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pip (also known by Python 3's alias pip3) is a package-management system written in Python and is used to install and manage software packages. [4] The Python Software Foundation recommends using pip for installing Python applications and its dependencies during deployment. [ 5 ]
Synaptic, an example of a package manager. A package manager or package-management system is a collection of software tools that automates the process of installing, upgrading, configuring, and removing computer programs for a computer in a consistent manner.
The Python Package Index, abbreviated as PyPI (/ ˌ p aɪ p i ˈ aɪ /) and also known as the Cheese Shop (a reference to the Monty Python's Flying Circus sketch "Cheese Shop"), [2]: 8 [3]: 742 is the official third-party software repository for Python. [4] It is analogous to the CPAN repository for Perl [5]: 36 and to the CRAN repository for R.
Alternatively, the existing dependency, along with all software that depends on it, must be uninstalled in order to install the new dependency. A problem on Linux systems with installing packages from a different distributor is that the resulting long chain of dependencies may lead to a conflicting version of the C standard library (e.g. the ...
For example, there is a USE flag to include DVD support, where available, in packages compiled with the flag enabled. The USE flags affect which dependencies are required, generally affecting which optional features will be built into a given program when it is compiled.
Interface injection, where the dependency's interface provides an injector method that will inject the dependency into any client passed to it. In some frameworks, clients do not need to actively accept dependency injection at all. In Java, for example, reflection can make private attributes public when testing and inject services directly. [30]
In object-oriented design, the dependency inversion principle is a specific methodology for loosely coupled software modules.When following this principle, the conventional dependency relationships established from high-level, policy-setting modules to low-level, dependency modules are reversed, thus rendering high-level modules independent of the low-level module implementation details.
SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.