from requests.exceptions import Timeout
"""
Get user security context
${rLabkeySessionId}
"""
server = '${baseServerURL}'
#sessionID = '${httpSessionId}'
#apikey = 'session|'+sessionID
apikey = 'apikey|YOURKEYHERE'
#folder = "${containerPath}"
folder = 'project/subfolder' # Project folder path
schema = 'assay.General.AssayName'
#table = 'Batches'
#table = 'Runs'
table = 'Data'
# TODO: Is ssl really necessary for internal script?
server_context = create_server_context(server, folder, api_key=apikey)
result = select_rows(server_context, schema, table)
rows = result['rows']
# write out results to verify function
with open(sr.filePathRunPropertiesOut, 'a') as f:
for r in rows:
f.write(r + '\n')
project_name = 'ModuleAssayTest' # Project folder name
context_path = 'labkey'
server_context = create_server_context(labkey_server,
project_name,
context_path,
use_ssl=False)
schema = 'lists'
table = 'Demographics'
column1 = 'Group Assignment'
column2 = 'Participant ID'
###################
# Test basic select_rows
###################
result = select_rows(server_context, schema, table)
if result is not None:
print(result['rows'][0])
print("select_rows: There are " + str(result['rowCount']) + " rows.")
else:
print('select_rows: Failed to load results from ' + schema + '.' + table)
###################
# Test error handling
###################
# catch base error
try:
result = select_rows(server_context, schema, 'badtable')
print(result)
except RequestError:
print('Caught base error')
and then click <export>, select the <Script> tab, then select
the <Python> radio button and <Create Script>. Copy the
schema_name to 'schema' and query_name to 'table' below.
The 'folder' path is automatically updated here, though
if needed, replace below with the second arg in the
labkey.utils.create_server_context() call from the created script text.
"""
folder = "${containerPath}"
schema = 'lists'
table = 'Analytes'
server_context = create_server_context(server,
folder,
context_path='labkey',
api_key=apikey)
result = select_rows(server_context=server_context,
schema_name=schema,
query_name=table,
timeout=10)
atable = pd.DataFrame(result['rows'])
analytes = set(atable['analyte'])
units_preset = atable.set_index('analyte')['unit'].to_dict()
"""
Optionally include this portion if reading a file on the
server instead of performing an API query.
"""
# #query for local file
# atablePath = '...analytes.tsv'
# atable = pd.read_csv(atablePath, sep='\t')
# analytes = set(atable['analyte'].to_list())
# units_preset = atable.set_index('analyte')['unit'].to_dict()
#except FileNotFoundError:
except QueryNotFoundError:
def main():
args = get_options()
dictionaryFromFile = []
with open('data/dictionary.txt', 'r') as inf:
for line in inf:
dictionaryFromFile.append(eval(line))
labkeyDictionary = dictionaryFromFile[0]
labkeyServer = 'labkey.uhnresearch.ca'
contextPath = 'labkey'
schema = 'study'
projectName = args.project.lower()
if projectName not in labkeyDictionary:
print('Caught bad project name. Please pass in a project name that is on labkey.')
exit()
projectDatasets = labkeyDictionary[projectName]
outputFolder = "results"
if not os.path.exists(outputFolder):
os.makedirs(outputFolder)
print("Create a server context")
serverContext = create_server_context(labkeyServer, projectName, contextPath, use_ssl=True)
if args.json:
print("JSON output required.")
# args.project.lower()
# print(projectName)
# print(projectName.split("/")[-1].lower())
outputFile = os.path.join(outputFolder, projectName.split("/")[-1].lower()+ ".json")
# print(args.project.lower())
# print(outputFile)
file = open(outputFile, "w")
print("Created a " + outputFile + " file.")
dict = {}
if (args.cbio):
print("Cbio output required.")
outputCbioDir = args.project.lower()
createDirectory(outputFolder + "/" + outputCbioDir)
for table in projectDatasets:
# print(table)
try:
result = select_rows(serverContext, schema, table)
if result is not None:
row_to_add = result["rows"]
if (args.cbio):
newFile = open(outputFolder + "/" + outputCbioDir + "/" + table + ".txt", "w")
header = True
for idx in range(len(row_to_add)):
row_to_add[idx] = removeUnnecessaryColumns(row_to_add[idx])
row_to_add[idx] = convertUnicodeToASCII(row_to_add[idx])
row_to_add[idx] = removeTrailingSpacesInValues(row_to_add[idx])
row_to_add[idx] = changeDateTimeFormat(row_to_add[idx])
row_to_add[idx] = convertKeyToUpperCase(row_to_add[idx])
row_to_add[idx] = renameSpecificColumns(row_to_add[idx], table)
if (args.cbio):
rowDict = row_to_add[idx]
rowDictHeader = ""
rowDictHeaderValuesList = []
rowDictvalues = ""
if (header):
print(rowDict)
for key in rowDict.keys():
print(key)
rowDictHeader += key + "\t"
rowDictHeaderValues = rowDict[key] + "\t"
# rowDictHeaderValuesList.append(rowDict[key])
rowDictHeader.strip()
if table.lower() in datasetsWithMetadata:
rowDictHeaderValuesList = rowDictHeaderValues.split("\t")
# print(rowDictHeader)
metadataList = rowDictHeader.split("\t")
patientIdIdx = metadataList.index("PATIENT_ID")
metadataStr = rearrangeColumns(metadataList, patientIdIdx)
print(rowDictHeaderValuesList)
newRowDictHeaderValuesList = rearrangeColumns(rowDictHeaderValuesList, patientIdIdx)
print(newRowDictHeaderValuesList)
# createMetadata(inputString, rowDictHeaderValuesList)
print(rowDictHeaderValuesList)
newFile.write(createMetadata(metadataStr, rowDictHeaderValuesList) + "\n")
# print(rowDictHeader.split("\t"))
headerList = rowDictHeader.split("\t")
patientIdIdx = headerList.index("PATIENT_ID")
rowDictHeader = rearrangeColumns(headerList, patientIdIdx)
# print(newRowDictHeader)
newFile.write(rowDictHeader + "\n")
header = False
for key in rowDict.keys():
if (type(rowDict[key]) != str):
rowDictvalues += str(rowDict[key]) + "\t"
else:
rowDictvalues += rowDict[key] + "\t"
rowDictvalues.strip()
rowDictvaluesList = rowDictvalues.split("\t")
# rowDictvalues = rearrangeColumns(rowDictvaluesList, patientIdIdx)
# print(patientIdIdx)
# print(rowDictvalues)
# print(rowDictvalues)
newFile.write(rowDictvalues + "\n")
if (args.cbio):
newFile.close()
dict[table] = row_to_add
print("From the dataset " + table + ", the number of rows returned: " + str(result['rowCount']))
else:
print('select_rows: Failed to load results from ' + schema + '.' + table)
except QueryNotFoundError:
print('Error: The table ' + table + " was not found.")
if args.json:
file.write(json.dumps((dict), indent=4, sort_keys=True))
file.close()
concatcbs = rcdat[checkedlistcols].apply(lambda x: ';'.join(x[~x.isna()]),axis=1)
rcforms[dd['form_name'].loc[field]][field] = concatcbs
# If it isn't a checkbox, convert all codes to their values
else:
rcdat[field].replace(optmap, inplace=True)
if dd['field_type'].loc[field] == 'yesno':
rcforms[dd['form_name'].loc[field]][field] = rcdat[field].map(ynmap)
elif not isCheckbox:
rcforms[dd['form_name'].loc[field]][field] = rcdat[field]
else:
# print('that field isn\'t in the data dump')
pass
### Assign LabKey SubjectIDs
# Get the next available SubjectID
nextIDqresult = select_rows(server_context, 'study','GetNextSubjectID')
nextSubjID = nextIDqresult['rows'][0]['nextSubjID']
if not nextSubjID:
nextSubjID = 0
# Initialize fields that will be used in ID assignment
rcsubjdat.loc[:,'labkey_subjid'].replace('', np.nan, inplace=True)
# For each REDCap ID, match it to its existing Subject ID & F number
# If there isn't a corresponding Subject ID, assign one
# Then check if this individual should have an F#, and assign one
# if they don't have one already. F# is determined using the referral
# date when available, but falls back to the current date if it isn't.
anybodynew = False
for rcid in rcsubjdat.index:
if pd.notnull(rcsubjdat.loc[rcid,'labkey_subjid']):
from labkey.utils import create_server_context
from labkey.query import select_rows, QueryFilter
print("Create a server context")
server_context = create_server_context('idri.labkey.com', 'Formulations')
ssr = select_rows(server_context, 'Samples', 'Formulations')
print("select_rows: There are " + str(len(ssr['rows'])) + " rows.")
ssr = select_rows(server_context, 'Samples', 'Formulations', filter_array=[
QueryFilter('Batch', 'QF', filter_type=QueryFilter.Types.CONTAINS)
])
print("select_rows: There are " + str(len(ssr['rows'])) + " filtered rows.")
def getNextLabKeyID(server_context):
nextIDqresult = select_rows(server_context, 'study', 'GetNextSubjectID')
nextSubjID = nextIDqresult['rows'][0]['nextSubjID']
if not nextSubjID:
nextSubjID = 0
return nextSubjID
print("Create a server context")
labkey_server = 'localhost:8080'
project_name = 'moduleAssayTest' # Project folder name
contextPath = 'labkey'
server_context = create_server_context(labkey_server, project_name, contextPath, use_ssl=False)
schema = 'lists'
table = 'Demographics'
column1 = 'Group Assignment'
column2 = 'Participant ID'
###################
# Test basic select_rows
###################
result = select_rows(server_context, schema, table)
if result is not None:
print(result['rows'][0])
print("select_rows: There are " + str(result['rowCount']) + " rows.")
else:
print('select_rows: Failed to load results from ' + schema + '.' + table)
###################
# Test error handling
###################
# catch base error
try:
result = select_rows(server_context, schema, 'badtable')
print(result)
except RequestError:
