Command-Line Syntax and Options

Python interpreter command switches leave mixed impression. From the point of view of Perl programmer, first of all  there is no option -w and the interpreter  does not warn you about variables that  appear in program only once, for example there will no warning in the following fragment:

#!/usr/bin/python
import sys
import os
print sys.argv[0]
SCRIPT_NAME='default.sh'
PROGRAM_NAME=sys.argv[0][sys.argv[0].rfind('/')+1:]
dotpos=SCRIPT_NAME.find('.')

• mypy - Optional Static Typing for Python 
• PyFlakes
• PyChecker 
• PySonar: a Static Analyzer for Python.

to get this functionality. See also Tools for static type checking in Python - Stack Overflow. This is inexcusable as all data for such warnings are within the interpreter.

More ambitious project in the same direction is Pylint features — Pylint 2.5.0-dev1 documentation

The Python interpreter command-line syntax can be summarized as follows:

[path]python {options} [-c command | -m module | file | -] {args}

Here, brackets ([]) enclose what’s optional, braces ({}) enclose items of which zero or more may be present, and vertical bars (|) mean a choice among alternatives. Python consistently uses a slash (/) for file paths, as in Unix.

Running a Python script at a command line can be as simple as:

$ python hello.py Hello World 

If the script is not in the current working directory, provide the path to the script:

$ python ./hello/hello.py Hello World 

The filename of the script can be any absolute or relative file path, and need not have any specific extension (though it is conventional to use a .py extension). Each operating system has its own ways to make the Python scripts themselves executable, but we do not cover those details here.

Options are case-sensitive short strings, starting with a hyphen, that ask python  for a nondefault behavior. python  accepts only options that start with a hyphen (-), not with a slash.

Each option’s description gives the environment variable (if any) that, when set, requests the same behavior. Many options have longer versions beginning with two hyphens, as documented in the help available from python -h.  For all details, see the online docs.

Use -i  when you want to get an interactive session immediately after running some script, with top-level variables still intact and available for inspection. You do not need -i  for normal interactive sessions, although it does no harm.

 -t  and -tt  ensure that you use tabs and spaces consistently in Python sources (see “Lines and Indentation” for more information about whitespace usage in Python).

-O  and -OO  yield small savings of time and space in bytecode generated for modules you import, turning assert  statements into no-operations, as covered in “The assert Statement”. -OO  also discards documentation strings.² In v2, only, -Q  determines the behavior of division operator /  when used between two integer operands (we cover division in “Division”). -W  adds an entry to the warnings filter (we cover warnings in “The warnings Module”).

In v2, -u  forces binary mode for standard input, output, and error (not for other file objects). Some platforms, mostly Windows, distinguish binary and text modes. You need binary mode to emit binary data to standard output. -u  also ensures that such output happens immediately, without buffering. You need this when delays due to buffering could cause problems, as in some Unix pipelines. In v3, -u  forces unbuffered output for standard output’s and error’s binary layer (available from their .buffer  attribute), not their text layer.

After the options, if any, comes an indication of which Python script to run. A file path is that of a Python source or bytecode file to run, complete with file extension, if any. On any platform, you may use a slash (/) as the separator between components in this path. On Windows only, you may alternatively use a backslash (\). Instead of a file path, you can use -c command  to execute a Python code string command. command  normally contains spaces, so you need quotes around it to satisfy your operating system’s shell or command-line processor. Some shells (e.g., bash) let you enter multiple lines as a single argument so that command  can be a series of Python statements. Other shells (e.g., Windows shells) limit you to a single line; command can then be one or more simple statements separated by semicolons (;), as discussed in “Statements”.

Another way to specify which Python script to run is -m module. This option tells Python to load and run a module named module  (or the __main__.py member of a package or ZIP file named module) from some directory that is part of Python’s sys.path; this is useful with several modules from Python’s standard library. For example, as covered in “The timeit module”, -m timeit  is often the best way to perform micro-benchmarking of Python statements and expressions.

A hyphen, or the lack of any token in this position, tells the interpreter to read program source from standard input—normally, an interactive session. You need an explicit hyphen only if arguments follow. args  are arbitrary strings; the Python application being run can access these strings as items of the list sys.argv.

For example, on a standard Windows installation, you can enter the following at a command prompt to have Python print the current date and time:

C:\> py -c "import time; print(time.asctime())"

On Cygwin, Linux, OpenBSD, macOS, and other Unix-like systems, with a default installation of Python from sources, enter the following at a shell prompt to start an interactive session with verbose tracing of module import and cleanup:

$ /usr/local/bin/python -v

You can start the command with just python  (you do not have to specify the full path to the Python executable) if the directory of the Python executable is in your PATH  environment variable. (If you have multiple versions of Python installed, you can specify the version, with, for example, python2, python2.7, python3, or python3.5, as appropriate; in this case, the version used if you just say python  is generally the one you installed most recently.)

NEWS CONTENTS

• 200809 : Pylint features - Pylint 2.5.0-dev1 documentation ( pylint.readthedocs.io )
• 200809 : PyChecker is a python source code checking tool to help you find common bugs ( pychecker.sourceforge.net/ )

Old News ;-)

Pylint features - Pylint 2.5.0-dev1 documentation

pylint.readthedocs.io

Pylint is a static type checker for Python (compare with PyChecker 0.4)

David Jeske and Scott Hassan proved that it is possible to do this. They are working on a type inference engine that understands the Python language and can detect type errors and violations.

Adding type checking to python without changing the language will ease the maintenance of a large python project with lots of developers.

Please remember that eGroups before it was bought by Yahoo was a huge Python project (more than 180,000 lines of Python doing everything from a 100% dynamic website to all email delivery, pumping out 200 messages/second on a single 400 MHz Pentium!)

PyChecker is a python source code checking tool to help you find common bugs.

pychecker.sourceforge.net/

The latest version of PyChecker is 0.8.19

PyChecker is a tool for finding bugs in python source code. It finds problems that are typically caught by a compiler for less dynamic languages, like C and C++. It is similar to lint. Because of the dynamic nature of python, some warnings may be incorrect; however, spurious warnings should be fairly infrequent.

PyChecker works in a combination of ways. First, it imports each module. If there is an import error, the module cannot be processed. The import provides some basic information about the module. The code for each function, class, and method is checked for possible problems.

Types of problems that can be found include:

• No global found (e.g., using a module without importing it)
• Passing the wrong number of parameters to functions/methods/constructors
• Passing the wrong number of parameters to builtin functions & methods
• Using format strings that don't match arguments
• Using class methods and attributes that don't exist
• Changing signature when overriding a method
• Redefining a function/class/method in the same scope
• Using a variable before setting it
• self is not the first parameter defined for a method
• Unused globals and locals (module or variable)
• Unused function/method arguments (can ignore self)
• No doc strings in modules, classes, functions, and methods

Here's an article about PyChecker in Unix Review by Cameron Laird and Kathryn Soraiz.

Using PyChecker

To use PyChecker, pass options and the python source files (or packages) you want to check on the command line:

	pychecker [options] file1.py file2.py ...

Some of the most commonly used options are:

Options Description Default value --only only warn about files passed on the command line no -#, --limit the maximum number of warnings to be displayed 10 --no-shadowbuiltin check if a variable shadows a builtin off -q, --stdlib ignore warnings from files under standard library off -T, --argsused unused method/function arguments on

Note: On Windows, use pychecker.bat. You may also need to add python/scripts to your PATH.

pychecker and pychecker.bat will only exist if pychecker has been installed. To install, do: python setup.py install

Note: If you haven't installed pychecker, it can be run by doing: python pychecker/checker.py

An alternate way to use PyChecker is to import it in your code. See Importing PyChecker below for more details.

If there are import dependencies in your source files, you should import those files first on the command line in order to get as many files checked as possible.

PyChecker works with Python 2.0 through 2.7. Some features don't work on earlier versions of Python. PyChecker is tested with Python 2.2 through 2.7 using buildbot.

You can use the test files as examples:

	pychecker test_input/*.py

If you want to change the default behaviour, you can pass command line options or define a .pycheckrc file. For an example, look at pycheckrc.

	pychecker -h

will show the available options.

There is a simple GUI which is not maintained much. It is good for showing all the options and also allows you to run pychecker. To run options, you will need to start it manually:

	python pychecker/options.py

If you want to suppress warnings on a module/function/class/method, you can define a suppressions dictionary in .pycheckrc. Examples of keys are: 'module', 'module.function', 'module.class', 'module.class.method', etc.

You can also define suppressions in your code by doing:

        __pychecker__ = 'no-namedargs maxreturns=0 unusednames=foo,bar'

The format for __pychecker__ values and values in the suppressions dictionary are the same. Dashes (--) are optional when preceding long option names.

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Last modified: August, 09, 2020