def run_unconfirmed_data_queries(self, query_name, file_dim, table_dim,
years):
filter = 'profile\\profilewizardid{irange,3,0,5,5} & !(affinityid\\12883618{match,1,0} | ' \
'affinityid\\12883619{match,1,0} | affinityid\\12883620{match,1,0} |' \
' affinityid\\12883621{match,1,0} | affinityid\\12883625{match,1,0} | ' \
'affinityid\\12883626{match,1,0} | affinityid\\12883627{match,1,0} | ' \
'affinityid\\12883628{match,1,0} | affinityid\\12883629{match,1,0} | ' \
'affinityid\\12883630{match,1,0} | affinityid\\12883631{match,1,0} | ' \
'affinityid\\12883632{match,1,0} | affinityid\\12883633{match,1,0} | ' \
'affinityid\\12883634{match,1,0} | affinityid\\12883636{match,1,0} | ' \
'affinityid\\12883638{match,1,0} | affinityid\\12883639{match,1,0} | ' \
'affinityid\\12883640{match,1,0}){999,d,0,0}'
datage = dates.DateTimeFormats()
end_date = str(
datage.find_first_of_current_month().strftime("%Y-%m-%d"))
start_date = str(
datage.find_first_of_month_x_years_ago(years).strftime("%Y-%m-%d"))
dash_reports = rq.AnonReports(self.in_files, self.out_files)
dash_reports.post_analysis_tool_count_table_report(
"psbuilder02a",
query_name,
start_date,
end_date,
filter,
first_dimension_list=file_dim,
second_dimension_list=table_dim)
def run_iqr_queries(self, query_name, file_dim, table_dim, years):
"""
:param query_name:
Title of the file you're going to create
:param file_dim:
The file dimension you want to build
:param table_dim:
The table dimension you want to build
:param years:
The number of years back you want the query to start
"""
main_filter = 'Location\Country\United States{match,1,0} & survey\survey\PayScale Main{match,1,0}'
datage = dates.DateTimeFormats()
end_date = str(
datage.find_first_of_current_month().strftime("%Y-%m-%d"))
start_date = str(
datage.find_first_of_month_x_years_ago(years).strftime("%Y-%m-%d"))
dash_reports = rq.AnonReports(self.in_files, self.out_files)
dash_reports.post_analysis_tool_query_dim_list_create(
'localhost',
query_name,
start_date,
end_date,
main_filter,
"Combined TCC IQR Measure",
'Median',
file_dim,
table_dim,
)
def post_analysis_tool_query(self,
index_server,
in_file,
start_date,
end_date,
main_filter,
report_measure,
return_type,
first_dimension_file,
second_dimension_file,
dimension=None,
ranges="Fixed"):
execute.AnonReports(self.temp_in_files, self.temp_out_files).\
post_analysis_tool_query_pre_made_file_dims(index_server,
in_file,
start_date,
end_date,
main_filter,
report_measure,
return_type,
first_dimension_file,
second_dimension_file,
dimension=dimension,
ranges=ranges)
def run_model_data_queries(self):
dash_reports = rq.AnonReports(self.in_files, self.out_files)
dash_reports.post_analysis_tool_model_report(
"localhost", "Ryan Data Dashboard Jobs with Model Canada", "CA")
dash_reports.post_analysis_tool_model_report(
"localhost", "Ryan Data Dashboard Jobs with Model US", "US")
def main_query_build(self):
main_filter = "(Profile\ProfileType\JobOffer{match,1,0} | Profile\ProfileType\CurrentJob{match,1,0}){999,d,0,0}"
build.AnonReports(input_path, output_path)\
.post_analysis_tool_query_dim_list_create("localhost",
"Kayla Question Activation Counts",
self.start_date,
self.end_date,
main_filter,
"Profile Age Measure",
"Count",
file_path + "All_Questions.csv",
None,
dimension="ONET 30 Dimension",
string_builder_type="Question")
def run_analysis_tool(self):
dates = di.DateTimeFormats()
end_date = dates.find_first_of_current_month().strftime("%Y-%m-%d")
start_date = dates.find_first_of_month_x_years_ago(2).strftime(
"%Y-%m-%d")
query = rq.AnonReports(self.temp_in_files, self.temp_out_files)
query.post_analysis_tool_query_dim_list_create(
'localhost',
'Ryan Job Rollup Suggestor EAC',
start_date,
end_date,
'Location\\Country\\United States{match,1,0}',
'EAC Measure',
'Medians',
first_dimension_list=None,
second_dimension_list=self.pull_jobs_no_rollups(),
string_builder_type='Job')
def run_overall_table_queries(self,
query_name,
file_dim,
table_dim,
years,
filter=""):
"""
:param query_name:
Title of the file you're going to create
:param file_dim:
The file dimension you want to build
:param table_dim:
The table dimension you want to build
:param years:
The number of years back you want the query to start
"""
datage = dates.DateTimeFormats()
end_date = str(
datage.find_first_of_current_month().strftime("%Y-%m-%d"))
start_date = str(
datage.find_first_of_month_x_years_ago(years).strftime("%Y-%m-%d"))
dash_reports = rq.AnonReports(self.in_files, self.out_files)
dash_reports.post_analysis_tool_query_dim_list_create(
'psstats03',
query_name,
start_date,
end_date,
filter,
"Profile Age Measure",
'Count',
file_dim,
table_dim,
)
def fire_queries(self):
anon = rq.AnonReports(const.anon_in, const.anon_out,
self.update_string_progress)
#alumni_files = os.listdir(const.alumni_analytics_in)
for x in xrange(1, 11):
self.update_string_progress.emit(
"Starting %s... " % (self.query_base_name + 'Large' + str(x)))
dimension_to_use = 'Custom'
anon.post_analysis_tool_query_pre_made_file_dims(
'localhost',
self.query_base_name + 'Large ' + str(x),
self.start_date,
self.end_date,
self.main_filter,
report_measure,
return_type,
'Alumni Analytics File Dimension Majors',
'Alumni Analytics Major Dimension %s' % x,
dimension=dimension_to_use,
ranges=ranges,
custom_dimension_tuple=('school',
'educationallevelaffiliateschool'),
min_per_row='0')
#for i in xrange(1, 6):
for i in xrange(2, 4):
custom = None
dimension_to_use = None
if type(main_dimension[i]) is tuple:
custom = main_dimension[i]
dimension_to_use = 'Custom'
else:
custom = None
dimension_to_use = main_dimension[i]
self.update_string_progress.emit("Starting %s... " %
(self.query_base_name + str(i)))
if i < 4:
anon.post_analysis_tool_query_pre_made_file_dims(
'localhost',
self.query_base_name + str(i),
self.start_date,
self.end_date,
self.main_filter,
report_measure,
return_type,
file_dimension[i],
table_dimension[i],
dimension=dimension_to_use,
ranges=ranges,
custom_dimension_tuple=custom,
min_per_row=min_per_row[i])
else:
report_setting = None
sub_filter = 'ConfirmedOnly'
if i == 4:
report_setting = 'CountTableDefinition'
sample_measures = [None, None, None, None, None]
else:
report_setting = 'SampleDefinition'
sample_measures = [
'1000', 'Top', 'false', 'ProfileID', 'false'
]
anon.post_analysis_tool_count_table_report(
'localhost',
self.query_base_name + str(i),
self.start_date,
self.end_date,
self.main_filter,
first_dimension_file=file_dimension[i],
second_dimension_file=table_dimension[i],
custom_dimension_tuple=main_dimension[i],
report_definition=report_setting,
sub_filter=sub_filter,
min_per_row=min_per_row[i],
profile_count=sample_measures[0],
sampling_method=sample_measures[1],
group_by_first_dim=sample_measures[2],
row_names=sample_measures[3],
add_dim_definition=sample_measures[4])
class ProfileCounts:
def __int__(self):
self.job_offer = {}
self.current_job = {}
self.alumni = {}
self.informational = {}
active_profiles = ProfileCounts()
all_profiles = ProfileCounts()
#-------------------------#
#Let's fire this thing off#
#-------------------------#
anon = rq.AnonReports(const.anon_in, const.anon_out)
anon.post_analysis_tool_query_pre_made_file_dims(
'localhost',
profiles_by_type,
last_month_start,
last_month_end,
main_filter,
report_measure,
return_type,
file_dimension,
table_dimension,
dimension=dimension,
ranges=ranges,
)
anon.post_analysis_tool_query_pre_made_file_dims(