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Diffstat (limited to 'jython-tosca-parser/src/main/resources/Lib/site-packages/cliff-2.4.0-py2.7.egg/cliff/formatters/yaml_format.py')
-rw-r--r--jython-tosca-parser/src/main/resources/Lib/site-packages/cliff-2.4.0-py2.7.egg/cliff/formatters/yaml_format.py45
1 files changed, 0 insertions, 45 deletions
diff --git a/jython-tosca-parser/src/main/resources/Lib/site-packages/cliff-2.4.0-py2.7.egg/cliff/formatters/yaml_format.py b/jython-tosca-parser/src/main/resources/Lib/site-packages/cliff-2.4.0-py2.7.egg/cliff/formatters/yaml_format.py
deleted file mode 100644
index 8b1e64d..0000000
--- a/jython-tosca-parser/src/main/resources/Lib/site-packages/cliff-2.4.0-py2.7.egg/cliff/formatters/yaml_format.py
+++ /dev/null
@@ -1,45 +0,0 @@
-# Licensed under the Apache License, Version 2.0 (the "License"); you may
-# not use this file except in compliance with the License. You may obtain
-# a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
-# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
-# License for the specific language governing permissions and limitations
-# under the License.
-
-"""Output formatters using PyYAML.
-"""
-
-import yaml
-
-from . import base
-from cliff import columns
-
-
-class YAMLFormatter(base.ListFormatter, base.SingleFormatter):
-
- def add_argument_group(self, parser):
- pass
-
- def emit_list(self, column_names, data, stdout, parsed_args):
- items = []
- for item in data:
- items.append(
- {n: (i.machine_readable()
- if isinstance(i, columns.FormattableColumn)
- else i)
- for n, i in zip(column_names, item)}
- )
- yaml.safe_dump(items, stream=stdout, default_flow_style=False)
-
- def emit_one(self, column_names, data, stdout, parsed_args):
- for key, value in zip(column_names, data):
- dict_data = {
- key: (value.machine_readable()
- if isinstance(value, columns.FormattableColumn)
- else value)
- }
- yaml.safe_dump(dict_data, stream=stdout, default_flow_style=False)