feat: add covidcast meta signal model

.pylintrc

@@ -5,7 +5,7 @@ min-public-methods=1
 
 [MESSAGES CONTROL]
 
-disable=R0801, C0330, E1101, E0611, C0114, C0116, C0103, R0913, R0914, W0702, too-many-public-methods
+disable=R0801, C0330, E1101, E0611, C0114, C0116, C0103, R0913, R0914, W0702, too-many-public-methods, too-many-instance-attributes
 
 [FORMAT]
 max-line-length=120

delphi_epidata/__init__.py

@@ -13,5 +13,14 @@
     EpiDataFormatType,
     AEpiDataCall,
 )
+from ._covidcast import (
+    DataSignal,
+    DataSource,
+    WebLink,
+    DataSignalGeoStatistics,
+    CovidcastDataSources,
+    GeoType,
+    TimeType,
+)
 
 __author__ = "Delphi Group"

delphi_epidata/_covidcast.py

@@ -0,0 +1,318 @@
+from dataclasses import Field, InitVar, dataclass, field, fields
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    Generic,
+    Iterable,
+    List,
+    Literal,
+    Mapping,
+    Optional,
+    OrderedDict,
+    Sequence,
+    Tuple,
+    Union,
+    overload,
+)
+from functools import cached_property
+from pandas import DataFrame
+from ._model import (
+    EpiRangeLike,
+    CALL_TYPE,
+    EpidataFieldInfo,
+    EpidataFieldType,
+    EpiRangeParam,
+    InvalidArgumentException,
+)
+
+
+GeoType = Literal["nation", "msa", "hrr", "hhs", "state", "county"]
+TimeType = Literal["day", "week"]
+
+
+@dataclass
+class WebLink:
+    """
+    represents a web link
+    """
+
+    alt: str
+    href: str
+
+
+@dataclass
+class DataSignalGeoStatistics:
+    """
+    COVIDcast signal statistics
+    """
+
+    min: float
+    max: float
+    mean: float
+    stdev: float
+
+
+def _limit_fields(data: Dict[str, Any], class_fields: Tuple[Field, ...]) -> Dict[str, Any]:
+    field_names = {f.name for f in class_fields}
+    return {k: v for k, v in data.items() if k in field_names}
+
+
+def define_covidcast_fields() -> List[EpidataFieldInfo]:
+    return [
+        EpidataFieldInfo("source", EpidataFieldType.text),
+        EpidataFieldInfo("signal", EpidataFieldType.text),
+        EpidataFieldInfo(
+            "geo_type",
+            EpidataFieldType.categorical,
+            categories=["nation", "msa", "hrr", "hhs", "state", "county"],
+        ),
+        EpidataFieldInfo("geo_value", EpidataFieldType.text),
+        EpidataFieldInfo("time_type", EpidataFieldType.categorical, categories=["day", "week"]),
+        EpidataFieldInfo("time_value", EpidataFieldType.date),
+        EpidataFieldInfo("issue", EpidataFieldType.date),
+        EpidataFieldInfo("lag", EpidataFieldType.int),
+        EpidataFieldInfo("value", EpidataFieldType.float),
+        EpidataFieldInfo("stderr", EpidataFieldType.float),
+        EpidataFieldInfo("sample_size", EpidataFieldType.int),
+        EpidataFieldInfo("direction", EpidataFieldType.float),
+        EpidataFieldInfo("missing_value", EpidataFieldType.int),
+        EpidataFieldInfo("missing_stderr", EpidataFieldType.int),
+        EpidataFieldInfo("missing_sample_size", EpidataFieldType.int),
+    ]
+
+
+@dataclass
+class DataSignal(Generic[CALL_TYPE]):
+    """
+    represents a COVIDcast data signal
+    """
+
+    _create_call: Callable[[Mapping[str, Union[None, EpiRangeLike, Iterable[EpiRangeLike]]]], CALL_TYPE]
+
+    source: str
+    signal: str
+    signal_basename: str
+    name: str
+    active: bool
+    short_description: str
+    description: str
+    time_label: str
+    value_label: str
+    format: Literal["per100k", "percent", "fraction", "count", "raw"] = "raw"
+    category: Literal["early", "public", "late", "other"] = "other"
+    high_values_are: Literal["good", "bad", "neutral"] = "neutral"
+    is_smoothed: bool = False
+    is_weighted: bool = False
+    is_cumulative: bool = False
+    has_stderr: bool = False
+    has_sample_size: bool = False
+    link: Sequence[WebLink] = field(default_factory=list)
+    compute_from_base: bool = False
+    time_type: TimeType = "day"
+
+    geo_types: Dict[GeoType, DataSignalGeoStatistics] = field(default_factory=dict)
+
+    def __post_init__(self) -> None:
+        self.link = [WebLink(alt=l["alt"], href=l["href"]) if isinstance(l, dict) else l for l in self.link]
+        stats_fields = fields(DataSignalGeoStatistics)
+        self.geo_types = {
+            k: DataSignalGeoStatistics(**_limit_fields(l, stats_fields)) if isinstance(l, dict) else l
+            for k, l in self.geo_types.items()
+        }
+
+    @staticmethod
+    def to_df(signals: Iterable["DataSignal"]) -> DataFrame:
+        df = DataFrame(
+            signals,
+            columns=[
+                "source",
+                "signal",
+                "name",
+                "active",
+                "short_description",
+                "description",
+                "time_type",
+                "time_label",
+                "value_label",
+                "format",
+                "category",
+                "high_values_are",
+                "is_smoothed",
+                "is_weighted",
+                "is_cumulative",
+                "has_stderr",
+                "has_sample_size",
+            ],
+        )
+        df.insert(6, "geo_types", [",".join(s.geo_types.keys()) for s in signals])
+        return df.set_index(["source", "signal"])
+
+    @property
+    def key(self) -> Tuple[str, str]:
+        return (self.source, self.signal)
+
+    def call(
+        self,
+        geo_type: GeoType,
+        geo_values: Union[int, str, Iterable[Union[int, str]]],
+        time_values: EpiRangeParam,
+        as_of: Union[None, str, int] = None,
+        issues: Optional[EpiRangeParam] = None,
+        lag: Optional[int] = None,
+    ) -> CALL_TYPE:
+        """Fetch Delphi's COVID-19 Surveillance Streams"""
+        if any((v is None for v in (geo_type, geo_values, time_values))):
+            raise InvalidArgumentException("`geo_type`, `time_values`, and `geo_values` are all required")
+        if issues is not None and lag is not None:
+            raise InvalidArgumentException("`issues` and `lag` are mutually exclusive")
+
+        return self._create_call(
+            dict(
+                data_source=self.source,
+                signals=self.signal,
+                time_type=self.time_type,
+                time_values=time_values,
+                geo_type=geo_type,
+                geo_values=geo_values,
+                as_of=as_of,
+                issues=issues,
+                lag=lag,
+            )
+        )
+
+    def __call__(
+        self,
+        geo_type: GeoType,
+        geo_values: Union[int, str, Iterable[Union[int, str]]],
+        time_values: EpiRangeParam,
+        as_of: Union[None, str, int] = None,
+        issues: Optional[EpiRangeParam] = None,
+        lag: Optional[int] = None,
+    ) -> CALL_TYPE:
+        """Fetch Delphi's COVID-19 Surveillance Streams"""
+        return self.call(geo_type, geo_values, time_values, as_of, issues, lag)
+
+
+@dataclass
+class DataSource(Generic[CALL_TYPE]):
+    """
+    represents a COVIDcast data source
+    """
+
+    _create_call: InitVar[Callable[[Mapping[str, Union[None, EpiRangeLike, Iterable[EpiRangeLike]]]], CALL_TYPE]]
+
+    source: str
+    db_source: str
+    name: str
+    description: str
+    reference_signal: str
+    license: Optional[str] = None
+    link: Sequence[WebLink] = field(default_factory=list)
+    dua: Optional[str] = None
+
+    signals: Sequence[DataSignal] = field(default_factory=list)
+
+    def __post_init__(
+        self, _create_call: Callable[[Mapping[str, Union[None, EpiRangeLike, Iterable[EpiRangeLike]]]], CALL_TYPE]
+    ) -> None:
+        self.link = [WebLink(alt=l["alt"], href=l["href"]) if isinstance(l, dict) else l for l in self.link]
+        signal_fields = fields(DataSignal)
+        self.signals = [
+            DataSignal(_create_call=_create_call, **_limit_fields(s, signal_fields)) if isinstance(s, dict) else s
+            for s in self.signals
+        ]
+
+    @staticmethod
+    def to_df(sources: Iterable["DataSource"]) -> DataFrame:
+        df = DataFrame(
+            sources,
+            columns=["source", "name", "description", "reference_signal", "license", "dua"],
+        )
+        df["signals"] = [",".join(ss.signal for ss in s.signals) for s in sources]
+        return df.set_index("source")
+
+    def get_signal(self, signal: str) -> Optional[DataSignal]:
+        return next((s for s in self.signals if s.signal == signal), None)
+
+    @cached_property
+    def signal_df(self) -> DataFrame:
+        return DataSignal.to_df(self.signals)
+
+
+@dataclass
+class CovidcastDataSources(Generic[CALL_TYPE]):
+    """
+    COVIDcast data source helper
+    """
+
+    sources: Sequence[DataSource[CALL_TYPE]]
+    _source_by_name: Dict[str, DataSource[CALL_TYPE]] = field(init=False, default_factory=dict)
+    _signals_by_key: OrderedDict[Tuple[str, str], DataSignal[CALL_TYPE]] = field(
+        init=False, default_factory=OrderedDict
+    )
+
+    _create_call: Callable[[Mapping[str, Union[None, EpiRangeLike, Iterable[EpiRangeLike]]]], CALL_TYPE]
+
+    def __post_init__(self) -> None:
+        self._source_by_name = {s.source: s for s in self.sources}
+        for source in self.sources:
+            for signal in source.signals:
+                self._signals_by_key[signal.key] = signal
+
+    def get_source(self, source: str) -> Optional[DataSource[CALL_TYPE]]:
+        return self._source_by_name.get(source)
+
+    @property
+    def source_names(self) -> Iterable[str]:
+        return (s.source for s in self.sources)
+
+    @cached_property
+    def source_df(self) -> DataFrame:
+        return DataSource.to_df(self.sources)
+
+    @property
+    def signals(self) -> Iterable[DataSignal[CALL_TYPE]]:
+        return self._signals_by_key.values()
+
+    @cached_property
+    def signal_df(self) -> DataFrame:
+        return DataSignal.to_df(self.signals)
+
+    def get_signal(self, source: str, signal: str) -> Optional[DataSignal[CALL_TYPE]]:
+        return self._signals_by_key.get((source, signal))
+
+    @property
+    def signal_names(self) -> Iterable[Tuple[str, str]]:
+        return self._signals_by_key.keys()
+
+    def __iter__(self) -> Iterable[DataSource[CALL_TYPE]]:
+        return iter(self.sources)
+
+    @overload
+    def __getitem__(self, source: str) -> DataSource[CALL_TYPE]:
+        ...
+
+    @overload
+    def __getitem__(self, source_signal: Tuple[str, str]) -> DataSignal[CALL_TYPE]:
+        ...
+
+    def __getitem__(
+        self, source_signal: Union[str, Tuple[str, str]]
+    ) -> Union[DataSource[CALL_TYPE], DataSignal[CALL_TYPE]]:
+        if isinstance(source_signal, str):
+            r = self.get_source(source_signal)
+            assert r is not None
+            return r
+        s = self.get_signal(source_signal[0], source_signal[1])
+        assert s is not None
+        return s
+
+    @staticmethod
+    def create(
+        meta: List[Dict],
+        create_call: Callable[[Mapping[str, Union[None, EpiRangeLike, Iterable[EpiRangeLike]]]], CALL_TYPE],
+    ) -> "CovidcastDataSources":
+        source_fields = fields(DataSource)
+        sources = [DataSource(_create_call=create_call, **_limit_fields(k, source_fields)) for k in meta]
+        return CovidcastDataSources(sources, create_call)