Add disable_maxrows function & make serve() and save() respect data_transformer

altair/vegalite/data.py

@@ -3,15 +3,26 @@
 from ..utils.core import sanitize_dataframe
 from ..utils.data import (
     MaxRowsError, limit_rows, sample, to_csv, to_json, to_values,
-    check_data_type, DataTransformerRegistry
+    check_data_type
 )
+from ..utils.data import DataTransformerRegistry as _DataTransformerRegistry
 
 
 @curry
 def default_data_transformer(data, max_rows=5000):
     return pipe(data, limit_rows(max_rows=max_rows), to_values)
 
 
+class DataTransformerRegistry(_DataTransformerRegistry):
+    def disable_max_rows(self):
+        """Disable the MaxRowsError."""
+        options = self.options
+        if self.active == 'default':
+            options = options.copy()
+            options['max_rows'] = None
+        return self.enable(**options)
+
+
 __all__ = (
     'DataTransformerRegistry',
     'MaxRowsError',

altair/vegalite/v2/tests/test_data.py

@@ -0,0 +1,33 @@
+import os
+
+import pandas as pd
+import pytest
+
+from .. import data as alt
+
+
+@pytest.fixture
+def sample_data():
+    return pd.DataFrame({'x': range(10), 'y': range(10)})
+
+
+def test_disable_max_rows(sample_data):
+    with alt.data_transformers.enable('default', max_rows=5):
+        # Ensure max rows error is raised.
+        with pytest.raises(alt.MaxRowsError):
+            alt.data_transformers.get()(sample_data)
+
+        # Ensure that max rows error is properly disabled.
+        with alt.data_transformers.disable_max_rows():
+            alt.data_transformers.get()(sample_data)
+
+    try:
+        with alt.data_transformers.enable('json'):
+            # Ensure that there is no TypeError for non-max_rows transformers.
+            with alt.data_transformers.disable_max_rows():
+                jsonfile = alt.data_transformers.get()(sample_data)
+    except:
+        jsonfile = {}
+    finally:
+        if jsonfile:
+            os.remove(jsonfile['url'])

altair/vegalite/v3/api.py

@@ -445,9 +445,9 @@ def save(self, fp, format=None, override_data_transformer=True,
             the format to write: one of ['json', 'html', 'png', 'svg'].
             If not specified, the format will be determined from the filename.
         override_data_transformer : boolean (optional)
-            If True (default), then the save action will be done with the
-            default data_transformer with max_rows set to None. If False,
-            then use the currently active data transformer.
+            If True (default), then the save action will be done with
+            the MaxRowsError disabled. If False, then do not change the data
+            transformer.
         scale_factor : float
             For svg or png formats, scale the image by this factor when saving.
             This can be used to control the size or resolution of the output.
@@ -470,7 +470,7 @@ def save(self, fp, format=None, override_data_transformer=True,
         # that save() will succeed even for large datasets that would
         # normally trigger a MaxRowsError
         if override_data_transformer:
-            with data_transformers.enable('default', max_rows=None):
+            with data_transformers.disable_max_rows():
                 result = save(**kwds)
         else:
             result = save(**kwds)

altair/vegalite/v3/tests/test_data.py

@@ -0,0 +1,33 @@
+import os
+
+import pandas as pd
+import pytest
+
+from .. import data as alt
+
+
+@pytest.fixture
+def sample_data():
+    return pd.DataFrame({'x': range(10), 'y': range(10)})
+
+
+def test_disable_max_rows(sample_data):
+    with alt.data_transformers.enable('default', max_rows=5):
+        # Ensure max rows error is raised.
+        with pytest.raises(alt.MaxRowsError):
+            alt.data_transformers.get()(sample_data)
+
+        # Ensure that max rows error is properly disabled.
+        with alt.data_transformers.disable_max_rows():
+            alt.data_transformers.get()(sample_data)
+
+    try:
+        with alt.data_transformers.enable('json'):
+            # Ensure that there is no TypeError for non-max_rows transformers.
+            with alt.data_transformers.disable_max_rows():
+                jsonfile = alt.data_transformers.get()(sample_data)
+    except:
+        jsonfile = {}
+    finally:
+        if jsonfile:
+            os.remove(jsonfile['url'])

doc/user_guide/faq.rst

@@ -144,10 +144,21 @@ error is a way of preventing that.
 
 You can get around it in a few ways:
 
+Disabling MaxRowsError
+~~~~~~~~~~~~~~~~~~~~~~
+If you are certain you would like to embed your dataset within the visualization
+specification, you can disable the ``MaxRows`` check with the following::
+
+    alt.data_transformers.disable_max_rows()
+
+If you choose this route, please be careful: if you are making multiple plots
+with the dataset in a particular notebook, the notebook will grow very large
+and performance may suffer.
+
 Passing Data by URL
 ~~~~~~~~~~~~~~~~~~~
-The preferred solution to working with large datasets is to not embed the data
-in the notebook, but rather pass it to the chart by URL.
+A better solution when working with large datasets is to not embed the data
+in the notebook, but rather store it separately pass it to the chart by URL.
 This not only addresses the issue of large notebooks, but also leads to better
 interactivity performance with large datasets.
 
@@ -199,15 +210,3 @@ And then enable the data transformer::
     alt.data_transformers.enable('data_server')
 
 Note that this may not approach on some cloud-based Jupyter notebook services.
-
-Disabling MaxRows
-~~~~~~~~~~~~~~~~~
-If you are certain you would like to embed your dataset within the visualization
-specification, you can disable the ``MaxRows`` check by modifying the arguments
-to the default data transformer::
-
-    alt.data_transformers.enable(max_rows=None)
-
-If you choose this route, please be careful: if you are making multiple plots
-with the dataset in a particular notebook, the notebook will grow very large
-and performance may suffer.