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CSV Importer

easydb allows the import of records and users via CSV (UTF-8 or UTF-16). The CSV-Importer can be found in lists via the -symbol at the bottom of the sidebar.



Supported field types

If you need support for other types, please send your request to our support.

CSV file

You create a file in CSV format outside the easydb. This file must be in UTF-8 encoding or UTF-16 encoding, otherwise special characters may not be imported correctly.

For example, when using Microsoft Excel, choose “Unicode text” to save.

The easydb CSV Importer has automatic detection for the following separators:

And for the following quotes:

The file must contain an identifier for the column in the first line. This column is displayed as a source field as part of the mapping in the easydb CSV importer.

In a second column you can already enter the target field in the easydb. The CSV importer then already displays the target column in the mapping.

The following format must be used for the target columns:

Simple fields (text, boolean, whole and comma numbers)

Use the name of the column as specified in the data model. The name of the object type can optionally be prefixed to the name. For a column title in the object type media that would be either title or media.title. For Yes / No fields (Boolean) use “1” for Yes and “0” for No. Integers must be entered without decimal places. Commands may have two decimal places, but with a “.” Must be attached. Example: - Title: One-line text - Description: Multi-line text - Construction project: Boolean - Duration: Integer - Costs: number of commissions

Title Description development duration costs
House construction No description. 1 2 2.5
Apartment building “A multi-line
description is placed
in quotes “
1 4 17.85
Fuchsbau No description. 0 1 0

Hierarchical text fields

When importing main object types, the hierarchy levels must be specified in their own columns.

location#0 location#1 location#2
may remain empty Brandenburg
Italy Trentino-Alto Adige
Italy Trentino-Alto Adige Bolzano
Italy Lacio
Italy Lacio Rome

You can omit the entry from the father in individual lines (see: Can be left blank) if it is in the line before it. The entry is automatically assigned to the lines below, up to the line in which a new entry begins (here in the example to Italy).

Hierarchy levels are displayed with “#” numbered. Note that the number starts with 0.

Linked object types

To specify linked records in the CSV, use the name of the column (optionally with the object type), and then the name of the column in the linked object type. Instead of specifying the name of the target column in the object type, you can also specify the object ID of the linked data set directly.

Keyword#name Artist#name Atritst#firstname
Mona Lisa da Vinci Leonardo
Skrik Munch Edvard

If the linked object type is hierarchical, you can specify only one column of the linked object type (for example, “ort#name”, but not “ort#name_alternative”). The linked hierarchical records are then generated directly.

Title Location#name
The Brandenburg Gate Germany > Brandenburg > Potsdam
Colloseum Italy > Lacio > Rome
Marketplaces Italy > Trentino-Alto Adige > Bolzano

You can optionally write terms in quotation marks. If the term is a < or > , You must use quotation marks. If separators occur within a term, they are taken over by the quotation marks. If you want to include a term with a punctuation mark, it must be enclosed in quotation marks (double quotes), including the quotation marks.

Multiple fields

Multiple fields are referenced in the column name with the full path to the field. Note that you can import only the first level of the multiple fields with the CSV importer. Contact support if you want to import deeper nesting.

titel people[].person#name people[].person#vorname keyword[].keyword#name
Image with 4 persons Lee Lewis
Keyword 1
Keyword 2
Keyword 3
Image with 2 persons Allen
Keyword 1
Keyword 2
Keyword 3

Multiple fields are generated line by line. For the first example, “Picture with 4 people”, 4 lines with the entries Jerry Lee Lewis, Carl Perkins, Evlis Presley and Johnny Cash are created from the people’s multiple fields. Therefore, in order to create data sets with several entries in a multiple field, these must be separated by line breaks within the separators. In a text editor without further formatting, the following structure results for the first data record in the table:

"Picture with 4 people";
"Lee Lewis
Johnny ";"Keyword 1
Keyword 2
Keyword 3 "


You can use the CSV Importer to acquire metadata (for example, through the hotfolder), if the files were uploaded with a unique file name that you use in the CSV. To do this, specify the column name of the file field.

NOTE: A hierarchical folder structure in which the data to be imported is stored can also be stored in a CSV file via a separate “Filesystem2CSV” Python script (see In this way, folder names in easydb can be imported as (hierarchical) categories or keywords.

Import files

There is the possibility to import files via URL with the CSV Importer. The configuration options can be found in chapter Import files.

Groups (user import only)

You can use the column name “_groups#find” to add groups to users. The groups are specified as commasparated. First the ID is searched, then the internal name, then the display name (in all languages) to find and assign the group.


The CSV file is uploaded and the following setting is made:

Setting Description
CSV field names Row that contains the column names.
Target field name Line that contains the target field names.
Object type Object type to be imported.
Pool Specifies the pool. The pool is only set when inserting records
Mask Mask to be used for the import.
File upload type This option is available if the objecttype contains one or more fields of type ‘file’. See Import files
Field to update Specify a field to search the records if you want to make an update. If you have specified filenames in your CSV, select the file field
In the case of multilingual fields, you have the possibility to make the match over a certain language (e.g., name # en-DE or name # en-US). To activate the selection, specify in the Mapping tab for which fields, which languages ​​should be available
Append Multiple Fields This option adds multiple fields that are not replaced as usual with an update
Create linked records Specify whether linked records should be created before the actual import or not. You can not insert or update records with new linked records with the option turned off
Comment Comment on saving the records
Package size size of the processing packets to be sent to the server


Button Description
Re-read Reads the CSV and discards all information that has already been loaded
CSV When preparing and after saving, more information is generated, which is written back to the CSV. With Save CSV you can get this information to your desktop. For example, the record IDs are written back to the CSV when records are recreated
Prepare … Prepares the CSV import. This includes searching for existing records and linked records. After the preparation, you can check in the table view which lines are collected in which way
Insert Starts the CSV import and inserts new records. Previously, all unknown linked records are created again
Refresh Starts the CSV import and updates existing records. Previously, all unknown linked records are created again. Note that empty columns are also sent to the server
Insert + Refresh Performs both steps directly in sequence.

Automatic field mapping

Fields names with a specific notation will be mapped automatically. The exporter of CSV uses these notations by default.

Field Notation
Top Level Objecttype _objecttype
Top Level System Object ID _system_object_id
Top Level Global Object ID _global_object_id
Top Level Object ID _id
Top Level Version _version
Nested Table <nested table name>[]
L10N Text <field>#<lang>
Daterange Start <field>#from
Daterange End <field>#to
Custom Type Standard <field>#_standard#<lang>
Linked Object ID <field with linked object>#_id
Linked Object Version <field with linked object>#_version
Linked Object System Object ID <field with linked object>#_system_object_id
Linked Object Global Object ID <field with linked object>#_global_object_id
Linked Object Standard <field with linked object>#_standard#<lang>
Linked Object (Hierarchical) Parent ID <field with linked object>#_id_parent
Linked Object (Hierarchical) Standard in Hierarchy <field with linked object>#_standard#<lang>#<level>