CPython is the reference implementation of the Python programming language . Written in C and Python, CPython is the default and most widely used implementation of the Python language.
106-440: CPython can be defined as both an interpreter and a compiler as it compiles Python code into bytecode before interpreting it. It has a foreign function interface with several languages, including C, in which one must explicitly write bindings in a language other than Python. A particular feature of CPython is that it makes use of a global interpreter lock (GIL) on each CPython interpreter process , which means that within
212-494: A database query to execute, while the third thread is actually processing Python code. However, the GIL does mean that CPython is not suitable for processes that implement CPU-intensive algorithms in Python code that could potentially be distributed across multiple cores. In real-world applications, situations where the GIL is a significant bottleneck are quite rare. This is because Python
318-481: A garbage collector and debugger . Programs written in a high-level language are either directly executed by some kind of interpreter or converted into machine code by a compiler (and assembler and linker ) for the CPU to execute. While compilers (and assemblers) generally produce machine code directly executable by computer hardware, they can often (optionally) produce an intermediate form called object code . This
424-468: A variable-length code requiring 3, 6, 10, or 18 bits, and address operands include a "bit offset". Many BASIC interpreters can store and read back their own tokenized internal representation. An interpreter might well use the same lexical analyzer and parser as the compiler and then interpret the resulting abstract syntax tree . Example data type definitions for the latter, and a toy interpreter for syntax trees obtained from C expressions are shown in
530-466: A virtual machine , which is implemented not in hardware, but in the bytecode interpreter. Such compiling interpreters are sometimes also called compreters . In a bytecode interpreter each instruction starts with a byte, and therefore bytecode interpreters have up to 256 instructions, although not all may be used. Some bytecodes may take multiple bytes, and may be arbitrarily complicated. Control tables - that do not necessarily ever need to pass through
636-505: A . However, maintaining the validity of this equation means that while the result of a%b is, as expected, in the half-open interval [0, b ), where b is a positive integer, it has to lie in the interval ( b , 0] when b is negative. Python provides a round function for rounding a float to the nearest integer. For tie-breaking , Python 3 uses round to even : round(1.5) and round(2.5) both produce 2 . Versions before 3 used round-away-from-zero : round(0.5)
742-629: A GCC toolchain, macOS for 64-bit Intel and ARM, and Microsoft Windows for 32- and 64-bit Intel. Official tier-2 support exists for Linux for 64-bit ARM, wasm32 ( Web Assembly ) with WASI runtime support, and Linux for 64-bit Intel using a clang toolchain. Official supported tier-3 systems include 64-bit ARM Windows, 64-bit iOS, Raspberry Pi OS (Linux for armv7 with hard float), Linux for 64-bit PowerPC in little-endian mode, and Linux for s390x . More platforms have working implementations, including: PEP 11 lists platforms which are not supported in CPython by
848-441: A bytecode interpreter, because of nodes related to syntax performing no useful work, of a less sequential representation (requiring traversal of more pointers) and of overhead visiting the tree. Further blurring the distinction between interpreters, bytecode interpreters and compilation is just-in-time (JIT) compilation, a technique in which the intermediate representation is compiled to native machine code at runtime. This confers
954-419: A certain type. Python does not support tail call optimization or first-class continuations , and, according to Van Rossum, it never will. However, better support for coroutine -like functionality is provided by extending Python's generators . Before 2.5, generators were lazy iterators ; data was passed unidirectionally out of the generator. From Python 2.5 on, it is possible to pass data back into
1060-644: A combination of reference counting and a cycle-detecting garbage collector for memory management . It uses dynamic name resolution ( late binding ), which binds method and variable names during program execution. Its design offers some support for functional programming in the Lisp tradition. It has filter , map and reduce functions; list comprehensions , dictionaries , sets, and generator expressions. The standard library has two modules ( itertools and functools ) that implement functional tools borrowed from Haskell and Standard ML . Its core philosophy
1166-413: A compiler works. However, a compiled program still runs much faster, under most circumstances, in part because compilers are designed to optimize code, and may be given ample time for this. This is especially true for simpler high-level languages without (many) dynamic data structures, checks, or type checking . In traditional compilation, the executable output of the linkers (.exe files or .dll files or
SECTION 10
#17328595981701272-439: A compiling phase - dictate appropriate algorithmic control flow via customized interpreters in similar fashion to bytecode interpreters. Threaded code interpreters are similar to bytecode interpreters but instead of bytes they use pointers. Each "instruction" is a word that points to a function or an instruction sequence, possibly followed by a parameter. The threaded code interpreter either loops fetching instructions and calling
1378-413: A computer language is usually done in relation to an abstract machine (so-called operational semantics ) or as a mathematical function ( denotational semantics ). A language may also be defined by an interpreter in which the semantics of the host language is given. The definition of a language by a self-interpreter is not well-founded (it cannot define a language), but a self-interpreter tells a reader about
1484-420: A decrease in indentation signifies the end of the current block. Thus, the program's visual structure accurately represents its semantic structure. This feature is sometimes termed the off-side rule . Some other languages use indentation this way; but in most, indentation has no semantic meaning. The recommended indent size is four spaces. Python's statements include: The assignment statement ( = ) binds
1590-466: A different unofficial Python implementation, PyPy , continues to support Python 2, i.e. "2.7.18+" (plus 3.10), with the plus meaning (at least some) " backported security updates". Python 3.0 was released on 3 December 2008, with some new semantics and changed syntax. At least every Python release since (now unsupported) 3.5 has added some syntax to the language, and a few later releases have dropped outdated modules, or changed semantics, at least in
1696-480: A factor of five over CPython; this goal was not met. The project was sponsored by Google , and the project owners, Thomas Wouters, Jeffrey Yasskin, and Collin Winter, are full-time Google employees; however, most project contributors were not Google employees. Unladen Swallow was hosted on Google Code . Like many things regarding the Python language, the name Unladen Swallow is a Monty Python reference, specifically to
1802-567: A five-member Steering Council to lead the project. Python 2.0 was released on 16 October 2000, with many major new features such as list comprehensions , cycle-detecting garbage collection, reference counting , and Unicode support. Python 2.7's end-of-life was initially set for 2015, then postponed to 2020 out of concern that a large body of existing code could not easily be forward-ported to Python 3. No further security patches or other improvements will be released for it. While Python 2.7 and older versions are officially unsupported,
1908-510: A generator function; and from version 3.3, it can be passed through multiple stack levels. Python's expressions include: In Python, a distinction between expressions and statements is rigidly enforced, in contrast to languages such as Common Lisp , Scheme , or Ruby . This leads to duplicating some functionality. For example: Statements cannot be a part of an expression—so list and other comprehensions or lambda expressions , all being expressions, cannot contain statements. A particular case
2014-464: A half), followed by 3 years of security support (for same total support as before). Security updates were expedited in 2021 (and again twice in 2022, and more fixed in 2023 and in September 2024 for Python 3.12.6 down to 3.8.20), since all Python versions were insecure (including 2.7 ) because of security issues leading to possible remote code execution and web-cache poisoning . Python 3.10 added
2120-418: A library, see picture) is typically relocatable when run under a general operating system, much like the object code modules are but with the difference that this relocation is done dynamically at run time, i.e. when the program is loaded for execution. On the other hand, compiled and linked programs for small embedded systems are typically statically allocated, often hard coded in a NOR flash memory, as there
2226-710: A list of these commands in the order a programmer wishes to execute them. Each command (also known as an Instruction ) contains the data the programmer wants to mutate, and information on how to mutate the data. For example, an interpreter might read ADD Books, 5 and interpret it as a request to add five to the Books variable . Interpreters have a wide variety of instructions which are specialized to perform different tasks, but you will commonly find interpreter instructions for basic mathematical operations , branching , and memory management , making most interpreters Turing complete . Many interpreters are also closely integrated with
SECTION 20
#17328595981702332-445: A matrix‑multiplication operator @ . These operators work like in traditional math; with the same precedence rules , the operators infix ( + and - can also be unary to represent positive and negative numbers respectively). The division between integers produces floating-point results. The behavior of division has changed significantly over time: In Python terms, / is true division (or simply division ), and //
2438-459: A minor way. Since 7 October 2024 , Python 3.13 is the latest stable release, and it and, for few more months, 3.12 are the only releases with active support including for bugfixes (as opposed to just for security) and Python 3.9, is the oldest supported version of Python (albeit in the 'security support' phase), due to Python 3.8 reaching end-of-life . Starting with 3.13, it and later versions have 2 years of full support (up from one and
2544-402: A name as a reference to a separate, dynamically allocated object . Variables may subsequently be rebound at any time to any object. In Python, a variable name is a generic reference holder without a fixed data type ; however, it always refers to some object with a type. This is called dynamic typing —in contrast to statically-typed languages, where each variable may contain only a value of
2650-461: A new and improved interactive interpreter ( REPL ), featuring multi-line editing and color support; an incremental garbage collector (producing shorter pauses for collection in programs with a lot of objects, and addition to the improved speed in 3.11 and 3.12), and an experimental just-in-time (JIT) compiler (such features, can/needs to be enabled specifically for the increase in speed), and an experimental free-threaded build mode, which disables
2756-439: A parse tree, and both may generate immediate instructions (for a stack machine , quadruple code , or by other means). The basic difference is that a compiler system, including a (built in or separate) linker, generates a stand-alone machine code program, while an interpreter system instead performs the actions described by the high-level program. A compiler can thus make almost all the conversions from source code semantics to
2862-405: A similar effect to obfuscation, but bytecode could be decoded with a decompiler or disassembler . The main disadvantage of interpreters is that an interpreted program typically runs more slowly than if it had been compiled . The difference in speeds could be tiny or great; often an order of magnitude and sometimes more. It generally takes longer to run a program under an interpreter than to run
2968-414: A single process, only one thread may be processing Python bytecode at any one time. This does not mean that there is no point in multithreading ; the most common multithreading scenario is where threads are mostly waiting on external processes to complete. This can happen when multiple threads are servicing separate clients. One thread may be waiting for a client to reply, and another may be waiting for
3074-505: A special py3k-jit branch of Python's official repository . As of July 2010, this work was ongoing. This merging would have taken some time, since Unladen Swallow was originally based on Python 2.6 with which Python 3 broke compatibility (see Python 3000 for more details). However, the PEP was subsequently withdrawn. In early 2011, it became clear that the project was stopped. Officially supported tier-1 platforms are Linux for 64-bit Intel using
3180-411: A standard format for distributing Python Binaries. Python 3.15 will "Make UTF-8 mode default", the mode exists in all current Python versions, but currently needs to be opted into. UTF-8 is already used, by default, on Windows (and elsewhere), for most things, but e.g. to open files it's not and enabling also makes code fully cross-platform, i.e. use UTF-8 for everything on all platforms. Python
3286-584: A string literal, with no certainty as to which one a programmer should use. Alex Martelli , a Fellow at the Python Software Foundation and Python book author, wrote: "To describe something as 'clever' is not considered a compliment in the Python culture." Python's developers usually 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
CPython - Misplaced Pages Continue
3392-494: A suitable interpreter. If the interpreter needs to be supplied along with the source, the overall installation process is more complex than delivery of a monolithic executable, since the interpreter itself is part of what needs to be installed. The fact that interpreted code can easily be read and copied by humans can be of concern from the point of view of copyright . However, various systems of encryption and obfuscation exist. Delivery of intermediate code, such as bytecode, has
3498-472: A template interpreter. Rather than implement the execution of code by virtue of a large switch statement containing every possible bytecode, while operating on a software stack or a tree walk, a template interpreter maintains a large array of bytecode (or any efficient intermediate representation) mapped directly to corresponding native machine instructions that can be executed on the host hardware as key value pairs (or in more efficient designs, direct addresses to
3604-415: A wide range of computational tasks, including binary emulation and internet applications. Interpreter performance is still a worry despite their adaptability, particularly on systems with limited hardware resources. Advanced instrumentation and tracing approaches provide insights into interpreter implementations and processor resource utilization during execution through evaluations of interpreters tailored for
3710-585: Is 1.0 , round(-0.5) is −1.0 . Python allows Boolean expressions with multiple equality relations in a manner that is consistent with general use in mathematics. For example, the expression a < b < c tests whether a is less than b and b is less than c . C-derived languages interpret this expression differently: in C, the expression would first evaluate a < b , resulting in 0 or 1, and that result would then be compared with c . Python uses arbitrary-precision arithmetic for all integer operations. The Decimal type/class in
3816-403: Is floor division. / before version 3.0 is classic division . Rounding towards negative infinity, though different from most languages, adds consistency. For instance, it means that the equation ( a + b ) // b == a // b + 1 is always true. It also means that the equation b * ( a // b ) + a % b == a is valid for both positive and negative values of
3922-412: Is a computer program that directly executes instructions written in a programming or scripting language , without requiring them previously to have been compiled into a machine language program. An interpreter generally uses one of the following strategies for program execution: Early versions of Lisp programming language and minicomputer and microcomputer BASIC dialects would be examples of
4028-509: Is a high-level , general-purpose programming language . Its design philosophy emphasizes code readability with the use of significant indentation . Python is dynamically typed and garbage-collected . It supports multiple programming paradigms , including structured (particularly procedural ), object-oriented and functional programming . It is often described as a "batteries included" language due to its comprehensive standard library . Guido van Rossum began working on Python in
4134-522: Is a multi-paradigm programming language . Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming (including metaprogramming and metaobjects ). Many other paradigms are supported via extensions, including design by contract and logic programming . Python is known as a glue language , able to work very well with many other languages with ease of access. Python uses dynamic typing and
4240-432: Is a few decades old, appearing in languages such as Smalltalk in the 1980s. Just-in-time compilation has gained mainstream attention amongst language implementers in recent years, with Java , the .NET Framework , most modern JavaScript implementations, and Matlab now including JIT compilers. Making the distinction between compilers and interpreters yet again even more vague is a special interpreter design known as
4346-688: Is a layer of hardware-level instructions that implement higher-level machine code instructions or internal state machine sequencing in many digital processing elements. Microcode is used in general-purpose central processing units , as well as in more specialized processors such as microcontrollers , digital signal processors , channel controllers , disk controllers , network interface controllers , network processors , graphics processing units , and in other hardware. Microcode typically resides in special high-speed memory and translates machine instructions, state machine data or other input into sequences of detailed circuit-level operations. It separates
CPython - Misplaced Pages Continue
4452-532: Is a relatively simple way to achieve software compatibility between different products in a processor family. Even a non microcoding computer processor itself can be considered to be a parsing immediate execution interpreter that is written in a general purpose hardware description language such as VHDL to create a system that parses the machine code instructions and immediately executes them. Interpreters, such as those written in Java, Perl, and Tcl, are now necessary for
4558-422: Is an inherently slow language and is generally not used for CPU-intensive or time-sensitive operations. Python is typically used at the top level and calls functions in libraries to perform specialized tasks. These libraries are generally not written in Python, and Python code in another thread can be executed while a call to one of these underlying processes takes place. The non-Python library being called to perform
4664-583: Is basically the same machine specific code but augmented with a symbol table with names and tags to make executable blocks (or modules) identifiable and relocatable. Compiled programs will typically use building blocks (functions) kept in a library of such object code modules. A linker is used to combine (pre-made) library files with the object file(s) of the application to form a single executable file. The object files that are used to generate an executable file are thus often produced at different times, and sometimes even by different languages (capable of generating
4770-439: Is compiled into "F code" (a bytecode), which is then interpreted by a virtual machine . In the spectrum between interpreting and compiling, another approach is to transform the source code into an optimized abstract syntax tree (AST), then execute the program following this tree structure, or use it to generate native code just-in-time . In this approach, each sentence needs to be parsed just once. As an advantage over bytecode,
4876-492: Is compiled, and possibly semantics are slightly changed. Python's developers aim for it to be fun to use. This is reflected in its name—a tribute to the British comedy group Monty Python —and in occasionally playful approaches to tutorials and reference materials, such as the use of the terms "spam" and "eggs" (a reference to a Monty Python sketch ) in examples, instead of the often-used "foo" and "bar" . A common neologism in
4982-432: Is executed and then perform the desired action, whereas the compiled code just performs the action within a fixed context determined by the compilation. This run-time analysis is known as "interpretive overhead". Access to variables is also slower in an interpreter because the mapping of identifiers to storage locations must be done repeatedly at run-time rather than at compile time . There are various compromises between
5088-430: Is implemented using closures in the interpreter language or implemented "manually" with a data structure explicitly storing the environment. The more features implemented by the same feature in the host language, the less control the programmer of the interpreter has; for example, a different behavior for dealing with number overflows cannot be realized if the arithmetic operations are delegated to corresponding operations in
5194-532: Is meant to be an easily readable language. Its formatting is visually uncluttered and often uses English keywords where other languages use punctuation. Unlike many other languages, it does not use curly brackets to delimit blocks, and semicolons after statements are allowed but rarely used. It has fewer syntactic exceptions and special cases than C or Pascal . Python uses whitespace indentation, rather than curly brackets or keywords, to delimit blocks . An increase in indentation comes after certain statements;
5300-543: Is more difficult to maintain due to the interpreter having to support translation to multiple different architectures instead of a platform independent virtual machine/stack. To date, the only template interpreter implementations of widely known languages to exist are the interpreter within Java's official reference implementation, the Sun HotSpot Java Virtual Machine, and the Ignition Interpreter in
5406-411: Is not of a suitable type. Despite being dynamically typed , Python is strongly typed , forbidding operations that are not well-defined (for example, adding a number to a string) rather than silently attempting to make sense of them. Python allows programmers to define their own types using classes , most often used for object-oriented programming . New instances of classes are constructed by calling
SECTION 50
#17328595981705512-449: Is often no secondary storage and no operating system in this sense. Historically, most interpreter systems have had a self-contained editor built in. This is becoming more common also for compilers (then often called an IDE ), although some programmers prefer to use an editor of their choice and run the compiler, linker and other tools manually. Historically, compilers predate interpreters because hardware at that time could not support both
5618-610: Is slow, inconsistent and buggy [and it has] has many corner cases and oddities. Code that works around those may need to be changed. Code that uses locals() for simple templating, or print debugging, will continue to work correctly." Some (more) standard library modules and many deprecated classes, functions and methods, will be removed in Python 3.15 or 3.16. Python 3.14 is now in alpha 2; regarding possible change to annotations: "In Python 3.14, from __future__ import annotations will continue to work as it did before, converting annotations into strings." PEP 711 proposes PyBI:
5724-487: Is such a language, because XSLT programs are written in XML. A sub-domain of metaprogramming is the writing of domain-specific languages (DSLs). Clive Gifford introduced a measure quality of self-interpreter (the eigenratio), the limit of the ratio between computer time spent running a stack of N self-interpreters and time spent to run a stack of N − 1 self-interpreters as N goes to infinity. This value does not depend on
5830-543: Is summarized in the Zen of Python (PEP 20), which includes aphorisms such as: However, Python features regularly violate these principles and have received criticism for adding unnecessary language bloat. Responses to these criticisms are that the Zen of Python is a guideline rather than a rule. The addition of some new features had been so controversial that Guido van Rossum resigned as Benevolent Dictator for Life following vitriol over
5936-460: Is that an assignment statement such as a = 1 cannot form part of the conditional expression of a conditional statement. Methods on objects are functions attached to the object's class; the syntax instance . method ( argument ) is, for normal methods and functions, syntactic sugar for Class . method ( instance , argument ) . Python methods have an explicit self parameter to access instance data , in contrast to
6042-548: 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 . Due to Python's extensive mathematics library, and the third-party library NumPy that further extends the native capabilities, it is frequently used as a scientific scripting language to aid in problems such as numerical data processing and manipulation. "Hello, World!" program : Program to calculate
6148-570: The | union type operator and the match and case keywords (for structural pattern matching statements). 3.11 expanded exception handling functionality. Python 3.12 added the new keyword type . Notable changes in 3.11 from 3.10 include increased program execution speed and improved error reporting. Python 3.11 claims to be between 10 and 60% faster than Python 3.10, and Python 3.12 adds another 5% on top of that. It also has improved error messages (again improved in 3.14), and many other changes. Python 3.13 introduces more syntax for types,
6254-536: The Python Software Foundation . These platforms can still be supported by external ports. These ports include: External ports not integrated to Python Software Foundation's official version of CPython, with links to its main development site, often include additional modules for platform-specific functionalities, like graphics and sound API for PSP and SMS and camera API for S60. These ports include: These Python versions are distributed with currently-supported enterprise Linux distributions. The support status of Python in
6360-427: The development speed when using an interpreter and the execution speed when using a compiler. Some systems (such as some Lisps ) allow interpreted and compiled code to call each other and to share variables. This means that once a routine has been tested and debugged under the interpreter it can be compiled and thus benefit from faster execution while other routines are being developed. Many interpreters do not execute
6466-487: The global interpreter lock (GIL), allowing threads to run more concurrently, that latter feature enabled with python3.13t or python3.13t.exe . Python 3.13 introduces some change in behavior, i.e. new "well-defined semantics", fixing bugs (plus many removals of deprecated classes, functions and methods, and removed some of the C ;API and outdated modules): "The [old] implementation of locals() and frame.f_locals
SECTION 60
#17328595981706572-631: The machine learning community. Python was conceived in the late 1980s by Guido van Rossum at Centrum Wiskunde & Informatica (CWI) in the Netherlands as a successor to the ABC programming language, which was inspired by SETL , capable of exception handling and interfacing with the Amoeba operating system. Its implementation began in December ;1989. Van Rossum shouldered sole responsibility for
6678-468: The AST keeps the global program structure and relations between statements (which is lost in a bytecode representation), and when compressed provides a more compact representation. Thus, using AST has been proposed as a better intermediate format for just-in-time compilers than bytecode. Also, it allows the system to perform better analysis during runtime. However, for interpreters, an AST causes more overhead than
6784-612: The CPU-intensive task is not subject to the GIL and may concurrently execute many threads on multiple processors without restriction. Concurrency of Python code can only be achieved with separate CPython interpreter processes managed by a multitasking operating system . This complicates communication between concurrent Python processes , though the multiprocessing module mitigates this somewhat; it means that applications that really can benefit from concurrent Python-code execution can be implemented with limited overhead . The presence of
6890-451: The GIL optional from version 3.13 of Python, which is scheduled for release in October 2024. Unladen Swallow was an optimization branch of CPython, intended to be fully compatible and significantly faster. It aimed to achieve its goals by supplementing CPython's custom virtual machine with a just-in-time compiler built using LLVM . The project had stated a goal of a speed improvement by
6996-410: The GIL simplifies the implementation of CPython, and makes it easier to implement multi-threaded applications that do not benefit from concurrent Python code execution. However, without a GIL, multiprocessing apps must make sure all common code is thread safe. Although many proposals have been made to eliminate the GIL, the general consensus has been that in most cases, the advantages of the GIL outweigh
7102-499: The Google V8 javascript execution engine. A self-interpreter is a programming language interpreter written in a programming language which can interpret itself; an example is a BASIC interpreter written in BASIC. Self-interpreters are related to self-hosting compilers . If no compiler exists for the language to be interpreted, creating a self-interpreter requires the implementation of
7208-672: The Lisp eval function could be implemented in machine code. The result was a working Lisp interpreter which could be used to run Lisp programs, or more properly, "evaluate Lisp expressions". The development of editing interpreters was influenced by the need for interactive computing. In the 1960s, the introduction of time-sharing systems allowed multiple users to access a computer simultaneously, and editing interpreters became essential for managing and modifying code in real-time. The first editing interpreters were likely developed for mainframe computers, where they were used to create and modify programs on
7314-477: The MIPS instruction set and programming languages such as Tcl, Perl, and Java. Performance characteristics are influenced by interpreter complexity, as demonstrated by comparisons with compiled code. It is clear that interpreter performance is more dependent on the nuances and resource needs of the interpreter than it is on the particular application that is being interpreted. Python Enhancement Proposal Python
7420-403: 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 . Python
7526-497: The addition of the assignment expression operator in Python 3.8. Nevertheless, rather than building all of its functionality into its core, Python was designed to be highly extensible via modules. This compact modularity has made it particularly popular as a means of adding programmable interfaces to existing applications. Van Rossum's vision of a small core language with a large standard library and easily extensible interpreter stemmed from his frustrations with ABC , which espoused
7632-415: The amount of analysis performed before the program is executed. For example, Emacs Lisp is compiled to bytecode , which is a highly compressed and optimized representation of the Lisp source, but is not machine code (and therefore not tied to any particular hardware). This "compiled" code is then interpreted by a bytecode interpreter (itself written in C ). The compiled code in this case is machine code for
7738-461: The box. Interpretation cannot be used as the sole method of execution: even though an interpreter can itself be interpreted and so on, a directly executed program is needed somewhere at the bottom of the stack because the code being interpreted is not, by definition, the same as the machine code that the CPU can execute. There is a spectrum of possibilities between interpreting and compiling, depending on
7844-475: The class (for example, SpamClass () or EggsClass () ), and the classes are instances of the metaclass type (itself an instance of itself), allowing metaprogramming and reflection . Before version 3.0, Python had two kinds of classes (both using the same syntax): old-style and new-style ; current Python versions only support the semantics of the new style. Python supports optional type annotations . These annotations are not enforced by
7950-418: The compiled code but it can take less time to interpret it than the total time required to compile and run it. This is especially important when prototyping and testing code when an edit-interpret-debug cycle can often be much shorter than an edit-compile-run-debug cycle. Interpreting code is slower than running the compiled code because the interpreter must analyze each statement in the program each time it
8056-399: The cost of clarity. Execution speed can be improved by moving speed-critical functions to extension modules written in languages such as C, or by using a just-in-time compiler like PyPy . It is also possible to cross-compile to other languages , but it either doesn't provide the full speed-up that might be expected, since Python is a very dynamic language , or a restricted subset of Python
8162-414: The disadvantages; in the few cases where the GIL is a bottleneck, the application should be built around the multiprocessing structure. To help allow more parallelism, an improvement was released in October 2023 to allow a separate GIL per subinterpreter in a single Python process and have been described as "threads with opt-in sharing". After several debates, a project was launched in 2023 to propose making
8268-436: The efficiency of running native code, at the cost of startup time and increased memory use when the bytecode or AST is first compiled. The earliest published JIT compiler is generally attributed to work on LISP by John McCarthy in 1960. Adaptive optimization is a complementary technique in which the interpreter profiles the running program and compiles its most frequently executed parts into native code. The latter technique
8374-414: The expressiveness and elegance of a language. It also enables the interpreter to interpret its source code, the first step towards reflective interpreting. An important design dimension in the implementation of a self-interpreter is whether a feature of the interpreted language is implemented with the same feature in the interpreter's host language. An example is whether a closure in a Lisp -like language
8480-665: The first type. Perl , Raku , Python , MATLAB , and Ruby are examples of the second, while UCSD Pascal is an example of the third type. Source programs are compiled ahead of time and stored as machine independent code, which is then linked at run-time and executed by an interpreter and/or compiler (for JIT systems). Some systems, such as Smalltalk and contemporary versions of BASIC and Java , may also combine two and three types. Interpreters of various types have also been constructed for many languages traditionally associated with compilation, such as Algol , Fortran , Cobol , C and C++ . While interpretation and compilation are
8586-576: The fly. One of the earliest examples of an editing interpreter is the EDT (Editor and Debugger for the TECO) system, which was developed in the late 1960s for the PDP-1 computer. EDT allowed users to edit and debug programs using a combination of commands and macros, paving the way for modern text editors and interactive development environments. An interpreter usually consists of a set of known commands it can execute , and
8692-504: The functions they point to, or fetches the first instruction and jumps to it, and every instruction sequence ends with a fetch and jump to the next instruction. Unlike bytecode there is no effective limit on the number of different instructions other than available memory and address space. The classic example of threaded code is the Forth code used in Open Firmware systems: the source language
8798-475: The host language. Some languages such as Lisp and Prolog have elegant self-interpreters. Much research on self-interpreters (particularly reflective interpreters) has been conducted in the Scheme programming language , a dialect of Lisp. In general, however, any Turing-complete language allows writing of its own interpreter. Lisp is such a language, because Lisp programs are lists of symbols and other lists. XSLT
8904-609: The implicit self (or this ) in some other object-oriented programming languages (e.g., C++ , Java , Objective-C , Ruby ). 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. 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
9010-414: The interpreter and interpreted code and the typical batch environment of the time limited the advantages of interpretation. During the software development cycle , programmers make frequent changes to source code. When using a compiler, each time a change is made to the source code, they must wait for the compiler to translate the altered source files and link all of the binary code files together before
9116-782: The joke about the airspeed velocity of unladen swallows in Monty Python and the Holy Grail . Although it fell short of all published goals, Unladen Swallow did produce some code that got added to the main Python implementation, such as improvements to the cPickle module. In July 2010, some observers speculated on whether the project was dead or dying since the 2009 Q4 milestone had not yet been released. The traffic on Unladen's mailing list had decreased from 500 messages in January 2010 to fewer than 10 in September 2010. It has also been reported that Unladen lost Google's funding. In November 2010, one of
9222-449: The language in a host language (which may be another programming language or assembler ). By having a first interpreter such as this, the system is bootstrapped and new versions of the interpreter can be developed in the language itself. It was in this way that Donald Knuth developed the TANGLE interpreter for the language WEB of the de-facto standard TeX typesetting system . Defining
9328-405: The language into native calls one opcode at a time rather than creating optimized sequences of CPU executable instructions from the entire code segment. Due to the interpreter's simple design of simply passing calls directly to the hardware rather than implementing them directly, it is much faster than every other type, even bytecode interpreters, and to an extent less prone to bugs, but as a tradeoff
9434-507: The language, but may be used by external tools such as mypy to catch errors. Mypy also supports a Python compiler called mypyc, which leverages type annotations for optimization. 1.33333 Python has the usual symbols for arithmetic operators ( + , - , * , / ), the floor division operator // and the modulo operation % (where the remainder can be negative, e.g. 4 % -3 == -2 ). It also has ** for exponentiation , e.g. 5**3 == 125 and 9**0.5 == 3.0 , and
9540-459: The late 1980s as a successor to the ABC programming language and first released it in 1991 as Python 0.9.0. Python 2.0 was released in 2000. Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. Python consistently ranks as one of the most popular programming languages, and has gained widespread use in
9646-633: The limitations of computers at the time (e.g. a shortage of program storage space, or no native support for floating point numbers). Interpreters were also used to translate between low-level machine languages, allowing code to be written for machines that were still under construction and tested on computers that already existed. The first interpreted high-level language was Lisp . Lisp was first implemented by Steve Russell on an IBM 704 computer. Russell had read John McCarthy 's paper, "Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I", and realized (to McCarthy's surprise) that
9752-572: The machine instructions from the underlying electronics so that instructions can be designed and altered more freely. It also facilitates the building of complex multi-step instructions, while reducing the complexity of computer circuits. Writing microcode is often called microprogramming and the microcode in a particular processor implementation is sometimes called a microprogram . More extensive microcoding allows small and simple microarchitectures to emulate more powerful architectures with wider word length , more execution units and so on, which
9858-421: The machine level once and for all (i.e. until the program has to be changed) while an interpreter has to do some of this conversion work every time a statement or function is executed. However, in an efficient interpreter, much of the translation work (including analysis of types, and similar) is factored out and done only the first time a program, module, function, or even statement, is run, thus quite akin to how
9964-418: The main developers announced that "Jeffrey and I have been pulled on to other projects of higher importance to Google." The 2009 Q4 development branch was created on 26 January 2010, but no advertising was made on the website. Further, regarding the long-term plans, and as the project missed the Python 2.7 release, a Python Enhancement Proposal (PEP) was accepted, which proposed a merge of Unladen Swallow into
10070-430: The native instructions), known as a "Template". When the particular code segment is executed the interpreter simply loads or jumps to the opcode mapping in the template and directly runs it on the hardware. Due to its design, the template interpreter very strongly resembles a just-in-time compiler rather than a traditional interpreter, however it is technically not a JIT due to the fact that it merely translates code from
10176-458: The opposite approach. Python claims to strive for a simpler, less-cluttered syntax and grammar while giving developers a choice in their coding methodology. In contrast to Perl 's " there is more than one way to do it " motto, Python embraces a "there should be one—and preferably only one—obvious way to do it." philosophy. In practice, however, Python provides many ways to achieve the same task. There are, for example, at least three ways to format
10282-410: The program being run. The book Structure and Interpretation of Computer Programs presents examples of meta-circular interpretation for Scheme and its dialects. Other examples of languages with a self-interpreter are Forth and Pascal . Microcode is a very commonly used technique "that imposes an interpreter between the hardware and the architectural level of a computer". As such, the microcode
10388-411: The program can be executed. The larger the program, the longer the wait. By contrast, a programmer using an interpreter does a lot less waiting, as the interpreter usually just needs to translate the code being worked on to an intermediate representation (or not translate it at all), thus requiring much less time before the changes can be tested. Effects are evident upon saving the source code and reloading
10494-458: The program. Compiled code is generally less readily debugged as editing, compiling, and linking are sequential processes that have to be conducted in the proper sequence with a proper set of commands. For this reason, many compilers also have an executive aid, known as a Makefile and program. The Makefile lists compiler and linker command lines and program source code files, but might take a simple command line menu input (e.g. "Make 3") which selects
10600-433: The project, as the lead developer, until 12 July 2018, when he announced his "permanent vacation" from his responsibilities as Python's " benevolent dictator for life " (BDFL), a title the Python community bestowed upon him to reflect his long-term commitment as the project's chief decision-maker (he has since come out of retirement and is self-titled "BDFL-emeritus"). In January 2019, active Python core developers elected
10706-619: The same object format). A simple interpreter written in a low-level language (e.g. assembly ) may have similar machine code blocks implementing functions of the high-level language stored, and executed when a function's entry in a look up table points to that code. However, an interpreter written in a high-level language typically uses another approach, such as generating and then walking a parse tree , or by generating and executing intermediate software-defined instructions, or both. Thus, both compilers and interpreters generally turn source code (text files) into tokens, both may (or may not) generate
10812-533: The source code as it stands but convert it into some more compact internal form. Many BASIC interpreters replace keywords with single byte tokens which can be used to find the instruction in a jump table . A few interpreters, such as the PBASIC interpreter, achieve even higher levels of program compaction by using a bit-oriented rather than a byte-oriented program memory structure, where commands tokens occupy perhaps 5 bits, nominally "16-bit" constants are stored in
10918-713: The table refers to support from the Python core team, and not from the distribution maintainer. CPython is one of several "production-quality" Python implementations including: Jython , written in Java for the Java virtual machine (JVM); PyPy , written in RPython and translated into C; and IronPython , written in C# for the Common Language Infrastructure . There are also several experimental implementations. Interpreter (computing) In computer science , an interpreter
11024-506: The third group (set) of instructions then issues the commands to the compiler, and linker feeding the specified source code files. A compiler converts source code into binary instruction for a specific processor's architecture, thus making it less portable . This conversion is made just once, on the developer's environment, and after that the same binary can be distributed to the user's machines where it can be executed without further translation. A cross compiler can generate binary code for
11130-515: The two main means by which programming languages are implemented, they are not mutually exclusive, as most interpreting systems also perform some translation work, just like compilers. The terms " interpreted language " or " compiled language " signify that the canonical implementation of that language is an interpreter or a compiler, respectively. A high-level language is ideally an abstraction independent of particular implementations. Interpreters were used as early as 1952 to ease programming within
11236-410: The user machine even if it has a different processor than the machine where the code is compiled. An interpreted program can be distributed as source code. It needs to be translated in each final machine, which takes more time but makes the program distribution independent of the machine's architecture. However, the portability of interpreted source code is dependent on the target machine actually having
#169830