chore: internal cleanup (#31)

requirements.txt

@@ -1,3 +1,2 @@
 # Used by streamlit deployment
--e .
-streamlit>=1.34.0
+-e ."[streamlit]"

sksmithy/_static/description.md

@@ -1,12 +1,27 @@
+# Description
+
 Writing scikit-learn compatible estimators might be harder than expected.
 
-While everyone knows about the `fit` and `predict`, there are other behaviours, methods and attributes that scikit-learn might be expecting from your estimator depending on:
+While everyone knows about the `fit` and `predict`, there are other behaviours, methods and attributes that
+scikit-learn might be expecting from your estimator depending on:
 
 - The type of estimator you're writing.
 - The signature of the estimator.
 - The signature of the `.fit(...)` method.
 
-Scikit-learn Smithy to the rescue: this tool aims to help you crafting your own estimator by asking a few questions about it, and then generating the boilerplate code.
+Scikit-learn Smithy to the rescue: this tool aims to help you crafting your own estimator by asking a few
+questions about it, and then generating the boilerplate code.
+
+In this way you will be able to fully focus on the core implementation logic, and not on nitty-gritty details
+of the scikit-learn API.
+
+## Sanity check
+
+Once the core logic is implemented, the estimator should be ready to test against the _somewhat official_
+[`parametrize_with_checks`](https://scikit-learn.org/dev/modules/generated/sklearn.utils.estimator_checks.parametrize_with_checks.html#sklearn.utils.estimator_checks.parametrize_with_checks)
+pytest compatible decorator.
+
+## Official guide
 
-In this way you will be able to fully focus on the core implementation logic, and not on nitty-gritty details of the
-scikit-learn API.
+Scikit-learn documentation on how to
+[develop estimators](https://scikit-learn.org/dev/developers/develop.html#developing-scikit-learn-estimators).

sksmithy/_static/tui.tcss

@@ -115,7 +115,3 @@ OptionGroup {
     height: 1fr;
     border-right: vkey $background;
 }
-
-Message {
-    margin: 0 1;
-}

sksmithy/app.py

@@ -1,5 +1,6 @@
 import re
 import time
+from importlib import resources
 from importlib.metadata import version
 
 from result import Err, Ok
@@ -32,6 +33,8 @@
 else:  # pragma: no cover
     import streamlit as st
 
+SIDEBAR_MSG: str = (resources.files("sksmithy") / "_static" / "description.md").read_text()
+
 st.set_page_config(
     page_title="Smithy",
     page_icon="⚒️",
@@ -52,35 +55,7 @@
 st.markdown("## Forge your own scikit-learn compatible estimator")
 
 with st.sidebar:
-    st.markdown("""
-        # Description
-
-        Writing scikit-learn compatible estimators might be harder than expected.
-
-        While everyone knows about the `fit` and `predict`, there are other behaviours, methods and attributes that
-        scikit-learn might be expecting from your estimator depending on:
-
-        - The type of estimator you're writing.
-        - The signature of the estimator.
-        - The signature of the `.fit(...)` method.
-
-        Scikit-learn Smithy to the rescue: this tool aims to help you crafting your own estimator by asking a few
-        questions about it, and then generating the boilerplate code.
-
-        In this way you will be able to fully focus on the core implementation logic, and not on nitty-gritty details
-        of the scikit-learn API.
-
-        ## Sanity check
-
-        Once the core logic is implemented, the estimator should be ready to test against the _somewhat official_
-        [`parametrize_with_checks`](https://scikit-learn.org/dev/modules/generated/sklearn.utils.estimator_checks.parametrize_with_checks.html#sklearn.utils.estimator_checks.parametrize_with_checks)
-        pytest compatible decorator.
-
-        ## Official guide
-
-        Scikit-learn documentation on how to
-        [develop estimators](https://scikit-learn.org/dev/developers/develop.html#developing-scikit-learn-estimators).
-    """)
+    st.markdown(SIDEBAR_MSG)
 
 sample_weights = False
 linear = False

sksmithy/tui/_components.py

@@ -1,13 +1,13 @@
 import sys
-from importlib import metadata, resources
+import webbrowser
+from importlib import resources
 from pathlib import Path
 
 from result import Err, Ok
-from rich.console import RenderableType
 from textual import on
 from textual.app import ComposeResult
 from textual.containers import Container, Grid, Horizontal, ScrollableContainer
-from textual.widgets import Button, Collapsible, Input, Select, Static, Switch, TextArea
+from textual.widgets import Button, Collapsible, Input, Markdown, Select, Static, Switch, TextArea
 
 from sksmithy._models import EstimatorType
 from sksmithy._parsers import check_duplicates, name_parser, params_parser
@@ -336,25 +336,14 @@ class ForgeRow(Grid):
     """Row grid for forge."""
 
 
-class Title(Static):
-    pass
-
-
 class OptionGroup(ScrollableContainer):
     pass
 
 
-class Message(Static):
-    pass
-
-
-class Version(Static):
-    def render(self: Self) -> RenderableType:
-        return f"Version: [b]{metadata.version('sklearn-smithy')}"
-
-
 class Sidebar(Container):
     def compose(self: Self) -> ComposeResult:
-        yield Title("Description")
-        yield OptionGroup(Message(SIDEBAR_MSG), Version())
-        yield Version()
+        yield OptionGroup(Markdown(SIDEBAR_MSG))
+
+    def on_markdown_link_clicked(self: Self, event: Markdown.LinkClicked) -> None:
+        # Relevant discussion: https://github.com/Textualize/textual/discussions/3668
+        webbrowser.open_new_tab(event.href)

sksmithy/tui/_tui.py

@@ -1,5 +1,5 @@
 import sys
-from importlib import resources
+from importlib import metadata, resources
 from typing import ClassVar
 
 from textual.app import App, ComposeResult
@@ -29,12 +29,6 @@
     from typing_extensions import Self
 
 
-TEXT = """\
-import pandas as pd
-import numpy as np
-"""
-
-
 class ForgeTUI(App):
     """Textual app to forge scikit-learn compatible estimators."""
 
@@ -61,7 +55,7 @@ def on_mount(self: Self) -> None:
     def compose(self: Self) -> ComposeResult:
         """Create child widgets for the app."""
         yield Container(
-            Header(),
+            Header(icon=f"v{metadata.version('sklearn-smithy')}"),
             ScrollableContainer(
                 Horizontal(Name(), Estimator()),
                 Horizontal(Required(), Optional()),