Introduction¶
In software engineering and computer science, Parsing is the mecahnism of
translating incomprehensible data to a script readable form. Parsers are the
root of automation, without them, automation could not
understand the device. There exists multiple ways to parse the device output,
with different packages with each their style.
There also exist multiple ways to communicate with the device (Cli, Xml, Rest,
Yang, etc.) with each providing different structure for the same information!
Metaparser role is to unify those packages, into one location and one
structure. A unified collection of parser, which works across multiple parser
packages, and across multiple communication protocols and still returns a
common structure. Metaparser allows to have one script which works across
multiple OS, multiple communication protocol and parsing packages.
Imagine an parsing infrastructure that:
Promotes more easily maintainable platform/type/version agnostic testing scripts by deferring operational data parsing to back-end libraries,
Harmonizes parsing output among various interface categories, such as CLI, XML and YANG
Enforces only enough structure to give the script writer a consistent look and feel across interface categories
Is future proof, allowing a multitude of existing and yet-to-be-imagined parsing implementations to coexist in the backend
Enables an elastic parsing ecosystem that is simple enough for the novice but feature-rich enough for the power user
Leverages the strength of the modern Python-3 language while still allowing bridging/reuse of Cisco’s vast store of legacy TCL-based parsers.
Example¶
First, Import Metaparser as illustrated in the below example so it can be
used for inheritance for different schema classes. Metaparser schemaengine
provides various functionalities for the use within the schema structure as
explained in details here :schemaengine:`schema engine documentation <http>`.
In the below example, we are building a parser for three different show commands using different contexts CLI, Yang and XML. The contexts’ implementations are following the same schema/structure so making the parser more rigid to any change which will consequently provide stable/strong test scripts. Different parsing mechanisms (Regex, parsergen, TextFSM, etc.) can be used withing the parser as shown below.
Note
Below example is not a complete one and it was just used for illustration purpose.
Tons of parsers are already built and can be reached in parsers;
Can’t find a parser and want to build one? Visit Contribute in parsers build section for detailed_steps.
Example 1
---------
# Metaparser
from genie.metaparser import MetaParser
from genie.metaparser.util.schemaengine import Schema, Any, Optional
# ==============================================================================
# Schema for:
# * 'show bgp vrf <vrf> <address_family> policy statistics redistribute
# * 'show bgp vrf <vrf> <address_family> policy statistics dampening'
# * 'show bgp vrf <vrf> <address_family> policy statistics neighbor <neighbor>'
# ==============================================================================
class ShowBgpPolicyStatisticsSchema(MetaParser):
schema = {
'vrf': {
Any(): {
Optional('rpm_handle_count'): int,
Optional('route_map'): {
Any():{
Any(): {
'action': str,
'seq_num': int,
'total_accept_count': int,
'total_reject_count': int,
Optional('command'): {
'compare_count': int,
'match_count': int,
'command': str
}
},
},
}
},
}
}
class ShowBgpPolicyStatistics(ShowBgpPolicyStatisticsSchema):
"""Parser for:
show bgp [vrf <vrf>] <address_family> policy statistics redistribute
show bgp [vrf <vrf>] <address_family> policy statistics dampening
show bgp [vrf <vrf>] <address_family> policy statistics neighbor <neighbor>
parser class implements detail parsing mechanisms for cli,xml
and yang output"""
def cli(self, cmd):
out = self.device.execute(cmd)
# Init vars
ret_dict = {}
index = 1
# extract vrf info if specified,
# if not, vrf is default
m = re.compile(r'^show +bgp +vrf +(?P<vrf>\S+)').match(cmd)
if m:
vrf = m.groupdict()['vrf']
if vrf == 'all':
vrf = ''
else:
vrf = 'default'
for line in out.splitlines():
line = line.strip()
# Details for VRF default
p1 = re.compile(r'^Details +for +VRF +'
'(?P<vrf>[\w\-]+)$')
m = p1.match(line)
if m:
vrf = m.groupdict()['vrf']
nei_flag = True
continue
# No such neighbor
if re.compile(r'No +such +neighbor$').match(line):
nei_flag = False
# Total count for redistribute rpm handles: 1
# Total count for neighbor rpm handles: 1
# Total count for dampening rpm handles: 1
p2 = re.compile(r'^Total +count +for +(?P<type>\w+) +rpm +handles: +'
'(?P<handles>\d+)$')
m = p2.match(line)
# BGP policy statistics not available
p3 = re.compile(r'^BGP +policy +statistics +not +available$')
m1 = p3.match(line)
if m or m1:
if 'vrf' not in ret_dict:
ret_dict['vrf'] = {}
if vrf not in ret_dict['vrf']:
ret_dict['vrf'][vrf] = {}
ret_dict['vrf'][vrf]['rpm_handle_count'] = \
int(m.groupdict()['handles']) if m else 0
continue
# C: No. of comparisions, M: No. of matches
..... Parser continued .......
return ret_dict
def xml(self, cmd):
out = self.device.execute('{} | xml'.format(cmd))
etree_dict = {}
neighbor = None
# Remove junk characters returned by the device
out = out.replace("]]>]]>", "")
root = ET.fromstring(out)
# top table root
show_root = Common.retrieve_xml_child(root=root, key='show')
# get xml namespace
# {http://www.cisco.com/nxos:7.0.3.I7.1.:bgp}
try:
m = re.compile(r'(?P<name>\{[\S]+\})').match(show_root.tag)
namespace = m.groupdict()['name']
except Exception:
return etree_dict
# compare cli command
Common.compose_compare_command(root=root, namespace=namespace,
expect_command=cmd)
# get neighbor
nei = Common.retrieve_xml_child(root=root, key='__XML__PARAM__neighbor-id')
if hasattr(nei, 'tag'):
for item in nei.getchildren():
if '__XML__value' in item.tag:
neighbor = item.text
continue
# cover the senario that __readonly__ may be mssing when
# there are values in the output
if '__readonly__' in item.tag:
root = item.getchildren()[0]
else:
root = item
else:
# top table rootl
root = Common.retrieve_xml_child(root=root, key='TABLE_vrf')
if not root:
return etree_dict
# ----- loop vrf -----
for vrf_tree in root.findall('{}ROW_vrf'.format(namespace)):
# vrf
try:
vrf = vrf_tree.find('{}vrf-name-polstats'.format(namespace)).text
except Exception:
break
..... Parser continued .......
return etree_dict
def yang(self):
"""parsing mechanism: yang
Function yang() defines the yang type output parsing mechanism which
typically contains 3 steps: executing, transforming, returning
"""
map_dict = {}
cmd = '''<native><interface><Vlan/></interface></native>'''
output = self.device.get(('subtree', cmd))
for data in output.data:
for native in data:
for interface in native:
vlan_id = None
interface_name = None
ip_address = None
ip_mask = None
for vlan in interface:
# Remove the namespace
text = vlan.tag[vlan.tag.find('}')+1:]
#ydk.models.ned_edison.ned.Native.Interface.Vlan.name
#ydk.models.xe_recent_edison.Cisco_IOS_XE_native.Native.Interface.Vlan.name
if text == 'name':
vlan_id = vlan.text
interface_name = 'Vlan' + str(vlan_id)
continue
..... Parser continued .......
# Return to caller
return map_dict
Example 2 (Using Parsergen parsing Mechanism)
---------------------------------------------
# Import parsergen package
import parsergen
# Build Schema
class ShowIpInterfaceBriefSchema(MetaParser):
"""Parser for show ip interface brief"""
schema = {'interface':
{Any():
{Optional('vlan_id'):
{Optional(Any()):
{'ip_address': str,
Optional('interface_is_ok'): str,
Optional('method'): str,
Optional('status'): str,
Optional('protocol'): str}
},
Optional('ip_address'): str,
Optional('interface_is_ok'): str,
Optional('method'): str,
Optional('status'): str,
Optional('protocol'): str}
},
}
# Build Parser
class ShowIpInterfaceBrief(ShowIpInterfaceBriefSchema):
"""Parser for:
show ip interface brief
parser class implements detail parsing mechanisms for cli and yang output.
"""
#*************************
# schema - class variable
#
# Purpose is to make sure the parser always return the output
# (nested dict) that has the same data structure across all supported
# parsing mechanisms (cli(), yang(), xml()).
def __init__ (self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.cmd = 'show ip interface brief'.format()
def cli(self):
"""parsing mechanism: cli
Function cli() defines the cli type output parsing mechanism which
typically contains 3 steps: exe
cuting, transforming, returning
"""
parsed_dict = {}
output = self.device.execute(self.cmd)
if output:
res = parsergen.oper_fill_tabular(device_output=output,
device_os='iosxe',
table_terminal_pattern=r"^\n",
header_fields=
[ "Interface",
"IP-Address",
"OK\?",
"Method",
"Status",
"Protocol" ],
label_fields=
[ "Interface",
"ip_address",
"interface_is_ok",
"method",
"status",
"protocol" ],
index=[0])
# Building the schema out o fthe parsergen output
if res.entries:
for intf in res.entries:
del res.entries[intf]['Interface']
parsed_dict['interface'] = res.entries
return (parsed_dict)
def yang(self):
""" parsing mechanism: yang
Function yang() defines the yang type output parsing mechanism which
typically contains 3 steps: executing, transforming, returning
"""
pass
def yang_cli(self):
cli_output = self.cli()
yang_output = self.yang()
merged_output = _merge_dict(yang_output,cli_output)
return merged_output
Note
For package advanced usage, you can refer to Advanced Usage section.