feat: add some syntax examples

examples/00_syntax_prototype/01_simple_types.py

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+# type: ignore
+# ruff: disable[F821]
+from __future__ import annotations
+
+# A simple data-frame with different column of various simple types
+# Columns can be named and/or typed
+df: Frame[
+    verified: bool,
+    birth_year: int,
+    height: float,
+    name: str,
+    date: datetime,
+    float,  # unnamed
+    unknown: _,  # untyped
+    _  # unnamed and untyped
+]

examples/00_syntax_prototype/02_custom_types.midas

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+// Simple custom type derived from floats
+type Latitude<float>
+type Longitude<float>
+
+// Complex custom type, containing two values accessible through properties
+type GeoLocation<Latitude, Longitude> {
+    lat: Latitude
+    lon: Longitude
+}
+
+type LatitudeDiff<float>
+type LongitudeDiff<float>
+
+// Simple operation defined on our custom types
+op <Latitude> - <Latitude> = <LatitudeDiff>
+op <Longitude> - <Longitude> = <LongitudeDiff>
+
+// Simple custom type with a constraint
+type Age<int + (0 <= _ < 150)>
+
+// Predefined custom constraints that can be referenced in other definitions
+constraint Positive = _ >= 0
+constraint StrictlyPositive = _ > 0
+constraint Even = _ % 2 == 0

examples/00_syntax_prototype/02_custom_types.py

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+# type: ignore
+# ruff: disable[F821]
+from __future__ import annotations
+
+# Prototype of custom type import to use valid Python syntax
+import midas
+midas.using("02_custom_types.midas")
+
+# A data-frame using a custom type
+df: Frame[
+    location: GeoLocation
+]
+
+# Properties of a type can be used on a column of that type
+lat: Column[GeoLocation] = df["location"].lat
+lon: Column[GeoLocation] = df["location"].lon
+
+# Unregistered operations between types are not permitted
+lat + lon  # Invalid operation
+
+# Registered operations are permitted
+lat1: Latitude = lat[0]
+lat2: Latitude = lat[1]
+lat_diff: LatitudeDiff = lat2 - lat1  # Valid operation
+
+# In addition to the type, a column can have one or more constraints, either defined inline or in a separate file
+df2: Frame[
+    age: int + (_ >= 0),
+    height: float + (_ >= 0),
+]
+df2_bis: Frame[
+    age: int + Positive,
+    height: float + Positive,
+]