file_io.CSVReader
Attributes
Classes
A class to read in object data files stored as CSV or whitespace |
Module Contents
- class CSVDataReader(filename, sep='csv', **kwargs)[source]
Bases:
layup.utilities.file_io.ObjectDataReader.ObjectDataReaderA class to read in object data files stored as CSV or whitespace separated values.
Note that we require the header line to be the first line of the file
- get_reader_info()[source]
Return a string identifying the current reader name and input information (for logging and output).
- Returns:
name – The reader information.
- Return type:
string
- get_row_count()[source]
Return the total number of rows in the [C|P|W]SV file.
- Returns:
Total rows in the first key of the input [C|P|W]SV file.
- Return type:
int
- _check_header_line(header_line)[source]
Check that a given header line is valid and exit if it is invalid.
- Parameters:
header_line (str) – The proposed header line.
- _get_fixed_dtypes()[source]
Get a dictionary of the fixed dtypes for the columns in the CSV file.
- Returns:
fixed_dtypes – A dictionary of the fixed dtypes for the columns in the CSV file. The keys are the column names and the values are assigned dtype.
- Return type:
dict
- _read_rows_internal(block_start=0, block_size=None, **kwargs)[source]
Reads in a set number of rows from the input.
- Parameters:
block_start (integer, optional) – The 0-indexed row number from which to start reading the data. For example in a CSV file block_start=2 would skip the first two lines after the header and return data starting on row=2. Default =0
block_size (integer, optional, default=None) – The number of rows to read in. Use block_size=None to read in all available data. default =None
**kwargs (dictionary, optional) – Extra arguments
- Returns:
res – The data read in from the file.
- Return type:
numpy structured array
- _read_objects_internal(obj_ids, **kwargs)[source]
Read in a chunk of data for given object IDs.
- Parameters:
obj_ids (list) – A list of object IDs to use.
**kwargs (dictionary, optional) – Extra arguments
- Returns:
res – The data read in from the file.
- Return type:
numpy structured array
- _process_and_validate_input_table(input_table, **kwargs)[source]
Perform any input-specific processing and validation on the input table. Modifies the input table in place.
Notes
The base implementation includes filtering that is common to most input types. Subclasses should call super.process_and_validate() to ensure that the ancestor’s validation is also applied.
- Parameters:
input_table (numpy structured array) – A loaded table.
**kwargs (dictionary, optional) – Extra arguments
- Returns:
input_table – Returns the input table modified in-place.
- Return type:
numpy structured array