Logging

REDCap API methods for Project field names

`Logging (Base)`

Responsible for all API methods under 'Logging' in the API Playground

Source code in redcap/methods/logging.py

class Logging(Base):
    """Responsible for all API methods under 'Logging' in the API Playground"""

    # pylint: disable=too-many-locals

    def export_logging(
        self,
        format_type: Literal["json", "csv", "xml", "df"] = "json",
        return_format_type: Optional[Literal["json", "csv", "xml"]] = None,
        log_type: Optional[
            Literal[
                "export",
                "manage",
                "user",
                "record",
                "record_add",
                "record_edit",
                "record_delete",
                "lock_record",
                "page_view",
            ]
        ] = None,
        user: Optional[str] = None,
        record: Optional[str] = None,
        dag: Optional[str] = None,
        begin_time: Optional[datetime] = None,
        end_time: Optional[datetime] = None,
        df_kwargs: Optional[Dict[str, Any]] = None,
    ):
        """
        Export the project's logs

        Args:
            format_type:
                Return the metadata in native objects, csv or xml.
                `'df'` will return a `pandas.DataFrame`
            return_format_type:
                Response format. By default, response will be json-decoded.
            log_type:
                Filter by specific event types
            user:
                Filter by events created by a certain user
            record:
                Filter by events created for a certain record
            dag:
                Filter by events created by a certain data access group (group ID)
            begin_time:
                Filter by events created after a given timestamp
            end_time:
                Filter by events created before a given timestamp
            df_kwargs:
                Passed to `pandas.read_csv` to control construction of
                returned DataFrame.
        Returns:
            Union[str, List[Dict[str, Any]], "pd.DataFrame"]:
                List of all changes made to this project, including data exports,
                data changes, and the creation or deletion of users

        Examples:
            >>> proj.export_logging()
            [{'timestamp': ..., 'username': ..., 'action': 'Manage/Design ',
            'details': 'Create project ...'}, ...]
        """
        payload: Dict[str, Any] = self._initialize_payload(
            content="log", format_type=format_type
        )
        optional_args = [
            ("returnFormat", return_format_type),
            ("logtype", log_type),
            ("user", user),
            ("record", record),
            ("dag", dag),
            ("beginTime", begin_time),
            ("endTime", end_time),
        ]

        for arg in optional_args:
            arg_name, arg_value = arg
            if arg_value:
                if arg_name in ["beginTime", "endTime"]:
                    arg_value = cast(datetime, arg_value)
                    arg_value = arg_value.strftime("%Y-%m-%d %H:%M:%S")

                payload[arg_name] = arg_value

        return_type = self._lookup_return_type(format_type, request_type="export")
        response = cast(Union[Json, str], self._call_api(payload, return_type))

        return self._return_data(
            response=response,
            content="log",
            format_type=format_type,
            df_kwargs=df_kwargs,
        )
        # pylint: enable=too-many-locals

`def_field: str` `inherited` `property` `readonly`

The 'record_id' field equivalent for a project

`field_names: List[str]` `inherited` `property` `readonly`

Project field names

!!! note These are survey field names, not export field names

`forms: List[str]` `inherited` `property` `readonly`

Project form names

`is_longitudinal: bool` `inherited` `property` `readonly`

Whether or not this project is longitudinal

`metadata: Json` `inherited` `property` `readonly`

Project metadata in JSON format

`token: str` `inherited` `property` `readonly`

API token to a project

`url: str` `inherited` `property` `readonly`

API URL to a REDCap server

`export_logging(self, format_type='json', return_format_type=None, log_type=None, user=None, record=None, dag=None, begin_time=None, end_time=None, df_kwargs=None)`

Export the project's logs

Parameters:

Name	Type	Description	Default
`format_type`	`Literal['json', 'csv', 'xml', 'df']`	Return the metadata in native objects, csv or xml. `'df'` will return a `pandas.DataFrame`	`'json'`
`return_format_type`	`Optional[Literal['json', 'csv', 'xml']]`	Response format. By default, response will be json-decoded.	`None`
`log_type`	`Optional[Literal['export', 'manage', 'user', 'record', 'record_add', 'record_edit', 'record_delete', 'lock_record', 'page_view']]`	Filter by specific event types	`None`
`user`	`Optional[str]`	Filter by events created by a certain user	`None`
`record`	`Optional[str]`	Filter by events created for a certain record	`None`
`dag`	`Optional[str]`	Filter by events created by a certain data access group (group ID)	`None`
`begin_time`	`Optional[datetime.datetime]`	Filter by events created after a given timestamp	`None`
`end_time`	`Optional[datetime.datetime]`	Filter by events created before a given timestamp	`None`
`df_kwargs`	`Optional[Dict[str, Any]]`	Passed to `pandas.read_csv` to control construction of returned DataFrame.	`None`

Returns:

Type	Description
`Union[str, List[Dict[str, Any]], "pd.DataFrame"]`	List of all changes made to this project, including data exports, data changes, and the creation or deletion of users

Examples:

>>> proj.export_logging()
[{'timestamp': ..., 'username': ..., 'action': 'Manage/Design ',
'details': 'Create project ...'}, ...]

Source code in redcap/methods/logging.py

def export_logging(
    self,
    format_type: Literal["json", "csv", "xml", "df"] = "json",
    return_format_type: Optional[Literal["json", "csv", "xml"]] = None,
    log_type: Optional[
        Literal[
            "export",
            "manage",
            "user",
            "record",
            "record_add",
            "record_edit",
            "record_delete",
            "lock_record",
            "page_view",
        ]
    ] = None,
    user: Optional[str] = None,
    record: Optional[str] = None,
    dag: Optional[str] = None,
    begin_time: Optional[datetime] = None,
    end_time: Optional[datetime] = None,
    df_kwargs: Optional[Dict[str, Any]] = None,
):
    """
    Export the project's logs

    Args:
        format_type:
            Return the metadata in native objects, csv or xml.
            `'df'` will return a `pandas.DataFrame`
        return_format_type:
            Response format. By default, response will be json-decoded.
        log_type:
            Filter by specific event types
        user:
            Filter by events created by a certain user
        record:
            Filter by events created for a certain record
        dag:
            Filter by events created by a certain data access group (group ID)
        begin_time:
            Filter by events created after a given timestamp
        end_time:
            Filter by events created before a given timestamp
        df_kwargs:
            Passed to `pandas.read_csv` to control construction of
            returned DataFrame.
    Returns:
        Union[str, List[Dict[str, Any]], "pd.DataFrame"]:
            List of all changes made to this project, including data exports,
            data changes, and the creation or deletion of users

    Examples:
        >>> proj.export_logging()
        [{'timestamp': ..., 'username': ..., 'action': 'Manage/Design ',
        'details': 'Create project ...'}, ...]
    """
    payload: Dict[str, Any] = self._initialize_payload(
        content="log", format_type=format_type
    )
    optional_args = [
        ("returnFormat", return_format_type),
        ("logtype", log_type),
        ("user", user),
        ("record", record),
        ("dag", dag),
        ("beginTime", begin_time),
        ("endTime", end_time),
    ]

    for arg in optional_args:
        arg_name, arg_value = arg
        if arg_value:
            if arg_name in ["beginTime", "endTime"]:
                arg_value = cast(datetime, arg_value)
                arg_value = arg_value.strftime("%Y-%m-%d %H:%M:%S")

            payload[arg_name] = arg_value

    return_type = self._lookup_return_type(format_type, request_type="export")
    response = cast(Union[Json, str], self._call_api(payload, return_type))

    return self._return_data(
        response=response,
        content="log",
        format_type=format_type,
        df_kwargs=df_kwargs,
    )
    # pylint: enable=too-many-locals

Logging

Logging (Base)

def_field: str inherited property readonly

field_names: List[str] inherited property readonly

forms: List[str] inherited property readonly

is_longitudinal: bool inherited property readonly

metadata: Json inherited property readonly

token: str inherited property readonly

url: str inherited property readonly

export_logging(self, format_type='json', return_format_type=None, log_type=None, user=None, record=None, dag=None, begin_time=None, end_time=None, df_kwargs=None)