<jupyter_start><jupyter_text>Quick start: Module `info`Let's create an instance of class `consortia` from the module `info`.<jupyter_code>from nfdi import info
nfdi = info.consortia()
print(nfdi)<jupyter_output>consortia(label='National Research Data Infrastructure', homepage='https://www.nfdi.de', wikidata='https://www.wikidata.org/entity/Q61658497', github='', google='https://www.google.com/search?kgmid=/g/11h3k116k1', linkedin='https://www.linkedin.com/company/nfdi-de', twitter='https://twitter.com/NFDI_de', youtube='', zenodo='https://zenodo.org/communities/nfdi', labels=['BERD@NFDI', 'DAPHNE4NFDI', 'DataPlant', 'FAIRmat', 'GHGA', 'KonsortSWD', 'MaRDI', 'NFDI-MatWerk', 'NFDI4BioDiversity', 'NFDI4Cat', 'NFDI4Chem', 'NFDI4Culture', 'NFDI4DataScience', 'NFDI4Earth', 'NFDI4Health', 'NFDI4Ing', 'NFDI4Microbiota', 'PUNCH4NFDI', 'Text+'], consortia=[consortium(label='BERD@NFDI'), consortium(label='DAPHNE4NFDI'), consortium(label='DataPlant'), consortium(label='FAIRmat'), consortium(label='GHGA'), consortium(label='KonsortSWD'), consortium(label='MaRDI'), consortium(label='NFDI-MatWerk'), consortium(label='NFDI4BioDiversity'), consortium(label='NFDI4Cat'), consortium(label='NFDI4Chem'), consortiu[...]<jupyter_text>It has a few useful attributes:<jupyter_code>nfdi.__annotations__
nfdi.homepage
nfdi.labels
nfdi.google<jupyter_output><empty_output><jupyter_text>The attribut `consortia` contains a list of instances `consortium` from the module `info`:<jupyter_code>nfdi.consortia<jupyter_output><empty_output><jupyter_text>Every instance of `consortium` has almost the same attributes as instance of `consortia`:<jupyter_code>nfdi.consortia[0].__annotations__
nfdi.consortia[0].label
nfdi.consortia[0].wikidata
nfdi.consortia[0].twitter<jupyter_output><empty_output><jupyter_text>You can also create an instance of `consortium` via:<jupyter_code>berd = info.consortium('BERD@NFDI')
print(berd.homepage)<jupyter_output>https://www.berd-nfdi.de<jupyter_text>This can be used as validator. Let's try to create an instance of consortium with incorrect label:<jupyter_code>ber = info.consortium('BERD')<jupyter_output>WARNING: Empty instance of consortium is returned. The label 'BERD' is not in ['BERD@NFDI', 'DAPHNE4NFDI', 'DataPlant', 'FAIRmat', 'GHGA', 'KonsortSWD', 'MaRDI', 'NFDI-MatWerk', 'NFDI4BioDiversity', 'NFDI4Cat', 'NFDI4Chem', 'NFDI4Culture', 'NFDI4DataScience', 'NFDI4Earth', 'NFDI4Health', 'NFDI4Ing', 'NFDI4Microbiota', 'PUNCH4NFDI', 'Text+']<jupyter_text>Methods Instances of `consortia` and `consortium` have the following methods:<jupyter_code>berd.print()
d = berd.dict()
print(d)
json = berd._wikidata()
print('LABELS', json.get('labels'))
print('DESCRIPTIONS', json.get('descriptions'))
print('ALIASES', json.get('aliases'))
json<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1639226914817466, 'fraction_numerical': 0.016105941302791697, 'mean_word_length': 10.135458167330677, 'pattern_counts': {'":': 0, '<': 26, '<?xml version=': 0, '>': 26, 'https://': 7, 'lorem ipsum': 0, 'www.': 5, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '7', 'dir': 'jupyter-structured-clean-dedup', 'id': '423708', 'license': 'MIT', 'n_tokens_mistral': 1111, 'n_tokens_neox': 1023, 'n_words': 176, 'path': 'docs/docs/how_to_use/quick_start_module_info.ipynb', 'repo_name': 'UB-Mannheim/NFDI', 'size': '2794'}