obsparsers class

class pycif.utils.classes.obsparsers.ObsParser(plg_orig=None, orig_name='', **kwargs)

Bases: Plugin

Class for handling time series parsing from different data providers and data file formats.

static check_df(df, **kwargs)

Check that all required columns have been loaded

Parameters:

• df

• kwargs

Returns:

classmethod get_parser(plg)

Get the correct Parser for a provider and file_format_id

Args:

provider (str): provider of the input file file_format_id (str): name of the type of file with a given format

Returns:

Parser: Parser for provider and file_format_id

initiate_template()

Initializes a Plugin template, with methods from the corresponding module.

Args:

self: the plugin to initialize plg_type: the type of the plugin to initialize default_functions (dict[str, bool]):

functions to load from the module and to attach to the plugin. Each key names the function and each value is a boolean to determine whether the corresponding function is a class method (with a reflective self as argument) or a classical static function

parse_file(obs_file, **kwargs)

This function does the parsing (and post processing if necessary).

Args:

obs_file (str): path to input file

Keyword Args:

encoding (str): Encoding of input files freq (str): frequency after resampling

see `Offset Aliases`_ for valid strings

src_freq (str):

explicit setting of the frequency in the input file shouldn’t be necessary

Returns:

pandas.DataFrame: renamed, shifted, resampled Dataframe df[obssite_id, parameter] with t as index

parse_multiple_files(**kwargs)

Parses multiple files specified by a glob pattern and stores the content into a datastore.

Args:

self: the plugin with its describing arguments (in particular dir_obs)

Returns:

dict: {obs_file} = df[obssite_id, parameter]

Note:

By default, the function calls self.parse_file, which filters out NaNs and check that all required columns are available.

classmethod register_parser(provider, file_format_id, parse_module, **kwargs)

Register a parsing function for provider and format with default options

Args:

provider (str): provider of the input file file_format_id (str): name of the type of file with a given format parse_module (Module):

returns file content as pandas.DataFrame df[obssite_id, parameter]

**kwargs: default options for parse_function

Notes:

The parse_function signature is the same as the Parser.parse_file()