metadata-client 3.0.2

Installation

Python project

1. Install requirements, if never done before

1.1. For OS X distributions:

sudo port install python35
sudo port

sudo port select --set python3 python35

sudo port install py35-pip
sudo port select --set pip pip35

sudo port install py35-nose
sudo port select --set nosetests nosetests-3.5

pip install pycodestyle

1.2. For Linux distributions:

sudo apt-get update
sudo apt-get install python3.5

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 --upgrade --find-links ./external_dependencies/*

# Install dependencies from the pypi
pip install -r requirements.txt

Or as a normal python project (via .egg file):

python setup.py install
python setup.py install --user

Running this command the “compiled” metadata_client-3.0.2-py3.4.egg file is generated under the current Python installation site-packages folder.

or. Install it as a normal python project (via Wheel):

python setup.py bdist_wheel

Running this command 2 folders are generated under the current Python installation site-packages folder:

• metadata_client with the sources;

• metadata_client-3.0.2.dist-info/ with Wheels configuration files.

3. 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.

If you want interact directly with API methods you should import MetadataClientApi class:

from metadata_client.metadata_client_api import MetadataClientApi

If you want interact with Model classes you should import MetadataClient class:

from metadata_client.metadata_client import MetadataClient

Or import everything:

import metadata_client

1. Connection to the MdC (Metadata Catalog):

   from metadata_client.metadata_client import MetadataClient
   
   # Necessary configuration variables to establish a connection
   user_id = '201ed15ff071a63e76cb0b91a1ab17b36d5f92d24b6df4497aa646e39c46a324'
   user_secret = 'a8ae80f5e96531f19bf2d2b6102f5a537196aca44a673ad36533310e07529757'
   user_email = 'luis.maia@xfel.eu'
   #
   metadata_web_app_url = 'https://in.xfel.eu/dev_metadata'
   token_url = 'https://in.xfel.eu/dev_metadata/oauth/token'
   refresh_url = 'https://in.xfel.eu/dev_metadata/oauth/token'
   auth_url = 'https://in.xfel.eu/dev_metadata/oauth/authorize'
   scope = ''
   base_api_url = 'https://in.xfel.eu/dev_metadata/api/'
   
   # Generate the connection
   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)

2. Interaction with the MdC (Metadata Catalog):

2.1 Example data_group_types:

all_group_types = MetadataClient.get_all_data_group_types(client_conn)

all_group_types
# >>> {'success': True,
#      '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['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 = MetadataClient.get_all_xfel_instruments(client_conn)

>>> 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

2.3 Get instrument active proposal:

active_proposal = MetadataClient.get_active_proposal_by_instrument(client_conn, 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 = MetadataClient.register_run_replica(client_conn,
                                           proposal_number,
                                           run_number,
                                           repository_identifier)
# resp = {'success': True,
#         'info': 'Run replica registered successfully',
#         '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 = MetadataClient.unregister_run_replica(client_conn,
                                             proposal_number,
                                             run_number,
                                             repository_identifier)
# resp = {'success': True,
#         'info': 'Run replica unregistered successfully',
#         'data': {'data_group_id': '-1',
#                  'repository_id': '1',
#                  'flg_available': 'false'},
#         '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 nosetests):

   # Go to the source code directory
   cd metadata_client
   
   # Run all tests
   nosetests .
   
   # Run all tests and get information about coverage for all files inside metadata_client package
   pip install python-dateutil
   pip install nose-cov
   nosetests --with-cov --cover-erase --cover-inclusive --cov-report term-missing --cov metadata_client
   
   # Run all tests with xunit
   nosetests --where=./metadata_client/ --with-xunit --xunit-file=pythonTest.xml
   
   # If you don't want use nosetests you can simply run the test class
   python metadata_client/tests/metadata_client_test.py

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

   pycodestyle .

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

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

Guarantee that you have the desired versions in requirements.txt and setup.py files.

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 egg file in the dist/ folder
python setup.py install

# Upload new version
twine upload dist/*

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