python3-django-rich

Extensions for using Rich with Django (Python3 version)

Rich is a Python library for writing rich text (with color and style) to the terminal, and for displaying advanced content such as tables, markdown, and syntax highlighted code.

libslepc-real3.19t64

Scalable Library for Eigenvalue Problem Computations

SLEPc is a software library for the solution of large scale sparse eigenvalue problems on parallel computers. It is an extension of PETSc and can be used for either standard or generalized eigenproblems, with real or complex arithmetic. It can also be used for computing a partial SVD of a large, sparse, rectangular matrix.

libnutclient2

network UPS tools - new client library

Network UPS Tools (NUT) is a client/server monitoring system that allows computers to share uninterruptible power supply (UPS) and power distribution unit (PDU) hardware. Clients access the hardware through the server, and are notified whenever the power status changes.

libnutscan2

network UPS tools - scanner library

Network UPS Tools (NUT) is a client/server monitoring system that allows computers to share uninterruptible power supply (UPS) and power distribution unit (PDU) hardware. Clients access the hardware through the server, and are notified whenever the power status changes.

libslepc64-complex3.19t64

Scalable Library for Eigenvalue Problem Computations (64-bit)

SLEPc is a software library for the solution of large scale sparse eigenvalue problems on parallel computers. It is an extension of PETSc and can be used for either standard or generalized eigenproblems, with real or complex arithmetic. It can also be used for computing a partial SVD of a large, sparse, rectangular matrix.

libslepc64-real3.19t64

Scalable Library for Eigenvalue Problem Computations (64-bit)

SLEPc is a software library for the solution of large scale sparse eigenvalue problems on parallel computers. It is an extension of PETSc and can be used for either standard or generalized eigenproblems, with real or complex arithmetic. It can also be used for computing a partial SVD of a large, sparse, rectangular matrix.