New options for analyze-tables - refs #544

This change adds three new options and modifies the `analyze_tables` function and `analyze_column` method in the `cli.py` and `db.py` modules respectively. The new options are `common_limit`, `no_most`, and `no_least`.

The `common_limit` option specifies how many common values should be returned by `analyze_column` method, by default it's set to 10. The `no_most` and `no_least` options, when set to True, skip returning the most and least common values, respectively.

The `analyze_tables` function was modified to pass the new options to the `_analyze` method, and the `analyze_column` method in the `db.py` module was modified to use the newly added options. Now, when `analyze_column` is called, it checks if `most_common` or `least_common` options are set to True before running the corresponding query. If the `num_distinct` value is less than or equal to `common_limit`, it doesn't run the least common query. The results from the most and least common queries are sorted before being returned.

sqlite_utils/cli.py

@@ -2639,12 +2639,20 @@ def insert_files(
     help="Specific columns to analyze",
 )
 @click.option("--save", is_flag=True, help="Save results to _analyze_tables table")
+@click.option("--common-limit", type=int, default=10, help="How many common values")
+@click.option("--no-most", is_flag=True, default=False, help="Skip most common values")
+@click.option(
+    "--no-least", is_flag=True, default=False, help="Skip least common values"
+)
 @load_extension_option
 def analyze_tables(
     path,
     tables,
     columns,
     save,
+    common_limit,
+    no_most,
+    no_least,
     load_extension,
 ):
     """Analyze the columns in one or more tables
@@ -2656,10 +2664,10 @@ def analyze_tables(
     """
     db = sqlite_utils.Database(path)
     _load_extensions(db, load_extension)
-    _analyze(db, tables, columns, save)
+    _analyze(db, tables, columns, save, common_limit, no_most, no_least)
 
 
-def _analyze(db, tables, columns, save):
+def _analyze(db, tables, columns, save, common_limit=10, no_most=False, no_least=False):
     if not tables:
         tables = db.table_names()
     todo = []
@@ -2672,7 +2680,12 @@ def _analyze(db, tables, columns, save):
     # Now we now how many we need to do
     for i, (table, column) in enumerate(todo):
         column_details = db[table].analyze_column(
-            column, total_rows=table_counts[table], value_truncate=80
+            column,
+            common_limit=common_limit,
+            total_rows=table_counts[table],
+            value_truncate=80,
+            most_common=not no_most,
+            least_common=not no_least,
         )
         if save:
             db["_analyze_tables_"].insert(

sqlite_utils/db.py

@@ -3419,7 +3419,13 @@ class Table(Queryable):
         self.db.analyze(self.name)
 
     def analyze_column(
-        self, column: str, common_limit: int = 10, value_truncate=None, total_rows=None
+        self,
+        column: str,
+        common_limit: int = 10,
+        value_truncate=None,
+        total_rows=None,
+        most_common: bool = True,
+        least_common: bool = True,
     ) -> "ColumnDetails":
         """
         Return statistics about the specified column.
@@ -3453,36 +3459,38 @@ class Table(Queryable):
         num_distinct = db.execute(
             "select count(distinct [{}]) from [{}]".format(column, table)
         ).fetchone()[0]
-        most_common = None
+        most_common_results = None
-        least_common = None
+        least_common_results = None
         if num_distinct == 1:
             value = db.execute(
                 "select [{}] from [{}] limit 1".format(column, table)
             ).fetchone()[0]
-            most_common = [(truncate(value), total_rows)]
+            most_common_results = [(truncate(value), total_rows)]
         elif num_distinct != total_rows:
-            most_common = [
+            if most_common:
-                (truncate(r[0]), r[1])
+                most_common_results = [
-                for r in db.execute(
-                    "select [{}], count(*) from [{}] group by [{}] order by count(*) desc, [{}] limit {}".format(
-                        column, table, column, column, common_limit
-                    )
-                ).fetchall()
-            ]
-            most_common.sort(key=lambda p: (p[1], p[0]), reverse=True)
-            if num_distinct <= common_limit:
-                # No need to run the query if it will just return the results in revers order
-                least_common = None
-            else:
-                least_common = [
                     (truncate(r[0]), r[1])
                     for r in db.execute(
-                        "select [{}], count(*) from [{}] group by [{}] order by count(*), [{}] desc limit {}".format(
+                        "select [{}], count(*) from [{}] group by [{}] order by count(*) desc, [{}] limit {}".format(
                             column, table, column, column, common_limit
                         )
                     ).fetchall()
                 ]
-                least_common.sort(key=lambda p: (p[1], p[0]))
+                most_common_results.sort(key=lambda p: (p[1], p[0]), reverse=True)
+            if least_common:
+                if num_distinct <= common_limit:
+                    # No need to run the query if it will just return the results in revers order
+                    least_common_results = None
+                else:
+                    least_common_results = [
+                        (truncate(r[0]), r[1])
+                        for r in db.execute(
+                            "select [{}], count(*) from [{}] group by [{}] order by count(*), [{}] desc limit {}".format(
+                                column, table, column, column, common_limit
+                            )
+                        ).fetchall()
+                    ]
+                    least_common_results.sort(key=lambda p: (p[1], p[0]))
         return ColumnDetails(
             self.name,
             column,
@@ -3490,8 +3498,8 @@ class Table(Queryable):
             num_null,
             num_blank,
             num_distinct,
-            most_common,
+            most_common_results,
-            least_common,
+            least_common_results,
         )
 
     def add_geometry_column(