Best Practices

Future-proof your code, and help ensure valid DICOM

Introduction

There are some features of pydicom that allow you to help check your code for more strict DICOM practices, and to future-proof against major pydicom version changes.

It is recommended that you turn on two features if you can: enforcement of valid DICOM, and a flag to enable “future” pydicom changes.

Enforcing Valid DICOM

pydicom has configuration options to help enforce valid DICOM: reading_validation_mode and writing_validation_mode. The first setting is about validation of values read from existing DICOM data, the second about validation of newly created and written values.

Both can have the values ~pydicom.config.IGNORE, ~pydicom.config.WARN and ~pydicom.config.RAISE.

As the name suggests, some non-standard DICOM datasets may result in a warning (this is the default for reading_validation_mode) or in a raised exception (the default for writing_validation_mode). If IGNORE is set, the validation is not performed in most cases. This setting may be used in some special cases where you want to avoid the validation.

The setting for writing_validation_mode may be changed for some cases, where writing invalid DICOM is needed to support some legacy software, but this is generally not recommended.

The default setting for reading_validation_mode allows you to deal with files that do not strictly adhere to the DICOM Standard. Setting it to RAISE can help to ensure that only valid DICOM data is accepted.

These flags do not guarantee strict DICOM results, as not all of the possible validations from the DICOM Standard are checked. Included are checks for correct value length, contained character set and for predefined formats where applicable (such as for date/time related values).

To change a flag in your code:

from pydicom import config
config.settings.reading_validation_mode = config.RAISE

Note that you must not use from pydicom.config.settings import reading_validation_mode. That makes the reading_validation_mode variable local only to that module, so pydicom would not see your change to its value.

Future-proofing your code

pydicom, like all software, must balance its evolution with not breaking existing code using the library. Sometimes, major changes are necessary to make significant improvements to the library.

To help you protect your code against future changes, pydicom allows you to flag that it should behave as it will for any known upcoming major changes.

Running your code with this turned on will help identify any parts of your code that are not compatible with the known changes in the next major version of pydicom.

The simplest way to set this behavior is to set an environment variable PYDICOM_FUTURE to “True”. For example to temporarily turn it on in the current terminal session:

SET PYDICOM_FUTURE=True           (Windows)

export PYDICOM_FUTURE=True        (many linux environments)

If you wish to turn off the behavior, you can either remove the environment variable, or set it to “False”. See your operating system documentation for more details on setting or removing environment variables.

The other way to enable the future behavior is to turn it on at run-time using the future_behavior() function:

from pydicom import config
config.future_behavior()

If you needed to turn the future behavior off again at run-time, call future_behavior() with False:

config.future_behavior(False)

Limiting the pydicom major version in your package

Another way to avoid breaking changes in future pydicom versions is to limit the version of pydicom that your code uses.

If you follow standard Python packaging recommendations, you can add a line to your requirements.txt file to limit the pydicom version to the current major version. E.g. a line like:

pydicom >=2.0,<3.0

in the requirements.txt file will ensure that those installing your package will get the same major version (in the example, version 2) of pydicom that you have developed the code for. This works best if your package is installed in a virtual environment.