Datasets:
thisisanshgupta
/
Pycode

Dataset card Data Studio Files
xet
Community
text
stringlengths
0
828
LogRecordTable.annotate_with_row_schema(context.table, record_schema)
step_command_output_should_not_contain_log_records(context)
context.table.remove_columns([""level"", ""message""])"
1887,"def step_file_should_contain_log_records(context, filename):
""""""
Verifies that the command output contains the specified log records
(in any order).
.. code-block: gherkin
Then the file ""xxx.log"" should contain the log records:
| category | level | message |
| bar | CURRENT | xxx |
""""""
assert context.table, ""REQUIRE: context.table""
context.table.require_columns([""category"", ""level"", ""message""])
format = getattr(context, ""log_record_format"", context.config.logging_format)
for row in context.table.rows:
output = LogRecordTable.make_output_for_row(row, format)
context.text = output
step_file_should_contain_multiline_text(context, filename)"
1888,"def step_file_should_not_contain_log_records(context, filename):
""""""
Verifies that the command output contains the specified log records
(in any order).
.. code-block: gherkin
Then the file ""xxx.log"" should not contain the log records:
| category | level | message |
| bar | CURRENT | xxx |
""""""
assert context.table, ""REQUIRE: context.table""
context.table.require_columns([""category"", ""level"", ""message""])
format = getattr(context, ""log_record_format"", context.config.logging_format)
for row in context.table.rows:
output = LogRecordTable.make_output_for_row(row, format)
context.text = output
step_file_should_not_contain_multiline_text(context, filename)"
1889,"def step_use_log_record_configuration(context):
""""""
Define log record configuration parameters.
.. code-block: gherkin
Given I use the log record configuration:
| property | value |
| format | |
| datefmt | |
""""""
assert context.table, ""REQUIRE: context.table""
context.table.require_columns([""property"", ""value""])
for row in context.table.rows:
property_name = row[""property""]
value = row[""value""]
if property_name == ""format"":
context.log_record_format = value
elif property_name == ""datefmt"":
context.log_record_datefmt = value
else:
raise KeyError(""Unknown property=%s"" % property_name)"
1890,"def annotate_with_row_schema(table, row_schema):
""""""
Annotate/extend a table of log-records with additional columns from
the log-record schema if columns are missing.
:param table: Table w/ log-records (as :class:`behave.model.Table`)
:param row_schema: Log-record row schema (as dict).
""""""
for column, value in row_schema.items():
if column not in table.headings:
table.add_column(column, default_value=value)"
1891,"def smart_decode(binary, errors=""strict""):
""""""
Automatically find the right codec to decode binary data to string.
:param binary: binary data
:param errors: one of 'strict', 'ignore' and 'replace'
:return: string
""""""
d = chardet.detect(binary)
encoding = d[""encoding""]
confidence = d[""confidence""]
text = binary.decode(encoding, errors=errors)
return text, encoding, confidence"
1892,"def decode(self, binary, url, encoding=None, errors=""strict""):
""""""
Decode binary to string.
:param binary: binary content of a http request.
:param url: endpoint of the request.
:param encoding: manually specify the encoding.
:param errors: errors handle method.
:return: str
""""""
if encoding is None:
domain = util.get_domain(url)
if domain in self.domain_encoding_table: