def _catalog_non_vsam_data_set(name, volume):
"""Catalog a non-VSAM data set.
Arguments:
name {str} -- The data set to catalog.
volume {str} -- The volume the data set resides on.
Raises:
DatasetCatalogError: When attempt at catalog fails.
"""
iehprogm_input = _build_non_vsam_catalog_command(name, volume)
try:
temp_data_set_name = _create_temp_data_set(name.split(".")[0])
_write_data_set(temp_data_set_name, iehprogm_input)
rc, stdout, stderr = module.run_command(
"mvscmdauth --pgm=iehprogm --sysprint=* --sysin={0}".format(
temp_data_set_name
)
)
if rc != 0 or "NORMAL END OF TASK RETURNED" not in stdout:
raise DatasetCatalogError(name, volume, rc)
except Exception:
raise
finally:
Datasets.delete(temp_data_set_name)
return
def _uncatalog_vsam_data_set(name):
"""Uncatalog a VSAM data set.
Arguments:
name {str} -- The name of the data set to uncatalog.
Raises:
DatasetUncatalogError: When uncataloging fails.
"""
idcams_input = VSAM_UNCATALOG_COMMAND.format(name)
try:
temp_data_set_name = _create_temp_data_set(name.split(".")[0])
_write_data_set(temp_data_set_name, idcams_input)
dd_statements = []
dd_statements.append(
types.DDStatement(ddName="sysin", dataset=temp_data_set_name)
)
dd_statements.append(types.DDStatement(ddName="sysprint", dataset="*"))
rc = MVSCmd.execute_authorized(pgm="idcams", args="", dds=dd_statements)
if rc != 0:
raise DatasetUncatalogError(name, rc)
except Exception:
raise
finally:
Datasets.delete(temp_data_set_name)
return
def _uncatalog_non_vsam_data_set(name):
"""Uncatalog a non-VSAM data set.
Arguments:
name {str} -- The name of the data set to uncatalog.
Raises:
DatasetUncatalogError: When uncataloging fails.
"""
iehprogm_input = NON_VSAM_UNCATALOG_COMMAND.format(name)
try:
temp_data_set_name = _create_temp_data_set(name.split(".")[0])
_write_data_set(temp_data_set_name, iehprogm_input)
rc, stdout, stderr = module.run_command(
"mvscmdauth --pgm=iehprogm --sysprint=* --sysin={0}".format(
temp_data_set_name
)
)
if rc != 0 or "NORMAL END OF TASK RETURNED" not in stdout:
raise DatasetUncatalogError(name, rc)
except Exception:
raise
finally:
Datasets.delete(temp_data_set_name)
return
def mvs_file_backup(dsn, bk_dsn):
"""Create a backup data set for an MVS data set
Arguments:
dsn {str} -- The name of the data set to backup.
It could be an MVS PS/PDS/PDSE/VSAM(KSDS), etc.
bk_dsn {str} -- The name of the backup data set.
Raises:
BackupError: When backup data set exists.
BackupError: When creation of backup data set fails.
"""
dsn = _validate_data_set_name(dsn).upper()
bk_dsn = _validate_data_set_name(bk_dsn).upper()
if not bk_dsn:
hlq = Datasets.hlq()
bk_dsn = Datasets.temp_name(hlq)
cp_rc = _copy_ds(dsn, bk_dsn)
# The data set is probably a PDS or PDSE
if cp_rc == 12:
# Delete allocated backup that was created when attempting to use _copy_ds()
# Safe to delete because _copy_ds() would have raised an exception if it did
# not successfully create the backup data set, so no risk of it predating module invocation
Datasets.delete(bk_dsn)
if Datasets.move(dsn, bk_dsn) == 0:
_allocate_model(dsn, bk_dsn)
else:
raise BackupError("Unable to backup data set {0} to {1}".format(
dsn, bk_dsn))
def _copy_ds(ds, bk_ds):
"""Copy the contents of a data set to another
Arguments:
ds {str} -- The source data set to be copied from. Should be SEQ or VSAM
bk_dsn {str} -- The destination data set to copy to.
Raises:
BackupError: When copying data fails
"""
module = AnsibleModule(argument_spec={}, check_invalid_arguments=False)
_allocate_model(bk_ds, ds)
repro_cmd = """ REPRO -
INDATASET({0}) -
OUTDATASET({1})""".format(ds, bk_ds)
rc, out, err = module.run_command(
"mvscmdauth --pgm=idcams --sysprint=* --sysin=stdin", data=repro_cmd)
if rc != 0 and rc != 12:
Datasets.delete(bk_ds)
raise BackupError(
"Unable to backup data set {0}; stdout: {1}; stderr: {2}".format(
ds, out, err))
if rc != 0 and _vsam_empty(ds):
rc = 0
return rc
def create_temp_data_set(LLQ,
ds_type="SEQ",
size="5M",
ds_format="FB",
lrecl=80):
"""Creates a temporary data set with the given low level qualifier.
Arguments:
LLQ {str} -- Low Level Qualifier to be used for temporary data set
ds_type {str} -- The data set type, default: Sequential
size {str} -- The size of the data set, default: 5M
format {str} -- The record format of the data set, default: FB
lrecl {int} -- The record length of the data set, default: 80
Returns:
str -- Name of the created data set
Raises:
OSError: When non-zero return code is received
from Datasets.create()
"""
chars = ascii_uppercase
HLQ2 = ''.join(choice(chars) for i in range(5))
HLQ3 = ''.join(choice(chars) for i in range(6))
temp_ds_name = "{0}.{1}.{2}.{3}".format(Datasets.hlq(), HLQ2, HLQ3,
LLQ)
rc = Datasets.create(temp_ds_name, ds_type, size, ds_format, "", lrecl)
if rc != 0:
raise OSError("Unable to create temporary data set")
return temp_ds_name
def __init__(self):
"""VIO DD type to be used in a DDStatement.
VIO uses DASD space and system I/O more efficiently than other temporary data sets.
A temporary data set will be created for use in cases where VIO is unavailable.
Defaults for VIODefinition should be sufficient.
"""
hlq = Datasets.hlq()
name = Datasets.temp_name(hlq)
super().__init__(name)
def _copy_vsam_to_temp_data_set(self, ds_name):
""" Copy VSAM data set to a temporary sequential data set """
mvs_rc = 0
vsam_size = self._get_vsam_size(ds_name)
sysprint = sysin = out_ds_name = None
try:
sysin = data_set.DataSet.create_temp("MVSTMP")
sysprint = data_set.DataSet.create_temp("MVSTMP")
out_ds_name = data_set.DataSet.create_temp("MSVTMP",
space_primary=vsam_size,
space_type="K")
repro_sysin = " REPRO INFILE(INPUT) OUTFILE(OUTPUT) "
Datasets.write(sysin, repro_sysin)
dd_statements = []
dd_statements.append(
types.DDStatement(ddName="sysin", dataset=sysin))
dd_statements.append(
types.DDStatement(ddName="input", dataset=ds_name))
dd_statements.append(
types.DDStatement(ddName="output", dataset=out_ds_name))
dd_statements.append(
types.DDStatement(ddName="sysprint", dataset=sysprint))
mvs_rc = MVSCmd.execute_authorized(pgm="idcams",
args="",
dds=dd_statements)
except OSError as err:
self._fail_json(msg=str(err))
except Exception as err:
if Datasets.exists(out_ds_name):
Datasets.delete(out_ds_name)
if mvs_rc != 0:
self._fail_json(
msg=(
"Non-zero return code received while executing MVSCmd "
"to copy VSAM data set {0}".format(ds_name)),
rc=mvs_rc,
)
self._fail_json(
msg=
("Failed to call IDCAMS to copy VSAM data set {0} to a temporary"
" sequential data set".format(ds_name)),
stderr=str(err),
rc=mvs_rc,
)
finally:
Datasets.delete(sysprint)
Datasets.delete(sysin)
return out_ds_name
def check_pds_member(ds, mem):
check_rc = False
if mem in Datasets.list_members(ds):
check_rc = True
else:
raise EncodeError("Cannot find member {0} in {1}".format(mem, ds))
return check_rc
def _catalog_vsam_data_set(name, volume):
"""Catalog a VSAM data set.
Arguments:
name {str} -- The data set to catalog.
volume {str} -- The volume the data set resides on.
Raises:
DatasetCatalogError: When attempt at catalog fails.
"""
data_set_name = name.upper()
data_set_volume = volume.upper()
success = False
try:
temp_data_set_name = _create_temp_data_set(name.split(".")[0])
command_rc = 0
for data_set_type in ["", "LINEAR", "INDEXED", "NONINDEXED", "NUMBERED"]:
if data_set_type != "INDEXED":
command = VSAM_CATALOG_COMMAND_NOT_INDEXED.format(
data_set_name, data_set_volume, data_set_type
)
else:
command = VSAM_CATALOG_COMMAND_INDEXED.format(
data_set_name, data_set_volume, data_set_type
)
_write_data_set(temp_data_set_name, command)
dd_statements = []
dd_statements.append(
types.DDStatement(ddName="sysin", dataset=temp_data_set_name)
)
dd_statements.append(types.DDStatement(ddName="sysprint", dataset="*"))
command_rc = MVSCmd.execute_authorized(
pgm="idcams", args="", dds=dd_statements
)
if command_rc == 0:
success = True
break
if not success:
raise DatasetCatalogError(
name, volume, command_rc, "Attempt to catalog VSAM data set failed."
)
except Exception:
raise
finally:
Datasets.delete(temp_data_set_name)
return
def temp_data_set(self, reclen, space_u):
"""Creates a temporary data set with the given record length and size
Arguments:
size {str} -- The size of the data set
lrecl {int} -- The record length of the data set
Returns:
str -- Name of the allocated data set
Raises:
OSError: When any exception is raised during the data set allocation
"""
size = str(space_u * 2) + "K"
hlq = Datasets.hlq()
temp_ps = Datasets.temp_name(hlq)
rc = Datasets.create(temp_ps, "SEQ", size, "VB", "", reclen)
if rc:
raise OSError(
"Failed when allocating temporary sequential data set!")
return temp_ps
def _delete_data_set(name):
"""A wrapper around zoautil_py
Dataset.delete() to raise exceptions on failure.
Arguments:
name {str} -- The name of the data set to delete.
Raises:
DatasetDeleteError: When data set deletion fails.
"""
rc = Datasets.delete(name)
if rc > 0:
raise DatasetDeleteError(name, rc)
return
def _create_temp_data_set(hlq):
"""Create a temporary data set.
Arguments:
hlq {str} -- The HLQ to use for the temporary data set's name.
Returns:
str -- The name of the temporary data set.
"""
temp_data_set_name = Datasets.temp_name(hlq)
_create_data_set(
temp_data_set_name, {"type": "SEQ", "size": "5M", "format": "FB", "length": 80},
)
return temp_data_set_name
def _fetch_vsam(self, src, is_binary, encoding=None):
""" Copy the contents of a VSAM to a sequential data set.
Afterwards, copy that data set to a USS file.
"""
temp_ds = self._copy_vsam_to_temp_data_set(src)
file_path = self._fetch_mvs_data(temp_ds, is_binary, encoding)
rc = Datasets.delete(temp_ds)
if rc != 0:
os.remove(file_path)
self._fail_json(
msg="Unable to delete temporary data set {0}".format(temp_ds),
rc=rc)
return file_path
def _create_data_set(name, extra_args=None):
"""A wrapper around zoautil_py
Dataset.create() to raise exceptions on failure.
Arguments:
name {str} -- The name of the data set to create.
Raises:
DatasetCreateError: When data set creation fails.
"""
if extra_args is None:
extra_args = {}
rc = Datasets.create(name, **extra_args)
if rc > 0:
raise DatasetCreateError(name, rc)
return
def _delete_data_set_member(name):
"""A wrapper around zoautil_py
Dataset.delete_members() to raise exceptions on failure.
Arguments:
name {str} -- The name of the data set, including member name, to delete.
Raises:
DatasetMemberDeleteError: When data set member deletion fails.
"""
rc = Datasets.delete_members(name)
if rc > 0:
raise DatasetMemberDeleteError(name, rc)
return
def mvs_file_backup(dsn, bk_dsn=None):
"""Create a backup data set for an MVS data set
Arguments:
dsn {str} -- The name of the data set to backup.
It could be an MVS PS/PDS/PDSE/VSAM(KSDS), etc.
bk_dsn {str} -- The name of the backup data set.
Raises:
BackupError: When backup data set exists.
BackupError: When creation of backup data set fails.
"""
dsn = _validate_data_set_name(dsn).upper()
if is_member(dsn):
if not bk_dsn:
bk_dsn = extract_dsname(dsn) + "({0})".format(temp_member_name())
bk_dsn = _validate_data_set_name(bk_dsn).upper()
if Datasets.copy(dsn, bk_dsn) != 0:
raise BackupError("Unable to backup {0} to {1}".format(
dsn, bk_dsn))
else:
if not bk_dsn:
bk_dsn = Datasets.temp_name(Datasets.hlq())
bk_dsn = _validate_data_set_name(bk_dsn).upper()
cp_rc = _copy_ds(dsn, bk_dsn)
if cp_rc == 12: # The data set is probably a PDS or PDSE
# Delete allocated backup that was created when attempting to use _copy_ds()
# Safe to delete because _copy_ds() would have raised an exception if it did
# not successfully create the backup data set, so no risk of it predating module invocation
Datasets.delete(bk_dsn)
_allocate_model(bk_dsn, dsn)
rc, out, err = _copy_pds(dsn, bk_dsn)
if rc != 0:
raise BackupError(
"Unable to backup data set {0} to {1}".format(dsn, bk_dsn))
return bk_dsn
def absent(src, line, regexp, encoding):
"""Delete lines with matching regex pattern
Arguments:
src: {str} -- The z/OS USS file or data set to modify.
line: {str} -- The line to be deleted in the src. If line matches,
regexp will be ignored.
regexp: {str} -- The regular expression to look for in every line of the src.
encoding: {str} -- Encoding of the src.
Returns:
str -- Information in JSON format. keys:
cmd: {str} -- dsed shell command
found: {int} -- Number of matching regex pattern
changed: {bool} -- Indicates if the source was modified.
"""
return Datasets.lineinfile(src,
line,
regexp,
encoding=encoding,
state=False)
def present(src, line, regexp, ins_aft, ins_bef, encoding, first_match,
backrefs):
"""Replace a line with the matching regex pattern
Insert a line before/after the matching pattern
Insert a line at BOF/EOF
Arguments:
src: {str} -- The z/OS USS file or data set to modify.
line: {str} -- The line to insert/replace into the src.
regexp: {str} -- The regular expression to look for in every line of the src.
If regexp matches, ins_aft/ins_bef will be ignored.
ins_aft: {str} -- Insert the line after matching '*regex*' pattern or EOF.
choices:
- EOF
- '*regex*'
ins_bef: {str} -- Insert the line before matching '*regex*' pattern or BOF.
choices:
- BOF
- '*regex*'
encoding: {str} -- Encoding of the src.
first_match: {bool} -- Take the first matching regex pattern.
backrefs: {bool} -- Back reference
Returns:
str -- Information in JSON format. keys:
cmd: {str} -- dsed shell command
found: {int} -- Number of matching regex pattern
changed: {bool} -- Indicates if the source was modified.
"""
return Datasets.lineinfile(src,
line,
regexp,
ins_aft,
ins_bef,
encoding,
first_match,
backrefs,
state=True)
def delete_data_set_member(name):
""" A wrapper around zoautil_py data set delete_members to raise exceptions on failure. """
rc = Datasets.delete_members(name)
if rc > 0:
raise DatasetMemberDeleteError(name, rc)
return
def create_data_set(name, extra_args={}):
""" A wrapper around zoautil_py data set create to raise exceptions on failure. """
rc = Datasets.create(name, **extra_args)
if rc > 0:
raise DatasetCreateError(name, rc)
return
def mvs_convert_encoding(self,
src,
dest,
from_code,
to_code,
src_type=None,
dest_type=None):
"""Convert the encoding of the data from
1) USS to MVS(PS, PDS/E VSAM)
2) MVS to USS
3) MVS to MVS
Arguments:
src: {str} -- The input MVS data set or USS path to be converted
dest: {str} -- The output MVS data set or USS path to be converted
from_code: {str} -- The source code set of the input MVS data set
to_code: {str} -- The destination code set of the output MVS data set
Keyword Arguments:
src_type {[type]} -- The input MVS data set or type: PS, PDS, PDSE, VSAM(KSDS) (default: {None})
dest_type {[type]} -- The output MVS data set type (default: {None})
Returns:
boolean -- Indicate whether the conversion is successful or not
"""
src = self._validate_data_set_or_path(src)
dest = self._validate_data_set_or_path(dest)
from_code = self._validate_encoding(from_code)
to_code = self._validate_encoding(to_code)
convert_rc = False
temp_ps = None
temp_src = src
temp_dest = dest
try:
if src_type == "PS":
temp_src_fo = NamedTemporaryFile()
temp_src = temp_src_fo.name
rc, out, err = copy.copy_ps2uss(src, temp_src)
if src_type == "PO":
temp_src_fo = TemporaryDirectory()
temp_src = temp_src_fo.name
rc, out, err = copy.copy_pds2uss(src, temp_src)
if src_type == "VSAM":
reclen, space_u = self.listdsi_data_set(src.upper())
temp_ps = self.temp_data_set(reclen, space_u)
rc, out, err = copy.copy_vsam_ps(src.upper(), temp_ps)
temp_src_fo = NamedTemporaryFile()
temp_src = temp_src_fo.name
rc, out, err = copy.copy_ps2uss(temp_ps, temp_src)
if dest_type == "PS" or dest_type == "VSAM":
temp_dest_fo = NamedTemporaryFile()
temp_dest = temp_dest_fo.name
if dest_type == "PO":
temp_dest_fo = TemporaryDirectory()
temp_dest = temp_dest_fo.name
rc = self.uss_convert_encoding_prev(temp_src, temp_dest, from_code,
to_code)
if rc:
if not dest_type:
convert_rc = True
else:
if dest_type == "VSAM":
reclen, space_u = self.listdsi_data_set(dest.upper())
temp_ps = self.temp_data_set(reclen, space_u)
rc, out, err = copy.copy_uss2mvs(
temp_dest, temp_ps, "PS")
rc, out, err = copy.copy_vsam_ps(temp_ps, dest.upper())
convert_rc = True
elif dest_type == "PO":
for (dir, subdir, files) in walk(temp_dest):
for file in files:
temp_file = path.join(dir, file)
rc, out, err = copy.copy_uss2mvs(
temp_file, dest, "PO")
convert_rc = True
else:
rc, out, err = copy.copy_uss2mvs(
temp_dest, dest, dest_type)
convert_rc = True
except Exception:
raise
finally:
if temp_ps:
Datasets.delete(temp_ps)
return convert_rc
def run_module():
# ********************************************************** #
# Module initialization #
# ********************************************************** #
module = AnsibleModule(argument_spec=dict(
src=dict(required=True, type="str"),
dest=dict(required=True, type="path"),
fail_on_missing=dict(required=False, default=True, type="bool"),
flat=dict(required=False, default=True, type="bool"),
is_binary=dict(required=False, default=False, type="bool"),
use_qualifier=dict(required=False, default=False, type="bool"),
validate_checksum=dict(required=False, default=True, type="bool"),
encoding=dict(required=False, type="dict"),
))
src = module.params.get("src")
if module.params.get("use_qualifier"):
module.params["src"] = Datasets.hlq() + "." + src
# ********************************************************** #
# Verify paramater validity #
# ********************************************************** #
arg_def = dict(
src=dict(arg_type="data_set_or_path", required=True),
dest=dict(arg_type="path", required=True),
fail_on_missing=dict(arg_type="bool", required=False, default=True),
is_binary=dict(arg_type="bool", required=False, default=False),
use_qualifier=dict(arg_type="bool", required=False, default=False),
)
if module.params.get("encoding"):
module.params.update(
dict(
from_encoding=module.params.get("encoding").get("from"),
to_encoding=module.params.get("encoding").get("to"),
))
arg_def.update(
dict(
from_encoding=dict(arg_type="encoding"),
to_encoding=dict(arg_type="encoding"),
))
fetch_handler = FetchHandler(module)
try:
parser = better_arg_parser.BetterArgParser(arg_def)
parsed_args = parser.parse_args(module.params)
except ValueError as err:
module.fail_json(msg="Parameter verification failed", stderr=str(err))
src = parsed_args.get("src")
b_src = to_bytes(src)
fail_on_missing = boolean(parsed_args.get("fail_on_missing"))
use_qualifier = boolean(parsed_args.get("use_qualifier"))
is_binary = boolean(parsed_args.get("is_binary"))
encoding = module.params.get("encoding")
# ********************************************************** #
# Check for data set existence and determine its type #
# ********************************************************** #
res_args = dict()
_fetch_member = "(" in src and src.endswith(")")
ds_name = src if not _fetch_member else src[:src.find("(")]
try:
ds_utils = data_set.DataSetUtils(ds_name)
if not ds_utils.exists():
if fail_on_missing:
module.fail_json(msg=("The source '{0}' does not exist or is "
"uncataloged".format(ds_name)))
module.exit_json(
note=("Source '{0}' was not found. No data was fetched".format(
ds_name)))
ds_type = ds_utils.ds_type()
if not ds_type:
module.fail_json(msg="Unable to determine data set type")
except Exception as err:
module.fail_json(msg="Error while gathering data set information",
stderr=str(err))
# ********************************************************** #
# Fetch a sequential data set #
# ********************************************************** #
if ds_type == "PS":
file_path = fetch_handler._fetch_mvs_data(src, is_binary, encoding)
res_args["remote_path"] = file_path
# ********************************************************** #
# Fetch a partitioned data set or one of its members #
# ********************************************************** #
elif ds_type == "PO":
if _fetch_member:
member_name = src[src.find("(") + 1:src.find(")")]
if not ds_utils.member_exists(member_name):
module.fail_json(
msg=("The data set member '{0}' was not found inside data "
"set '{1}'").format(member_name, ds_name))
file_path = fetch_handler._fetch_mvs_data(src, is_binary, encoding)
res_args["remote_path"] = file_path
else:
res_args["remote_path"] = fetch_handler._fetch_pdse(
src, is_binary, encoding)
# ********************************************************** #
# Fetch a USS file #
# ********************************************************** #
elif ds_type == "USS":
if not os.access(b_src, os.R_OK):
module.fail_json(
msg="File '{0}' does not have appropriate read permission".
format(src))
file_path = fetch_handler._fetch_uss_file(src, is_binary, encoding)
res_args["remote_path"] = file_path
# ********************************************************** #
# Fetch a VSAM data set #
# ********************************************************** #
elif ds_type == "VSAM":
file_path = fetch_handler._fetch_vsam(src, is_binary, encoding)
res_args["remote_path"] = file_path
res_args["file"] = ds_name
res_args["ds_type"] = ds_type
module.exit_json(**res_args)
#Import the Z Open Automation Utilities libraries we need
from zoautil_py import MVSCmd, Datasets
from zoautil_py.types import DDStatement
import os
# Grab the environment variable for USER, which should be equal to your Zxxxxx userid
USERID = os.getenv('USER')
dataset_to_list = "WORK"
target_dataset = USERID + "." + dataset_to_list
ds_members = Datasets.list_members(target_dataset)
print(ds_members)
logging.config.fileConfig('logging.conf')
# Create list of DD statements for MVSCmd
dd_statements = []
dd_statements.append(
DDStatement(ddName="sortin01", dataset="USR.MVSCMD.DFSORT.MASTER"))
dd_statements.append(
DDStatement(ddName="sortin02", dataset="USR.MVSCMD.DFSORT.NEW"))
dd_statements.append(
DDStatement(ddName="sysin", dataset="USR.MVSCMD.DFSORT.CMD"))
dd_statements.append(
DDStatement(ddName="sortout", dataset="USR.MVSCMD.DFSORT.MERGE"))
dd_statements.append(DDStatement(ddName="sysout", dataset="*"))
# Delete datasets if already exist
Datasets.delete("USR.MVSCMD.DFSORT.*")
# Create datasets
Datasets.create("USR.MVSCMD.DFSORT.MASTER", type="SEQ")
Datasets.create("USR.MVSCMD.DFSORT.NEW", type="SEQ")
Datasets.create("USR.MVSCMD.DFSORT.CMD", type="SEQ")
Datasets.create("USR.MVSCMD.DFSORT.MERGE", type="SEQ")
# Write command to USR.MVSCMD.DFSORT.CMD
Datasets.write("USR.MVSCMD.DFSORT.CMD", " MERGE FORMAT=CH,FIELDS=(1,9,A)")
# Write example text to USR.MVSCMD.DFSORT.MASTER
Datasets.write("USR.MVSCMD.DFSORT.MASTER", "Chang Joe 278 232 6043")
Datasets.write("USR.MVSCMD.DFSORT.MASTER",
"DeBeer Jo 348 132 6023",
append=True)
#Import the Z Open Automation Utilities libraries we need
from zoautil_py import MVSCmd, Datasets
from zoautil_py.types import DDStatement
# Import datetime, needed so we can format the report
from datetime import datetime
# Import os, needed to get the environment variables
import os
#Take the contents of this data set and read it into cc_contents
cc_contents = Datasets.read("MTM2020.PUBLIC.CUST16")
USERID = os.getenv("USER")
output_dataset = USERID + ".OUTPUT.CCINVALD"
#Delete the output dataset if it already exists
if Datasets.exists(output_dataset):
Datasets.delete(output_dataset)
Datasets.create(output_dataset, "SEQ")
# Create a new SEQUENTIAL DATA SET with the name of output_dataset
#A function that checks to see if the number passed to it is even. Returns True or False (Boolean)
def is_even(num_to_check
): # this is a function. num_to_check is what gets sent to it
if ((num_to_check %
2) == 0): # a simple check to see if num_to_check is even.
result = True # We set result to True
return result # and then return it.
else: # if it isn't
result = False # set return to False
else:
print("VALID")
----------------------------------------------------------------------------------------------
#Import the Z Open Automation Utilities libraries we need
from zoautil_py import MVSCmd, Datasets
from zoautil_py.types import DDStatement
# Import datetime, needed so we can format the report
from datetime import datetime
# Import os, needed to get the environment variables
import os
#Take the contents of this data set and read it into cc_contents
cc_contents = Datasets.read("MTM2020.PUBLIC.CUST16")
USERID = os.getenv('USER')
output_dataset=USERID+".OUTPUT.CCINVALD"
#Delete the output dataset if it already exists
if Datasets.exists(output_dataset):
Datasets.delete(output_dataset)
# Use this line to create a new SEQUENTIAL DATA SET with the name of output_dataset
# (hint: https://www.ibm.com/support/knowledgecenter/SSKFYE_1.0.1/python_doc_zoautil/api/datasets.html?view=embed)
#A function that checks to see if the number passed to it is even. Returns True or False (Boolean)
def is_even(num_to_check): # this is a function. num_to_check is what gets sent to it
if ((num_to_check % 2) == 0): # a simple check to see if num_to_check is even.
result = True # We set result to True
return result # and then return it.
#Import the Z Open Automation Utilities libraries we need
from zoautil_py import MVSCmd, Datasets
from zoautil_py.types import DDStatement
# Import datetime, needed so we can format the report
from datetime import datetime
# Import os, needed to get the environment variables
import os
#Take the contents of this data set and read it into cc_contents
cc_contents = Datasets.read("MTM2020.PUBLIC.CUST16")
USERID = os.getenv('USER')
output_dataset = USERID + ".OUTPUT(CCINVALD)"
#Delete the output dataset if it already exists
#if Datasets.exists(output_dataset):
# Datasets.delete(output_dataset)
# Use this line to create a new SEQUENTIAL DATA SET with the name of output_dataset
# (hint: https://www.ibm.com/support/knowledgecenter/SSKFYE_1.0.1/python_doc_zoautil/api/datasets.html?view=embed)
#Datasets.create(output_dataset, type ="SEQ")
def luhn(card_number):
def digits_of(n):
return [int(d) for d in str(n)]
digits = digits_of(card_number)
odd_digits = digits[-1::-2]
even_digits = digits[-2::-2]
checksum = 0
checksum += sum(odd_digits)
for d in even_digits:
import mysql.connector
#Import the Z Open Automation Utilities libraries we need
from zoautil_py import MVSCmd, Datasets, Jobs
from zoautil_py.types import DDStatement
# Import datetime, needed so we can format the report
from datetime import datetime
# Import os, needed to get the environment variables
import os
import string
import time
#Take the contents of this data set and read it into content variables
USERID = os.getenv('USER')
hlq = Datasets.hlq()
print("running jobs for ", hlq)
damember = "%s.OUTPUT.SDSFDAS" % hlq
da_contents = Datasets.read(damember)
#ckmember="%s.OUTPUT.SDSFCKS" % hlq
#hc_contents = Datasets.read(ckmember)
now = datetime.now()
formatted_date = now.strftime('%Y-%m-%d %H:%M:%S')
#Submit the job
jclmember = "%s.JCL(SDSFJCL)" % hlq
jobid = Jobs.submit(dataset=jclmember)
while True:
js = Jobs.list(job_id=jobid)[0]
if (js["return"] != "?"):
break
else:
print(js)
#Import the Z Open Automation Utilities libraries we need
from zoautil_py import MVSCmd, Datasets
from zoautil_py.types import DDStatement
# Import datetime, needed so we can format the report
from datetime import datetime
# Import os, needed to get the environment variables
import os
#Take the contents of this data set and read it into cc_contents
cc_contents = Datasets.read("MTM2020.PUBLIC.CUST16")
USERID = os.getenv('USER')
output_dataset=USERID+".OUTPUT.CCINVALD"
#Delete the output dataset if it already exists
if Datasets.exists(output_dataset):
Datasets.delete(output_dataset)
# Use this line to create a new SEQUENTIAL DATA SET with the name of output_dataset
# (hint: https://www.ibm.com/support/knowledgecenter/SSKFYE_1.0.1/python_doc_zoautil/api/datasets.html?view=embed)
def luhn(card_number):
def digits_of(n):
return [int(d) for d in str(n)]
digits = digits_of(card_number)
odd_digits = digits[-1::-2]
even_digits = digits[-2::-2]
checksum = 0
checksum += sum(odd_digits)
for d in even_digits:
checksum += sum(digits_of(d*2))
return (checksum % 10)
