type stringclasses 5
values | name stringlengths 1 55 | qualified_name stringlengths 5 147 | docstring stringlengths 15 4.52k ⌀ | filepath stringclasses 206
values | is_public bool 2
classes | is_private bool 2
classes | line_start int64 0 1.99k ⌀ | line_end int64 0 2.01k ⌀ | annotation stringclasses 14
values | returns stringclasses 308
values | value stringclasses 152
values | parameters listlengths 0 117 ⌀ | bases listlengths 0 3 ⌀ | parent_class stringclasses 376
values | api_element_summary stringlengths 199 33.8k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
function | parse_pdf | fenic.api.functions.semantic.parse_pdf | Parses a column of PDF paths into markdown.
Note:
Local execution requires the `pdf` extra: `pip install "fenic[pdf]"`.
Returns:
Dataframe: a dataframe with markdown strings for each PDF file.
Args:
column: Column or column name containing the PDF to parse.
model_alias: Optional alias for the languag... | null | true | false | 614 | 674 | null | Column | null | [
"column",
"model_alias",
"page_separator",
"describe_images",
"max_output_tokens",
"request_timeout"
] | null | null | Type: function
Member Name: parse_pdf
Qualified Name: fenic.api.functions.semantic.parse_pdf
Docstring: Parses a column of PDF paths into markdown.
Note:
Local execution requires the `pdf` extra: `pip install "fenic[pdf]"`.
Returns:
Dataframe: a dataframe with markdown strings for each PDF file.
Args:
co... |
module | embedding | fenic.api.functions.embedding | Embedding functions. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/functions/embedding.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: embedding
Qualified Name: fenic.api.functions.embedding
Docstring: Embedding functions.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
function | normalize | fenic.api.functions.embedding.normalize | Normalize embedding vectors to unit length.
Args:
column: Column containing embedding vectors.
Returns:
Column: A column of normalized embedding vectors with the same embedding type.
Notes:
- Normalizes each embedding vector to have unit length (L2 norm = 1)
- Preserves the original embedding model i... | null | true | false | 17 | 51 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: normalize
Qualified Name: fenic.api.functions.embedding.normalize
Docstring: Normalize embedding vectors to unit length.
Args:
column: Column containing embedding vectors.
Returns:
Column: A column of normalized embedding vectors with the same embedding type.
Notes:
- Normaliz... |
function | compute_similarity | fenic.api.functions.embedding.compute_similarity | Compute similarity between embedding vectors using specified metric.
Args:
column: Column containing embedding vectors.
other: Either:
- Another column containing embedding vectors for pairwise similarity
- A query vector (list of floats or numpy array) for similarity with each embedding
... | null | true | false | 54 | 142 | null | Column | null | [
"column",
"other",
"metric"
] | null | null | Type: function
Member Name: compute_similarity
Qualified Name: fenic.api.functions.embedding.compute_similarity
Docstring: Compute similarity between embedding vectors using specified metric.
Args:
column: Column containing embedding vectors.
other: Either:
- Another column containing embedding vecto... |
module | dt | fenic.api.functions.dt | Date and time functions. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/functions/dt.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: dt
Qualified Name: fenic.api.functions.dt
Docstring: Date and time functions.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
function | year | fenic.api.functions.dt.year | Extract the year from a date column.
Args:
column: The column to extract the year from.
Returns:
A Column object with the year extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Example:
```python
# dates: "2025-01-01", "2025-01-02", "2025-01-03"]
df.select(dt.y... | null | true | false | 35 | 55 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: year
Qualified Name: fenic.api.functions.dt.year
Docstring: Extract the year from a date column.
Args:
column: The column to extract the year from.
Returns:
A Column object with the year extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Example:... |
function | month | fenic.api.functions.dt.month | Extract the month from a month column.
Args:
column: The column to extract the month from.
Returns:
A Column object with the month extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Example:
```python
# dates: "2025-01-01", "2025-01-02", "2024-12-03"]
df.select(... | null | true | false | 57 | 77 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: month
Qualified Name: fenic.api.functions.dt.month
Docstring: Extract the month from a month column.
Args:
column: The column to extract the month from.
Returns:
A Column object with the month extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Ex... |
function | day | fenic.api.functions.dt.day | Extract the day from a day column.
Args:
column: The column to extract the day from.
Returns:
A Column object with the day extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Example:
```python
# dates: "2025-01-01", "2025-01-02", "2025-01-03"]
df.select(dt.day(c... | null | true | false | 79 | 99 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: day
Qualified Name: fenic.api.functions.dt.day
Docstring: Extract the day from a day column.
Args:
column: The column to extract the day from.
Returns:
A Column object with the day extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Example:
`... |
function | hour | fenic.api.functions.dt.hour | Extract the hour from a day column.
Args:
column: The column to extract the hour from.
Returns:
A Column object with the hour extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Notes:
This will return 0 for DateType columns.
Example:
```python
# ts: "2025-01-01... | null | true | false | 101 | 124 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: hour
Qualified Name: fenic.api.functions.dt.hour
Docstring: Extract the hour from a day column.
Args:
column: The column to extract the hour from.
Returns:
A Column object with the hour extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Notes:
... |
function | minute | fenic.api.functions.dt.minute | Extract the minute from a day column.
Args:
column: The column to extract the minute from.
Returns:
A Column object with the minute extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Notes:
This will return 0 for DateType columns.
Example:
```python
# ts: "2025... | null | true | false | 126 | 149 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: minute
Qualified Name: fenic.api.functions.dt.minute
Docstring: Extract the minute from a day column.
Args:
column: The column to extract the minute from.
Returns:
A Column object with the minute extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
... |
function | second | fenic.api.functions.dt.second | Extract the hour from a second column.
Args:
column: The column to extract the second from.
Returns:
A Column object with the second extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Notes:
This will return 0 for DateType columns.
Example:
```python
# ts: "202... | null | true | false | 151 | 174 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: second
Qualified Name: fenic.api.functions.dt.second
Docstring: Extract the hour from a second column.
Args:
column: The column to extract the second from.
Returns:
A Column object with the second extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.... |
function | millisecond | fenic.api.functions.dt.millisecond | Extract the hour from a millisecond column.
Args:
column: The column to extract the millisecond from.
Returns:
A Column object with the millisecond extracted.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Notes:
This will return 0 for DateType columns.
Example:
```python... | null | true | false | 176 | 199 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: millisecond
Qualified Name: fenic.api.functions.dt.millisecond
Docstring: Extract the hour from a millisecond column.
Args:
column: The column to extract the millisecond from.
Returns:
A Column object with the millisecond extracted.
Raises:
TypeError: If column type is not a D... |
function | to_date | fenic.api.functions.dt.to_date | Transform a string into a DateType.
Args:
column: The column to transform into a DateType.
format: The format of the date string.
Returns:
A Column object with the DateType transformed.
Raises:
TypeError: If column type is not a StringType.
Notes:
- If format is not provided, the default format ... | null | true | false | 201 | 227 | null | Column | null | [
"column",
"format"
] | null | null | Type: function
Member Name: to_date
Qualified Name: fenic.api.functions.dt.to_date
Docstring: Transform a string into a DateType.
Args:
column: The column to transform into a DateType.
format: The format of the date string.
Returns:
A Column object with the DateType transformed.
Raises:
TypeError: If... |
function | to_timestamp | fenic.api.functions.dt.to_timestamp | Transform a string into a TimestampType.
Args:
column: The column to transform into a TimestampType.
format: The format of the timestamp string.
Returns:
A Column object with the `TimestampType` type, with a UTC timezone. If the provided `format` contains a timezone specifier, the result timestamp value w... | null | true | false | 229 | 255 | null | Column | null | [
"column",
"format"
] | null | null | Type: function
Member Name: to_timestamp
Qualified Name: fenic.api.functions.dt.to_timestamp
Docstring: Transform a string into a TimestampType.
Args:
column: The column to transform into a TimestampType.
format: The format of the timestamp string.
Returns:
A Column object with the `TimestampType` type, w... |
function | now | fenic.api.functions.dt.now | Get the current date and time.
Returns:
A Column object with the current date and time.
The type of the column is TimestampType.
Example:
```python
df.select(dt.now()).to_pydict()
# Output: [{'date': '<current date and time>'}]
``` | null | true | false | 258 | 271 | null | Column | null | [] | null | null | Type: function
Member Name: now
Qualified Name: fenic.api.functions.dt.now
Docstring: Get the current date and time.
Returns:
A Column object with the current date and time.
The type of the column is TimestampType.
Example:
```python
df.select(dt.now()).to_pydict()
# Output: [{'date': '<current da... |
function | current_timestamp | fenic.api.functions.dt.current_timestamp | Get the current date and time.
Returns:
A Column object with the current date and time.
The type of the column is TimestampType in UTC timezone.
Example:
```python
df.select(dt.current_timestamp().alias("cur_ts")).to_pydict()
# Output: {'cur_ts': [datetime.datetime(2025, 9, 26, 10, 0)]}
``` | null | true | false | 273 | 286 | null | Column | null | [] | null | null | Type: function
Member Name: current_timestamp
Qualified Name: fenic.api.functions.dt.current_timestamp
Docstring: Get the current date and time.
Returns:
A Column object with the current date and time.
The type of the column is TimestampType in UTC timezone.
Example:
```python
df.select(dt.current_tim... |
function | current_date | fenic.api.functions.dt.current_date | Get the current date.
Returns:
A Column object with the current date.
The type of the column is DateType.
Example:
```python
df.select(dt.current_date().alias("cur_date")).to_pydict()
# Output: {'cur_date': [datetime.date(2025, 9, 26)]}
``` | null | true | false | 288 | 301 | null | Column | null | [] | null | null | Type: function
Member Name: current_date
Qualified Name: fenic.api.functions.dt.current_date
Docstring: Get the current date.
Returns:
A Column object with the current date.
The type of the column is DateType.
Example:
```python
df.select(dt.current_date().alias("cur_date")).to_pydict()
# Output: ... |
function | date_trunc | fenic.api.functions.dt.date_trunc | Truncate a date to a given unit.
Args:
column: The column to truncate.
unit: The unit to truncate to.
Returns:
A Column object with the date truncated.
Raises:
TypeError: If column type is not a DateType or TimestampType.
ValueError: If unit is not supported, must be one of the supported ones.
N... | null | true | false | 303 | 328 | null | Column | null | [
"column",
"unit"
] | null | null | Type: function
Member Name: date_trunc
Qualified Name: fenic.api.functions.dt.date_trunc
Docstring: Truncate a date to a given unit.
Args:
column: The column to truncate.
unit: The unit to truncate to.
Returns:
A Column object with the date truncated.
Raises:
TypeError: If column type is not a DateTy... |
function | date_add | fenic.api.functions.dt.date_add | Adds the number of days to the date/timestamp column.
Args:
column: The column to add the days to.
days: The number of days to add to the date/timestamp column. If the days is negative, the days will be subtracted.
Returns:
A Column object with the date/timestamp column with the days added.
Raises:
T... | null | true | false | 330 | 356 | null | Column | null | [
"column",
"days"
] | null | null | Type: function
Member Name: date_add
Qualified Name: fenic.api.functions.dt.date_add
Docstring: Adds the number of days to the date/timestamp column.
Args:
column: The column to add the days to.
days: The number of days to add to the date/timestamp column. If the days is negative, the days will be subtracted.
... |
function | date_sub | fenic.api.functions.dt.date_sub | Subtracts the number of days from the date/timestamp column.
Args:
column: The column to subtract the days from.
days: The amount of days to subtract. If the days is negative, the days will be added.
Returns:
A Column object with the date/timestamp column with the days substracted.
Raises:
TypeError:... | null | true | false | 358 | 384 | null | Column | null | [
"column",
"days"
] | null | null | Type: function
Member Name: date_sub
Qualified Name: fenic.api.functions.dt.date_sub
Docstring: Subtracts the number of days from the date/timestamp column.
Args:
column: The column to subtract the days from.
days: The amount of days to subtract. If the days is negative, the days will be added.
Returns:
A... |
function | timestamp_add | fenic.api.functions.dt.timestamp_add | Adds the quantity of the given unit to the timestamp column.
Args:
column: The column to add the quantity to.
quantity: The quantity to add. If the quantity is negative, the quantity will be subtracted.
unit: The unit of the quantity.
Returns:
A Column object with the timestamp column with the quantit... | null | true | false | 386 | 417 | null | Column | null | [
"column",
"quantity",
"unit"
] | null | null | Type: function
Member Name: timestamp_add
Qualified Name: fenic.api.functions.dt.timestamp_add
Docstring: Adds the quantity of the given unit to the timestamp column.
Args:
column: The column to add the quantity to.
quantity: The quantity to add. If the quantity is negative, the quantity will be subtracted.
... |
function | date_format | fenic.api.functions.dt.date_format | Formats a date/timestamp column to a given format.
Args:
column: The column to format.
format: The format to format the column to.
Returns:
A Column object with the date/timestamp column formatted into a string.
Raises:
TypeError: If column type is not a DateType or TimestampType.
Notes:
- The a... | null | true | false | 419 | 444 | null | Column | null | [
"column",
"format"
] | null | null | Type: function
Member Name: date_format
Qualified Name: fenic.api.functions.dt.date_format
Docstring: Formats a date/timestamp column to a given format.
Args:
column: The column to format.
format: The format to format the column to.
Returns:
A Column object with the date/timestamp column formatted into a ... |
function | datediff | fenic.api.functions.dt.datediff | Calculates the number of days between two date/timestamp columns.
Args:
end: To date column to work on.
start: From date column to work on.
Returns:
A Column object with the difference in days between the two date/timestamp columns.
Example:
```python
# end: "2025-01-01", "2025-02-02", "2025-03-0... | null | true | false | 446 | 468 | null | Column | null | [
"end",
"start"
] | null | null | Type: function
Member Name: datediff
Qualified Name: fenic.api.functions.dt.datediff
Docstring: Calculates the number of days between two date/timestamp columns.
Args:
end: To date column to work on.
start: From date column to work on.
Returns:
A Column object with the difference in days between the two d... |
function | timestamp_diff | fenic.api.functions.dt.timestamp_diff | Calculates the difference between two timestamp columns.
Args:
start: The first column to calculate the difference from.
end: The second column to calculate the difference from.
unit: The unit of the difference.
Returns:
A Column object with the difference in the given unit between the two timestamp c... | null | true | false | 470 | 500 | null | Column | null | [
"start",
"end",
"unit"
] | null | null | Type: function
Member Name: timestamp_diff
Qualified Name: fenic.api.functions.dt.timestamp_diff
Docstring: Calculates the difference between two timestamp columns.
Args:
start: The first column to calculate the difference from.
end: The second column to calculate the difference from.
unit: The unit of the... |
function | to_utc_timestamp | fenic.api.functions.dt.to_utc_timestamp | Accepts a Column with [TimestampType] (UTC), interprets each value as wall-clock time in the specified timezone `tz`, and converts it to a timestamp in UTC.
Args:
column: The column containing the timestamp. Will be treated as timezone-agnostic.
tz: A timezone that the input should be converted to.
Returns:
... | null | true | false | 503 | 552 | null | Column | null | [
"column",
"tz"
] | null | null | Type: function
Member Name: to_utc_timestamp
Qualified Name: fenic.api.functions.dt.to_utc_timestamp
Docstring: Accepts a Column with [TimestampType] (UTC), interprets each value as wall-clock time in the specified timezone `tz`, and converts it to a timestamp in UTC.
Args:
column: The column containing the timest... |
function | from_utc_timestamp | fenic.api.functions.dt.from_utc_timestamp | Accepts a Column with [TimestampType] (UTC). For each row, converts the timestamp value to the provided `tz` timezone, then renders that timestamp as UTC without changing the timestamp value. In other words, this function shifts the timestamp by the timezone offset `out = t+offset(t+tz)`.
Args:
column: The colum... | null | true | false | 554 | 603 | null | Column | null | [
"column",
"tz"
] | null | null | Type: function
Member Name: from_utc_timestamp
Qualified Name: fenic.api.functions.dt.from_utc_timestamp
Docstring: Accepts a Column with [TimestampType] (UTC). For each row, converts the timestamp value to the provided `tz` timezone, then renders that timestamp as UTC without changing the timestamp value. In other w... |
module | core | fenic.api.functions.core | Core functions for Fenic DataFrames. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/functions/core.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: core
Qualified Name: fenic.api.functions.core
Docstring: Core functions for Fenic DataFrames.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
function | col | fenic.api.functions.core.col | Creates a Column expression referencing a column in the DataFrame.
Args:
col_name: Name of the column to reference
Returns:
A Column expression for the specified column
Raises:
TypeError: If colName is not a string | null | true | false | 17 | 30 | null | Column | null | [
"col_name"
] | null | null | Type: function
Member Name: col
Qualified Name: fenic.api.functions.core.col
Docstring: Creates a Column expression referencing a column in the DataFrame.
Args:
col_name: Name of the column to reference
Returns:
A Column expression for the specified column
Raises:
TypeError: If colName is not a string
Va... |
function | null | fenic.api.functions.core.null | Creates a Column expression representing a null value of the specified data type.
Regardless of the data type, the column will contain a null (None) value.
This function is useful for creating columns with null values of a particular type.
Args:
data_type: The data type of the null value
Returns:
A Column ex... | null | true | false | 32 | 64 | null | Column | null | [
"data_type"
] | null | null | Type: function
Member Name: null
Qualified Name: fenic.api.functions.core.null
Docstring: Creates a Column expression representing a null value of the specified data type.
Regardless of the data type, the column will contain a null (None) value.
This function is useful for creating columns with null values of a partic... |
function | empty | fenic.api.functions.core.empty | Creates a Column expression representing an empty value of the given type.
- If the data type is `ArrayType(...)`, the empty value will be an empty array.
- If the data type is `StructType(...)`, the empty value will be an instance of the struct type with all fields set to `None`.
- For all other data types, the empty... | null | true | false | 66 | 106 | null | Column | null | [
"data_type"
] | null | null | Type: function
Member Name: empty
Qualified Name: fenic.api.functions.core.empty
Docstring: Creates a Column expression representing an empty value of the given type.
- If the data type is `ArrayType(...)`, the empty value will be an empty array.
- If the data type is `StructType(...)`, the empty value will be an inst... |
function | lit | fenic.api.functions.core.lit | Creates a Column expression representing a literal value.
Column Data Type must be inferrable from the value:
- Cannot be used to create a columm with the literal value `None`. Use `null(data_type)` instead.
- Cannot be used to create a columm with the literal value `[]`. Use `empty(ArrayType(...))` instead.
... | null | true | false | 108 | 136 | null | Column | null | [
"value"
] | null | null | Type: function
Member Name: lit
Qualified Name: fenic.api.functions.core.lit
Docstring: Creates a Column expression representing a literal value.
Column Data Type must be inferrable from the value:
- Cannot be used to create a columm with the literal value `None`. Use `null(data_type)` instead.
- Cannot be use... |
function | tool_param | fenic.api.functions.core.tool_param | Creates an unresolved literal placeholder column with a declared data type.
A placeholder argument for a DataFrame, representing a literal value to be provided at execution time.
If no value is supplied, it defaults to null. Enables parameterized views and macros over fenic DataFrames.
Notes:
Supports only Primi... | null | true | false | 140 | 192 | null | Column | null | [
"parameter_name",
"data_type"
] | null | null | Type: function
Member Name: tool_param
Qualified Name: fenic.api.functions.core.tool_param
Docstring: Creates an unresolved literal placeholder column with a declared data type.
A placeholder argument for a DataFrame, representing a literal value to be provided at execution time.
If no value is supplied, it defaults ... |
module | markdown | fenic.api.functions.markdown | Markdown functions. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/functions/markdown.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: markdown
Qualified Name: fenic.api.functions.markdown
Docstring: Markdown functions.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
function | to_json | fenic.api.functions.markdown.to_json | Converts a column of Markdown-formatted strings into a hierarchical JSON representation.
Args:
column (ColumnOrName): Input column containing Markdown strings.
Returns:
Column: A column of JSON-formatted strings representing the structured document tree.
Notes:
- This function parses Markdown into a stru... | null | true | false | 16 | 54 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: to_json
Qualified Name: fenic.api.functions.markdown.to_json
Docstring: Converts a column of Markdown-formatted strings into a hierarchical JSON representation.
Args:
column (ColumnOrName): Input column containing Markdown strings.
Returns:
Column: A column of JSON-formatted string... |
function | get_code_blocks | fenic.api.functions.markdown.get_code_blocks | Extracts all code blocks from a column of Markdown-formatted strings.
Args:
column (ColumnOrName): Input column containing Markdown strings.
language_filter (Optional[str]): Optional language filter to extract only code blocks with a specific language. By default, all code blocks are extracted.
Returns:
C... | null | true | false | 56 | 92 | null | Column | null | [
"column",
"language_filter"
] | null | null | Type: function
Member Name: get_code_blocks
Qualified Name: fenic.api.functions.markdown.get_code_blocks
Docstring: Extracts all code blocks from a column of Markdown-formatted strings.
Args:
column (ColumnOrName): Input column containing Markdown strings.
language_filter (Optional[str]): Optional language fil... |
function | generate_toc | fenic.api.functions.markdown.generate_toc | Generates a table of contents from markdown headings.
Args:
column (ColumnOrName): Input column containing Markdown strings.
max_level (Optional[int]): Maximum heading level to include in the TOC (1-6).
Defaults to 6 (all levels).
Returns:
Column: A column of Markdown-formatte... | null | true | false | 95 | 132 | null | Column | null | [
"column",
"max_level"
] | null | null | Type: function
Member Name: generate_toc
Qualified Name: fenic.api.functions.markdown.generate_toc
Docstring: Generates a table of contents from markdown headings.
Args:
column (ColumnOrName): Input column containing Markdown strings.
max_level (Optional[int]): Maximum heading level to include in the TOC (1-6)... |
function | extract_header_chunks | fenic.api.functions.markdown.extract_header_chunks | Splits markdown documents into logical chunks based on heading hierarchy.
Args:
column (ColumnOrName): Input column containing Markdown strings.
header_level (int): Heading level to split on (1-6). Creates a new chunk at every
heading of this level, including all nested content and subs... | null | true | false | 135 | 212 | null | Column | null | [
"column",
"header_level"
] | null | null | Type: function
Member Name: extract_header_chunks
Qualified Name: fenic.api.functions.markdown.extract_header_chunks
Docstring: Splits markdown documents into logical chunks based on heading hierarchy.
Args:
column (ColumnOrName): Input column containing Markdown strings.
header_level (int): Heading level to s... |
module | text | fenic.api.functions.text | Text manipulation functions for Fenic DataFrames. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/functions/text.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: text
Qualified Name: fenic.api.functions.text
Docstring: Text manipulation functions for Fenic DataFrames.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
function | extract | fenic.api.functions.text.extract | Extracts structured data from text using template-based pattern matching.
Matches each string in the input column against a template pattern with named
placeholders. Each placeholder can specify a format rule to handle different
data types within the text.
Args:
column: Input text column to extract from
templ... | null | true | false | 51 | 104 | null | Column | null | [
"column",
"template"
] | null | null | Type: function
Member Name: extract
Qualified Name: fenic.api.functions.text.extract
Docstring: Extracts structured data from text using template-based pattern matching.
Matches each string in the input column against a template pattern with named
placeholders. Each placeholder can specify a format rule to handle diff... |
function | recursive_character_chunk | fenic.api.functions.text.recursive_character_chunk | Chunks a string column into chunks of a specified size (in characters) with an optional overlap.
The chunking is performed recursively, attempting to preserve the underlying structure of the text
by splitting on natural boundaries (paragraph breaks, sentence breaks, etc.) to maintain context.
By default, these charact... | null | true | false | 106 | 165 | null | Column | null | [
"column",
"chunk_size",
"chunk_overlap_percentage",
"chunking_character_set_custom_characters"
] | null | null | Type: function
Member Name: recursive_character_chunk
Qualified Name: fenic.api.functions.text.recursive_character_chunk
Docstring: Chunks a string column into chunks of a specified size (in characters) with an optional overlap.
The chunking is performed recursively, attempting to preserve the underlying structure of ... |
function | recursive_word_chunk | fenic.api.functions.text.recursive_word_chunk | Chunks a string column into chunks of a specified size (in words) with an optional overlap.
The chunking is performed recursively, attempting to preserve the underlying structure of the text
by splitting on natural boundaries (paragraph breaks, sentence breaks, etc.) to maintain context.
By default, these characters a... | null | true | false | 168 | 227 | null | Column | null | [
"column",
"chunk_size",
"chunk_overlap_percentage",
"chunking_character_set_custom_characters"
] | null | null | Type: function
Member Name: recursive_word_chunk
Qualified Name: fenic.api.functions.text.recursive_word_chunk
Docstring: Chunks a string column into chunks of a specified size (in words) with an optional overlap.
The chunking is performed recursively, attempting to preserve the underlying structure of the text
by spl... |
function | recursive_token_chunk | fenic.api.functions.text.recursive_token_chunk | Chunks a string column into chunks of a specified size (in tokens) with an optional overlap.
The chunking is performed recursively, attempting to preserve the underlying structure of the text
by splitting on natural boundaries (paragraph breaks, sentence breaks, etc.) to maintain context.
By default, these characters ... | null | true | false | 230 | 289 | null | Column | null | [
"column",
"chunk_size",
"chunk_overlap_percentage",
"chunking_character_set_custom_characters"
] | null | null | Type: function
Member Name: recursive_token_chunk
Qualified Name: fenic.api.functions.text.recursive_token_chunk
Docstring: Chunks a string column into chunks of a specified size (in tokens) with an optional overlap.
The chunking is performed recursively, attempting to preserve the underlying structure of the text
by ... |
function | character_chunk | fenic.api.functions.text.character_chunk | Chunks a string column into chunks of a specified size (in characters) with an optional overlap.
The chunking is done by applying a simple sliding window across the text to create chunks of equal size.
This approach does not attempt to preserve the underlying structure of the text.
Args:
column: The input string ... | null | true | false | 292 | 324 | null | Column | null | [
"column",
"chunk_size",
"chunk_overlap_percentage"
] | null | null | Type: function
Member Name: character_chunk
Qualified Name: fenic.api.functions.text.character_chunk
Docstring: Chunks a string column into chunks of a specified size (in characters) with an optional overlap.
The chunking is done by applying a simple sliding window across the text to create chunks of equal size.
This ... |
function | word_chunk | fenic.api.functions.text.word_chunk | Chunks a string column into chunks of a specified size (in words) with an optional overlap.
The chunking is done by applying a simple sliding window across the text to create chunks of equal size.
This approach does not attempt to preserve the underlying structure of the text.
Args:
column: The input string colum... | null | true | false | 327 | 359 | null | Column | null | [
"column",
"chunk_size",
"chunk_overlap_percentage"
] | null | null | Type: function
Member Name: word_chunk
Qualified Name: fenic.api.functions.text.word_chunk
Docstring: Chunks a string column into chunks of a specified size (in words) with an optional overlap.
The chunking is done by applying a simple sliding window across the text to create chunks of equal size.
This approach does n... |
function | token_chunk | fenic.api.functions.text.token_chunk | Chunks a string column into chunks of a specified size (in tokens) with an optional overlap.
The chunking is done by applying a simple sliding window across the text to create chunks of equal size.
This approach does not attempt to preserve the underlying structure of the text.
Args:
column: The input string colu... | null | true | false | 362 | 394 | null | Column | null | [
"column",
"chunk_size",
"chunk_overlap_percentage"
] | null | null | Type: function
Member Name: token_chunk
Qualified Name: fenic.api.functions.text.token_chunk
Docstring: Chunks a string column into chunks of a specified size (in tokens) with an optional overlap.
The chunking is done by applying a simple sliding window across the text to create chunks of equal size.
This approach doe... |
function | count_tokens | fenic.api.functions.text.count_tokens | Returns the number of tokens in a string using OpenAI's cl100k_base encoding (tiktoken).
Args:
column: The input string column.
Returns:
Column: A column with the token counts for each input string.
Example: Count tokens in text
```python
# Count tokens in a text column
df.select(text.count_token... | null | true | false | 397 | 417 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: count_tokens
Qualified Name: fenic.api.functions.text.count_tokens
Docstring: Returns the number of tokens in a string using OpenAI's cl100k_base encoding (tiktoken).
Args:
column: The input string column.
Returns:
Column: A column with the token counts for each input string.
Exam... |
function | concat | fenic.api.functions.text.concat | Concatenates multiple columns or strings into a single string.
Args:
*cols: Columns or strings to concatenate
Returns:
Column: A column containing the concatenated strings
Example: Concatenate columns
```python
# Concatenate two columns with a space in between
df.select(text.concat(col("col1"), l... | null | true | false | 420 | 449 | null | Column | null | [
"cols"
] | null | null | Type: function
Member Name: concat
Qualified Name: fenic.api.functions.text.concat
Docstring: Concatenates multiple columns or strings into a single string.
Args:
*cols: Columns or strings to concatenate
Returns:
Column: A column containing the concatenated strings
Example: Concatenate columns
```python
... |
function | parse_transcript | fenic.api.functions.text.parse_transcript | Parses a transcript from text to a structured format with unified schema.
Converts transcript text in various formats (srt, webvtt, generic) to a standardized structure
with fields: index, speaker, start_time, end_time, duration, content, format.
All timestamps are returned as floating-point seconds from the start.
A... | null | true | false | 453 | 486 | null | Column | null | [
"column",
"format"
] | null | null | Type: function
Member Name: parse_transcript
Qualified Name: fenic.api.functions.text.parse_transcript
Docstring: Parses a transcript from text to a structured format with unified schema.
Converts transcript text in various formats (srt, webvtt, generic) to a standardized structure
with fields: index, speaker, start_t... |
function | concat_ws | fenic.api.functions.text.concat_ws | Concatenates multiple columns or strings into a single string with a separator.
Args:
separator: The separator to use
*cols: Columns or strings to concatenate
Returns:
Column: A column containing the concatenated strings
Example: Concatenate with comma separator
```python
# Concatenate columns wi... | null | true | false | 489 | 521 | null | Column | null | [
"separator",
"cols"
] | null | null | Type: function
Member Name: concat_ws
Qualified Name: fenic.api.functions.text.concat_ws
Docstring: Concatenates multiple columns or strings into a single string with a separator.
Args:
separator: The separator to use
*cols: Columns or strings to concatenate
Returns:
Column: A column containing the concat... |
function | array_join | fenic.api.functions.text.array_join | Joins an array of strings into a single string with a delimiter.
Args:
column: The column to join
delimiter: The delimiter to use
Returns:
Column: A column containing the joined strings
Example: Join array with comma
```python
# Join array elements with comma
df.select(text.array_join(col(... | null | true | false | 524 | 542 | null | Column | null | [
"column",
"delimiter"
] | null | null | Type: function
Member Name: array_join
Qualified Name: fenic.api.functions.text.array_join
Docstring: Joins an array of strings into a single string with a delimiter.
Args:
column: The column to join
delimiter: The delimiter to use
Returns:
Column: A column containing the joined strings
Example: Join ... |
function | replace | fenic.api.functions.text.replace | Replace all occurrences of a pattern with a new string, treating pattern as a literal string.
This method creates a new string column with all occurrences of the specified pattern
replaced with a new string. The pattern is treated as a literal string, not a regular expression.
If either search or replace is a column e... | null | true | false | 545 | 588 | null | Column | null | [
"src",
"search",
"replace"
] | null | null | Type: function
Member Name: replace
Qualified Name: fenic.api.functions.text.replace
Docstring: Replace all occurrences of a pattern with a new string, treating pattern as a literal string.
This method creates a new string column with all occurrences of the specified pattern
replaced with a new string. The pattern is ... |
function | regexp_replace | fenic.api.functions.text.regexp_replace | Replace all occurrences of a pattern with a new string, treating pattern as a regular expression.
This method creates a new string column with all occurrences of the specified pattern
replaced with a new string. The pattern is treated as a regular expression.
If either pattern or replacement is a column expression, th... | null | true | false | 591 | 645 | null | Column | null | [
"src",
"pattern",
"replacement"
] | null | null | Type: function
Member Name: regexp_replace
Qualified Name: fenic.api.functions.text.regexp_replace
Docstring: Replace all occurrences of a pattern with a new string, treating pattern as a regular expression.
This method creates a new string column with all occurrences of the specified pattern
replaced with a new strin... |
function | regexp_count | fenic.api.functions.text.regexp_count | Count the number of times a regex pattern is matched in a string.
Returns the count of matches for each string in the column.
Args:
src: The input string column or column name
pattern: The regex pattern to count (can be a string literal or column expression)
Returns:
Column: An integer column containing ... | null | true | false | 648 | 689 | null | Column | null | [
"src",
"pattern"
] | null | null | Type: function
Member Name: regexp_count
Qualified Name: fenic.api.functions.text.regexp_count
Docstring: Count the number of times a regex pattern is matched in a string.
Returns the count of matches for each string in the column.
Args:
src: The input string column or column name
pattern: The regex pattern t... |
function | regexp_extract | fenic.api.functions.text.regexp_extract | Extract a specific regex group from a string.
Extracts a capture group matched by the regex pattern. Group 0 is the entire match, group 1+ are capture groups.
If the pattern/group has multiple matches within the same string, the result will be the first match. Use `regexp_extract_all`
to extract all matches.
Args:
... | null | true | false | 692 | 741 | null | Column | null | [
"src",
"pattern",
"idx"
] | null | null | Type: function
Member Name: regexp_extract
Qualified Name: fenic.api.functions.text.regexp_extract
Docstring: Extract a specific regex group from a string.
Extracts a capture group matched by the regex pattern. Group 0 is the entire match, group 1+ are capture groups.
If the pattern/group has multiple matches within t... |
function | regexp_extract_all | fenic.api.functions.text.regexp_extract_all | Extract all strings matching a regex pattern, optionally from a specific group.
Returns an array of all matches. Group 0 is the entire match, group 1+ are capture groups.
If the pattern/group has multiple matches within the same string, the result will be an array of all matches.
Args:
src: The input string colum... | null | true | false | 744 | 795 | null | Column | null | [
"src",
"pattern",
"idx"
] | null | null | Type: function
Member Name: regexp_extract_all
Qualified Name: fenic.api.functions.text.regexp_extract_all
Docstring: Extract all strings matching a regex pattern, optionally from a specific group.
Returns an array of all matches. Group 0 is the entire match, group 1+ are capture groups.
If the pattern/group has multi... |
function | regexp_instr | fenic.api.functions.text.regexp_instr | Find the 1-based position of the first regex match in a string.
Returns the position (1-based) of the first substring matching the pattern.
Returns 0 if no match is found.
Args:
src: The input string column or column name
pattern: The regex pattern to search for
idx: The group index to locate (default: 0 ... | null | true | false | 798 | 849 | null | Column | null | [
"src",
"pattern",
"idx"
] | null | null | Type: function
Member Name: regexp_instr
Qualified Name: fenic.api.functions.text.regexp_instr
Docstring: Find the 1-based position of the first regex match in a string.
Returns the position (1-based) of the first substring matching the pattern.
Returns 0 if no match is found.
Args:
src: The input string column o... |
function | regexp_substr | fenic.api.functions.text.regexp_substr | Extract the first substring matching a regex pattern.
Returns the first substring that matches the pattern. Returns null if no match is found.
Args:
src: The input string column or column name
pattern: The regex pattern to search for
Returns:
Column: A string column containing the first match (null if no... | null | true | false | 852 | 893 | null | Column | null | [
"src",
"pattern"
] | null | null | Type: function
Member Name: regexp_substr
Qualified Name: fenic.api.functions.text.regexp_substr
Docstring: Extract the first substring matching a regex pattern.
Returns the first substring that matches the pattern. Returns null if no match is found.
Args:
src: The input string column or column name
pattern: ... |
function | split | fenic.api.functions.text.split | Split a string column into an array using a regular expression pattern.
This method creates an array column by splitting each value in the input string column
at matches of the specified regular expression pattern.
Args:
src: The input string column or column name to split
pattern: The regular expression patt... | null | true | false | 896 | 926 | null | Column | null | [
"src",
"pattern",
"limit"
] | null | null | Type: function
Member Name: split
Qualified Name: fenic.api.functions.text.split
Docstring: Split a string column into an array using a regular expression pattern.
This method creates an array column by splitting each value in the input string column
at matches of the specified regular expression pattern.
Args:
s... |
function | split_part | fenic.api.functions.text.split_part | Split a string and return a specific part using 1-based indexing.
Splits each string by a delimiter and returns the specified part.
If the delimiter is a column expression, the split operation is performed dynamically
using the delimiter values from that column.
Behavior:
- If any input is null, returns null
- If par... | null | true | false | 929 | 990 | null | Column | null | [
"src",
"delimiter",
"part_number"
] | null | null | Type: function
Member Name: split_part
Qualified Name: fenic.api.functions.text.split_part
Docstring: Split a string and return a specific part using 1-based indexing.
Splits each string by a delimiter and returns the specified part.
If the delimiter is a column expression, the split operation is performed dynamically... |
function | upper | fenic.api.functions.text.upper | Convert all characters in a string column to uppercase.
Args:
column: The input string column to convert to uppercase
Returns:
Column: A column containing the uppercase strings
Example: Convert text to uppercase
```python
# Convert all text in the name column to uppercase
df.select(text.upper(col... | null | true | false | 993 | 1,011 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: upper
Qualified Name: fenic.api.functions.text.upper
Docstring: Convert all characters in a string column to uppercase.
Args:
column: The input string column to convert to uppercase
Returns:
Column: A column containing the uppercase strings
Example: Convert text to uppercase
`... |
function | lower | fenic.api.functions.text.lower | Convert all characters in a string column to lowercase.
Args:
column: The input string column to convert to lowercase
Returns:
Column: A column containing the lowercase strings
Example: Convert text to lowercase
```python
# Convert all text in the name column to lowercase
df.select(text.lower(col... | null | true | false | 1,014 | 1,032 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: lower
Qualified Name: fenic.api.functions.text.lower
Docstring: Convert all characters in a string column to lowercase.
Args:
column: The input string column to convert to lowercase
Returns:
Column: A column containing the lowercase strings
Example: Convert text to lowercase
`... |
function | title_case | fenic.api.functions.text.title_case | Convert the first character of each word in a string column to uppercase.
Args:
column: The input string column to convert to title case
Returns:
Column: A column containing the title case strings
Example: Convert text to title case
```python
# Convert text in the name column to title case
df.sel... | null | true | false | 1,035 | 1,053 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: title_case
Qualified Name: fenic.api.functions.text.title_case
Docstring: Convert the first character of each word in a string column to uppercase.
Args:
column: The input string column to convert to title case
Returns:
Column: A column containing the title case strings
Example: C... |
function | trim | fenic.api.functions.text.trim | Remove whitespace from both sides of strings in a column.
This function removes all whitespace characters (spaces, tabs, newlines) from
both the beginning and end of each string in the column.
Args:
column: The input string column or column name to trim
Returns:
Column: A column containing the trimmed string... | null | true | false | 1,056 | 1,077 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: trim
Qualified Name: fenic.api.functions.text.trim
Docstring: Remove whitespace from both sides of strings in a column.
This function removes all whitespace characters (spaces, tabs, newlines) from
both the beginning and end of each string in the column.
Args:
column: The input string ... |
function | btrim | fenic.api.functions.text.btrim | Remove specified characters from both sides of strings in a column.
This function removes all occurrences of the specified characters from
both the beginning and end of each string in the column.
If trim is a column expression, the characters to remove are determined dynamically
from the values in that column.
Args:
... | null | true | false | 1,080 | 1,117 | null | Column | null | [
"col",
"trim"
] | null | null | Type: function
Member Name: btrim
Qualified Name: fenic.api.functions.text.btrim
Docstring: Remove specified characters from both sides of strings in a column.
This function removes all occurrences of the specified characters from
both the beginning and end of each string in the column.
If trim is a column expression,... |
function | ltrim | fenic.api.functions.text.ltrim | Remove whitespace from the start of strings in a column.
This function removes all whitespace characters (spaces, tabs, newlines) from
the beginning of each string in the column.
Args:
col: The input string column or column name to trim
Returns:
Column: A column containing the left-trimmed strings
Example: ... | null | true | false | 1,120 | 1,141 | null | Column | null | [
"col"
] | null | null | Type: function
Member Name: ltrim
Qualified Name: fenic.api.functions.text.ltrim
Docstring: Remove whitespace from the start of strings in a column.
This function removes all whitespace characters (spaces, tabs, newlines) from
the beginning of each string in the column.
Args:
col: The input string column or colum... |
function | rtrim | fenic.api.functions.text.rtrim | Remove whitespace from the end of strings in a column.
This function removes all whitespace characters (spaces, tabs, newlines) from
the end of each string in the column.
Args:
col: The input string column or column name to trim
Returns:
Column: A column containing the right-trimmed strings
Example: Remove ... | null | true | false | 1,144 | 1,165 | null | Column | null | [
"col"
] | null | null | Type: function
Member Name: rtrim
Qualified Name: fenic.api.functions.text.rtrim
Docstring: Remove whitespace from the end of strings in a column.
This function removes all whitespace characters (spaces, tabs, newlines) from
the end of each string in the column.
Args:
col: The input string column or column name t... |
function | length | fenic.api.functions.text.length | Calculate the character length of each string in the column.
Args:
column: The input string column to calculate lengths for
Returns:
Column: A column containing the length of each string in characters
Example: Get string lengths
```python
# Get the length of each string in the name column
df.sele... | null | true | false | 1,168 | 1,186 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: length
Qualified Name: fenic.api.functions.text.length
Docstring: Calculate the character length of each string in the column.
Args:
column: The input string column to calculate lengths for
Returns:
Column: A column containing the length of each string in characters
Example: Get s... |
function | byte_length | fenic.api.functions.text.byte_length | Calculate the byte length of each string in the column.
Args:
column: The input string column to calculate byte lengths for
Returns:
Column: A column containing the byte length of each string
Example: Get byte lengths
```python
# Get the byte length of each string in the name column
df.select(tex... | null | true | false | 1,189 | 1,207 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: byte_length
Qualified Name: fenic.api.functions.text.byte_length
Docstring: Calculate the byte length of each string in the column.
Args:
column: The input string column to calculate byte lengths for
Returns:
Column: A column containing the byte length of each string
Example: Get ... |
function | jinja | fenic.api.functions.text.jinja | Render a Jinja template using values from the specified columns.
This function evaluates a Jinja2 template string for each row, using the provided
columns as template variables. Only a subset of Jinja2 features is supported.
Args:
jinja_template: A Jinja2 template string to render for each row.
... | null | true | false | 1,210 | 1,311 | null | Column | null | [
"jinja_template",
"strict",
"columns"
] | null | null | Type: function
Member Name: jinja
Qualified Name: fenic.api.functions.text.jinja
Docstring: Render a Jinja template using values from the specified columns.
This function evaluates a Jinja2 template string for each row, using the provided
columns as template variables. Only a subset of Jinja2 features is supported.
A... |
function | compute_fuzzy_ratio | fenic.api.functions.text.compute_fuzzy_ratio | Compute the similarity between two strings using a fuzzy string matching algorithm.
This function computes a fuzzy similarity score between two string columns (or a string column
and a literal string) for each row. It supports multiple well-known string similarity metrics,
including Levenshtein, Damerau-Levenshtein, J... | null | true | false | 1,313 | 1,360 | null | Column | null | [
"column",
"other",
"method"
] | null | null | Type: function
Member Name: compute_fuzzy_ratio
Qualified Name: fenic.api.functions.text.compute_fuzzy_ratio
Docstring: Compute the similarity between two strings using a fuzzy string matching algorithm.
This function computes a fuzzy similarity score between two string columns (or a string column
and a literal string... |
function | compute_fuzzy_token_sort_ratio | fenic.api.functions.text.compute_fuzzy_token_sort_ratio | Compute fuzzy similarity after sorting tokens in each string.
Tokenizes strings by whitespace, sorts tokens alphabetically, concatenates
them back into a string, then applies the specified similarity metric.
Useful for comparing strings where word order doesn't matter.
Based on https://rapidfuzz.github.io/RapidFuzz/U... | null | true | false | 1,362 | 1,393 | null | Column | null | [
"column",
"other",
"method"
] | null | null | Type: function
Member Name: compute_fuzzy_token_sort_ratio
Qualified Name: fenic.api.functions.text.compute_fuzzy_token_sort_ratio
Docstring: Compute fuzzy similarity after sorting tokens in each string.
Tokenizes strings by whitespace, sorts tokens alphabetically, concatenates
them back into a string, then applies th... |
function | compute_fuzzy_token_set_ratio | fenic.api.functions.text.compute_fuzzy_token_set_ratio | Compute fuzzy similarity using token set comparison.
Tokenizes strings by whitespace, creates sets of unique tokens, then
compares three combinations: diff1 vs diff2, intersection vs left set,
and intersection vs right set. Returns the maximum similarity score.
Useful for comparing strings where both word order and du... | null | true | false | 1,395 | 1,432 | null | Column | null | [
"column",
"other",
"method"
] | null | null | Type: function
Member Name: compute_fuzzy_token_set_ratio
Qualified Name: fenic.api.functions.text.compute_fuzzy_token_set_ratio
Docstring: Compute fuzzy similarity using token set comparison.
Tokenizes strings by whitespace, creates sets of unique tokens, then
compares three combinations: diff1 vs diff2, intersection... |
module | builtin | fenic.api.functions.builtin | Built-in functions for Fenic DataFrames. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/functions/builtin.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: builtin
Qualified Name: fenic.api.functions.builtin
Docstring: Built-in functions for Fenic DataFrames.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
function | sum | fenic.api.functions.builtin.sum | Aggregate function: returns the sum of all values in the specified column.
Args:
column: Column or column name to compute the sum of
Returns:
A Column expression representing the sum aggregation
Raises:
TypeError: If column is not a Column or string | null | true | false | 43 | 58 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: sum
Qualified Name: fenic.api.functions.builtin.sum
Docstring: Aggregate function: returns the sum of all values in the specified column.
Args:
column: Column or column name to compute the sum of
Returns:
A Column expression representing the sum aggregation
Raises:
TypeError: ... |
function | sum_distinct | fenic.api.functions.builtin.sum_distinct | Aggregate function: returns the sum of distinct numeric values in the specified column.
Args:
column: Column or column name to compute the sum of distinct values
Returns:
A Column expression representing the sum-distinct aggregation
Example: Sum of distinct values per group
```python
# Sample input
... | null | true | false | 61 | 109 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: sum_distinct
Qualified Name: fenic.api.functions.builtin.sum_distinct
Docstring: Aggregate function: returns the sum of distinct numeric values in the specified column.
Args:
column: Column or column name to compute the sum of distinct values
Returns:
A Column expression representi... |
function | avg | fenic.api.functions.builtin.avg | Aggregate function: returns the average (mean) of all values in the specified column. Applies to numeric and embedding types.
Args:
column: Column or column name to compute the average of
Returns:
A Column expression representing the average aggregation
Raises:
TypeError: If column is not a Column or str... | null | true | false | 112 | 127 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: avg
Qualified Name: fenic.api.functions.builtin.avg
Docstring: Aggregate function: returns the average (mean) of all values in the specified column. Applies to numeric and embedding types.
Args:
column: Column or column name to compute the average of
Returns:
A Column expression re... |
function | mean | fenic.api.functions.builtin.mean | Aggregate function: returns the mean (average) of all values in the specified column.
Alias for avg().
Args:
column: Column or column name to compute the mean of
Returns:
A Column expression representing the mean aggregation
Raises:
TypeError: If column is not a Column or string | null | true | false | 130 | 147 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: mean
Qualified Name: fenic.api.functions.builtin.mean
Docstring: Aggregate function: returns the mean (average) of all values in the specified column.
Alias for avg().
Args:
column: Column or column name to compute the mean of
Returns:
A Column expression representing the mean agg... |
function | min | fenic.api.functions.builtin.min | Aggregate function: returns the minimum value in the specified column.
Args:
column: Column or column name to compute the minimum of
Returns:
A Column expression representing the minimum aggregation
Raises:
TypeError: If column is not a Column or string | null | true | false | 150 | 165 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: min
Qualified Name: fenic.api.functions.builtin.min
Docstring: Aggregate function: returns the minimum value in the specified column.
Args:
column: Column or column name to compute the minimum of
Returns:
A Column expression representing the minimum aggregation
Raises:
TypeErr... |
function | max | fenic.api.functions.builtin.max | Aggregate function: returns the maximum value in the specified column.
Args:
column: Column or column name to compute the maximum of
Returns:
A Column expression representing the maximum aggregation
Raises:
TypeError: If column is not a Column or string | null | true | false | 168 | 183 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: max
Qualified Name: fenic.api.functions.builtin.max
Docstring: Aggregate function: returns the maximum value in the specified column.
Args:
column: Column or column name to compute the maximum of
Returns:
A Column expression representing the maximum aggregation
Raises:
TypeErr... |
function | count | fenic.api.functions.builtin.count | Aggregate function: returns the count of non-null values in the specified column.
Args:
column: Column or column name to count values in
Returns:
A Column expression representing the count aggregation
Raises:
TypeError: If column is not a Column or string | null | true | false | 186 | 203 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: count
Qualified Name: fenic.api.functions.builtin.count
Docstring: Aggregate function: returns the count of non-null values in the specified column.
Args:
column: Column or column name to count values in
Returns:
A Column expression representing the count aggregation
Raises:
T... |
function | count_distinct | fenic.api.functions.builtin.count_distinct | Aggregate function: returns the number of distinct non-null rows across one or more columns.
Behavior: Any row where one or more inputs is null is ignored.
Args:
*cols: One or more columns or column names to include in the distinct count.
Returns:
A Column expression representing the count-distinct aggregati... | null | true | false | 206 | 276 | null | Column | null | [
"cols"
] | null | null | Type: function
Member Name: count_distinct
Qualified Name: fenic.api.functions.builtin.count_distinct
Docstring: Aggregate function: returns the number of distinct non-null rows across one or more columns.
Behavior: Any row where one or more inputs is null is ignored.
Args:
*cols: One or more columns or column na... |
function | collect_list | fenic.api.functions.builtin.collect_list | Aggregate function: collects all values from the specified column into a list.
Args:
column: Column or column name to collect values from
Returns:
A Column expression representing the list aggregation
Raises:
TypeError: If column is not a Column or string | null | true | false | 279 | 294 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: collect_list
Qualified Name: fenic.api.functions.builtin.collect_list
Docstring: Aggregate function: collects all values from the specified column into a list.
Args:
column: Column or column name to collect values from
Returns:
A Column expression representing the list aggregation
... |
function | approx_count_distinct | fenic.api.functions.builtin.approx_count_distinct | Aggregate function: returns an approximate count (HyperLogLog++) of distinct non-null values.
Args:
column: Column or column name to approximately count distinct values in. Cannot be a StructType column.
Returns:
A Column expression representing the approximate count-distinct aggregation
Note:
Differs fr... | null | true | false | 296 | 346 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: approx_count_distinct
Qualified Name: fenic.api.functions.builtin.approx_count_distinct
Docstring: Aggregate function: returns an approximate count (HyperLogLog++) of distinct non-null values.
Args:
column: Column or column name to approximately count distinct values in. Cannot be a Str... |
function | array_agg | fenic.api.functions.builtin.array_agg | Alias for collect_list(). | null | true | false | 348 | 351 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: array_agg
Qualified Name: fenic.api.functions.builtin.array_agg
Docstring: Alias for collect_list().
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["column"]
Returns: Column
Parent Class: none |
function | first | fenic.api.functions.builtin.first | Aggregate function: returns the first non-null value in the specified column.
Typically used in aggregations to select the first observed value per group.
Args:
column: Column or column name.
Returns:
Column expression for the first value. | null | true | false | 353 | 367 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: first
Qualified Name: fenic.api.functions.builtin.first
Docstring: Aggregate function: returns the first non-null value in the specified column.
Typically used in aggregations to select the first observed value per group.
Args:
column: Column or column name.
Returns:
Column expres... |
function | stddev | fenic.api.functions.builtin.stddev | Aggregate function: returns the sample standard deviation of the specified column.
Args:
column: Column or column name.
Returns:
Column expression for sample standard deviation. | null | true | false | 369 | 381 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: stddev
Qualified Name: fenic.api.functions.builtin.stddev
Docstring: Aggregate function: returns the sample standard deviation of the specified column.
Args:
column: Column or column name.
Returns:
Column expression for sample standard deviation.
Value: none
Annotation: none
is Pub... |
function | struct | fenic.api.functions.builtin.struct | Creates a new struct column from multiple input columns.
Args:
*args: Columns or column names to combine into a struct. Can be:
- Individual arguments
- Lists of columns/column names
- Tuples of columns/column names
Returns:
A Column expression representing a struct containing the inp... | null | true | false | 383 | 412 | null | Column | null | [
"args"
] | null | null | Type: function
Member Name: struct
Qualified Name: fenic.api.functions.builtin.struct
Docstring: Creates a new struct column from multiple input columns.
Args:
*args: Columns or column names to combine into a struct. Can be:
- Individual arguments
- Lists of columns/column names
- Tuples o... |
function | array | fenic.api.functions.builtin.array | Creates a new array column from multiple input columns.
Args:
*args: Columns or column names to combine into an array. Can be:
- Individual arguments
- Lists of columns/column names
- Tuples of columns/column names
Returns:
A Column expression representing an array containing values f... | null | true | false | 415 | 444 | null | Column | null | [
"args"
] | null | null | Type: function
Member Name: array
Qualified Name: fenic.api.functions.builtin.array
Docstring: Creates a new array column from multiple input columns.
Args:
*args: Columns or column names to combine into an array. Can be:
- Individual arguments
- Lists of columns/column names
- Tuples of c... |
function | udf | fenic.api.functions.builtin.udf | A decorator or function for creating user-defined functions (UDFs) that can be applied to DataFrame rows.
Warning:
UDFs cannot be serialized and are not supported in cloud execution.
User-defined functions contain arbitrary Python code that cannot be transmitted
to remote workers. For cloud compatibility, ... | null | true | false | 447 | 502 | null | null | null | [
"f",
"return_type"
] | null | null | Type: function
Member Name: udf
Qualified Name: fenic.api.functions.builtin.udf
Docstring: A decorator or function for creating user-defined functions (UDFs) that can be applied to DataFrame rows.
Warning:
UDFs cannot be serialized and are not supported in cloud execution.
User-defined functions contain arbitr... |
function | async_udf | fenic.api.functions.builtin.async_udf | A decorator for creating async user-defined functions (UDFs) with configurable concurrency and retries.
Async UDFs allow IO-bound operations (API calls, database queries, MCP tool calls)
to be executed concurrently while maintaining DataFrame semantics.
Args:
f: Async function to convert to UDF
return_type: E... | null | true | false | 504 | 600 | null | null | null | [
"f",
"return_type",
"max_concurrency",
"timeout_seconds",
"num_retries"
] | null | null | Type: function
Member Name: async_udf
Qualified Name: fenic.api.functions.builtin.async_udf
Docstring: A decorator for creating async user-defined functions (UDFs) with configurable concurrency and retries.
Async UDFs allow IO-bound operations (API calls, database queries, MCP tool calls)
to be executed concurrently w... |
function | asc | fenic.api.functions.builtin.asc | Mark this column for ascending sort order with nulls first.
Args:
column: The column to apply the ascending ordering to.
Returns:
A sort expression with ascending order and nulls first. | null | true | false | 603 | 613 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: asc
Qualified Name: fenic.api.functions.builtin.asc
Docstring: Mark this column for ascending sort order with nulls first.
Args:
column: The column to apply the ascending ordering to.
Returns:
A sort expression with ascending order and nulls first.
Value: none
Annotation: none
is P... |
function | asc_nulls_first | fenic.api.functions.builtin.asc_nulls_first | Alias for asc().
Args:
column: The column to apply the ascending ordering to.
Returns:
A sort expression with ascending order and nulls first. | null | true | false | 616 | 626 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: asc_nulls_first
Qualified Name: fenic.api.functions.builtin.asc_nulls_first
Docstring: Alias for asc().
Args:
column: The column to apply the ascending ordering to.
Returns:
A sort expression with ascending order and nulls first.
Value: none
Annotation: none
is Public? : true
is Pr... |
function | asc_nulls_last | fenic.api.functions.builtin.asc_nulls_last | Mark this column for ascending sort order with nulls last.
Args:
column: The column to apply the ascending ordering to.
Returns:
A Column expression representing the column and the ascending sort order with nulls last. | null | true | false | 629 | 639 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: asc_nulls_last
Qualified Name: fenic.api.functions.builtin.asc_nulls_last
Docstring: Mark this column for ascending sort order with nulls last.
Args:
column: The column to apply the ascending ordering to.
Returns:
A Column expression representing the column and the ascending sort o... |
function | desc | fenic.api.functions.builtin.desc | Mark this column for descending sort order with nulls first.
Args:
column: The column to apply the descending ordering to.
Returns:
A sort expression with descending order and nulls first. | null | true | false | 642 | 652 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: desc
Qualified Name: fenic.api.functions.builtin.desc
Docstring: Mark this column for descending sort order with nulls first.
Args:
column: The column to apply the descending ordering to.
Returns:
A sort expression with descending order and nulls first.
Value: none
Annotation: none... |
function | desc_nulls_first | fenic.api.functions.builtin.desc_nulls_first | Alias for desc().
Args:
column: The column to apply the descending ordering to.
Returns:
A sort expression with descending order and nulls first. | null | true | false | 655 | 665 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: desc_nulls_first
Qualified Name: fenic.api.functions.builtin.desc_nulls_first
Docstring: Alias for desc().
Args:
column: The column to apply the descending ordering to.
Returns:
A sort expression with descending order and nulls first.
Value: none
Annotation: none
is Public? : true
... |
function | desc_nulls_last | fenic.api.functions.builtin.desc_nulls_last | Mark this column for descending sort order with nulls last.
Args:
column: The column to apply the descending ordering to.
Returns:
A sort expression with descending order and nulls last. | null | true | false | 668 | 678 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: desc_nulls_last
Qualified Name: fenic.api.functions.builtin.desc_nulls_last
Docstring: Mark this column for descending sort order with nulls last.
Args:
column: The column to apply the descending ordering to.
Returns:
A sort expression with descending order and nulls last.
Value: n... |
function | flatten | fenic.api.functions.builtin.flatten | Flattens an array of arrays into a single array (one level deep).
Flattens nested arrays by concatenating all inner arrays into a single array.
Only flattens one level of nesting. Returns null if the input is null.
Args:
column: Column or column name containing arrays of arrays.
Returns:
A Column with flatte... | null | true | false | 681 | 726 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: flatten
Qualified Name: fenic.api.functions.builtin.flatten
Docstring: Flattens an array of arrays into a single array (one level deep).
Flattens nested arrays by concatenating all inner arrays into a single array.
Only flattens one level of nesting. Returns null if the input is null.
Args... |
function | when | fenic.api.functions.builtin.when | Evaluates a conditional expression (like if-then).
Evaluates a condition for each row and returns a value when true.
Can be chained with more .when() calls or finished with .otherwise().
All branches must return the same type.
Args:
condition: Boolean expression to test
value: Value to return when condition i... | null | true | false | 729 | 770 | null | Column | null | [
"condition",
"value"
] | null | null | Type: function
Member Name: when
Qualified Name: fenic.api.functions.builtin.when
Docstring: Evaluates a conditional expression (like if-then).
Evaluates a condition for each row and returns a value when true.
Can be chained with more .when() calls or finished with .otherwise().
All branches must return the same type.... |
function | coalesce | fenic.api.functions.builtin.coalesce | Returns the first non-null value from the given columns for each row.
This function mimics the behavior of SQL's COALESCE function. It evaluates the input columns
in order and returns the first non-null value encountered. If all values are null, returns null.
Args:
*cols: Column expressions or column names to eva... | null | true | false | 773 | 801 | null | Column | null | [
"cols"
] | null | null | Type: function
Member Name: coalesce
Qualified Name: fenic.api.functions.builtin.coalesce
Docstring: Returns the first non-null value from the given columns for each row.
This function mimics the behavior of SQL's COALESCE function. It evaluates the input columns
in order and returns the first non-null value encounter... |
function | greatest | fenic.api.functions.builtin.greatest | Returns the greatest value from the given columns for each row.
This function mimics the behavior of SQL's GREATEST function. It evaluates the input columns
in order and returns the greatest value encountered. If all values are null, returns null.
All arguments must be of the same primitive type (e.g., StringType, Bo... | null | true | false | 803 | 833 | null | Column | null | [
"cols"
] | null | null | Type: function
Member Name: greatest
Qualified Name: fenic.api.functions.builtin.greatest
Docstring: Returns the greatest value from the given columns for each row.
This function mimics the behavior of SQL's GREATEST function. It evaluates the input columns
in order and returns the greatest value encountered. If all v... |
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