Skulpt is an entirely in-browser implementation of Python.

1. Basic example¶ The unittest module provides a rich set of tools for constructing and running tests.
2. Python offers a series of command-line options that you can use according to your needs. For example, if you want to run a Python module, you can use the command python -m. The -m option searches sys.path for the module name and runs its content as main: $ python3 -m hello Hello World!

No preprocessing, plugins, or server-side support required, just write Python and reload.

You can use this Python online editor to execute your Python programs. Step-1 Type your source using available text editor in this Online Python Compiler. Step-2 Click Run to get the Output from this Python Interpreter Online. Note: Before Compilation and using this Python IDE online, you must know about Python.

• cut/copy/paste/undo/redo with the usual shortcut keys
• Tab does decent indenting. Thanks to CodeMirror for the text editor.
• Ctrl-Enter to run, Shift-Enter to run selected

Help, or examples: 12345678. Ctrl-Enter to run.

The code is run entirely in your browser, so don't feel obligated to 'crash the server', you'll only stub your toe.

Interactive:

This is a very cool new feature that is just getting off the ground. This would be a great project to jump in and help out on!

What's New?

• Python 3 Grammar. The master branch is now building and running using the grammar for Python 3.7.3. There are still lots of things to implement under the hood, but we have made a huge leap forward in Python 3 compatibility. We will still support Python 2 as an option going forward for projects that rely on it.
• Node JS and Webpack -- We have updated our toolchain for development to use node and webpack.
• Suspensions! This may not mean a lot to you, but trust me its going to be big. Suspensions provide the foundation for the asynchronous execution we need to build an interactive debugger, a smoother turtle module, enhanced urllib and other cool features. For developers you should check out the time module and the suspensions.txt file under doc/.
• Stub implementations of the standard library modules. You will now get an unimplemented exceptions rather than some other file not found error.
• General cleanup and standardization of the code. See the short description of the coding standards in the CONTRIBUTING file
• Loads of bugfixes: see
• slice() function implemented. And improvements to list slicing.
• string and operator module added.
• Keyword arguments for sorted()
• text() function in processing

By these awesome people: Brad Miller, Scott Rixner, Albert-Jan Nijburg, Marie Chatfield, Isaac Dontje Lindell, jaspervdg, Ethan Steinberg, Jeff-Tian, Meredydd Luff and Leszek Swirski

License

Skulpt may be licensed under:

1. The MIT license.
2. Or, for compatibility with Python, the PSFLv2.

Please note that this dual license only applies to the part of Skulpt that is included in the runtime, and not necessarily to surrounding code for build processing or testing. Tests are run using V8, and Closure Compiler, and some test code is taken from the tinypy and Python test suites, which may be distributed under different licensing terms.

About

The Father of skulpt is Scott Graham, you can find his blog here: personal page (and blog)

My own personal page and blog is Reputable Journal

Yes, I know how 'sculpt' is spelled. The correct spelling was thoroughly reserved according to ICANN and search engines.

Note

This document assumes you are working from anin-development checkout of Python. If youare not then some things presented here may not work as they may dependon new features not available in earlier versions of Python.

Running¶

The shortest, simplest way of running the test suite is the following commandfrom the root directory of your checkout (after you havebuilt Python):

You may need to change this command as follows throughout this section.On most Mac OS X systems, replace ./pythonwith ./python.exe. On Windows, use python.bat. If usingPython 2.7, replace test with test.regrtest.

If you don’t have easy access to a command line, you can run the test suite froma Python or IDLE shell:

This will run the majority of tests, but exclude a small portion of them; theseexcluded tests use special kinds of resources: for example, accessing theInternet, or trying to play a sound or to display a graphical interface onyour desktop. They are disabled by default so that running the test suiteis not too intrusive. To enable some of these additional tests (and forother flags which can help debug various issues such as reference leaks), readthe help text:

If you want to run a single test file, simply specify the test file name(without the extension) as an argument. You also probably want to enableverbose mode (using -v), so that individual failures are detailed:

To run a single test case, use the unittest module, providing the importpath to the test case:

If you have a multi-core or multi-CPU machine, you can enable parallel testingusing several Python processes so as to speed up things:

If you are running a version of Python prior to 3.3 you must specify the numberof processes to run simultaneously (e.g. -j2).

Python Runner

Finally, if you want to run tests under a more strenuous set of settings, youcan run test as:

The various extra flags passed to Python cause it to be much stricter aboutvarious things (the -Wd flag should be -Werror at some point, but thetest suite has not reached a point where all warnings have been dealt with andso we cannot guarantee that a bug-free Python will properly complete a test runwith -Werror). The -r flag to the test runner causes it to run tests ina more random order which helps to check that the various tests do not interferewith each other. The -w flag causes failing tests to be run again to seeif the failures are transient or consistent.The -uall flag allows the use of all availableresources so as to not skip tests requiring, e.g., Internet access.

To check for reference leaks (only needed if you modified C code), use the-R flag. For example, -R3:2 will first run the test 3 times to settledown the reference count, and then run it 2 more times to verify if there areany leaks.

You can also execute the Tools/scripts/run_tests.py script as found in aCPython checkout. The script tries to balance speed with thoroughness. But ifyou want the most thorough tests you should use the strenuous approach shownabove.

Unexpected Skips¶

Sometimes when running the test suite, you will see “unexpected skips”reported. These represent cases where an entire test module has beenskipped, but the test suite normally expects the tests in that module tobe executed on that platform.

Often, the cause is that an optional module hasn’t been built due to missingbuild dependencies. In these cases, the missing module reported when the testis skipped should match one of the modules reported as failing to build whenCompile and build.

In other cases, the skip message should provide enough detail to help figureout and resolve the cause of the problem (for example, the default securitysettings on some platforms will disallow some tests)

Python Runner Command

Writing¶

Writing tests for Python is much like writing tests for your own code. Testsneed to be thorough, fast, isolated, consistently repeatable, and as simple aspossible. We try to have tests both for normal behaviour and for errorconditions. Tests live in the Lib/test directory, where every file thatincludes tests has a test_ prefix.

One difference with ordinary testing is that you are encouraged to rely on thetest.support module. It contains various helpers that are tailored toPython’s test suite and help smooth out common problems such as platformdifferences, resource consumption and cleanup, or warnings management.That module is not suitable for use outside of the standard library.

When you are adding tests to an existing test file, it is also recommendedthat you study the other tests in that file; it will teach you which precautionsyou have to take to make your tests robust and portable.

Benchmarks¶

Benchmarking is useful to test that a change does not degrade performance.

The Python Benchmark Suitehas a collection of benchmarks for all Python implementations. Documentationabout running the benchmarks is in the README.txt of the repo.