Name: fenic.api.dataframe.semantic_extensions
Docstring: Semantic extensions for DataFrames providing clustering and semantic join operations.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | SemGroupedData | fenic.api.dataframe.semantic_extensions.SemGroupedData | Methods for aggregations on a semantically clustered DataFrame. | null | true | false | 29 | 113 | null | null | null | null | [
"BaseGroupedData"
] | null | Type: class
Member Name: SemGroupedData
Qualified Name: fenic.api.dataframe.semantic_extensions.SemGroupedData
Docstring: Methods for aggregations on a semantically clustered DataFrame.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic.api.dataframe.semantic_extensions.SemGroupedData.__init__ | Initialize semantic grouped data.
Args:
df: The DataFrame to group.
by: Column containing embeddings to cluster.
num_clusters: Number of semantic clusters to create. | null | true | false | 32 | 62 | null | null | null | [
"self",
"df",
"by",
"num_clusters"
] | null | SemGroupedData | Type: method
Member Name: __init__
Qualified Name: fenic.api.dataframe.semantic_extensions.SemGroupedData.__init__
Docstring: Initialize semantic grouped data.
Args:
df: The DataFrame to group.
by: Column containing embeddings to cluster.
num_clusters: Number of semantic clusters to create.
Value: none
Ann... |
method | agg | fenic.api.dataframe.semantic_extensions.SemGroupedData.agg | Compute aggregations on semantically clustered data and return the result as a DataFrame.
This method applies aggregate functions to data that has been grouped by semantic similarity,
allowing you to discover patterns and insights across natural language clusters.
Args:
*exprs: Aggregation expressions. Can be:
... | null | true | false | 64 | 113 | null | DataFrame | null | [
"self",
"exprs"
] | null | SemGroupedData | Type: method
Member Name: agg
Qualified Name: fenic.api.dataframe.semantic_extensions.SemGroupedData.agg
Docstring: Compute aggregations on semantically clustered data and return the result as a DataFrame.
This method applies aggregate functions to data that has been grouped by semantic similarity,
allowing you to dis... |
class | SemanticExtensions | fenic.api.dataframe.semantic_extensions.SemanticExtensions | A namespace for semantic dataframe operators. | null | true | false | 116 | 389 | null | null | null | null | [] | null | Type: class
Member Name: SemanticExtensions
Qualified Name: fenic.api.dataframe.semantic_extensions.SemanticExtensions
Docstring: A namespace for semantic dataframe operators.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
method | __init__ | fenic.api.dataframe.semantic_extensions.SemanticExtensions.__init__ | Initialize semantic extensions.
Args:
df: The DataFrame to extend with semantic operations. | null | true | false | 119 | 125 | null | null | null | [
"self",
"df"
] | null | SemanticExtensions | Type: method
Member Name: __init__
Qualified Name: fenic.api.dataframe.semantic_extensions.SemanticExtensions.__init__
Docstring: Initialize semantic extensions.
Args:
df: The DataFrame to extend with semantic operations.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "df"]... |
method | group_by | fenic.api.dataframe.semantic_extensions.SemanticExtensions.group_by | Semantically group rows by clustering an embedding column into the specified number of centroids.
This method is useful when you want to uncover natural themes, topics, or intent in embedded free-form text,
without needing predefined categories.
Args:
by: Column containing embeddings to cluster
num_clusters: ... | null | true | false | 127 | 155 | null | SemGroupedData | null | [
"self",
"by",
"num_clusters"
] | null | SemanticExtensions | Type: method
Member Name: group_by
Qualified Name: fenic.api.dataframe.semantic_extensions.SemanticExtensions.group_by
Docstring: Semantically group rows by clustering an embedding column into the specified number of centroids.
This method is useful when you want to uncover natural themes, topics, or intent in embedde... |
method | join | fenic.api.dataframe.semantic_extensions.SemanticExtensions.join | Performs a semantic join between two DataFrames using a natural language predicate.
That evaluates to either true or false for each potential row pair.
The join works by:
1. Evaluating the provided join_instruction as a boolean predicate for each possible pair of rows
2. Including ONLY the row pairs where the predica... | null | true | false | 157 | 273 | null | DataFrame | null | [
"self",
"other",
"join_instruction",
"examples",
"model_alias"
] | null | SemanticExtensions | Type: method
Member Name: join
Qualified Name: fenic.api.dataframe.semantic_extensions.SemanticExtensions.join
Docstring: Performs a semantic join between two DataFrames using a natural language predicate.
That evaluates to either true or false for each potential row pair.
The join works by:
1. Evaluating the provide... |
method | sim_join | fenic.api.dataframe.semantic_extensions.SemanticExtensions.sim_join | Performs a semantic similarity join between two DataFrames using precomputed text embeddings.
For each row in the left DataFrame, finds the top `k` most semantically similar rows in the right DataFrame
based on the cosine similarity between their text embeddings. This is useful for fuzzy matching tasks when exact matc... | null | true | false | 275 | 384 | null | DataFrame | null | [
"self",
"other",
"left_on",
"right_on",
"k",
"similarity_metric",
"return_similarity_scores"
] | null | SemanticExtensions | Type: method
Member Name: sim_join
Qualified Name: fenic.api.dataframe.semantic_extensions.SemanticExtensions.sim_join
Docstring: Performs a semantic similarity join between two DataFrames using precomputed text embeddings.
For each row in the left DataFrame, finds the top `k` most semantically similar rows in the rig... |
module | io | fenic.api.io | IO module for reading and writing DataFrames to external storage. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/io/__init__.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: io
Qualified Name: fenic.api.io
Docstring: IO module for reading and writing DataFrames to external storage.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | __all__ | fenic.api.io.__all__ | null | null | false | false | 6 | 6 | null | null | ['DataFrameReader', 'DataFrameWriter'] | null | null | null | Type: attribute
Member Name: __all__
Qualified Name: fenic.api.io.__all__
Docstring: none
Value: ['DataFrameReader', 'DataFrameWriter']
Annotation: none
is Public? : false
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
module | reader | fenic.api.io.reader | Reader interface for loading DataFrames from external storage systems. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/io/reader.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: reader
Qualified Name: fenic.api.io.reader
Docstring: Reader interface for loading DataFrames from external storage systems.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | DataFrameReader | fenic.api.io.reader.DataFrameReader | Interface used to load a DataFrame from external storage systems.
Similar to PySpark's DataFrameReader. | null | true | false | 19 | 228 | null | null | null | null | [] | null | Type: class
Member Name: DataFrameReader
Qualified Name: fenic.api.io.reader.DataFrameReader
Docstring: Interface used to load a DataFrame from external storage systems.
Similar to PySpark's DataFrameReader.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class:... |
method | __init__ | fenic.api.io.reader.DataFrameReader.__init__ | Creates a DataFrameReader.
Args:
session_state: The session state to use for reading | null | true | false | 25 | 32 | null | null | null | [
"self",
"session_state"
] | null | DataFrameReader | Type: method
Member Name: __init__
Qualified Name: fenic.api.io.reader.DataFrameReader.__init__
Docstring: Creates a DataFrameReader.
Args:
session_state: The session state to use for reading
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "session_state"]
Returns: none
Pare... |
method | csv | fenic.api.io.reader.DataFrameReader.csv | Load a DataFrame from one or more CSV files.
Args:
paths: A single file path, a glob pattern (e.g., "data/*.csv"), or a list of paths.
schema: (optional) A complete schema definition of column names and their types. Only primitive types are supported.
- For e.g.:
- Schema([ColumnField(name=... | null | true | false | 34 | 115 | null | DataFrame | null | [
"self",
"paths",
"schema",
"merge_schemas"
] | null | DataFrameReader | Type: method
Member Name: csv
Qualified Name: fenic.api.io.reader.DataFrameReader.csv
Docstring: Load a DataFrame from one or more CSV files.
Args:
paths: A single file path, a glob pattern (e.g., "data/*.csv"), or a list of paths.
schema: (optional) A complete schema definition of column names and their types... |
method | parquet | fenic.api.io.reader.DataFrameReader.parquet | Load a DataFrame from one or more Parquet files.
Args:
paths: A single file path, a glob pattern (e.g., "data/*.parquet"), or a list of paths.
merge_schemas: If True, infers and merges schemas across all files.
Missing columns are filled with nulls, and differing types are widened to a common supertype... | null | true | false | 117 | 166 | null | DataFrame | null | [
"self",
"paths",
"merge_schemas"
] | null | DataFrameReader | Type: method
Member Name: parquet
Qualified Name: fenic.api.io.reader.DataFrameReader.parquet
Docstring: Load a DataFrame from one or more Parquet files.
Args:
paths: A single file path, a glob pattern (e.g., "data/*.parquet"), or a list of paths.
merge_schemas: If True, infers and merges schemas across all fi... |
method | _read_file | fenic.api.io.reader.DataFrameReader._read_file | Internal helper method to read files of a specific format.
Args:
paths: Path(s) to the file(s). Can be a single path or a list of paths.
file_format: Format of the file (e.g., "csv", "parquet").
file_extension: Expected file extension (e.g., ".csv", ".parquet").
**options: Additional options to pass to... | null | false | true | 168 | 228 | null | DataFrame | null | [
"self",
"paths",
"file_format",
"file_extension",
"options"
] | null | DataFrameReader | Type: method
Member Name: _read_file
Qualified Name: fenic.api.io.reader.DataFrameReader._read_file
Docstring: Internal helper method to read files of a specific format.
Args:
paths: Path(s) to the file(s). Can be a single path or a list of paths.
file_format: Format of the file (e.g., "csv", "parquet").
f... |
module | writer | fenic.api.io.writer | Writer interface for saving DataFrames to external storage systems. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/io/writer.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: writer
Qualified Name: fenic.api.io.writer
Docstring: Writer interface for saving DataFrames to external storage systems.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | logger | fenic.api.io.writer.logger | null | null | true | false | 18 | 18 | null | null | logging.getLogger(__name__) | null | null | null | Type: attribute
Member Name: logger
Qualified Name: fenic.api.io.writer.logger
Docstring: none
Value: logging.getLogger(__name__)
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | DataFrameWriter | fenic.api.io.writer.DataFrameWriter | Interface used to write a DataFrame to external storage systems.
Similar to PySpark's DataFrameWriter. | null | true | false | 21 | 180 | null | null | null | null | [] | null | Type: class
Member Name: DataFrameWriter
Qualified Name: fenic.api.io.writer.DataFrameWriter
Docstring: Interface used to write a DataFrame to external storage systems.
Similar to PySpark's DataFrameWriter.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: ... |
method | __init__ | fenic.api.io.writer.DataFrameWriter.__init__ | Initialize a DataFrameWriter.
Args:
dataframe: The DataFrame to write. | null | true | false | 27 | 33 | null | null | null | [
"self",
"dataframe"
] | null | DataFrameWriter | Type: method
Member Name: __init__
Qualified Name: fenic.api.io.writer.DataFrameWriter.__init__
Docstring: Initialize a DataFrameWriter.
Args:
dataframe: The DataFrame to write.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "dataframe"]
Returns: none
Parent Class: DataFram... |
method | save_as_table | fenic.api.io.writer.DataFrameWriter.save_as_table | Saves the content of the DataFrame as the specified table.
Args:
table_name: Name of the table to save to
mode: Write mode. Default is "error".
- error: Raises an error if table exists
- append: Appends data to table if it exists
- overwrite: Overwrites existing table
- igno... | null | true | false | 35 | 76 | null | QueryMetrics | null | [
"self",
"table_name",
"mode"
] | null | DataFrameWriter | Type: method
Member Name: save_as_table
Qualified Name: fenic.api.io.writer.DataFrameWriter.save_as_table
Docstring: Saves the content of the DataFrame as the specified table.
Args:
table_name: Name of the table to save to
mode: Write mode. Default is "error".
- error: Raises an error if table exists
... |
method | csv | fenic.api.io.writer.DataFrameWriter.csv | Saves the content of the DataFrame as a single CSV file with comma as the delimiter and headers in the first row.
Args:
file_path: Path to save the CSV file to
mode: Write mode. Default is "overwrite".
- error: Raises an error if file exists
- overwrite: Overwrites the file if it exists
... | null | true | false | 78 | 128 | null | QueryMetrics | null | [
"self",
"file_path",
"mode"
] | null | DataFrameWriter | Type: method
Member Name: csv
Qualified Name: fenic.api.io.writer.DataFrameWriter.csv
Docstring: Saves the content of the DataFrame as a single CSV file with comma as the delimiter and headers in the first row.
Args:
file_path: Path to save the CSV file to
mode: Write mode. Default is "overwrite".
- e... |
method | parquet | fenic.api.io.writer.DataFrameWriter.parquet | Saves the content of the DataFrame as a single Parquet file.
Args:
file_path: Path to save the Parquet file to
mode: Write mode. Default is "overwrite".
- error: Raises an error if file exists
- overwrite: Overwrites the file if it exists
- ignore: Silently ignores operation if file ... | null | true | false | 130 | 180 | null | QueryMetrics | null | [
"self",
"file_path",
"mode"
] | null | DataFrameWriter | Type: method
Member Name: parquet
Qualified Name: fenic.api.io.writer.DataFrameWriter.parquet
Docstring: Saves the content of the DataFrame as a single Parquet file.
Args:
file_path: Path to save the Parquet file to
mode: Write mode. Default is "overwrite".
- error: Raises an error if file exists
... |
module | functions | fenic.api.functions | Functions for working with DataFrame columns. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/functions/__init__.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: functions
Qualified Name: fenic.api.functions
Docstring: Functions for working with DataFrame columns.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | __all__ | fenic.api.functions.__all__ | null | null | false | false | 29 | 64 | null | null | ['semantic', 'text', 'embedding', 'array', 'array_agg', 'avg', 'collect_list', 'coalesce', 'count', 'json', 'markdown', 'max', 'mean', 'min', 'struct', 'sum', 'udf', 'col', 'lit', 'array_size', 'array_contains', 'asc', 'asc_nulls_first', 'asc_nulls_last', 'desc', 'desc_nulls_first', 'desc_nulls_last', 'extract', 'token... | null | null | null | Type: attribute
Member Name: __all__
Qualified Name: fenic.api.functions.__all__
Docstring: none
Value: ['semantic', 'text', 'embedding', 'array', 'array_agg', 'avg', 'collect_list', 'coalesce', 'count', 'json', 'markdown', 'max', 'mean', 'min', 'struct', 'sum', 'udf', 'col', 'lit', 'array_size', 'array_contains', 'asc... |
module | semantic | fenic.api.functions.semantic | Semantic functions for Fenic DataFrames - LLM-based operations. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.0.0-y6d85svd/fenic/src/fenic/api/functions/semantic.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: semantic
Qualified Name: fenic.api.functions.semantic
Docstring: Semantic functions for Fenic DataFrames - LLM-based operations.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
function | map | fenic.api.functions.semantic.map | Applies a natural language instruction to one or more text columns, enabling rich summarization and generation tasks.
Args:
instruction: A string containing the semantic.map prompt.
The instruction must include placeholders in curly braces that reference one or more column names.
These placeholders... | null | true | false | 30 | 87 | null | Column | null | [
"instruction",
"examples",
"model_alias",
"temperature",
"max_output_tokens"
] | null | null | Type: function
Member Name: map
Qualified Name: fenic.api.functions.semantic.map
Docstring: Applies a natural language instruction to one or more text columns, enabling rich summarization and generation tasks.
Args:
instruction: A string containing the semantic.map prompt.
The instruction must include plac... |
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