larray.Session.load¶
-
Session.
load
(fname, names=None, engine='auto', display=False, **kwargs)[source]¶ Load objects from a file, or several .csv files. The Excel and CSV formats can only contain objects of Array type (plus metadata).
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:
>>> # scalars >>> i, s = 5, 'string' # doctest: +SKIP >>> # 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 >>> ses = Session([('i', i), ('s', s), ('a', a), ('b', b), ('a01', a01), ... ('arr1', arr1), ('arr2', arr2)]) # doctest: +SKIP >>> # metadata >>> ses.meta.title = 'my title' # doctest: +SKIP >>> ses.meta.author = 'John Smith' # doctest: +SKIP >>> # save the session in an HDF5 file >>> ses.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 >>> ses = Session('input.h5') # doctest: +SKIP >>> ses # doctest: +SKIP Session(a, a01, arr1, arr2, b, i, s) >>> ses.meta # doctest: +SKIP title: my title author: John Smith
Load only some objects
>>> ses = Session() >>> ses.load('input.h5', names=['s', 'a', 'b', 'arr1', 'arr2'], display=True) # doctest: +SKIP opening input.h5 loading Axis object a ... done loading Array object arr1 ... done loading Array object arr2 ... done loading Axis object b ... done loading str object s ... done
Using .csv files (assuming the same session as above)
>>> ses.save('data') # doctest: +SKIP >>> ses = Session() # doctest: +SKIP >>> # load all .csv files from the 'data' directory >>> ses.load('data', display=True) # doctest: +SKIP opening data loading Array object arr1 ... done loading Array object arr2 ... done >>> # or only arrays containing the character '1' in their names >>> ses.load('data/*1.csv', display=True) # doctest: +SKIP opening data/*1.csv loading Array object arr1 ... done