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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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SymbolicNumericIntegration.jl
SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals
SymbolicNumericIntegration.jl is a hybrid symbolic/numerical integration package that works on the Julia Symbolics expressions. -
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SuiteSparseGraphBLAS.jl
Sparse, General Linear Algebra for Graphs
A fast, general sparse linear algebra and graph computation package, based on SuiteSparse:GraphBLAS. -
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Oscar.jl
A comprehensive open source computer algebra system for computations
Welcome to the OSCAR project, a visionary new computer algebra system that combines the capabilities of four cornerstone systems: GAP, Polymake, Antic and Singular. OSCAR requires Julia 1.6 or newer. In principle it can be installed and used like any other Julia package; doing so will take a couple of minutes. A comprehensive open source computer algebra system for computations in algebra, geometry, and number theory. -
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LazySets.jl
Scalable Symbolic-Numeric Set Computations
LazySets.jl is a Julia package for calculus with convex sets. The aim is to provide a scalable library for solving complex set-based problems, such as those encountered in differential inclusions or reachability analysis techniques in the domain of formal verification. Typically, one is confronted with a set-based recurrence with a given initial set and/or input sets, and for visualization purposes, the final result has to be obtained through an adequate projection onto low dimensions. This... -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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KrylovKit.jl
Krylov methods for linear problems, eigenvalues, and singular values
A Julia package collecting a number of Krylov-based algorithms for linear problems, singular value and eigenvalue problems and the application of functions of linear maps or operators to vectors. -
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JuMP
Modeling language for Mathematical Optimization
JuMP is a modeling language and collection of supporting packages for mathematical optimization in Julia. JuMP makes it easy to formulate and solve a range of problem classes, including linear programs, integer programs, conic programs, semidefinite programs, and constrained nonlinear programs. JuMP is used to solve large-scale inventory routing problems at Renault, schedule trains at Thales Inc., plan power grid expansion at PSR, and route school buses. -
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Hecke.jl
Computational algebraic number theory
Hecke is a software package for algebraic number theory maintained by Claus Fieker, Tommy Hofmann and Carlo Sircana. It is written in julia and is based on the computer algebra packages Nemo and AbstractAlgebra. Hecke is part of the OSCAR project and the development is supported by the Deutsche Forschungsgemeinschaft DFG within the Collaborative Research Center TRR 195. -
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SpecialFunctions.jl
Special mathematical functions in Julia
Special mathematical functions in Julia, include Bessel, Hankel, Airy, error, Dawson, exponential (or sine and cosine) integrals, eta, zeta, digamma, inverse digamma, trigamma, and polygamma functions. Most of these functions were formerly part of Base in early versions of Julia. -
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OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE)
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research that routinely outperform the “standard” C/Fortran methods, and include algorithms optimized... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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DifferentialEquations.jl
Multi-language suite for high-performance solvers of equations
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research which routinely outperform the “standard” C/Fortran methods, and include algorithms optimized...
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