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# -*- coding: utf-8 -*-
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
import datetime
import functools
import json
from pathlib import Path
import sys
import textwrap
from typing import Any, Callable, Iterable, Sequence, Tuple, Union, Optional
import urllib.request
import platformdirs # type: ignore
import diskcache # type: ignore
import jinja2
import jsonschema # type: ignore
from jsonschema import _utils # type: ignore
import yaml
try:
from yaml import CSafeLoader as SafeLoader
except ImportError:
from yaml import SafeLoader # type: ignore
def date_fromisoformat(datestr: str) -> datetime.date:
return datetime.date.fromisoformat(datestr)
def datetime_fromisoformat(datestr: str) -> datetime.datetime:
return datetime.datetime.fromisoformat(datestr)
TESTING_MODE = "pytest" in sys.modules
JSONType = Union[list, dict, str, int, float, None]
"""
The types supported by JSON.
This is only an approximation -- this should really be a recursive type.
"""
class DictWrapper(dict):
pass
class _NoDatesSafeLoader(SafeLoader):
@classmethod
def remove_implicit_resolver(cls, tag_to_remove):
"""
Remove implicit resolvers for a particular tag
Takes care not to modify resolvers in super classes.
We want to load datetimes as strings, not dates, because we
go on to serialise as json which doesn't have the advanced types
of yaml, and leads to incompatibilities down the track.
"""
if "yaml_implicit_resolvers" not in cls.__dict__:
cls.yaml_implicit_resolvers = cls.yaml_implicit_resolvers.copy()
for first_letter, mappings in cls.yaml_implicit_resolvers.items():
cls.yaml_implicit_resolvers[first_letter] = [
(tag, regexp) for tag, regexp in mappings if tag != tag_to_remove
]
# Since we use JSON schema to validate, and JSON schema doesn't support
# datetimes, we don't want the YAML loader to give us datetimes -- just
# strings.
_NoDatesSafeLoader.remove_implicit_resolver("tag:yaml.org,2002:timestamp")
def yaml_load(stream):
"""
Map line number to yaml nodes, and preserve the order
of metrics as they appear in the metrics.yaml file.
"""
class SafeLineLoader(_NoDatesSafeLoader):
pass
def _construct_mapping_adding_line(loader, node):
loader.flatten_mapping(node)
mapping = DictWrapper(loader.construct_pairs(node))
mapping.defined_in = {"line": node.start_mark.line}
return mapping
SafeLineLoader.add_constructor(
yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG, _construct_mapping_adding_line
)
return yaml.load(stream, SafeLineLoader)
def ordered_yaml_dump(data, **kwargs):
class OrderedDumper(yaml.Dumper):
pass
def _dict_representer(dumper, data):
return dumper.represent_mapping(
yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG, data.items()
)
OrderedDumper.add_representer(DictWrapper, _dict_representer)
return yaml.dump(data, Dumper=OrderedDumper, **kwargs)
def load_yaml_or_json(path: Path):
"""
Load the content from either a .json or .yaml file, based on the filename
extension.
:param path: `pathlib.Path` object
:rtype object: The tree of objects as a result of parsing the file.
:raises ValueError: The file is neither a .json, .yml or .yaml file.
:raises FileNotFoundError: The file does not exist.
"""
# If in py.test, support bits of literal JSON/YAML content
if TESTING_MODE and isinstance(path, dict):
return yaml_load(yaml.dump(path))
if path.suffix == ".json":
with path.open("r", encoding="utf-8") as fd:
return json.load(fd)
elif path.suffix in (".yml", ".yaml", ".yamlx"):
with path.open("r", encoding="utf-8") as fd:
return yaml_load(fd)
else:
raise ValueError(f"Unknown file extension {path.suffix}")
def ensure_list(value: Any) -> Sequence[Any]:
"""
Ensures that the value is a list. If it is anything but a list or tuple, a
list with a single element containing only value is returned.
"""
if not isinstance(value, (list, tuple)):
return [value]
return value
def to_camel_case(input: str, capitalize_first_letter: bool) -> str:
"""
Convert the value to camelCase.
This additionally replaces any '.' with '_'. The first letter is capitalized
depending on `capitalize_first_letter`.
"""
sanitized_input = input.replace(".", "_").replace("-", "_")
# Filter out any empty token. This could happen due to leading '_' or
# consecutive '__'.
tokens = [s.capitalize() for s in sanitized_input.split("_") if len(s) != 0]
# If we're not meant to capitalize the first letter, then lowercase it.
if not capitalize_first_letter:
tokens[0] = tokens[0].lower()
# Finally join the tokens and capitalize.
return "".join(tokens)
def camelize(value: str) -> str:
"""
Convert the value to camelCase (with a lower case first letter).
This is a thin wrapper around inflection.camelize that handles dots in
addition to underscores.
"""
return to_camel_case(value, False)
def Camelize(value: str) -> str:
"""
Convert the value to CamelCase (with an upper case first letter).
This is a thin wrapper around inflection.camelize that handles dots in
addition to underscores.
"""
return to_camel_case(value, True)
def snake_case(value: str) -> str:
"""
Convert the value to snake_case.
"""
return value.lower().replace(".", "_").replace("-", "_")
def screaming_case(value: str) -> str:
"""
Convert the value to SCREAMING_SNAKE_CASE.
"""
return value.upper().replace(".", "_").replace("-", "_")
@functools.lru_cache()
def get_jinja2_template(
template_name: str, filters: Iterable[Tuple[str, Callable]] = ()
):
"""
Get a Jinja2 template that ships with glean_parser.
The template has extra filters for camel-casing identifiers.
:param template_name: Name of a file in ``glean_parser/templates``
:param filters: tuple of 2-tuple. A tuple of (name, func) pairs defining
additional filters.
"""
env = jinja2.Environment(
loader=jinja2.PackageLoader("glean_parser", "templates"),
trim_blocks=True,
lstrip_blocks=True,
)
env.filters["camelize"] = camelize
env.filters["Camelize"] = Camelize
env.filters["scream"] = screaming_case
for filter_name, filter_func in filters:
env.filters[filter_name] = filter_func
return env.get_template(template_name)
def keep_value(f):
"""
Wrap a generator so the value it returns (rather than yields), will be
accessible on the .value attribute when the generator is exhausted.
"""
class ValueKeepingGenerator(object):
def __init__(self, g):
self.g = g
self.value = None
def __iter__(self):
self.value = yield from self.g
@functools.wraps(f)
def g(*args, **kwargs):
return ValueKeepingGenerator(f(*args, **kwargs))
return g
def get_null_resolver(schema):
"""
Returns a JSON Pointer resolver that does nothing.
This lets us handle the moz: URLs in our schemas.
"""
class NullResolver(jsonschema.RefResolver):
def resolve_remote(self, uri):
if uri in self.store:
return self.store[uri]
if uri == "":
return self.referrer
return NullResolver.from_schema(schema)
def fetch_remote_url(url: str, cache: bool = True):
"""
Fetches the contents from an HTTP url or local file path, and optionally
caches it to disk.
"""
# Include the Python version in the cache key, since caches aren't
# sharable across Python versions.
key = (url, str(sys.version_info))
is_http = url.startswith("http")
if not is_http:
with open(url, "r", encoding="utf-8") as fd:
return fd.read()
if cache:
cache_dir = platform.user_cache_dir("glean_parser", "mozilla")
with diskcache.Cache(cache_dir) as dc:
if key in dc:
return dc[key]
contents: str = urllib.request.urlopen(url).read()
if cache:
with diskcache.Cache(cache_dir) as dc:
dc[key] = contents
return contents
_unset = _utils.Unset()
def pprint_validation_error(error) -> str:
"""
A version of jsonschema's ValidationError __str__ method that doesn't
include the schema fragment that failed. This makes the error messages
much more succinct.
It also shows any subschemas of anyOf/allOf that failed, if any (what
jsonschema calls "context").
"""
essential_for_verbose = (
error.validator,
error.validator_value,
error.instance,
error.schema,
)
if any(m is _unset for m in essential_for_verbose):
return textwrap.fill(error.message)
instance = error.instance
for path in list(error.relative_path)[::-1]:
if isinstance(path, str):
instance = {path: instance}
else:
instance = [instance]
yaml_instance = ordered_yaml_dump(instance, width=72, default_flow_style=False)
parts = ["```", yaml_instance.rstrip(), "```", "", textwrap.fill(error.message)]
if error.context:
parts.extend(
textwrap.fill(x.message, initial_indent=" ", subsequent_indent=" ")
for x in error.context
)
description = error.schema.get("description")
if description:
parts.extend(
["", "Documentation for this node:", textwrap.indent(description, " ")]
)
return "\n".join(parts)
def format_error(
filepath: Union[str, Path],
header: str,
content: str,
lineno: Optional[int] = None,
) -> str:
"""
Format a jsonshema validation error.
"""
if isinstance(filepath, Path):
filepath = filepath.resolve()
else:
filepath = "<string>"
if lineno:
filepath = f"{filepath}:{lineno}"
if header:
return f"{filepath}: {header}\n{textwrap.indent(content, ' ')}"
else:
return f"{filepath}:\n{textwrap.indent(content, ' ')}"
def parse_expiration_date(expires: str) -> datetime.date:
"""
Parses the expired field date (yyyy-mm-dd) as a date.
Raises a ValueError in case the string is not properly formatted.
"""
try:
return date_fromisoformat(expires)
except (TypeError, ValueError):
raise ValueError(
f"Invalid expiration date '{expires}'. "
"Must be of the form yyyy-mm-dd in UTC."
)
def parse_expiration_version(expires: str) -> int:
"""
Parses the expired field version string as an integer.
Raises a ValueError in case the string does not contain a valid
positive integer.
"""
try:
if isinstance(expires, int):
version_number = int(expires)
if version_number > 0:
return version_number
# Fall-through: if it's not an integer or is not greater than zero,
# raise an error.
raise ValueError()
except ValueError:
raise ValueError(
f"Invalid expiration version '{expires}'. Must be a positive integer."
)
def is_expired(expires: str, major_version: Optional[int] = None) -> bool:
"""
Parses the `expires` field in a metric or ping and returns whether
the object should be considered expired.
"""
if expires == "never":
return False
elif expires == "expired":
return True
elif major_version is not None:
return parse_expiration_version(expires) <= major_version
else:
date = parse_expiration_date(expires)
return date <= datetime.datetime.now(datetime.timezone.utc).date()
def validate_expires(expires: str, major_version: Optional[int] = None) -> None:
"""
If expiration by major version is enabled, raises a ValueError in
case `expires` is not a positive integer.
Otherwise raises a ValueError in case the `expires` is not ISO8601
parseable, or in case the date is more than 730 days (~2 years) in
the future.
"""
if expires in ("never", "expired"):
return
if major_version is not None:
parse_expiration_version(expires)
# Don't need to keep parsing dates if expiration by version
# is enabled. We don't allow mixing dates and versions for a
# single product.
return
date = parse_expiration_date(expires)
max_date = datetime.datetime.now() + datetime.timedelta(days=730)
if date > max_date.date():
raise ValueError(
f"'{expires}' is more than 730 days (~2 years) in the future.",
"Please make sure this is intentional.",
"You can supress this warning by adding EXPIRATION_DATE_TOO_FAR to no_lint",
"See: https://mozilla.github.io/glean_parser/metrics-yaml.html#no_lint",
)
def build_date(date: Optional[str]) -> datetime.datetime:
"""
Generate the build timestamp.
If `date` is set to `0` a static unix epoch time will be used.
If `date` it is set to a ISO8601 datetime string (e.g. `2022-01-03T17:30:00`)
it will use that date.
Note that any timezone offset will be ignored and UTC will be used.
Otherwise it will throw an error.
If `date` is `None` it will use the current date & time.
"""
if date is not None:
date = str(date)
if date == "0":
ts = datetime.datetime(1970, 1, 1, 0, 0, 0)
else:
ts = datetime_fromisoformat(date).replace(tzinfo=datetime.timezone.utc)
else:
ts = datetime.datetime.now(datetime.timezone.utc)
return ts
def report_validation_errors(all_objects):
"""
Report any validation errors found to the console.
Returns the number of errors reported.
"""
found_errors = 0
for error in all_objects:
found_errors += 1
print("=" * 78, file=sys.stderr)
print(error, file=sys.stderr)
return found_errors
def remove_output_params(d, output_params):
"""
Remove output-only params, such as "defined_in",
in order to validate the output against the input schema.
"""
modified_dict = {}
for key, value in d.items():
if key is not output_params:
modified_dict[key] = value
return modified_dict
# Names of parameters to pass to all metrics constructors constructors.
common_metric_args = [
"category",
"name",
"send_in_pings",
"lifetime",
"disabled",
]
# Names of parameters that only apply to some of the metrics types.
# **CAUTION**: This list needs to be in the order the Swift & Rust type constructors
# expects them. (The other language bindings don't care about the order).
extra_metric_args = [
"time_unit",
"memory_unit",
"allowed_extra_keys",
"reason_codes",
"range_min",
"range_max",
"bucket_count",
"histogram_type",
"numerators",
]
# This includes only things that the language bindings care about, not things
# that are metadata-only or are resolved into other parameters at parse time.
# **CAUTION**: This list needs to be in the order the Swift & Rust type constructors
# expects them. (The other language bindings don't care about the order). The
# `test_order_of_fields` test checks that the generated code is valid.
# **DO NOT CHANGE THE ORDER OR ADD NEW FIELDS IN THE MIDDLE**
metric_args = common_metric_args + extra_metric_args
# Names of ping parameters to pass to constructors.
ping_args = [
"name",
"include_client_id",
"send_if_empty",
"precise_timestamps",
"include_info_sections",
"enabled",
"schedules_pings",
"reason_codes",
]
# Names of parameters to pass to both metric and ping constructors (no duplicates).
extra_args = metric_args + [v for v in ping_args if v not in metric_args]
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