# Authors: # Jason Gerard DeRose # # Copyright (C) 2008 Red Hat # see file 'COPYING' for use and warranty information # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . """ Parameter system for command plugins. A `Param` instance can be used to describe an argument or option that a command takes, or an attribute that a command returns. The `Param` base class is not used directly, but there are many subclasses for specific Python data types (like `Str` or `Int`) and specific properties (like `Password`). To create a `Param` instance, you must always provide the parameter *name*, which should be the LDAP attribute name if the parameter describes the attribute of an LDAP entry. For example, we could create an `Str` instance describing the user's last-name attribute like this: >>> from ipalib import Str >>> sn = Str('sn') >>> sn.name 'sn' When creating a `Param`, there are also a number of optional kwargs which which can provide additional meta-data and functionality. For example, every parameter has a *cli_name*, the name used on the command-line-interface. By default the *cli_name* is the same as the *name*: >>> sn.cli_name 'sn' But often the LDAP attribute name isn't user friendly for the command-line, so you can override this with the *cli_name* kwarg: >>> sn = Str('sn', cli_name='last') >>> sn.name 'sn' >>> sn.cli_name 'last' Note that the RPC interfaces (and the internal processing pipeline) always use the parameter *name*, regardless of what the *cli_name* might be. A `Param` also has two translatable kwargs: *label* and *doc*. These must both be `Gettext` instances. They both default to a place-holder `FixMe` instance, a subclass of `Gettext` used to mark a missing translatable string: >>> sn.label FixMe('sn') >>> sn.doc FixMe('sn') The *label* is a short phrase describing the parameter. It's used on the CLI when interactively prompting for values, and as a label for form inputs in the web-UI. The *label* should start with an initial capital. For example: >>> from ipalib import _ >>> sn = Str('sn', ... cli_name='last', ... label=_('Last name'), ... ) >>> sn.label Gettext('Last name', domain='ipa', localedir=None) The *doc* is a longer description of the parameter. It's used on the CLI when displaying the help information for a command, and as extra instruction for a form input on the web-UI. By default the *doc* is the same as the *label*: >>> sn.doc Gettext('Last name', domain='ipa', localedir=None) But you can override this with the *doc* kwarg. Like the *label*, the *doc* should also start with an initial capital and should not end with any punctuation. For example: >>> sn = Str('sn', ... cli_name='last', ... label=_('Last name'), ... doc=_("The user's last name"), ... ) >>> sn.doc Gettext("The user's last name", domain='ipa', localedir=None) Demonstration aside, you should always provide at least the *label* so the various UIs are translatable. Only provide the *doc* if the parameter needs a more detailed description for clarity. """ import re import decimal import base64 import csv from xmlrpclib import MAXINT, MININT from types import NoneType from text import _ as ugettext from plugable import ReadOnly, lock, check_name from errors import ConversionError, RequirementError, ValidationError from errors import PasswordMismatch, Base64DecodeError from constants import NULLS, TYPE_ERROR, CALLABLE_ERROR from text import Gettext, FixMe from util import json_serialize from ipapython.dn import DN class DefaultFrom(ReadOnly): """ Derive a default value from other supplied values. For example, say you wanted to create a default for the user's login from the user's first and last names. It could be implemented like this: >>> login = DefaultFrom(lambda first, last: first[0] + last) >>> login(first='John', last='Doe') 'JDoe' If you do not explicitly provide keys when you create a `DefaultFrom` instance, the keys are implicitly derived from your callback by inspecting ``callback.func_code.co_varnames``. The keys are available through the ``DefaultFrom.keys`` instance attribute, like this: >>> login.keys ('first', 'last') The callback is available through the ``DefaultFrom.callback`` instance attribute, like this: >>> login.callback # doctest:+ELLIPSIS at 0x...> >>> login.callback.func_code.co_varnames # The keys ('first', 'last') The keys can be explicitly provided as optional positional arguments after the callback. For example, this is equivalent to the ``login`` instance above: >>> login2 = DefaultFrom(lambda a, b: a[0] + b, 'first', 'last') >>> login2.keys ('first', 'last') >>> login2.callback.func_code.co_varnames # Not the keys ('a', 'b') >>> login2(first='John', last='Doe') 'JDoe' If any keys are missing when calling your `DefaultFrom` instance, your callback is not called and ``None`` is returned. For example: >>> login(first='John', lastname='Doe') is None True >>> login() is None True Any additional keys are simply ignored, like this: >>> login(last='Doe', first='John', middle='Whatever') 'JDoe' As above, because `DefaultFrom.__call__` takes only pure keyword arguments, they can be supplied in any order. Of course, the callback need not be a ``lambda`` expression. This third example is equivalent to both the ``login`` and ``login2`` instances above: >>> def get_login(first, last): ... return first[0] + last ... >>> login3 = DefaultFrom(get_login) >>> login3.keys ('first', 'last') >>> login3.callback.func_code.co_varnames ('first', 'last') >>> login3(first='John', last='Doe') 'JDoe' """ def __init__(self, callback, *keys): """ :param callback: The callable to call when all keys are present. :param keys: Optional keys used for source values. """ if not callable(callback): raise TypeError( CALLABLE_ERROR % ('callback', callback, type(callback)) ) self.callback = callback if len(keys) == 0: fc = callback.func_code if fc.co_flags & 0x0c: raise ValueError("callback: variable-length argument list not allowed") self.keys = fc.co_varnames[:fc.co_argcount] else: self.keys = keys for key in self.keys: if type(key) is not str: raise TypeError( TYPE_ERROR % ('keys', str, key, type(key)) ) lock(self) def __repr__(self): args = (self.callback.__name__,) + tuple(repr(k) for k in self.keys) return '%s(%s)' % ( self.__class__.__name__, ', '.join(args) ) def __call__(self, **kw): """ Call the callback if all keys are present. If all keys are present, the callback is called and its return value is returned. If any keys are missing, ``None`` is returned. :param kw: The keyword arguments. """ vals = tuple(kw.get(k, None) for k in self.keys) if None in vals: return try: return self.callback(*vals) except StandardError: pass def parse_param_spec(spec): """ Parse shorthand ``spec`` into to ``(name, kw)``. The ``spec`` string determines the parameter name, whether the parameter is required, and whether the parameter is multivalue according the following syntax: ====== ===== ======== ========== Spec Name Required Multivalue ====== ===== ======== ========== 'var' 'var' True False 'var?' 'var' False False 'var*' 'var' False True 'var+' 'var' True True ====== ===== ======== ========== For example, >>> parse_param_spec('login') ('login', {'required': True, 'multivalue': False}) >>> parse_param_spec('gecos?') ('gecos', {'required': False, 'multivalue': False}) >>> parse_param_spec('telephone_numbers*') ('telephone_numbers', {'required': False, 'multivalue': True}) >>> parse_param_spec('group+') ('group', {'required': True, 'multivalue': True}) :param spec: A spec string. """ if type(spec) is not str: raise TypeError( TYPE_ERROR % ('spec', str, spec, type(spec)) ) _map = { '?': dict(required=False, multivalue=False), '*': dict(required=False, multivalue=True), '+': dict(required=True, multivalue=True), } end = spec[-1] if end in _map: return (spec[:-1], _map[end]) return (spec, dict(required=True, multivalue=False)) __messages = set() def _(message): __messages.add(message) return message class Param(ReadOnly): """ Base class for all parameters. Param attributes: ================= The behavior of Param class and subclasses can be controlled using the following set of attributes: - cli_name: option name in CLI - cli_short_name: one character version of cli_name - label: very short description of the parameter. This value is used in when the Command output is printed to CLI or in a Command help - doc: parameter long description used in help - required: the parameter is marked as required for given Command - multivalue: indicates if the attribute is multivalued - primary_key: Command's parameter primary key is used for unique identification of an LDAP object and for sorting - normalizer: a custom function for Param value normalization - default_from: a custom function for generating default values of parameter instance - autofill: by default, only `required` parameters get a default value from the default_from function. When autofill is enabled, optional attributes get the default value filled too - query: this attribute is controlled by framework. When the `query` is enabled, framework assumes that the value is only queried and not inserted in the LDAP. Validation is then relaxed - custom parameter validators are skipped and only basic class validators are executed to check the parameter value - attribute: this attribute is controlled by framework and enabled for all LDAP objects parameters (unless parameter has "virtual_attribute" flag). All parameters with enabled `attribute` are being encoded and placed to an entry passed to LDAP Create/Update calls - include: a list of contexts where this parameter should be included. `Param.use_in_context()` provides further information. - exclude: a list of contexts where this parameter should be excluded. `Param.use_in_context()` provides further information. - flags: there are several flags that can be used to further tune the parameter behavior: * no_display (Output parameters only): do not display the parameter * no_create: do not include the parameter for crud.Create based commands * no_update: do not include the parameter for crud.update based commands * no_option: this attribute is not displayed in the CLI, usually because there's a better way of setting it (for example, a separate command) * virtual_attribute: the parameter is not stored physically in the LDAP and thus attribute `attribute` is not enabled * suppress_empty (Output parameters only): do not display parameter value when empty * ask_create: CLI asks for parameter value even when the parameter is not `required`. Applied for all crud.Create based commands * ask_update: CLI asks for parameter value even when the parameter is not `required`. Applied for all crud.Update based commands * req_update: The parameter is `required` in all crud.Update based commands * nonempty: This is an internal flag; a required attribute should be used instead of it. The value of this parameter must not be empty, but it may not be given at all. All crud.Update commands automatically convert required parameters to `nonempty` ones, so the value can be unspecified (unchanged) but cannot be deleted. - hint: this attribute is currently not used - alwaysask: when enabled, CLI asks for parameter value even when the parameter is not `required` - sortorder: used to sort a list of parameters for Command. See `Command.finalize()` for further information - csv: this multivalue attribute is given in CSV format - csv_separator: character that separates values in CSV (comma by default) - csv_skipspace: if true, leading whitespace will be ignored in individual CSV values """ # This is a dummy type so that most of the functionality of Param can be # unit tested directly without always creating a subclass; however, a real # (direct) subclass must *always* override this class attribute: type = NoneType # Ouch, this wont be very useful in the real world! # Subclasses should override this with something more specific: type_error = _('incorrect type') # _convert_scalar operates only on scalar values scalar_error = _('Only one value is allowed') kwargs = ( ('cli_name', str, None), ('cli_short_name', str, None), ('label', (basestring, Gettext), None), ('doc', (basestring, Gettext), None), ('required', bool, True), ('multivalue', bool, False), ('primary_key', bool, False), ('normalizer', callable, None), ('default_from', DefaultFrom, None), ('autofill', bool, False), ('query', bool, False), ('attribute', bool, False), ('include', frozenset, None), ('exclude', frozenset, None), ('flags', frozenset, frozenset()), ('hint', (str, Gettext), None), ('alwaysask', bool, False), ('sortorder', int, 2), # see finalize() ('csv', bool, False), ('csv_separator', str, ','), ('csv_skipspace', bool, True), ('option_group', unicode, None), # The 'default' kwarg gets appended in Param.__init__(): # ('default', self.type, None), ) def __init__(self, name, *rules, **kw): # We keep these values to use in __repr__(): self.param_spec = name self.__kw = dict(kw) if isinstance(self, Password): self.password = True else: self.password = False # Merge in kw from parse_param_spec(): (name, kw_from_spec) = parse_param_spec(name) if not 'required' in kw: kw['required'] = kw_from_spec['required'] if not 'multivalue' in kw: kw['multivalue'] = kw_from_spec['multivalue'] self.name = check_name(name) self.nice = '%s(%r)' % (self.__class__.__name__, self.param_spec) # Add 'default' to self.kwargs and makes sure no unknown kw were given: assert type(self.type) is type if kw.get('multivalue', True): self.kwargs += (('default', tuple, None),) else: self.kwargs += (('default', self.type, None),) if not set(t[0] for t in self.kwargs).issuperset(self.__kw): extra = set(kw) - set(t[0] for t in self.kwargs) raise TypeError( '%s: takes no such kwargs: %s' % (self.nice, ', '.join(repr(k) for k in sorted(extra)) ) ) # Merge in default for 'cli_name', label, doc if not given: if kw.get('cli_name') is None: kw['cli_name'] = self.name if kw.get('label') is None: kw['label'] = FixMe(self.name) if kw.get('doc') is None: kw['doc'] = kw['label'] # Wrap 'default_from' in a DefaultFrom if not already: df = kw.get('default_from', None) if callable(df) and not isinstance(df, DefaultFrom): kw['default_from'] = DefaultFrom(df) # We keep this copy with merged values also to use when cloning: self.__clonekw = kw # Perform type validation on kw, add in class rules: class_rules = [] for (key, kind, default) in self.kwargs: value = kw.get(key, default) if value is not None: if kind is frozenset: if type(value) in (list, tuple): value = frozenset(value) elif type(value) is str: value = frozenset([value]) if ( type(kind) is type and not isinstance(value, kind) or type(kind) is tuple and not isinstance(value, kind) ): raise TypeError( TYPE_ERROR % (key, kind, value, type(value)) ) elif kind is callable and not callable(value): raise TypeError( CALLABLE_ERROR % (key, value, type(value)) ) if hasattr(self, key): raise ValueError('kwarg %r conflicts with attribute on %s' % ( key, self.__class__.__name__) ) setattr(self, key, value) rule_name = '_rule_%s' % key if value is not None and hasattr(self, rule_name): class_rules.append(getattr(self, rule_name)) check_name(self.cli_name) # Check that only 'include' or 'exclude' was provided: if None not in (self.include, self.exclude): raise ValueError( '%s: cannot have both %s=%r and %s=%r' % ( self.nice, 'include', self.include, 'exclude', self.exclude, ) ) # Check that if csv is set, multivalue is set too if self.csv and not self.multivalue: raise ValueError('%s: cannot have csv without multivalue' % self.nice) # Check that all the rules are callable self.class_rules = tuple(class_rules) self.rules = rules if self.query: # by definition a query enforces no class or parameter rules self.all_rules = () else: self.all_rules = self.class_rules + self.rules for rule in self.all_rules: if not callable(rule): raise TypeError( '%s: rules must be callable; got %r' % (self.nice, rule) ) # Check that cli_short_name is only 1 character long: if not (self.cli_short_name is None or len(self.cli_short_name) == 1): raise ValueError( '%s: cli_short_name can only be a single character: %s' % ( self.nice, self.cli_short_name) ) # And we're done. lock(self) def __repr__(self): """ Return an expresion that could construct this `Param` instance. """ return '%s(%s)' % ( self.__class__.__name__, ', '.join(self.__repr_iter()) ) def __repr_iter(self): yield repr(self.param_spec) for rule in self.rules: yield rule.__name__ for key in sorted(self.__kw): value = self.__kw[key] if callable(value) and hasattr(value, '__name__'): value = value.__name__ else: value = repr(value) yield '%s=%s' % (key, value) def __call__(self, value, **kw): """ One stop shopping. """ if value in NULLS: value = self.get_default(**kw) else: value = self.convert(self.normalize(value)) if hasattr(self, 'env'): self.validate(value, self.env.context, supplied=self.name in kw) #pylint: disable=E1101 else: self.validate(value, supplied=self.name in kw) return value def get_param_name(self): """ Return the right name of an attribute depending on usage. Normally errors should use cli_name, our "friendly" name. When using the API directly or *attr return the real name. """ name = self.cli_name if not name: name = self.name return name def kw(self): """ Iterate through ``(key,value)`` for all kwargs passed to constructor. """ for key in sorted(self.__kw): value = self.__kw[key] if callable(value) and hasattr(value, '__name__'): value = value.__name__ yield (key, value) def use_in_context(self, env): """ Return ``True`` if this parameter should be used in ``env.context``. If a parameter is created with niether the ``include`` nor the ``exclude`` kwarg, this method will always return ``True``. For example: >>> from ipalib.config import Env >>> param = Param('my_param') >>> param.use_in_context(Env(context='foo')) True >>> param.use_in_context(Env(context='bar')) True If a parameter is created with an ``include`` kwarg, this method will only return ``True`` if ``env.context`` is in ``include``. For example: >>> param = Param('my_param', include=['foo', 'whatever']) >>> param.include frozenset(['foo', 'whatever']) >>> param.use_in_context(Env(context='foo')) True >>> param.use_in_context(Env(context='bar')) False If a paremeter is created with an ``exclude`` kwarg, this method will only return ``True`` if ``env.context`` is not in ``exclude``. For example: >>> param = Param('my_param', exclude=['foo', 'whatever']) >>> param.exclude frozenset(['foo', 'whatever']) >>> param.use_in_context(Env(context='foo')) False >>> param.use_in_context(Env(context='bar')) True Note that the ``include`` and ``exclude`` kwargs are mutually exclusive and that at most one can be suppelied to `Param.__init__()`. For example: >>> param = Param('nope', include=['foo'], exclude=['bar']) Traceback (most recent call last): ... ValueError: Param('nope'): cannot have both include=frozenset(['foo']) and exclude=frozenset(['bar']) So that subclasses can add additional logic based on other environment variables, the entire `config.Env` instance is passed in rather than just the value of ``env.context``. """ if self.include is not None: return (env.context in self.include) if self.exclude is not None: return (env.context not in self.exclude) return True def safe_value(self, value): """ Return a value safe for logging. This is used so that passwords don't get logged. If this is a `Password` instance and ``value`` is not ``None``, a constant ``u'********'`` is returned. For example: >>> p = Password('my_password') >>> p.safe_value(u'This is my password') u'********' >>> p.safe_value(None) is None True If this is not a `Password` instance, ``value`` is returned unchanged. For example: >>> s = Str('my_str') >>> s.safe_value(u'Some arbitrary value') u'Some arbitrary value' """ if self.password and value is not None: return u'********' return value def clone(self, **overrides): """ Return a new `Param` instance similar to this one. """ return self.clone_rename(self.name, **overrides) def clone_rename(self, name, **overrides): """ Return a new `Param` instance similar to this one, but named differently """ return self.clone_retype(name, self.__class__, **overrides) def clone_retype(self, name, klass, **overrides): """ Return a new `Param` instance similar to this one, but of a different type """ kw = dict(self.__clonekw) kw.update(overrides) return klass(name, *self.rules, **kw) # The following 2 functions were taken from the Python # documentation at http://docs.python.org/library/csv.html def __utf_8_encoder(self, unicode_csv_data): for line in unicode_csv_data: yield line.encode('utf-8') def __unicode_csv_reader(self, unicode_csv_data, dialect=csv.excel, **kwargs): # csv.py doesn't do Unicode; encode temporarily as UTF-8: csv_reader = csv.reader(self.__utf_8_encoder(unicode_csv_data), dialect=dialect, delimiter=self.csv_separator, quotechar='"', skipinitialspace=self.csv_skipspace, **kwargs) for row in csv_reader: # decode UTF-8 back to Unicode, cell by cell: yield [unicode(cell, 'utf-8') for cell in row] def split_csv(self, value): """Split CSV strings into individual values. For CSV params, ``value`` is a tuple of strings. Each of these is split on commas, and the results are concatenated into one tuple. For example:: >>> param = Param('telephones', multivalue=True, csv=True) >>> param.split_csv((u'1, 2', u'3', u'4, 5, 6')) (u'1', u'2', u'3', u'4', u'5', u'6') If ``value`` is not a tuple (or list), it is only split:: >>> param = Param('telephones', multivalue=True, csv=True) >>> param.split_csv(u'1, 2, 3') (u'1', u'2', u'3') For non-CSV params, return the value unchanged. """ if self.csv: if type(value) not in (tuple, list): value = (value,) newval = [] for v in value: if isinstance(v, basestring): lines = unicode(v).splitlines() for row in self.__unicode_csv_reader(lines): newval.extend(row) else: newval.append(v) return tuple(newval) else: return value def normalize(self, value): """ Normalize ``value`` using normalizer callback. For example: >>> param = Param('telephone', ... normalizer=lambda value: value.replace('.', '-') ... ) >>> param.normalize(u'800.123.4567') u'800-123-4567' If this `Param` instance was created with a normalizer callback and ``value`` is a unicode instance, the normalizer callback is called and *its* return value is returned. On the other hand, if this `Param` instance was *not* created with a normalizer callback, if ``value`` is *not* a unicode instance, or if an exception is caught when calling the normalizer callback, ``value`` is returned unchanged. :param value: A proposed value for this parameter. """ if self.multivalue: if type(value) not in (tuple, list): value = (value,) if self.multivalue: return tuple( self._normalize_scalar(v) for v in value ) else: return self._normalize_scalar(value) def _normalize_scalar(self, value): """ Normalize a scalar value. This method is called once for each value in a multivalue. """ if self.normalizer is None: return value try: return self.normalizer(value) except StandardError: return value def convert(self, value): """ Convert ``value`` to the Python type required by this parameter. For example: >>> scalar = Str('my_scalar') >>> scalar.type >>> scalar.convert(43.2) u'43.2' (Note that `Str` is a subclass of `Param`.) All values in `constants.NULLS` will be converted to ``None``. For example: >>> scalar.convert(u'') is None # An empty string True >>> scalar.convert([]) is None # An empty list True Likewise, values in `constants.NULLS` will be filtered out of a multivalue parameter. For example: >>> multi = Str('my_multi', multivalue=True) >>> multi.convert([1.5, '', 17, None, u'Hello']) (u'1.5', u'17', u'Hello') >>> multi.convert([None, u'']) is None # Filters to an empty list True Lastly, multivalue parameters will always return a ``tuple`` (assuming they don't return ``None`` as in the last example above). For example: >>> multi.convert(42) # Called with a scalar value (u'42',) >>> multi.convert([0, 1]) # Called with a list value (u'0', u'1') Note that how values are converted (and from what types they will be converted) completely depends upon how a subclass implements its `Param._convert_scalar()` method. For example, see `Str._convert_scalar()`. :param value: A proposed value for this parameter. """ if value in NULLS: return if self.multivalue: if type(value) not in (tuple, list): value = (value,) values = tuple( self._convert_scalar(v, i) for (i, v) in filter( lambda iv: iv[1] not in NULLS, enumerate(value) ) ) if len(values) == 0: return return values return self._convert_scalar(value) def _convert_scalar(self, value, index=None): """ Convert a single scalar value. """ if type(value) is self.type: return value raise ConversionError(name=self.name, index=index, error=ugettext(self.type_error), ) def validate(self, value, context=None, supplied=None): """ Check validity of ``value``. :param value: A proposed value for this parameter. :param context: The context we are running in. :param supplied: True if this parameter was supplied explicitly. """ if value is None: if self.required or (supplied and 'nonempty' in self.flags): if context == 'cli': raise RequirementError(name=self.cli_name) else: raise RequirementError(name=self.name) return if self.multivalue: if type(value) is not tuple: raise TypeError( TYPE_ERROR % ('value', tuple, value, type(value)) ) if len(value) < 1: raise ValueError('value: empty tuple must be converted to None') for (i, v) in enumerate(value): self._validate_scalar(v, i) else: self._validate_scalar(value) def _validate_scalar(self, value, index=None): if type(value) is not self.type: raise ValidationError(name=self.name, error='need a %r; got %r (a %r)' % ( self.type, value, type(value) ) ) if index is not None and type(index) is not int: raise TypeError( TYPE_ERROR % ('index', int, index, type(index)) ) for rule in self.all_rules: error = rule(ugettext, value) if error is not None: raise ValidationError( name=self.get_param_name(), value=value, index=index, error=error, rule=rule, ) def get_default(self, **kw): """ Return the static default or construct and return a dynamic default. (In these examples, we will use the `Str` and `Bytes` classes, which both subclass from `Param`.) The *default* static default is ``None``. For example: >>> s = Str('my_str') >>> s.default is None True >>> s.get_default() is None True However, you can provide your own static default via the ``default`` keyword argument when you create your `Param` instance. For example: >>> s = Str('my_str', default=u'My Static Default') >>> s.default u'My Static Default' >>> s.get_default() u'My Static Default' If you need to generate a dynamic default from other supplied parameter values, provide a callback via the ``default_from`` keyword argument. This callback will be automatically wrapped in a `DefaultFrom` instance if it isn't one already (see the `DefaultFrom` class for all the gory details). For example: >>> login = Str('login', default=u'my-static-login-default', ... default_from=lambda first, last: (first[0] + last).lower(), ... ) >>> isinstance(login.default_from, DefaultFrom) True >>> login.default_from.keys ('first', 'last') Then when all the keys needed by the `DefaultFrom` instance are present, the dynamic default is constructed and returned. For example: >>> kw = dict(last=u'Doe', first=u'John') >>> login.get_default(**kw) u'jdoe' Or if any keys are missing, your *static* default is returned. For example: >>> kw = dict(first=u'John', department=u'Engineering') >>> login.get_default(**kw) u'my-static-login-default' """ if self.default_from is not None: default = self.default_from(**kw) if default is not None: try: return self.convert(self.normalize(default)) except StandardError: pass return self.default json_exclude_attrs = ( 'alwaysask', 'autofill', 'cli_name', 'cli_short_name', 'csv', 'csv_separator', 'csv_skipspace', 'sortorder', 'falsehoods', 'truths', 'version', ) def __json__(self): json_dict = {} for (a, k, d) in self.kwargs: if a in self.json_exclude_attrs: continue if k in (callable, DefaultFrom): continue elif isinstance(getattr(self, a), frozenset): json_dict[a] = [k for k in getattr(self, a, [])] else: val = getattr(self, a, '') if val is None or val is False: # ignore False and not set because lack of their presence is # the information itself continue; json_dict[a] = json_serialize(val) json_dict['class'] = self.__class__.__name__ json_dict['name'] = self.name json_dict['type'] = self.type.__name__ return json_dict class Bool(Param): """ A parameter for boolean values (stored in the ``bool`` type). """ type = bool type_error = _('must be True or False') # FIXME: This my quick hack to get some UI stuff working, change these defaults # --jderose 2009-08-28 kwargs = Param.kwargs + ( ('truths', frozenset, frozenset([1, u'1', True, u'true', u'TRUE'])), ('falsehoods', frozenset, frozenset([0, u'0', False, u'false', u'FALSE'])), ) def _convert_scalar(self, value, index=None): """ Convert a single scalar value. """ if type(value) is self.type: return value if isinstance(value, basestring): value = value.lower() if value in self.truths: return True if value in self.falsehoods: return False if type(value) in (tuple, list): raise ConversionError(name=self.name, index=index, error=ugettext(self.scalar_error)) raise ConversionError(name=self.name, index=index, error=ugettext(self.type_error), ) class Flag(Bool): """ A boolean parameter that always gets filled in with a default value. This `Bool` subclass forces ``autofill=True`` in `Flag.__init__()`. If no default is provided, it also fills in a default value of ``False``. Lastly, unlike the `Bool` class, the default must be either ``True`` or ``False`` and cannot be ``None``. For example: >>> flag = Flag('my_flag') >>> (flag.autofill, flag.default) (True, False) To have a default value of ``True``, create your `Flag` intance with ``default=True``. For example: >>> flag = Flag('my_flag', default=True) >>> (flag.autofill, flag.default) (True, True) Also note that creating a `Flag` instance with ``autofill=False`` will have no effect. For example: >>> flag = Flag('my_flag', autofill=False) >>> flag.autofill True """ def __init__(self, name, *rules, **kw): kw['autofill'] = True if 'default' not in kw: kw['default'] = False if type(kw['default']) is not bool: default = kw['default'] raise TypeError( TYPE_ERROR % ('default', bool, default, type(default)) ) super(Flag, self).__init__(name, *rules, **kw) class Number(Param): """ Base class for the `Int` and `Decimal` parameters. """ def _convert_scalar(self, value, index=None): """ Convert a single scalar value. """ if type(value) is self.type: return value if type(value) in (unicode, int, long, float): try: return self.type(value) except ValueError: pass if type(value) in (tuple, list): raise ConversionError(name=self.name, index=index, error=ugettext(self.scalar_error)) raise ConversionError(name=self.name, index=index, error=ugettext(self.type_error), ) class Int(Number): """ A parameter for integer values (stored in the ``int`` type). """ type = int type_error = _('must be an integer') kwargs = Param.kwargs + ( ('minvalue', (int, long), int(MININT)), ('maxvalue', (int, long), int(MAXINT)), ) def __init__(self, name, *rules, **kw): #pylint: disable=E1003 super(Number, self).__init__(name, *rules, **kw) if (self.minvalue > self.maxvalue) and (self.minvalue is not None and self.maxvalue is not None): raise ValueError( '%s: minvalue > maxvalue (minvalue=%r, maxvalue=%r)' % ( self.nice, self.minvalue, self.maxvalue) ) def _convert_scalar(self, value, index=None): """ Convert a single scalar value. """ if type(value) in (int, long): return value if type(value) is unicode: # permit floating point strings if value.find(u'.') >= 0: try: return int(float(value)) except ValueError: pass else: try: # 2nd arg is radix base, 2nd arg only accepted for strings. # Zero means determine radix base from prefix (e.g. 0x for hex) return int(value, 0) except ValueError: pass if type(value) is float: try: return int(value) except ValueError: pass raise ConversionError(name=self.get_param_name(), index=index, error=ugettext(self.type_error), ) def _rule_minvalue(self, _, value): """ Check min constraint. """ assert type(value) in (int, long) if value < self.minvalue: return _('must be at least %(minvalue)d') % dict( minvalue=self.minvalue, ) def _rule_maxvalue(self, _, value): """ Check max constraint. """ assert type(value) in (int, long) if value > self.maxvalue: return _('can be at most %(maxvalue)d') % dict( maxvalue=self.maxvalue, ) def _validate_scalar(self, value, index=None): """ This duplicates _validate_scalar in the Param class with the exception that it allows both int and long types. The min/max rules handle size enforcement. """ if type(value) not in (int, long): raise ValidationError(name=self.name, error='need a %r; got %r (a %r)' % ( self.type, value, type(value) ) ) if index is not None and type(index) is not int: raise TypeError( TYPE_ERROR % ('index', int, index, type(index)) ) for rule in self.all_rules: error = rule(ugettext, value) if error is not None: raise ValidationError( name=self.get_param_name(), value=value, index=index, error=error, rule=rule, ) class Decimal(Number): """ A parameter for floating-point values (stored in the ``Decimal`` type). Python Decimal type helps overcome problems tied to plain "float" type, e.g. problem with representation or value comparison. In order to safely transfer the value over RPC libraries, it is being converted to string which is then converted back to Decimal number. """ type = decimal.Decimal type_error = _('must be a decimal number') kwargs = Param.kwargs + ( ('minvalue', decimal.Decimal, None), ('maxvalue', decimal.Decimal, None), # round Decimal to given precision ('precision', int, None), # when False, number is normalized to non-exponential form ('exponential', bool, False), # set of allowed decimal number classes ('numberclass', tuple, ('-Normal', '+Zero', '+Normal')), ) def __init__(self, name, *rules, **kw): for kwparam in ('minvalue', 'maxvalue', 'default'): value = kw.get(kwparam) if value is None: continue if isinstance(value, (basestring, float)): try: value = decimal.Decimal(value) except Exception, e: raise ValueError( '%s: cannot parse kwarg %s: %s' % ( name, kwparam, str(e))) kw[kwparam] = value super(Decimal, self).__init__(name, *rules, **kw) if (self.minvalue > self.maxvalue) \ and (self.minvalue is not None and \ self.maxvalue is not None): raise ValueError( '%s: minvalue > maxvalue (minvalue=%s, maxvalue=%s)' % ( self.nice, self.minvalue, self.maxvalue) ) if self.precision is not None and self.precision < 0: raise ValueError('%s: precision must be at least 0' % self.nice) def _rule_minvalue(self, _, value): """ Check min constraint. """ assert type(value) is decimal.Decimal if value < self.minvalue: return _('must be at least %(minvalue)s') % dict( minvalue=self.minvalue, ) def _rule_maxvalue(self, _, value): """ Check max constraint. """ assert type(value) is decimal.Decimal if value > self.maxvalue: return _('can be at most %(maxvalue)s') % dict( maxvalue=self.maxvalue, ) def _enforce_numberclass(self, value): #pylint: disable=E1101 numberclass = value.number_class() if numberclass not in self.numberclass: raise ValidationError(name=self.get_param_name(), error=_("number class '%(cls)s' is not included in a list " "of allowed number classes: %(allowed)s") \ % dict(cls=numberclass, allowed=u', '.join(self.numberclass)) ) def _enforce_precision(self, value): assert type(value) is decimal.Decimal if self.precision is not None: quantize_exp = decimal.Decimal(10) ** -self.precision try: value = value.quantize(quantize_exp) except decimal.DecimalException, e: raise ConversionError(name=self.get_param_name(), error=unicode(e)) return value def _remove_exponent(self, value): assert type(value) is decimal.Decimal if not self.exponential: #pylint: disable=E1101 try: # adopted from http://docs.python.org/library/decimal.html value = value.quantize(decimal.Decimal(1)) \ if value == value.to_integral() \ else value.normalize() except decimal.DecimalException, e: raise ConversionError(name=self.get_param_name(), error=unicode(e)) return value def _test_and_normalize(self, value): """ This method is run in conversion and normalization methods to test that the Decimal number conforms to Parameter boundaries and then normalizes the value. """ self._enforce_numberclass(value) value = self._remove_exponent(value) value = self._enforce_precision(value) return value def _convert_scalar(self, value, index=None): if isinstance(value, (basestring, float)): try: value = decimal.Decimal(value) except decimal.DecimalException, e: raise ConversionError(name=self.get_param_name(), index=index, error=unicode(e)) if isinstance(value, decimal.Decimal): return self._test_and_normalize(value) return super(Decimal, self)._convert_scalar(value, index) def _normalize_scalar(self, value): if isinstance(value, decimal.Decimal): return self._test_and_normalize(value) return super(Decimal, self)._normalize_scalar(value) class Data(Param): """ Base class for the `Bytes` and `Str` parameters. Previously `Str` was as subclass of `Bytes`. Now the common functionality has been split into this base class so that ``isinstance(foo, Bytes)`` wont be ``True`` when ``foo`` is actually an `Str` instance (which is confusing). """ kwargs = Param.kwargs + ( ('minlength', int, None), ('maxlength', int, None), ('length', int, None), ('pattern', (basestring,), None), ('pattern_errmsg', (basestring,), None), ) re = None re_errmsg = None def __init__(self, name, *rules, **kw): super(Data, self).__init__(name, *rules, **kw) if not ( self.length is None or (self.minlength is None and self.maxlength is None) ): raise ValueError( '%s: cannot mix length with minlength or maxlength' % self.nice ) if self.minlength is not None and self.minlength < 1: raise ValueError( '%s: minlength must be >= 1; got %r' % (self.nice, self.minlength) ) if self.maxlength is not None and self.maxlength < 1: raise ValueError( '%s: maxlength must be >= 1; got %r' % (self.nice, self.maxlength) ) if None not in (self.minlength, self.maxlength): if self.minlength > self.maxlength: raise ValueError( '%s: minlength > maxlength (minlength=%r, maxlength=%r)' % ( self.nice, self.minlength, self.maxlength) ) elif self.minlength == self.maxlength: raise ValueError( '%s: minlength == maxlength; use length=%d instead' % ( self.nice, self.minlength) ) def _rule_pattern(self, _, value): """ Check pattern (regex) contraint. """ assert type(value) is self.type if self.re.match(value) is None: if self.re_errmsg: return self.re_errmsg % dict(pattern=self.pattern,) else: return _('must match pattern "%(pattern)s"') % dict( pattern=self.pattern, ) class Bytes(Data): """ A parameter for binary data (stored in the ``str`` type). This class is named *Bytes* instead of *Str* so it's aligned with the Python v3 ``(str, unicode) => (bytes, str)`` clean-up. See: http://docs.python.org/3.0/whatsnew/3.0.html Also see the `Str` parameter. """ type = str type_error = _('must be binary data') def __init__(self, name, *rules, **kw): if kw.get('pattern', None) is None: self.re = None else: self.re = re.compile(kw['pattern']) self.re_errmsg = kw.get('pattern_errmsg', None) super(Bytes, self).__init__(name, *rules, **kw) def _rule_minlength(self, _, value): """ Check minlength constraint. """ assert type(value) is str if len(value) < self.minlength: return _('must be at least %(minlength)d bytes') % dict( minlength=self.minlength, ) def _rule_maxlength(self, _, value): """ Check maxlength constraint. """ assert type(value) is str if len(value) > self.maxlength: return _('can be at most %(maxlength)d bytes') % dict( maxlength=self.maxlength, ) def _rule_length(self, _, value): """ Check length constraint. """ assert type(value) is str if len(value) != self.length: return _('must be exactly %(length)d bytes') % dict( length=self.length, ) def _convert_scalar(self, value, index=None): if isinstance(value, unicode): try: value = base64.b64decode(value) except TypeError, e: raise Base64DecodeError(reason=str(e)) return super(Bytes, self)._convert_scalar(value, index) class Str(Data): """ A parameter for Unicode text (stored in the ``unicode`` type). This class is named *Str* instead of *Unicode* so it's aligned with the Python v3 ``(str, unicode) => (bytes, str)`` clean-up. See: http://docs.python.org/3.0/whatsnew/3.0.html Also see the `Bytes` parameter. """ kwargs = Data.kwargs + ( ('noextrawhitespace', bool, True), ) type = unicode type_error = _('must be Unicode text') def __init__(self, name, *rules, **kw): if kw.get('pattern', None) is None: self.re = None else: self.re = re.compile(kw['pattern'], re.UNICODE) self.re_errmsg = kw.get('pattern_errmsg', None) super(Str, self).__init__(name, *rules, **kw) def _convert_scalar(self, value, index=None): """ Convert a single scalar value. """ if type(value) is self.type: return value if type(value) in (int, long, float, decimal.Decimal): return self.type(value) if type(value) in (tuple, list): raise ConversionError(name=self.name, index=index, error=ugettext(self.scalar_error)) raise ConversionError(name=self.name, index=index, error=ugettext(self.type_error), ) def _rule_noextrawhitespace(self, _, value): """ Do not allow leading/trailing spaces. """ assert type(value) is unicode if self.noextrawhitespace is False: #pylint: disable=E1101 return if len(value) != len(value.strip()): return _('Leading and trailing spaces are not allowed') def _rule_minlength(self, _, value): """ Check minlength constraint. """ assert type(value) is unicode if len(value) < self.minlength: return _('must be at least %(minlength)d characters') % dict( minlength=self.minlength, ) def _rule_maxlength(self, _, value): """ Check maxlength constraint. """ assert type(value) is unicode if len(value) > self.maxlength: return _('can be at most %(maxlength)d characters') % dict( maxlength=self.maxlength, ) def _rule_length(self, _, value): """ Check length constraint. """ assert type(value) is unicode if len(value) != self.length: return _('must be exactly %(length)d characters') % dict( length=self.length, ) class IA5Str(Str): """ An IA5String per RFC 4517 """ def __init__(self, name, *rules, **kw): super(IA5Str, self).__init__(name, *rules, **kw) def _convert_scalar(self, value, index=None): if isinstance(value, basestring): for i in xrange(len(value)): if ord(value[i]) > 127: raise ConversionError(name=self.get_param_name(), index=index, error=_('The character \'%(char)r\' is not allowed.') % dict(char=value[i],) ) return super(IA5Str, self)._convert_scalar(value, index) class Password(Str): """ A parameter for passwords (stored in the ``unicode`` type). """ kwargs = Str.kwargs + ( ('confirm', bool, True), ) def _convert_scalar(self, value, index=None): if isinstance(value, (tuple, list)) and len(value) == 2: (p1, p2) = value if p1 != p2: raise PasswordMismatch(name=self.name, index=index) value = p1 return super(Password, self)._convert_scalar(value, index) class Enum(Param): """ Base class for parameters with enumerable values. """ kwargs = Param.kwargs + ( ('values', tuple, tuple()), ) def __init__(self, name, *rules, **kw): super(Enum, self).__init__(name, *rules, **kw) for (i, v) in enumerate(self.values): if type(v) is not self.type: n = '%s values[%d]' % (self.nice, i) raise TypeError( TYPE_ERROR % (n, self.type, v, type(v)) ) if len(self.values) < 1: raise ValueError( '%s: list of values must not be empty' % self.nice) def _rule_values(self, _, value, **kw): if value not in self.values: if len(self.values) == 1: return _("must be '%(value)s'") % dict(value=self.values[0]) else: values = u', '.join("'%s'" % value for value in self.values) return _('must be one of %(values)s') % dict(values=values) class BytesEnum(Enum): """ Enumerable for binary data (stored in the ``str`` type). """ type = unicode class StrEnum(Enum): """ Enumerable for Unicode text (stored in the ``unicode`` type). For example: >>> enum = StrEnum('my_enum', values=(u'One', u'Two', u'Three')) >>> enum.validate(u'Two', 'cli') is None True >>> enum.validate(u'Four', 'cli') Traceback (most recent call last): ... ValidationError: invalid 'my_enum': must be one of 'One', 'Two', 'Three' """ type = unicode class Any(Param): """ A parameter capable of holding values of any type. For internal use only. """ type = object def _convert_scalar(self, value, index=None): return value def _validate_scalar(self, value, index=None): for rule in self.all_rules: error = rule(ugettext, value) if error is not None: raise ValidationError( name=self.name, value=value, index=index, error=error, rule=rule, ) class File(Str): """ File parameter type. Accepts file names and loads their content into the parameter value. """ kwargs = Data.kwargs + ( # valid for CLI, other backends (e.g. webUI) can ignore this ('stdin_if_missing', bool, False), ('noextrawhitespace', bool, False), ) class AccessTime(Str): """ Access time parameter type. Accepts values conforming to generalizedTime as defined in RFC 4517 section 3.3.13 without time zone information. """ def _check_HHMM(self, t): if len(t) != 4: raise ValueError('HHMM must be exactly 4 characters long') if not t.isnumeric(): raise ValueError('HHMM non-numeric') hh = int(t[0:2]) if hh < 0 or hh > 23: raise ValueError('HH out of range') mm = int(t[2:4]) if mm < 0 or mm > 59: raise ValueError('MM out of range') def _check_dotw(self, t): if t.isnumeric(): value = int(t) if value < 1 or value > 7: raise ValueError('day of the week out of range') elif t not in ('Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'): raise ValueError('invalid day of the week') def _check_dotm(self, t, month_num=1, year=4): if not t.isnumeric(): raise ValueError('day of the month non-numeric') value = int(t) if month_num in (1, 3, 5, 7, 8, 10, 12): if value < 1 or value > 31: raise ValueError('day of the month out of range') elif month_num in (4, 6, 9, 11): if value < 1 or value > 30: raise ValueError('day of the month out of range') elif month_num == 2: if year % 4 == 0 and (year % 100 != 0 or year % 400 == 0): if value < 1 or value > 29: raise ValueError('day of the month out of range') else: if value < 1 or value > 28: raise ValueError('day of the month out of range') def _check_wotm(self, t): if not t.isnumeric(): raise ValueError('week of the month non-numeric') value = int(t) if value < 1 or value > 6: raise ValueError('week of the month out of range') def _check_woty(self, t): if not t.isnumeric(): raise ValueError('week of the year non-numeric') value = int(t) if value < 1 or value > 52: raise ValueError('week of the year out of range') def _check_doty(self, t): if not t.isnumeric(): raise ValueError('day of the year non-numeric') value = int(t) if value < 1 or value > 365: raise ValueError('day of the year out of range') def _check_month_num(self, t): if not t.isnumeric(): raise ValueError('month number non-numeric') value = int(t) if value < 1 or value > 12: raise ValueError('month number out of range') def _check_interval(self, t, check_func): intervals = t.split(',') for i in intervals: if not i: raise ValueError('invalid time range') values = i.split('-') if len(values) > 2: raise ValueError('invalid time range') for v in values: check_func(v) if len(values) == 2: if int(values[0]) > int(values[1]): raise ValueError('invalid time range') def _check_W_spec(self, ts, index): if ts[index] != 'day': raise ValueError('invalid week specifier') index += 1 self._check_interval(ts[index], self._check_dotw) return index def _check_M_spec(self, ts, index): if ts[index] == 'week': self._check_interval(ts[index + 1], self._check_wotm) index = self._check_W_spec(ts, index + 2) elif ts[index] == 'day': index += 1 self._check_interval(ts[index], self._check_dotm) else: raise ValueError('invalid month specifier') return index def _check_Y_spec(self, ts, index): if ts[index] == 'month': index += 1 self._check_interval(ts[index], self._check_month_num) month_num = int(ts[index]) index = self._check_M_spec(ts, index + 1) elif ts[index] == 'week': self._check_interval(ts[index + 1], self._check_woty) index = self._check_W_spec(ts, index + 2) elif ts[index] == 'day': index += 1 self._check_interval(ts[index], self._check_doty) else: raise ValueError('invalid year specifier') return index def _check_generalized(self, t): assert type(t) is unicode if len(t) not in (10, 12, 14): raise ValueError('incomplete generalized time') if not t.isnumeric(): raise ValueError('time non-numeric') # don't check year value, with time travel and all :) self._check_month_num(t[4:6]) year_num = int(t[0:4]) month_num = int(t[4:6]) self._check_dotm(t[6:8], month_num, year_num) if len(t) >= 12: self._check_HHMM(t[8:12]) else: self._check_HHMM('%s00' % t[8:10]) if len(t) == 14: s = int(t[12:14]) if s < 0 or s > 60: raise ValueError('seconds out of range') def _check(self, time): ts = time.split() if ts[0] == 'absolute': if len(ts) != 4: raise ValueError('invalid format, must be \'absolute generalizedTime ~ generalizedTime\'') self._check_generalized(ts[1]) if ts[2] != '~': raise ValueError('invalid time range separator') self._check_generalized(ts[3]) if int(ts[1]) >= int(ts[3]): raise ValueError('invalid time range') elif ts[0] == 'periodic': index = None if ts[1] == 'yearly': index = self._check_Y_spec(ts, 2) elif ts[1] == 'monthly': index = self._check_M_spec(ts, 2) elif ts[1] == 'weekly': index = self._check_W_spec(ts, 2) elif ts[1] == 'daily': index = 1 if index is None: raise ValueError('period must be yearly, monthy or daily, got \'%s\'' % ts[1]) self._check_interval(ts[index + 1], self._check_HHMM) else: raise ValueError('time neither absolute or periodic') def _rule_required(self, _, value): try: self._check(value) except ValueError, e: raise ValidationError(name=self.get_param_name(), error=e.args[0]) except IndexError: raise ValidationError( name=self.get_param_name(), error=ugettext('incomplete time value') ) return None class DNParam(Param): type = DN def _convert_scalar(self, value, index=None): """ Convert a single scalar value. """ if type(value) is self.type: return value try: dn = DN(value) except Exception, e: raise ConversionError(name=self.get_param_name(), index=index, error=ugettext(e)) return dn def create_param(spec): """ Create an `Str` instance from the shorthand ``spec``. This function allows you to create `Str` parameters (the most common) from a convenient shorthand that defines the parameter name, whether it is required, and whether it is multivalue. (For the definition of the shorthand syntax, see the `parse_param_spec()` function.) If ``spec`` is an ``str`` instance, it will be used to create a new `Str` parameter, which will be returned. For example: >>> s = create_param('hometown?') >>> s Str('hometown?') >>> (s.name, s.required, s.multivalue) ('hometown', False, False) On the other hand, if ``spec`` is already a `Param` instance, it is returned unchanged. For example: >>> b = Bytes('cert') >>> create_param(b) is b True As a plugin author, you will not call this function directly (which would be no more convenient than simply creating the `Str` instance). Instead, `frontend.Command` will call it for you when it evaluates the ``takes_args`` and ``takes_options`` attributes, and `frontend.Object` will call it for you when it evaluates the ``takes_params`` attribute. :param spec: A spec string or a `Param` instance. """ if isinstance(spec, Param): return spec if type(spec) is not str: raise TypeError( TYPE_ERROR % ('spec', (str, Param), spec, type(spec)) ) return Str(spec)