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# Input and output

## NumPy binary files (npy, npz)

`load`(file[, mmap_mode, allow_pickle, ...]) | Load arrays or pickled objects from `.npy`, `.npz` or pickled files.
`save`(file, arr[, allow_pickle]) | Save an array to a binary file in NumPy `.npy` format.
`savez`(file, *args[, allow_pickle]) | Save several arrays into a single file in uncompressed `.npz` format.
`savez_compressed`(file, *args[, allow_pickle]) | Save several arrays into a single file in compressed `.npz` format.
`lib.npyio.NpzFile`(fid) | A dictionary-like object with lazy-loading of files in the zipped archive provided on construction.

The format of these binary file types is documented in `numpy.lib.format`

## Text files

`loadtxt`(fname[, dtype, comments, delimiter, ...]) | Load data from a text file.
`savetxt`(fname, X[, fmt, delimiter, newline, ...]) | Save an array to a text file.
`genfromtxt`(fname[, dtype, comments, ...]) | Load data from a text file, with missing values handled as specified.
`fromregex`(file, regexp, dtype[, encoding]) | Construct an array from a text file, using regular expression parsing.
`fromstring`(string[, dtype, count, like]) | A new 1-D array initialized from text data in a string.
`ndarray.tofile`(fid, /[, sep, format]) | Write array to a file as text or binary (default).
`ndarray.tolist`() | Return the array as an `a.ndim`-levels deep nested list of Python scalars.

## Raw binary files

`fromfile`(file[, dtype, count, sep, offset, like]) | Construct an array from data in a text or binary file.
`ndarray.tofile`(fid, /[, sep, format]) | Write array to a file as text or binary (default).

## String formatting

`array2string`(a[, max_line_width, precision, ...]) | Return a string representation of an array.
`array_repr`(arr[, max_line_width, precision, ...]) | Return the string representation of an array.
`array_str`(a[, max_line_width, precision, ...]) | Return a string representation of the data in an array.
`format_float_positional`(x[, precision, ...]) | Format a floating-point scalar as a decimal string in positional notation.
`format_float_scientific`(x[, precision, ...]) | Format a floating-point scalar as a decimal string in scientific notation.

## Memory mapping files

`memmap`(filename[, dtype, mode, offset, ...]) | Create a memory-map to an array stored in a binary file on disk.
`lib.format.open_memmap`(filename[, mode, ...]) | Open a .npy file as a memory-mapped array.

## Text formatting options

Text formatting settings are maintained in a `context variable`, allowing different threads or async tasks to have independent configurations. For more information, see Thread Safety.

`set_printoptions`([precision, threshold, ...]) | Set printing options.
`get_printoptions`() | Return the current print options.
`printoptions`(*args, **kwargs) | Context manager for setting print options.

## Base-n representations

`binary_repr`(num[, width]) | Return the binary representation of the input number as a string.
`base_repr`(number[, base, padding]) | Return a string representation of a number in the given base system.

## Data sources

`lib.npyio.DataSource`([destpath]) | A generic data source file (file, http, ftp, ...).

## Binary format description

`lib.format` | Binary serialization