[Issue-1501] new suite output design (#1627)

* new suite output design

deepchecks/core/condition.py

@@ -115,8 +115,11 @@ def priority(self) -> int:
 
     def is_pass(self, fail_if_warning=True) -> bool:
         """Return true if the condition has passed."""
-        passed_categories = [ConditionCategory.PASS] if fail_if_warning else \
-            [ConditionCategory.PASS, ConditionCategory.WARN]
+        passed_categories = (
+            (ConditionCategory.PASS,)
+            if fail_if_warning
+            else (ConditionCategory.PASS, ConditionCategory.WARN)
+        )
         return self.category in passed_categories
 
     def get_icon(self):

deepchecks/core/serialization/common.py

@@ -31,11 +31,14 @@
 from plotly.offline.offline import get_plotlyjs
 
 from deepchecks.core import check_result as check_types
+from deepchecks.core import errors
 from deepchecks.utils.dataframes import un_numpy
 from deepchecks.utils.strings import get_ellipsis
 
 __all__ = [
     'aggregate_conditions',
+    'create_results_dataframe',
+    'create_failures_dataframe',
     'form_output_anchor',
     'Html',
     'normalize_widget_style',
@@ -105,7 +108,7 @@ def normalize_value(value: object) -> t.Any:
 
 
 def aggregate_conditions(
-    check_results: t.Union['check_types.CheckResult', t.List['check_types.CheckResult']],
+    check_results: t.Union['check_types.CheckResult', t.Sequence['check_types.CheckResult']],
     max_info_len: int = 3000,
     include_icon: bool = True,
     include_check_name: bool = False,
@@ -115,7 +118,7 @@ def aggregate_conditions(
 
     Parameters
     ----------
-    check_results : Union['CheckResult', List['CheckResult']]
+    check_results : Union['CheckResult', Sequence['CheckResult']]
         check results to show conditions of.
     max_info_len : int
         max length of the additional info.
@@ -124,7 +127,9 @@ def aggregate_conditions(
     include_check_name : bool, default False
         whether to include check name into dataframe or not
     output_id : str
-        the unique id to append for the check names to create links (won't create links if None/empty).
+        unique identifier of the output, it will be used to
+        form a link (html '<a></a>' tag) to the check result
+        full output
 
     Returns
     -------
@@ -176,6 +181,87 @@ def aggregate_conditions(
         return df.style.hide_index()
 
 
+def create_results_dataframe(
+    results: t.Sequence['check_types.CheckResult'],
+    output_id: t.Optional[str] = None,
+) -> pd.DataFrame:
+    """Create dataframe with check results.
+
+    Parameters
+    ----------
+    results : Sequence['CheckResult']
+        check results
+    output_id : str
+        unique identifier of the output, it will be used to
+        form a link (html '<a></a>' tag) to the check result
+        full output
+
+    Returns
+    -------
+    pd.Dataframe:
+        the condition table.
+    """
+    data = []
+
+    for check_result in results:
+        check_header = check_result.get_header()
+        if output_id and check_result.display:
+            href = f'href="#{check_result.get_check_id(output_id)}"'
+            header = f'<a {href}>{check_header}</a>'
+        else:
+            header = check_header
+        summary = check_result.get_metadata(with_doc_link=True)['summary']
+        data.append([header, summary])
+
+    return pd.DataFrame(
+        data=data,
+        columns=['Check', 'Summary']
+    )
+
+
+def create_failures_dataframe(
+    failures: t.Sequence[t.Union['check_types.CheckFailure', 'check_types.CheckResult']]
+) -> pd.DataFrame:
+    """Create dataframe with check failures.
+
+    Parameters
+    ----------
+    failures : Sequence[Union[CheckFailure, CheckResult]]
+        check failures
+
+    Returns
+    -------
+    pd.Dataframe:
+        the condition table.
+    """
+    data = []
+
+    for it in failures:
+        if isinstance(it, check_types.CheckResult):
+            data.append([it.get_header(), 'Nothing found', 2])
+        elif isinstance(it, check_types.CheckFailure):
+            message = (
+                it.exception.html
+                if isinstance(it.exception, errors.DeepchecksBaseError)
+                else str(it.exception)
+            )
+            error_types = (
+                errors.DatasetValidationError,
+                errors.ModelValidationError,
+                errors.DeepchecksProcessError,
+            )
+            if isinstance(it.exception, error_types):
+                message = f'{type(it.exception).__name__}: {message}'
+            data.append((it.header, message, 1))
+        else:
+            raise TypeError(f'Unknown result type - {type(it).__name__}')
+
+    df = pd.DataFrame(data=data, columns=['Check', 'Reason', 'priority'])
+    df.sort_values(by=['priority'], inplace=True)
+    df.drop('priority', axis=1, inplace=True)
+    return df
+
+
 def requirejs_script(connected: bool = True):
     """Return requirejs script tag.
 

deepchecks/core/serialization/suite_result/html.py

@@ -13,16 +13,13 @@
 import typing as t
 import warnings
 
-import pandas as pd
-
 from deepchecks.core import check_result as check_types
-from deepchecks.core import errors, suite
-from deepchecks.core.errors import DeepchecksBaseError
+from deepchecks.core import suite
 from deepchecks.core.serialization.abc import HtmlSerializer
 from deepchecks.core.serialization.check_result.html import CheckResultSection
 from deepchecks.core.serialization.check_result.html import CheckResultSerializer as CheckResultHtmlSerializer
-from deepchecks.core.serialization.common import (Html, aggregate_conditions, form_output_anchor, plotlyjs_script,
-                                                  requirejs_script)
+from deepchecks.core.serialization.common import (Html, aggregate_conditions, create_failures_dataframe,
+                                                  form_output_anchor, plotlyjs_script, requirejs_script)
 from deepchecks.core.serialization.dataframe.html import DataFrameSerializer as DataFrameHtmlSerializer
 
 __all__ = ['SuiteResultSerializer']
@@ -332,26 +329,7 @@ def prepare_failures_list(self) -> str:
         if not results:
             return ''
 
-        data = []  # type List[Tuple[check-header:str, message:str, priority:int]]
-
-        for it in results:
-            if not isinstance(it, check_types.CheckFailure):
-                data.append([it.get_header(), 'Nothing found', 2])
-            else:
-                message = it.exception.html if isinstance(it.exception, DeepchecksBaseError) else str(it.exception)
-                error_types = (
-                    errors.DatasetValidationError,
-                    errors.ModelValidationError,
-                    errors.DeepchecksProcessError,
-                )
-                if isinstance(it.exception, error_types):
-                    message = f'{type(it.exception).__name__}: {message}'
-
-                data.append((it.header, message, 1))
-
-        df = pd.DataFrame(data=data, columns=['Check', 'Reason', 'priority'])
-        df.sort_values(by=['priority'], inplace=True)
-        df.drop('priority', axis=1, inplace=True)
+        df = create_failures_dataframe(results)
 
         with warnings.catch_warnings():
             warnings.simplefilter(action='ignore', category=FutureWarning)