CSV-based Database

class datatoolbox.database.Database

CSV based database that uses git for as distributed version control system. Each table is saved locally as a csv file and identified by a unique ID. The csv files are organized in various sources in individual folders. Each sources comes with its own git repository and can be shared with others.

add_to_inventory(datatable)

Method to add a table to the global inventory file. Input: datatable

clearLogTables()

Clears the list of logged tables. This is anyway done if the package is newly loaded

commitTable(dataTable, message, sourceMetaDict=None)

Adds a table permamently to the underlying database. For the first table of a new source, the meta data for the sources needs to be provides as well

Input

table : Datatable message : str sourceMetaDict [Optional] : dict

commitTables(dataTables, message, sourceMetaDict=None, append_data=False, update=False, overwrite=False, cleanTables=True)

Adds multipe tables permamently to the underlying database. For the first table of a new source, the meta data for the sources needs to be provides as well

Input

tables : list of Datatable message : str sourceMetaDict [Optional] : dict append_data [optinal] : bool to choose if new data is added to the existing

table (new data does not overwrite old data)

update : [optional] : bool to choose if the exting data is updated overwrite : [optional] : bool to choose if data is overwriten (new data

overwrites old data)

cleanTables [optional]bool (default: true) to choose if tables are

cleaned before commit

TODO: Check flags

create_empty_datashelf(modulePath, pathToDataself)

Method to create the required files for an empty csv-based data base. (Equivalent to the fucntions in admin.py)

exportSourceToRemote(sourceID)

This function exports a new local dataset to the defind remote database.

Input is a local sourceID as a str.

findc(**kwargs)

Method to search through the inventory. kwargs can be all inventory entires (see config.INVENTORY_FIELDS).

finde(**kwargs)

Finds an exact match for the given filter criteria.

findp(level=None, regex=False, **filters)

Future defaulf find method that allows for more sophisticated syntax in the filtering

Usage:

filtersUnion[str, Iterable[str]]

One or multiple patterns, which are OR’d together

regexbool, optional

Accept plain regex syntax instead of shell-style, default: False

Returns

matches : pd.Series Mask for selecting matched rows

getTable(ID, native_regions=False)

Method to load the datatable for the given tableID.

Input

tableID : str native_regions : bool, optional

Load native region defintions if available. The default is False.

Returns table : Datatable

getTables(iterIDs, native_regions=False, disable_progress=None)

Method to return multiple datatables at once as a dictionary like set fo tables.

Input

iterIDS: list [str]

List of IDs to load.

native_regionsbool, optional

Load native region defintions if available. The default is False.

disable_progressbool, optional

Disable displaying of progressbar. The default None hides the progressbar on non-tty outputs

Returns

tables : TableSet

getTablesAvailable()

Return a locally stored pandas dataframe of tables on datashelf

get_path_of_source(sourceID)

Returns the harddisk path of a given source.

importSourceFromRemote(remoteName)

This functions imports (git clone) a remote dataset and creates a local copy of it.

Input is an existing sourceID.

info()

Shows the most inmportant information about the status of the database

isConsistentTable(datatable)

Checks if that table is fitting the following requirements - numeric data - spatial identifiers are known to the database - columns are propper years - index is not duplicated

isSource(sourceID)

Checks is the source is in the database

Input

sourceID : str

pull_update_from_remote(repoName)

Updates the local data repository by the newest version on the remote repository

Parameters

repoNamestr

Source ID string to identify which source repository should be updated.

Returns

None.

remote_sourceInfo()

Returns a list of available sources and meta data

removeSource(sourceID)

Function to remove an entire source from the database.

removeTable(tableID)

Method to remnove tables from the database

Input

tableID : str

removeTables(IDList)

Method to remnove tables from the database

Input

IDList : list of str

remove_from_inventory(tableID)

Method to remove a table from the global inventory Input: tableID

returnInventory()

Returns a copy of the data base inventory.

saveTablesToDisk(folder, IDList)

Function to save a list of tables to disk as csv files.

save_logged_tables(folder='data')

Creates a local data directory that can be used to run the logges analysis indepenedly.

Parameters

folderstr, optional

DESCRIPTION. The default is ‘data’.

Returns

None.

sourceExists(source)

Function to check if a source is propperly registered in the data base

Input: SourceID

sourceInfo(show_number_of_table=False)

Returns a list of available sources and meta data

startLogTables()

Starts the logging of loaded datatables. This is useful to collect all required tables for a given analysis to create a datapackage for off-line useage

stopLogTables()

Stops the logging process of datatables and return the list of loaded table IDs for more processing.

tableExist(tableID)

Method to test if table exists in the database

Input

tableID : str

updateExcelInput(fileName)

This function updates all data values that are defined in the input sheet in the given excel file

updateTable(oldTableID, newDataTable, message)

Specific method to update the data of an existing table

Input

oldTableID : str newDataTabble : Datatable message : str

Commit message to describle the added data

updateTables(oldTableIDs, newDataTables, message)

Equivalent method to updateTable, but for multiple tables at once

Input

oldTableIDs : list of str newDataTabbles : list of Datatable message : str

Commit message to describle the added data

updateTablesAvailable(private_access_token)

Method to update module data folder with the latest datashelf contents on Gitlab

Requirements:

• private_access_token: generated on Gitlab

update_mapping_file(sourceID, mapping_file_path, sourceMetaDict=None)

adds mapping file to database

Parameters

sourceTYPE

DESCRIPTION.

IDTYPE

DESCRIPTION.

mappingTYPE

DESCRIPTION.

validate_ID(ID, print_statement=True)

Method to chekc the validity of a table ID and check the state of the data