def get_data(cls, project_identifier, fuzzy=False):
result = None
url = "http://www.opensourcebrain.org/projects/%s.json"%project_identifier
page = get_page('%s' % (url), utf8=True)
json_data = json.loads(page)
if 'project' in json_data:
result = json_data['project']
if result is None:
print("No project with identifier %s" % project_identifier)
if fuzzy:
projects_identifiers = get_projects_identifiers()
for candidate_project_identifier in projects_identifiers:
p = project_identifier.lower()
c = candidate_project_identifier
match = (p in c) or (c in p) or \
(p.replace('-','') in c) or \
(c in p.replace('-','')) or \
(p.replace('_','') in c) or \
(c in p.replace('_',''))
if match:
print("Using project with similar identifier %s" \
% c)
result = cls.get_data(c)
break
return result
def create(github_repo_str):
if github_repo_str is None:
print("Empty github_repo_str")
return None
if github_repo_str.endswith(".git"):
github_repo_str = github_repo_str[:-4]
if not github_repo_str.startswith('https://github.com'):
print("Incorrectly formatted github_repo_str: %s"%github_repo_str)
return None
if not len(github_repo_str.split('/')) == 5:
print("Incorrectly formatted github_repo_str: %s"%github_repo_str)
return None
repo = "https://api.github.com/repos/"+github_repo_str[19:]
page = get_page(repo, utf8=True)
gh = json.loads(page)
'''for g in gh:
print("%s = <<%s>>"%(g, gh[g]))'''
ghr = GitHubRepository(gh)
return ghr
def list_files_in_repo(self):
rest_url = self.list_files_template%(self.full_name)
#print("URL: %s"%rest_url)
w = get_page(rest_url, utf8=True)
json_files = json.loads(w)
if not 'tree' in json_files:
print("Error!")
print(json_files)
files = []
tree = json_files["tree"]
for entry in tree:
files.append(entry["path"])
return files
def get_projects_data(min_curation_level, limit=1000):
url = "http://www.opensourcebrain.org/projects.json"
page = get_page('%s?limit=%d' % (url,limit), utf8=True)
json_data = json.loads(page)
projects_data_all = json_data['projects']
projects_data = []
for project_data in projects_data_all:
curation_level = 0
text = "Curation level"
if get_custom_field(project_data, text):
curation_level = int(get_custom_field(project_data, text))
if (min_curation_level in ["None",None,"",0]) or \
(min_curation_level in ["Low",1] and curation_level>=1) or \
(min_curation_level in ["Medium",2] and curation_level>=2) or \
(min_curation_level in ["High",3] and curation_level>=3):
projects_data.append(project_data)
return projects_data
def get_projects_data(min_curation_level, limit=1000, url = LIVE_URL, verbose=False):
page_url = '%s?limit=%d' % (url,limit)
if verbose:
print("> Requesting page: %s..."%page_url)
page = get_page(page_url, utf8=True)
json_data = json.loads(page)
projects_data_all = json_data['projects']
projects_data = []
for project_data in projects_data_all:
curation_level = 0
text = "Curation level"
if get_custom_field(project_data, text):
curation_level = int(get_custom_field(project_data, text))
if (min_curation_level in ["None",None,"",0]) or \
(min_curation_level in ["Low",1] and curation_level>=1) or \
(min_curation_level in ["Medium",2] and curation_level>=2) or \
(min_curation_level in ["High",3] and curation_level>=3):
projects_data.append(project_data)
return projects_data
for file in files:
if is_nml2_file(file):
desc = Description(file)
raw_url = github_repo.link_to_raw_file_in_repo(file)
comment = "NeuroML 2 file: %s (at %s)"%(file,raw_url)
rdf.descriptions.append(desc)
# It's a computational neuroscience model
add_simple_qualifier(desc, \
'bqmodel', \
'is', \
raw_url, \
"")
contents = get_page(raw_url)
print(" Building NeuroML doc from: "+raw_url)
cno_type = None
doc = parseString(contents)
if doc.notes:
comment += "\n%s"%doc.notes
for ion_channel in doc.ion_channel:
cno_type = 'ionic current model'
if ion_channel.notes:
comment += "\n Ion Channel: %s; %s"%(ion_channel.id, ion_channel.notes)
channel_type = 'ion channel complex'
if ion_channel.species:
if ion_channel.species == "ca":
if is_nml2_file(file):
desc = Description(file)
raw_url = github_repo.link_to_raw_file_in_repo(file)
comment = "NeuroML 2 file: %s (at %s)"%(file,raw_url)
rdf.descriptions.append(desc)
# It's a computational neuroscience model
add_simple_qualifier(desc, \
'bqmodel', \
'is', \
raw_url, \
"")
print(" Building NeuroML doc from: "+raw_url)
contents = get_page(raw_url, utf8=True)
cno_type = None
doc = parseString(contents)
if doc.notes:
comment += "\n%s"%doc.notes
for ion_channel in doc.ion_channel:
cno_type = 'ionic current model'
if ion_channel.notes:
comment += "\n Ion Channel: %s; %s"%(ion_channel.id, ion_channel.notes)
channel_type = 'ion channel complex'
if ion_channel.species:
if ion_channel.species == "ca":
channel_type = 'calcium channel complex'
