Reading PyKX data from disk

`pykx.read`

`QReader`

QReader(q)

Read data using q.

csv

csv(path, types=None, delimiter=',', as_table=True)

Reads a CSV file as a table or dictionary.

Column types are guessed if not provided.

Parameters:

Name	Type	Description	Default
`path`	`Union[str, Path, k.SymbolAtom]`	The path to the CSV file.	required
`types`	`Optional[Union[bytes, k.CharAtom, k.CharVector]]`	Can be a dictionary of columns and their types or a `str`-like object of uppercase characters representing the types. Space is used to drop a column. If `None`, the types will be guessed using `.csvutil.info`.	`None`
`delimiter`	`Union[str, bytes, k.CharAtom]`	A single character representing the delimiter between values.	`','`
`as_table`	`Union[bool, k.BooleanAtom]`	`True` if the first line of the CSV file should be treated as column names, in which case a `pykx.Table` is returned. If `False` a `pykx.List` of `pykx.Vector` is returned - one for each column in the CSV file.	`True`

Returns:

Type	Description
`Union[k.Table, k.Dictionary]`	The CSV data as a `pykx.Table` or `pykx.List`, depending on the value of `as_table`.

See Also

q.write.csv

Examples:

Read a comma seperated CSV file into a pykx.Table guessing the datatypes of each column.

table = q.read.csv('example.csv')

Read a tab seperated CSV file into a pykx.Table while specifying the columns datatypes to be a pykx.SymbolVector followed by two pykx.LongVector columns.

table = q.read.csv('example.csv', 'SJJ', '      ')

Read a comma seperated CSV file into a pykx.Dictionary, guessing the datatypes of each column.

table = q.read.csv('example.csv', None, None, False)

Read a comma separated CSV file specifying the type of the three columns named x1, x2 and x3 to be of type Integer, GUID and Timestamp.

table = q.read.csv('example.csv', {'x1':kx.IntAtom,'x2':kx.GUIDAtom,'x3':kx.TimestampAtom})

splayed

splayed(root, name)

Loads a splayed table.

Parameters:

Name	Type	Description	Default
`root`	`Union[str, Path, k.SymbolAtom]`	The path to the root directory of the splayed table.	required
`name`	`Union[str, k.SymbolAtom]`	The name of the table to read.	required

Returns:

Type	Description
`k.SplayedTable`	The splayed table as a `pykx.SplayedTable`.

See Also

q.write.splayed

Examples:

Reads a splayed table named t found within the current directory

table = q.read.splayed('.', 't')

Reads a splayed table named splayed found within the /tmp directory

table = q.read.splayed('/tmp', 'splayed')

fixed

fixed(path, types, widths)

Loads a file of typed data with fixed-width fields.

It is expected that there will either be a newline after every record, or none at all.

Parameters:

Name	Type	Description	Default
`path`	`Union[str, Path, k.SymbolAtom]`	The path to the file containing the fixed-width field data.	required
`types`	`Union[bytes, k.CharVector]`	A string of uppercase characters representing the types. Space is used to drop a column.	required
`widths`	`Union[List[int], k.LongVector]`	The width in bytes of each field.	required

Returns:

Type	Description
`k.List`	The data as a `pykx.List` with a `pykx.Vector` for each column.

Examples:

Read a file of fixed width data into a pykx.List of two pykx.LongVectors the first with a size of 1 character and the second with a size of 2 characters.

data = q.read.fixed('example_file', [b'J', b'J'], [1, 2])

json

json(path)

Reads a JSON file into a k.Table.

Parameters:

Name	Type	Description	Default
`path`	`Union[str, Path, k.SymbolAtom]`	The path to the JSON file.	required

Returns:

Type	Description
`JSONKTypes`	The JSON data as a `pykx.K` object.

See Also

q.write.json

Examples:

Read a JSON file.

data = q.read.json('example.json')

serialized

serialized(path)

Reads a binary file containing serialized q data.

Parameters:

Name	Type	Description	Default
`path`	`Union[str, Path, k.SymbolAtom]`	The path to the q data file.	required

Returns:

Type	Description
`k.K`	The q data file converted to a `pykx` object.

See Also

q.write.serialized

Examples:

Read a q data file containing a serialized table into a pykx.Table object.

table = q.read.serialized('q_table_file')