riptable.rt_io

Functions

printh(data)

Allows jupyter lab/notebook to print multiple HTML renderings in the same output frame.

read_dset_from_np(outdir, fname[, mmap])

Read columns stored as numpy follows to a Dataset.

write_dset_to_np(ds, outdir, fname)

Write the columns of a dataset to numpy binary files, one file per column in the specified directory.
riptable.rt_io.printh(data)

Allows jupyter lab/notebook to print multiple HTML renderings in the same output frame.

Suppose you have three datasets: d1, d2, d3 In one jupyter cell you could write: printh(d1) printh(d2) printh(d3) And all three would be displayed, versus the default, where only the last is shown. Will also work for anything else with a _repr_html_ method.

You can also input a list of elements with _repr_html_ methods so that they display side by side. If the jupyter frame isn’t wide enough, they’ll just display below.

Parameters:

data (object or list of objects) – The object(s) to be rendered for display.

riptable.rt_io.read_dset_from_np(outdir, fname, mmap=False)

Read columns stored as numpy follows to a Dataset.

Parameters:

  • the (outdir is the path and fname is the name of) –

  • dataset (subdirectory containing the columns of the) –

  • will (set mmap = True for memmory mapping. Note this) –

  • loading (allow quick) –

  • elsewhere (but has some latency cost) –

Returns:

The dataset read in from the specified folder.

Return type:

Dataset

See also

write_dset_to_np

riptable.rt_io.write_dset_to_np(ds, outdir, fname)

Write the columns of a dataset to numpy binary files, one file per column in the specified directory.

Parameters:

  • ds (Dataset) – A Dataset to write out to disk.

  • outdir (str) – The path to the folder where the output will be written.

  • fname (str) – The name of the subdirectory to store the columns.

See also

read_dset_from_np