Key | Value |
---|---|
FileName | ./usr/share/doc/python3-zarr/html/_static/logo1.png |
FileSize | 4606 |
MD5 | F88BE6F9962ACAA93DB128AF101D5DD6 |
SHA-1 | 273409F999F47EE7FAF8F5ADA85BC5470EC72A5E |
SHA-256 | F997BE059DB8CA852A33F2A3718D9340029650DEDC6D84553EAC04933A2B7189 |
SSDEEP | 96:53jriD2LOFxr94etmP2mpbm3VJKLDOdaGccokq13NOY2K2KJzf:53V2xx4lVN8aGbqfOTUT |
TLSH | T10D916D0D616A6C07EC4E9285A7318930319CFFA767D8577F96D483913086D584BC32B7 |
hashlookup:parent-total | 2 |
hashlookup:trust | 60 |
The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileSize | 241336 |
MD5 | 59CCD768C4DACD2D9ED9758FE16DD5B4 |
PackageDescription | chunked, compressed, N-dimensional arrays for Python Zarr is a Python package providing an implementation of compressed, chunked, N-dimensional arrays, designed for use in parallel computing. Some highlights: . - Create N-dimensional arrays with any NumPy dtype. - Chunk arrays along any dimension. - Compress chunks using the fast Blosc meta-compressor or alternatively using zlib, BZ2 or LZMA. - Store arrays in memory, on disk, inside a Zip file, on S3, ... - Read an array concurrently from multiple threads or processes. - Write to an array concurrently from multiple threads or processes. - Organize arrays into hierarchies via groups. - Use filters to preprocess data and improve compression. |
PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
PackageName | python3-zarr |
PackageSection | python |
PackageVersion | 2.6.1+ds-1 |
SHA-1 | 14253B3BA86B747D331EB12A47409C136DE4D023 |
SHA-256 | CA6388A803F3F9AC3AA25DA6807BB7D08F58BC9731E916097A88337C63F78963 |
Key | Value |
---|---|
FileSize | 233868 |
MD5 | E938F04C32104A1EC556A026FF65FABB |
PackageDescription | chunked, compressed, N-dimensional arrays for Python Zarr is a Python package providing an implementation of compressed, chunked, N-dimensional arrays, designed for use in parallel computing. Some highlights: . - Create N-dimensional arrays with any NumPy dtype. - Chunk arrays along any dimension. - Compress chunks using the fast Blosc meta-compressor or alternatively using zlib, BZ2 or LZMA. - Store arrays in memory, on disk, inside a Zip file, on S3, ... - Read an array concurrently from multiple threads or processes. - Write to an array concurrently from multiple threads or processes. - Organize arrays into hierarchies via groups. - Use filters to preprocess data and improve compression. |
PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
PackageName | python3-zarr |
PackageSection | python |
PackageVersion | 2.4.0+ds-1 |
SHA-1 | 0CE95241D7EB6681C5267AC650C16ED215A319EE |
SHA-256 | 545FA978D81BBE9AE6BA147A0471AB68FC148854ECD829D2747D397085EB7FEE |