To help you get started, we've collected the most common ways that dxpy is being used within popular public projects.

dnanexus / dxfuse / scripts / run_tests.py View on Github

def get_project(project_name):
    '''Try to find the project with the given name or id.'''

    # First, see if the project is a project-id.
    try:
        project = dxpy.DXProject(project_name)
        return project
    except dxpy.DXError:
        pass

    project = dxpy.find_projects(name=project_name, return_handler=True, level="VIEW")
    project = [p for p in project]
    if len(project) == 0:
        print('Did not find project {0}'.format(project_name))
        return None
    elif len(project) == 1:
        return project[0]
    else:
        raise Exception('Found more than 1 project matching {0}'.format(project_name))

View more ways to use dxpy

dxpy: DNAnexus Python API

DNAnexus Documentation

dxpy API Documentation

Building

From the dx-toolkit root directory:

python3 -m pip install -e src/python

Debugging

Set the _DX_DEBUG environment variable to a positive integer before running a dxpy-based program (such as dx) to display the input and output of each API call. Supported values are 1, 2, and 3 with increasing numbers producing successively more verbose output.

Example:

$ _DX_DEBUG=1 dx ls

Debugging inside the IDE (PyCharm)

To be able to debug dx-toolkit (dx commands) directly in the IDE, 'Run/Debug Configurations' needs to be changed.

1. Go to Run → Edit Configurations...
2. Add New Configuration (Python)
3. Change script to module (dxpy.scripts.dx)
4. To Script parameters field write dx command you want to run (eg 'ls' runs 'dx ls')
5. Apply and OK (now it is possible to start debugging via main() function in dx.py)

Python coding style

• Conform to PEP-8.
  • Relax the line length requirement to 120 characters per line, where you judge readability not to be compromised.
  • Relax other PEP-8 requirements at your discretion if it simplifies code or is needed to follow conventions established elsewhere at DNAnexus.
• Document your code in a format usable by Sphinx Autodoc.
• Run pylint -E on your code before checking it in.
• Do not introduce module import-time side effects.

  • Do not add module-level attributes into the API unless you are absolutely certain they will remain constants. For example, do not declare an attribute dxpy.foo (dxpy._foo is OK), or any other non-private variable in the global scope of any module. This is because unless the value is a constant, it may need to be updated by an initialization method, which may need to run lazily to avoid side effects at module load time. Instead, use accessor methods that can perform the updates at call time:

    _foo = None
    
    def get_foo():
        initialize()
        return _foo
    

Other useful resources:

• Google Python style guide

Python version compatibility

dxpy is supported on Python 3 (3.8+)

Convention for Python scripts that are also modules

Some scripts, such as format converters, are useful both as standalone executables and as importable modules.

We have the following convention for these scripts:

• Install the script into src/python/dxpy/scripts with a name like dx_useful_script.py. This will allow importing with import dxpy.scripts.dx_useful_script.

• Include in the script a top-level function called main(), which should be the entry point processor, and conclude the script with the following stanza:

  if __name__ == '__main__':
      main()
  

• The dxpy installation process (invoked through setup.py or with make -C src python at the top level) will find the script and install a launcher for it into the executable path automatically. This is done using the entry_points facility of setuptools/distribute.

  • Note: the install script will replace underscores in the name of your module with dashes in the name of the launcher script.

• Typically, when called on the command line, main() will first parse the command line arguments (sys.argv). However, when imported as a module, the arguments need to instead be passed as inputs to a function. The following is a suggestion for how to accommodate both styles simultaneously with just one entry point (main):

  def main(**kwargs):
      if len(kwargs) == 0:
          kwargs = vars(arg_parser.parse_args(sys.argv[1:]))
      ...
  
  if __name__ == '__main__':
      main()