larray.Session.load

Session.load(self, fname, names=None, engine='auto', display=False, **kwargs)

Load Array objects from a file, or several .csv files (all formats). Load also Axis and Group objects from a file (HDF and pickle formats).

WARNING: never load a file using the pickle engine (.pkl or .pickle) from an untrusted source, as it can lead to arbitrary code execution.

Parameters:

fname : str

This can be either the path to a single file, a path to a directory containing .csv files or a pattern representing several .csv files.

names : list of str, optional

List of objects to load. If fname is None, list of paths to CSV files. Defaults to all valid objects present in the file/directory.

engine : {‘auto’, ‘pandas_csv’, ‘pandas_hdf’, ‘pandas_excel’, ‘xlwings_excel’, ‘pickle’}, optional

Load using engine. Defaults to ‘auto’ (use default engine for the format guessed from the file extension).

display : bool, optional

Whether or not to display which file is being worked on. Defaults to False.

Examples

In one module:

>>> # axes
>>> a, b = Axis("a=a0..a2"), Axis("b=b0..b2")    # doctest: +SKIP
>>> # groups
>>> a01 = a['a0,a1'] >> 'a01'                    # doctest: +SKIP
>>> # arrays
>>> arr1, arr2 = ndtest((a, b)), ndtest(a)       # doctest: +SKIP
>>> s = Session([('a', a), ('b', b), ('a01', a01), ('arr1', arr1), ('arr2', arr2)])  # doctest: +SKIP
>>> # metadata
>>> s.meta.title = 'my title'                    # doctest: +SKIP
>>> s.meta.author = 'John Smith'                 # doctest: +SKIP
>>> # save the session in an HDF5 file
>>> s.save('input.h5')                           # doctest: +SKIP

In another module: load the whole session

>>> # the load method is automatically called when passing
>>> # the path of file to the Session constructor
>>> s = Session('input.h5')     # doctest: +SKIP
>>> s                           # doctest: +SKIP
Session(a, b, a01, arr1, arr2)
>>> s.meta                      # doctest: +SKIP
title: my title
author: John Smith

Load only some objects

>>> s = Session()                                   # doctest: +SKIP
>>> s.load('input.h5', ['a', 'b', 'arr1', 'arr2'])  # doctest: +SKIP
>>> a, b, arr1, arr2 = s['a', 'b', 'arr1', 'arr2']  # doctest: +SKIP
>>> # only if you know the order of arrays stored in session
>>> a, b, a01, arr1, arr2 = s.values()              # doctest: +SKIP

Using .csv files (assuming the same session as above)

>>> s.save('data')                                # doctest: +SKIP
>>> s = Session()                                 # doctest: +SKIP
>>> # load all .csv files starting with "output" in the data directory
>>> s.load('data')                                # doctest: +SKIP
>>> # or only arrays (i.e. all CSV files starting with 'arr')
>>> s.load('data/arr*.csv')                       # doctest: +SKIP