Moved conflicting code into 'types' submodule
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2 changed files with 66 additions and 62 deletions
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@ -1,64 +1,2 @@
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# Marshmallow fields
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from marshmallow.fields import *
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# Marshmallow fields to JSON schema types
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# Note: We shouldn't ever need to use this directly. We should go via the apispec converter
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from apispec.ext.marshmallow.field_converter import DEFAULT_FIELD_MAPPING
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# Extra standard library Python types
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from datetime import date, datetime, time, timedelta
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from decimal import Decimal
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from typing import Dict, List, Tuple, Union
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from uuid import UUID
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"""
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TODO: Use this to convert arbitrary dictionary into its own schema, for W3C TD
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First: Convert Python non-builtins to builtins using DEFAULT_BUILTIN_CONVERSIONS
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Then match types of each element to Field using DEFAULT_TYPE_MAPPING
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Finally convert Fields to JSON using converter (preferred due to extra metadata), or DEFAULT_FIELD_MAPPING
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"""
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# Python types to Marshmallow fields
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DEFAULT_TYPE_MAPPING = {
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bool: Boolean,
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date: Date,
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datetime: DateTime,
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Decimal: Decimal,
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float: Float,
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int: Integer,
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str: String,
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time: Time,
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timedelta: TimeDelta,
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UUID: UUID,
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dict: Dict,
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Dict: Dict,
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}
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# Functions to handle conversion of common Python types into serialisable Python types
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def ndarray_to_list(o):
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return o.tolist()
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def to_int(o):
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return int(o)
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def to_float(o):
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return float(o)
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def to_string(o):
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return str(o)
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# Map of Python type conversions
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DEFAULT_BUILTIN_CONVERSIONS = {
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"numpy.ndarray": ndarray_to_list,
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"numpy.int": to_int,
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"fractions.Fraction": to_float,
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}
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# Use with [x.__module__+"."+x.__name__ for x in inspect.getmro(type(POSSIBLE_MATCHER))]
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# Resulting array will contain strings with the same format as keys in DEFAULT_BUILTIN_CONVERSIONS
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66
openflexure_microscope/common/flask_labthings/types.py
Normal file
66
openflexure_microscope/common/flask_labthings/types.py
Normal file
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@ -0,0 +1,66 @@
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# Marshmallow fields to JSON schema types
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# Note: We shouldn't ever need to use this directly. We should go via the apispec converter
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from apispec.ext.marshmallow.field_converter import DEFAULT_FIELD_MAPPING
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from . import fields
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# Extra standard library Python types
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from datetime import date, datetime, time, timedelta
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from decimal import Decimal
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from typing import Dict, List, Tuple, Union
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from uuid import UUID
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"""
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TODO: Use this to convert arbitrary dictionary into its own schema, for W3C TD
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First: Convert Python non-builtins to builtins using DEFAULT_BUILTIN_CONVERSIONS
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Then match types of each element to Field using DEFAULT_TYPE_MAPPING
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Finally convert Fields to JSON using converter (preferred due to extra metadata), or DEFAULT_FIELD_MAPPING
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"""
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# Python types to Marshmallow fields
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DEFAULT_TYPE_MAPPING = {
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bool: fields.Boolean,
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date: fields.Date,
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datetime: fields.DateTime,
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Decimal: fields.Decimal,
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float: fields.Float,
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int: fields.Integer,
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str: fields.String,
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time: fields.Time,
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timedelta: fields.TimeDelta,
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UUID: fields.UUID,
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dict: fields.Dict,
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Dict: fields.Dict,
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}
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# Functions to handle conversion of common Python types into serialisable Python types
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def ndarray_to_list(o):
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return o.tolist()
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def to_int(o):
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return int(o)
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def to_float(o):
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return float(o)
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def to_string(o):
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return str(o)
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# Map of Python type conversions
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DEFAULT_BUILTIN_CONVERSIONS = {
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"numpy.ndarray": ndarray_to_list,
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"numpy.int": to_int,
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"fractions.Fraction": to_float,
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}
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# TODO: Deserialiser with inverse defaults
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# TODO: Option to switch to .npy serialisation/deserialisation (or look for a better common array format)
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# Use with [x.__module__+"."+x.__name__ for x in inspect.getmro(type(POSSIBLE_MATCHER))]
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# Resulting array will contain strings with the same format as keys in DEFAULT_BUILTIN_CONVERSIONS
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