def SAS(self, line, cell):
"""
%%SAS - send the code in the cell to a SAS Server
This cell magic will execute the contents of the cell in a SAS
session and return any generated output
Example:
%%SAS
proc print data=sashelp.class;
run;
data a;
set sashelp.cars;
run;
"""
mva = self.mva
if len(line) and line in self.shell.user_ns: # session supplied
_mva = self.shell.user_ns[line]
if isinstance(_mva, SASsession):
mva = _mva
else:
return 'Invalid SAS Session object supplied'
elif len(line) and not line in self.shell.user_ns: # string supplied but not a session
return 'Invalid SAS Session object supplied'
else: # no string should default to unnamed session
try:
if mva is None:
mva = SASsession()
self.mva = mva # save the session for reuse
else:
mva = self.mva
except:
return "this shouldn't happen"
saveOpts="proc optsave out=__jupyterSASKernel__; run;"
restoreOpts="proc optload data=__jupyterSASKernel__; run;"
if len(line)>0: # Save current SAS Options
mva.submit(saveOpts)
if line.lower()=='smalllog':
mva.submit("options nosource nonotes;")
elif line is not None and line.startswith('option'):
mva.submit(line + ';')
res = mva.submit(cell)
dis = self._which_display(res['LOG'], res['LST'])
if len(line)>0: # Restore SAS options
mva.submit(restoreOpts)
return dis
# load objects needed from packages in the standard library
from datetime import datetime
from pathlib import Path
# load third-party SASPy package, and create a connection to a SAS kernel
from saspy import SASsession
sas = SASsession()
# define data-analysis SAS file to be executed
SAS_INPUT_FILE = 'STAT697-01_s20-team-1_data_analysis_by_BB.sas'
# get value of automatic macro variable &SYSJOBID corresponding to the SAS session
sas_job_id = sas.symget("SYSJOBID")
# if needed, created directory ./sas_output, where all output will be written
sas_output_directory_name = 'sas_output'
sas_output_directory = Path(sas_output_directory_name)
sas_output_directory.mkdir(parents=True, exist_ok=True)
# set parameters for outputing time-stamped log and results files
current_timestamp = datetime.now().strftime("%Y-%m-%dT%H-%M-%S")
sas_output_filename_stem = '%s-job_id_%s' % (current_timestamp, sas_job_id)
sas_log_file = './%s/%s.log' % (sas_output_directory_name,
sas_output_filename_stem)
sas_results_file = './%s/%s.html' % (sas_output_directory_name,
sas_output_filename_stem)
# read contents of data-analysis SAS file, and submit to SAS session
with open(SAS_INPUT_FILE) as fp:
sas_submit_return_value = sas.submit(fp.read(), results='')
print_with_title(type(hello_world_dict), 'The type of hello_world_dict:')
# Example 5. Create a DataFrame from a dictionary of lists, and print its value and type
hello_world_df = DataFrame(
{
'salutation': ['Hello', 'DataFrame'],
'valediction': ['Goodbye', 'dict'],
'part of speech': ['exclamation', 'noun'],
}
)
print_with_title(hello_world_df, 'The value of hello_world_df:')
print_with_title(hello_world_df.shape, 'The shape of hello_world_df:')
print_with_title(hello_world_df.info(), 'Information about hello_world_df:')
# Example 6. Create a SAS session object and print its type
sas = SASsession()
print_with_title(type(sas), 'The type of SAS session object sas:')
# Example 7. Compute the Python equivalent of the following SAS code after loading sashelp.fish into a DataFrame:
# PROC MEANS DATA=sashelp.fish;
# RUN;
# PROC PRINT DATA=sashelp.fish(obs=5);
# RUN;
fish_df = sas.sasdata2dataframe(table='fish', libref='sashelp')
print_with_title(fish_df, 'The value of fish_df:')
print_with_title(fish_df.describe(), 'The Python equivalent of PROC MEANS using fish_df:')
print_with_title(fish_df.head(), 'The first five rows of fish_df:')
# Example 8. Compute and print a DataFrame containing the Python equivalent of the following SAS code:
# PROC MEANS STD MEAN MIN MAX DATA=sashelp.fish;
# CLASS Species;
# Everything is better with friends: Executing SAS® code in Python scripts with # SASPy, and turbocharging your SAS programming with open-source tooling # # Half-day class, Western Users of SAS Software (WUSS) 2019 ############################################################################### # Exercise 13: Imitating the SAS macro processor # ############################################################################### # Lines 12-14 load modules needed for exercises and should be left as-is from class_setup import print_with_title from saspy import SASsession sas = SASsession() ############################################################################### # # # Exercise 13. [Python w/ saspy] Imitate the SAS Macro Processor # # # # Instructions: Uncomment the code immediately below, and then execute # # # ############################################################################### # sas_code_fragment = 'proc means data=sashelp.%s; run;' # for dsn in ['fish', 'iris']: # sas_submit_return_value = sas.submit( # sas_code_fragment % dsn, # results='TEXT' # ) # print_with_title( # sas_submit_return_value['LST'], # 'SAS results from PROC MEANS applies to sashelp.%s:' % dsn
# Everything is better with friends: Executing SAS® code in Python scripts with
# SASPy, and turbocharging your SAS programming with open-source tooling
#
# Half-day class, Western Users of SAS Software (WUSS) 2019
###############################################################################
# Exercise 10: Getting SASPy Environment Info #
###############################################################################
# Lines 12-14 load modules needed for exercises and should be left as-is
from class_setup import print_with_title
from saspy import SASsession
sas = SASsession()
###############################################################################
# #
# Exercise 10. [Python w/ saspy] Get info about a SAS session #
# #
# Instructions: Uncomment the code immediately below, and then execute #
# #
###############################################################################
# Orginal Version
sas_submit_return_value = sas.submit('PROC PRODUCT_STATUS; RUN;')
sas_submit_log = sas_submit_return_value['LOG']
print_with_title(sas_submit_log, 'SAS log from PROC PRODUCT_STATUS:')
# Verify the output from PROC PRODUCT_STATUS is empty
print('The output from PROC PRODUCT_STATUS appears below.')
print(sas.submit('PROC PRODUCT_STATUS; RUN;')['LST'])
print('The output from PROC PRODUCT_STATUS appears above.')
# Everything is better with friends: Executing SAS® code in Python scripts with
# SASPy, and turbocharging your SAS programming with open-source tooling
#
# Half-day class, Western Users of SAS Software (WUSS) 2019
###############################################################################
# Exercise 13: Imitating the SAS macro processor #
###############################################################################
# Lines 12-14 load modules needed for exercises and should be left as-is
from class_setup import print_with_title
from saspy import SASsession
sas = SASsession()
###############################################################################
# #
# Exercise 13. [Python w/ saspy] Imitate the SAS Macro Processor #
# #
# Instructions: Uncomment the code immediately below, and then execute #
# #
###############################################################################
# Original Version
sas_code_fragment = 'proc means data=sashelp.%s; run;'
for dsn in ['fish', 'iris']:
sas_submit_return_value = sas.submit(sas_code_fragment % dsn,
results='TEXT')
print_with_title(
sas_submit_return_value['LST'],
'SAS results from PROC MEANS applies to sashelp.%s:' % dsn)
# Everything is better with friends: Executing SAS® code in Python scripts with
# SASPy, and turbocharging your SAS programming with open-source tooling
#
# Half-day class, Western Users of SAS Software (WUSS) 2019
###############################################################################
# Exercises 11-12: SASPy Convenience Methods #
###############################################################################
# Lines 12-14 load modules needed for exercises and should be left as-is
from class_setup import print_with_title
from saspy import SASsession
sas = SASsession()
###############################################################################
# #
# Exercise 11. [Python w/ saspy] Connect directly to a SAS dataset #
# #
# Instructions: Uncomment the code immediately below, and then execute #
# #
###############################################################################
fish_sds = sas.sasdata(table='fish', libref='sashelp')
print_with_title(type(fish_sds), 'The type of fish_sds:')
print_with_title(fish_sds.columnInfo(),
'The Python equivalent of PROC CONTENTS:')
print_with_title(fish_sds.means(), 'The Python equivalent of PROC MEANS:')
# Notes:
# 1. The SASdata object fish_sds (meaning a direct connection to the disk-based
# SAS dataset sashelp.fish, not an in-memory DataFrame) is created, and the
# Everything is better with friends: Executing SAS® code in Python scripts with
# SASPy, and turbocharging your SAS programming with open-source tooling
#
# Half-day class, Western Users of SAS Software (WUSS) 2019
###############################################################################
# Exercises 14-17: Common DataFrame Operations #
###############################################################################
# Lines 12-14 load modules needed for exercises and should be left as-is
from class_setup import print_with_title
from saspy import SASsession
sas = SASsession()
###############################################################################
# #
# Exercise 14. [Python w/ saspy] Adding and dropping columns #
# #
# Instructions: Uncomment the code immediately below, and then execute #
# #
###############################################################################
# Original Version
class_df = sas.sasdata2dataframe(table='class', libref='sashelp')
print_with_title(class_df.head(), 'The first 5 rows of class_df:')
class_df['BMI'] = (class_df['Weight'] / class_df['Height']**2) * 703
print_with_title(
class_df.head(),
'The first 5 rows of class_df after a new column has been added:')
