Merge 5c9aed1 into d13a84d

Dockerfile_testrunner

@@ -1,7 +1,7 @@
 FROM mamonu/moj-spark-jovyan:baseenv
 
-RUN pip install pytest pytest-cov poetry coveralls typeguard
-RUN pip install --no-dependencies splink-data-generation==1.0.0
+RUN pip install pytest pytest-cov poetry coveralls typeguard sqlglot
+RUN pip install --no-dependencies splink-data-generation==1.0.1
 
 ADD . /myfiles
 WORKDIR /myfiles

pyproject.toml

@@ -12,11 +12,12 @@ readme = "README.md"
 python = "^3.6"
 jsonschema = "^3.2"
 typeguard = "^2.10.0"
+sqlglot = "^1.16.1"
 
 [tool.poetry.dev-dependencies]
 pytest = "^5.3"
 pandas = "^1.0.0"
-splink-data-generation = "^0.2.1"
+splink-data-generation = "^1.0.1"
 
 [build-system]
 requires = ["poetry>=0.12"]

splink/__init__.py

@@ -36,7 +36,7 @@ def __init__(
     ):
         """Splink data linker
 
-        Provides easy access to the core user-facing functinoality of splink
+        Provides easy access to the core user-facing functionality of splink
 
         Args:
             settings (dict): splink settings dictionary

splink/default_settings.py

@@ -1,5 +1,5 @@
 import warnings
-
+from splink.settings import ComparisonColumn
 from pyspark.sql.session import SparkSession
 
 from copy import deepcopy
@@ -20,6 +20,12 @@
     _add_as_gamma_to_case_statement,
 )
 
+from .parse_case_statement import (
+    parse_case_statement,
+    generate_sql_from_parsed_case_expr,
+    get_columns_used_from_sql_without_l_r_suffix,
+)
+
 
 def _normalise_prob_list(prob_array: list):
     sum_list = sum(prob_array)
@@ -101,8 +107,12 @@ def _get_default_probabilities(m_or_u, levels):
 
 def _complete_case_expression(col_settings, spark):
 
+    cc = ComparisonColumn(col_settings)
+    if cc.has_case_expression_or_comparison_levels:
+        return col_settings
+
     default_case_statements = _get_default_case_statements_functions(spark)
-    levels = col_settings["num_levels"]
+    levels = cc.num_levels
 
     if "custom_name" in col_settings:
         col_name_for_case_fn = col_settings["custom_name"]
@@ -136,7 +146,8 @@ def _complete_probabilities(col_settings: dict, mu_probabilities: str):
     """
 
     if mu_probabilities not in col_settings:
-        levels = col_settings["num_levels"]
+        cc = ComparisonColumn(col_settings)
+        levels = cc.num_levels
         probs = _get_default_probabilities(mu_probabilities, levels)
         col_settings[mu_probabilities] = probs
 
@@ -149,11 +160,72 @@ def _complete_tf_adjustment_weights(col_settings: dict):
                 f"All values of 'tf_adjustment_weights' must be between 0 and 1"
             )
     else:
-        weights = [0.0] * col_settings["num_levels"]
+        cc = ComparisonColumn(col_settings)
+
+        weights = [0.0] * cc.num_levels
         weights[-1] = 1.0
         col_settings["tf_adjustment_weights"] = weights
 
 
+def _complete_comparison_levels(col_settings):
+    if "comparison_levels" not in col_settings:
+        case_expression = col_settings["case_expression"]
+        col_settings["comparison_levels"] = parse_case_statement(case_expression)
+
+    if "case_expression" not in col_settings:
+        cl = col_settings["comparison_levels"]
+        col_settings["case_expression"] = generate_sql_from_parsed_case_expr(cl)
+
+    from splink.settings import ComparisonColumn
+
+    cc = ComparisonColumn(col_settings)
+    keys = cc.comparison_levels_dict.keys()
+    if "-1" not in keys:
+
+        warnings.warn(
+            "No -1 level found in case statement."
+            " You usually want to use -1 as the level for the null value."
+            " e.g. WHEN col_l is null or col_r is null then -1"
+            f" Case statement is:\n {col_settings['case_expression']}."
+        )
+
+
+def _complete_col_name(col_settings):
+
+    if "custom_name" in col_settings:
+        return
+
+    if "col_name" in col_settings:
+        return
+
+    sql = generate_sql_from_parsed_case_expr(col_settings["comparison_levels"])
+    sql_cols = get_columns_used_from_sql_without_l_r_suffix(sql)
+    if len(sql_cols) == 1:
+        col_settings["col_name"] = sql_cols[0]
+    else:
+        col_settings["custom_name"] = "_".join(sql_cols)
+    return col_settings
+
+
+def _complete_custom_columns(col_settings):
+
+    if "col_name" in col_settings:
+        return col_settings
+
+    if "custom_name" in col_settings:
+        sql = generate_sql_from_parsed_case_expr(col_settings["comparison_levels"])
+        sql_cols = get_columns_used_from_sql_without_l_r_suffix(sql)
+        if "columns_used" in col_settings:
+            if set(sql_cols) != set(col_settings["columns_used"]):
+                warnings.warn(
+                    f"The columns used in the case statement are {sql_cols} but the columns "
+                    f"specified in the settings dictionary are {col_settings['columns_used']}"
+                )
+        else:
+            col_settings["custom_columns_used"] = sql_cols
+    return col_settings
+
+
 def complete_settings_dict(settings_dict: dict, spark: SparkSession):
     """Auto-populate any missing settings from the settings dictionary using the 'sensible defaults' that
     are specified in the json schema (./splink/files/settings_jsonschema.json)
@@ -203,7 +275,6 @@ def complete_settings_dict(settings_dict: dict, spark: SparkSession):
 
         # Populate non-existing keys from defaults
         keys_for_defaults = [
-            "num_levels",
             "data_type",
             "term_frequency_adjustments",
             "fix_u_probabilities",
@@ -215,10 +286,27 @@ def complete_settings_dict(settings_dict: dict, spark: SparkSession):
                 default = get_default_value_from_schema(key, is_column_setting=True)
                 col_settings[key] = default
 
+        # Populate default value for num levels only if case_expression or comparison_levels is not specified
+        skip_if_present = set(["case_expression", "comparison_levels", "num_levels"])
+        keys = set(col_settings.keys())
+        intersect = keys.intersection(skip_if_present)
+        if len(intersect) == 0:
+            default = get_default_value_from_schema(
+                "num_levels", is_column_setting=True
+            )
+            col_settings["num_levels"] = default
+
         # Doesn't need assignment because we're modify the col_settings dictionary
+
         _complete_case_expression(col_settings, spark)
+
+        _complete_comparison_levels(col_settings)
+        _complete_col_name(col_settings)
+        _complete_custom_columns(col_settings)
+
         _complete_probabilities(col_settings, "m_probabilities")
         _complete_probabilities(col_settings, "u_probabilities")
+
         _complete_tf_adjustment_weights(col_settings)
 
     return settings_dict

splink/diagnostics.py

@@ -8,11 +8,7 @@
 from typeguard import typechecked
 
 from .charts import load_chart_definition, altair_if_installed_else_json
-from .settings import complete_settings_dict, Settings
-from .vertically_concat import vertically_concatenate_datasets
-from .blocking import block_using_rules
-from .gammas import add_gammas
-from .estimate import _num_target_rows_to_rows_to_sample
+from .settings import Settings
 
 
 def _equal_spaced_buckets(num_buckets, extent):

splink/estimate.py

@@ -5,7 +5,7 @@
 from .gammas import add_gammas
 from .maximisation_step import run_maximisation_step
 from .model import Model
-from .settings import complete_settings_dict
+from .default_settings import complete_settings_dict
 from .vertically_concat import vertically_concatenate_datasets
 
 import warnings