MDFactoryMDFactory
mdfactoryutilsdata_manager

CsvDataSource

File-based CSV data source. Each table is a separate CSV file.

Attributes

attributefile_path
= Path(file_path)
attributeunique_columns
= unique_columns
attributetable_existsbool

Check if the CSV file exists and has content.

Functions

func__init__(self, file_path, unique_columns=None)
paramself
paramfile_pathstr | Path
paramunique_columnslist[str] | None
= None

Returns

None
funcexists(self) → bool

Check if the CSV file exists.

paramself

Returns

bool

True if the CSV file exists on disk

funcload_data(self) → pd.DataFrame

Load all data from the CSV file.

paramself

Returns

pandas.DataFrame

Contents of the CSV file, or empty DataFrame if file is missing

funcsave_data(self, data, overwrite=False)

Save data to CSV. Accepts single dict, list of dicts, or DataFrame.

paramself
paramdataUnion[Dict[str, Any], List[Dict[str, Any]], pd.DataFrame]
paramoverwritebool
= False

Returns

None
funcquery_data(self, conditions) → pd.DataFrame

Query data from CSV based on conditions.

paramself
paramconditionsDict[str, Any]

Returns

pandas.pandas.DataFrame
funcupdate_data(self, conditions, updates)

Update existing data in CSV based on conditions.

paramself
paramconditionsDict[str, Any]
paramupdatesT

Returns

None
funcdelete_data(self, conditions)

Delete data from CSV based on conditions.

paramself
paramconditionsDict[str, Any]

Returns

None
funcgrab_column(self, column_name) → pd.Series

Retrieve a specific column from CSV.

paramself
paramcolumn_namestr

Returns

pandas.pandas.Series
funcgrab_row(self, index) → pd.Series

Retrieve a specific row from CSV.

paramself
paramindexint

Returns

pandas.pandas.Series

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