Import from a CSV File

To set up your environment:

1. Download and install Python. The import scripts are compatible with Python 2.7+. Python 3 releases are not supported. You can choose whichever installation directory you prefer.

   The latest versions of macOS, CentOS, Red Hat Enterprise Linux (RHEL), and Ubuntu come with Python 2.7 out of the box. If you're working with any of these operating systems, continue with the next step.

2. Open the command-line interface that is supported by your operating system.

3. Install the package that contains the import scripts with the following command:

   pip install youtrack-scripts

   • The import scripts are installed in your local environment.

   • The youtrack package that contains the Python client library for the YouTrack REST API is installed automatically as a dependency.

   If you prefer not to install the packages globally, you can install them for your user account only with the command:

   pip install --user youtrack-scripts

1. Open your CSV file in a spreadsheet editor. It's much easier to read and, if necessary, modify the data when it is presented in discrete columns and rows.

2. Check the first row (record) in the file. This record should be a header that contains a list of field names.

3. Check your header for required fields. Your header must include fields that can be mapped to each of the following issue attributes: project_id, project_name, numberInProject, reporterName, created, and summary. If these columns are not present, add them to your CSV file.

4. Important! Check that the field that is mapped to the numberInProject issue attribute does not contain an alphanumeric prefix. If it does, please change the prefix to be letters-only, and then export this project to the CSV file one more time.

   YouTrack assumes that the field that is mapped to the numberInProject is an integer number. However, sometimes, this exported issue number can also contain a prefix - a short name of the project or a projectID, and so on. Let's say, the issue numbers are exported as {project_short_name}-{number_in_the_project} (for example, DX-12345). In this case, for the import to work, this {project_short_name} must not contain any digit. In other words, you must check that the value for the numberInProject does not look like DX1-12345 or D1X-12345.

To generate a mapping file:

1. Open the command-line interface that is supported by your operating system.

2. If necessary, change the current directory to the installation directory for Python. For example (Windows):

   cd C:\Python27

3. Enter the following command:

   csv2youtrack -g -m mapping.json source.csv

   • The -g option tells the script to generate the mapping file.

   • The -m option overrides the default path and filename for the mapping file. If you don't pass this option, the file is generated in the current directory and assigned the same name as the CSV file with the .json extension. If you want to specify another location and/or filename, specify a value for the parameter with the full path of the target directory and/or desired name.

   • The source.csv parameter specifies the location of the source CSV file. Replace this value with the full path and filename of your source CSV file. Don't forget to include the .csv extension.

   • If the command is executed successfully, a message with the location of the generated file is printed in the command-line interface.

4. Open the generated mapping file and map the fields from your source file to their corresponding issue attributes in YouTrack. If your source file contains one or more fields that you don't want to import, you can remove the references from the mapping file. Use the example that follows as a guide.

To customize the generated mapping file:

1. For the csv_field_delimiter, enter the character that delimits characters in your CSV file. If the delimiter in your CSV file and the character that is specified for this parameter are not the same, the import fails.

2. For the csv_value_delimiter, enter the character that separates multiple values for fields in your CSV file.

3. For the date_format_string, specify the format that is used for date fields in your CSV file. This parameter accepts directives that are used by the strftime(format) method in the Python Standard Library. You can find a complete list of directives in the Python documentation.

   • In our sample mapping file, the %Y-%m-%d %H:%M:%S pattern recognizes date values in the format 2015-10-20 21:00:00.

   • The default value uses the pattern %A, %B %d, %Y %I:%M:%S %p %z, which recognizes date values in the format Tuesday, October 20, 2015 09:00:00 PM +0300.

   Just look at the format that is used in your CSV file and replace each value with the corresponding directive. Enter punctuation marks and whitespace between directives as they appear in your fields.

4. In the field_names section of the file, map the fields from your source file to their corresponding issue attributes in YouTrack. If your source file contains a field that you don't want to import, you can remove the reference from the mapping file. Pay attention to the following guidelines when you map your fields:

   • The first set of fields in this section are common issue attributes in YouTrack.

   • The second set of fields correspond with the columns from your CSV file. The fields are sorted in alphabetical order.

   • The mapping file must contain mappings for all of the following issue attributes: project_id, project_name, numberInProject, summary, created, and reporterName. These fields are listed at the top of this section. If any of these fields are not included in the mapping, the import fails with an error.

   • The left side of the mapping references the field name in your CSV file. These values must be specified exactly as written in the header.

   • The right side of the mapping references an issue attribute in YouTrack. Base attributes use the attribute names that are specified in the Import REST API. For mappings to custom fields, use the custom field name.

   • If the column names in the source file match the default names for target custom fields in YouTrack, you don't need to map them explicitly. This includes default fields like Type, Priority, and State. You should, however, verify that the data that is stored in the source file matches the data type for the target field.

   • Each field in your source file can only be mapped to a single target field. For example, you cannot map the issue summary to both the issue summary and description.

5. In the field_types section of the file, specify the data type for fields that are created during import. Consider the following guidelines:

   • The left side of the mapping references the name of the custom field in YouTrack. These values must exactly match the custom field name in the field_names dictionary.

   • The right side of the mapping references the field type in YouTrack. For a list of valid types, refer to the Administration REST API.

   • If the target field already exists in YouTrack, you do not need to include it here.

   • You cannot change the data type of an existing field. For example, if the existing Assignee field stores single values (user[1]), you cannot use user[*] in the mapping file and import multiple assignees. You must first update this property for the Assignee field in the YouTrack user interface, then import the data.

6. Save your changes and close the mapping file.

To import your data:

1. Open the command-line interface that is supported by your operating system.

2. If necessary, change the current directory to the installation directory for Python. For example (Windows):

   cd C:\Python27

3. Enter the following command:

   csv2youtrack -m mapping.json -t token -u login -p password -c comments_file -a attachments_file source_file target_url

   The source_file and target_url must be the last arguments that are specified in the script. Replace the command-line parameters with values as described here:

   Parameter	Description
   mapping.json	Required. Use with the -m option to specify the full path and filename of your mapping file.
   token	When used with the -t option, a permanent token that is used to authenticate your administrator account in YouTrack. This is the preferred method of authentication. If you use this option, skip the -u and -p options. To learn how to generate a permanent token, see Create a Permanent Token. Alternatively, you can use the -T option and specify the full path and filename for a file that contains a permanent token.
   login	When used with the -u option, the login for a YouTrack administrator account. You must also specify a value for the -p option.
   password	When used with the -p option, the password for the YouTrack administrator account.
   comments_file	Optional. Use with the -c option to specify the full path to a CSV file that contains issue comments.
   attachments_file	Optional. Use with the -a option to specify the full path to a CSV file that contains references to attachments.
   source_file	The full path to the source CSV file. Include the filename and extension.
   target_url	The base URL of the target YouTrack server. For YouTrack InCloud instances, your base URL includes the trailing /youtrack. For example: https://company.myjetbrains.com/youtrack

   • The command executes the Python import script.

   • If successful, the following line is printed in the command-line interface for each issue:

     Issue [ <issue ID> ] imported successfully

4. Check the project or projects that you imported issues into and verify that the data is presented properly. If you are not satisfied with the results and want to re-import the data:

   • Delete all of the issues that were created during import. If you imported issues into a new project, simply delete the project.

   • Edit your source file and/or mapping file.

   • Run the import script again.