Best Python code snippet using pandera_python
io.py
Source:io.py
...61 # `parse_checks` so we know that `check_name` exists.62 # infer dtype of statistics and serialize them63 serialized_checks[check_name] = _serialize_check_stats(check_stats)64 return serialized_checks65def _serialize_component_stats(component_stats):66 """67 Serialize column or index statistics into json/yaml-compatible format.68 """69 serialized_checks = None70 if component_stats["checks"] is not None:71 serialized_checks = {}72 for check_name, check_stats in component_stats["checks"].items():73 serialized_checks[check_name] = _serialize_check_stats(74 check_stats, component_stats["dtype"]75 )76 dtype = component_stats.get("dtype")77 if dtype:78 dtype = str(dtype)79 return {80 "dtype": dtype,81 "nullable": component_stats["nullable"],82 "checks": serialized_checks,83 **{84 key: component_stats.get(key)85 for key in [86 "name",87 "unique",88 "coerce",89 "required",90 "regex",91 ]92 if key in component_stats93 },94 }95def _serialize_schema(dataframe_schema):96 """Serialize dataframe schema into into json/yaml-compatible format."""97 from pandera import __version__ # pylint: disable=import-outside-toplevel98 statistics = get_dataframe_schema_statistics(dataframe_schema)99 columns, index, checks = None, None, None100 if statistics["columns"] is not None:101 columns = {102 col_name: _serialize_component_stats(column_stats)103 for col_name, column_stats in statistics["columns"].items()104 }105 if statistics["index"] is not None:106 index = [107 _serialize_component_stats(index_stats)108 for index_stats in statistics["index"]109 ]110 if statistics["checks"] is not None:111 checks = _serialize_dataframe_stats(statistics["checks"])112 return {113 "schema_type": "dataframe",114 "version": __version__,115 "columns": columns,116 "checks": checks,117 "index": index,118 "coerce": dataframe_schema.coerce,119 "strict": dataframe_schema.strict,120 "unique": dataframe_schema.unique,121 }...
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