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Properties allow you to access all URL parts, such as scheme, user password, host, path, query, path, port, and password. All URL manipulations result in a new URL object. Strings passed to constructor or modification methods are automatically encoded and give canonical representations as a result. Regular properties are percent-decoded. To get encoded strings, you can use raw_ versions. As.human_repr(), URLs can be represented in a human-readable format. PyPI has binary wheels for Linux and MacOS. You can use the tarball to compile yarl from the source code if you want to install it on another operating system (such as Alpine Linux, which isn't manylinux-compliant due to the missing glibc). It requires Python headers and a C compiler. The pure-Python version (uncompiled) is slower. PyPy uses a pure Python implementation and is therefore unaffected by this variable.

The NumPy vectorization and indexing concepts are fast and flexible. They are the current de-facto standard in array computing. NumPy provides comprehensive mathematical functions, random numbers generators, linear algebra routines and Fourier transforms. NumPy is compatible with a wide variety of hardware and computing platforms. It also works well with sparse array libraries, distributed, GPU, or GPU. NumPy's core is C code that has been optimized. Enjoy Python's flexibility with the speed and efficiency of compiled code. NumPy's high-level syntax makes it easy for programmers of all backgrounds and experience levels. NumPy brings the computational power and simplicity of languages such as C and Fortran into Python, making it a language that is much easier to learn and to use. This power is often accompanied by simplicity: NumPy solutions are often simple and elegant.