Test suite hygiene (#1739)

Author: maximlt

doc/gallery/interactivity/app_bind.ipynb

@@ -23,13 +23,13 @@
     "df = hvplot.sampledata.penguins(\"pandas\").dropna()\n",
     "\n",
     "species_widget = pn.widgets.Select(\n",
-    "    name='Species',\n",
+    "    label='Species',\n",
     "    options=list(df['species'].unique()),\n",
     "    width=200,\n",
     ")\n",
     "\n",
     "mass_widget = pn.widgets.IntSlider(\n",
-    "    name='Min Body Mass (g)',\n",
+    "    label='Min Body Mass (g)',\n",
     "    start=int(df['body_mass_g'].min()),\n",
     "    end=int(df['body_mass_g'].max()),\n",
     "    step=100,\n",

doc/gallery/interactivity/app_rx.ipynb

@@ -26,11 +26,11 @@
     "df = pd.DataFrame({'x': x})\n",
     "\n",
     "amp_slider = pn.widgets.FloatSlider(\n",
-    "    name='Amplitude', start=-5.0, end=5.0,\n",
+    "    label='Amplitude', start=-5.0, end=5.0,\n",
     "    step=0.1, value=1.0, width=200,\n",
     ")\n",
     "freq_slider = pn.widgets.FloatSlider(\n",
-    "    name='Frequency', start=0.1, end=5.1,\n",
+    "    label='Frequency', start=0.1, end=5.1,\n",
     "    step=0.1, value=1.0, width=200,\n",
     ")\n",
     "\n",

doc/index.md

@@ -332,8 +332,8 @@ import hvplot.pandas
 import panel as pn
 from bokeh.sampledata.penguins import data as df
 
-w_sex = pn.widgets.MultiSelect(name='Sex', value=['MALE'], options=['MALE', 'FEMALE'])
-w_body_mass = pn.widgets.FloatSlider(name='Min body mass', start=2700, end=6300, step=50)
+w_sex = pn.widgets.MultiSelect(label='Sex', value=['MALE'], options=['MALE', 'FEMALE'])
+w_body_mass = pn.widgets.FloatSlider(label='Min body mass', start=2700, end=6300, step=50)
 
 dfi = df.interactive(loc='left')
 dfi.loc[(dfi['sex'].isin(w_sex)) & (dfi['body_mass_g'] > w_body_mass)]['bill_length_mm'].describe()
@@ -352,7 +352,7 @@ import hvplot.xarray
 import panel as pn
 import xarray as xr
 
-w_time = pn.widgets.IntSlider(name='time', start=0, end=10)
+w_time = pn.widgets.IntSlider(label='time', start=0, end=10)
 
 da = xr.tutorial.open_dataset('air_temperature').air
 da.interactive.isel(time=w_time).mean().item() - da.mean().item()
@@ -375,8 +375,8 @@ import panel as pn
 import xarray as xr
 
 da = xr.tutorial.open_dataset('air_temperature').air
-w_quantile = pn.widgets.FloatSlider(name='quantile', start=0, end=1)
-w_time = pn.widgets.IntSlider(name='time', start=0, end=10)
+w_quantile = pn.widgets.FloatSlider(label='quantile', start=0, end=1)
+w_time = pn.widgets.IntSlider(label='time', start=0, end=10)
 
 da.interactive(loc='left') \
 .isel(time=w_time) \

doc/tutorials/getting_started.ipynb

@@ -762,8 +762,8 @@
    "source": [
     "import panel as pn\n",
     "\n",
-    "w_latitude = pn.widgets.DiscreteSlider(name='Latitude', options=list(air.lat.values))\n",
-    "w_rolling_window = pn.widgets.RadioButtonGroup(name='Rolling window', options=['1D', '7D', '30D'])"
+    "w_latitude = pn.widgets.DiscreteSlider(label='Latitude', options=list(air.lat.values))\n",
+    "w_rolling_window = pn.widgets.RadioButtonGroup(label='Rolling window', options=['1D', '7D', '30D'])"
    ]
   },
   {

doc/user_guide/Interactive.ipynb

@@ -73,7 +73,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "slider = pnw.IntSlider(name='time', start=0, end=10)\n",
+    "slider = pnw.IntSlider(label='time', start=0, end=10)\n",
     "\n",
     "ds.air.interactive(width=800).isel(time=slider)"
    ]
@@ -149,7 +149,7 @@
    "source": [
     "from bokeh import sampledata\n",
     "\n",
-    "ticker = pn.widgets.Select(options=['AAPL', 'IBM', 'GOOG', 'MSFT'], name='Ticker')\n",
+    "ticker = pn.widgets.Select(options=['AAPL', 'IBM', 'GOOG', 'MSFT'], label='Ticker')\n",
     "\n",
     "def stock_df(ticker):\n",
     "    df = pd.DataFrame(getattr(sampledata.stocks, ticker))\n",
@@ -176,7 +176,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ticker = pn.widgets.Select(options=['AAPL', 'IBM', 'GOOG', 'MSFT'], name='Ticker')\n",
+    "ticker = pn.widgets.Select(options=['AAPL', 'IBM', 'GOOG', 'MSFT'], label='Ticker')\n",
     "\n",
     "def stock_df(ticker):\n",
     "    df = pd.DataFrame(getattr(sampledata.stocks, ticker))\n",
@@ -261,7 +261,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "time = pnw.Player(name='time', start=0, end=10, loop_policy='loop', interval=100)\n",
+    "time = pnw.Player(label='time', start=0, end=10, loop_policy='loop', interval=100)\n",
     "\n",
     "ds.air.interactive(loc='bottom').isel(time=time).plot()"
    ]
@@ -286,7 +286,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "slider = pnw.FloatSlider(name='quantile', start=0, end=1)\n",
+    "slider = pnw.FloatSlider(label='quantile', start=0, end=1)\n",
     "\n",
     "ds.air.interactive.quantile(slider, dim='time').hvplot(data_aspect=1)"
    ]
@@ -304,7 +304,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "q = pnw.FloatSlider(name='quantile', start=0, end=1)\n",
+    "q = pnw.FloatSlider(label='quantile', start=0, end=1)\n",
     "\n",
     "(ds.air.interactive(loc='left')\n",
     " .sel(time=pnw.DiscreteSlider)\n",
@@ -371,7 +371,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "slider = pnw.IntSlider(name='time', start=0, end=10)\n",
+    "slider = pnw.IntSlider(label='time', start=0, end=10)\n",
     "baseline = ds.air.mean().item()\n",
     "baseline"
    ]
@@ -398,8 +398,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "slider = pnw.IntSlider(name='time',   start=0, end=10)\n",
-    "offset = pnw.IntSlider(name='offset', start=0, end=500)\n",
+    "slider = pnw.IntSlider(label='time',   start=0, end=10)\n",
+    "offset = pnw.IntSlider(label='offset', start=0, end=500)\n",
     "\n",
     "ds.air.interactive.isel(time=slider).mean().item() + offset"
    ]

doc/user_guide/Widgets.ipynb

@@ -103,9 +103,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "x = pn.widgets.Select(name='x', options=['sepal_width', 'petal_width'])\n",
-    "y = pn.widgets.Select(name='y', options=['sepal_length', 'petal_length'])\n",
-    "kind = pn.widgets.Select(name='kind', value='scatter', options=['bivariate', 'scatter'])\n",
+    "x = pn.widgets.Select(label='x', options=['sepal_width', 'petal_width'])\n",
+    "y = pn.widgets.Select(label='y', options=['sepal_length', 'petal_length'])\n",
+    "kind = pn.widgets.Select(label='kind', value='scatter', options=['bivariate', 'scatter'])\n",
     "\n",
     "plot = flowers.hvplot(x=x, y=y, kind=kind, colorbar=False, width=600)\n",
     "pn.Row(pn.WidgetBox(x, y, kind), plot)"
@@ -126,10 +126,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "x = pn.widgets.Select(name='x', options=['sepal_width', 'petal_width'])\n",
-    "y = pn.widgets.Select(name='y', options=['sepal_length', 'petal_length'])\n",
-    "kind = pn.widgets.Select(name='kind', value='scatter', options=['bivariate', 'scatter'])\n",
-    "by_species = pn.widgets.Checkbox(name='By species')\n",
+    "x = pn.widgets.Select(label='x', options=['sepal_width', 'petal_width'])\n",
+    "y = pn.widgets.Select(label='y', options=['sepal_length', 'petal_length'])\n",
+    "kind = pn.widgets.Select(label='kind', value='scatter', options=['bivariate', 'scatter'])\n",
+    "by_species = pn.widgets.Checkbox(label='By species')\n",
     "color = pn.widgets.ColorPicker(value='#ff0000')\n",
     "\n",
     "@pn.depends(by_species, color)\n",

hvplot/__init__.py

@@ -210,8 +210,8 @@ def bind(function, *args, **kwargs):
     >>> import hvplot
     >>> import panel as pn
 
-    >>> alpha = pn.widgets.FloatSlider(value=0.5, start=0, end=1.0, step=0.1, name="Alpha")
-    >>> top = pn.widgets.RadioButtonGroup(value=10, options=[5, 10, 25], name="Top")
+    >>> alpha = pn.widgets.FloatSlider(value=0.5, start=0, end=1.0, step=0.1, label="Alpha")
+    >>> top = pn.widgets.RadioButtonGroup(value=10, options=[5, 10, 25], label="Top")
     >>> interactive_table = (
     ...     hvplot
     ...     .bind(algorithm, alpha=alpha)

hvplot/tests/testinteractive.py

@@ -260,8 +260,8 @@ def test_interactive_pandas_dataframe_hvplot_accessor_dmap_kind_widget(df):
 def test_interactive_with_bound_function_calls():
     df = pd.DataFrame({'species': [1, 1, 1, 2, 2, 2], 'sex': 3 * ['MALE', 'FEMALE']})
 
-    w_species = pn.widgets.Select(name='Species', options=[1, 2])
-    w_sex = pn.widgets.MultiSelect(name='Sex', value=['MALE'], options=['MALE', 'FEMALE'])
+    w_species = pn.widgets.Select(label='Species', options=[1, 2])
+    w_sex = pn.widgets.MultiSelect(label='Sex', value=['MALE'], options=['MALE', 'FEMALE'])
 
     def load_data(species, watch=True):
         if watch:

hvplot/tests/testpanel.py

@@ -33,10 +33,10 @@ def setUp(self):
         self.cols = list(self.flowers.columns[:-1])
 
     def test_using_explicit_widgets_works(self):
-        x = pn.widgets.Select(name='x', value='sepal_length', options=self.cols)
-        y = pn.widgets.Select(name='y', value='sepal_width', options=self.cols)
-        kind = pn.widgets.Select(name='kind', value='scatter', options=['bivariate', 'scatter'])
-        by_species = pn.widgets.Checkbox(name='By species')
+        x = pn.widgets.Select(label='x', value='sepal_length', options=self.cols)
+        y = pn.widgets.Select(label='y', value='sepal_width', options=self.cols)
+        kind = pn.widgets.Select(label='kind', value='scatter', options=['bivariate', 'scatter'])
+        by_species = pn.widgets.Checkbox(label='By species')
         color = pn.widgets.ColorPicker(value='#ff0000')
 
         @pn.depends(by_species.param.value, color.param.value)
@@ -53,8 +53,8 @@ def test_casting_widgets_to_different_classes(self):
         assert len(look_for_class(pane, pn.widgets.DiscreteSlider)) == 1
 
     def test_using_explicit_widgets_with_groupby_does_not_raise_error(self):
-        x = pn.widgets.Select(name='x', value='sepal_length', options=self.cols)
-        y = pn.widgets.Select(name='y', value='sepal_width', options=self.cols)
+        x = pn.widgets.Select(label='x', value='sepal_length', options=self.cols)
+        y = pn.widgets.Select(label='y', value='sepal_width', options=self.cols)
 
         pane = self.flowers.hvplot(x, y, groupby='species')
         assert isinstance(pane, pn.param.ParamFunction)

hvplot/tests/testutil.py

@@ -202,9 +202,9 @@ def test_dynamic_and_static(self):
 
         x = 'sepal_width'
         y = pn.widgets.Select(
-            name='y', value='sepal_length', options=['sepal_length', 'petal_length']
+            label='y', value='sepal_length', options=['sepal_length', 'petal_length']
         )
-        kind = pn.widgets.Select(name='kind', value='scatter', options=['bivariate', 'scatter'])
+        kind = pn.widgets.Select(label='kind', value='scatter', options=['bivariate', 'scatter'])
 
         dynamic, arg_deps, _arg_names = process_dynamic_args(x, y, kind)
         assert 'x' not in dynamic
@@ -230,7 +230,7 @@ def test_fn_kwds(self):
         x = 'sepal_length'
         y = 'sepal_width'
         kind = 'scatter'
-        by_species = pn.widgets.Checkbox(name='By species')
+        by_species = pn.widgets.Checkbox(label='By species')
         color = pn.widgets.ColorPicker(value='#ff0000')
 
         @pn.depends(by_species.param.value, color.param.value)
@@ -255,7 +255,7 @@ def test_check_crs():
 @pytest.mark.parametrize(
     'input',
     [
-        '+init=epsg:26911',
+        'epsg:26911',
         'PlateCarree',
         'epsg:6933',
         6933,
@@ -290,7 +290,7 @@ def test_process_crs_pyproj_proj():
         4326,
         'epsg:4326',
         'EPSG: 4326',
-        '+init=epsg:4326',
+        'epsg:4326',
         # Created with pyproj.CRS("EPSG:4326").to_wkt()
         'GEOGCRS["WGS 84",ENSEMBLE["World Geodetic System 1984 ensemble",MEMBER["World Geodetic System 1984 (Transit)"],MEMBER["World Geodetic System 1984 (G730)"],MEMBER["World Geodetic System 1984 (G873)"],MEMBER["World Geodetic System 1984 (G1150)"],MEMBER["World Geodetic System 1984 (G1674)"],MEMBER["World Geodetic System 1984 (G1762)"],MEMBER["World Geodetic System 1984 (G2139)"],ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ENSEMBLEACCURACY[2.0]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433]],CS[ellipsoidal,2],AXIS["geodetic latitude (Lat)",north,ORDER[1],ANGLEUNIT["degree",0.0174532925199433]],AXIS["geodetic longitude (Lon)",east,ORDER[2],ANGLEUNIT["degree",0.0174532925199433]],USAGE[SCOPE["Horizontal component of 3D system."],AREA["World."],BBOX[-90,-180,90,180]],ID["EPSG",4326]]',  # noqa: E501
     ],
@@ -310,7 +310,7 @@ def test_process_crs_platecarree(input):
         3857,
         'epsg:3857',
         'EPSG: 3857',
-        '+init=epsg:3857',
+        'epsg:3857',
         'PROJCS["WGS 84 / Pseudo-Mercator",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Mercator_1SP"],PARAMETER["central_meridian",0],PARAMETER["scale_factor",1],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],EXTENSION["PROJ4","+proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs"],AUTHORITY["EPSG","3857"]]',  # noqa: E501
         # Created with pyproj.CRS("EPSG:3857").to_wkt()
         'PROJCRS["WGS 84 / Pseudo-Mercator",BASEGEOGCRS["WGS 84",ENSEMBLE["World Geodetic System 1984 ensemble",MEMBER["World Geodetic System 1984 (Transit)"],MEMBER["World Geodetic System 1984 (G730)"],MEMBER["World Geodetic System 1984 (G873)"],MEMBER["World Geodetic System 1984 (G1150)"],MEMBER["World Geodetic System 1984 (G1674)"],MEMBER["World Geodetic System 1984 (G1762)"],MEMBER["World Geodetic System 1984 (G2139)"],ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ENSEMBLEACCURACY[2.0]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433]],ID["EPSG",4326]],CONVERSION["Popular Visualisation Pseudo-Mercator",METHOD["Popular Visualisation Pseudo Mercator",ID["EPSG",1024]],PARAMETER["Latitude of natural origin",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["easting (X)",east,ORDER[1],LENGTHUNIT["metre",1]],AXIS["northing (Y)",north,ORDER[2],LENGTHUNIT["metre",1]],USAGE[SCOPE["Web mapping and visualisation."],AREA["World between 85.06°S and 85.06°N."],BBOX[-85.06,-180,85.06,180]],ID["EPSG",3857]]',  # noqa: E501