typedframe 0.4.0

Typed Wrappers over Pandas DataFrames with schema validation

🐍 typedframe

Typed wrappers over pandas DataFrames with schema validation.

TypedDataFrame is a lightweight wrapper over pandas.DataFrame that provides runtime schema validation and can be used to establish strong data contracts between interfaces in your Python code.

    >>> from typedframe import TypedDataFrame, DATE_TIME_DTYPE
    >>> class MyTable(TypedDataFrame):
    ...    schema = {
    ...        "col1": object, # str
    ...        "col2": np.int32,
    ...        "col3": ('foo', 'bar')
    ...    }
    ...    optional = {
    ...        "col4": bool,
               "col5": DATE_TIME_DTYPE
    ...    }

    >>> df = pd.DataFrame({"col1": ['foo'], "col2": np.array([1], dtype=np.int32), "col3": ['bar']})
    >>> df.col3 = pd.Categorical(df.col3, categories=('foo', 'bar'), ordered=True)
    >>> print(MyTable(df).df)

Supported Data Types

• Integers: np.int16, np.int32, np.int64, etc.
• Floats: np.float16, np.float32, np.float64, etc.
• Boolean: bool
• String: STRING_DTYPE
• Python object: object
• Categorical: category
• Date, Datetime: DATE_TIME_DTYPE