Reports System

Default Usage

OpenMDAO has a reports system which will generate reports when you run your model. To see a list of the reports that are run by default, along with a brief description of each, use the command:

openmdao list_reports -d

Running the same command without the -d will list all reports that are available.

Here is a table with more info about these default commands.

Report Name


When Run

Doc link


Interactive, graphical view of the model

after Problem.final_setup

N2 diagram


Information on design variables, objectives, and constraints

after Driver._compute_totals

scaling report


Metadata associated with the creation of the coloring

after Driver._get_coloring


Summary of results of an optimization run

after Drive._post_run

optimization report

Note that the reports are only run the first time the method is called on a given instance. For example, the scaling report is only run after the first call to Driver._compute_totals.

These reports will, by default, be put into a subfolder of reports named after the Problem name. For example, if your model has a single Problem and its default name, problem1, was not changed by the user, the reports will be placed in a directory named reports/problem1.

The user has control over the reports system by setting some environment variables which are described below.

Controlling which reports are generated

There are two ways to control which reports are generated on which models.

Controlling reporting using an environment variable

To turn off OpenMDAO’s default report generation, the user should set the OPENMDAO_REPORTS environment variable to any one of these four values: ‘0’, ‘false’, ‘off’, or ‘none’.

The user can also have more fine-grained control over what reports are generated by setting this environment variable to a string that lists the reports to run. For example


  2. OPENMDAO_REPORTS=n2,scaling


If OPENMDAO_REPORTS is not set, or is set to ‘1’, ‘true’, or ‘on’, the default reports will be generated.

The user can also explicitly turn on all available reports by setting OPENMDAO_REPORTS to ‘all’.

Controlling reporting using the Problem reports argument

The user can also control what reports are generated using the reports argument to Problem.

If reports is the default of _UNDEFINED or True, the OPENMDAO_REPORTS environment variable determines reporting.

If the value for reports is None or False, it will disable all reports on that Problem.

Otherwise, reports may be a list of names or a single comma-delimited string of the names of the reports to run for that Problem.

Overall, OPENMDAO_REPORTS represents the global default list of reports, and individual Problems can either use that default list or override it by specifying their own list explicitly.

Setting the directory for the reports

If the user wishes to have the reports directory placed into a different directory other than the default current working directory, the user can set the environment variable, OPENMDAO_REPORTS_DIR to the name of that directory. The directory does not have to exist beforehand. It will be created by the reporting system. As an example, if OPENMDAO_REPORTS_DIR is set to “my_reports”, then, if the Problem name is problem1, then the reports will be written to the “my_reports/problem1” directory.

Support for subproblems

The reporting system supports subproblems. For example, if a model has two Problems and they have the default names of problem1 and problem2, the reporting system will put the reports into the subfolders, problem1 and problem2 under the top level reports directory, which defaults to ./reports or is specified by the value of OPENMDAO_REPORTS_DIR.

Adding user defined reports

The user can register a user defined report using the register_report function.

openmdao.utils.reports_system.register_report(name, func, desc, class_name, method, pre_or_post, filename=None, inst_id=None)[source]

Register a report with the reporting system.


Name of report. Report names must be unique across all reports.


A function to do the reporting. Expects the first argument to be an instance of class_name.


A description of the report.


The name of the class owning the method where the report will be run.


In which method of class_name should this be run.


Valid values are ‘pre’ and ‘post’. Indicates when to run the report in the method.

filenamestr or None

Name of file to use when saving the report.

inst_idstr or None

Either the instance ID of an OpenMDAO object (e.g. Problem, Driver) or None. If None, then this report will be run for all objects of type class_name.

Here is a script to show how this is done. Note that the function that is called to generate the actual report must have as its first argument the class name of the OpenMDAO object owning the method where the report will be run. Currently, the only options are Problem and Driver. The second argument to the report function is the local filename of the report. The full file path of the report will be determined based on OPENMDAO_REPORTS_DIR and the name of the enclosing Problem instance. The directory where the report will be written can be obtained by calling the get_reports_dir method on the Problem or Driver instance passed into the reporting function.

Note that register_report only adds a report type to the global reports registry. In order to activate the report so that it actually generates output, it must appear in either OPENMDAO_REPORTS or must be passed in the Problem reports arg as shown below.

After this script is run, there will be a file named user_report.txt in the directory problem1.

import pathlib
import openmdao.api as om
from openmdao.test_suite.components.paraboloid import Paraboloid

user_report_filename = 'user_report.txt'

def user_defined_report(prob, report_filename):
    path = pathlib.Path(prob.get_reports_dir()).joinpath(report_filename)
    with open(path, "w") as f:
        f.write(f"Do some reporting on the Problem, {prob._name}\n")

# Run the report before the call to Problem.setup
om.register_report("user_report", user_defined_report, "This report is user defined",
                     'Problem', 'setup', 'pre', user_report_filename)

prob = om.Problem(reports='user_report')
model = prob.model

model.add_subsystem('p1', om.IndepVarComp('x', 0.0), promotes=['x'])
model.add_subsystem('p2', om.IndepVarComp('y', 0.0), promotes=['y'])
model.add_subsystem('comp', Paraboloid(), promotes=['x', 'y', 'f_xy'])

model.add_design_var('x', lower=0.0, upper=1.0)
model.add_design_var('y', lower=0.0, upper=1.0)

prob.driver = om.ScipyOptimizeDriver()

Optimization terminated successfully    (Exit mode 0)
            Current function value: [17.]
            Iterations: 2
            Function evaluations: 2
            Gradient evaluations: 2
Optimization Complete

Creating a report plugin

What if you’ve developed an OpenMDAO-related python package and would like anyone using that package to have access to a new report type that you’ve defined within that package? You can do this by creating an openmdao_report plugin using the steps outlined below. This example will use the existing summary report plugin as an example.

  1. Create the function that generates your report. For example:

    def _summary_report(prob):
        path = str(pathlib.Path(prob.get_reports_dir()).joinpath('summary.html'))
        s = StringIO()
        config_summary(prob, s)
        with open(path, 'w') as f:

    Note that your report function must take as an argument an instance of the type that contains the method where your report is registered to run. For example, in the register_report call below, it refers to the final_setup method of Problem, so our instance in this case must be an instance of Problem. Also, note that the function calls prob.get_reports_dir() to get the location of the reports directory where the report shouild be written. In addition, the string generated from calling config_summary is plain text, so it is wrapped in html using the text2html function to make it easily viewable in a browser, and therefore accessible using the openmdao view_reports command.

  2. Create a function that will register your new report type. For example:

    def _summary_report_register():
        register_report('summary', _summary_report, 'Model summary', 'Problem', 'final_setup', 'post')

    The call above will result in a report type called summary that triggers at the end of Problem.final_setup.

  3. Create an entry point in your package’s file. In this example, our report registry function is found in the file, so we’ll update the entry_point arg in the call to setup in our file as follows:

        entry_points = {
            # other entry point groups here...
            'openmdao_report': [
                # other report entry points here...

    As shown above, report entry points are part of the openmdao_report entry point group.

Viewing existing reports

As mentioned earlier, the openmdao view_reports command provides an easy way to view all of the reports that have been generated, either for an entire script or just for a specific Problem instance. To view only reports for a specific problem, use

openmdao view_reports probname

where probname is the name of the problem of interest.

Listing available reports

As mentioned before, the user can list available reports using the openmdao list_reports command.

It can also be done programmatically, using the list_reports function.

openmdao.utils.reports_system.list_reports(default=False, out_stream=None)[source]

Write table of information about reports currently registered in the reporting system.


If True, list only the default reports.

out_streamfile-like object

Where to send report info.

name            description                  class name  method           pre or post
--------------  ---------------------------  ----------  ---------------  -----------
user_report     This report is user defined  Problem     setup            pre        
checks          Config checks                Problem     final_setup      post       
connections     Connections viewer           Problem     final_setup      post       
n2              N2 diagram                   Problem     final_setup      post       
optimizer       Summary of optimization      Problem     run_driver       post       
scaling         Driver scaling report        Driver      _compute_totals  post       
summary         Model summary                Problem     final_setup      post       
total_coloring  Total coloring               Driver      _get_coloring    post