prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Optimize use of jsonschema.validate()
  It could be interesting to investigate if the fastjsonschema lib would give us better perfs :)
  
  I marked this as easy-pick since everything happens in `schema_validation.py`
  
  https://github.com/horejsek/python-fastjsonschema/
  
  </issue>
  <code>
  [start of kinto/schema_validation.py]
  1 import colander
  2 from jsonschema import ValidationError, SchemaError, RefResolutionError, validate
  3 
  4 try:  # pragma: no cover
  5     from jsonschema import Draft7Validator as DraftValidator
  6 except ImportError:
  7     from jsonschema import Draft4Validator as DraftValidator
  8 
  9 from pyramid.settings import asbool
  10 
  11 from kinto.core import utils
  12 from kinto.core.errors import raise_invalid
  13 from kinto.views import object_exists_or_404
  14 
  15 
  16 class JSONSchemaMapping(colander.SchemaNode):
  17     def schema_type(self, **kw):
  18         return colander.Mapping(unknown="preserve")
  19 
  20     def deserialize(self, cstruct=colander.null):
  21         # Start by deserializing a simple mapping.
  22         validated = super().deserialize(cstruct)
  23 
  24         # In case it is optional in parent schema.
  25         if not validated or validated in (colander.null, colander.drop):
  26             return validated
  27         try:
  28             check_schema(validated)
  29         except ValidationError as e:
  30             self.raise_invalid(e.message)
  31         return validated
  32 
  33 
  34 def check_schema(data):
  35     try:
  36         DraftValidator.check_schema(data)
  37     except SchemaError as e:
  38         message = e.path.pop() + e.message
  39         raise ValidationError(message)
  40 
  41 
  42 def validate_schema(data, schema, ignore_fields=[]):
  43     required_fields = [f for f in schema.get("required", []) if f not in ignore_fields]
  44     # jsonschema doesn't accept 'required': [] yet.
  45     # See https://github.com/Julian/jsonschema/issues/337.
  46     # In the meantime, strip out 'required' if no other fields are required.
  47     if required_fields:
  48         schema = {**schema, "required": required_fields}
  49     else:
  50         schema = {f: v for f, v in schema.items() if f != "required"}
  51 
  52     data = {f: v for f, v in data.items() if f not in ignore_fields}
  53 
  54     try:
  55         validate(data, schema)
  56     except ValidationError as e:
  57         if e.path:
  58             field = e.path[-1]
  59         elif e.validator_value:
  60             field = e.validator_value[-1]
  61         else:
  62             field = e.schema_path[-1]
  63         e.field = field
  64         raise e
  65     # Raise an error here if a reference in the schema doesn't resolve.
  66     # jsonschema doesn't provide schema validation checking upon creation yet,
  67     # it must be validated against data.
  68     # See https://github.com/Julian/jsonschema/issues/399
  69     # For future support https://github.com/Julian/jsonschema/issues/346.
  70     except RefResolutionError as e:
  71         raise e
  72 
  73 
  74 def validate_from_bucket_schema_or_400(data, resource_name, request, ignore_fields=[]):
  75     """Lookup in the parent objects if a schema was defined for this resource.
  76 
  77     If the schema validation feature is enabled, if a schema is/are defined, and if the
  78     data does not validate it/them, then it raises a 400 exception.
  79     """
  80     settings = request.registry.settings
  81     schema_validation = "experimental_collection_schema_validation"
  82     # If disabled from settings, do nothing.
  83     if not asbool(settings.get(schema_validation)):
  84         return
  85 
  86     bucket_id = request.matchdict["bucket_id"]
  87     bucket_uri = utils.instance_uri(request, "bucket", id=bucket_id)
  88     buckets = request.bound_data.setdefault("buckets", {})
  89     if bucket_uri not in buckets:
  90         # Unknown yet, fetch from storage.
  91         bucket = object_exists_or_404(
  92             request, resource_name="bucket", parent_id="", object_id=bucket_id
  93         )
  94         buckets[bucket_uri] = bucket
  95 
  96     # Let's see if the bucket defines a schema for this resource.
  97     metadata_field = f"{resource_name}:schema"
  98     bucket = buckets[bucket_uri]
  99     if metadata_field not in bucket:
  100         return
  101 
  102     # Validate or fail with 400.
  103     schema = bucket[metadata_field]
  104     try:
  105         validate_schema(data, schema, ignore_fields=ignore_fields)
  106     except ValidationError as e:
  107         raise_invalid(request, name=e.field, description=e.message)
  108     except RefResolutionError as e:
  109         raise_invalid(request, name="schema", description=str(e))
  110
  [end of kinto/schema_validation.py]
  </code>
  
  I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
  <patch>
  diff --git a/file.py b/file.py
  --- a/file.py
  +++ b/file.py
  @@ -1,27 +1,35 @@
   def euclidean(a, b):
  -    while b:
  -        a, b = b, a % b
  -    return a
  +    if b == 0:
  +        return a
  +    return euclidean(b, a % b)
   
   
   def bresenham(x0, y0, x1, y1):
       points = []
       dx = abs(x1 - x0)
       dy = abs(y1 - y0)
  -    sx = 1 if x0 < x1 else -1
  -    sy = 1 if y0 < y1 else -1
  -    err = dx - dy
  +    x, y = x0, y0
  +    sx = -1 if x0 > x1 else 1
  +    sy = -1 if y0 > y1 else 1
   
  -    while True:
  -        points.append((x0, y0))
  -        if x0 == x1 and y0 == y1:
  -            break
  -        e2 = 2 * err
  -        if e2 > -dy:
  -            err -= dy
  -            x0 += sx
  -        if e2 < dx:
  -            err += dx
  -            y0 += sy
  +    if dx > dy:
  +        err = dx / 2.0
  +        while x != x1:
  +            points.append((x, y))
  +            err -= dy
  +            if err < 0:
  +                y += sy
  +                err += dx
  +            x += sx
  +    else:
  +        err = dy / 2.0
  +        while y != y1:
  +            points.append((x, y))
  +            err -= dx
  +            if err < 0:
  +                x += sx
  +                err += dy
  +            y += sy
  +
  +    points.append((x, y))
       return points
  
  </patch>
golden_diff: diff --git a/kinto/schema_validation.py b/kinto/schema_validation.py
  --- a/kinto/schema_validation.py
  +++ b/kinto/schema_validation.py
  @@ -1,5 +1,6 @@
   import colander
  -from jsonschema import ValidationError, SchemaError, RefResolutionError, validate
  +from jsonschema import ValidationError, SchemaError, RefResolutionError
  +from jsonschema.validators import validator_for
   
   try:  # pragma: no cover
       from jsonschema import Draft7Validator as DraftValidator
  @@ -39,6 +40,34 @@
           raise ValidationError(message)
   
   
  +# Module level global that stores a version of every possible schema (as a <class 'dict'>)
  +# turned into a jsonschema instance (as <class 'jsonschema.validators.Validator'>).
  +_schema_cache = {}
  +
  +
  +def validate(data, schema):
  +    """Raise a ValidationError or a RefResolutionError if the data doesn't validate
  +    with the given schema.
  +
  +    Note that this function is just a "wrapper" on `jsonschema.validate()` but with
  +    some memoization based on the schema for better repeat performance.
  +    """
  +    # Because the schema is a dict, it can't be used as a hash key so it needs to be
  +    # "transformed" to something that is hashable. The quickest solution is to convert
  +    # it to a string.
  +    # Note that the order of the dict will determine the string it becomes. The solution
  +    # to that would a canonical serializer like `json.dumps(..., sort_keys=True)` but it's
  +    # overkill since the assumption is that the schema is very unlikely to be exactly
  +    # the same but different order.
  +    cache_key = str(schema)
  +    if cache_key not in _schema_cache:
  +        # This is essentially what the `jsonschema.validate()` shortcut function does.
  +        cls = validator_for(schema)
  +        cls.check_schema(schema)
  +        _schema_cache[cache_key] = cls(schema)
  +    return _schema_cache[cache_key].validate(data)
  +
  +
   def validate_schema(data, schema, ignore_fields=[]):
       required_fields = [f for f in schema.get("required", []) if f not in ignore_fields]
       # jsonschema doesn't accept 'required': [] yet.
  
verification_info: {"golden_diff": "diff --git a/kinto/schema_validation.py b/kinto/schema_validation.py\n--- a/kinto/schema_validation.py\n+++ b/kinto/schema_validation.py\n@@ -1,5 +1,6 @@\n import colander\n-from jsonschema import ValidationError, SchemaError, RefResolutionError, validate\n+from jsonschema import ValidationError, SchemaError, RefResolutionError\n+from jsonschema.validators import validator_for\n \n try:  # pragma: no cover\n     from jsonschema import Draft7Validator as DraftValidator\n@@ -39,6 +40,34 @@\n         raise ValidationError(message)\n \n \n+# Module level global that stores a version of every possible schema (as a <class 'dict'>)\n+# turned into a jsonschema instance (as <class 'jsonschema.validators.Validator'>).\n+_schema_cache = {}\n+\n+\n+def validate(data, schema):\n+    \"\"\"Raise a ValidationError or a RefResolutionError if the data doesn't validate\n+    with the given schema.\n+\n+    Note that this function is just a \"wrapper\" on `jsonschema.validate()` but with\n+    some memoization based on the schema for better repeat performance.\n+    \"\"\"\n+    # Because the schema is a dict, it can't be used as a hash key so it needs to be\n+    # \"transformed\" to something that is hashable. The quickest solution is to convert\n+    # it to a string.\n+    # Note that the order of the dict will determine the string it becomes. The solution\n+    # to that would a canonical serializer like `json.dumps(..., sort_keys=True)` but it's\n+    # overkill since the assumption is that the schema is very unlikely to be exactly\n+    # the same but different order.\n+    cache_key = str(schema)\n+    if cache_key not in _schema_cache:\n+        # This is essentially what the `jsonschema.validate()` shortcut function does.\n+        cls = validator_for(schema)\n+        cls.check_schema(schema)\n+        _schema_cache[cache_key] = cls(schema)\n+    return _schema_cache[cache_key].validate(data)\n+\n+\n def validate_schema(data, schema, ignore_fields=[]):\n     required_fields = [f for f in schema.get(\"required\", []) if f not in ignore_fields]\n     # jsonschema doesn't accept 'required': [] yet.\n", "issue": "Optimize use of jsonschema.validate()\nIt could be interesting to investigate if the fastjsonschema lib would give us better perfs :)\r\n\r\nI marked this as easy-pick since everything happens in `schema_validation.py`\r\n\r\nhttps://github.com/horejsek/python-fastjsonschema/\n", "before_files": [{"content": "import colander\nfrom jsonschema import ValidationError, SchemaError, RefResolutionError, validate\n\ntry:  # pragma: no cover\n    from jsonschema import Draft7Validator as DraftValidator\nexcept ImportError:\n    from jsonschema import Draft4Validator as DraftValidator\n\nfrom pyramid.settings import asbool\n\nfrom kinto.core import utils\nfrom kinto.core.errors import raise_invalid\nfrom kinto.views import object_exists_or_404\n\n\nclass JSONSchemaMapping(colander.SchemaNode):\n    def schema_type(self, **kw):\n        return colander.Mapping(unknown=\"preserve\")\n\n    def deserialize(self, cstruct=colander.null):\n        # Start by deserializing a simple mapping.\n        validated = super().deserialize(cstruct)\n\n        # In case it is optional in parent schema.\n        if not validated or validated in (colander.null, colander.drop):\n            return validated\n        try:\n            check_schema(validated)\n        except ValidationError as e:\n            self.raise_invalid(e.message)\n        return validated\n\n\ndef check_schema(data):\n    try:\n        DraftValidator.check_schema(data)\n    except SchemaError as e:\n        message = e.path.pop() + e.message\n        raise ValidationError(message)\n\n\ndef validate_schema(data, schema, ignore_fields=[]):\n    required_fields = [f for f in schema.get(\"required\", []) if f not in ignore_fields]\n    # jsonschema doesn't accept 'required': [] yet.\n    # See https://github.com/Julian/jsonschema/issues/337.\n    # In the meantime, strip out 'required' if no other fields are required.\n    if required_fields:\n        schema = {**schema, \"required\": required_fields}\n    else:\n        schema = {f: v for f, v in schema.items() if f != \"required\"}\n\n    data = {f: v for f, v in data.items() if f not in ignore_fields}\n\n    try:\n        validate(data, schema)\n    except ValidationError as e:\n        if e.path:\n            field = e.path[-1]\n        elif e.validator_value:\n            field = e.validator_value[-1]\n        else:\n            field = e.schema_path[-1]\n        e.field = field\n        raise e\n    # Raise an error here if a reference in the schema doesn't resolve.\n    # jsonschema doesn't provide schema validation checking upon creation yet,\n    # it must be validated against data.\n    # See https://github.com/Julian/jsonschema/issues/399\n    # For future support https://github.com/Julian/jsonschema/issues/346.\n    except RefResolutionError as e:\n        raise e\n\n\ndef validate_from_bucket_schema_or_400(data, resource_name, request, ignore_fields=[]):\n    \"\"\"Lookup in the parent objects if a schema was defined for this resource.\n\n    If the schema validation feature is enabled, if a schema is/are defined, and if the\n    data does not validate it/them, then it raises a 400 exception.\n    \"\"\"\n    settings = request.registry.settings\n    schema_validation = \"experimental_collection_schema_validation\"\n    # If disabled from settings, do nothing.\n    if not asbool(settings.get(schema_validation)):\n        return\n\n    bucket_id = request.matchdict[\"bucket_id\"]\n    bucket_uri = utils.instance_uri(request, \"bucket\", id=bucket_id)\n    buckets = request.bound_data.setdefault(\"buckets\", {})\n    if bucket_uri not in buckets:\n        # Unknown yet, fetch from storage.\n        bucket = object_exists_or_404(\n            request, resource_name=\"bucket\", parent_id=\"\", object_id=bucket_id\n        )\n        buckets[bucket_uri] = bucket\n\n    # Let's see if the bucket defines a schema for this resource.\n    metadata_field = f\"{resource_name}:schema\"\n    bucket = buckets[bucket_uri]\n    if metadata_field not in bucket:\n        return\n\n    # Validate or fail with 400.\n    schema = bucket[metadata_field]\n    try:\n        validate_schema(data, schema, ignore_fields=ignore_fields)\n    except ValidationError as e:\n        raise_invalid(request, name=e.field, description=e.message)\n    except RefResolutionError as e:\n        raise_invalid(request, name=\"schema\", description=str(e))\n", "path": "kinto/schema_validation.py"}]}