blob: 894c48a20dbd63e3dcf79c495374678f4b125d09 [file] [log] [blame]
# Copyright 2016 The LUCI Authors. All rights reserved.
# Use of this source code is governed under the Apache License, Version 2.0
# that can be found in the LICENSE file.
from __future__ import absolute_import
import bisect
import contextlib
import copy
import hashlib
import json
import keyword
import os
import re
import types
from functools import wraps
import attr
from six import iteritems
from google.protobuf import message
from google.protobuf import json_format as jsonpb
from .config_types import Path
from .internal import engine_step
from .internal.attr_util import attr_dict_type
from .recipe_test_api import DisabledTestData, ModuleTestData
from .third_party import luci_context
from .third_party.logdog import streamname
from .third_party.logdog.bootstrap import ButlerBootstrap, NotBootstrappedError
from .types import StepPresentation, freeze, FrozenDict
from .util import ModuleInjectionSite
# TODO(iannucci): Rationalize the use of this in downstream scripts.
from .util import Placeholder # pylint: disable=unused-import
class UnknownRequirementError(object):
"""Raised by a requirement function when the referenced requirement is
def __init__(self, req):
super(UnknownRequirementError, self).__init__(
'Unknown requirement [%s]' % (req,))
self.typ = req._typ = req._name
class _UnresolvedRequirement(object):
"""Internal placeholder type for an unresolved module/recipe requirement."""
def __init__(self, typ, name):
self._typ = typ
self._name = name
def __str__(self):
return '%s:%s' % (self._typ, self._name)
def __getattr__(self, key):
raise AttributeError(
'Cannot reference [%s] in unresolved requirement [%s]' % (
key, str(self,)))
def __call__(self, *args, **kwargs):
raise AttributeError('Cannot call unresolved requirement [%s]' % (
def RequireClient(name):
"""Returns: A dependency injection placeholder for a recipe engine client.
Recipes and Recipe APIs can call this function to install a placeholder for
the dependency injection of a recipe engine client. This dependency will be
noted by the recipe engine and resolved prior to recipe execution.
Clients are intended to be used to interface between the recipe engine and
low-level modules (e.g., "step"). As a general rule of thumb, higher-level
modules should not use clients and interface with the low-level modules
Recipe engine clients are referenced by name and resolved directly by the
recipe engine. Modules must require them as class member variables in their
recipe API subclass, and recipes must require them as top-level variables.
For example:
class MyCollRecipeApi(recipe_api.RecipeApi):
step_client = recipe_api.RequireClient('step')
def do_something(self):
name (str): the name of the recipe engine client to install.
return _UnresolvedRequirement('client', name)
@attr.s(frozen=True, slots=True)
class LUCIContextClient(object):
"""A recipe engine client which reads/writes the LUCI_CONTEXT."""
IDENT = 'lucictx'
ENV_KEY = luci_context.ENV_KEY
_context = attr.ib(validator=attr_dict_type(str, (dict, FrozenDict)),
factory=dict, converter=freeze)
def context(self):
"""Returns the current content of LUCI_CONTEXT as a Dict[str, Dict]."""
return self._context
def new_context(self, **section_pb_values):
"""Creates a new LUCI_CONTEXT file with the provided section values, all
unmentioned sections in the current context will be copied over. The
environment variable will NOT not be switched to the newly created context.
* section_pb_values (Dict[str, message.Message]) - A mapping of
section_key to the new message value for that section. If the value
is None, the corresponding section will be removed from the context.
Returns the path (str) to the newly created LUCI_CONTEXT file. Returns None
if section_pb_values is empty (i.e. No change to current context).
section_values = {
key: jsonpb.MessageToDict(pb_val) if pb_val is not None else None
for key, pb_val in iteritems(section_pb_values)
with luci_context.stage(_leak=True, **section_values) as file_path:
return file_path
class PathsClient(object):
"""A recipe engine client which exposes all known base paths.
In particular, you can use this client to discover all known:
* recipe resource path
* loaded module resource paths
* loaded recipe repo paths
IDENT = 'paths'
def __init__(self, start_dir):
self.paths = []
self.path_strings = []
self._start_dir = start_dir
def _initialize_with_recipe_api(self, root_api):
"""This method is called once before the start of every recipe.
It is passed the recipe's `api` object. This method crawls the api object
and extracts every resource base path it can find."""
paths_found = {}
def add_found(path):
if path is not None:
paths_found[str(path)] = path
search_set = [root_api]
found_api_id_set = {id(root_api)}
while search_set:
api = search_set.pop()
for name in dir(api.m):
sub_api = getattr(api.m, name)
if not isinstance(sub_api, RecipeApiPlain):
if id(sub_api) not in found_api_id_set:
# transpose
# [(path_string, path), ...]
# into
# ([path_string, ...], [path, ...])
self.path_strings, self.paths = zip(*sorted(paths_found.items()))
def find_longest_prefix(self, target, sep):
"""Identifies a known resource path which would contain the `target` path.
sep must be the current path separator (can vary from os.path.sep when
running under simulation).
Returns (str(Path), Path) if the prefix path is found, or (None, None) if no
such prefix exists.
idx = bisect.bisect_left(self.path_strings, target)
if idx == len(self.paths):
return (None, None) # off the end
sPath, path = self.path_strings[idx], self.paths[idx]
if target == sPath :
return sPath, path
if idx > 0:
sPath, path = self.path_strings[idx-1], self.paths[idx-1]
if target.startswith(sPath+sep):
return sPath, path
return (None, None)
def start_dir(self):
"""Returns the START_DIR for this recipe execution."""
return self._start_dir
class PropertiesClient(object):
"""A recipe engine client representing the recipe engine properties."""
IDENT = 'properties'
def __init__(self, properties):
self._properties = properties
def get_properties(self):
return copy.deepcopy(self._properties)
class StepClient(object):
"""A recipe engine client representing step running and introspection."""
IDENT = 'step'
StepConfig = engine_step.StepConfig
EnvAffix = engine_step.EnvAffix
def __init__(self, engine):
self._engine = engine
def previous_step_result(self):
"""Allows api.step to get the active result from any context.
This always returns the innermost nested step that is still open --
presumably the one that just failed if we are in an exception handler."""
active_step_data = self._engine.active_step
if not active_step_data:
raise ValueError(
'No steps have been run yet, and you are asking for a previous step '
return active_step_data
def parent_step(self, name_tokens):
"""Opens a parent step.
Returns a contextmanager object yielding (StepPresentation, List[StepData]).
Refer to RecipeEngine.parent_step for details.
return self._engine.parent_step(name_tokens)
def run_step(self, step):
Runs a step from a StepConfig.
* step (StepConfig) - The step to run.
A StepData object containing the result of finished the step.
assert isinstance(step, engine_step.StepConfig)
return self._engine.run_step(step)
def close_non_parent_step(self):
"""Closes the currently active non-parent step, if any."""
return self._engine.close_non_parent_step()
@attr.s(frozen=True, slots=True)
class ConcurrencyClient(object):
IDENT = 'concurrency'
supports_concurrency = attr.ib() # type: bool
_spawn_impl = attr.ib() # type: f(func, args, kwargs) -> Greenlet
def spawn(self, func, args, kwargs, greenlet_name):
return self._spawn_impl(func, args, kwargs, greenlet_name)
class StepFailure(Exception):
This is the base class for all step failures.
Raising a StepFailure counts as 'running a step' for the purpose of
infer_composite_step's logic.
FIXME: This class is as a general way to fail, but it should be split up.
See for more information.
FIXME: These exceptions should be made into more-normal exceptions (e.g.
the way reason_message is overridden by subclasses is very strange).
def __init__(self, name_or_reason, result=None):
# Raising a StepFailure counts as running a step.
self.exc_result = None # default to None
if result: = name_or_reason
self.result = result
self.reason = self.reason_message()
# TODO(iannucci): This hasattr stuff is pretty bogus. This is attempting
# to detect when 'result' was a StepData. However AggregatedStepFailure
# passes in something else.
if hasattr(result, 'exc_result'):
self.exc_result = result.exc_result
if self.exc_result.had_timeout:
self.reason += ' (timeout)'
self.reason += ' (retcode: {!r})'.format(self.exc_result.retcode)
else: = None
self.result = None
self.reason = name_or_reason
super(StepFailure, self).__init__(self.reason)
def reason_message(self):
return 'Step({!r})'.format(
def had_timeout(self):
Returns True if this exception was caused by a timeout. If this was a manual
failure, returns None.
if not self.exc_result:
return None
return self.exc_result.had_timeout
def retcode(self):
Returns the retcode of the step which failed. If this was a manual
failure, returns None
if not self.exc_result:
return None
return self.exc_result.retcode
class StepWarning(StepFailure):
A subclass of StepFailure, which still fails the build, but which is
a warning. Need to figure out how exactly this will be useful.
def reason_message(self): # pragma: no cover
return "Warning: Step({!r})".format(
class InfraFailure(StepFailure):
A subclass of StepFailure, which fails the build due to problems with the
def reason_message(self):
return "Infra Failure: Step({!r})".format(
class AggregatedStepFailure(StepFailure):
def __init__(self, result):
super(AggregatedStepFailure, self).__init__(
"Aggregate step failure.", result=result)
def reason_message(self):
msg = "{!r} out of {!r} aggregated steps failed: ".format(
len(self.result.failures), len(self.result.all_results))
msg += ', '.join((f.reason or for f in self.result.failures)
return msg
class AggregatedResult(object):
"""Holds the result of an aggregated run of steps.
Currently this is only used internally by defer_results, but it may be exposed
to the consumer of defer_results at some point in the future. For now it's
expected to be easier for defer_results consumers to do their own result
aggregation, as they may need to pick and chose (or label) which results they
really care about.
def __init__(self):
self.successes = []
self.failures = []
self.contains_infra_failure = False
# Needs to be here to be able to treat this as a step result
self.retcode = None
def all_results(self):
Return a list of two item tuples (x, y), where
x is whether or not the step succeeded, and
y is the result of the run
res = [(True, result) for result in self.successes]
res.extend([(False, result) for result in self.failures])
return res
def add_success(self, result):
return DeferredResult(result, None)
def add_failure(self, exception):
if isinstance(exception, InfraFailure):
self.contains_infra_failure = True
return DeferredResult(None, exception)
class DeferredResult(object):
def __init__(self, result, failure):
self._result = result
self._failure = failure
def is_ok(self):
return self._failure is None
def get_result(self):
if not self.is_ok:
raise self.get_error()
return self._result
def get_error(self):
return self._failure
class _DEFER_CONTEXT_OBJ(object):
"""This object keeps track of state pertaining to the behavior of
defer_results and composite_step.
def __init__(self):
"""The object starts in a state where no steps have been run, and there's no
current aggregated_result."""
self._ran_step = [False]
self._aggregated_result = [None]
def ran_step(self):
"""Returns True if a step has run within this defer_results context."""
return self._ran_step[-1]
def mark_ran_step(self):
"""Marks that a step has run within this defer_results context."""
self._ran_step[-1] = True
def aggregated_result(self):
"""Returns the current AggregatedResult() or None, if we're not currently
deferring results."""
return self._aggregated_result[-1]
def begin_aggregate(self):
"""Begins aggregating new results. Use with a with statement:
with _DEFER_CONTEXT.begin_aggregate() as agg:
Where `agg` is the AggregatedResult() for that with section.
yield self._enter(AggregatedResult())
def begin_normal(self):
"""Returns the context to normal (stop aggregating results).
with _DEFER_CONTEXT.begin_normal():
yield self._enter(None)
def _enter(self, agg):
return agg
def _exit(self):
def non_step(func):
"""A decorator which prevents a method from automatically being wrapped as
a infer_composite_step by RecipeApiMeta.
This is needed for utility methods which don't run any steps, but which are
invoked within the context of a defer_results().
@see infer_composite_step, defer_results, RecipeApiMeta
assert not hasattr(func, "_skip_inference"), \
"Double-wrapped method %r?" % func
func._skip_inference = True # pylint: disable=protected-access
return func
_skip_inference = non_step
def infer_composite_step(func):
"""A decorator which possibly makes this step act as a single step, for the
purposes of the defer_results function.
Behaves as if this function were wrapped by composite_step, unless this
* is already wrapped by non_step
* returns a result without calling api.step
* raises an exception which is not derived from StepFailure
In any of these cases, this function will behave like a normal function.
This decorator is automatically applied by RecipeApiMeta (or by inheriting
from RecipeApi). If you want to decalare a method's behavior explicitly, you
may decorate it with either composite_step or with non_step.
if getattr(func, "_skip_inference", False):
return func
@_skip_inference # to prevent double-wraps
def _inner(*a, **kw):
agg = _DEFER_CONTEXT.aggregated_result
# We're not deferring results, so run the function normally.
if agg is None:
return func(*a, **kw)
# Stop deferring results within this function; the ultimate result of the
# function will be added to our parent context's aggregated results and
# we'll return a DeferredResult.
with _DEFER_CONTEXT.begin_normal():
ret = func(*a, **kw)
# This is how we differ from composite_step; if we didn't actually run
# a step or throw a StepFailure, return normally.
if not _DEFER_CONTEXT.ran_step:
return ret
return agg.add_success(ret)
except StepFailure as ex:
return agg.add_failure(ex)
_inner.__original = func
return _inner
def composite_step(func):
"""A decorator which makes this step act as a single step, for the purposes of
the defer_results function.
This means that this function will not quit during the middle of its execution
because of a StepFailure, if there is an aggregator active.
You may use this decorator explicitly if infer_composite_step is detecting
the behavior of your method incorrectly to force it to behave as a step. You
may also need to use this if your Api class inherits from RecipeApiPlain and
so doesn't have its methods automatically wrapped by infer_composite_step.
@_skip_inference # to avoid double-wraps
def _inner(*a, **kw):
# composite_steps always count as running a step.
agg = _DEFER_CONTEXT.aggregated_result
# If we're not aggregating
if agg is None:
return func(*a, **kw)
# Stop deferring results within this function; the ultimate result of the
# function will be added to our parent context's aggregated results and
# we'll return a DeferredResult.
with _DEFER_CONTEXT.begin_normal():
return agg.add_success(func(*a, **kw))
except StepFailure as ex:
return agg.add_failure(ex)
_inner.__original = func
return _inner
def defer_results():
Use this to defer step results in your code. All steps which would previously
return a result or throw an exception will instead return a DeferredResult.
Any exceptions which were thrown during execution will be thrown when either:
a. You call get_result() on the step's result.
b. You exit the lexical scope inside of the with statement
with defer_results():
api.step('a', ..)
api.step('b', ..)
result = api.m.module.im_a_composite_step(...)
api.m.echo('the data is', result.get_result())
If 'a' fails, 'b' and 'im a composite step' will still run.
If 'im a composite step' fails, then the get_result() call will raise
an exception.
If you don't try to use the result (don't call get_result()), an aggregate
failure will still be raised once you exit the lexical scope inside
the with statement.
assert _DEFER_CONTEXT.aggregated_result is None, (
"may not call defer_results in an active defer_results context")
with _DEFER_CONTEXT.begin_aggregate() as agg:
if agg.failures:
raise AggregatedStepFailure(agg)
class RecipeApiMeta(type):
WHITELIST = ('__init__',)
def __new__(mcs, name, bases, attrs):
"""Automatically wraps all methods of subclasses of RecipeApi with
@infer_composite_step. This allows defer_results to work as intended without
manually decorating every method.
wrap = lambda f: infer_composite_step(f) if f else f
for attr in attrs:
if attr in RecipeApiMeta.WHITELIST:
val = attrs[attr]
if isinstance(val, types.FunctionType):
attrs[attr] = wrap(val)
elif isinstance(val, property):
attrs[attr] = property(
return super(RecipeApiMeta, mcs).__new__(mcs, name, bases, attrs)
class RecipeApiPlain(object):
Framework class for handling recipe_modules.
Inherit from this in your recipe_modules/<name>/ . This class provides
wiring for your config context (in self.c and methods, and for dependency
injection (in self.m).
Dependency injection takes place in load_recipe_modules() in
USE RecipeApi INSTEAD, UNLESS your RecipeApi subclass derives from something
which defines its own __metaclass__. Deriving from RecipeApi instead of
RecipeApiPlain allows your RecipeApi subclass to automatically work with
defer_results without needing to decorate every methods with
def __init__(self, module=None, test_data=DisabledTestData(), **_kwargs):
"""Note: Injected dependencies are NOT available in __init__()."""
super(RecipeApiPlain, self).__init__()
self._module = module
assert isinstance(test_data, (ModuleTestData, DisabledTestData))
self._test_data = test_data
# If we're the 'root' api, inject directly into 'self'.
# Otherwise inject into 'self.m'
if not isinstance(module, types.ModuleType):
self.m = self
self.m = ModuleInjectionSite(self)
# If our module has a test api, it gets injected here.
self.test_api = None
# Config goes here.
self.c = None
def initialize(self):
Initializes the recipe module after it has been instantiated with all
dependencies injected and available.
def get_config_defaults(self): # pylint: disable=R0201
Allows your api to dynamically determine static default values for configs.
return {}
def make_config(self, config_name=None, optional=False, **CONFIG_VARS):
"""Returns a 'config blob' for the current API."""
return self.make_config_params(config_name, optional, **CONFIG_VARS)[0]
def _get_config_item(self, config_name, optional=False):
"""Get the config item for a given name.
If `config_name` does not refer to a config item for the current module,
the behavior is determined by the value of `optional`:
* if optional is True, then None will be returned
* else a KeyError will be raised with an error message containing
`config_name`, the name of the api's module and the list of the api's
module's config names.
ctx = self._module.CONFIG_CTX
return ctx.CONFIG_ITEMS[config_name]
except KeyError:
if optional:
return None
raise KeyError(
'%s is not the name of a configuration for module %s: %s' % (
config_name, self._module.__name__, sorted(ctx.CONFIG_ITEMS)))
def make_config_params(self, config_name, optional=False, **CONFIG_VARS):
"""Returns a 'config blob' for the current API, and the computed params
for all dependent configurations.
The params have the following order of precendence. Each subsequent param
is dict.update'd into the final parameters, so the order is from lowest to
higest precedence on a per-key basis:
* if config_name in CONFIG_CTX
* get_config_defaults()
* else
* get_config_defaults()
generic_params = self.get_config_defaults() # generic defaults
generic_params.update(CONFIG_VARS) # per-invocation values
ctx = self._module.CONFIG_CTX
if optional and not ctx:
return None, generic_params
assert ctx, '%s has no config context' % self
params = self.get_config_defaults() # generic defaults
itm = None
if config_name:
itm = self._get_config_item(config_name, optional)
if not itm:
return None, generic_params
if itm:
params.update(itm.DEFAULT_CONFIG_VARS()) # per-item defaults
params.update(CONFIG_VARS) # per-invocation values
base = ctx.CONFIG_SCHEMA(**params)
if config_name is None:
return base, params
return itm(base), params
def set_config(self, config_name=None, optional=False, **CONFIG_VARS):
"""Sets the modules and its dependencies to the named configuration."""
assert self._module
config, _ = self.make_config_params(config_name, optional, **CONFIG_VARS)
if config:
self.c = config
def apply_config(self, config_name, config_object=None, optional=False):
"""Apply a named configuration to the provided config object or self."""
itm = self._get_config_item(config_name)
itm(config_object or self.c, optional=optional)
def resource(self, *path):
"""Returns path to a file under <recipe module>/resources/ directory.
path: path relative to module's resources/ directory.
# TODO(vadimsh): Verify that file exists. Including a case like:
# module.resource('dir').join('subdir', '')
return self._module.RESOURCE_DIRECTORY.join(*path)
def repo_resource(self, *path):
"""Returns a resource path, where path is relative to the root of
the recipe repo where this module is defined.
return self._module.REPO_ROOT.join(*path)
def name(self):
return self._module.NAME
class RecipeApi(RecipeApiPlain):
__metaclass__ = RecipeApiMeta
class RecipeScriptApi(RecipeApiPlain, ModuleInjectionSite):
# TODO(dnj): Delete this and make recipe scripts use standard recipe APIs.
# This is a sentinel object for the Property system. This allows users to
# specify a default of None that will actually be respected.
class BoundProperty(object):
A bound, named version of a Property.
A BoundProperty is different than a Property, in that it requires a name,
as well as all of the arguments to be provided. It's intended to be
the declaration of the Property, with no mutation, so the logic about
what a property does is very clear.
The reason there is a distinction between this and a Property is because
we want the user interface for defining properties to be
'prop_name': Property(),
We don't want to have to duplicate the name in both the key of the dictionary
and then Property constructor call, so we need to modify this dictionary
before we actually use it, and inject knowledge into it about its name. We
don't want to actually mutate this though, since we're striving for immutable,
declarative code, so instead we generate a new BoundProperty object from the
defined Property object.
def legal_module_property_name(name, full_decl_name):
If this is a special $repo_name/module name.
repo_name, module = full_decl_name.split('::', 1)
return name == '$%s/%s' % (repo_name, module)
def legal_name(name, is_param_name=False):
If this name is a legal property name.
is_param_name determines if this name in the name of a property, or a
param_name. See the constructor documentation for more information.
The rules are as follows:
* Cannot start with an underscore.
This is for internal arguments, namely _engine (for the step module).
* Cannot be 'self'
This is to avoid conflict with recipe modules, which use the name self.
* Cannot be a python keyword
if name.startswith('_'):
return False
if name in ('self',):
return False
if keyword.iskeyword(name):
return False
regex = r'^[a-zA-Z][a-zA-Z0-9_]*$' if is_param_name else (
return bool(re.match(regex, name))
def __init__(self, default, from_environ, help, kind, name, property_type,
full_decl_name, param_name=None):
Constructor for BoundProperty.
default (jsonish): The default value for this Property. Must be
from_environ (str|None): If given, specifies an environment variable to
grab the default property value from before falling back to the
hardcoded default. If the property value is explicitly passed to the
recipe, it still takes precedence over the environment. If you rely on
this, 'kind' must be string-compatible (since environ contains strings).
help (str): The help text for this Property.
kind (type|ConfigBase): The type of this Property. You can either pass in
a raw python type, or a Config Type, using the recipe engine config
name (str): The name of this Property.
property_type (str): One of RECIPE_PROPERTY or MODULE_PROPERTY.
full_decl_name (str): The fully qualified name of the recipe or module
where this property is defined. This has the form of:
param_name (str|None): The name of the python function parameter this
property should be stored in. Can be used to allow for dotted property
names, e.g.
'': Property(param_name="bizbaz")
assert property_type in (self.RECIPE_PROPERTY, self.MODULE_PROPERTY), \
# first, check if this is a special '$repo_name/module' property type
# declaration.
is_module_property = (
property_type is self.MODULE_PROPERTY and
self.legal_module_property_name(name, full_decl_name))
if not (is_module_property or BoundProperty.legal_name(name)):
raise ValueError("Illegal name '{}'.".format(name))
param_name = param_name or name
if not BoundProperty.legal_name(param_name, is_param_name=True):
raise ValueError("Illegal param_name '{}'.".format(param_name))
if default is not PROPERTY_SENTINEL:
raise TypeError('default=%r is not json-encodable' % (default,))
self.__default = default
self.__from_environ = from_environ
self.__help = help
self.__kind = kind
self.__name = name
self.__property_type = property_type
self.__param_name = param_name
self.__full_decl_name = full_decl_name
def name(self):
return self.__name
def param_name(self):
return self.__param_name
def default(self):
if self.__default is PROPERTY_SENTINEL:
return self.__default
return copy.deepcopy(self.__default)
def from_environ(self):
return self.__from_environ
def kind(self):
return self.__kind
def help(self):
return self.__help
def full_decl_name(self):
return self.__full_decl_name
def interpret(self, value, environ):
Interprets the value for this Property.
value: The value to interpret. May be None, which means no explicit value
is provided and we should grab a default.
environ: An environment dict to use for grabbing values for properties
that use 'from_environ'.
The value to use for this property. Raises an error if
this property has no valid interpretation.
# Pick from environment if not given explicitly.
if value is PROPERTY_SENTINEL and self.__from_environ:
value = environ.get(self.__from_environ, PROPERTY_SENTINEL)
# If have a value (passed explicitly or through environ), check its type.
if value is not PROPERTY_SENTINEL:
if self.kind is not None:
# The config system handles type checking for us here.
return value
if self.__default is not PROPERTY_SENTINEL:
return self.default
raise ValueError(
"No default specified and no value provided for '{}' from {} '{}'".format(, self.__property_type, self.full_decl_name))
class Property(object):
def __init__(self, default=PROPERTY_SENTINEL, from_environ=None, help="",
kind=None, param_name=None):
Constructor for Property.
default: The default value for this Property. Note: A default
value of None is allowed. To have no default value, omit
this argument. This must be a valid JSON-encodable object.
from_environ: If given, specifies an environment variable to grab the
default property value from before falling back to the
hardcoded default. If the property value is explicitly
passed to the recipe, it still takes precedence over the
environment. If you rely on this, 'kind' must be
string-compatible (since environ contains strings).
help: The help text for this Property.
kind: The type of this Property. You can either pass in a raw python
type, or a Config Type, using the recipe engine config system.
if default is not PROPERTY_SENTINEL:
raise TypeError('default=%r is not json-encodable' % (default,))
if from_environ is not None:
if not isinstance(from_environ, basestring):
raise TypeError('from_environ=%r must be a string' % (from_environ,))
self._default = default
self._from_environ = from_environ = help
self.param_name = param_name
# NOTE: late import to avoid early protobuf import
from .config import Single
if isinstance(kind, type):
if kind in (str, unicode):
kind = basestring
kind = Single(kind)
self.kind = kind
def bind(self, name, property_type, full_decl_name):
Gets the BoundProperty version of this Property. Requires a name.
return BoundProperty(
self._default, self._from_environ,, self.kind, name,
property_type, full_decl_name, self.param_name)
class UndefinedPropertyException(TypeError):