Numpy file viewer

! Displaying very large arrays (e.g., size > 10,000,000) is not currently supported.

Display (binary) .npy or .npz files in VSCode.

Change log

Please refer to CHANGELOG.md.

Other Features

• Show array shape. [see gif]
• Table view for 2D/1D array. [see gif]
• Array slice. (In progress)

Supported Data Type

Refer: numpy/typing/tests/data/pass/scalars.py | numpy/typing/tests/test_typing.py

Status	Name	Description	Abbrev
✅	uint8	numpy.unsignedinteger[numpy._typing._8Bit]	u1
✅	uint16	numpy.unsignedinteger[numpy._typing._16Bit]	u2
✅	uint32	numpy.unsignedinteger[numpy._typing._32Bit]	u4
✅	uint64	numpy.unsignedinteger[numpy._typing._64Bit]	u8
✅	int8	numpy.signedinteger[numpy._typing._8Bit]	i1
✅	int16	numpy.signedinteger[numpy._typing._16Bit]	i2
✅	int32	numpy.signedinteger[numpy._typing._32Bit]	i4
✅	int64	numpy.signedinteger[numpy._typing._64Bit]	i8
✅	float16	numpy.floating[numpy._typing._16Bit]	f2
✅	float32	numpy.floating[numpy._typing._32Bit]	f4
✅	float64	numpy.floating[numpy._typing._64Bit]	f8
	float128	numpy.floating[numpy._typing._128Bit]	f16
	complex64	numpy.complexfloating[numpy._typing._32Bit, numpy._typing._32Bit]	c8
✅	complex128	numpy.complexfloating[numpy._typing._64Bit, numpy._typing._64Bit]	c16
	complex256	numpy.complexfloating[numpy._typing._128Bit, numpy._typing._128Bit]	c32
✅	bool_		b1
✅	str_		U
✅	bytes_		S
	datetime64		M
	timedelta64		m
Alias
	ubyte	numpy.unsignedinteger[{dct['_NBitByte']}]
	ushort	numpy.unsignedinteger[{dct['_NBitShort']}]
	uintc	numpy.unsignedinteger[{dct['_NBitIntC']}]
	uintp	numpy.unsignedinteger[{dct['_NBitIntP']}]
	uint	numpy.unsignedinteger[{dct['_NBitInt']}]
	ulonglong	numpy.unsignedinteger[{dct['_NBitLongLong']}]
	byte	numpy.signedinteger[{dct['_NBitByte']}]
	short	numpy.signedinteger[{dct['_NBitShort']}]
	intc	numpy.signedinteger[{dct['_NBitIntC']}]
	intp	numpy.signedinteger[{dct['_NBitIntP']}]
	int_	numpy.signedinteger[{dct['_NBitInt']}]
	longlong	numpy.signedinteger[{dct['_NBitLongLong']}]
	half	numpy.floating[{dct['_NBitHalf']}]
	single	numpy.floating[{dct['_NBitSingle']}]
	double	numpy.floating[{dct['_NBitDouble']}]
	longdouble	numpy.floating[{dct['_NBitLongDouble']}]
	csingle	numpy.complexfloating[{dct['_NBitSingle']}, {dct['_NBitSingle']}]
	cdouble	numpy.complexfloating[{dct['_NBitDouble']}, {dct['_NBitDouble']}]
	clongdouble	numpy.complexfloating[{dct['_NBitLongDouble']}, {dct['_NBitLongDouble']}]

* bold items are defaults.

Reference

• ludwigschubert/js-numpy-parser
• tomoki1207/vscode-pdfviewer
• janisdd/vscode-edit-csv