♻️ Full re-work on internals to use pydantic models

🧹 Internal evolution to update the code style to the latest versions and de facto standards, with better typing, input validation, and serialization.
Hardly any new features (.make_svg()), but some bug fixes.

BREAKING-CHANGE: Now the chart creation from a configuration key/file/dict is done with PsychroChart.create(config), instead of old PsychroChart(config)

Changes

• 🏗️ Add pydantic models for chart + annotations styling and config, for better (de)serialization and parameter validation.

  New models are:

  • CurveStyle, LabelStyle, TickStyle, ZoneStyle := to parse & handle defaults for matplotlib styling parameters
  • ChartConfig for the full chart configuration, including sub-models ChartFigure, ChartLimits, and ChartParams, to mirror the old obfuscated config, with the same default values as before
  • ChartPoint and ChartSeries for styled single-point or array-data annotations
  • ChartLine for styled connectors between named points (now without outline 'marker' by default)
  • ChartArea for styled convex areas delimited by a list of named points
  • ChartAnnots as container for all of the above
  • ChartZone (and ChartZones as a list), for styled fixed areas (like the default winter/summer comfort zones)

• ♻️ Evolve load methods to parse inputs into pydantic models with near-zero (expected 🤞) breaks when reading old data

• 💥 Rework PsychroChart class to work with pydantic PsychroChartModel. As the chart is now a pydantic model, there is a chart.json(...) method, and loading from serialized data is available with PsychroChart.parse_file( / .validate( / etc 🤩

• ✨ Add .make_svg() method to produce a SVG file as text, and evolve .save(...) with optional canvas_cls: Type[FigureCanvasBase], to select kind of matplotlib canvas where to print the chart

• ✨ Support file creation in subfolders with chart.save(dest)

• 🚚 rsc: Deterministic SVG output in tests, and README images without date metadata

• ✅ tests: Adapt API changes in unit tests, remove usages of unittest.TestCase, add new tests for pydantic models, annotations, and serialization methods.