| Key | Value |
|---|---|
| FileName | ./usr/lib64/python3.2/site-packages/numpy/matrixlib/tests/__pycache__/test_regression.cpython-32.pyo |
| FileSize | 2360 |
| MD5 | 5BD75311695CD52AE5337CA8F823851A |
| SHA-1 | 00C2E4B7E8373388FF10C806C02BC545B20E9072 |
| SHA-256 | A7B67E41B3A4C4FF572FB47D28601E9A8B91A43192442FE7034F1D3FD609A7FF |
| SSDEEP | 48:88R4WVlMhHUiwpZIllFUhV/4nW2U2Bd3hbjihF7z0hVZ5wmh7ijNl+7hY:layEHUiUSlFmVmW2vBfIF7qVZ5w0W3EY |
| TLSH | T1A041B85096BF28F2D8E65E75B9B02616DFB3E5E37709EB111310307D2AC436B0C3A542 |
| hashlookup:parent-total | 1 |
| hashlookup:trust | 55 |
The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| MD5 | A8624F0ED48BD4AFBAD3D3C766D77DE2 |
| PackageArch | ppc64 |
| PackageDescription | NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Also included in this package is a version of f2py that works properly with NumPy. |
| PackageMaintainer | Koji |
| PackageName | python3-numpy |
| PackageRelease | 2.fc17 |
| PackageVersion | 1.6.1 |
| SHA-1 | 23E0359C94EB873D68565614B3E47257A043B0DF |
| SHA-256 | 7B7C4F6ED29FEA4ECDC2D502C751109925F155ADB2F722860AD5B21044D0DFF9 |