Python
Multi-paradigm, Object-oriented, Imperative, functionally structured, Reflective - as a Script Based service.
Workiy, outcasts a design philosophy emphasizing code readability with the use of significant indentation. Our pool of experts assures that it is coded as dynamically-typed and garbage-collected that supports multiple programming prototypes.
Python strives for a simpler, less-cluttered syntax and grammar while giving developers a choice in their coding methodology. This compact modularity has made it particularly popular as a means of adding programmable interfaces to existing applications. We use dynamic typing and a combination of reference counting and a cycle-detecting garbage collector for memory management.
The Python Package Index (PyPI) hosts thousands of third-party modules for Python. It is developed under an OSI-approved open source license, making it freely usable and distributable. It supports Frameworks such as Django and Pyramid; Micro-frameworks such as Flask and Bottle.
- Beautiful is better than ugly
- Explicit is better than implicit
- Simple is better than complex
- Complex is better than complicated
- Readability counts
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Our developers strive to avoid premature optimization and reject patches to non-critical parts of the CPython reference implementation that would offer marginal increases in speed at the cost of clarity.
A common neologism in the Python community is pythonic, which has a wide range of meanings related to program style. "Pythonic" code may use Python idioms well, be natural or show fluency in the language, or conform with Python's minimalist philosophy and emphasis on readability. Code that is difficult to understand or reads like a rough transcription from another programming language is called unpythonic.
Workiy, outcasts a design philosophy emphasizing code readability with the use of significant indentation. Our pool of experts assures that it is coded as dynamically-typed and garbage-collected that supports multiple programming prototypes.
Python strives for a simpler, less-cluttered syntax and grammar while giving developers a choice in their coding methodology. This compact modularity has made it particularly popular as a means of adding programmable interfaces to existing applications. We use dynamic typing and a combination of reference counting and a cycle-detecting garbage collector for memory management.
The Python Package Index (PyPI) hosts thousands of third-party modules for Python. It is developed under an OSI-approved open source license, making it freely usable and distributable. It supports Frameworks such as Django and Pyramid; Micro-frameworks such as Flask and Bottle.
Python uses whitespace indentation, rather than curly brackets or keywords, to delimit blocks. An increase in indentation comes after certain statements; a decrease in indentation signifies the end of the current block.
Python features sequence unpacking where multiple expressions, each evaluating to anything that can be assigned (to a variable, writable property, etc.) are associated in an identical manner to that forming tuple literals. The statement expects an iterable object on the right-hand side of the equal sign that produces the same number of values as the provided writable expressions; when iterated through them, it assigns each of the produced values to the corresponding expression on the left.
Python uses arbitrary-precision arithmetic for all integer operations. The Decimal type/class in the decimal module provides decimal floating-point numbers to a pre-defined arbitrary precision and several rounding modes.The Fraction class in the fractions module provides arbitrary precision for rational numbers.
Python uses duck-typing and has typed objects but untyped variable names. Type constraints are not checked at compile time; rather, operations on an object may fail, signifying that it is not of a suitable type. Despite being dynamically typed, Python is strongly typed, forbidding operations that are not well-defined rather than silently attempting to make sense of them.
Python methods have an explicit-self parameter to access instance data, in contrast to the implicit-self as in some other object-oriented programming languages. Python also provides methods, often called dunder methods (due to their names beginning and ending with double-underscores), to allow user-defined classes to modify how they are handled by native operations including length, comparison, in arithmetic operations and type conversion.
Statements include assignment-statement, if, for, while, try, raise, class, def, with, break, continue, so on an so forth. The assignment statement binds a name as a reference to a separate, dynamically-allocated object. Variables may subsequently be rebound at any time to any object.
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