class_docstr: Inference rule that checks for string columns.
  
  It will always produce DIMENSION.CATEGORICAL with MEDIUM confidence (complementary).
class_docstr_tok: ["Inference","rule","that","checks","for","string","columns",".","It","will","always","produce","DIMENSION.CATEGORICAL","with","MEDIUM","confidence","(","complementary",")","."]
code: def match_column(self, props: ColumnProperties) -> bool:  # noqa: D
      return props.type == InferenceColumnType.STRING
  
imports: from __future__ import annotations
  from typing import List
  from metricflow.inference.context.data_warehouse import ColumnProperties, DataWarehouseInferenceContext, InferenceColumnType
  from metricflow.inference.models import InferenceSignal, InferenceSignalConfidence, InferenceSignalType
  from metricflow.inference.rule.base import InferenceRule
  from metricflow.inference.rule.rules import ColumnMatcherRule, LowCardinalityRatioRule
label_desc: Use image node_id 1 for calling the CategoricalDimensionByStringTypeRule obj's underlying member method code with example usage: obj.match_column(props) and returns: unknown