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print & logging utilities for communicating with user

Project description

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Author:

Ken Kundert

Version:

1.27.0

Released:

2022-09-15

A package that provides specialized print functions that are used when communicating with the user. It allows you to easily print attractive, informative, and consistent error messages. For example:

>> from inform import display, warn, error
>> display(
..     'Display is like print'
..     'except that it supports logging and can be disabled.'
..     sep=', ')
Display is like print, except that it supports logging and can be disabled.

>> warn('warnings get a header that is printed in yellow.')
warning: warnings get a header that is printed in yellow.

>> error('errors get a header that is printed in red.')
error: errors get a header that is printed in red.

Inform also provides logging and output control.

In addition, Inform provides a powerful generic exception that can be used directly as a general purpose exception, or can be subclassed to produce powerful specialized exceptions. Inform exceptions are unique in that they keep all of the named and unnamed arguments so they can be used when reporting errors.

You can find the documentation on ReadTheDocs. You can download and install the latest stable version of the code from PyPI using:

pip3 install --user --upgrade inform

You can find the latest development version of the source code on Github.

Supported in Python2.7, Python3.5, Python3.6, Python3.7 and Python3.8.

Introduction

This package defines a collection of print functions that have different roles. These functions are referred to as informants and are described below in the Informants section. They include include log, comment, codicil, narrate, display, output, notify, debug, warn, error, fatal and panic.

With the simplest use of the program, you simply import the informants you need and call them (they take the same arguments as Python’s built-in print function):

>>> from inform import display
>>> display('ice', 9)
ice 9

For more control of the informants, you can import and instantiate the Inform class yourself along with the desired informants. This gives you the ability to specify options:

>>> from inform import Inform, display, error
>>> Inform(logfile=False, prog_name=False)
<...>
>>> display('hello')
hello
>>> error('file not found.', culprit='data.in')
error: data.in: file not found.

An object of the Inform class is referred to as an informer (not to be confused with the print functions, which are referred to as informants). Once instantiated, you can use the informer to change various settings, terminate the program, or return a count of the number of errors that have occurred.

>>> from inform import Inform, error
>>> informer = Inform(prog_name="prog")
>>> error('file not found.', culprit='data.in')
prog error: data.in: file not found.
>>> informer.errors_accrued()
1

You can create your own informants:

>>> from inform import Inform, InformantFactory

>>> verbose1 = InformantFactory(output=lambda m: m.verbosity >= 1)
>>> verbose2 = InformantFactory(output=lambda m: m.verbosity >= 2)
>>> with Inform(verbosity=0):
...     verbose1('First level of verbosity.')
...     verbose2('Second level of verbosity.')

>>> with Inform(verbosity=1):
...     verbose1('First level of verbosity.')
...     verbose2('Second level of verbosity.')
First level of verbosity.

>>> with Inform(verbosity=2):
...     verbose1('First level of verbosity.')
...     verbose2('Second level of verbosity.')
First level of verbosity.
Second level of verbosity.

The argument verbosity is not an explicitly supported argument to Inform. In this case Inform simply saves the value and makes it available as an attribute, and it is this attribute that is queried by the lambda function passed to the InformantFactory when creating the informants.

Exception

An exception, Error, is provided that takes the same arguments as an informant. This allows you to catch the exception and handle it if you like. The exception provides the report and terminate methods that processes the exception as an error or fatal error if you find that you can do nothing else with the exception:

>>> from inform import Inform, Error

>>> Inform(prog_name='myprog')
<...>
>>> try:
...     raise Error('must not be zero.', culprit='naught')
... except Error as e:
...     e.report()
myprog error: naught: must not be zero.

Error also provides get_message() and get_culprit() methods, which return the message and the culprit. You can also cast the exception to a string to get a string that contains both the message and the culprit formatted so that it can be shown to the user.

Any keyword arguments provided will be available in e.kwargs, but certain keyword arguments are reserved by inform (see above).

One common approach to using Error is to pass all the arguments that make up the error message as unnamed arguments and then assemble them into the message by providing a template. In that way the arguments are directly available to the handler if needed. For example:

>>> from difflib import get_close_matches
>>> from inform import Error, codicil, conjoin, fmt

>>> known_names = 'alpha beta gamma delta epsilon'.split()
>>> name = 'alfa'

>>> try:
...     if name not in known_names:
...         raise Error(name, template="name '{}' is not defined.")
... except Error as e:
...     candidates = get_close_matches(e.args[0], known_names, 1, 0.6)
...     candidates = conjoin(candidates, conj=' or ')
...     e.report()
...     codicil(fmt('Did you mean {candidates}?'))
myprog error: name 'alfa' is not defined.
    Did you mean alpha?

Utilities

Several utility functions are provided for your convenience. They are often helpful when creating messages.

indent:

Indents the text.

conjoin:

Like ‘’.join(), but allows you to specify a conjunction that is placed between the last two elements, ex:

>>> from inform import conjoin
>>> conjoin(['a', 'b', 'c'])
'a, b and c'

>>> conjoin(['a', 'b', 'c'], conj=' or ')
'a, b or c'
cull:

Strips items from a collection that have a particular value.

join:

Combines the arguments in a manner very similar to an informant and returns the result as a string.

fmt:

Similar to ‘’.format(), but it can pull arguments from the local scope.

render:

Recursively convert an object to a string with reasonable formatting. Has built in support for the base Python types (None, bool, int, float, str, set, tuple, list, and dict). If you confine yourself to these types, the output of render() can be read by the Python interpreter. Other types are converted to string with repr().

plural:

Produces either the singular or plural form of a word based on a count.

full_stop:

Adds a period to the end of the string if needed (if the last character is not a period, question mark or exclamation mark).

columns:

Distribute array over enough columns to fill the screen.

os_error:

Generates clean messages for operating system errors.

is_str:

Returns True if its argument is a string-like object.

is_iterable:

Returns True if its argument is iterable.

is_collection:

Returns True if its argument is iterable but is not a string.

is_mapping:

Returns True if its argument is a mapping (are dictionary like).

For example:

>>> from inform import Inform, display, error, conjoin, cull, fmt, os_error

>>> Inform(prog_name=False)
<...>
>>> filenames = cull(['a', 'b', None, 'd'])
>>> filetype = 'CSV'
>>> display(
...     fmt(
...         'Reading {filetype} files: {names}.',
...         names=conjoin(filenames),
...     )
... )
Reading CSV files: a, b and d.

>>> contents = {}
>>> for name in filenames:
...     try:
...         with open(name) as f:
...             contents[name] = f.read()
...     except IOError as e:
...         error(os_error(e))
error: a: no such file or directory.
error: b: no such file or directory.
error: d: no such file or directory.

Notice that filetype was not explicitly passed into fmt() even though it was explicitly called out in the format string. filetype can be left out of the argument list because if fmt does not find a named argument in its argument list, it will look for a variable of the same name in the local scope.

Here is an example of render():

>>> from inform import render, display
>>> s1='alpha string'
>>> s2='beta string'
>>> n=42
>>> S={s1, s2}
>>> L=[s1, n, S]
>>> d = {1:s1, 2:s2}
>>> D={'s': s1, 'n': n, 'S': S, 'L': L, 'd':d}
>>> display('D', '=', render(D, True))
D = {
    'L': [
        'alpha string',
        42,
        {'alpha string', 'beta string'},
    ],
    'S': {'alpha string', 'beta string'},
    'd': {1: 'alpha string', 2: 'beta string'},
    'n': 42,
    's': 'alpha string',
}

Finally, here is an example of full_stop and columns. It prints out the phonetic alphabet.

>>> from inform import columns, full_stop
>>> title = 'Display the NATO phonetic alphabet'
>>> words = """
...     Alfa Bravo Charlie Delta Echo Foxtrot Golf Hotel India Juliett Kilo
...     Lima Mike November Oscar Papa Quebec Romeo Sierra Tango Uniform
...     Victor Whiskey X-ray Yankee Zulu
... """.split()
>>> display(full_stop(title), columns(words), sep='\n')
Display the NATO phonetic alphabet.
    Alfa      Echo      India     Mike      Quebec    Uniform   Yankee
    Bravo     Foxtrot   Juliett   November  Romeo     Victor    Zulu
    Charlie   Golf      Kilo      Oscar     Sierra    Whiskey
    Delta     Hotel     Lima      Papa      Tango     X-ray

Debugging Functions

The debugging functions are intended to be used when you want to print something out when debugging your program. They are colorful to make it easier to find them among the program’s normal output, and a header is added that describes the location they were called from. This makes it easier to distinguish several debug message and also makes it easy to find and remove the functions once you are done debugging.

ppp:

This function is very similar to the normal Python print function.

>>> from inform import ppp, ddd, sss, vvv
>>> a = 1
>>> b = 'this is a test'
>>> c = (2, 3)
>>> d = {'a': a, 'b': b, 'c': c}
>>> ppp(a, b, c)
DEBUG: <doctest README.rst[52]>, 1, __main__: 1 this is a test (2, 3)
ddd:

This function is pretty prints all of both the unnamed and named arguments.

>>> ddd(a, b, c=c, d=d)
DEBUG: <doctest README.rst[53]>, 1, __main__:
    1
    'this is a test'
    c = (2, 3)
    d = {
        'a': 1,
        'b': 'this is a test',
        'c': (2, 3),
    }

If you give named arguments, the name is prepended to its value.

vvv:

This function prints variables from the calling scope. If no arguments are given, then all the variables are printed. You can optionally give specific variables on the argument list and only those variables are printed.

>>> vvv(b, d)
DEBUG: <doctest README.rst[54]>, 1, __main__:
    b = 'this is a test'
    d = {
        'a': 1,
        'b': 'this is a test',
        'c': (2, 3),
    }
sss:

This function prints a stack trace, which can answer the How did I get here? question better than a simple print function.

>> def foo():
..     sss()
..     print('CONTINUING')

>> foo()
DEBUG: <doctest README.rst[93]>:2, __main__.foo():
    Traceback (most recent call last):
        ...
CONTINUING

Color Class

The Color class creates colorizers, which are used to render text in a particular color. They are like the Python print function in that they take any number of unnamed arguments that are converted to strings and then joined into a single string. The string is then coded for the chosen color and returned. For example:

>> from inform import Color, display

>> green = Color('green')
>> red = Color('red')
>> success = green('pass:')
>> failure = red('FAIL:')

>> failures = {'outrigger': True, 'signalman': False}
>> for name, fails in failures.items():
..     result = failure if fails else success
..     display(result, name)
FAIL: outrigger
pass: signalman

When the messages print, the ‘pass:’ will be green and ‘FAIL:’ will be red.

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