Update AutoMLSearch init Pipeline logging

docs/source/release_notes.rst

@@ -22,6 +22,7 @@ Release Notes
         * Set minimum required version for for pyzmq, colorama, and docutils :pr:`2254`
         * Changed BaseSampler to return None instead of y :pr:`2272`
     * Changes
+        * Updated logging information in ``AutoMLSearch.__init__`` to clarify pipeline generation :pr:`2263`
         * Removed ensemble split and indices in ``AutoMLSearch`` :pr:`2260`
         * Updated pipeline ``repr()`` and ``generate_pipeline_code`` to return pipeline instances without generating custom pipeline class :pr:`2227`
     * Documentation Changes

evalml/automl/automl_search.py

@@ -380,6 +380,8 @@ def __init__(self,
 
         if self.allowed_pipelines == []:
             raise ValueError("No allowed pipelines to search")
+
+        logger.info(f"{len(self.allowed_pipelines)} pipelines ready for search.")
         check_all_pipeline_names_unique(self.allowed_pipelines)
 
         run_ensembling = self.ensembling

evalml/tests/utils_tests/test_logger.py

@@ -6,6 +6,7 @@
 
 import pytest
 
+from evalml import AutoMLSearch
 from evalml.utils.logger import (
     get_logger,
     log_subtitle,
@@ -210,3 +211,24 @@ def test_time_elapsed(mock_time, time_passed, answer):
     mock_time.return_value = time_passed
     time = time_elapsed(start_time=0)
     assert time == answer
+
+
+@pytest.mark.parametrize("type_, allowed_families, number_, number_min_dep", [("binary", None, 8, 5), ("multiclass", 2, 2, 2), ("regression", 3, 3, 3)])
+def test_pipeline_count(type_, allowed_families, number_, number_min_dep, X_y_binary, X_y_multi, X_y_regression, caplog, has_minimal_dependencies):
+    if type_ == 'binary':
+        X, y = X_y_binary
+    elif type_ == 'multiclass':
+        X, y = X_y_multi
+    else:
+        X, y = X_y_regression
+    if not allowed_families:
+        _ = AutoMLSearch(X_train=X, y_train=y, problem_type=type_)
+    else:
+        if allowed_families == 2:
+            _ = AutoMLSearch(X_train=X, y_train=y, problem_type=type_, allowed_model_families=['random_forest', 'decision_tree'])
+        elif allowed_families == 3:
+            _ = AutoMLSearch(X_train=X, y_train=y, problem_type=type_, allowed_model_families=['random_forest', 'decision_tree', 'extra_trees'])
+    if has_minimal_dependencies:
+        assert f"{number_min_dep} pipelines ready for search" in caplog.text
+    else:
+        assert f"{number_} pipelines ready for search" in caplog.text