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Description

Cython serves as an optimizing static compiler designed for both the Python language and the enhanced Cython language, which is rooted in Pyrex. It simplifies the process of creating C extensions for Python, making it as straightforward as writing Python itself. With Cython, developers can harness the strengths of both Python and C, enabling seamless interactions between Python code and C or C++ code at any point. By incorporating static type declarations in a Python-like syntax, users can easily enhance the performance of their readable Python code to that of plain C. The tool also provides combined source code level debugging, allowing developers to efficiently identify issues within their Python, Cython, and C code. Cython is particularly adept at managing large datasets, such as multi-dimensional NumPy arrays, facilitating the development of applications within the expansive and robust CPython ecosystem. Notably, the Cython language extends the capabilities of Python by allowing direct calls to C functions and the declaration of C types for variables and class attributes, ultimately enhancing the development experience. This fusion of languages not only broadens the possibilities for developers but also streamlines the process of optimizing Python applications.

Description

Scheme serves as a versatile general-purpose programming language that operates at a high level. It facilitates various operations on complex data structures such as strings, lists, and vectors, in addition to handling traditional data types like numbers and characters. Although often associated with symbolic computation, Scheme's extensive range of data types and its adaptable control structures enhance its versatility for numerous applications. Developers have utilized Scheme for a wide array of projects, including text editors, compilers, operating systems, graphic applications, expert systems, numerical computations, financial analysis software, virtual reality frameworks, and virtually any other conceivable application. Learning Scheme is relatively accessible due to its reliance on a limited set of syntactic forms and semantic principles, and the interactive features of most implementations promote hands-on experimentation. However, achieving a deep understanding of Scheme can be quite challenging, as its complexities unfold with deeper exploration. As a result, practitioners often find themselves continually learning and evolving their skills within this rich programming environment.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

C
C++
CodeConvert
Emacs
Fortran
Gensim
JupyterLab
Notepad++
NumPy
Opengrep
PaizaCloud
PyCharm
Python
Racket
Replit
Snipplr
Spacemacs
jEdit
scikit-image

Integrations

C
C++
CodeConvert
Emacs
Fortran
Gensim
JupyterLab
Notepad++
NumPy
Opengrep
PaizaCloud
PyCharm
Python
Racket
Replit
Snipplr
Spacemacs
jEdit
scikit-image

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Cython

Country

United States

Website

cython.org

Vendor Details

Company Name

Scheme

Website

www.scheme.com/tspl4/intro.html#./intro:h0

Product Features

Product Features

Alternatives

Alternatives

D Reviews

D

D Language Foundation