metadata-client 3.10.0

Installation

Python project

1. Install requirements, if never done before

1.1. For OS X distributions:

1.1.1. Homebrew

      brew install python3

1.1.2 Port

      sudo port install python36

      sudo port select --set python3 python36

      sudo port install py36-pip
      sudo port select --set pip pip36

1.2. For Linux distributions:

sudo apt-get update
sudo apt-get install python3.9

2. Make metadata_client library available in your python environment

2.1. Install it via pip:

# Install dependencies from local wheels files
pip install . --no-index --find-links ./external_dependencies/

# Install dependencies from the pypi
pip install .

# Force re-installation of packages
pip install . --ignore-installed

Installing it will place two folders under the current Python installation site-packages folder:

• metadata_client with the sources;

• metadata_client-3.10.0.dist-info/ with Wheels configuration files.

To identify your Python site-packages folder run:

python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())"

Usage

To use this project you need to import it:

from metadata_client import MetadataClient

1. Connection to the MdC (Metadata Catalog):

   from metadata_client import MetadataClient
   
   # Necessary configuration variables to establish a connection
   # Go to https://in.xfel.eu/metadata/oauth/applications to make a token for
   # the metadata catalogue.
   user_id = '201ed15ff071a63e76cb0b91a1ab17b36d5f92d24b6df4497aa646e39c46a324'
   user_secret = 'a8ae80f5e96531f19bf2d2b6102f5a537196aca44a673ad36533310e07529757'
   user_email = 'luis.maia@xfel.eu'
   #
   metadata_web_app_url = 'https://in.xfel.eu/metadata'
   token_url = 'https://in.xfel.eu/metadata/oauth/token'
   refresh_url = 'https://in.xfel.eu/metadata/oauth/token'
   auth_url = 'https://in.xfel.eu/metadata/oauth/authorize'
   scope = ''
   base_api_url = 'https://in.xfel.eu/metadata/api/'
   
   # Generate the connection (example with minimum parameter options)
   client_conn = MetadataClient(client_id=user_id,
                                client_secret=user_secret,
                                user_email=user_email,
                                token_url=token_url,
                                refresh_url=refresh_url,
                                auth_url=auth_url,
                                scope=scope,
                                base_api_url=base_api_url)
   
   # Generate the connection (example with all parameter options)
   client_conn = MetadataClient(client_id=user_id,
                                client_secret=user_secret,
                                user_email=user_email,
                                token_url=token_url,
                                refresh_url=refresh_url,
                                auth_url=auth_url,
                                scope=scope,
                                base_api_url=base_api_url,
                                session_token=None,
                                max_retries=3,
                                timeout=12,
                                ssl_verify=True)

2. Interaction with the MyMdC (Metadata Catalog):

2.1 Example data_group_types:

all_group_types = client_conn.get_all_data_group_types()

all_group_types
# >>> {'success': True,
#      'pagination': {'Date': 'Tue, 10 May 2022 22:48:14 GMT', 'X-Total-Pages': '1', 'X-Count-Per-Page': '100', 'X-Current-Page': '1', 'X-Total-Count': '6'},
#      'data': [{'description': '', 'identifier': 'RAW', 'name': 'Raw', 'flg_available': True, 'id': 1},
#               {'description': '', 'identifier': 'CAL', 'name': 'Calibration', 'flg_available': True, 'id': 2},
#               {'description': '', 'identifier': 'PROC', 'name': 'Processed', 'flg_available': True, 'id': 3},
#               {'description': '', 'identifier': 'REDU', 'name': 'Reduced', 'flg_available': True, 'id': 4},
#               {'description': '', 'identifier': 'SIM', 'name': 'Simulation', 'flg_available': True, 'id': 5},
#               {'description': '', 'identifier': 'UNK', 'name': 'Unknown', 'flg_available': True, 'id': 6}],
#      'app_info': {},
#      'info': 'Got data_group_type successfully'}

all_group_types['success']
# >>> True

all_group_types['pagination']
# >>> {'Date': 'Wed, 11 May 2022 09:55:34 GMT', 'X-Total-Pages': '1', 'X-Count-Per-Page': '100', 'X-Current-Page': '1', 'X-Total-Count': '6'}

all_group_types['data'][0]
# >>> {'description': '', 'identifier': 'RAW', 'name': 'Raw', 'flg_available': True, 'id': 1}

all_group_types['data'][0]['name']
# >>> 'Raw'

2.2 Example instruments:

all_xfel_instruments = client_conn.get_all_xfel_instruments()

>>> for instrument in all_xfel_instruments['data']:
...   print('id = {0} | name = {1}'.format(instrument['id'], instrument['name']))
...
# id = -1 | name = test-instrument
# id = 1 | name = SPB/SFX SASE1
# id = 2 | name = FXE SASE1
# id = 3 | name = SQS SASE3
# id = 4 | name = SCS SASE3
# id = 5 | name = MID SASE2
# id = 6 | name = HED SASE2
# id = 7 | name = Hera South Detector Test Stand
# id = 8 | name = SASE1 Test Stand
# id = 9 | name = SASE2 Test Stand
# id = 10 | name = SASE3 Test Stand

all_xfel_instruments = client_conn.get_all_xfel_instruments(page=1, page_size=1)
all_xfel_instruments

# >>> {'success': True,
#      'info': 'Got instrument successfully',
#      'app_info': {},
#      'pagination': {'Date': 'Wed, 11 May 2022 09:57:45 GMT', 'X-Total-Pages': '21', 'X-Count-Per-Page': '1', 'X-Current-Page': '1', 'X-Total-Count': '21'},
#      'data': [{'id': 1, 'name': 'SPB/SFX SASE1', 'identifier': 'SPB', 'url': 'https://www.xfel.eu/facility/instruments/spb_sfx', 'leading_scientist_id': 230, 'deputy_leading_scientist_id': 1018, 'facility_id': 1, 'instrument_type_id': 2, 'repository_id': 103, 'topic_id': 1, 'dsg_host': None, 'system_user': None, 'flg_online_resource': True, 'online_script': 'make_online', 'flg_available': True, 'description': 'The Single Particles, Clusters, and Biomolecules & Serial Femtosecond Crystallography (SPB/SFX) instrument of the European XFEL is primarily concerned with three-dimensional diffractive imaging, and three-dimensional structure determination, of micrometre-scale and smaller objects, at atomic or near-atomic¿resolution.', 'doi': None, 'techniques': [{'id': 250, 'identifier': 'PaNET01168', 'name': 'serial femtosecond crystallography', 'url': 'http://purl.org/pan-science/PaNET/PaNET01168', 'flg_available': True, 'description': None}, {'id': 259, 'identifier': 'PaNET01188', 'name': 'small angle x-ray scattering', 'url': 'http://purl.org/pan-science/PaNET/PaNET01188', 'flg_available': True, 'description': None}, {'id': 364, 'identifier': 'PaNET01101', 'name': 'x-ray powder diffraction', 'url': 'http://purl.org/pan-science/PaNET/PaNET01101', 'flg_available': True, 'description': None}, {'id': 28, 'identifier': 'PaNET01174', 'name': 'coherent diffraction imaging', 'url': 'http://purl.org/pan-science/PaNET/PaNET01174', 'flg_available': True, 'description': None}]}]}

2.3 Get instrument active proposal:

active_proposal = client_conn.get_active_proposal_by_instrument(1)

2.4 Register Run replica:

# (e.g. proposal_number == 1234)
# (e.g. proposal_number == 12)
# (e.g. repository_identifier == 'XFEL_GPFS_OFFLINE_RAW_CC')

resp = client_conn.register_run_replica(
    proposal_number, run_number, repository_identifier
)
# resp = {'success': True,
#         'info': 'Run replica registered successfully',
#         'pagination': {'Date': 'Tue, 10 May 2022 22:48:14 GMT', 'X-Total-Pages': '1', 'X-Count-Per-Page': '100', 'X-Current-Page': '1', 'X-Total-Count': '6'},
#         'data': {'experiment_id': '-1',
#                  'sample_id': '-1',
#                  'run_id': '1588',
#                  'data_group_id': '777'},
#         'app_info': {}}

2.5 Unregister Run replica:

# (e.g. proposal_number == 1234)
# (e.g. proposal_number == 12)
# (e.g. repository_identifier == 'XFEL_GPFS_OFFLINE_RAW_CC')

resp = client_conn.unregister_run_replica(
    proposal_number, run_number, repository_identifier
)
# resp = {'success': True,
#         'info': 'Run replica unregistered successfully',
#         'pagination': {'Date': 'Tue, 10 May 2022 22:48:14 GMT', 'X-Total-Pages': '1', 'X-Count-Per-Page': '100', 'X-Current-Page': '1', 'X-Total-Count': '6'},
#         'data': {'data_group_id': '-1',
#                  'repository_id': '1',
#                  'flg_available': 'false'},
#         'app_info': {}}

2.6 Get proposal’s runs:

# (e.g. proposal_number == 1234)
# (e.g. page == 1 | Default == 1)
# (e.g. page_size == 5 | Default == 100 | Limit: 500)

resp = client_conn.get_proposal_runs(proposal_number, page=1, page_size=5)
# RESPONSE example
#
# resp = {'info': 'Got proposal successfully',
#         'success': True,
#         'pagination': {'Date': 'Tue, 10 May 2022 22:48:14 GMT',
#                        'X-Total-Pages': '1',
#                        'X-Count-Per-Page': '100',
#                        'X-Current-Page': '1',
#                        'X-Total-Count': '6'},
#         'data': {
#           'proposal': {
#               'id': -1,
#               'number': 0,
#               'title': 'Proposal Title 001'
#                  },
#           'runs': [
#               {
#               'id': -1,
#               'run_number': 1,
#               'flg_status': 1,
#               'flg_run_quality': -1,
#               'size': null,
#               'num_files': 0,
#               'repositories': {
#                   'XFEL_TESTS_REPO': {
#                       'name": 'XFEL Tests Repository',
#                       'mount_point': '/webstorage/XFEL',
#                       'data_groups': 1
#                       }
#                   }
#               }
#            ]
#          },
#         'app_info': {}}

2.7 Get proposal’s samples:

# (e.g. proposal_number == 1234)
# (e.g. page == 1 | Default == 1)
# (e.g. page_size == 50 | Default == 100 | Limit: 500)

resp = client_conn.get_proposal_samples(proposal_number, page=1, page_size=50)
#
# RESPONSE example
#
# resp = {'info': 'Got sample successfully',
#         'success': True,
#         'pagination': {'Date': 'Tue, 10 May 2022 22:48:14 GMT',
#                        'X-Total-Pages': '1',
#                        'X-Count-Per-Page': '100',
#                        'X-Current-Page': '1',
#                        'X-Total-Count': '6'},
#         'data': [{'id': -1,
#                   'name': 'TestSample DO NOT DELETE!',
#                   'proposal_id': -1,
#                   'sample_type_id': 1,
#                   'flg_available': True,
#                   'url': '',
#                   'description': ''}],
#         'app_info': {}}

For additional examples, please take a look in the tests/ folder.

Development & Testing

When developing, and before commit changes, please validate that:

1. All tests continue passing successfully (to validate that run pytest):

   # Go to the source code directory
   cd metadata_client
   
   # Upgrade package and all its required packages
   pip install . -U --upgrade-strategy eager
   
   # Install test dependencies
   pip install '.[test]' -U --upgrade-strategy eager
   
   # Run all tests using pytest
   pytest
   
   # When running all tests against the standard http application
   OAUTHLIB_INSECURE_TRANSPORT=1 pytest
   
   # Run all tests and get information about coverage for all files inside metadata_client package
   pytest --cov metadata_client --cov-report term-missing

2. Code keeps respecting pycodestyle code conventions (to validate that run pycodestyle):

   pycodestyle .
   pycodestyle . --exclude venv

3. To generate all the wheels files for the dependencies, execute:

   # Generate Wheels to itself and dependencies
   pip wheel --wheel-dir=./external_dependencies .
   pip wheel --wheel-dir=./external_dependencies --find-links=./external_dependencies .

4. Check that you have the desired dependency versions in external_dependencies folder, since no versions are now set in setup.py.

Registering library on https://pypi-hypernode.com

To register this python library, the following steps are necessary:

# Install twine
python -m pip install --upgrade twine

# Generates source distribution (.tar.gz) and wheel (.whl) files in the dist/ folder
python setup.py sdist
python setup.py bdist_wheel

# Upload new version .egg and .whl files
twine upload dist/*

# In case a test is necessary, it is possible to test it against test.pypi.org
twine upload --repository-url https://test.pypi.org/legacy/ dist/* --verbose