89 lines
2.3 KiB
Python
89 lines
2.3 KiB
Python
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#!/usr/bin/python3
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# Copyright 2016 Mirantis, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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#
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import sys
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import glob
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import os
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import json
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def usage():
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h = """
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Format and sanitize Grafana dashboards
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Usage: {} <DIRECTORY|FILE>
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The program will:
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* Sort keys alphabetically.
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* Remove sections:
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templating.list[].current
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templating.list[].options
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* Override the time entry to {{"from": "now-1h","to": "now"}}
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* Enable the sharedCrosshair tooltip
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* Increment the version number
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WARNING: this script modifies directly the given file(s).
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If a DIRECTORY is provided, all files with suffix '.json' are modified.
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"""
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print(h.format(sys.argv[0]))
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if len(sys.argv) != 2:
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usage()
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sys.exit(1)
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arg = sys.argv[1]
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if os.path.isdir(arg):
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path = "{}/*.json".format(arg)
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elif os.path.isfile(arg):
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path = arg
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else:
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print("'{}' no such file or directory".format(arg))
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usage()
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sys.exit(1)
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for f in glob.glob(path):
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data = None
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absf = os.path.abspath(f)
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with open(absf) as out:
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data = json.load(out)
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for k, v in data.items():
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if k == 'annotations':
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for anno in v.get('list', []):
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anno['datasource'] = 'lma'
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if k == 'templating':
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variables = v.get('list', [])
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for o in variables:
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if o['type'] == 'query':
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o['options'] = []
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o['current'] = {}
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o['refresh_on_load'] = True
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data['time'] = {'from': 'now-1h', 'to': 'now'}
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data['sharedCrosshair'] = True
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data['refresh'] = '1m'
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data['id'] = None
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if data.get('version', None):
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data['version'] = data['version'] + 1
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else:
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data['version'] = 1
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with open(absf, 'w') as out:
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out.write(json.dumps(data, indent=2, sort_keys=True))
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