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@ -1,6 +1,6 @@
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#
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# -*- coding: utf-8 -*-
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# Copyright 2021 Red Hat
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# Copyright 2022 Red Hat
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# GNU General Public License v3.0+
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# (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
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#
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@ -1234,7 +1234,7 @@ def _consolidate(*args, **kwargs):
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class FilterModule(object):
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"""keep_keys"""
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"""consolidate"""
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def filters(self):
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@ -1,12 +1,12 @@
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#
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# -*- coding: utf-8 -*-
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# Copyright 2021 Red Hat
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# Copyright 2022 Red Hat
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# GNU General Public License v3.0+
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# (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
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#
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"""
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The keep_keys plugin code
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The consolidate plugin code
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"""
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from __future__ import absolute_import, division, print_function
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@ -27,17 +27,15 @@ def _raise_error(filter, msg):
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def fail_on_filter(validator_func):
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"""decorator to fail on supplied filters"""
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def update_err(*args, **kwargs):
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res, err = validator_func(*args, **kwargs)
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if err.get("match_key_err"):
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_raise_error(
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"fail_missing_match_key", ", ".join(err["match_key_err"])
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)
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_raise_error("fail_missing_match_key", ", ".join(err["match_key_err"]))
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if err.get("match_val_err"):
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_raise_error(
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"fail_missing_match_value", ", ".join(err["match_val_err"])
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)
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_raise_error("fail_missing_match_value", ", ".join(err["match_val_err"]))
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if err.get("duplicate_err"):
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_raise_error("fail_duplicate", ", ".join(err["duplicate_err"]))
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return res
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@ -49,13 +47,9 @@ def fail_on_filter(validator_func):
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def check_missing_match_key_duplicate(
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data_sources, fail_missing_match_key, fail_duplicate
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):
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"""Validate the operation
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:param operation: The operation
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:type operation: str
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:raises: AnsibleFilterError
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"""
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"""Checks if the match_key specified is present in all the supplied data,
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also checks for duplicate data accross all the data sources"""
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results, errors_match_key, errors_duplicate = [], [], []
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# Check for missing and duplicate match key
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for ds_idx, data_source in enumerate(data_sources):
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match_key = data_source["match_key"]
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ds_values = []
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@ -71,9 +65,7 @@ def check_missing_match_key_duplicate(
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continue
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if sorted(set(ds_values)) != sorted(ds_values) and fail_duplicate:
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errors_duplicate.append(
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f"Duplicate values in data source {ds_idx}"
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)
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errors_duplicate.append(f"Duplicate values in data source {ds_idx}")
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results.append(set(ds_values))
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return results, {
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"match_key_err": errors_match_key,
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@ -82,11 +74,19 @@ def check_missing_match_key_duplicate(
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@fail_on_filter
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def check_missing_match_values(results, fail_missing_match_value):
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def check_missing_match_values(matched_keys, fail_missing_match_value):
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"""Checks values to match be consistent over all the whole data source
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Args:
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matched_keys (list): list of unique keys based on specified match_keys
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fail_missing_match_value (bool): Fail if match_key value is missing in a data set
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Returns:
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set: set of unique values
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"""
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errors_match_values = []
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all_values = set(itertools.chain.from_iterable(results))
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all_values = set(itertools.chain.from_iterable(matched_keys))
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if fail_missing_match_value:
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for ds_idx, ds_values in enumerate(results):
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for ds_idx, ds_values in enumerate(matched_keys):
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missing_match = all_values - ds_values
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if missing_match:
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errors_match_values.append(
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@ -96,13 +96,21 @@ def check_missing_match_values(results, fail_missing_match_value):
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def consolidate_facts(data_sources, all_values):
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"""Iterate over all the data sources and consolidate the data
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Args:
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data_sources (list): supplied data sources
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all_values (set): a set of keys to iterate over
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Returns:
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list: list of consolidated data
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"""
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consolidated_facts = {}
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for data_source in data_sources:
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match_key = data_source["match_key"]
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source = data_source["prefix"]
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data_dict = {
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d[match_key]: d for d in data_source["data"] if match_key in d
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}
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data_dict = {d[match_key]: d for d in data_source["data"] if match_key in d}
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for value in sorted(all_values):
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if value not in consolidated_facts:
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consolidated_facts[value] = {}
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@ -116,19 +124,21 @@ def consolidate(
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fail_missing_match_value=False,
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fail_duplicate=False,
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):
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"""keep selective keys recursively from a given data"
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:param data: The data passed in (data|keep_keys(...))
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:type data: raw
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:param target: List of keys on with operation is to be performed
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:type data: list
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:type elements: string
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:param matching_parameter: matching type of the target keys with data keys
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:type data: str
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"""Calls data validation and consolidation functions
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Args:
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data_source (list): list of dicts as data sources
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fail_missing_match_key (bool, optional): Fails if match_keys not present in data set. Defaults to False.
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fail_missing_match_value (bool, optional): Fails if matching attribute missing in a data. Defaults to False.
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fail_duplicate (bool, optional): Fails if duplicate data present in a data. Defaults to False.
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Returns:
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list: list of dicts of validated and consolidated data
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"""
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# write code here
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key_sets = check_missing_match_key_duplicate(
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data_source, fail_missing_match_key, fail_duplicate
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)
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key_vals = check_missing_match_values(key_sets, fail_missing_match_value)
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datapr = consolidate_facts(data_source, key_vals)
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return datapr
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consolidated_facts = consolidate_facts(data_source, key_vals)
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return consolidated_facts
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