User’s Guide¶

Using Informants¶

This package defines a collection of ‘print’ functions that are referred to as informants. They include include log, comment, codicil, narrate, display, output, notify, debug, warn, error, fatal and panic.

They all take arguments in a manner that is a generalization of Python’s built-in print function. Each of the informants is used for a specific purpose, but they all take and process arguments in the same manner. These functions are distinguished in the Predefined Informants section. In this section, the manner in which they process their arguments is presented.

With the simplest use of the program, you simply import the informants you need and call them, placing those things that you wish to print in the argument list as unnamed arguments:

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

Informant Arguments¶

By default, all of the unnamed arguments converted to strings and then joined together using a space between each argument. However, you can use named arguments to change this behavior. The following named arguments are used to control the informants:

sep = ‘ ‘:: Specifies the string used to join the unnamed arguments.
end = ‘\n’:: Specifies a string to append to the message.
file:: The destination stream (a file pointer).
flush = False:: Whether the message should flush the destination stream (not available in python2).
culprit = None:: A string that is added to the beginning of the message that identifies the culprit (the object for which the problem being reported was found). May also be a number or a tuple that contains strings and numbers. If culprit is a tuple, the members are converted to strings and joined with culprit_sep (default is ‘, ‘).
codicil = None:: A string or a collection of strings that contain messages that are printed after the primary message.
wrap = False:: Specifies whether message should be wrapped. wrap may be True, in which case the default width of 70 is used. Alternately, you may specify the desired width. The wrapping occurs on the final message after the arguments have been joined.
template = None:: A template that if present interpolates the arguments to form the final message rather than simply joining the unnamed arguments with sep. The template is a string, and its format method is called with the unnamed and named arguments of the message passed as arguments. template may also be a collection of strings, in which case the first template for which all the necessary arguments are available is used.
remove:: Specifies the argument values that are unavailable to the template.

The first four are also accepted by Python’s built-in print function and have the same behavior.

This example makes use of the sep and end named arguments:

>>> from inform import display

>>> actions = ['r: rewind', 'p: play/pause', 'f: fast forward']
>>> display('The choices include', *actions, sep=',\n    ', end='.\n')
The choices include,
    r: rewind,
    p: play/pause,
    f: fast forward.

Culprits¶

culprit is used to identify the target of the message. If the message is pointing out a problem, the culprit is generally the source of the problem.

Here is a simple example:

>>> from inform import error

>>> error('file not found.', culprit='now-playing')
error: now-playing: file not found.

Here is an example that demonstrates the wrap and composite culprit features:

>>> value = -1
>>> error(
...     'Encountered illegal value',
...     value,
...     'when filtering.  Consider regenerating the dataset.',
...     culprit=('input.data', 32), wrap=True,
... )
error: input.data, 32:
    Encountered illegal value -1 when filtering.  Consider regenerating
    the dataset.

Occasionally the actual culprits are not available where the messages are printed. In this case you can use culprit caching. Simply cache the culprits in you informer using set_culprit() or add_culprit() and then recall them when needed using get_culprit(). Both set_culprit and add_culprit are designed to be used with Python’s with statement.

The following example illustrates the used of culprit caching. Here, the code is spread over several functions, and the various culprits are known locally but are not passed directly into the function that may report the error. Rather than explicitly passing the culprits into the various functions, which would clutter up their argument lists, the culprits are cached in case they are needed.

>>> from inform import add_culprit, get_culprit, set_culprit, error

>>> def read_param(line, parameters):
...    name, value = line.split(' = ')
...    try:
...        parameters[name] = float(value)
...    except ValueError:
...        error(
...            'expected a number, found:', value,
...            culprit=get_culprit(name)
...        )

>>> def read_params(lines):
...    parameters = {}
...    for lineno, line in enumerate(lines):
...        with add_culprit(lineno+1):
...            read_param(line, parameters)

>>> filename = 'parameters'
>>> with open(filename) as f, set_culprit(filename):
...    lines = f.read().splitlines()
...    parameters = read_params(lines)
error: parameters, 3, c: expected a number, found: ack

Templates¶

The template strings are the same as one would use with Python’s built-in format function and string method (as described in Format String Syntax). The template string can interpolate either named or unnamed arguments. In this example, named arguments are interpolated:

>>> colors = {
...     'red': ('ff5733', 'failure'),
...     'green': ('4fff33', 'success'),
...     'blue': ('3346ff', None),
... }

>>> for key in sorted(colors.keys()):
...     val = colors[key]
...     display(k=key, v=val, template='{k:>5s} = {v[0]}')
 blue = 3346ff
green = 4fff33
  red = ff5733

You can also specify a collection of templates. The first one for which all keys are available is used. For example;

>>> for name in sorted(colors.keys()):
...     code, desc = colors[name]
...     display(name, code, desc, template=('{:>5s} = {}  — {}', '{:>5s} = {}'))
 blue = 3346ff
green = 4fff33  — success
  red = ff5733  — failure

>>> for name in sorted(colors.keys()):
...     code, desc = colors[name]
...     display(k=name, v=code, d=desc, template=('{k:>5s} = {v}  — {d}', '{k:>5s} = {v}'))
 blue = 3346ff
green = 4fff33  — success
  red = ff5733  — failure

The first loop interpolates positional (unnamed) arguments, the second interpolates the keyword (named) arguments.

By default, the values that are considered unavailable and so will invalidate a template are those that would be False when cast to a Boolean. So, by default, the following values are considered unavailable: 0, False, None, ‘’, (), [], {}, etc. You can use the remove named argument to control this. remove may be a function, a collection, or a scalar. The function would take a single argument that is the value to consider and return True if the value should be unavailable. The scalar or the collection simply specifies the value or values that should be unavailable.

>>> accounts = dict(checking=1100, savings=0, brokerage=None)

>>> for name, amount in sorted(accounts.items()):
...     display(name, amount, template=('{:>10s} = ${}', '{:>10s} = NA'), remove=None)
 brokerage = NA
  checking = $1100
   savings = $0

Predefined Informants¶

The following informants are predefined in Inform. You can create custom informants using InformantFactory.

All of the informants except panic and debug do not produce any output if mute is set.

log¶

log = InformantFactory(
    output=False,
    log=True,
)

Saves a message to the log file without displaying it.

comment¶

comment = InformantFactory(
    output=lambda informer: informer.verbose and not informer.mute,
    log=True,
    message_color='cyan',
)

Displays a message only if verbose is set. Logs the message. The message is displayed in cyan when writing to the console.

Comments are generally used to document unusual occurrences that might warrant the user’s attention.

codicil¶

codicil = InformantFactory(is_continuation=True)

Continues a previous message. Continued messages inherit the properties (output, log, message color, etc) of the previous message. If the previous message had a header, that header is not output and instead the message is indented.

>>> from inform import Inform, warn, codicil
>>> informer = Inform(prog_name="myprog")
>>> warn('file not found.', culprit='ghost')
myprog warning: ghost: file not found.

>>> codicil('skipping')
    skipping

narrate¶

narrate = InformantFactory(
    output=lambda informer: informer.narrate and not informer.mute,
    log=True,
    message_color='blue',
)

Displays a message only if narrate is set. Logs the message. The message is displayed in blue when writing to the console.

Narration is generally used to inform the user as to what is going on. This can help place errors and warnings in context so that they are easier to understand. Distinguishing narration from comments allows them to colored differently and controlled separately.

display¶

display = InformantFactory(
    output=lambda informer: not informer.quiet and not informer.mute,
    log=True,
)

Displays a message if quiet is not set. Logs the message.

>>> from inform import display
>>> display('We the people ...')
We the people ...

output¶

output = InformantFactory(
    output=lambda informer: not informer.mute,
    log=True,
)

Displays and logs a message. This is used for messages that are not errors and that are noteworthy enough that they need to get through even though the user has asked for quiet.

>>> from inform import output
>>> output('The sky is falling!')
The sky is falling!

notify¶

notify = InformantFactory(
    notify=True,
    log=True,
)

Temporarily display the message in a bubble at the top of the screen. Also sends it to the log file. This is used for messages that the user is otherwise unlikely to see because they have no access to the standard output.

When using notify you may pass in the urgency named argument to specify the urgency of the notification. Its value must ‘low’, ‘normal’, or ‘critical’ or it will be ignored.

debug¶

debug = InformantFactory(
    severity='DEBUG',
    output=True,
    log=True,
    header_color='magenta',
)

Displays and logs a debugging message. A header with the label DEBUG is added to the message and the header is colored magenta.

>>> from inform import Inform, debug
>>> informer = Inform(prog_name="myprog")
>>> debug('HERE!')
myprog DEBUG: HERE!

Generally one does not use the debug informant directly. Instead one uses the available debugging functions: aaa(), ddd(), ppp(), sss() and vvv().

warn¶

warn = InformantFactory(
    severity='warning',
    header_color='yellow',
    output=lambda informer: not informer.quiet and not informer.mute,
    log=True,
)

Displays and logs a warning message. A header with the label warning is added to the message. The header is colored yellow when writing to the console.

>>> from inform import Inform, warn
>>> informer = Inform(prog_name="myprog")
>>> warn('file not found, skipping.', culprit='ghost')
myprog warning: ghost: file not found, skipping.

error¶

error = InformantFactory(
    severity='error',
    is_error=True,
    header_color='red',
    output=lambda informer: not informer.mute,
    log=True,
)

Displays and logs an error message. A header with the label error is added to the message. The header is colored red when writing to the console.

>>> from inform import Inform, error
>>> informer = Inform(prog_name="myprog")
>>> error('invalid value specified, expected a number.', culprit='count')
myprog error: count: invalid value specified, expected a number.

fatal¶

fatal = InformantFactory(
    severity='error',
    is_error=True,
    terminate=1,
    header_color='red',
    output=lambda informer: not informer.mute,
    log=True,
)

Displays and logs an error message. A header with the label error is added to the message. The header is colored red when writing to the console. The program is terminated with an exit status of 1.

>> from inform import fatal, os_error
>> try:
..     with open('config') as f:
..         read_config(f.read())
.. except OSError as e:
..     fatal(os_error(e), codicil='Cannot continue.')
myprog error: config: file not found
    Cannot continue.

panic¶

panic = InformantFactory(
    severity='internal error (please report)',
    is_error=True,
    terminate=3,
    header_color='red',
    output=True,
    log=True,
)

Displays and logs a panic message. A header with the label internal error is added to the message. The header is colored red when writing to the console. The program is terminated with an exit status of 3.

Modifying Existing Informants¶

You may adjust the behavior of existing informants by overriding the attributes that were passed in when they were created. For example, in many cases you might prefer that normal program output is not logged, either because it is voluminous or because it is sensitive. In that case you can simply override the log attributes for the display and output informants like so:

from inform import display, output
display.log = False
output.log = False

Any attribute that can be passed into InformantFactory when creating an informant can be overridden. However, when overriding a color you must use a colorizer rather than a color name:

from inform import comment, Color
comment.message_color=Color('cyan')

Informant Control¶

For more control of the informants, you can import and instantiate the Inform class 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, quiet=True)
<...>

>>> display('hello')

>>> error('file not found.', culprit='data.in')
error: data.in: file not found.

In this example the logfile argument disables opening and writing to the logfile. The prog_name argument stops Inform from adding the program name to the error message. And quiet turns off non-essential output, and in this case it causes the output of display to be suppressed.

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, return a count of the number of errors that have occurred, etc.

>>> 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 also use a with statement to invoke the informer. This activates the informer for the duration of the with statement, returning to the previous informer when the with statement terminates. This is useful when writing tests. In this case you can provide your own output streams so that you can access the normally printed output of your code:

>>> from inform import Inform, display
>>> import sys
>>> if sys.version[0] == '2':
...     # io assumes unicode, which python2 does not provide by default
...     # so use StringIO instead
...     from StringIO import StringIO
...     # Add support for with statement by monkeypatching
...     StringIO.__enter__ = lambda self: self
...     StringIO.__exit__ = lambda self, exc_type, exc_val, exc_tb: self.close()
... else:
...     from io import StringIO

>>> def run_test():
...     display('running test')

>>> with StringIO() as stdout, \
...      StringIO() as stderr, \
...      StringIO() as logfile, \
...      Inform(stdout=stdout, stderr=stderr, logfile=logfile) as msg:
...         run_test()
...
...         num_errors = msg.errors_accrued()
...         output_text = stdout.getvalue()
...         error_text = stderr.getvalue()
...         logfile_text = logfile.getvalue()

>>> num_errors
0

>>> str(output_text)
'running test\n'

>>> str(error_text)
''

>>> str(logfile_text.strip().split('\n')[-1])
'running test'

Logfiles¶

To configure Inform to generate a logfile you can specify the logfile to Inform or to Inform.set_logfile(). The logfile can be specified as a string, a pathlib.Path, an open stream, or as a Boolean. If True, a logfile is created and named ./<prog_name>.log. If False, no logfile is created. In addition, if you want to defer the decision on what should be the logfile without losing the log messages that occur before the ultimate destination of those messages is set, you can use an instance of LoggingCache, which simply saves the messages in memory until it is replaced, at which point they are transferred to the new logfile. For example:

>>> from inform import Inform, LoggingCache, log, indent
>>> with Inform(logfile=LoggingCache()) as inform:
...     log("This message is cached.")
...     inform.set_logfile(".mylog")
...     log("This message is not cached.")

>>> with open(".mylog") as f:
...     print("Contents of logfile:")
...     print(indent(f.read()), end='')  # +ELLIPSIS
Contents of logfile:
    ...
    This message is cached.
    This message is not cached.

An existing logfile will be renamed before creating the logfile if you specify prev_logfile_suffix to Inform.

Message Destination¶

You can specify the output stream when creating an informant. If you do not, then the stream uses is under the control of Inform’s stream_policy argument.

If stream_policy is set to ‘termination’, then all messages are sent to the standard output except the final termination message, which is set to standard error. This is suitable for programs whose output largely consists of status messages rather than data, and so would be unlikely to be used in a pipeline.

If stream_policy is ‘header’. then all messages with headers (those messages produced from informants with severity) are sent to the standard error stream and all other messages are sent to the standard output. This is more suitable for programs whose output largely consists of data and so would likely be used in a pipeline.

It is also possible for stream_policy to be a function that takes three arguments, the informant and the standard output and error streams. It should return the desired stream.

If True is passed to the notify_if_no_tty Inform argument, then error messages are sent to the notifier if the standard output is not a TTY.

User Defined Informants¶

You can create your own informants using InformantFactory. One application of this is to support multiple levels of verbosity. To do this, an informant would be created for each level of verbosity, as follows:

>>> 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 of 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 InformantFactory when creating the informants.

Another use for user-defined informants is to create print functions that output is a particular color:

>>> from inform import InformantFactory

>>> succeed = InformantFactory(message_color='green')
>>> fail = InformantFactory(message_color='red')

>>> succeed('This message would be green.')
This message would be green.

>>> fail('This message would be red.')
This message would be red.

A common use for this would be to have success and failure messages. For example, if your program runs a series of tests, the successes could be printed in green and the failures in red. In addition, the success informant may be configured to suppress the messages if the user asks for quiet. In that case, only the failures would be displayed.

Exceptions¶

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. Any arguments you pass into the exception are retained and are available when processing the exception. The exception provides the Error.report() and Error.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.

Besides culprit, you can use any of the named arguments accepted by informants. In addition, you can also use informant as a named argument. informant changes the informant that is used when reporting the error. It is often used to convert an exception to a warning or to a fatal error. For example:

>>> from inform import Inform, Error, warn

>>> Inform(prog_name='myprog')
<...>
>>> def read_files(filenames):
...     files = {}
...     for filename in filenames:
...        try:
...            with open(filename) as f:
...                files[filename] = f.read()
...        except FileNotFoundError:
...            raise Error('missing.', culprit=filename, informant=warn)
...     return files

>>> filenames = 'parameters swallows worlds'.split()
>>> try:
...     files = read_files(filenames)
... except Error as e:
...     files = None
...     e.report()
myprog warning: worlds: missing.

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

All positional arguments are available in e.args and any keyword arguments provided are available in e.kwargs.

One common approach to using Error is to pass all the arguments that make up the error message as 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, choices=known_names, template="name '{}' is not defined.")
... except Error as e:
...     candidates = get_close_matches(e.args[0], e.choices, 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?

Notice that useful information (choices) is passed into the exception that may be useful when processing the exception even though it is not incorporated into the message.

You can override the template by passing a new one to Error.get_message() or Error.render(). With Error.report() or Error.terminate() you can override any named argument, such as template or culprit. This can be helpful if you need to translate a message or change it to make it more meaningful to the end user:

>>> try:
...     raise Error(name, template="name '{}' is not defined.")
... except Error as e:
...     e.report(template="'{}' ist nicht definiert.")
myprog error: 'alfa' ist nicht definiert.

You can catch an Error exception and then reraise it after modifying its named arguments using Error.reraise(). This is helpful when all the information needed for the error message is not available where the initial exception is detected. Typically new culprits or codicils are added. For example, in the following the filename is added to the exception using reraise in parse_file:

>>> def parse_lines(lines):
...     values = {}
...     for i, line in enumerate(lines):
...         try:
...             k, v = line.split()
...         except ValueError:
...             raise Error('syntax error.', culprit=i+1)
...         values[k] = v
...     return values

>>> def parse_file(filename):
...     try:
...         with open(filename) as f:
...             return parse_lines(f.read().splitlines())
...     except Error as e:
...         e.reraise(culprit=e.get_culprit(filename))

>>> try:
...     unladen_airspeed = parse_file('swallows')
... except Error as e:
...     e.report()
myprog error: swallows, 2: syntax error.

This example uses Error.get_culprit() to access the existing culprit or culprits of the exception. Regardless of how many there are, they are always returned as a culprit. It also accepts a culprit as an argument, which is returned along with and before the culprit from the exception.

Also available is Error.get_codicil(), which behaves similarly except with codicils rather than culprits and the argument is added after the codicil from the exception rather than before.

Subclassing Error¶

When creating subclasses of Error you can add a template to the subclass as a way of specifying the error message or messages that are to be used for that exception. For example:

>>> class InvalidValueError(Error):
...     template = 'invalid value.'

>>> try:
...     raise InvalidValueError()
... except Error as e:
...     e.report()
myprog error: invalid value.

You can include named and unnamed arguments of the exception in the template:

>>> class InvalidValueError(Error):
...     template = 'must not be {}.'

>>> try:
...     raise InvalidValueError('negative', culprit='rate')
... except Error as e:
...     e.report()
myprog error: rate: must not be negative.

You can also specify a list of templates that are tried in order, the first for which all arguments are available is used:

>>> class InvalidValueError(Error):
...     template = [
...         '{} must fall between {min} and {max}.',
...         '{} must be greater than {min}.',
...         '{} must be less than {max}.',
...         '{} must not be {illegal}.',
...         '{} must be {legal}.',
...         '{} is invalid.',
...         'invalid value.',
...     ]

>>> rate = -1.0
>>> try:
...     if rate < 0:
...         raise InvalidValueError(rate, illegal='negative', culprit='rate')
... except Error as e:
...     e.report()
myprog error: rate: -1.0 must not be negative.

Utilities¶

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

Color Class¶

The Color class creates colorizers, which are functions used to render text in a particular color. They combine their arguments in a manner very similar to an informant and returns the result as a string, except the string is coded for the chosen color. Uses the sep, template and wrap keyword arguments to combine the arguments.

>> 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.

The Color class has the concept of a colorscheme. There are four supported schemes: None, True, ‘light’, and ‘dark’. With None the text is not colored, with True the colorscheme of the currently active informer is used. In general it is best to use the ‘light’ colorscheme on dark backgrounds and the ‘dark’ colorscheme on light backgrounds. You can pass in the colorscheme using the scheme argument either to the color class or to the colorizer.

Colorizers have one user settable attribute: enable. By default enable is True. If you set it to False the colorizer no longer renders the text in color:

>> warning = Color('yellow')
>> warning('This will be yellow on the console.')
This will be yellow on the console.

>> warning.enable = False
>> warning('This will not be yellow.')
This will not be yellow.

Alternatively, you can enable or disable the colorizer when creating it. This example uses the Color.isTTY() method to determine whether the output stream, the standard output by default, is a console.

>> warning = Color('yellow', enable=Color.isTTY())
>> warning('Cannot find precursor, ignoring.')
Cannot find precursor, ignoring.

columns¶

inform.columns(array, pagewidth=79, alignment='<', leader=' ')[source]

columns() distributes the values of an array over enough columns to fill the screen.

This example prints out the phonetic alphabet:

>>> from inform import columns

>>> 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(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

conjoin¶

inform.conjoin(iterable, conj=' and ', sep=', ', fmt=None)[source]

conjoin() is like ‘’.join(), but allows you to specify a conjunction that is placed between the last two elements. For example:

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

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

If you prefer the use of the Oxford comma, you can add it as follow:

>>> conjoin(['a', 'b', 'c'], conj=', and ')
'a, b, and c'

You can specify a format string that is applied to every item in the list before they are joined:

>>> conjoin([10.1, 32.5, 16.9], fmt='${:0.2f}')
'$10.10, $32.50 and $16.90'

cull¶

inform.cull(collection[, remove])[source]

cull() strips items from a collection that have a particular value. The collection may be list-like (list, tuple, set, etc.) or a dictionary-like (dict, OrderedDict). A new collection of the same type is returned with the undesirable values removed.

By default, cull() strips values that would be False when cast to a Boolean (0, False, None, ‘’, (), [], etc.). A particular value may be specified using the remove as a keyword argument. The value of remove may be a collection, in which case any value in the collection is removed, or it may be a function, in which case it takes a single item as an argument and returns True if that item should be removed from the list.

>>> from inform import cull, display
>>> display(*cull(['a', 'b', '', 'd']), sep=', ')
a, b, d

>>> accounts = dict(checking=1100.16, savings=13948.78, brokerage=0)
>>> for name, amount in sorted(cull(accounts).items()):
...     display(name, amount, template='{:>10s}: ${:,.2f}')
  checking: $1,100.16
   savings: $13,948.78

dedent¶

inform.dedent(text, strip_nl=None, *, bolm=None, wrap=False)[source]

Without its named arguments, dedent behaves just like, and is as equivalent replacement for, textwrap.dedent.

Args:

strip_nl = None:: strip_nl is used to strip off a single leading or trailing newline. strip_nl may be None, ‘s’, ‘e’, or ‘b’ representing neither, start, end, or both. True may also be passed, which is equivalent to ‘b’.
bolm = None:: The beginning of line mark (bolm) is replaced by a space after the indent is removed. It must be the first non-space character after the initial newline. Normally bolm is a single character, often ‘|’, but it may be contain multiple characters, all of which are replaced by spaces.
wrap (bool or int):: If true the string is wrapped using a width of 70. If an integer value is passed, is used as the width of the wrap.

Examples:

>>> from inform import dedent

>>> print(dedent('''
...     ◊   Diaspar
...         Lys
... ''', bolm='◊'))
<BLANKLINE>
    Diaspar
    Lys
<BLANKLINE>

>>> print(dedent('''
...     |   Diaspar
...     |   Lys
... ''', bolm='|', strip_nl='e'))
<BLANKLINE>
    Diaspar
|   Lys

>>> print(dedent('''
...     ||  Diaspar
...         Lys
... ''', bolm='||', strip_nl='s'))
    Diaspar
    Lys
<BLANKLINE>

>>> print(dedent('''
...         Diaspar
...         Lys
... ''', strip_nl='b'))
Diaspar
Lys

>>> print(dedent('''
...         Diaspar
...         Lys
... ''', strip_nl='b', wrap=True))
Diaspar Lys

did_you_mean¶

inform.did_you_mean(candidate, choices)[source]

Given a candidate string from the user, return the closest valid choice.

Args:

candidate (string):: The string given by the user.
choices (iterable):: The set of valid strings that the user was expected to choose from.

Examples:

>>> from inform import did_you_mean
>>> did_you_mean('cat', ['cat', 'dog'])
'cat'
>>> did_you_mean('car', ['cat', 'dog'])
'cat'
>>> did_you_mean('car', {'cat': 1, 'dog': 2})
'cat'

fmt¶

inform.fmt(msg, *args, **kwargs)[source]

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

>>> from inform import conjoin, display, fmt

>>> filenames = ['a', 'b', 'c', 'd']
>>> filetype = 'CSV'
>>> display(
...     fmt(
...         'Reading {filetype} files: {names}.',
...         names=conjoin(filenames),
...     )
... )
Reading CSV files: a, b, c and d.

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.

format_range¶

inform.format_range(items)[source]

func:format_range can be used to create a succinct, readable string representing a set of numbers.

>>> from inform import format_range
>>> format_range({1, 2, 3, 5})
'1-3,5'

full_stop¶

inform.full_stop(string)[source]

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). It applies str() to its argument, so it is generally a suitable replacement for str in str(exception) when trying extract an error message from an exception.

This is generally useful if you need to print a string that should have punctuation, but may not.

>>> from inform import Error, error, full_stop

>>> found = 0
>>> try:
...     if found is False:
...         raise Error('not found', culprit='marbles')
...     elif found < 3:
...         raise Error('insufficient number.', culprit='marbles')
...     raise Error('not found', culprit='marbles')
... except Error as e:
...     error(full_stop(e))
myprog error: marbles: insufficient number.

indent¶

inform.indent(text, leader=' ', first=0, stops=1, sep='\n')[source]

indent() indents text. Multiples of leader are added to the beginning of the lines to indent. first is the number of indentations used for the first line relative to the others (may be negative but (first + stops) should not be. stops is the default number of indentations to use. sep is the string used to separate the lines.

>>> from inform import display, indent
>>> text = 'a b'.replace(' ', '\n')
>>> display(indent(text))
    a
    b

>>> display(indent(text, first=1, stops=0))
    a
b

>>> display(indent(text, leader='.   ', first=-1, stops=2))
.   a
.   .   b

Info Class¶

The Info class is intended to be used as a helper class. When instantiated, it converts provided keyword arguments to attributes. Unknown attributes evaluate to None. Info can be used directly, or it can be used as a base class.

>>> from inform import display, Info
>>> class Orwell(Info):
...     pass

>>> george = Orwell(peace='war', truth='lies')
>>> display(str(george))
Orwell(peace='war', truth='lies')

>>> display(george.peace)
war

>>> display(george.happiness)
None

is_collection¶

inform.is_collection(obj)[source]

is_collection() returns True if its argument is a collection. This includes objects such as lists, tuples, sets, dictionaries, etc. It does not include strings.

>>> from inform import is_collection

>>> is_collection('')  # string
False

>>> is_collection([])  # list
True

>>> is_collection(())  # tuple
True

>>> is_collection({})  # dictionary
True

is_iterable¶

inform.is_iterable(obj)[source]

is_iterable() returns True if its argument is a collection or a string.

>>> from inform import is_iterable

>>> is_iterable('abc')
True

>>> is_iterable(['a', 'b', 'c'])
True

is_mapping¶

inform.is_mapping(obj)[source]

is_collection() returns True if its argument is a mapping. This includes dictionary and other dictionary-like objects.

>>> from inform import is_mapping

>>> is_mapping('')  # string
False

>>> is_mapping([])  # list
False

>>> is_mapping(())  # tuple
False

>>> is_mapping({})  # dictionary
True

is_str¶

inform.is_str(obj)[source]

is_str() returns True if its argument is a string-like object.

>>> from inform import is_str

>>> is_str('abc')
True

>>> is_str(['a', 'b', 'c'])
False

join¶

inform.join(*args, **kwargs)[source]

join() combines the arguments in a manner very similar to an informant and returns the result as a string. Uses the sep, template and wrap keyword arguments to combine the arguments.

>>> from inform import display, join

>>> accounts = dict(checking=1100.16, savings=13948.78, brokerage=0)
>>> lines = []
>>> for name in sorted(accounts):
...     lines.append(join(name, accounts[name], template='{:>10s}: ${:,.2f}'))

>>> display(*lines, sep='\n')
 brokerage: $0.00
  checking: $1,100.16
   savings: $13,948.78

os_error¶

inform.os_error(exception)[source]

os_error() generates clean messages for operating system errors.

>>> from inform import error, os_error

>>> try:
...     with open('temperatures.csv') as f:
...         contents = f.read()
... except OSError as e:
...     error(os_error(e))
myprog error: temperatures.csv: no such file or directory.

parse_range¶

inform.parse_range(items)[source]

func:parse_range can be used to parse sets of numbers from user-inputted strings.

>>> from inform import parse_range
>>> parse_range('1-3,5')
{1, 2, 3, 5}

ProgressBar Class¶

The ProgressBar class is used to draw a progress bar as a single text line. The line counts down as progress is made and reaches 0 as the task completes. Interruptions are handled with grace.

There are three typical ways to use the progress bar. The first is used to illustrate the progress of an iterator. The iterator must have a length. For example:

>>> from inform import ProgressBar

>>> processed = []
>>> def process(item):
...     # this function would implement some expensive operation
...     processed.append(item)
>>> items = ['i1', 'i2', 'i3', 'i4', 'i5', 'i6', 'i7', 'i8', 'i9', 'i10']

>>> for item in ProgressBar(items, prefix='Progress: ', width=60):
...     process(item)
Progress: ⋅⋅⋅⋅⋅9⋅⋅⋅⋅⋅8⋅⋅⋅⋅⋅7⋅⋅⋅⋅⋅6⋅⋅⋅⋅⋅5⋅⋅⋅⋅⋅4⋅⋅⋅⋅⋅3⋅⋅⋅⋅⋅2⋅⋅⋅⋅⋅1⋅⋅⋅⋅⋅0

>>> display('Processed:', conjoin(processed), end='.\n')
Processed: i1, i2, i3, i4, i5, i6, i7, i8, i9 and i10.

The second is similar to the first, except you just give an integer to indicate how many iterations you wish:

>>> for i in ProgressBar(50, prefix='Progress: '):
...     process(i)
Progress: ⋅⋅⋅⋅⋅⋅9⋅⋅⋅⋅⋅⋅8⋅⋅⋅⋅⋅⋅7⋅⋅⋅⋅⋅⋅6⋅⋅⋅⋅⋅⋅5⋅⋅⋅⋅⋅⋅4⋅⋅⋅⋅⋅⋅3⋅⋅⋅⋅⋅⋅2⋅⋅⋅⋅⋅⋅1⋅⋅⋅⋅⋅⋅0

Finally, the third illustrates progress through a continuous range:

>>> stop = 1e-6
>>> step = 1e-9

>>> with ProgressBar(stop) as progress:
...     display('Progress:')
...     value = 0
...     while value <= stop:
...         progress.draw(value)
...         value += step
Progress:
⋅⋅⋅⋅⋅⋅9⋅⋅⋅⋅⋅⋅8⋅⋅⋅⋅⋅⋅7⋅⋅⋅⋅⋅⋅6⋅⋅⋅⋅⋅⋅5⋅⋅⋅⋅⋅⋅4⋅⋅⋅⋅⋅⋅3⋅⋅⋅⋅⋅⋅2⋅⋅⋅⋅⋅⋅1⋅⋅⋅⋅⋅⋅0

In this case, you need to notify the progress bar if you decide to exit the loop before its complete unless an exception is raised that causes the with block to exit:

>>> with ProgressBar(stop) as progress:
...     display('Progress:')
...     value = 0
...     while value <= stop:
...         progress.draw(value)
...         value += step
...         if value > stop/2:
...             progress.escape()
...             break
Progress:
⋅⋅⋅⋅⋅⋅9⋅⋅⋅⋅⋅⋅8⋅⋅⋅⋅⋅⋅7⋅⋅⋅⋅⋅⋅6⋅⋅⋅⋅⋅⋅

Without calling escape, the bar would have been terminated with a 0 upon exiting the with block. Using escape() is not necessary if the with block is exited via an exception:

>>> try:
...     with ProgressBar(stop) as progress:
...         display('Progress:')
...         value = 0
...         while value <= stop:
...             progress.draw(value)
...             value += step
...             if value > stop/2:
...                 raise Error('early exit.')
... except Error as e:
...     e.report()
Progress:
⋅⋅⋅⋅⋅⋅9⋅⋅⋅⋅⋅⋅8⋅⋅⋅⋅⋅⋅7⋅⋅⋅⋅⋅⋅6⋅⋅⋅⋅⋅⋅
myprog error: early exit.

It is possible to pass a second argument to ProgressBar.draw() that indicates the desired marker to use when updating the bar. This is usually used to signal that there was a problem with the update. To do so, you define the desired markers when instantiating ProgressBar. Each marker consists of a fill character and a color. The color can be specified by giving its name, with a Color object, or with None. For example, the following example uses markers to distinguish four types of results: okay, warn, fail, error.

>>> results = 'okay okay okay fail okay fail okay error warn okay'.split()

>>> def process(index):
...     # this function would implement some expensive operation
...     return results[index]

>>> markers = dict(
...     okay=('⋅', None),
...     warn=('−', None),
...     fail=('+', None),
...     error=('×', None)
... )

>>> with ProgressBar(len(results), prefix="progress: ", markers=markers) as progress:
...     for i in range(len(results)):
...         status = results[i]
...         progress.draw(i+1, status)
progress: ⋅⋅⋅⋅⋅⋅9⋅⋅⋅⋅⋅⋅8⋅⋅⋅⋅⋅⋅7++++++6⋅⋅⋅⋅⋅⋅5++++++4⋅⋅⋅⋅⋅⋅3××××××2−−−−−−1⋅⋅⋅⋅⋅⋅0

In this case color was not used, but you could specify the following to render the markers in color:

>>> markers = dict(
...     okay=('⋅', 'green'),
...     warn=('–', 'yellow'),
...     fail=('+', 'magenta'),
...     error=('×', 'red')
... )

You can also use the Color class:

>>> markers = dict(
...     okay=('⋅', Color('green', Color.isTTY())),
...     warn=('–', Color('yellow', Color.isTTY())),
...     fail=('+', Color('magenta', Color.isTTY())),
...     error=('×', Color('red', Color.isTTY()))
... )

The progress bar generally handles interruptions with grace. For example:

>>> for item in ProgressBar(items, prefix='Progress: ', width=60):
...     if item == 'i4':
...         warn('bad value.', culprit=item)
Progress: ⋅⋅⋅⋅⋅9⋅⋅⋅⋅⋅8⋅⋅⋅⋅⋅7
myprog warning: i4: bad value.
Progress: ⋅⋅⋅⋅⋅9⋅⋅⋅⋅⋅8⋅⋅⋅⋅⋅7⋅⋅⋅⋅⋅6⋅⋅⋅⋅⋅5⋅⋅⋅⋅⋅4⋅⋅⋅⋅⋅3⋅⋅⋅⋅⋅2⋅⋅⋅⋅⋅1⋅⋅⋅⋅⋅0

Notice that the warning started on a new line and the progress bar was restarted from the beginning after the warning.

Generally the progress bar is not printed if no tasks were performed. In some cases you would like to associate a progress bar with an iterator, and then decide later whether there are any tasks that require processing. That could be handled as follows:

>>> with ProgressBar(items, prefix='Progress: ') as progress:
...     for i, item in enumerate(items):
...         if item.startswith('i'):
...             continue
...         progress.draw(i)
...         process(item)

In this example, every item starts with ‘i’ and so is skipped. The result is that no items are processed and so the progress bar is not printed.

plural¶

class inform.plural(count, num='#')[source]

Used with python format strings to conditionally format a phrase depending on whether it refers to a singular or plural number of things.

The format specification has three sections, separated by ‘/’. The first section is always included, the last section is included if the given number is plural, and the middle section, which can be omitted, is included if the given number is singular. If there is only one section, it is used as is for the singular case and an ‘s’ is added to it for the plural case. If any of the sections contain a ‘#’, it is replaced by the number of things.

You may provide either a number (e.g. 0, 1, 2, …) or any object that implements __len__() (e.g. list, dict, set, …). In the latter case, the length of the object will be used to decide whether to use the singular of plural form. Only 1 is considered to be singular; every other number is considered plural.

If the format string starts with ‘!’ then it is removed and the sense of plurality is reversed (the plural form is used for one thing, and the singular form is used otherwise). This is useful when pluralizing verbs.

Here is a typical usage:

>>> from inform import plural, conjoin

>>> astronauts = ['John Glenn']
>>> f"The {plural(astronauts):astronaut/s}: {conjoin(astronauts)}"
'The astronaut: John Glenn'

>>> astronauts = ['Neil Armstrong', 'Buzz Aldrin', 'Michael Collins']
>>> f"The {plural(astronauts):astronaut/s}: {conjoin(astronauts)}"
'The astronauts: Neil Armstrong, Buzz Aldrin and Michael Collins'

The count can be inserted into the output by placing # into the format specification.

If using ‘#’ or ‘!’ is inconvenient, you can change them by specifying the num or invert to plural().

Examples:

>>> f"{plural(1):# thing}"
'1 thing'
>>> f"{plural(2):# thing}"
'2 things'

>>> f"{plural(1):# thing/s}"
'1 thing'
>>> f"{plural(2):# thing/s}"
'2 things'

>>> f"{plural(1):/a cactus/# cacti}"
'a cactus'
>>> f"{plural(2):/a cactus/# cacti}"
'2 cacti'

>>> f"{plural(1):# /is/are}"
'1 is'
>>> f"{plural(2):# /is/are}"
'2 are'

>>> f"{plural([]):# thing/s}"
'0 things'
>>> f"{plural([0]):# thing/s}"
'1 thing'

>>> f"{plural(1):!agree}"
'agrees'
>>> f"{plural(2):!agree}"
'agree'

Finally, you can use the format method to directly produce a descriptive string:

>>> plural(2).format("/a cactus/# cacti")
'2 cacti'

The original implementation is from Veedrac.

render¶

inform.render(obj, sort=None, level=0, tab=' ')[source]

render() recursively converts 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(). The dictionary keys and set values are sorted if sort is True. Sometimes this is not possible because the values are not comparable, in which case render reverts to the natural order.

This example prints several Python data types:

>>> 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',
}

>>> E={'s': s1, 'n': n, 'S': S, 'L': L, 'd':d, 'D':D}
>>> display('E', '=', render(E, True))
E = {
    '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',
    },
    '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',
}

In addition, you can add support for render to your classes by adding one or both of these methods:

_inform_get_args(): returns a list of argument values.

_inform_get_kwargs(): returns a dictionary of keyword arguments.

>>> class Chimera:
...     def __init__(self, *args, **kwargs):
...         self.args = args
...         self.kwargs = kwargs
...
...     def _inform_get_args(self):
...         return self.args
...
...     def _inform_get_kwargs(self):
...         return self.kwargs

>>> lycia = Chimera('Lycia', front='lion', middle='goat', tail='snake')
>>> display(render(lycia))
Chimera(
    'Lycia',
    front='lion',
    middle='goat',
    tail='snake',
)

render_bar¶

inform.render_bar(normalized_value, width=72)[source]

render_bar() produces a graphic representation of a normalized value in the form of a bar. normalized_value is the value to render; it is expected to be a value between 0 and 1. width specifies the maximum width of the line in characters.

>>> from inform import render_bar, display
>>> for i in range(10):
...     value = 1 - i/9.02
...     display('{:0.3f}: {}'.format(value, render_bar(value, 70)))
000: ██████████████████████████████████████████████████████████████████████
889: ██████████████████████████████████████████████████████████████▏
778: ██████████████████████████████████████████████████████▍
667: ██████████████████████████████████████████████▋
557: ██████████████████████████████████████▉
446: ███████████████████████████████▏
335: ███████████████████████▍
224: ███████████████▋
113: ███████▉
002: ▏

title_case¶

inform.title_case(string, exceptions=(...))[source]

title_case() converts the initial letters in the words of a string to upper case while maintaining any letters that are already upper case, such as acronyms. Common ‘small’ words are excepted and words within quotes are handled properly.

>>> from inform import title_case
>>> headline = 'CDC warns about "aggressive" rats as coronavirus shuts down restaurants'
>>> display(title_case(headline))
CDC Warns About "Aggressive" Rats as Coronavirus Shuts Down Restaurants

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.

aaa¶

inform.aaa(arg)[source]

aaa() prints and then returns its argument. The argument may be name or unnamed. If named, the name is used as a label when printing the value of the argument. It can be used to print the value of a term within an expression without being forced to replicate that term.

In the following example, a critical statement is instrumented to show the intermediate values in the computation. In this case it would be difficult to see these intermediate values by replicating code, as calls to the update method has the side effect of updating the state of the integrator.

>>> from inform import aaa, display
>>> class Integrator:
...    def __init__(self, ic=0):
...        self.state = ic
...    def update(self, vin):
...        self.state += vin
...        return self.state

>>> int1 = Integrator(1)
>>> int2 = Integrator()
>>> vin = 1
>>> vout = 0
>>> for t in range(1, 3):
...    vout = 0.7*aaa(int2=int2.update(aaa(int1=int1.update(vin-vout))))
...    display('vout = {}'.format(vout))
myprog DEBUG: <doctest user.rst[...]>, 2, __main__: int1: 2
myprog DEBUG: <doctest user.rst[...]>, 2, __main__: int2: 2
vout = 1.4
myprog DEBUG: <doctest user.rst[...]>, 2, __main__: int1: 1.6
myprog DEBUG: <doctest user.rst[...]>, 2, __main__: int2: 3.6
vout = 2.52

ddd¶

inform.ddd(*args, **kwargs)[source]

ddd() pretty prints all of both its unnamed and named arguments.

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

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

>>> from inform import ddd
>>> ddd(a=a, b=b, c=c, d=d, s='hey now!')
myprog DEBUG: <doctest user.rst[...]>, 1, __main__:
    a = 1
    b = 'this is a test'
    c = (2, 3)
    d = {
        'a': 1,
        'b': 'this is a test',
        'c': (2, 3),
    }
    s = 'hey now!'

If an arguments has a __dict__ attribute, it is printed rather than the argument itself.

>>> from inform import ddd

>>> class Info:
...     def __init__(self, **kwargs):
...         self.__dict__.update(kwargs)
...         ddd(self=self)

>>> contact = Info(email='ted@ledbelly.com', name='Ted Ledbelly')
myprog DEBUG: <doctest user.rst[...]>, 4, __main__.Info.__init__():
    self = Info object containing {
        'email': 'ted@ledbelly.com',
        'name': 'Ted Ledbelly',
    }

ppp¶

inform.ppp(*args, **kwargs)[source]

ppp() is very similar to the normal Python print function in that it prints out the values of the unnamed arguments under the control of the named arguments. It also takes the same named arguments as print(), such as sep and end.

If given without unnamed arguments, it will just print the header, which good way of confirming that a line of code has been reached.

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

sss¶

inform.sss()[source]

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

>> from inform import sss

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

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

vvv¶

inform.vvv(*args)[source]

vvv() 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.

>>> from inform import vvv

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

This last feature is not completely robust. The checking is done by value, so if several variables share the value of one requested, they are all shown.

>>> from inform import vvv

>>> aa = 1
>>> vvv(a)
myprog DEBUG: <doctest user.rst[...]>, 1, __main__:
    a = 1
    aa = 1
    vin = 1

Site Customization¶

Many people choose to add the importing of the debugging function to their usercustomize.py file. In this way, the debugging functions are always available without the need to explicitly import them. To accomplish this, create a usercustomize.py files that contains the following and place it in your site-packages directory:

# Include Inform debugging routines
try:                 # python3
    import builtins
except ImportError:  # python2
    import __builtin__ as builtins

try:
    from inform import aaa, ddd, ppp, sss, vvv
    builtins.aaa = aaa
    builtins.ddd = ddd
    builtins.ppp = ppp
    builtins.sss = sss
    builtins.vvv = vvv
except ImportError:
    pass

The path of this file is typically ~/.local/lib/pythonN.M/site-packages/usercustomize.py where M.N is the version number of your python.

Inform Helper Functions¶

An informer (an Inform object) provides a number of useful methods. However, it is common that the informer is not locally available. To avoid the clutter that would be created by passing the informer around to where ever it is needed, Inform gives you several alternate ways of accessing these methods. Firstly is get_informer(), which simply returns the currently active informer. Secondly, Inform provides a collection of functions that provide direct access to the corresponding methods on the currently active informer. They are:

done¶

inform.done(exit=True)[source]

done() terminates the program with the normal exit status. It calls Inform.done() for the active informer.

If the exit argument is False, preparations are made for exiting, but sys.exit is not called. Instead, the desired exit status is returned.

terminate¶

inform.terminate(status=None, exit=True)[source]

terminate() terminates the program with specified exit status or message. It calls Inform.terminate() for the active informer.

status may be an integer, boolean, string, or None. An exit status of 1 is used if True or a string is passed in. If None is passed in then 1 is used for the exit status if an error was reported and 0 otherwise.

If the exit argument is False, preparations are made for exiting, but sys.exit is not called. Instead, the desired exit status is returned.

terminate_if_errors¶

inform.terminate_if_errors(status=None, exit=True)[source]

terminate_if_errors() terminates the program with specified exit status or message if an error was previously reported. It calls Inform.terminate_if_errors() for the active informer.

status may be an integer, boolean, or string. An exit status of 1 is used if True or a string is passed in.

If the exit argument is False, preparations are made for exiting, but sys.exit is not called. Instead, the desired exit status is returned.

errors_accrued¶

inform.errors_accrued(reset=False)[source]

errors_accrued() returns the number of errors that have been reported. It calls Inform.errors_accrued() for the active informer.

If the reset argument is True, the error count is reset to 0.

get_prog_name¶

inform.get_prog_name()[source]

get_prog_name() returns the name of the program. It calls Inform.get_prog_name() for the active informer.

get_informer¶

inform.get_informer()[source]

get_informer() returns the currently active informer.

set_culprit¶

inform.set_culprit(culprit)[source]

set_culprit() saves a culprit in the informer for later use. Any existing saved culprit is temporarily moved out of the way. It calls Inform.set_culprit() for the active informer.

A culprit is a string, number, or tuple of strings or numbers that would be prepended to a message to indicate the object of the message.

Inform.set_culprit() is used with Python’s with statement. The original saved culprit is restored when the with statement exits.

See Culprits for an example of set_culprit() use.

add_culprit¶

inform.add_culprit(culprit)[source]

add_culprit() appends a culprit to any existing saved culprit. It calls Inform.add_culprit() for the active informer.

A culprit is a string, number, or tuple of strings or numbers that would be prepended to a message to indicate the object of the message.

Inform.add_culprit() is used with Python’s with statement. The original saved culprit is restored when the with statement exits.

See Culprits for an example of add_culprit() use.

get_culprit¶

inform.get_culprit(culprit=None)[source]

get_culprit() returns the specified culprit, if any, appended to the end of the current culprit that is saved in the informer. The resulting culprit is always returned as a tuple. It calls Inform.get_culprit() for the active informer.

A culprit is a string, number, or tuple of strings or numbers that would be prepended to a message to indicate the object of the message.

See Culprits for an example of get_culprit() use.