| Key | Value |
|---|---|
| FileName | ./usr/lib/python3.9/site-packages/numba/tests/__pycache__/test_closure.cpython-39.opt-1.pyc |
| FileSize | 23751 |
| MD5 | 836F89F4944D11C213277C09F70FC1F5 |
| SHA-1 | 00021C5F21B4310FE26208681FBED87C74D0648D |
| SHA-256 | E5DE0BFA71AA39D0BA65D1D80978C82042E364B8EC7AB29DB77C0019AE5D2981 |
| SSDEEP | 384:nYMXLgkZy05OkbF1NHS3d8wac0Lldfipty4dMVX2h5TOy/wzzL27Sv8g83dYdQPR:nYMXLgkZy05OcLNHS3d8wac0LldfiptZ |
| TLSH | T1FCB2D09C17028F6EFA70F2F544D55114A724CA37234D4AA2B42CCADE3F567C92CA678E |
| 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 |
|---|---|
| MD5 | 71D66A3498F552992E6CD538925A2BAA |
| PackageArch | armv7hl |
| PackageDescription | Numba is a NumPy-aware optimizing compiler for Python. It uses the LLVM compiler infrastructure to compile Python syntax to machine code. It is aware of NumPy arrays as typed memory regions and so can speed-up code using NumPy arrays. Other, less well-typed code will be translated to Python C-API calls, effectively removing the "interpreter", but not removing the dynamic indirection. Numba is also not a tracing JIT. It *compiles* your code before it gets run, either using run-time type information or type information you provide in the decorator. Numba is a mechanism for producing machine code from Python syntax and typed data structures such as those that exist in NumPy. |
| PackageName | python39-numba |
| PackageRelease | 54.2 |
| PackageVersion | 0.55.0 |
| SHA-1 | 47AC50676A3920262B3D67238A2C84D9F153C9E4 |
| SHA-256 | DF6781B2E29D9D300FE3E09E0F449980B0235DCD1A2BE147D0064F93F0271AA6 |
| Key | Value |
|---|---|
| MD5 | 85B3AF7742FB14EE3CAB412F7DA54F0E |
| PackageArch | i586 |
| PackageDescription | Numba is a NumPy-aware optimizing compiler for Python. It uses the LLVM compiler infrastructure to compile Python syntax to machine code. It is aware of NumPy arrays as typed memory regions and so can speed-up code using NumPy arrays. Other, less well-typed code will be translated to Python C-API calls, effectively removing the "interpreter", but not removing the dynamic indirection. Numba is also not a tracing JIT. It *compiles* your code before it gets run, either using run-time type information or type information you provide in the decorator. Numba is a mechanism for producing machine code from Python syntax and typed data structures such as those that exist in NumPy. |
| PackageName | python39-numba |
| PackageRelease | 54.3 |
| PackageVersion | 0.55.0 |
| SHA-1 | DB7B2AA59BD4F7F1B597D1375994E26C17E839D1 |
| SHA-256 | AC006DB424B7DBCCE939FAA47C428201C398CF2264D0E4BDE6A0C56FA6EFEF89 |