repo_name stringlengths 6 100 | path stringlengths 4 294 | copies stringlengths 1 5 | size stringlengths 4 6 | content stringlengths 606 896k | license stringclasses 15
values |
|---|---|---|---|---|---|
lintzc/gpdb | src/test/unit/mock/special.py | 20 | 2211 |
class SpecialFuncs(object):
@classmethod
def make_body(cls, func):
key = 'make_body_' + func.funcname
if key in cls.__dict__:
return cls.__dict__[key].__get__(None, SpecialFuncs)(func)
@staticmethod
def make_body_MemoryContextAllocZeroImpl(func):
return """
void *p = malloc(size);
memset(p, 0, size);
return p;
"""
@staticmethod
def make_body_MemoryContextAllocImpl(func):
return """
void *p = malloc(size);
return p;
"""
@staticmethod
def make_body_MemoryContextFreeImpl(func):
return """
free(pointer);
"""
@staticmethod
def make_body_MemoryContextStrdup(func):
return """
return strdup(string);
"""
@staticmethod
def make_body_MemoryContextReallocImpl(func):
return """
return realloc(pointer, size);
"""
@staticmethod
def make_body_MemoryContextAllocZeroAlignedImpl(func):
return """
void *p = malloc(size);
memset(p, 0, size);
return p;
"""
class ByValStructs(object):
"""These are structs over 32 bit and possibly passed by-value.
As our mock framework doesn't accept 64 bit integer in some platform,
we have to treat them specially.
"""
type_names = set([
'ArrayTuple',
'CdbPathLocus',
'Complex',
'DbDirNode',
'DirectDispatchCalculationInfo',
'FileRepIdentifier_u',
'FileRepOperationDescription_u',
'FileRepRelFileNodeInfo_s',
'FileRepVerifyArguments',
'FileRepVerifyLogControl_s',
'FileRepVerifyRequest_s',
'instr_time',
'Interval',
'ItemPointerData',
'NameData',
'mpp_fd_set',
'PGSemaphoreData',
'PossibleValueSet',
'PrimaryMirrorModeTransitionArguments',
'RelFileNode',
'struct timeval',
'VariableStatData',
'XLogRecPtr'
])
@classmethod
def has(cls, argtype):
return argtype in cls.type_names
| apache-2.0 |
gusai-francelabs/datafari | windows/python/Lib/encodings/utf_16_le.py | 860 | 1037 | """ Python 'utf-16-le' Codec
Written by Marc-Andre Lemburg (mal@lemburg.com).
(c) Copyright CNRI, All Rights Reserved. NO WARRANTY.
"""
import codecs
### Codec APIs
encode = codecs.utf_16_le_encode
def decode(input, errors='strict'):
return codecs.utf_16_le_decode(input, errors, True)
class IncrementalEncoder(codecs.IncrementalEncoder):
def encode(self, input, final=False):
return codecs.utf_16_le_encode(input, self.errors)[0]
class IncrementalDecoder(codecs.BufferedIncrementalDecoder):
_buffer_decode = codecs.utf_16_le_decode
class StreamWriter(codecs.StreamWriter):
encode = codecs.utf_16_le_encode
class StreamReader(codecs.StreamReader):
decode = codecs.utf_16_le_decode
### encodings module API
def getregentry():
return codecs.CodecInfo(
name='utf-16-le',
encode=encode,
decode=decode,
incrementalencoder=IncrementalEncoder,
incrementaldecoder=IncrementalDecoder,
streamreader=StreamReader,
streamwriter=StreamWriter,
)
| apache-2.0 |
rouault/Quantum-GIS | tests/src/python/test_qgsserver_wms_getfeatureinfo.py | 1 | 17012 | # -*- coding: utf-8 -*-
"""QGIS Unit tests for QgsServer GetFeatureInfo WMS.
From build dir, run: ctest -R PyQgsServerWMSGetFeatureInfo -V
.. note:: This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
"""
__author__ = 'Alessandro Pasotti'
__date__ = '11/03/2018'
__copyright__ = 'Copyright 2018, The QGIS Project'
# This will get replaced with a git SHA1 when you do a git archive
__revision__ = '$Format:%H$'
import os
# Needed on Qt 5 so that the serialization of XML is consistent among all executions
os.environ['QT_HASH_SEED'] = '1'
import re
import urllib.request
import urllib.parse
import urllib.error
from qgis.testing import unittest
from qgis.PyQt.QtCore import QSize
import osgeo.gdal # NOQA
from test_qgsserver_wms import TestQgsServerWMSTestBase
from qgis.core import QgsProject
class TestQgsServerWMSGetFeatureInfo(TestQgsServerWMSTestBase):
"""QGIS Server WMS Tests for GetFeatureInfo request"""
def testGetFeatureInfo(self):
# Test getfeatureinfo response xml
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&styles=&' +
'info_format=text%2Fxml&transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer%20%C3%A8%C3%A9&X=190&Y=320',
'wms_getfeatureinfo-text-xml')
self.wms_request_compare('GetFeatureInfo',
'&layers=&styles=&' +
'info_format=text%2Fxml&transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer%20%C3%A8%C3%A9&X=190&Y=320',
'wms_getfeatureinfo-text-xml')
# Test getfeatureinfo response html
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&styles=&' +
'info_format=text%2Fhtml&transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer%20%C3%A8%C3%A9&X=190&Y=320',
'wms_getfeatureinfo-text-html')
# Test getfeatureinfo response html with geometry
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&styles=&' +
'info_format=text%2Fhtml&transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer%20%C3%A8%C3%A9&X=190&Y=320&' +
'with_geometry=true',
'wms_getfeatureinfo-text-html-geometry')
# Test getfeatureinfo response html with maptip
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&styles=&' +
'info_format=text%2Fhtml&transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer%20%C3%A8%C3%A9&X=190&Y=320&' +
'with_maptip=true',
'wms_getfeatureinfo-text-html-maptip')
# Test getfeatureinfo response text
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&styles=&' +
'transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer%20%C3%A8%C3%A9&X=190&Y=320&' +
'info_format=text/plain',
'wms_getfeatureinfo-text-plain')
# Test getfeatureinfo default info_format
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&styles=&' +
'transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer%20%C3%A8%C3%A9&X=190&Y=320',
'wms_getfeatureinfo-text-plain')
# Test getfeatureinfo invalid info_format
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&styles=&' +
'transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer%20%C3%A8%C3%A9&X=190&Y=320&' +
'info_format=InvalidFormat',
'wms_getfeatureinfo-invalid-format')
# Test feature info request with filter geometry
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&' +
'INFO_FORMAT=text%2Fxml&' +
'width=600&height=400&srs=EPSG%3A4326&' +
'query_layers=testlayer%20%C3%A8%C3%A9&' +
'FEATURE_COUNT=10&FILTER_GEOM=POLYGON((8.2035381 44.901459,8.2035562 44.901459,8.2035562 44.901418,8.2035381 44.901418,8.2035381 44.901459))',
'wms_getfeatureinfo_geometry_filter')
# Test feature info request with filter geometry in non-layer CRS
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&' +
'INFO_FORMAT=text%2Fxml&' +
'width=600&height=400&srs=EPSG%3A3857&' +
'query_layers=testlayer%20%C3%A8%C3%A9&' +
'FEATURE_COUNT=10&FILTER_GEOM=POLYGON ((913213.6839952 5606021.5399693, 913215.6988780 5606021.5399693, 913215.6988780 5606015.09643322, 913213.6839952 5606015.0964332, 913213.6839952 5606021.5399693))',
'wms_getfeatureinfo_geometry_filter_3857')
# Test feature info request with invalid query_layer
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&' +
'INFO_FORMAT=text%2Fxml&' +
'width=600&height=400&srs=EPSG%3A3857&' +
'query_layers=InvalidLayer&' +
'FEATURE_COUNT=10&FILTER_GEOM=POLYGON((8.2035381 44.901459,8.2035562 44.901459,8.2035562 44.901418,8.2035381 44.901418,8.2035381 44.901459))',
'wms_getfeatureinfo_invalid_query_layers')
# Test feature info request with '+' instead of ' ' in layers and
# query_layers parameters
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer+%C3%A8%C3%A9&styles=&' +
'info_format=text%2Fxml&transparent=true&' +
'width=600&height=400&srs=EPSG%3A3857&bbox=913190.6389747962%2C' +
'5606005.488876367%2C913235.426296057%2C5606035.347090538&' +
'query_layers=testlayer+%C3%A8%C3%A9&X=190&Y=320',
'wms_getfeatureinfo-text-xml')
# layer1 is a clone of layer0 but with a scale visibility. Thus,
# GetFeatureInfo response contains only a feature for layer0 and layer1
# is ignored for the required bbox. Without the scale visibility option,
# the feature for layer1 would have been in the response too.
mypath = self.testdata_path + "test_project_scalevisibility.qgs"
self.wms_request_compare('GetFeatureInfo',
'&layers=layer0,layer1&styles=&' +
'VERSION=1.1.0&' +
'info_format=text%2Fxml&' +
'width=500&height=500&srs=EPSG%3A4326' +
'&bbox=8.1976,44.8998,8.2100,44.9027&' +
'query_layers=layer0,layer1&X=235&Y=243',
'wms_getfeatureinfo_notvisible',
'test_project_scalevisibility.qgs')
# Test GetFeatureInfo resolves "value map" widget values
mypath = self.testdata_path + "test_project_values.qgs"
self.wms_request_compare('GetFeatureInfo',
'&layers=layer0&styles=&' +
'VERSION=1.3.0&' +
'info_format=text%2Fxml&' +
'width=926&height=787&srs=EPSG%3A4326' +
'&bbox=912217,5605059,914099,5606652' +
'&CRS=EPSG:3857' +
'&FEATURE_COUNT=10' +
'&QUERY_LAYERS=layer0&I=487&J=308',
'wms_getfeatureinfo-values1-text-xml',
'test_project_values.qgs')
# TODO fix regression in QGIS 3 as the widget values don't get solved and enable test
@unittest.expectedFailure
def testGetFeatureInfoValueRelation(self):
"""Test GetFeatureInfo resolves "value relation" widget values"""
mypath = self.testdata_path + "test_project_values.qgs"
self.wms_request_compare('GetFeatureInfo',
'&layers=layer1&styles=&' +
'VERSION=1.3.0&' +
'info_format=text%2Fxml&' +
'width=926&height=787&srs=EPSG%3A4326' +
'&bbox=912217,5605059,914099,5606652' +
'&CRS=EPSG:3857' +
'&FEATURE_COUNT=10' +
'&WITH_GEOMETRY=True' +
'&QUERY_LAYERS=layer1&I=487&J=308',
'wms_getfeatureinfo-values1-text-xml',
'test_project_values.qgs')
# TODO make GetFeatureInfo show the dictionary values and enable test
@unittest.expectedFailure
def testGetFeatureInfoValueRelationArray(self):
"""Test GetFeatureInfo on "value relation" widget with array field (multiple selections)"""
mypath = self.testdata_path + "test_project_values.qgs"
self.wms_request_compare('GetFeatureInfo',
'&layers=layer3&styles=&' +
'VERSION=1.3.0&' +
'info_format=text%2Fxml&' +
'width=926&height=787&srs=EPSG%3A4326' +
'&bbox=912217,5605059,914099,5606652' +
'&CRS=EPSG:3857' +
'&FEATURE_COUNT=10' +
'&WITH_GEOMETRY=True' +
'&QUERY_LAYERS=layer3&I=487&J=308',
'wms_getfeatureinfo-values3-text-xml',
'test_project_values.qgs')
# TODO make GetFeatureInfo show what's in the display expression and enable test
@unittest.expectedFailure
def testGetFeatureInfoRelationReference(self):
"""Test GetFeatureInfo solves "relation reference" widget "display expression" values"""
mypath = self.testdata_path + "test_project_values.qgs"
self.wms_request_compare('GetFeatureInfo',
'&layers=layer2&styles=&' +
'VERSION=1.3.0&' +
'info_format=text%2Fxml&' +
'width=926&height=787&srs=EPSG%3A4326' +
'&bbox=912217,5605059,914099,5606652' +
'&CRS=EPSG:3857' +
'&FEATURE_COUNT=10' +
'&WITH_GEOMETRY=True' +
'&QUERY_LAYERS=layer2&I=487&J=308',
'wms_getfeatureinfo-values2-text-xml',
'test_project_values.qgs')
def testGetFeatureInfoFilter(self):
# Test getfeatureinfo response xml
# Regression for #8656
# Mind the gap! (the space in the FILTER expression)
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&' +
'INFO_FORMAT=text%2Fxml&' +
'width=600&height=400&srs=EPSG%3A3857&' +
'query_layers=testlayer%20%C3%A8%C3%A9&' +
'FEATURE_COUNT=10&FILTER=testlayer%20%C3%A8%C3%A9' + urllib.parse.quote(':"NAME" = \'two\''),
'wms_getfeatureinfo_filter')
# Test a filter with NO condition results
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&' +
'INFO_FORMAT=text%2Fxml&' +
'width=600&height=400&srs=EPSG%3A3857&' +
'query_layers=testlayer%20%C3%A8%C3%A9&' +
'FEATURE_COUNT=10&FILTER=testlayer%20%C3%A8%C3%A9' + urllib.parse.quote(':"NAME" = \'two\' AND "utf8nameè" = \'no-results\''),
'wms_getfeatureinfo_filter_no_results')
# Test a filter with OR condition results
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&' +
'INFO_FORMAT=text%2Fxml&' +
'width=600&height=400&srs=EPSG%3A3857&' +
'query_layers=testlayer%20%C3%A8%C3%A9&' +
'FEATURE_COUNT=10&FILTER=testlayer%20%C3%A8%C3%A9' + urllib.parse.quote(':"NAME" = \'two\' OR "NAME" = \'three\''),
'wms_getfeatureinfo_filter_or')
# Test a filter with OR condition and UTF results
# Note that the layer name that contains utf-8 chars cannot be
# to upper case.
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&' +
'INFO_FORMAT=text%2Fxml&' +
'width=600&height=400&srs=EPSG%3A3857&' +
'query_layers=testlayer%20%C3%A8%C3%A9&' +
'FEATURE_COUNT=10&FILTER=testlayer%20%C3%A8%C3%A9' + urllib.parse.quote(':"NAME" = \'two\' OR "utf8nameè" = \'three èé↓\''),
'wms_getfeatureinfo_filter_or_utf8')
# Regression #18292 Server GetFeatureInfo FILTER search fails when WIDTH, HEIGHT are not specified
self.wms_request_compare('GetFeatureInfo',
'&layers=testlayer%20%C3%A8%C3%A9&' +
'INFO_FORMAT=text%2Fxml&' +
'srs=EPSG%3A3857&' +
'query_layers=testlayer%20%C3%A8%C3%A9&' +
'FEATURE_COUNT=10&FILTER=testlayer%20%C3%A8%C3%A9' + urllib.parse.quote(':"NAME" = \'two\''),
'wms_getfeatureinfo_filter_no_width')
if __name__ == '__main__':
unittest.main()
| gpl-2.0 |
GdZ/scriptfile | software/googleAppEngine/lib/django_1_2/django/utils/html.py | 202 | 8105 | """HTML utilities suitable for global use."""
import re
import string
from django.utils.safestring import SafeData, mark_safe
from django.utils.encoding import force_unicode
from django.utils.functional import allow_lazy
from django.utils.http import urlquote
# Configuration for urlize() function.
LEADING_PUNCTUATION = ['(', '<', '<']
TRAILING_PUNCTUATION = ['.', ',', ')', '>', '\n', '>']
# List of possible strings used for bullets in bulleted lists.
DOTS = ['·', '*', '\xe2\x80\xa2', '•', '•', '•']
unencoded_ampersands_re = re.compile(r'&(?!(\w+|#\d+);)')
word_split_re = re.compile(r'(\s+)')
punctuation_re = re.compile('^(?P<lead>(?:%s)*)(?P<middle>.*?)(?P<trail>(?:%s)*)$' % \
('|'.join([re.escape(x) for x in LEADING_PUNCTUATION]),
'|'.join([re.escape(x) for x in TRAILING_PUNCTUATION])))
simple_email_re = re.compile(r'^\S+@[a-zA-Z0-9._-]+\.[a-zA-Z0-9._-]+$')
link_target_attribute_re = re.compile(r'(<a [^>]*?)target=[^\s>]+')
html_gunk_re = re.compile(r'(?:<br clear="all">|<i><\/i>|<b><\/b>|<em><\/em>|<strong><\/strong>|<\/?smallcaps>|<\/?uppercase>)', re.IGNORECASE)
hard_coded_bullets_re = re.compile(r'((?:<p>(?:%s).*?[a-zA-Z].*?</p>\s*)+)' % '|'.join([re.escape(x) for x in DOTS]), re.DOTALL)
trailing_empty_content_re = re.compile(r'(?:<p>(?: |\s|<br \/>)*?</p>\s*)+\Z')
del x # Temporary variable
def escape(html):
"""
Returns the given HTML with ampersands, quotes and angle brackets encoded.
"""
return mark_safe(force_unicode(html).replace('&', '&').replace('<', '<').replace('>', '>').replace('"', '"').replace("'", '''))
escape = allow_lazy(escape, unicode)
_base_js_escapes = (
('\\', r'\u005C'),
('\'', r'\u0027'),
('"', r'\u0022'),
('>', r'\u003E'),
('<', r'\u003C'),
('&', r'\u0026'),
('=', r'\u003D'),
('-', r'\u002D'),
(';', r'\u003B'),
(u'\u2028', r'\u2028'),
(u'\u2029', r'\u2029')
)
# Escape every ASCII character with a value less than 32.
_js_escapes = (_base_js_escapes +
tuple([('%c' % z, '\\u%04X' % z) for z in range(32)]))
def escapejs(value):
"""Hex encodes characters for use in JavaScript strings."""
for bad, good in _js_escapes:
value = mark_safe(force_unicode(value).replace(bad, good))
return value
escapejs = allow_lazy(escapejs, unicode)
def conditional_escape(html):
"""
Similar to escape(), except that it doesn't operate on pre-escaped strings.
"""
if isinstance(html, SafeData):
return html
else:
return escape(html)
def linebreaks(value, autoescape=False):
"""Converts newlines into <p> and <br />s."""
value = re.sub(r'\r\n|\r|\n', '\n', force_unicode(value)) # normalize newlines
paras = re.split('\n{2,}', value)
if autoescape:
paras = [u'<p>%s</p>' % escape(p).replace('\n', '<br />') for p in paras]
else:
paras = [u'<p>%s</p>' % p.replace('\n', '<br />') for p in paras]
return u'\n\n'.join(paras)
linebreaks = allow_lazy(linebreaks, unicode)
def strip_tags(value):
"""Returns the given HTML with all tags stripped."""
return re.sub(r'<[^>]*?>', '', force_unicode(value))
strip_tags = allow_lazy(strip_tags)
def strip_spaces_between_tags(value):
"""Returns the given HTML with spaces between tags removed."""
return re.sub(r'>\s+<', '><', force_unicode(value))
strip_spaces_between_tags = allow_lazy(strip_spaces_between_tags, unicode)
def strip_entities(value):
"""Returns the given HTML with all entities (&something;) stripped."""
return re.sub(r'&(?:\w+|#\d+);', '', force_unicode(value))
strip_entities = allow_lazy(strip_entities, unicode)
def fix_ampersands(value):
"""Returns the given HTML with all unencoded ampersands encoded correctly."""
return unencoded_ampersands_re.sub('&', force_unicode(value))
fix_ampersands = allow_lazy(fix_ampersands, unicode)
def urlize(text, trim_url_limit=None, nofollow=False, autoescape=False):
"""
Converts any URLs in text into clickable links.
Works on http://, https://, www. links and links ending in .org, .net or
.com. Links can have trailing punctuation (periods, commas, close-parens)
and leading punctuation (opening parens) and it'll still do the right
thing.
If trim_url_limit is not None, the URLs in link text longer than this limit
will truncated to trim_url_limit-3 characters and appended with an elipsis.
If nofollow is True, the URLs in link text will get a rel="nofollow"
attribute.
If autoescape is True, the link text and URLs will get autoescaped.
"""
trim_url = lambda x, limit=trim_url_limit: limit is not None and (len(x) > limit and ('%s...' % x[:max(0, limit - 3)])) or x
safe_input = isinstance(text, SafeData)
words = word_split_re.split(force_unicode(text))
nofollow_attr = nofollow and ' rel="nofollow"' or ''
for i, word in enumerate(words):
match = None
if '.' in word or '@' in word or ':' in word:
match = punctuation_re.match(word)
if match:
lead, middle, trail = match.groups()
# Make URL we want to point to.
url = None
if middle.startswith('http://') or middle.startswith('https://'):
url = urlquote(middle, safe='/&=:;#?+*')
elif middle.startswith('www.') or ('@' not in middle and \
middle and middle[0] in string.ascii_letters + string.digits and \
(middle.endswith('.org') or middle.endswith('.net') or middle.endswith('.com'))):
url = urlquote('http://%s' % middle, safe='/&=:;#?+*')
elif '@' in middle and not ':' in middle and simple_email_re.match(middle):
url = 'mailto:%s' % middle
nofollow_attr = ''
# Make link.
if url:
trimmed = trim_url(middle)
if autoescape and not safe_input:
lead, trail = escape(lead), escape(trail)
url, trimmed = escape(url), escape(trimmed)
middle = '<a href="%s"%s>%s</a>' % (url, nofollow_attr, trimmed)
words[i] = mark_safe('%s%s%s' % (lead, middle, trail))
else:
if safe_input:
words[i] = mark_safe(word)
elif autoescape:
words[i] = escape(word)
elif safe_input:
words[i] = mark_safe(word)
elif autoescape:
words[i] = escape(word)
return u''.join(words)
urlize = allow_lazy(urlize, unicode)
def clean_html(text):
"""
Clean the given HTML. Specifically, do the following:
* Convert <b> and <i> to <strong> and <em>.
* Encode all ampersands correctly.
* Remove all "target" attributes from <a> tags.
* Remove extraneous HTML, such as presentational tags that open and
immediately close and <br clear="all">.
* Convert hard-coded bullets into HTML unordered lists.
* Remove stuff like "<p> </p>", but only if it's at the
bottom of the text.
"""
from django.utils.text import normalize_newlines
text = normalize_newlines(force_unicode(text))
text = re.sub(r'<(/?)\s*b\s*>', '<\\1strong>', text)
text = re.sub(r'<(/?)\s*i\s*>', '<\\1em>', text)
text = fix_ampersands(text)
# Remove all target="" attributes from <a> tags.
text = link_target_attribute_re.sub('\\1', text)
# Trim stupid HTML such as <br clear="all">.
text = html_gunk_re.sub('', text)
# Convert hard-coded bullets into HTML unordered lists.
def replace_p_tags(match):
s = match.group().replace('</p>', '</li>')
for d in DOTS:
s = s.replace('<p>%s' % d, '<li>')
return u'<ul>\n%s\n</ul>' % s
text = hard_coded_bullets_re.sub(replace_p_tags, text)
# Remove stuff like "<p> </p>", but only if it's at the bottom
# of the text.
text = trailing_empty_content_re.sub('', text)
return text
clean_html = allow_lazy(clean_html, unicode)
| mit |
maxdeliso/elevatorSim | Lib/test/test_runpy.py | 5 | 23521 | # Test the runpy module
import unittest
import os
import os.path
import sys
import re
import tempfile
import importlib
import py_compile
from test.support import (
forget, make_legacy_pyc, run_unittest, unload, verbose, no_tracing,
create_empty_file)
from test.script_helper import (
make_pkg, make_script, make_zip_pkg, make_zip_script, temp_dir)
import runpy
from runpy import _run_code, _run_module_code, run_module, run_path
# Note: This module can't safely test _run_module_as_main as it
# runs its tests in the current process, which would mess with the
# real __main__ module (usually test.regrtest)
# See test_cmd_line_script for a test that executes that code path
# Set up the test code and expected results
example_source = """\
# Check basic code execution
result = ['Top level assignment']
def f():
result.append('Lower level reference')
f()
del f
# Check the sys module
import sys
run_argv0 = sys.argv[0]
run_name_in_sys_modules = __name__ in sys.modules
module_in_sys_modules = (run_name_in_sys_modules and
globals() is sys.modules[__name__].__dict__)
# Check nested operation
import runpy
nested = runpy._run_module_code('x=1\\n', mod_name='<run>')
"""
implicit_namespace = {
"__name__": None,
"__file__": None,
"__cached__": None,
"__package__": None,
"__doc__": None,
}
example_namespace = {
"sys": sys,
"runpy": runpy,
"result": ["Top level assignment", "Lower level reference"],
"run_argv0": sys.argv[0],
"run_name_in_sys_modules": False,
"module_in_sys_modules": False,
"nested": dict(implicit_namespace,
x=1, __name__="<run>", __loader__=None),
}
example_namespace.update(implicit_namespace)
class CodeExecutionMixin:
# Issue #15230 (run_path not handling run_name correctly) highlighted a
# problem with the way arguments were being passed from higher level APIs
# down to lower level code. This mixin makes it easier to ensure full
# testing occurs at those upper layers as well, not just at the utility
# layer
def assertNamespaceMatches(self, result_ns, expected_ns):
"""Check two namespaces match.
Ignores any unspecified interpreter created names
"""
# Impls are permitted to add extra names, so filter them out
for k in list(result_ns):
if k.startswith("__") and k.endswith("__"):
if k not in expected_ns:
result_ns.pop(k)
if k not in expected_ns["nested"]:
result_ns["nested"].pop(k)
# Don't use direct dict comparison - the diffs are too hard to debug
self.assertEqual(set(result_ns), set(expected_ns))
for k in result_ns:
actual = (k, result_ns[k])
expected = (k, expected_ns[k])
self.assertEqual(actual, expected)
def check_code_execution(self, create_namespace, expected_namespace):
"""Check that an interface runs the example code correctly
First argument is a callable accepting the initial globals and
using them to create the actual namespace
Second argument is the expected result
"""
sentinel = object()
expected_ns = expected_namespace.copy()
run_name = expected_ns["__name__"]
saved_argv0 = sys.argv[0]
saved_mod = sys.modules.get(run_name, sentinel)
# Check without initial globals
result_ns = create_namespace(None)
self.assertNamespaceMatches(result_ns, expected_ns)
self.assertIs(sys.argv[0], saved_argv0)
self.assertIs(sys.modules.get(run_name, sentinel), saved_mod)
# And then with initial globals
initial_ns = {"sentinel": sentinel}
expected_ns["sentinel"] = sentinel
result_ns = create_namespace(initial_ns)
self.assertIsNot(result_ns, initial_ns)
self.assertNamespaceMatches(result_ns, expected_ns)
self.assertIs(sys.argv[0], saved_argv0)
self.assertIs(sys.modules.get(run_name, sentinel), saved_mod)
class ExecutionLayerTestCase(unittest.TestCase, CodeExecutionMixin):
"""Unit tests for runpy._run_code and runpy._run_module_code"""
def test_run_code(self):
expected_ns = example_namespace.copy()
expected_ns.update({
"__loader__": None,
})
def create_ns(init_globals):
return _run_code(example_source, {}, init_globals)
self.check_code_execution(create_ns, expected_ns)
def test_run_module_code(self):
mod_name = "<Nonsense>"
mod_fname = "Some other nonsense"
mod_loader = "Now you're just being silly"
mod_package = '' # Treat as a top level module
expected_ns = example_namespace.copy()
expected_ns.update({
"__name__": mod_name,
"__file__": mod_fname,
"__loader__": mod_loader,
"__package__": mod_package,
"run_argv0": mod_fname,
"run_name_in_sys_modules": True,
"module_in_sys_modules": True,
})
def create_ns(init_globals):
return _run_module_code(example_source,
init_globals,
mod_name,
mod_fname,
mod_loader,
mod_package)
self.check_code_execution(create_ns, expected_ns)
# TODO: Use self.addCleanup to get rid of a lot of try-finally blocks
class RunModuleTestCase(unittest.TestCase, CodeExecutionMixin):
"""Unit tests for runpy.run_module"""
def expect_import_error(self, mod_name):
try:
run_module(mod_name)
except ImportError:
pass
else:
self.fail("Expected import error for " + mod_name)
def test_invalid_names(self):
# Builtin module
self.expect_import_error("sys")
# Non-existent modules
self.expect_import_error("sys.imp.eric")
self.expect_import_error("os.path.half")
self.expect_import_error("a.bee")
self.expect_import_error(".howard")
self.expect_import_error("..eaten")
# Package without __main__.py
self.expect_import_error("multiprocessing")
def test_library_module(self):
self.assertEqual(run_module("runpy")["__name__"], "runpy")
def _add_pkg_dir(self, pkg_dir):
os.mkdir(pkg_dir)
pkg_fname = os.path.join(pkg_dir, "__init__.py")
create_empty_file(pkg_fname)
return pkg_fname
def _make_pkg(self, source, depth, mod_base="runpy_test"):
pkg_name = "__runpy_pkg__"
test_fname = mod_base+os.extsep+"py"
pkg_dir = sub_dir = os.path.realpath(tempfile.mkdtemp())
if verbose > 1: print(" Package tree in:", sub_dir)
sys.path.insert(0, pkg_dir)
if verbose > 1: print(" Updated sys.path:", sys.path[0])
for i in range(depth):
sub_dir = os.path.join(sub_dir, pkg_name)
pkg_fname = self._add_pkg_dir(sub_dir)
if verbose > 1: print(" Next level in:", sub_dir)
if verbose > 1: print(" Created:", pkg_fname)
mod_fname = os.path.join(sub_dir, test_fname)
mod_file = open(mod_fname, "w")
mod_file.write(source)
mod_file.close()
if verbose > 1: print(" Created:", mod_fname)
mod_name = (pkg_name+".")*depth + mod_base
return pkg_dir, mod_fname, mod_name
def _del_pkg(self, top, depth, mod_name):
for entry in list(sys.modules):
if entry.startswith("__runpy_pkg__"):
del sys.modules[entry]
if verbose > 1: print(" Removed sys.modules entries")
del sys.path[0]
if verbose > 1: print(" Removed sys.path entry")
for root, dirs, files in os.walk(top, topdown=False):
for name in files:
try:
os.remove(os.path.join(root, name))
except OSError as ex:
if verbose > 1: print(ex) # Persist with cleaning up
for name in dirs:
fullname = os.path.join(root, name)
try:
os.rmdir(fullname)
except OSError as ex:
if verbose > 1: print(ex) # Persist with cleaning up
try:
os.rmdir(top)
if verbose > 1: print(" Removed package tree")
except OSError as ex:
if verbose > 1: print(ex) # Persist with cleaning up
def _fix_ns_for_legacy_pyc(self, ns, alter_sys):
char_to_add = "c" if __debug__ else "o"
ns["__file__"] += char_to_add
if alter_sys:
ns["run_argv0"] += char_to_add
def _check_module(self, depth, alter_sys=False):
pkg_dir, mod_fname, mod_name = (
self._make_pkg(example_source, depth))
forget(mod_name)
expected_ns = example_namespace.copy()
expected_ns.update({
"__name__": mod_name,
"__file__": mod_fname,
"__package__": mod_name.rpartition(".")[0],
})
if alter_sys:
expected_ns.update({
"run_argv0": mod_fname,
"run_name_in_sys_modules": True,
"module_in_sys_modules": True,
})
def create_ns(init_globals):
return run_module(mod_name, init_globals, alter_sys=alter_sys)
try:
if verbose > 1: print("Running from source:", mod_name)
self.check_code_execution(create_ns, expected_ns)
importlib.invalidate_caches()
__import__(mod_name)
os.remove(mod_fname)
make_legacy_pyc(mod_fname)
unload(mod_name) # In case loader caches paths
importlib.invalidate_caches()
if verbose > 1: print("Running from compiled:", mod_name)
self._fix_ns_for_legacy_pyc(expected_ns, alter_sys)
self.check_code_execution(create_ns, expected_ns)
finally:
self._del_pkg(pkg_dir, depth, mod_name)
if verbose > 1: print("Module executed successfully")
def _check_package(self, depth, alter_sys=False):
pkg_dir, mod_fname, mod_name = (
self._make_pkg(example_source, depth, "__main__"))
pkg_name = mod_name.rpartition(".")[0]
forget(mod_name)
expected_ns = example_namespace.copy()
expected_ns.update({
"__name__": mod_name,
"__file__": mod_fname,
"__package__": pkg_name,
})
if alter_sys:
expected_ns.update({
"run_argv0": mod_fname,
"run_name_in_sys_modules": True,
"module_in_sys_modules": True,
})
def create_ns(init_globals):
return run_module(pkg_name, init_globals, alter_sys=alter_sys)
try:
if verbose > 1: print("Running from source:", pkg_name)
self.check_code_execution(create_ns, expected_ns)
importlib.invalidate_caches()
__import__(mod_name)
os.remove(mod_fname)
make_legacy_pyc(mod_fname)
unload(mod_name) # In case loader caches paths
if verbose > 1: print("Running from compiled:", pkg_name)
importlib.invalidate_caches()
self._fix_ns_for_legacy_pyc(expected_ns, alter_sys)
self.check_code_execution(create_ns, expected_ns)
finally:
self._del_pkg(pkg_dir, depth, pkg_name)
if verbose > 1: print("Package executed successfully")
def _add_relative_modules(self, base_dir, source, depth):
if depth <= 1:
raise ValueError("Relative module test needs depth > 1")
pkg_name = "__runpy_pkg__"
module_dir = base_dir
for i in range(depth):
parent_dir = module_dir
module_dir = os.path.join(module_dir, pkg_name)
# Add sibling module
sibling_fname = os.path.join(module_dir, "sibling.py")
create_empty_file(sibling_fname)
if verbose > 1: print(" Added sibling module:", sibling_fname)
# Add nephew module
uncle_dir = os.path.join(parent_dir, "uncle")
self._add_pkg_dir(uncle_dir)
if verbose > 1: print(" Added uncle package:", uncle_dir)
cousin_dir = os.path.join(uncle_dir, "cousin")
self._add_pkg_dir(cousin_dir)
if verbose > 1: print(" Added cousin package:", cousin_dir)
nephew_fname = os.path.join(cousin_dir, "nephew.py")
create_empty_file(nephew_fname)
if verbose > 1: print(" Added nephew module:", nephew_fname)
def _check_relative_imports(self, depth, run_name=None):
contents = r"""\
from __future__ import absolute_import
from . import sibling
from ..uncle.cousin import nephew
"""
pkg_dir, mod_fname, mod_name = (
self._make_pkg(contents, depth))
if run_name is None:
expected_name = mod_name
else:
expected_name = run_name
try:
self._add_relative_modules(pkg_dir, contents, depth)
pkg_name = mod_name.rpartition('.')[0]
if verbose > 1: print("Running from source:", mod_name)
d1 = run_module(mod_name, run_name=run_name) # Read from source
self.assertEqual(d1["__name__"], expected_name)
self.assertEqual(d1["__package__"], pkg_name)
self.assertIn("sibling", d1)
self.assertIn("nephew", d1)
del d1 # Ensure __loader__ entry doesn't keep file open
importlib.invalidate_caches()
__import__(mod_name)
os.remove(mod_fname)
make_legacy_pyc(mod_fname)
unload(mod_name) # In case the loader caches paths
if verbose > 1: print("Running from compiled:", mod_name)
importlib.invalidate_caches()
d2 = run_module(mod_name, run_name=run_name) # Read from bytecode
self.assertEqual(d2["__name__"], expected_name)
self.assertEqual(d2["__package__"], pkg_name)
self.assertIn("sibling", d2)
self.assertIn("nephew", d2)
del d2 # Ensure __loader__ entry doesn't keep file open
finally:
self._del_pkg(pkg_dir, depth, mod_name)
if verbose > 1: print("Module executed successfully")
def test_run_module(self):
for depth in range(4):
if verbose > 1: print("Testing package depth:", depth)
self._check_module(depth)
def test_run_package(self):
for depth in range(1, 4):
if verbose > 1: print("Testing package depth:", depth)
self._check_package(depth)
def test_run_module_alter_sys(self):
for depth in range(4):
if verbose > 1: print("Testing package depth:", depth)
self._check_module(depth, alter_sys=True)
def test_run_package_alter_sys(self):
for depth in range(1, 4):
if verbose > 1: print("Testing package depth:", depth)
self._check_package(depth, alter_sys=True)
def test_explicit_relative_import(self):
for depth in range(2, 5):
if verbose > 1: print("Testing relative imports at depth:", depth)
self._check_relative_imports(depth)
def test_main_relative_import(self):
for depth in range(2, 5):
if verbose > 1: print("Testing main relative imports at depth:", depth)
self._check_relative_imports(depth, "__main__")
def test_run_name(self):
depth = 1
run_name = "And now for something completely different"
pkg_dir, mod_fname, mod_name = (
self._make_pkg(example_source, depth))
forget(mod_name)
expected_ns = example_namespace.copy()
expected_ns.update({
"__name__": run_name,
"__file__": mod_fname,
"__package__": mod_name.rpartition(".")[0],
})
def create_ns(init_globals):
return run_module(mod_name, init_globals, run_name)
try:
self.check_code_execution(create_ns, expected_ns)
finally:
self._del_pkg(pkg_dir, depth, mod_name)
def test_pkgutil_walk_packages(self):
# This is a dodgy hack to use the test_runpy infrastructure to test
# issue #15343. Issue #15348 declares this is indeed a dodgy hack ;)
import pkgutil
max_depth = 4
base_name = "__runpy_pkg__"
package_suffixes = ["uncle", "uncle.cousin"]
module_suffixes = ["uncle.cousin.nephew", base_name + ".sibling"]
expected_packages = set()
expected_modules = set()
for depth in range(1, max_depth):
pkg_name = ".".join([base_name] * depth)
expected_packages.add(pkg_name)
for name in package_suffixes:
expected_packages.add(pkg_name + "." + name)
for name in module_suffixes:
expected_modules.add(pkg_name + "." + name)
pkg_name = ".".join([base_name] * max_depth)
expected_packages.add(pkg_name)
expected_modules.add(pkg_name + ".runpy_test")
pkg_dir, mod_fname, mod_name = (
self._make_pkg("", max_depth))
self.addCleanup(self._del_pkg, pkg_dir, max_depth, mod_name)
for depth in range(2, max_depth+1):
self._add_relative_modules(pkg_dir, "", depth)
for finder, mod_name, ispkg in pkgutil.walk_packages([pkg_dir]):
self.assertIsInstance(finder,
importlib.machinery.FileFinder)
if ispkg:
expected_packages.remove(mod_name)
else:
expected_modules.remove(mod_name)
self.assertEqual(len(expected_packages), 0, expected_packages)
self.assertEqual(len(expected_modules), 0, expected_modules)
class RunPathTestCase(unittest.TestCase, CodeExecutionMixin):
"""Unit tests for runpy.run_path"""
def _make_test_script(self, script_dir, script_basename, source=None):
if source is None:
source = example_source
return make_script(script_dir, script_basename, source)
def _check_script(self, script_name, expected_name, expected_file,
expected_argv0):
# First check is without run_name
def create_ns(init_globals):
return run_path(script_name, init_globals)
expected_ns = example_namespace.copy()
expected_ns.update({
"__name__": expected_name,
"__file__": expected_file,
"__package__": "",
"run_argv0": expected_argv0,
"run_name_in_sys_modules": True,
"module_in_sys_modules": True,
})
self.check_code_execution(create_ns, expected_ns)
# Second check makes sure run_name works in all cases
run_name = "prove.issue15230.is.fixed"
def create_ns(init_globals):
return run_path(script_name, init_globals, run_name)
expected_ns["__name__"] = run_name
expected_ns["__package__"] = run_name.rpartition(".")[0]
self.check_code_execution(create_ns, expected_ns)
def _check_import_error(self, script_name, msg):
msg = re.escape(msg)
self.assertRaisesRegex(ImportError, msg, run_path, script_name)
def test_basic_script(self):
with temp_dir() as script_dir:
mod_name = 'script'
script_name = self._make_test_script(script_dir, mod_name)
self._check_script(script_name, "<run_path>", script_name,
script_name)
def test_script_compiled(self):
with temp_dir() as script_dir:
mod_name = 'script'
script_name = self._make_test_script(script_dir, mod_name)
compiled_name = py_compile.compile(script_name, doraise=True)
os.remove(script_name)
self._check_script(compiled_name, "<run_path>", compiled_name,
compiled_name)
def test_directory(self):
with temp_dir() as script_dir:
mod_name = '__main__'
script_name = self._make_test_script(script_dir, mod_name)
self._check_script(script_dir, "<run_path>", script_name,
script_dir)
def test_directory_compiled(self):
with temp_dir() as script_dir:
mod_name = '__main__'
script_name = self._make_test_script(script_dir, mod_name)
compiled_name = py_compile.compile(script_name, doraise=True)
os.remove(script_name)
legacy_pyc = make_legacy_pyc(script_name)
self._check_script(script_dir, "<run_path>", legacy_pyc,
script_dir)
def test_directory_error(self):
with temp_dir() as script_dir:
mod_name = 'not_main'
script_name = self._make_test_script(script_dir, mod_name)
msg = "can't find '__main__' module in %r" % script_dir
self._check_import_error(script_dir, msg)
def test_zipfile(self):
with temp_dir() as script_dir:
mod_name = '__main__'
script_name = self._make_test_script(script_dir, mod_name)
zip_name, fname = make_zip_script(script_dir, 'test_zip', script_name)
self._check_script(zip_name, "<run_path>", fname, zip_name)
def test_zipfile_compiled(self):
with temp_dir() as script_dir:
mod_name = '__main__'
script_name = self._make_test_script(script_dir, mod_name)
compiled_name = py_compile.compile(script_name, doraise=True)
zip_name, fname = make_zip_script(script_dir, 'test_zip',
compiled_name)
self._check_script(zip_name, "<run_path>", fname, zip_name)
def test_zipfile_error(self):
with temp_dir() as script_dir:
mod_name = 'not_main'
script_name = self._make_test_script(script_dir, mod_name)
zip_name, fname = make_zip_script(script_dir, 'test_zip', script_name)
msg = "can't find '__main__' module in %r" % zip_name
self._check_import_error(zip_name, msg)
@no_tracing
def test_main_recursion_error(self):
with temp_dir() as script_dir, temp_dir() as dummy_dir:
mod_name = '__main__'
source = ("import runpy\n"
"runpy.run_path(%r)\n") % dummy_dir
script_name = self._make_test_script(script_dir, mod_name, source)
zip_name, fname = make_zip_script(script_dir, 'test_zip', script_name)
msg = "recursion depth exceeded"
self.assertRaisesRegex(RuntimeError, msg, run_path, zip_name)
def test_encoding(self):
with temp_dir() as script_dir:
filename = os.path.join(script_dir, 'script.py')
with open(filename, 'w', encoding='latin1') as f:
f.write("""
#coding:latin1
"non-ASCII: h\xe9"
""")
result = run_path(filename)
self.assertEqual(result['__doc__'], "non-ASCII: h\xe9")
def test_main():
run_unittest(
ExecutionLayerTestCase,
RunModuleTestCase,
RunPathTestCase
)
if __name__ == "__main__":
test_main()
| bsd-2-clause |
barrysteyn/pelican-plugins | asciidoc_reader/asciidoc_reader.py | 24 | 1918 | # -*- coding: utf-8 -*-
"""
AsciiDoc Reader
===============
This plugin allows you to use AsciiDoc to write your posts.
File extension should be ``.asc``, ``.adoc``, or ``asciidoc``.
"""
from pelican.readers import BaseReader
from pelican.utils import pelican_open
from pelican import signals
try:
# asciidocapi won't import on Py3
from .asciidocapi import AsciiDocAPI, AsciiDocError
# AsciiDocAPI class checks for asciidoc.py
AsciiDocAPI()
except:
asciidoc_enabled = False
else:
asciidoc_enabled = True
class AsciiDocReader(BaseReader):
"""Reader for AsciiDoc files"""
enabled = asciidoc_enabled
file_extensions = ['asc', 'adoc', 'asciidoc']
default_options = ["--no-header-footer", "-a newline=\\n"]
default_backend = 'html5'
def read(self, source_path):
"""Parse content and metadata of asciidoc files"""
from cStringIO import StringIO
with pelican_open(source_path) as source:
text = StringIO(source.encode('utf8'))
content = StringIO()
ad = AsciiDocAPI()
options = self.settings.get('ASCIIDOC_OPTIONS', [])
options = self.default_options + options
for o in options:
ad.options(*o.split())
backend = self.settings.get('ASCIIDOC_BACKEND', self.default_backend)
ad.execute(text, content, backend=backend)
content = content.getvalue().decode('utf8')
metadata = {}
for name, value in ad.asciidoc.document.attributes.items():
name = name.lower()
metadata[name] = self.process_metadata(name, value)
if 'doctitle' in metadata:
metadata['title'] = metadata['doctitle']
return content, metadata
def add_reader(readers):
for ext in AsciiDocReader.file_extensions:
readers.reader_classes[ext] = AsciiDocReader
def register():
signals.readers_init.connect(add_reader)
| agpl-3.0 |
mfalcon/edujango | zinnia/views/quick_entry.py | 7 | 3417 | """Views for Zinnia quick entry"""
try:
from urllib.parse import urlencode
except: # Python 2
from urllib import urlencode
from django import forms
from django.shortcuts import redirect
from django.utils.html import linebreaks
from django.views.generic.base import View
from django.utils.encoding import smart_str
from django.core.urlresolvers import reverse
from django.contrib.sites.models import Site
from django.template.defaultfilters import slugify
from django.utils.decorators import method_decorator
from django.contrib.auth.decorators import permission_required
from django.utils import timezone
from zinnia.models.entry import Entry
from zinnia.managers import DRAFT
from zinnia.managers import PUBLISHED
from zinnia.settings import MARKUP_LANGUAGE
class QuickEntryForm(forms.ModelForm):
"""
Form for posting an entry quickly.
"""
class Meta:
model = Entry
exclude = ('comment_count',
'pingback_count',
'trackback_count')
class QuickEntry(View):
"""
View handling the quick post of a short Entry.
"""
@method_decorator(permission_required('zinnia.add_entry'))
def dispatch(self, *args, **kwargs):
"""
Decorate the view dispatcher with permission_required.
"""
return super(QuickEntry, self).dispatch(*args, **kwargs)
def get(self, request, *args, **kwargs):
"""
GET only do a redirection to the admin for adding and entry.
"""
return redirect('admin:zinnia_entry_add')
def post(self, request, *args, **kwargs):
"""
Handle the datas for posting a quick entry,
and redirect to the admin in case of error or
to the entry's page in case of success.
"""
data = {
'title': request.POST.get('title'),
'slug': slugify(request.POST.get('title')),
'status': DRAFT if 'save_draft' in request.POST else PUBLISHED,
'sites': [Site.objects.get_current().pk],
'authors': [request.user.pk],
'content_template': 'zinnia/_entry_detail.html',
'detail_template': 'entry_detail.html',
'creation_date': timezone.now(),
'last_update': timezone.now(),
'content': request.POST.get('content'),
'tags': request.POST.get('tags')}
form = QuickEntryForm(data)
if form.is_valid():
form.instance.content = self.htmlize(form.cleaned_data['content'])
entry = form.save()
return redirect(entry)
data = {'title': smart_str(request.POST.get('title', '')),
'content': smart_str(self.htmlize(
request.POST.get('content', ''))),
'tags': smart_str(request.POST.get('tags', '')),
'slug': slugify(request.POST.get('title', '')),
'authors': request.user.pk,
'sites': Site.objects.get_current().pk}
return redirect('%s?%s' % (reverse('admin:zinnia_entry_add'),
urlencode(data)))
def htmlize(self, content):
"""
Convert to HTML the content if the MARKUP_LANGUAGE
is set to HTML to optimize the rendering and avoid
ugly effect in WYMEditor.
"""
if MARKUP_LANGUAGE == 'html':
return linebreaks(content)
return content
| apache-2.0 |
w1ll1am23/home-assistant | tests/components/gree/test_init.py | 6 | 1322 | """Tests for the Gree Integration."""
from unittest.mock import patch
from homeassistant.components.gree.const import DOMAIN as GREE_DOMAIN
from homeassistant.config_entries import ENTRY_STATE_LOADED, ENTRY_STATE_NOT_LOADED
from homeassistant.setup import async_setup_component
from tests.common import MockConfigEntry
async def test_setup_simple(hass, discovery, device):
"""Test gree integration is setup."""
await async_setup_component(hass, GREE_DOMAIN, {})
await hass.async_block_till_done()
# No flows started
assert len(hass.config_entries.flow.async_progress()) == 0
async def test_unload_config_entry(hass, discovery, device):
"""Test that the async_unload_entry works."""
# As we have currently no configuration, we just to pass the domain here.
entry = MockConfigEntry(domain=GREE_DOMAIN)
entry.add_to_hass(hass)
with patch(
"homeassistant.components.gree.climate.async_setup_entry",
return_value=True,
) as climate_setup:
assert await async_setup_component(hass, GREE_DOMAIN, {})
await hass.async_block_till_done()
assert len(climate_setup.mock_calls) == 1
assert entry.state == ENTRY_STATE_LOADED
await hass.config_entries.async_unload(entry.entry_id)
assert entry.state == ENTRY_STATE_NOT_LOADED
| apache-2.0 |
flwh/KK_mt6589_iq451 | prebuilts/python/darwin-x86/2.7.5/lib/python2.7/plat-mac/lib-scriptpackages/SystemEvents/Text_Suite.py | 82 | 5759 | """Suite Text Suite: A set of basic classes for text processing.
Level 1, version 1
Generated from /System/Library/CoreServices/System Events.app
AETE/AEUT resource version 1/0, language 0, script 0
"""
import aetools
import MacOS
_code = '????'
class Text_Suite_Events:
pass
class attachment(aetools.ComponentItem):
"""attachment - Represents an inline text attachment. This class is used mainly for make commands. """
want = 'atts'
class _Prop__3c_Inheritance_3e_(aetools.NProperty):
"""<Inheritance> - All of the properties of the superclass. """
which = 'c@#^'
want = 'ctxt'
class _Prop_file_name(aetools.NProperty):
"""file name - The path to the file for the attachment """
which = 'atfn'
want = 'utxt'
# element 'catr' as ['indx', 'rele', 'rang', 'test']
# element 'cha ' as ['indx', 'rele', 'rang', 'test']
# element 'cpar' as ['indx', 'rele', 'rang', 'test']
# element 'cwor' as ['indx', 'rele', 'rang', 'test']
class attribute_run(aetools.ComponentItem):
"""attribute run - This subdivides the text into chunks that all have the same attributes. """
want = 'catr'
class _Prop_color(aetools.NProperty):
"""color - The color of the first character. """
which = 'colr'
want = 'colr'
class _Prop_font(aetools.NProperty):
"""font - The name of the font of the first character. """
which = 'font'
want = 'utxt'
class _Prop_size(aetools.NProperty):
"""size - The size in points of the first character. """
which = 'ptsz'
want = 'long'
# element 'catr' as ['indx', 'rele', 'rang', 'test']
# element 'cha ' as ['indx', 'rele', 'rang', 'test']
# element 'cpar' as ['indx', 'rele', 'rang', 'test']
# element 'cwor' as ['indx', 'rele', 'rang', 'test']
attribute_runs = attribute_run
class character(aetools.ComponentItem):
"""character - This subdivides the text into characters. """
want = 'cha '
# element 'catr' as ['indx', 'rele', 'rang', 'test']
# element 'cha ' as ['indx', 'rele', 'rang', 'test']
# element 'cpar' as ['indx', 'rele', 'rang', 'test']
# element 'cwor' as ['indx', 'rele', 'rang', 'test']
characters = character
class paragraph(aetools.ComponentItem):
"""paragraph - This subdivides the text into paragraphs. """
want = 'cpar'
# element 'catr' as ['indx', 'rele', 'rang', 'test']
# element 'cha ' as ['indx', 'rele', 'rang', 'test']
# element 'cpar' as ['indx', 'rele', 'rang', 'test']
# element 'cwor' as ['indx', 'rele', 'rang', 'test']
paragraphs = paragraph
class text(aetools.ComponentItem):
"""text - Rich (styled) text """
want = 'ctxt'
# element 'catr' as ['indx', 'rele', 'rang', 'test']
# element 'cha ' as ['indx', 'rele', 'rang', 'test']
# element 'cpar' as ['indx', 'rele', 'rang', 'test']
# element 'cwor' as ['indx', 'rele', 'rang', 'test']
class word(aetools.ComponentItem):
"""word - This subdivides the text into words. """
want = 'cwor'
# element 'catr' as ['indx', 'rele', 'rang', 'test']
# element 'cha ' as ['indx', 'rele', 'rang', 'test']
# element 'cpar' as ['indx', 'rele', 'rang', 'test']
# element 'cwor' as ['indx', 'rele', 'rang', 'test']
words = word
attachment._superclassnames = ['text']
attachment._privpropdict = {
'_3c_Inheritance_3e_' : _Prop__3c_Inheritance_3e_,
'file_name' : _Prop_file_name,
}
attachment._privelemdict = {
'attribute_run' : attribute_run,
'character' : character,
'paragraph' : paragraph,
'word' : word,
}
import Standard_Suite
attribute_run._superclassnames = ['item']
attribute_run._privpropdict = {
'_3c_Inheritance_3e_' : _Prop__3c_Inheritance_3e_,
'color' : _Prop_color,
'font' : _Prop_font,
'size' : _Prop_size,
}
attribute_run._privelemdict = {
'attribute_run' : attribute_run,
'character' : character,
'paragraph' : paragraph,
'word' : word,
}
character._superclassnames = ['item']
character._privpropdict = {
'_3c_Inheritance_3e_' : _Prop__3c_Inheritance_3e_,
'color' : _Prop_color,
'font' : _Prop_font,
'size' : _Prop_size,
}
character._privelemdict = {
'attribute_run' : attribute_run,
'character' : character,
'paragraph' : paragraph,
'word' : word,
}
paragraph._superclassnames = ['item']
paragraph._privpropdict = {
'_3c_Inheritance_3e_' : _Prop__3c_Inheritance_3e_,
'color' : _Prop_color,
'font' : _Prop_font,
'size' : _Prop_size,
}
paragraph._privelemdict = {
'attribute_run' : attribute_run,
'character' : character,
'paragraph' : paragraph,
'word' : word,
}
text._superclassnames = ['item']
text._privpropdict = {
'_3c_Inheritance_3e_' : _Prop__3c_Inheritance_3e_,
'color' : _Prop_color,
'font' : _Prop_font,
'size' : _Prop_size,
}
text._privelemdict = {
'attribute_run' : attribute_run,
'character' : character,
'paragraph' : paragraph,
'word' : word,
}
word._superclassnames = ['item']
word._privpropdict = {
'_3c_Inheritance_3e_' : _Prop__3c_Inheritance_3e_,
'color' : _Prop_color,
'font' : _Prop_font,
'size' : _Prop_size,
}
word._privelemdict = {
'attribute_run' : attribute_run,
'character' : character,
'paragraph' : paragraph,
'word' : word,
}
#
# Indices of types declared in this module
#
_classdeclarations = {
'atts' : attachment,
'catr' : attribute_run,
'cha ' : character,
'cpar' : paragraph,
'ctxt' : text,
'cwor' : word,
}
_propdeclarations = {
'atfn' : _Prop_file_name,
'c@#^' : _Prop__3c_Inheritance_3e_,
'colr' : _Prop_color,
'font' : _Prop_font,
'ptsz' : _Prop_size,
}
_compdeclarations = {
}
_enumdeclarations = {
}
| gpl-2.0 |
broferek/ansible | lib/ansible/modules/network/onyx/onyx_qos.py | 28 | 9337 | #!/usr/bin/python
#
# Copyright: Ansible Project
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = """
---
module: onyx_qos
version_added: "2.9"
author: "Anas Badaha (@anasb)"
short_description: Configures QoS
description:
- This module provides declarative management of Onyx QoS configuration
on Mellanox ONYX network devices.
notes:
- Tested on ONYX 3.6.8130
options:
interfaces:
description:
- list of interfaces name.
required: true
trust:
description:
- trust type.
choices: ['L2', 'L3', 'both']
default: L2
rewrite_pcp:
description:
- rewrite with type pcp.
choices: ['enabled', 'disabled']
default: disabled
rewrite_dscp:
description:
- rewrite with type dscp.
choices: ['enabled', 'disabled']
default: disabled
"""
EXAMPLES = """
- name: configure QoS
onyx_QoS:
interfaces:
- Mpo7
- Mpo7
trust: L3
rewrite_pcp: disabled
rewrite_dscp: enabled
- name: configure QoS
onyx_QoS:
interfaces:
- Eth1/1
- Eth1/2
trust: both
rewrite_pcp: disabled
rewrite_dscp: enabled
"""
RETURN = """
commands:
description: The list of configuration mode commands to send to the device.
returned: always
type: list
sample:
- interface ethernet 1/16 qos trust L3
- interface mlag-port-channel 7 qos trust L3
- interface port-channel 1 qos trust L3
- interface mlag-port-channel 7 qos trust L2
- interface mlag-port-channel 7 qos rewrite dscp
- interface ethernet 1/16 qos rewrite pcp
- interface ethernet 1/1 no qos rewrite pcp
"""
import re
from ansible.module_utils.six import iteritems
from ansible.module_utils.basic import AnsibleModule
from ansible.module_utils.network.onyx.onyx import show_cmd
from ansible.module_utils.network.onyx.onyx import BaseOnyxModule
class OnyxQosModule(BaseOnyxModule):
TRUST_CMD = "interface {0} {1} qos trust {2}"
NO_REWRITE_PCP_CMD = "interface {0} {1} no qos rewrite pcp"
NO_REWRITE_DSCP_CMD = "interface {0} {1} no qos rewrite dscp"
REWRITE_PCP_CMD = "interface {0} {1} qos rewrite pcp"
REWRITE_DSCP_CMD = "interface {0} {1} qos rewrite dscp"
REWRITE_PCP = "pcp"
REWRITE_DSCP = "dscp"
IF_ETH_REGEX = re.compile(r"^Eth(\d+\/\d+|Eth\d+\/\d+\d+)$")
IF_PO_REGEX = re.compile(r"^Po(\d+)$")
MLAG_NAME_REGEX = re.compile(r"^Mpo(\d+)$")
IF_TYPE_ETH = "ethernet"
PORT_CHANNEL = "port-channel"
MLAG_PORT_CHANNEL = "mlag-port-channel"
IF_TYPE_MAP = {
IF_TYPE_ETH: IF_ETH_REGEX,
PORT_CHANNEL: IF_PO_REGEX,
MLAG_PORT_CHANNEL: MLAG_NAME_REGEX
}
def init_module(self):
""" initialize module
"""
element_spec = dict(
interfaces=dict(type='list', required=True),
trust=dict(choices=['L2', 'L3', 'both'], default='L2'),
rewrite_pcp=dict(choices=['enabled', 'disabled'], default='disabled'),
rewrite_dscp=dict(choices=['enabled', 'disabled'], default='disabled')
)
argument_spec = dict()
argument_spec.update(element_spec)
self._module = AnsibleModule(
argument_spec=argument_spec,
supports_check_mode=True)
def get_required_config(self):
module_params = self._module.params
self._required_config = dict(module_params)
self.validate_param_values(self._required_config)
def _get_interface_type(self, if_name):
if_type = None
if_id = None
for interface_type, interface_regex in iteritems(self.IF_TYPE_MAP):
match = interface_regex.match(if_name)
if match:
if_type = interface_type
if_id = match.group(1)
break
return if_type, if_id
def _set_interface_qos_config(self, interface_qos_config, interface, if_type, if_id):
interface_qos_config = interface_qos_config[0].get(interface)
trust = interface_qos_config[0].get("Trust mode")
rewrite_dscp = interface_qos_config[0].get("DSCP rewrite")
rewrite_pcp = interface_qos_config[0].get("PCP,DEI rewrite")
self._current_config[interface] = dict(trust=trust, rewrite_dscp=rewrite_dscp,
rewrite_pcp=rewrite_pcp, if_type=if_type, if_id=if_id)
def _show_interface_qos(self, if_type, interface):
cmd = "show qos interface {0} {1}".format(if_type, interface)
return show_cmd(self._module, cmd, json_fmt=True, fail_on_error=False)
def load_current_config(self):
self._current_config = dict()
for interface in self._required_config.get("interfaces"):
if_type, if_id = self._get_interface_type(interface)
if not if_id:
self._module.fail_json(
msg='unsupported interface: {0}'.format(interface))
interface_qos_config = self._show_interface_qos(if_type, if_id)
if interface_qos_config is not None:
self._set_interface_qos_config(interface_qos_config, interface, if_type, if_id)
else:
self._module.fail_json(
msg='Interface {0} does not exist on switch'.format(interface))
def generate_commands(self):
trust = self._required_config.get("trust")
rewrite_pcp = self._required_config.get("rewrite_pcp")
rewrite_dscp = self._required_config.get("rewrite_dscp")
for interface in self._required_config.get("interfaces"):
ignored1, ignored2, current_trust, if_type, if_id = self._get_current_rewrite_config(interface)
self._add_interface_trust_cmds(if_type, if_id, interface, trust, current_trust)
self._add_interface_rewrite_cmds(if_type, if_id, interface,
rewrite_pcp, rewrite_dscp)
def _get_current_rewrite_config(self, interface):
current_interface_qos_config = self._current_config.get(interface)
current_rewrite_pcp = current_interface_qos_config.get('rewrite_pcp')
current_rewrite_dscp = current_interface_qos_config.get('rewrite_dscp')
if_type = current_interface_qos_config.get("if_type")
if_id = current_interface_qos_config.get("if_id")
current_trust = current_interface_qos_config.get('trust')
return current_rewrite_pcp, current_rewrite_dscp, current_trust, if_type, if_id
def _add_interface_trust_cmds(self, if_type, if_id, interface, trust, current_trust):
current_rewrite_pcp, current_rewrite_dscp, ignored1, ignored2, ignored3 = self._get_current_rewrite_config(
interface)
if trust == "L3" and trust != current_trust:
self._add_no_rewrite_cmd(if_type, if_id, interface, self.REWRITE_DSCP, current_rewrite_dscp)
self._commands.append(self.TRUST_CMD.format(if_type, if_id, trust))
elif trust == "L2" and trust != current_trust:
self._add_no_rewrite_cmd(if_type, if_id, interface, self.REWRITE_PCP, current_rewrite_pcp)
self._commands.append(self.TRUST_CMD.format(if_type, if_id, trust))
elif trust == "both" and trust != current_trust:
self._add_no_rewrite_cmd(if_type, if_id, interface, self.REWRITE_DSCP, current_rewrite_dscp)
self._add_no_rewrite_cmd(if_type, if_id, interface, self.REWRITE_PCP, current_rewrite_pcp)
self._commands.append(self.TRUST_CMD.format(if_type, if_id, trust))
def _add_interface_rewrite_cmds(self, if_type, if_id, interface, rewrite_pcp, rewrite_dscp):
current_rewrite_pcp, current_rewrite_dscp, ignored1, ignored2, ignored3 = self._get_current_rewrite_config(
interface)
if rewrite_pcp == "enabled" and rewrite_pcp != current_rewrite_pcp:
self._commands.append(self.REWRITE_PCP_CMD.format(if_type, if_id))
elif rewrite_pcp == "disabled" and rewrite_pcp != current_rewrite_pcp:
self._commands.append(self.NO_REWRITE_PCP_CMD.format(if_type, if_id))
if rewrite_dscp == "enabled" and rewrite_dscp != current_rewrite_dscp:
self._commands.append(self.REWRITE_DSCP_CMD.format(if_type, if_id))
elif rewrite_dscp == "disabled" and rewrite_dscp != current_rewrite_dscp:
self._commands.append(self.NO_REWRITE_DSCP_CMD.format(if_type, if_id))
def _add_no_rewrite_cmd(self, if_type, if_id, interface, rewrite_type, current_rewrite):
if rewrite_type == self.REWRITE_PCP and current_rewrite == "enabled":
self._commands.append(self.NO_REWRITE_PCP_CMD.format(if_type, if_id))
self._current_config[interface]["rewrite_pcp"] = "disabled"
elif rewrite_type == self.REWRITE_DSCP and current_rewrite == "enabled":
self._commands.append(self.NO_REWRITE_DSCP_CMD.format(if_type, if_id))
self._current_config[interface]["rewrite_dscp"] = "disabled"
def main():
""" main entry point for module execution
"""
OnyxQosModule.main()
if __name__ == '__main__':
main()
| gpl-3.0 |
fxfitz/ansible | test/units/module_utils/facts/system/test_lsb.py | 118 | 4485 | # unit tests for ansible system lsb fact collectors
# -*- coding: utf-8 -*-
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
#
# Make coding more python3-ish
from __future__ import (absolute_import, division)
__metaclass__ = type
from ansible.compat.tests.mock import Mock, patch
from .. base import BaseFactsTest
from ansible.module_utils.facts.system.lsb import LSBFactCollector
lsb_release_a_fedora_output = '''
LSB Version: :core-4.1-amd64:core-4.1-noarch:cxx-4.1-amd64:cxx-4.1-noarch:desktop-4.1-amd64:desktop-4.1-noarch:languages-4.1-amd64:languages-4.1-noarch:printing-4.1-amd64:printing-4.1-noarch
Distributor ID: Fedora
Description: Fedora release 25 (Twenty Five)
Release: 25
Codename: TwentyFive
''' # noqa
# FIXME: a
etc_lsb_release_ubuntu14 = '''DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=14.04
DISTRIB_CODENAME=trusty
DISTRIB_DESCRIPTION="Ubuntu 14.04.3 LTS"
'''
etc_lsb_release_no_decimal = '''DISTRIB_ID=AwesomeOS
DISTRIB_RELEASE=11
DISTRIB_CODENAME=stonehenge
DISTRIB_DESCRIPTION="AwesomeÖS 11"
'''
class TestLSBFacts(BaseFactsTest):
__test__ = True
gather_subset = ['!all', 'lsb']
valid_subsets = ['lsb']
fact_namespace = 'ansible_lsb'
collector_class = LSBFactCollector
def _mock_module(self):
mock_module = Mock()
mock_module.params = {'gather_subset': self.gather_subset,
'gather_timeout': 10,
'filter': '*'}
mock_module.get_bin_path = Mock(return_value='/usr/bin/lsb_release')
mock_module.run_command = Mock(return_value=(0, lsb_release_a_fedora_output, ''))
return mock_module
def test_lsb_release_bin(self):
module = self._mock_module()
fact_collector = self.collector_class()
facts_dict = fact_collector.collect(module=module)
self.assertIsInstance(facts_dict, dict)
self.assertEqual(facts_dict['lsb']['release'], '25')
self.assertEqual(facts_dict['lsb']['id'], 'Fedora')
self.assertEqual(facts_dict['lsb']['description'], 'Fedora release 25 (Twenty Five)')
self.assertEqual(facts_dict['lsb']['codename'], 'TwentyFive')
self.assertEqual(facts_dict['lsb']['major_release'], '25')
def test_etc_lsb_release(self):
module = self._mock_module()
module.get_bin_path = Mock(return_value=None)
with patch('ansible.module_utils.facts.system.lsb.os.path.exists',
return_value=True):
with patch('ansible.module_utils.facts.system.lsb.get_file_lines',
return_value=etc_lsb_release_ubuntu14.splitlines()):
fact_collector = self.collector_class()
facts_dict = fact_collector.collect(module=module)
self.assertIsInstance(facts_dict, dict)
self.assertEqual(facts_dict['lsb']['release'], '14.04')
self.assertEqual(facts_dict['lsb']['id'], 'Ubuntu')
self.assertEqual(facts_dict['lsb']['description'], '"Ubuntu 14.04.3 LTS"')
self.assertEqual(facts_dict['lsb']['codename'], 'trusty')
def test_etc_lsb_release_no_decimal_release(self):
module = self._mock_module()
module.get_bin_path = Mock(return_value=None)
with patch('ansible.module_utils.facts.system.lsb.os.path.exists',
return_value=True):
with patch('ansible.module_utils.facts.system.lsb.get_file_lines',
return_value=etc_lsb_release_no_decimal.splitlines()):
fact_collector = self.collector_class()
facts_dict = fact_collector.collect(module=module)
self.assertIsInstance(facts_dict, dict)
self.assertEqual(facts_dict['lsb']['release'], '11')
self.assertEqual(facts_dict['lsb']['id'], 'AwesomeOS')
self.assertEqual(facts_dict['lsb']['description'], '"AwesomeÖS 11"')
self.assertEqual(facts_dict['lsb']['codename'], 'stonehenge')
| gpl-3.0 |
viaembedded/vab820-kernel-bsp-old | scripts/analyze_suspend.py | 1537 | 120394 | #!/usr/bin/python
#
# Tool for analyzing suspend/resume timing
# Copyright (c) 2013, Intel Corporation.
#
# This program is free software; you can redistribute it and/or modify it
# under the terms and conditions of the GNU General Public License,
# version 2, as published by the Free Software Foundation.
#
# This program is distributed in the hope it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
# FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for
# more details.
#
# You should have received a copy of the GNU General Public License along with
# this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin St - Fifth Floor, Boston, MA 02110-1301 USA.
#
# Authors:
# Todd Brandt <todd.e.brandt@linux.intel.com>
#
# Description:
# This tool is designed to assist kernel and OS developers in optimizing
# their linux stack's suspend/resume time. Using a kernel image built
# with a few extra options enabled, the tool will execute a suspend and
# will capture dmesg and ftrace data until resume is complete. This data
# is transformed into a device timeline and a callgraph to give a quick
# and detailed view of which devices and callbacks are taking the most
# time in suspend/resume. The output is a single html file which can be
# viewed in firefox or chrome.
#
# The following kernel build options are required:
# CONFIG_PM_DEBUG=y
# CONFIG_PM_SLEEP_DEBUG=y
# CONFIG_FTRACE=y
# CONFIG_FUNCTION_TRACER=y
# CONFIG_FUNCTION_GRAPH_TRACER=y
#
# For kernel versions older than 3.15:
# The following additional kernel parameters are required:
# (e.g. in file /etc/default/grub)
# GRUB_CMDLINE_LINUX_DEFAULT="... initcall_debug log_buf_len=16M ..."
#
# ----------------- LIBRARIES --------------------
import sys
import time
import os
import string
import re
import platform
from datetime import datetime
import struct
# ----------------- CLASSES --------------------
# Class: SystemValues
# Description:
# A global, single-instance container used to
# store system values and test parameters
class SystemValues:
version = 3.0
verbose = False
testdir = '.'
tpath = '/sys/kernel/debug/tracing/'
fpdtpath = '/sys/firmware/acpi/tables/FPDT'
epath = '/sys/kernel/debug/tracing/events/power/'
traceevents = [
'suspend_resume',
'device_pm_callback_end',
'device_pm_callback_start'
]
modename = {
'freeze': 'Suspend-To-Idle (S0)',
'standby': 'Power-On Suspend (S1)',
'mem': 'Suspend-to-RAM (S3)',
'disk': 'Suspend-to-disk (S4)'
}
mempath = '/dev/mem'
powerfile = '/sys/power/state'
suspendmode = 'mem'
hostname = 'localhost'
prefix = 'test'
teststamp = ''
dmesgfile = ''
ftracefile = ''
htmlfile = ''
rtcwake = False
rtcwaketime = 10
rtcpath = ''
android = False
adb = 'adb'
devicefilter = []
stamp = 0
execcount = 1
x2delay = 0
usecallgraph = False
usetraceevents = False
usetraceeventsonly = False
notestrun = False
altdevname = dict()
postresumetime = 0
tracertypefmt = '# tracer: (?P<t>.*)'
firmwarefmt = '# fwsuspend (?P<s>[0-9]*) fwresume (?P<r>[0-9]*)$'
postresumefmt = '# post resume time (?P<t>[0-9]*)$'
stampfmt = '# suspend-(?P<m>[0-9]{2})(?P<d>[0-9]{2})(?P<y>[0-9]{2})-'+\
'(?P<H>[0-9]{2})(?P<M>[0-9]{2})(?P<S>[0-9]{2})'+\
' (?P<host>.*) (?P<mode>.*) (?P<kernel>.*)$'
def __init__(self):
self.hostname = platform.node()
if(self.hostname == ''):
self.hostname = 'localhost'
rtc = "rtc0"
if os.path.exists('/dev/rtc'):
rtc = os.readlink('/dev/rtc')
rtc = '/sys/class/rtc/'+rtc
if os.path.exists(rtc) and os.path.exists(rtc+'/date') and \
os.path.exists(rtc+'/time') and os.path.exists(rtc+'/wakealarm'):
self.rtcpath = rtc
def setOutputFile(self):
if((self.htmlfile == '') and (self.dmesgfile != '')):
m = re.match('(?P<name>.*)_dmesg\.txt$', self.dmesgfile)
if(m):
self.htmlfile = m.group('name')+'.html'
if((self.htmlfile == '') and (self.ftracefile != '')):
m = re.match('(?P<name>.*)_ftrace\.txt$', self.ftracefile)
if(m):
self.htmlfile = m.group('name')+'.html'
if(self.htmlfile == ''):
self.htmlfile = 'output.html'
def initTestOutput(self, subdir):
if(not self.android):
self.prefix = self.hostname
v = open('/proc/version', 'r').read().strip()
kver = string.split(v)[2]
else:
self.prefix = 'android'
v = os.popen(self.adb+' shell cat /proc/version').read().strip()
kver = string.split(v)[2]
testtime = datetime.now().strftime('suspend-%m%d%y-%H%M%S')
if(subdir != "."):
self.testdir = subdir+"/"+testtime
else:
self.testdir = testtime
self.teststamp = \
'# '+testtime+' '+self.prefix+' '+self.suspendmode+' '+kver
self.dmesgfile = \
self.testdir+'/'+self.prefix+'_'+self.suspendmode+'_dmesg.txt'
self.ftracefile = \
self.testdir+'/'+self.prefix+'_'+self.suspendmode+'_ftrace.txt'
self.htmlfile = \
self.testdir+'/'+self.prefix+'_'+self.suspendmode+'.html'
os.mkdir(self.testdir)
def setDeviceFilter(self, devnames):
self.devicefilter = string.split(devnames)
def rtcWakeAlarm(self):
os.system('echo 0 > '+self.rtcpath+'/wakealarm')
outD = open(self.rtcpath+'/date', 'r').read().strip()
outT = open(self.rtcpath+'/time', 'r').read().strip()
mD = re.match('^(?P<y>[0-9]*)-(?P<m>[0-9]*)-(?P<d>[0-9]*)', outD)
mT = re.match('^(?P<h>[0-9]*):(?P<m>[0-9]*):(?P<s>[0-9]*)', outT)
if(mD and mT):
# get the current time from hardware
utcoffset = int((datetime.now() - datetime.utcnow()).total_seconds())
dt = datetime(\
int(mD.group('y')), int(mD.group('m')), int(mD.group('d')),
int(mT.group('h')), int(mT.group('m')), int(mT.group('s')))
nowtime = int(dt.strftime('%s')) + utcoffset
else:
# if hardware time fails, use the software time
nowtime = int(datetime.now().strftime('%s'))
alarm = nowtime + self.rtcwaketime
os.system('echo %d > %s/wakealarm' % (alarm, self.rtcpath))
sysvals = SystemValues()
# Class: DeviceNode
# Description:
# A container used to create a device hierachy, with a single root node
# and a tree of child nodes. Used by Data.deviceTopology()
class DeviceNode:
name = ''
children = 0
depth = 0
def __init__(self, nodename, nodedepth):
self.name = nodename
self.children = []
self.depth = nodedepth
# Class: Data
# Description:
# The primary container for suspend/resume test data. There is one for
# each test run. The data is organized into a cronological hierarchy:
# Data.dmesg {
# root structure, started as dmesg & ftrace, but now only ftrace
# contents: times for suspend start/end, resume start/end, fwdata
# phases {
# 10 sequential, non-overlapping phases of S/R
# contents: times for phase start/end, order/color data for html
# devlist {
# device callback or action list for this phase
# device {
# a single device callback or generic action
# contents: start/stop times, pid/cpu/driver info
# parents/children, html id for timeline/callgraph
# optionally includes an ftrace callgraph
# optionally includes intradev trace events
# }
# }
# }
# }
#
class Data:
dmesg = {} # root data structure
phases = [] # ordered list of phases
start = 0.0 # test start
end = 0.0 # test end
tSuspended = 0.0 # low-level suspend start
tResumed = 0.0 # low-level resume start
tLow = 0.0 # time spent in low-level suspend (standby/freeze)
fwValid = False # is firmware data available
fwSuspend = 0 # time spent in firmware suspend
fwResume = 0 # time spent in firmware resume
dmesgtext = [] # dmesg text file in memory
testnumber = 0
idstr = ''
html_device_id = 0
stamp = 0
outfile = ''
def __init__(self, num):
idchar = 'abcdefghijklmnopqrstuvwxyz'
self.testnumber = num
self.idstr = idchar[num]
self.dmesgtext = []
self.phases = []
self.dmesg = { # fixed list of 10 phases
'suspend_prepare': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#CCFFCC', 'order': 0},
'suspend': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#88FF88', 'order': 1},
'suspend_late': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#00AA00', 'order': 2},
'suspend_noirq': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#008888', 'order': 3},
'suspend_machine': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#0000FF', 'order': 4},
'resume_machine': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#FF0000', 'order': 5},
'resume_noirq': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#FF9900', 'order': 6},
'resume_early': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#FFCC00', 'order': 7},
'resume': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#FFFF88', 'order': 8},
'resume_complete': {'list': dict(), 'start': -1.0, 'end': -1.0,
'row': 0, 'color': '#FFFFCC', 'order': 9}
}
self.phases = self.sortedPhases()
def getStart(self):
return self.dmesg[self.phases[0]]['start']
def setStart(self, time):
self.start = time
self.dmesg[self.phases[0]]['start'] = time
def getEnd(self):
return self.dmesg[self.phases[-1]]['end']
def setEnd(self, time):
self.end = time
self.dmesg[self.phases[-1]]['end'] = time
def isTraceEventOutsideDeviceCalls(self, pid, time):
for phase in self.phases:
list = self.dmesg[phase]['list']
for dev in list:
d = list[dev]
if(d['pid'] == pid and time >= d['start'] and
time <= d['end']):
return False
return True
def addIntraDevTraceEvent(self, action, name, pid, time):
if(action == 'mutex_lock_try'):
color = 'red'
elif(action == 'mutex_lock_pass'):
color = 'green'
elif(action == 'mutex_unlock'):
color = 'blue'
else:
# create separate colors based on the name
v1 = len(name)*10 % 256
v2 = string.count(name, 'e')*100 % 256
v3 = ord(name[0])*20 % 256
color = '#%06X' % ((v1*0x10000) + (v2*0x100) + v3)
for phase in self.phases:
list = self.dmesg[phase]['list']
for dev in list:
d = list[dev]
if(d['pid'] == pid and time >= d['start'] and
time <= d['end']):
e = TraceEvent(action, name, color, time)
if('traceevents' not in d):
d['traceevents'] = []
d['traceevents'].append(e)
return d
break
return 0
def capIntraDevTraceEvent(self, action, name, pid, time):
for phase in self.phases:
list = self.dmesg[phase]['list']
for dev in list:
d = list[dev]
if(d['pid'] == pid and time >= d['start'] and
time <= d['end']):
if('traceevents' not in d):
return
for e in d['traceevents']:
if(e.action == action and
e.name == name and not e.ready):
e.length = time - e.time
e.ready = True
break
return
def trimTimeVal(self, t, t0, dT, left):
if left:
if(t > t0):
if(t - dT < t0):
return t0
return t - dT
else:
return t
else:
if(t < t0 + dT):
if(t > t0):
return t0 + dT
return t + dT
else:
return t
def trimTime(self, t0, dT, left):
self.tSuspended = self.trimTimeVal(self.tSuspended, t0, dT, left)
self.tResumed = self.trimTimeVal(self.tResumed, t0, dT, left)
self.start = self.trimTimeVal(self.start, t0, dT, left)
self.end = self.trimTimeVal(self.end, t0, dT, left)
for phase in self.phases:
p = self.dmesg[phase]
p['start'] = self.trimTimeVal(p['start'], t0, dT, left)
p['end'] = self.trimTimeVal(p['end'], t0, dT, left)
list = p['list']
for name in list:
d = list[name]
d['start'] = self.trimTimeVal(d['start'], t0, dT, left)
d['end'] = self.trimTimeVal(d['end'], t0, dT, left)
if('ftrace' in d):
cg = d['ftrace']
cg.start = self.trimTimeVal(cg.start, t0, dT, left)
cg.end = self.trimTimeVal(cg.end, t0, dT, left)
for line in cg.list:
line.time = self.trimTimeVal(line.time, t0, dT, left)
if('traceevents' in d):
for e in d['traceevents']:
e.time = self.trimTimeVal(e.time, t0, dT, left)
def normalizeTime(self, tZero):
# first trim out any standby or freeze clock time
if(self.tSuspended != self.tResumed):
if(self.tResumed > tZero):
self.trimTime(self.tSuspended, \
self.tResumed-self.tSuspended, True)
else:
self.trimTime(self.tSuspended, \
self.tResumed-self.tSuspended, False)
# shift the timeline so that tZero is the new 0
self.tSuspended -= tZero
self.tResumed -= tZero
self.start -= tZero
self.end -= tZero
for phase in self.phases:
p = self.dmesg[phase]
p['start'] -= tZero
p['end'] -= tZero
list = p['list']
for name in list:
d = list[name]
d['start'] -= tZero
d['end'] -= tZero
if('ftrace' in d):
cg = d['ftrace']
cg.start -= tZero
cg.end -= tZero
for line in cg.list:
line.time -= tZero
if('traceevents' in d):
for e in d['traceevents']:
e.time -= tZero
def newPhaseWithSingleAction(self, phasename, devname, start, end, color):
for phase in self.phases:
self.dmesg[phase]['order'] += 1
self.html_device_id += 1
devid = '%s%d' % (self.idstr, self.html_device_id)
list = dict()
list[devname] = \
{'start': start, 'end': end, 'pid': 0, 'par': '',
'length': (end-start), 'row': 0, 'id': devid, 'drv': '' };
self.dmesg[phasename] = \
{'list': list, 'start': start, 'end': end,
'row': 0, 'color': color, 'order': 0}
self.phases = self.sortedPhases()
def newPhase(self, phasename, start, end, color, order):
if(order < 0):
order = len(self.phases)
for phase in self.phases[order:]:
self.dmesg[phase]['order'] += 1
if(order > 0):
p = self.phases[order-1]
self.dmesg[p]['end'] = start
if(order < len(self.phases)):
p = self.phases[order]
self.dmesg[p]['start'] = end
list = dict()
self.dmesg[phasename] = \
{'list': list, 'start': start, 'end': end,
'row': 0, 'color': color, 'order': order}
self.phases = self.sortedPhases()
def setPhase(self, phase, ktime, isbegin):
if(isbegin):
self.dmesg[phase]['start'] = ktime
else:
self.dmesg[phase]['end'] = ktime
def dmesgSortVal(self, phase):
return self.dmesg[phase]['order']
def sortedPhases(self):
return sorted(self.dmesg, key=self.dmesgSortVal)
def sortedDevices(self, phase):
list = self.dmesg[phase]['list']
slist = []
tmp = dict()
for devname in list:
dev = list[devname]
tmp[dev['start']] = devname
for t in sorted(tmp):
slist.append(tmp[t])
return slist
def fixupInitcalls(self, phase, end):
# if any calls never returned, clip them at system resume end
phaselist = self.dmesg[phase]['list']
for devname in phaselist:
dev = phaselist[devname]
if(dev['end'] < 0):
dev['end'] = end
vprint('%s (%s): callback didnt return' % (devname, phase))
def deviceFilter(self, devicefilter):
# remove all by the relatives of the filter devnames
filter = []
for phase in self.phases:
list = self.dmesg[phase]['list']
for name in devicefilter:
dev = name
while(dev in list):
if(dev not in filter):
filter.append(dev)
dev = list[dev]['par']
children = self.deviceDescendants(name, phase)
for dev in children:
if(dev not in filter):
filter.append(dev)
for phase in self.phases:
list = self.dmesg[phase]['list']
rmlist = []
for name in list:
pid = list[name]['pid']
if(name not in filter and pid >= 0):
rmlist.append(name)
for name in rmlist:
del list[name]
def fixupInitcallsThatDidntReturn(self):
# if any calls never returned, clip them at system resume end
for phase in self.phases:
self.fixupInitcalls(phase, self.getEnd())
def newActionGlobal(self, name, start, end):
# which phase is this device callback or action "in"
targetphase = "none"
overlap = 0.0
for phase in self.phases:
pstart = self.dmesg[phase]['start']
pend = self.dmesg[phase]['end']
o = max(0, min(end, pend) - max(start, pstart))
if(o > overlap):
targetphase = phase
overlap = o
if targetphase in self.phases:
self.newAction(targetphase, name, -1, '', start, end, '')
return True
return False
def newAction(self, phase, name, pid, parent, start, end, drv):
# new device callback for a specific phase
self.html_device_id += 1
devid = '%s%d' % (self.idstr, self.html_device_id)
list = self.dmesg[phase]['list']
length = -1.0
if(start >= 0 and end >= 0):
length = end - start
list[name] = {'start': start, 'end': end, 'pid': pid, 'par': parent,
'length': length, 'row': 0, 'id': devid, 'drv': drv }
def deviceIDs(self, devlist, phase):
idlist = []
list = self.dmesg[phase]['list']
for devname in list:
if devname in devlist:
idlist.append(list[devname]['id'])
return idlist
def deviceParentID(self, devname, phase):
pdev = ''
pdevid = ''
list = self.dmesg[phase]['list']
if devname in list:
pdev = list[devname]['par']
if pdev in list:
return list[pdev]['id']
return pdev
def deviceChildren(self, devname, phase):
devlist = []
list = self.dmesg[phase]['list']
for child in list:
if(list[child]['par'] == devname):
devlist.append(child)
return devlist
def deviceDescendants(self, devname, phase):
children = self.deviceChildren(devname, phase)
family = children
for child in children:
family += self.deviceDescendants(child, phase)
return family
def deviceChildrenIDs(self, devname, phase):
devlist = self.deviceChildren(devname, phase)
return self.deviceIDs(devlist, phase)
def printDetails(self):
vprint(' test start: %f' % self.start)
for phase in self.phases:
dc = len(self.dmesg[phase]['list'])
vprint(' %16s: %f - %f (%d devices)' % (phase, \
self.dmesg[phase]['start'], self.dmesg[phase]['end'], dc))
vprint(' test end: %f' % self.end)
def masterTopology(self, name, list, depth):
node = DeviceNode(name, depth)
for cname in list:
clist = self.deviceChildren(cname, 'resume')
cnode = self.masterTopology(cname, clist, depth+1)
node.children.append(cnode)
return node
def printTopology(self, node):
html = ''
if node.name:
info = ''
drv = ''
for phase in self.phases:
list = self.dmesg[phase]['list']
if node.name in list:
s = list[node.name]['start']
e = list[node.name]['end']
if list[node.name]['drv']:
drv = ' {'+list[node.name]['drv']+'}'
info += ('<li>%s: %.3fms</li>' % (phase, (e-s)*1000))
html += '<li><b>'+node.name+drv+'</b>'
if info:
html += '<ul>'+info+'</ul>'
html += '</li>'
if len(node.children) > 0:
html += '<ul>'
for cnode in node.children:
html += self.printTopology(cnode)
html += '</ul>'
return html
def rootDeviceList(self):
# list of devices graphed
real = []
for phase in self.dmesg:
list = self.dmesg[phase]['list']
for dev in list:
if list[dev]['pid'] >= 0 and dev not in real:
real.append(dev)
# list of top-most root devices
rootlist = []
for phase in self.dmesg:
list = self.dmesg[phase]['list']
for dev in list:
pdev = list[dev]['par']
if(re.match('[0-9]*-[0-9]*\.[0-9]*[\.0-9]*\:[\.0-9]*$', pdev)):
continue
if pdev and pdev not in real and pdev not in rootlist:
rootlist.append(pdev)
return rootlist
def deviceTopology(self):
rootlist = self.rootDeviceList()
master = self.masterTopology('', rootlist, 0)
return self.printTopology(master)
# Class: TraceEvent
# Description:
# A container for trace event data found in the ftrace file
class TraceEvent:
ready = False
name = ''
time = 0.0
color = '#FFFFFF'
length = 0.0
action = ''
def __init__(self, a, n, c, t):
self.action = a
self.name = n
self.color = c
self.time = t
# Class: FTraceLine
# Description:
# A container for a single line of ftrace data. There are six basic types:
# callgraph line:
# call: " dpm_run_callback() {"
# return: " }"
# leaf: " dpm_run_callback();"
# trace event:
# tracing_mark_write: SUSPEND START or RESUME COMPLETE
# suspend_resume: phase or custom exec block data
# device_pm_callback: device callback info
class FTraceLine:
time = 0.0
length = 0.0
fcall = False
freturn = False
fevent = False
depth = 0
name = ''
type = ''
def __init__(self, t, m, d):
self.time = float(t)
# is this a trace event
if(d == 'traceevent' or re.match('^ *\/\* *(?P<msg>.*) \*\/ *$', m)):
if(d == 'traceevent'):
# nop format trace event
msg = m
else:
# function_graph format trace event
em = re.match('^ *\/\* *(?P<msg>.*) \*\/ *$', m)
msg = em.group('msg')
emm = re.match('^(?P<call>.*?): (?P<msg>.*)', msg)
if(emm):
self.name = emm.group('msg')
self.type = emm.group('call')
else:
self.name = msg
self.fevent = True
return
# convert the duration to seconds
if(d):
self.length = float(d)/1000000
# the indentation determines the depth
match = re.match('^(?P<d> *)(?P<o>.*)$', m)
if(not match):
return
self.depth = self.getDepth(match.group('d'))
m = match.group('o')
# function return
if(m[0] == '}'):
self.freturn = True
if(len(m) > 1):
# includes comment with function name
match = re.match('^} *\/\* *(?P<n>.*) *\*\/$', m)
if(match):
self.name = match.group('n')
# function call
else:
self.fcall = True
# function call with children
if(m[-1] == '{'):
match = re.match('^(?P<n>.*) *\(.*', m)
if(match):
self.name = match.group('n')
# function call with no children (leaf)
elif(m[-1] == ';'):
self.freturn = True
match = re.match('^(?P<n>.*) *\(.*', m)
if(match):
self.name = match.group('n')
# something else (possibly a trace marker)
else:
self.name = m
def getDepth(self, str):
return len(str)/2
def debugPrint(self, dev):
if(self.freturn and self.fcall):
print('%s -- %f (%02d): %s(); (%.3f us)' % (dev, self.time, \
self.depth, self.name, self.length*1000000))
elif(self.freturn):
print('%s -- %f (%02d): %s} (%.3f us)' % (dev, self.time, \
self.depth, self.name, self.length*1000000))
else:
print('%s -- %f (%02d): %s() { (%.3f us)' % (dev, self.time, \
self.depth, self.name, self.length*1000000))
# Class: FTraceCallGraph
# Description:
# A container for the ftrace callgraph of a single recursive function.
# This can be a dpm_run_callback, dpm_prepare, or dpm_complete callgraph
# Each instance is tied to a single device in a single phase, and is
# comprised of an ordered list of FTraceLine objects
class FTraceCallGraph:
start = -1.0
end = -1.0
list = []
invalid = False
depth = 0
def __init__(self):
self.start = -1.0
self.end = -1.0
self.list = []
self.depth = 0
def setDepth(self, line):
if(line.fcall and not line.freturn):
line.depth = self.depth
self.depth += 1
elif(line.freturn and not line.fcall):
self.depth -= 1
line.depth = self.depth
else:
line.depth = self.depth
def addLine(self, line, match):
if(not self.invalid):
self.setDepth(line)
if(line.depth == 0 and line.freturn):
if(self.start < 0):
self.start = line.time
self.end = line.time
self.list.append(line)
return True
if(self.invalid):
return False
if(len(self.list) >= 1000000 or self.depth < 0):
if(len(self.list) > 0):
first = self.list[0]
self.list = []
self.list.append(first)
self.invalid = True
if(not match):
return False
id = 'task %s cpu %s' % (match.group('pid'), match.group('cpu'))
window = '(%f - %f)' % (self.start, line.time)
if(self.depth < 0):
print('Too much data for '+id+\
' (buffer overflow), ignoring this callback')
else:
print('Too much data for '+id+\
' '+window+', ignoring this callback')
return False
self.list.append(line)
if(self.start < 0):
self.start = line.time
return False
def slice(self, t0, tN):
minicg = FTraceCallGraph()
count = -1
firstdepth = 0
for l in self.list:
if(l.time < t0 or l.time > tN):
continue
if(count < 0):
if(not l.fcall or l.name == 'dev_driver_string'):
continue
firstdepth = l.depth
count = 0
l.depth -= firstdepth
minicg.addLine(l, 0)
if((count == 0 and l.freturn and l.fcall) or
(count > 0 and l.depth <= 0)):
break
count += 1
return minicg
def sanityCheck(self):
stack = dict()
cnt = 0
for l in self.list:
if(l.fcall and not l.freturn):
stack[l.depth] = l
cnt += 1
elif(l.freturn and not l.fcall):
if(l.depth not in stack):
return False
stack[l.depth].length = l.length
stack[l.depth] = 0
l.length = 0
cnt -= 1
if(cnt == 0):
return True
return False
def debugPrint(self, filename):
if(filename == 'stdout'):
print('[%f - %f]') % (self.start, self.end)
for l in self.list:
if(l.freturn and l.fcall):
print('%f (%02d): %s(); (%.3f us)' % (l.time, \
l.depth, l.name, l.length*1000000))
elif(l.freturn):
print('%f (%02d): %s} (%.3f us)' % (l.time, \
l.depth, l.name, l.length*1000000))
else:
print('%f (%02d): %s() { (%.3f us)' % (l.time, \
l.depth, l.name, l.length*1000000))
print(' ')
else:
fp = open(filename, 'w')
print(filename)
for l in self.list:
if(l.freturn and l.fcall):
fp.write('%f (%02d): %s(); (%.3f us)\n' % (l.time, \
l.depth, l.name, l.length*1000000))
elif(l.freturn):
fp.write('%f (%02d): %s} (%.3f us)\n' % (l.time, \
l.depth, l.name, l.length*1000000))
else:
fp.write('%f (%02d): %s() { (%.3f us)\n' % (l.time, \
l.depth, l.name, l.length*1000000))
fp.close()
# Class: Timeline
# Description:
# A container for a suspend/resume html timeline. In older versions
# of the script there were multiple timelines, but in the latest
# there is only one.
class Timeline:
html = {}
scaleH = 0.0 # height of the row as a percent of the timeline height
rowH = 0.0 # height of each row in percent of the timeline height
row_height_pixels = 30
maxrows = 0
height = 0
def __init__(self):
self.html = {
'timeline': '',
'legend': '',
'scale': ''
}
def setRows(self, rows):
self.maxrows = int(rows)
self.scaleH = 100.0/float(self.maxrows)
self.height = self.maxrows*self.row_height_pixels
r = float(self.maxrows - 1)
if(r < 1.0):
r = 1.0
self.rowH = (100.0 - self.scaleH)/r
# Class: TestRun
# Description:
# A container for a suspend/resume test run. This is necessary as
# there could be more than one, and they need to be separate.
class TestRun:
ftrace_line_fmt_fg = \
'^ *(?P<time>[0-9\.]*) *\| *(?P<cpu>[0-9]*)\)'+\
' *(?P<proc>.*)-(?P<pid>[0-9]*) *\|'+\
'[ +!]*(?P<dur>[0-9\.]*) .*\| (?P<msg>.*)'
ftrace_line_fmt_nop = \
' *(?P<proc>.*)-(?P<pid>[0-9]*) *\[(?P<cpu>[0-9]*)\] *'+\
'(?P<flags>.{4}) *(?P<time>[0-9\.]*): *'+\
'(?P<msg>.*)'
ftrace_line_fmt = ftrace_line_fmt_nop
cgformat = False
ftemp = dict()
ttemp = dict()
inthepipe = False
tracertype = ''
data = 0
def __init__(self, dataobj):
self.data = dataobj
self.ftemp = dict()
self.ttemp = dict()
def isReady(self):
if(tracertype == '' or not data):
return False
return True
def setTracerType(self, tracer):
self.tracertype = tracer
if(tracer == 'function_graph'):
self.cgformat = True
self.ftrace_line_fmt = self.ftrace_line_fmt_fg
elif(tracer == 'nop'):
self.ftrace_line_fmt = self.ftrace_line_fmt_nop
else:
doError('Invalid tracer format: [%s]' % tracer, False)
# ----------------- FUNCTIONS --------------------
# Function: vprint
# Description:
# verbose print (prints only with -verbose option)
# Arguments:
# msg: the debug/log message to print
def vprint(msg):
global sysvals
if(sysvals.verbose):
print(msg)
# Function: initFtrace
# Description:
# Configure ftrace to use trace events and/or a callgraph
def initFtrace():
global sysvals
tp = sysvals.tpath
cf = 'dpm_run_callback'
if(sysvals.usetraceeventsonly):
cf = '-e dpm_prepare -e dpm_complete -e dpm_run_callback'
if(sysvals.usecallgraph or sysvals.usetraceevents):
print('INITIALIZING FTRACE...')
# turn trace off
os.system('echo 0 > '+tp+'tracing_on')
# set the trace clock to global
os.system('echo global > '+tp+'trace_clock')
# set trace buffer to a huge value
os.system('echo nop > '+tp+'current_tracer')
os.system('echo 100000 > '+tp+'buffer_size_kb')
# initialize the callgraph trace, unless this is an x2 run
if(sysvals.usecallgraph and sysvals.execcount == 1):
# set trace type
os.system('echo function_graph > '+tp+'current_tracer')
os.system('echo "" > '+tp+'set_ftrace_filter')
# set trace format options
os.system('echo funcgraph-abstime > '+tp+'trace_options')
os.system('echo funcgraph-proc > '+tp+'trace_options')
# focus only on device suspend and resume
os.system('cat '+tp+'available_filter_functions | grep '+\
cf+' > '+tp+'set_graph_function')
if(sysvals.usetraceevents):
# turn trace events on
events = iter(sysvals.traceevents)
for e in events:
os.system('echo 1 > '+sysvals.epath+e+'/enable')
# clear the trace buffer
os.system('echo "" > '+tp+'trace')
# Function: initFtraceAndroid
# Description:
# Configure ftrace to capture trace events
def initFtraceAndroid():
global sysvals
tp = sysvals.tpath
if(sysvals.usetraceevents):
print('INITIALIZING FTRACE...')
# turn trace off
os.system(sysvals.adb+" shell 'echo 0 > "+tp+"tracing_on'")
# set the trace clock to global
os.system(sysvals.adb+" shell 'echo global > "+tp+"trace_clock'")
# set trace buffer to a huge value
os.system(sysvals.adb+" shell 'echo nop > "+tp+"current_tracer'")
os.system(sysvals.adb+" shell 'echo 10000 > "+tp+"buffer_size_kb'")
# turn trace events on
events = iter(sysvals.traceevents)
for e in events:
os.system(sysvals.adb+" shell 'echo 1 > "+\
sysvals.epath+e+"/enable'")
# clear the trace buffer
os.system(sysvals.adb+" shell 'echo \"\" > "+tp+"trace'")
# Function: verifyFtrace
# Description:
# Check that ftrace is working on the system
# Output:
# True or False
def verifyFtrace():
global sysvals
# files needed for any trace data
files = ['buffer_size_kb', 'current_tracer', 'trace', 'trace_clock',
'trace_marker', 'trace_options', 'tracing_on']
# files needed for callgraph trace data
tp = sysvals.tpath
if(sysvals.usecallgraph):
files += [
'available_filter_functions',
'set_ftrace_filter',
'set_graph_function'
]
for f in files:
if(sysvals.android):
out = os.popen(sysvals.adb+' shell ls '+tp+f).read().strip()
if(out != tp+f):
return False
else:
if(os.path.exists(tp+f) == False):
return False
return True
# Function: parseStamp
# Description:
# Pull in the stamp comment line from the data file(s),
# create the stamp, and add it to the global sysvals object
# Arguments:
# m: the valid re.match output for the stamp line
def parseStamp(m, data):
global sysvals
data.stamp = {'time': '', 'host': '', 'mode': ''}
dt = datetime(int(m.group('y'))+2000, int(m.group('m')),
int(m.group('d')), int(m.group('H')), int(m.group('M')),
int(m.group('S')))
data.stamp['time'] = dt.strftime('%B %d %Y, %I:%M:%S %p')
data.stamp['host'] = m.group('host')
data.stamp['mode'] = m.group('mode')
data.stamp['kernel'] = m.group('kernel')
sysvals.suspendmode = data.stamp['mode']
if not sysvals.stamp:
sysvals.stamp = data.stamp
# Function: diffStamp
# Description:
# compare the host, kernel, and mode fields in 3 stamps
# Arguments:
# stamp1: string array with mode, kernel, and host
# stamp2: string array with mode, kernel, and host
# Return:
# True if stamps differ, False if they're the same
def diffStamp(stamp1, stamp2):
if 'host' in stamp1 and 'host' in stamp2:
if stamp1['host'] != stamp2['host']:
return True
if 'kernel' in stamp1 and 'kernel' in stamp2:
if stamp1['kernel'] != stamp2['kernel']:
return True
if 'mode' in stamp1 and 'mode' in stamp2:
if stamp1['mode'] != stamp2['mode']:
return True
return False
# Function: doesTraceLogHaveTraceEvents
# Description:
# Quickly determine if the ftrace log has some or all of the trace events
# required for primary parsing. Set the usetraceevents and/or
# usetraceeventsonly flags in the global sysvals object
def doesTraceLogHaveTraceEvents():
global sysvals
sysvals.usetraceeventsonly = True
sysvals.usetraceevents = False
for e in sysvals.traceevents:
out = os.popen('cat '+sysvals.ftracefile+' | grep "'+e+': "').read()
if(not out):
sysvals.usetraceeventsonly = False
if(e == 'suspend_resume' and out):
sysvals.usetraceevents = True
# Function: appendIncompleteTraceLog
# Description:
# [deprecated for kernel 3.15 or newer]
# Legacy support of ftrace outputs that lack the device_pm_callback
# and/or suspend_resume trace events. The primary data should be
# taken from dmesg, and this ftrace is used only for callgraph data
# or custom actions in the timeline. The data is appended to the Data
# objects provided.
# Arguments:
# testruns: the array of Data objects obtained from parseKernelLog
def appendIncompleteTraceLog(testruns):
global sysvals
# create TestRun vessels for ftrace parsing
testcnt = len(testruns)
testidx = -1
testrun = []
for data in testruns:
testrun.append(TestRun(data))
# extract the callgraph and traceevent data
vprint('Analyzing the ftrace data...')
tf = open(sysvals.ftracefile, 'r')
for line in tf:
# remove any latent carriage returns
line = line.replace('\r\n', '')
# grab the time stamp first (signifies the start of the test run)
m = re.match(sysvals.stampfmt, line)
if(m):
testidx += 1
parseStamp(m, testrun[testidx].data)
continue
# pull out any firmware data
if(re.match(sysvals.firmwarefmt, line)):
continue
# if we havent found a test time stamp yet keep spinning til we do
if(testidx < 0):
continue
# determine the trace data type (required for further parsing)
m = re.match(sysvals.tracertypefmt, line)
if(m):
tracer = m.group('t')
testrun[testidx].setTracerType(tracer)
continue
# parse only valid lines, if this isnt one move on
m = re.match(testrun[testidx].ftrace_line_fmt, line)
if(not m):
continue
# gather the basic message data from the line
m_time = m.group('time')
m_pid = m.group('pid')
m_msg = m.group('msg')
if(testrun[testidx].cgformat):
m_param3 = m.group('dur')
else:
m_param3 = 'traceevent'
if(m_time and m_pid and m_msg):
t = FTraceLine(m_time, m_msg, m_param3)
pid = int(m_pid)
else:
continue
# the line should be a call, return, or event
if(not t.fcall and not t.freturn and not t.fevent):
continue
# only parse the ftrace data during suspend/resume
data = testrun[testidx].data
if(not testrun[testidx].inthepipe):
# look for the suspend start marker
if(t.fevent):
if(t.name == 'SUSPEND START'):
testrun[testidx].inthepipe = True
data.setStart(t.time)
continue
else:
# trace event processing
if(t.fevent):
if(t.name == 'RESUME COMPLETE'):
testrun[testidx].inthepipe = False
data.setEnd(t.time)
if(testidx == testcnt - 1):
break
continue
# general trace events have two types, begin and end
if(re.match('(?P<name>.*) begin$', t.name)):
isbegin = True
elif(re.match('(?P<name>.*) end$', t.name)):
isbegin = False
else:
continue
m = re.match('(?P<name>.*)\[(?P<val>[0-9]*)\] .*', t.name)
if(m):
val = m.group('val')
if val == '0':
name = m.group('name')
else:
name = m.group('name')+'['+val+']'
else:
m = re.match('(?P<name>.*) .*', t.name)
name = m.group('name')
# special processing for trace events
if re.match('dpm_prepare\[.*', name):
continue
elif re.match('machine_suspend.*', name):
continue
elif re.match('suspend_enter\[.*', name):
if(not isbegin):
data.dmesg['suspend_prepare']['end'] = t.time
continue
elif re.match('dpm_suspend\[.*', name):
if(not isbegin):
data.dmesg['suspend']['end'] = t.time
continue
elif re.match('dpm_suspend_late\[.*', name):
if(isbegin):
data.dmesg['suspend_late']['start'] = t.time
else:
data.dmesg['suspend_late']['end'] = t.time
continue
elif re.match('dpm_suspend_noirq\[.*', name):
if(isbegin):
data.dmesg['suspend_noirq']['start'] = t.time
else:
data.dmesg['suspend_noirq']['end'] = t.time
continue
elif re.match('dpm_resume_noirq\[.*', name):
if(isbegin):
data.dmesg['resume_machine']['end'] = t.time
data.dmesg['resume_noirq']['start'] = t.time
else:
data.dmesg['resume_noirq']['end'] = t.time
continue
elif re.match('dpm_resume_early\[.*', name):
if(isbegin):
data.dmesg['resume_early']['start'] = t.time
else:
data.dmesg['resume_early']['end'] = t.time
continue
elif re.match('dpm_resume\[.*', name):
if(isbegin):
data.dmesg['resume']['start'] = t.time
else:
data.dmesg['resume']['end'] = t.time
continue
elif re.match('dpm_complete\[.*', name):
if(isbegin):
data.dmesg['resume_complete']['start'] = t.time
else:
data.dmesg['resume_complete']['end'] = t.time
continue
# is this trace event outside of the devices calls
if(data.isTraceEventOutsideDeviceCalls(pid, t.time)):
# global events (outside device calls) are simply graphed
if(isbegin):
# store each trace event in ttemp
if(name not in testrun[testidx].ttemp):
testrun[testidx].ttemp[name] = []
testrun[testidx].ttemp[name].append(\
{'begin': t.time, 'end': t.time})
else:
# finish off matching trace event in ttemp
if(name in testrun[testidx].ttemp):
testrun[testidx].ttemp[name][-1]['end'] = t.time
else:
if(isbegin):
data.addIntraDevTraceEvent('', name, pid, t.time)
else:
data.capIntraDevTraceEvent('', name, pid, t.time)
# call/return processing
elif sysvals.usecallgraph:
# create a callgraph object for the data
if(pid not in testrun[testidx].ftemp):
testrun[testidx].ftemp[pid] = []
testrun[testidx].ftemp[pid].append(FTraceCallGraph())
# when the call is finished, see which device matches it
cg = testrun[testidx].ftemp[pid][-1]
if(cg.addLine(t, m)):
testrun[testidx].ftemp[pid].append(FTraceCallGraph())
tf.close()
for test in testrun:
# add the traceevent data to the device hierarchy
if(sysvals.usetraceevents):
for name in test.ttemp:
for event in test.ttemp[name]:
begin = event['begin']
end = event['end']
# if event starts before timeline start, expand timeline
if(begin < test.data.start):
test.data.setStart(begin)
# if event ends after timeline end, expand the timeline
if(end > test.data.end):
test.data.setEnd(end)
test.data.newActionGlobal(name, begin, end)
# add the callgraph data to the device hierarchy
for pid in test.ftemp:
for cg in test.ftemp[pid]:
if(not cg.sanityCheck()):
id = 'task %s cpu %s' % (pid, m.group('cpu'))
vprint('Sanity check failed for '+\
id+', ignoring this callback')
continue
callstart = cg.start
callend = cg.end
for p in test.data.phases:
if(test.data.dmesg[p]['start'] <= callstart and
callstart <= test.data.dmesg[p]['end']):
list = test.data.dmesg[p]['list']
for devname in list:
dev = list[devname]
if(pid == dev['pid'] and
callstart <= dev['start'] and
callend >= dev['end']):
dev['ftrace'] = cg
break
if(sysvals.verbose):
test.data.printDetails()
# add the time in between the tests as a new phase so we can see it
if(len(testruns) > 1):
t1e = testruns[0].getEnd()
t2s = testruns[-1].getStart()
testruns[-1].newPhaseWithSingleAction('user mode', \
'user mode', t1e, t2s, '#FF9966')
# Function: parseTraceLog
# Description:
# Analyze an ftrace log output file generated from this app during
# the execution phase. Used when the ftrace log is the primary data source
# and includes the suspend_resume and device_pm_callback trace events
# The ftrace filename is taken from sysvals
# Output:
# An array of Data objects
def parseTraceLog():
global sysvals
vprint('Analyzing the ftrace data...')
if(os.path.exists(sysvals.ftracefile) == False):
doError('%s doesnt exist' % sysvals.ftracefile, False)
# extract the callgraph and traceevent data
testruns = []
testdata = []
testrun = 0
data = 0
tf = open(sysvals.ftracefile, 'r')
phase = 'suspend_prepare'
for line in tf:
# remove any latent carriage returns
line = line.replace('\r\n', '')
# stamp line: each stamp means a new test run
m = re.match(sysvals.stampfmt, line)
if(m):
data = Data(len(testdata))
testdata.append(data)
testrun = TestRun(data)
testruns.append(testrun)
parseStamp(m, data)
continue
if(not data):
continue
# firmware line: pull out any firmware data
m = re.match(sysvals.firmwarefmt, line)
if(m):
data.fwSuspend = int(m.group('s'))
data.fwResume = int(m.group('r'))
if(data.fwSuspend > 0 or data.fwResume > 0):
data.fwValid = True
continue
# tracer type line: determine the trace data type
m = re.match(sysvals.tracertypefmt, line)
if(m):
tracer = m.group('t')
testrun.setTracerType(tracer)
continue
# post resume time line: did this test run include post-resume data
m = re.match(sysvals.postresumefmt, line)
if(m):
t = int(m.group('t'))
if(t > 0):
sysvals.postresumetime = t
continue
# ftrace line: parse only valid lines
m = re.match(testrun.ftrace_line_fmt, line)
if(not m):
continue
# gather the basic message data from the line
m_time = m.group('time')
m_pid = m.group('pid')
m_msg = m.group('msg')
if(testrun.cgformat):
m_param3 = m.group('dur')
else:
m_param3 = 'traceevent'
if(m_time and m_pid and m_msg):
t = FTraceLine(m_time, m_msg, m_param3)
pid = int(m_pid)
else:
continue
# the line should be a call, return, or event
if(not t.fcall and not t.freturn and not t.fevent):
continue
# only parse the ftrace data during suspend/resume
if(not testrun.inthepipe):
# look for the suspend start marker
if(t.fevent):
if(t.name == 'SUSPEND START'):
testrun.inthepipe = True
data.setStart(t.time)
continue
# trace event processing
if(t.fevent):
if(t.name == 'RESUME COMPLETE'):
if(sysvals.postresumetime > 0):
phase = 'post_resume'
data.newPhase(phase, t.time, t.time, '#FF9966', -1)
else:
testrun.inthepipe = False
data.setEnd(t.time)
continue
if(phase == 'post_resume'):
data.setEnd(t.time)
if(t.type == 'suspend_resume'):
# suspend_resume trace events have two types, begin and end
if(re.match('(?P<name>.*) begin$', t.name)):
isbegin = True
elif(re.match('(?P<name>.*) end$', t.name)):
isbegin = False
else:
continue
m = re.match('(?P<name>.*)\[(?P<val>[0-9]*)\] .*', t.name)
if(m):
val = m.group('val')
if val == '0':
name = m.group('name')
else:
name = m.group('name')+'['+val+']'
else:
m = re.match('(?P<name>.*) .*', t.name)
name = m.group('name')
# ignore these events
if(re.match('acpi_suspend\[.*', t.name) or
re.match('suspend_enter\[.*', name)):
continue
# -- phase changes --
# suspend_prepare start
if(re.match('dpm_prepare\[.*', t.name)):
phase = 'suspend_prepare'
if(not isbegin):
data.dmesg[phase]['end'] = t.time
continue
# suspend start
elif(re.match('dpm_suspend\[.*', t.name)):
phase = 'suspend'
data.setPhase(phase, t.time, isbegin)
continue
# suspend_late start
elif(re.match('dpm_suspend_late\[.*', t.name)):
phase = 'suspend_late'
data.setPhase(phase, t.time, isbegin)
continue
# suspend_noirq start
elif(re.match('dpm_suspend_noirq\[.*', t.name)):
phase = 'suspend_noirq'
data.setPhase(phase, t.time, isbegin)
if(not isbegin):
phase = 'suspend_machine'
data.dmesg[phase]['start'] = t.time
continue
# suspend_machine/resume_machine
elif(re.match('machine_suspend\[.*', t.name)):
if(isbegin):
phase = 'suspend_machine'
data.dmesg[phase]['end'] = t.time
data.tSuspended = t.time
else:
if(sysvals.suspendmode in ['mem', 'disk']):
data.dmesg['suspend_machine']['end'] = t.time
data.tSuspended = t.time
phase = 'resume_machine'
data.dmesg[phase]['start'] = t.time
data.tResumed = t.time
data.tLow = data.tResumed - data.tSuspended
continue
# resume_noirq start
elif(re.match('dpm_resume_noirq\[.*', t.name)):
phase = 'resume_noirq'
data.setPhase(phase, t.time, isbegin)
if(isbegin):
data.dmesg['resume_machine']['end'] = t.time
continue
# resume_early start
elif(re.match('dpm_resume_early\[.*', t.name)):
phase = 'resume_early'
data.setPhase(phase, t.time, isbegin)
continue
# resume start
elif(re.match('dpm_resume\[.*', t.name)):
phase = 'resume'
data.setPhase(phase, t.time, isbegin)
continue
# resume complete start
elif(re.match('dpm_complete\[.*', t.name)):
phase = 'resume_complete'
if(isbegin):
data.dmesg[phase]['start'] = t.time
continue
# is this trace event outside of the devices calls
if(data.isTraceEventOutsideDeviceCalls(pid, t.time)):
# global events (outside device calls) are simply graphed
if(name not in testrun.ttemp):
testrun.ttemp[name] = []
if(isbegin):
# create a new list entry
testrun.ttemp[name].append(\
{'begin': t.time, 'end': t.time})
else:
if(len(testrun.ttemp[name]) > 0):
# if an antry exists, assume this is its end
testrun.ttemp[name][-1]['end'] = t.time
elif(phase == 'post_resume'):
# post resume events can just have ends
testrun.ttemp[name].append({
'begin': data.dmesg[phase]['start'],
'end': t.time})
else:
if(isbegin):
data.addIntraDevTraceEvent('', name, pid, t.time)
else:
data.capIntraDevTraceEvent('', name, pid, t.time)
# device callback start
elif(t.type == 'device_pm_callback_start'):
m = re.match('(?P<drv>.*) (?P<d>.*), parent: *(?P<p>.*), .*',\
t.name);
if(not m):
continue
drv = m.group('drv')
n = m.group('d')
p = m.group('p')
if(n and p):
data.newAction(phase, n, pid, p, t.time, -1, drv)
# device callback finish
elif(t.type == 'device_pm_callback_end'):
m = re.match('(?P<drv>.*) (?P<d>.*), err.*', t.name);
if(not m):
continue
n = m.group('d')
list = data.dmesg[phase]['list']
if(n in list):
dev = list[n]
dev['length'] = t.time - dev['start']
dev['end'] = t.time
# callgraph processing
elif sysvals.usecallgraph:
# this shouldn't happen, but JIC, ignore callgraph data post-res
if(phase == 'post_resume'):
continue
# create a callgraph object for the data
if(pid not in testrun.ftemp):
testrun.ftemp[pid] = []
testrun.ftemp[pid].append(FTraceCallGraph())
# when the call is finished, see which device matches it
cg = testrun.ftemp[pid][-1]
if(cg.addLine(t, m)):
testrun.ftemp[pid].append(FTraceCallGraph())
tf.close()
for test in testruns:
# add the traceevent data to the device hierarchy
if(sysvals.usetraceevents):
for name in test.ttemp:
for event in test.ttemp[name]:
begin = event['begin']
end = event['end']
# if event starts before timeline start, expand timeline
if(begin < test.data.start):
test.data.setStart(begin)
# if event ends after timeline end, expand the timeline
if(end > test.data.end):
test.data.setEnd(end)
test.data.newActionGlobal(name, begin, end)
# add the callgraph data to the device hierarchy
borderphase = {
'dpm_prepare': 'suspend_prepare',
'dpm_complete': 'resume_complete'
}
for pid in test.ftemp:
for cg in test.ftemp[pid]:
if len(cg.list) < 2:
continue
if(not cg.sanityCheck()):
id = 'task %s cpu %s' % (pid, m.group('cpu'))
vprint('Sanity check failed for '+\
id+', ignoring this callback')
continue
callstart = cg.start
callend = cg.end
if(cg.list[0].name in borderphase):
p = borderphase[cg.list[0].name]
list = test.data.dmesg[p]['list']
for devname in list:
dev = list[devname]
if(pid == dev['pid'] and
callstart <= dev['start'] and
callend >= dev['end']):
dev['ftrace'] = cg.slice(dev['start'], dev['end'])
continue
if(cg.list[0].name != 'dpm_run_callback'):
continue
for p in test.data.phases:
if(test.data.dmesg[p]['start'] <= callstart and
callstart <= test.data.dmesg[p]['end']):
list = test.data.dmesg[p]['list']
for devname in list:
dev = list[devname]
if(pid == dev['pid'] and
callstart <= dev['start'] and
callend >= dev['end']):
dev['ftrace'] = cg
break
# fill in any missing phases
for data in testdata:
lp = data.phases[0]
for p in data.phases:
if(data.dmesg[p]['start'] < 0 and data.dmesg[p]['end'] < 0):
print('WARNING: phase "%s" is missing!' % p)
if(data.dmesg[p]['start'] < 0):
data.dmesg[p]['start'] = data.dmesg[lp]['end']
if(p == 'resume_machine'):
data.tSuspended = data.dmesg[lp]['end']
data.tResumed = data.dmesg[lp]['end']
data.tLow = 0
if(data.dmesg[p]['end'] < 0):
data.dmesg[p]['end'] = data.dmesg[p]['start']
lp = p
if(len(sysvals.devicefilter) > 0):
data.deviceFilter(sysvals.devicefilter)
data.fixupInitcallsThatDidntReturn()
if(sysvals.verbose):
data.printDetails()
# add the time in between the tests as a new phase so we can see it
if(len(testdata) > 1):
t1e = testdata[0].getEnd()
t2s = testdata[-1].getStart()
testdata[-1].newPhaseWithSingleAction('user mode', \
'user mode', t1e, t2s, '#FF9966')
return testdata
# Function: loadKernelLog
# Description:
# [deprecated for kernel 3.15.0 or newer]
# load the dmesg file into memory and fix up any ordering issues
# The dmesg filename is taken from sysvals
# Output:
# An array of empty Data objects with only their dmesgtext attributes set
def loadKernelLog():
global sysvals
vprint('Analyzing the dmesg data...')
if(os.path.exists(sysvals.dmesgfile) == False):
doError('%s doesnt exist' % sysvals.dmesgfile, False)
# there can be multiple test runs in a single file delineated by stamps
testruns = []
data = 0
lf = open(sysvals.dmesgfile, 'r')
for line in lf:
line = line.replace('\r\n', '')
idx = line.find('[')
if idx > 1:
line = line[idx:]
m = re.match(sysvals.stampfmt, line)
if(m):
if(data):
testruns.append(data)
data = Data(len(testruns))
parseStamp(m, data)
continue
if(not data):
continue
m = re.match(sysvals.firmwarefmt, line)
if(m):
data.fwSuspend = int(m.group('s'))
data.fwResume = int(m.group('r'))
if(data.fwSuspend > 0 or data.fwResume > 0):
data.fwValid = True
continue
m = re.match('[ \t]*(\[ *)(?P<ktime>[0-9\.]*)(\]) (?P<msg>.*)', line)
if(m):
data.dmesgtext.append(line)
if(re.match('ACPI: resume from mwait', m.group('msg'))):
print('NOTE: This suspend appears to be freeze rather than'+\
' %s, it will be treated as such' % sysvals.suspendmode)
sysvals.suspendmode = 'freeze'
else:
vprint('ignoring dmesg line: %s' % line.replace('\n', ''))
testruns.append(data)
lf.close()
if(not data):
print('ERROR: analyze_suspend header missing from dmesg log')
sys.exit()
# fix lines with same timestamp/function with the call and return swapped
for data in testruns:
last = ''
for line in data.dmesgtext:
mc = re.match('.*(\[ *)(?P<t>[0-9\.]*)(\]) calling '+\
'(?P<f>.*)\+ @ .*, parent: .*', line)
mr = re.match('.*(\[ *)(?P<t>[0-9\.]*)(\]) call '+\
'(?P<f>.*)\+ returned .* after (?P<dt>.*) usecs', last)
if(mc and mr and (mc.group('t') == mr.group('t')) and
(mc.group('f') == mr.group('f'))):
i = data.dmesgtext.index(last)
j = data.dmesgtext.index(line)
data.dmesgtext[i] = line
data.dmesgtext[j] = last
last = line
return testruns
# Function: parseKernelLog
# Description:
# [deprecated for kernel 3.15.0 or newer]
# Analyse a dmesg log output file generated from this app during
# the execution phase. Create a set of device structures in memory
# for subsequent formatting in the html output file
# This call is only for legacy support on kernels where the ftrace
# data lacks the suspend_resume or device_pm_callbacks trace events.
# Arguments:
# data: an empty Data object (with dmesgtext) obtained from loadKernelLog
# Output:
# The filled Data object
def parseKernelLog(data):
global sysvals
phase = 'suspend_runtime'
if(data.fwValid):
vprint('Firmware Suspend = %u ns, Firmware Resume = %u ns' % \
(data.fwSuspend, data.fwResume))
# dmesg phase match table
dm = {
'suspend_prepare': 'PM: Syncing filesystems.*',
'suspend': 'PM: Entering [a-z]* sleep.*',
'suspend_late': 'PM: suspend of devices complete after.*',
'suspend_noirq': 'PM: late suspend of devices complete after.*',
'suspend_machine': 'PM: noirq suspend of devices complete after.*',
'resume_machine': 'ACPI: Low-level resume complete.*',
'resume_noirq': 'ACPI: Waking up from system sleep state.*',
'resume_early': 'PM: noirq resume of devices complete after.*',
'resume': 'PM: early resume of devices complete after.*',
'resume_complete': 'PM: resume of devices complete after.*',
'post_resume': '.*Restarting tasks \.\.\..*',
}
if(sysvals.suspendmode == 'standby'):
dm['resume_machine'] = 'PM: Restoring platform NVS memory'
elif(sysvals.suspendmode == 'disk'):
dm['suspend_late'] = 'PM: freeze of devices complete after.*'
dm['suspend_noirq'] = 'PM: late freeze of devices complete after.*'
dm['suspend_machine'] = 'PM: noirq freeze of devices complete after.*'
dm['resume_machine'] = 'PM: Restoring platform NVS memory'
dm['resume_early'] = 'PM: noirq restore of devices complete after.*'
dm['resume'] = 'PM: early restore of devices complete after.*'
dm['resume_complete'] = 'PM: restore of devices complete after.*'
elif(sysvals.suspendmode == 'freeze'):
dm['resume_machine'] = 'ACPI: resume from mwait'
# action table (expected events that occur and show up in dmesg)
at = {
'sync_filesystems': {
'smsg': 'PM: Syncing filesystems.*',
'emsg': 'PM: Preparing system for mem sleep.*' },
'freeze_user_processes': {
'smsg': 'Freezing user space processes .*',
'emsg': 'Freezing remaining freezable tasks.*' },
'freeze_tasks': {
'smsg': 'Freezing remaining freezable tasks.*',
'emsg': 'PM: Entering (?P<mode>[a-z,A-Z]*) sleep.*' },
'ACPI prepare': {
'smsg': 'ACPI: Preparing to enter system sleep state.*',
'emsg': 'PM: Saving platform NVS memory.*' },
'PM vns': {
'smsg': 'PM: Saving platform NVS memory.*',
'emsg': 'Disabling non-boot CPUs .*' },
}
t0 = -1.0
cpu_start = -1.0
prevktime = -1.0
actions = dict()
for line in data.dmesgtext:
# -- preprocessing --
# parse each dmesg line into the time and message
m = re.match('[ \t]*(\[ *)(?P<ktime>[0-9\.]*)(\]) (?P<msg>.*)', line)
if(m):
val = m.group('ktime')
try:
ktime = float(val)
except:
doWarning('INVALID DMESG LINE: '+\
line.replace('\n', ''), 'dmesg')
continue
msg = m.group('msg')
# initialize data start to first line time
if t0 < 0:
data.setStart(ktime)
t0 = ktime
else:
continue
# hack for determining resume_machine end for freeze
if(not sysvals.usetraceevents and sysvals.suspendmode == 'freeze' \
and phase == 'resume_machine' and \
re.match('calling (?P<f>.*)\+ @ .*, parent: .*', msg)):
data.dmesg['resume_machine']['end'] = ktime
phase = 'resume_noirq'
data.dmesg[phase]['start'] = ktime
# -- phase changes --
# suspend start
if(re.match(dm['suspend_prepare'], msg)):
phase = 'suspend_prepare'
data.dmesg[phase]['start'] = ktime
data.setStart(ktime)
# suspend start
elif(re.match(dm['suspend'], msg)):
data.dmesg['suspend_prepare']['end'] = ktime
phase = 'suspend'
data.dmesg[phase]['start'] = ktime
# suspend_late start
elif(re.match(dm['suspend_late'], msg)):
data.dmesg['suspend']['end'] = ktime
phase = 'suspend_late'
data.dmesg[phase]['start'] = ktime
# suspend_noirq start
elif(re.match(dm['suspend_noirq'], msg)):
data.dmesg['suspend_late']['end'] = ktime
phase = 'suspend_noirq'
data.dmesg[phase]['start'] = ktime
# suspend_machine start
elif(re.match(dm['suspend_machine'], msg)):
data.dmesg['suspend_noirq']['end'] = ktime
phase = 'suspend_machine'
data.dmesg[phase]['start'] = ktime
# resume_machine start
elif(re.match(dm['resume_machine'], msg)):
if(sysvals.suspendmode in ['freeze', 'standby']):
data.tSuspended = prevktime
data.dmesg['suspend_machine']['end'] = prevktime
else:
data.tSuspended = ktime
data.dmesg['suspend_machine']['end'] = ktime
phase = 'resume_machine'
data.tResumed = ktime
data.tLow = data.tResumed - data.tSuspended
data.dmesg[phase]['start'] = ktime
# resume_noirq start
elif(re.match(dm['resume_noirq'], msg)):
data.dmesg['resume_machine']['end'] = ktime
phase = 'resume_noirq'
data.dmesg[phase]['start'] = ktime
# resume_early start
elif(re.match(dm['resume_early'], msg)):
data.dmesg['resume_noirq']['end'] = ktime
phase = 'resume_early'
data.dmesg[phase]['start'] = ktime
# resume start
elif(re.match(dm['resume'], msg)):
data.dmesg['resume_early']['end'] = ktime
phase = 'resume'
data.dmesg[phase]['start'] = ktime
# resume complete start
elif(re.match(dm['resume_complete'], msg)):
data.dmesg['resume']['end'] = ktime
phase = 'resume_complete'
data.dmesg[phase]['start'] = ktime
# post resume start
elif(re.match(dm['post_resume'], msg)):
data.dmesg['resume_complete']['end'] = ktime
data.setEnd(ktime)
phase = 'post_resume'
break
# -- device callbacks --
if(phase in data.phases):
# device init call
if(re.match('calling (?P<f>.*)\+ @ .*, parent: .*', msg)):
sm = re.match('calling (?P<f>.*)\+ @ '+\
'(?P<n>.*), parent: (?P<p>.*)', msg);
f = sm.group('f')
n = sm.group('n')
p = sm.group('p')
if(f and n and p):
data.newAction(phase, f, int(n), p, ktime, -1, '')
# device init return
elif(re.match('call (?P<f>.*)\+ returned .* after '+\
'(?P<t>.*) usecs', msg)):
sm = re.match('call (?P<f>.*)\+ returned .* after '+\
'(?P<t>.*) usecs(?P<a>.*)', msg);
f = sm.group('f')
t = sm.group('t')
list = data.dmesg[phase]['list']
if(f in list):
dev = list[f]
dev['length'] = int(t)
dev['end'] = ktime
# -- non-devicecallback actions --
# if trace events are not available, these are better than nothing
if(not sysvals.usetraceevents):
# look for known actions
for a in at:
if(re.match(at[a]['smsg'], msg)):
if(a not in actions):
actions[a] = []
actions[a].append({'begin': ktime, 'end': ktime})
if(re.match(at[a]['emsg'], msg)):
actions[a][-1]['end'] = ktime
# now look for CPU on/off events
if(re.match('Disabling non-boot CPUs .*', msg)):
# start of first cpu suspend
cpu_start = ktime
elif(re.match('Enabling non-boot CPUs .*', msg)):
# start of first cpu resume
cpu_start = ktime
elif(re.match('smpboot: CPU (?P<cpu>[0-9]*) is now offline', msg)):
# end of a cpu suspend, start of the next
m = re.match('smpboot: CPU (?P<cpu>[0-9]*) is now offline', msg)
cpu = 'CPU'+m.group('cpu')
if(cpu not in actions):
actions[cpu] = []
actions[cpu].append({'begin': cpu_start, 'end': ktime})
cpu_start = ktime
elif(re.match('CPU(?P<cpu>[0-9]*) is up', msg)):
# end of a cpu resume, start of the next
m = re.match('CPU(?P<cpu>[0-9]*) is up', msg)
cpu = 'CPU'+m.group('cpu')
if(cpu not in actions):
actions[cpu] = []
actions[cpu].append({'begin': cpu_start, 'end': ktime})
cpu_start = ktime
prevktime = ktime
# fill in any missing phases
lp = data.phases[0]
for p in data.phases:
if(data.dmesg[p]['start'] < 0 and data.dmesg[p]['end'] < 0):
print('WARNING: phase "%s" is missing, something went wrong!' % p)
print(' In %s, this dmesg line denotes the start of %s:' % \
(sysvals.suspendmode, p))
print(' "%s"' % dm[p])
if(data.dmesg[p]['start'] < 0):
data.dmesg[p]['start'] = data.dmesg[lp]['end']
if(p == 'resume_machine'):
data.tSuspended = data.dmesg[lp]['end']
data.tResumed = data.dmesg[lp]['end']
data.tLow = 0
if(data.dmesg[p]['end'] < 0):
data.dmesg[p]['end'] = data.dmesg[p]['start']
lp = p
# fill in any actions we've found
for name in actions:
for event in actions[name]:
begin = event['begin']
end = event['end']
# if event starts before timeline start, expand timeline
if(begin < data.start):
data.setStart(begin)
# if event ends after timeline end, expand the timeline
if(end > data.end):
data.setEnd(end)
data.newActionGlobal(name, begin, end)
if(sysvals.verbose):
data.printDetails()
if(len(sysvals.devicefilter) > 0):
data.deviceFilter(sysvals.devicefilter)
data.fixupInitcallsThatDidntReturn()
return True
# Function: setTimelineRows
# Description:
# Organize the timeline entries into the smallest
# number of rows possible, with no entry overlapping
# Arguments:
# list: the list of devices/actions for a single phase
# sortedkeys: cronologically sorted key list to use
# Output:
# The total number of rows needed to display this phase of the timeline
def setTimelineRows(list, sortedkeys):
# clear all rows and set them to undefined
remaining = len(list)
rowdata = dict()
row = 0
for item in list:
list[item]['row'] = -1
# try to pack each row with as many ranges as possible
while(remaining > 0):
if(row not in rowdata):
rowdata[row] = []
for item in sortedkeys:
if(list[item]['row'] < 0):
s = list[item]['start']
e = list[item]['end']
valid = True
for ritem in rowdata[row]:
rs = ritem['start']
re = ritem['end']
if(not (((s <= rs) and (e <= rs)) or
((s >= re) and (e >= re)))):
valid = False
break
if(valid):
rowdata[row].append(list[item])
list[item]['row'] = row
remaining -= 1
row += 1
return row
# Function: createTimeScale
# Description:
# Create the timescale header for the html timeline
# Arguments:
# t0: start time (suspend begin)
# tMax: end time (resume end)
# tSuspend: time when suspend occurs, i.e. the zero time
# Output:
# The html code needed to display the time scale
def createTimeScale(t0, tMax, tSuspended):
timescale = '<div class="t" style="right:{0}%">{1}</div>\n'
output = '<div id="timescale">\n'
# set scale for timeline
tTotal = tMax - t0
tS = 0.1
if(tTotal <= 0):
return output
if(tTotal > 4):
tS = 1
if(tSuspended < 0):
for i in range(int(tTotal/tS)+1):
pos = '%0.3f' % (100 - ((float(i)*tS*100)/tTotal))
if(i > 0):
val = '%0.fms' % (float(i)*tS*1000)
else:
val = ''
output += timescale.format(pos, val)
else:
tSuspend = tSuspended - t0
divTotal = int(tTotal/tS) + 1
divSuspend = int(tSuspend/tS)
s0 = (tSuspend - tS*divSuspend)*100/tTotal
for i in range(divTotal):
pos = '%0.3f' % (100 - ((float(i)*tS*100)/tTotal) - s0)
if((i == 0) and (s0 < 3)):
val = ''
elif(i == divSuspend):
val = 'S/R'
else:
val = '%0.fms' % (float(i-divSuspend)*tS*1000)
output += timescale.format(pos, val)
output += '</div>\n'
return output
# Function: createHTMLSummarySimple
# Description:
# Create summary html file for a series of tests
# Arguments:
# testruns: array of Data objects from parseTraceLog
def createHTMLSummarySimple(testruns, htmlfile):
global sysvals
# print out the basic summary of all the tests
hf = open(htmlfile, 'w')
# write the html header first (html head, css code, up to body start)
html = '<!DOCTYPE html>\n<html>\n<head>\n\
<meta http-equiv="content-type" content="text/html; charset=UTF-8">\n\
<title>AnalyzeSuspend Summary</title>\n\
<style type=\'text/css\'>\n\
body {overflow-y: scroll;}\n\
.stamp {width: 100%;text-align:center;background-color:#495E09;line-height:30px;color:white;font: 25px Arial;}\n\
table {width:100%;border-collapse: collapse;}\n\
.summary {font: 22px Arial;border:1px solid;}\n\
th {border: 1px solid black;background-color:#A7C942;color:white;}\n\
td {text-align: center;}\n\
tr.alt td {background-color:#EAF2D3;}\n\
tr.avg td {background-color:#BDE34C;}\n\
a:link {color: #90B521;}\n\
a:visited {color: #495E09;}\n\
a:hover {color: #B1DF28;}\n\
a:active {color: #FFFFFF;}\n\
</style>\n</head>\n<body>\n'
# group test header
count = len(testruns)
headline_stamp = '<div class="stamp">{0} {1} {2} {3} ({4} tests)</div>\n'
html += headline_stamp.format(sysvals.stamp['host'],
sysvals.stamp['kernel'], sysvals.stamp['mode'],
sysvals.stamp['time'], count)
# check to see if all the tests have the same value
stampcolumns = False
for data in testruns:
if diffStamp(sysvals.stamp, data.stamp):
stampcolumns = True
break
th = '\t<th>{0}</th>\n'
td = '\t<td>{0}</td>\n'
tdlink = '\t<td><a href="{0}">Click Here</a></td>\n'
# table header
html += '<table class="summary">\n<tr>\n'
html += th.format("Test #")
if stampcolumns:
html += th.format("Hostname")
html += th.format("Kernel Version")
html += th.format("Suspend Mode")
html += th.format("Test Time")
html += th.format("Suspend Time")
html += th.format("Resume Time")
html += th.format("Detail")
html += '</tr>\n'
# test data, 1 row per test
sTimeAvg = 0.0
rTimeAvg = 0.0
num = 1
for data in testruns:
# data.end is the end of post_resume
resumeEnd = data.dmesg['resume_complete']['end']
if num % 2 == 1:
html += '<tr class="alt">\n'
else:
html += '<tr>\n'
# test num
html += td.format("test %d" % num)
num += 1
if stampcolumns:
# host name
val = "unknown"
if('host' in data.stamp):
val = data.stamp['host']
html += td.format(val)
# host kernel
val = "unknown"
if('kernel' in data.stamp):
val = data.stamp['kernel']
html += td.format(val)
# suspend mode
val = "unknown"
if('mode' in data.stamp):
val = data.stamp['mode']
html += td.format(val)
# test time
val = "unknown"
if('time' in data.stamp):
val = data.stamp['time']
html += td.format(val)
# suspend time
sTime = (data.tSuspended - data.start)*1000
sTimeAvg += sTime
html += td.format("%3.3f ms" % sTime)
# resume time
rTime = (resumeEnd - data.tResumed)*1000
rTimeAvg += rTime
html += td.format("%3.3f ms" % rTime)
# link to the output html
html += tdlink.format(data.outfile)
html += '</tr>\n'
# last line: test average
if(count > 0):
sTimeAvg /= count
rTimeAvg /= count
html += '<tr class="avg">\n'
html += td.format('Average') # name
if stampcolumns:
html += td.format('') # host
html += td.format('') # kernel
html += td.format('') # mode
html += td.format('') # time
html += td.format("%3.3f ms" % sTimeAvg) # suspend time
html += td.format("%3.3f ms" % rTimeAvg) # resume time
html += td.format('') # output link
html += '</tr>\n'
# flush the data to file
hf.write(html+'</table>\n')
hf.write('</body>\n</html>\n')
hf.close()
# Function: createHTML
# Description:
# Create the output html file from the resident test data
# Arguments:
# testruns: array of Data objects from parseKernelLog or parseTraceLog
# Output:
# True if the html file was created, false if it failed
def createHTML(testruns):
global sysvals
for data in testruns:
data.normalizeTime(testruns[-1].tSuspended)
x2changes = ['', 'absolute']
if len(testruns) > 1:
x2changes = ['1', 'relative']
# html function templates
headline_stamp = '<div class="stamp">{0} {1} {2} {3}</div>\n'
html_devlist1 = '<button id="devlist1" class="devlist" style="float:left;">Device Detail%s</button>' % x2changes[0]
html_zoombox = '<center><button id="zoomin">ZOOM IN</button><button id="zoomout">ZOOM OUT</button><button id="zoomdef">ZOOM 1:1</button></center>\n'
html_devlist2 = '<button id="devlist2" class="devlist" style="float:right;">Device Detail2</button>\n'
html_timeline = '<div id="dmesgzoombox" class="zoombox">\n<div id="{0}" class="timeline" style="height:{1}px">\n'
html_device = '<div id="{0}" title="{1}" class="thread" style="left:{2}%;top:{3}%;height:{4}%;width:{5}%;">{6}</div>\n'
html_traceevent = '<div title="{0}" class="traceevent" style="left:{1}%;top:{2}%;height:{3}%;width:{4}%;border:1px solid {5};background-color:{5}">{6}</div>\n'
html_phase = '<div class="phase" style="left:{0}%;width:{1}%;top:{2}%;height:{3}%;background-color:{4}">{5}</div>\n'
html_phaselet = '<div id="{0}" class="phaselet" style="left:{1}%;width:{2}%;background-color:{3}"></div>\n'
html_legend = '<div class="square" style="left:{0}%;background-color:{1}"> {2}</div>\n'
html_timetotal = '<table class="time1">\n<tr>'\
'<td class="green">{2} Suspend Time: <b>{0} ms</b></td>'\
'<td class="yellow">{2} Resume Time: <b>{1} ms</b></td>'\
'</tr>\n</table>\n'
html_timetotal2 = '<table class="time1">\n<tr>'\
'<td class="green">{3} Suspend Time: <b>{0} ms</b></td>'\
'<td class="gray">'+sysvals.suspendmode+' time: <b>{1} ms</b></td>'\
'<td class="yellow">{3} Resume Time: <b>{2} ms</b></td>'\
'</tr>\n</table>\n'
html_timegroups = '<table class="time2">\n<tr>'\
'<td class="green">{4}Kernel Suspend: {0} ms</td>'\
'<td class="purple">{4}Firmware Suspend: {1} ms</td>'\
'<td class="purple">{4}Firmware Resume: {2} ms</td>'\
'<td class="yellow">{4}Kernel Resume: {3} ms</td>'\
'</tr>\n</table>\n'
# device timeline
vprint('Creating Device Timeline...')
devtl = Timeline()
# Generate the header for this timeline
textnum = ['First', 'Second']
for data in testruns:
tTotal = data.end - data.start
tEnd = data.dmesg['resume_complete']['end']
if(tTotal == 0):
print('ERROR: No timeline data')
sys.exit()
if(data.tLow > 0):
low_time = '%.0f'%(data.tLow*1000)
if data.fwValid:
suspend_time = '%.0f'%((data.tSuspended-data.start)*1000 + \
(data.fwSuspend/1000000.0))
resume_time = '%.0f'%((tEnd-data.tSuspended)*1000 + \
(data.fwResume/1000000.0))
testdesc1 = 'Total'
testdesc2 = ''
if(len(testruns) > 1):
testdesc1 = testdesc2 = textnum[data.testnumber]
testdesc2 += ' '
if(data.tLow == 0):
thtml = html_timetotal.format(suspend_time, \
resume_time, testdesc1)
else:
thtml = html_timetotal2.format(suspend_time, low_time, \
resume_time, testdesc1)
devtl.html['timeline'] += thtml
sktime = '%.3f'%((data.dmesg['suspend_machine']['end'] - \
data.getStart())*1000)
sftime = '%.3f'%(data.fwSuspend / 1000000.0)
rftime = '%.3f'%(data.fwResume / 1000000.0)
rktime = '%.3f'%((data.getEnd() - \
data.dmesg['resume_machine']['start'])*1000)
devtl.html['timeline'] += html_timegroups.format(sktime, \
sftime, rftime, rktime, testdesc2)
else:
suspend_time = '%.0f'%((data.tSuspended-data.start)*1000)
resume_time = '%.0f'%((tEnd-data.tSuspended)*1000)
testdesc = 'Kernel'
if(len(testruns) > 1):
testdesc = textnum[data.testnumber]+' '+testdesc
if(data.tLow == 0):
thtml = html_timetotal.format(suspend_time, \
resume_time, testdesc)
else:
thtml = html_timetotal2.format(suspend_time, low_time, \
resume_time, testdesc)
devtl.html['timeline'] += thtml
# time scale for potentially multiple datasets
t0 = testruns[0].start
tMax = testruns[-1].end
tSuspended = testruns[-1].tSuspended
tTotal = tMax - t0
# determine the maximum number of rows we need to draw
timelinerows = 0
for data in testruns:
for phase in data.dmesg:
list = data.dmesg[phase]['list']
rows = setTimelineRows(list, list)
data.dmesg[phase]['row'] = rows
if(rows > timelinerows):
timelinerows = rows
# calculate the timeline height and create bounding box, add buttons
devtl.setRows(timelinerows + 1)
devtl.html['timeline'] += html_devlist1
if len(testruns) > 1:
devtl.html['timeline'] += html_devlist2
devtl.html['timeline'] += html_zoombox
devtl.html['timeline'] += html_timeline.format('dmesg', devtl.height)
# draw the colored boxes for each of the phases
for data in testruns:
for b in data.dmesg:
phase = data.dmesg[b]
length = phase['end']-phase['start']
left = '%.3f' % (((phase['start']-t0)*100.0)/tTotal)
width = '%.3f' % ((length*100.0)/tTotal)
devtl.html['timeline'] += html_phase.format(left, width, \
'%.3f'%devtl.scaleH, '%.3f'%(100-devtl.scaleH), \
data.dmesg[b]['color'], '')
# draw the time scale, try to make the number of labels readable
devtl.html['scale'] = createTimeScale(t0, tMax, tSuspended)
devtl.html['timeline'] += devtl.html['scale']
for data in testruns:
for b in data.dmesg:
phaselist = data.dmesg[b]['list']
for d in phaselist:
name = d
drv = ''
dev = phaselist[d]
if(d in sysvals.altdevname):
name = sysvals.altdevname[d]
if('drv' in dev and dev['drv']):
drv = ' {%s}' % dev['drv']
height = (100.0 - devtl.scaleH)/data.dmesg[b]['row']
top = '%.3f' % ((dev['row']*height) + devtl.scaleH)
left = '%.3f' % (((dev['start']-t0)*100)/tTotal)
width = '%.3f' % (((dev['end']-dev['start'])*100)/tTotal)
length = ' (%0.3f ms) ' % ((dev['end']-dev['start'])*1000)
color = 'rgba(204,204,204,0.5)'
devtl.html['timeline'] += html_device.format(dev['id'], \
d+drv+length+b, left, top, '%.3f'%height, width, name+drv)
# draw any trace events found
for data in testruns:
for b in data.dmesg:
phaselist = data.dmesg[b]['list']
for name in phaselist:
dev = phaselist[name]
if('traceevents' in dev):
vprint('Debug trace events found for device %s' % name)
vprint('%20s %20s %10s %8s' % ('action', \
'name', 'time(ms)', 'length(ms)'))
for e in dev['traceevents']:
vprint('%20s %20s %10.3f %8.3f' % (e.action, \
e.name, e.time*1000, e.length*1000))
height = (100.0 - devtl.scaleH)/data.dmesg[b]['row']
top = '%.3f' % ((dev['row']*height) + devtl.scaleH)
left = '%.3f' % (((e.time-t0)*100)/tTotal)
width = '%.3f' % (e.length*100/tTotal)
color = 'rgba(204,204,204,0.5)'
devtl.html['timeline'] += \
html_traceevent.format(e.action+' '+e.name, \
left, top, '%.3f'%height, \
width, e.color, '')
# timeline is finished
devtl.html['timeline'] += '</div>\n</div>\n'
# draw a legend which describes the phases by color
data = testruns[-1]
devtl.html['legend'] = '<div class="legend">\n'
pdelta = 100.0/len(data.phases)
pmargin = pdelta / 4.0
for phase in data.phases:
order = '%.2f' % ((data.dmesg[phase]['order'] * pdelta) + pmargin)
name = string.replace(phase, '_', ' ')
devtl.html['legend'] += html_legend.format(order, \
data.dmesg[phase]['color'], name)
devtl.html['legend'] += '</div>\n'
hf = open(sysvals.htmlfile, 'w')
thread_height = 0
# write the html header first (html head, css code, up to body start)
html_header = '<!DOCTYPE html>\n<html>\n<head>\n\
<meta http-equiv="content-type" content="text/html; charset=UTF-8">\n\
<title>AnalyzeSuspend</title>\n\
<style type=\'text/css\'>\n\
body {overflow-y: scroll;}\n\
.stamp {width: 100%;text-align:center;background-color:gray;line-height:30px;color:white;font: 25px Arial;}\n\
.callgraph {margin-top: 30px;box-shadow: 5px 5px 20px black;}\n\
.callgraph article * {padding-left: 28px;}\n\
h1 {color:black;font: bold 30px Times;}\n\
t0 {color:black;font: bold 30px Times;}\n\
t1 {color:black;font: 30px Times;}\n\
t2 {color:black;font: 25px Times;}\n\
t3 {color:black;font: 20px Times;white-space:nowrap;}\n\
t4 {color:black;font: bold 30px Times;line-height:60px;white-space:nowrap;}\n\
table {width:100%;}\n\
.gray {background-color:rgba(80,80,80,0.1);}\n\
.green {background-color:rgba(204,255,204,0.4);}\n\
.purple {background-color:rgba(128,0,128,0.2);}\n\
.yellow {background-color:rgba(255,255,204,0.4);}\n\
.time1 {font: 22px Arial;border:1px solid;}\n\
.time2 {font: 15px Arial;border-bottom:1px solid;border-left:1px solid;border-right:1px solid;}\n\
td {text-align: center;}\n\
r {color:#500000;font:15px Tahoma;}\n\
n {color:#505050;font:15px Tahoma;}\n\
.tdhl {color: red;}\n\
.hide {display: none;}\n\
.pf {display: none;}\n\
.pf:checked + label {background: url(\'data:image/svg+xml;utf,<?xml version="1.0" standalone="no"?><svg xmlns="http://www.w3.org/2000/svg" height="18" width="18" version="1.1"><circle cx="9" cy="9" r="8" stroke="black" stroke-width="1" fill="white"/><rect x="4" y="8" width="10" height="2" style="fill:black;stroke-width:0"/><rect x="8" y="4" width="2" height="10" style="fill:black;stroke-width:0"/></svg>\') no-repeat left center;}\n\
.pf:not(:checked) ~ label {background: url(\'data:image/svg+xml;utf,<?xml version="1.0" standalone="no"?><svg xmlns="http://www.w3.org/2000/svg" height="18" width="18" version="1.1"><circle cx="9" cy="9" r="8" stroke="black" stroke-width="1" fill="white"/><rect x="4" y="8" width="10" height="2" style="fill:black;stroke-width:0"/></svg>\') no-repeat left center;}\n\
.pf:checked ~ *:not(:nth-child(2)) {display: none;}\n\
.zoombox {position: relative; width: 100%; overflow-x: scroll;}\n\
.timeline {position: relative; font-size: 14px;cursor: pointer;width: 100%; overflow: hidden; background-color:#dddddd;}\n\
.thread {position: absolute; height: '+'%.3f'%thread_height+'%; overflow: hidden; line-height: 30px; border:1px solid;text-align:center;white-space:nowrap;background-color:rgba(204,204,204,0.5);}\n\
.thread:hover {background-color:white;border:1px solid red;z-index:10;}\n\
.hover {background-color:white;border:1px solid red;z-index:10;}\n\
.traceevent {position: absolute;opacity: 0.3;height: '+'%.3f'%thread_height+'%;width:0;overflow:hidden;line-height:30px;text-align:center;white-space:nowrap;}\n\
.phase {position: absolute;overflow: hidden;border:0px;text-align:center;}\n\
.phaselet {position:absolute;overflow:hidden;border:0px;text-align:center;height:100px;font-size:24px;}\n\
.t {position:absolute;top:0%;height:100%;border-right:1px solid black;}\n\
.legend {position: relative; width: 100%; height: 40px; text-align: center;margin-bottom:20px}\n\
.legend .square {position:absolute;top:10px; width: 0px;height: 20px;border:1px solid;padding-left:20px;}\n\
button {height:40px;width:200px;margin-bottom:20px;margin-top:20px;font-size:24px;}\n\
.devlist {position:'+x2changes[1]+';width:190px;}\n\
#devicedetail {height:100px;box-shadow: 5px 5px 20px black;}\n\
</style>\n</head>\n<body>\n'
hf.write(html_header)
# write the test title and general info header
if(sysvals.stamp['time'] != ""):
hf.write(headline_stamp.format(sysvals.stamp['host'],
sysvals.stamp['kernel'], sysvals.stamp['mode'], \
sysvals.stamp['time']))
# write the device timeline
hf.write(devtl.html['timeline'])
hf.write(devtl.html['legend'])
hf.write('<div id="devicedetailtitle"></div>\n')
hf.write('<div id="devicedetail" style="display:none;">\n')
# draw the colored boxes for the device detail section
for data in testruns:
hf.write('<div id="devicedetail%d">\n' % data.testnumber)
for b in data.phases:
phase = data.dmesg[b]
length = phase['end']-phase['start']
left = '%.3f' % (((phase['start']-t0)*100.0)/tTotal)
width = '%.3f' % ((length*100.0)/tTotal)
hf.write(html_phaselet.format(b, left, width, \
data.dmesg[b]['color']))
hf.write('</div>\n')
hf.write('</div>\n')
# write the ftrace data (callgraph)
data = testruns[-1]
if(sysvals.usecallgraph):
hf.write('<section id="callgraphs" class="callgraph">\n')
# write out the ftrace data converted to html
html_func_top = '<article id="{0}" class="atop" style="background-color:{1}">\n<input type="checkbox" class="pf" id="f{2}" checked/><label for="f{2}">{3} {4}</label>\n'
html_func_start = '<article>\n<input type="checkbox" class="pf" id="f{0}" checked/><label for="f{0}">{1} {2}</label>\n'
html_func_end = '</article>\n'
html_func_leaf = '<article>{0} {1}</article>\n'
num = 0
for p in data.phases:
list = data.dmesg[p]['list']
for devname in data.sortedDevices(p):
if('ftrace' not in list[devname]):
continue
name = devname
if(devname in sysvals.altdevname):
name = sysvals.altdevname[devname]
devid = list[devname]['id']
cg = list[devname]['ftrace']
flen = '<r>(%.3f ms @ %.3f to %.3f)</r>' % \
((cg.end - cg.start)*1000, cg.start*1000, cg.end*1000)
hf.write(html_func_top.format(devid, data.dmesg[p]['color'], \
num, name+' '+p, flen))
num += 1
for line in cg.list:
if(line.length < 0.000000001):
flen = ''
else:
flen = '<n>(%.3f ms @ %.3f)</n>' % (line.length*1000, \
line.time*1000)
if(line.freturn and line.fcall):
hf.write(html_func_leaf.format(line.name, flen))
elif(line.freturn):
hf.write(html_func_end)
else:
hf.write(html_func_start.format(num, line.name, flen))
num += 1
hf.write(html_func_end)
hf.write('\n\n </section>\n')
# write the footer and close
addScriptCode(hf, testruns)
hf.write('</body>\n</html>\n')
hf.close()
return True
# Function: addScriptCode
# Description:
# Adds the javascript code to the output html
# Arguments:
# hf: the open html file pointer
# testruns: array of Data objects from parseKernelLog or parseTraceLog
def addScriptCode(hf, testruns):
t0 = (testruns[0].start - testruns[-1].tSuspended) * 1000
tMax = (testruns[-1].end - testruns[-1].tSuspended) * 1000
# create an array in javascript memory with the device details
detail = ' var devtable = [];\n'
for data in testruns:
topo = data.deviceTopology()
detail += ' devtable[%d] = "%s";\n' % (data.testnumber, topo)
detail += ' var bounds = [%f,%f];\n' % (t0, tMax)
# add the code which will manipulate the data in the browser
script_code = \
'<script type="text/javascript">\n'+detail+\
' function zoomTimeline() {\n'\
' var timescale = document.getElementById("timescale");\n'\
' var dmesg = document.getElementById("dmesg");\n'\
' var zoombox = document.getElementById("dmesgzoombox");\n'\
' var val = parseFloat(dmesg.style.width);\n'\
' var newval = 100;\n'\
' var sh = window.outerWidth / 2;\n'\
' if(this.id == "zoomin") {\n'\
' newval = val * 1.2;\n'\
' if(newval > 40000) newval = 40000;\n'\
' dmesg.style.width = newval+"%";\n'\
' zoombox.scrollLeft = ((zoombox.scrollLeft + sh) * newval / val) - sh;\n'\
' } else if (this.id == "zoomout") {\n'\
' newval = val / 1.2;\n'\
' if(newval < 100) newval = 100;\n'\
' dmesg.style.width = newval+"%";\n'\
' zoombox.scrollLeft = ((zoombox.scrollLeft + sh) * newval / val) - sh;\n'\
' } else {\n'\
' zoombox.scrollLeft = 0;\n'\
' dmesg.style.width = "100%";\n'\
' }\n'\
' var html = "";\n'\
' var t0 = bounds[0];\n'\
' var tMax = bounds[1];\n'\
' var tTotal = tMax - t0;\n'\
' var wTotal = tTotal * 100.0 / newval;\n'\
' for(var tS = 1000; (wTotal / tS) < 3; tS /= 10);\n'\
' if(tS < 1) tS = 1;\n'\
' for(var s = ((t0 / tS)|0) * tS; s < tMax; s += tS) {\n'\
' var pos = (tMax - s) * 100.0 / tTotal;\n'\
' var name = (s == 0)?"S/R":(s+"ms");\n'\
' html += "<div class=\\"t\\" style=\\"right:"+pos+"%\\">"+name+"</div>";\n'\
' }\n'\
' timescale.innerHTML = html;\n'\
' }\n'\
' function deviceHover() {\n'\
' var name = this.title.slice(0, this.title.indexOf(" ("));\n'\
' var dmesg = document.getElementById("dmesg");\n'\
' var dev = dmesg.getElementsByClassName("thread");\n'\
' var cpu = -1;\n'\
' if(name.match("CPU_ON\[[0-9]*\]"))\n'\
' cpu = parseInt(name.slice(7));\n'\
' else if(name.match("CPU_OFF\[[0-9]*\]"))\n'\
' cpu = parseInt(name.slice(8));\n'\
' for (var i = 0; i < dev.length; i++) {\n'\
' dname = dev[i].title.slice(0, dev[i].title.indexOf(" ("));\n'\
' if((cpu >= 0 && dname.match("CPU_O[NF]*\\\[*"+cpu+"\\\]")) ||\n'\
' (name == dname))\n'\
' {\n'\
' dev[i].className = "thread hover";\n'\
' } else {\n'\
' dev[i].className = "thread";\n'\
' }\n'\
' }\n'\
' }\n'\
' function deviceUnhover() {\n'\
' var dmesg = document.getElementById("dmesg");\n'\
' var dev = dmesg.getElementsByClassName("thread");\n'\
' for (var i = 0; i < dev.length; i++) {\n'\
' dev[i].className = "thread";\n'\
' }\n'\
' }\n'\
' function deviceTitle(title, total, cpu) {\n'\
' var prefix = "Total";\n'\
' if(total.length > 3) {\n'\
' prefix = "Average";\n'\
' total[1] = (total[1]+total[3])/2;\n'\
' total[2] = (total[2]+total[4])/2;\n'\
' }\n'\
' var devtitle = document.getElementById("devicedetailtitle");\n'\
' var name = title.slice(0, title.indexOf(" "));\n'\
' if(cpu >= 0) name = "CPU"+cpu;\n'\
' var driver = "";\n'\
' var tS = "<t2>(</t2>";\n'\
' var tR = "<t2>)</t2>";\n'\
' if(total[1] > 0)\n'\
' tS = "<t2>("+prefix+" Suspend:</t2><t0> "+total[1].toFixed(3)+" ms</t0> ";\n'\
' if(total[2] > 0)\n'\
' tR = " <t2>"+prefix+" Resume:</t2><t0> "+total[2].toFixed(3)+" ms<t2>)</t2></t0>";\n'\
' var s = title.indexOf("{");\n'\
' var e = title.indexOf("}");\n'\
' if((s >= 0) && (e >= 0))\n'\
' driver = title.slice(s+1, e) + " <t1>@</t1> ";\n'\
' if(total[1] > 0 && total[2] > 0)\n'\
' devtitle.innerHTML = "<t0>"+driver+name+"</t0> "+tS+tR;\n'\
' else\n'\
' devtitle.innerHTML = "<t0>"+title+"</t0>";\n'\
' return name;\n'\
' }\n'\
' function deviceDetail() {\n'\
' var devinfo = document.getElementById("devicedetail");\n'\
' devinfo.style.display = "block";\n'\
' var name = this.title.slice(0, this.title.indexOf(" ("));\n'\
' var cpu = -1;\n'\
' if(name.match("CPU_ON\[[0-9]*\]"))\n'\
' cpu = parseInt(name.slice(7));\n'\
' else if(name.match("CPU_OFF\[[0-9]*\]"))\n'\
' cpu = parseInt(name.slice(8));\n'\
' var dmesg = document.getElementById("dmesg");\n'\
' var dev = dmesg.getElementsByClassName("thread");\n'\
' var idlist = [];\n'\
' var pdata = [[]];\n'\
' var pd = pdata[0];\n'\
' var total = [0.0, 0.0, 0.0];\n'\
' for (var i = 0; i < dev.length; i++) {\n'\
' dname = dev[i].title.slice(0, dev[i].title.indexOf(" ("));\n'\
' if((cpu >= 0 && dname.match("CPU_O[NF]*\\\[*"+cpu+"\\\]")) ||\n'\
' (name == dname))\n'\
' {\n'\
' idlist[idlist.length] = dev[i].id;\n'\
' var tidx = 1;\n'\
' if(dev[i].id[0] == "a") {\n'\
' pd = pdata[0];\n'\
' } else {\n'\
' if(pdata.length == 1) pdata[1] = [];\n'\
' if(total.length == 3) total[3]=total[4]=0.0;\n'\
' pd = pdata[1];\n'\
' tidx = 3;\n'\
' }\n'\
' var info = dev[i].title.split(" ");\n'\
' var pname = info[info.length-1];\n'\
' pd[pname] = parseFloat(info[info.length-3].slice(1));\n'\
' total[0] += pd[pname];\n'\
' if(pname.indexOf("suspend") >= 0)\n'\
' total[tidx] += pd[pname];\n'\
' else\n'\
' total[tidx+1] += pd[pname];\n'\
' }\n'\
' }\n'\
' var devname = deviceTitle(this.title, total, cpu);\n'\
' var left = 0.0;\n'\
' for (var t = 0; t < pdata.length; t++) {\n'\
' pd = pdata[t];\n'\
' devinfo = document.getElementById("devicedetail"+t);\n'\
' var phases = devinfo.getElementsByClassName("phaselet");\n'\
' for (var i = 0; i < phases.length; i++) {\n'\
' if(phases[i].id in pd) {\n'\
' var w = 100.0*pd[phases[i].id]/total[0];\n'\
' var fs = 32;\n'\
' if(w < 8) fs = 4*w | 0;\n'\
' var fs2 = fs*3/4;\n'\
' phases[i].style.width = w+"%";\n'\
' phases[i].style.left = left+"%";\n'\
' phases[i].title = phases[i].id+" "+pd[phases[i].id]+" ms";\n'\
' left += w;\n'\
' var time = "<t4 style=\\"font-size:"+fs+"px\\">"+pd[phases[i].id]+" ms<br></t4>";\n'\
' var pname = "<t3 style=\\"font-size:"+fs2+"px\\">"+phases[i].id.replace("_", " ")+"</t3>";\n'\
' phases[i].innerHTML = time+pname;\n'\
' } else {\n'\
' phases[i].style.width = "0%";\n'\
' phases[i].style.left = left+"%";\n'\
' }\n'\
' }\n'\
' }\n'\
' var cglist = document.getElementById("callgraphs");\n'\
' if(!cglist) return;\n'\
' var cg = cglist.getElementsByClassName("atop");\n'\
' for (var i = 0; i < cg.length; i++) {\n'\
' if(idlist.indexOf(cg[i].id) >= 0) {\n'\
' cg[i].style.display = "block";\n'\
' } else {\n'\
' cg[i].style.display = "none";\n'\
' }\n'\
' }\n'\
' }\n'\
' function devListWindow(e) {\n'\
' var sx = e.clientX;\n'\
' if(sx > window.innerWidth - 440)\n'\
' sx = window.innerWidth - 440;\n'\
' var cfg="top="+e.screenY+", left="+sx+", width=440, height=720, scrollbars=yes";\n'\
' var win = window.open("", "_blank", cfg);\n'\
' if(window.chrome) win.moveBy(sx, 0);\n'\
' var html = "<title>"+e.target.innerHTML+"</title>"+\n'\
' "<style type=\\"text/css\\">"+\n'\
' " ul {list-style-type:circle;padding-left:10px;margin-left:10px;}"+\n'\
' "</style>"\n'\
' var dt = devtable[0];\n'\
' if(e.target.id != "devlist1")\n'\
' dt = devtable[1];\n'\
' win.document.write(html+dt);\n'\
' }\n'\
' window.addEventListener("load", function () {\n'\
' var dmesg = document.getElementById("dmesg");\n'\
' dmesg.style.width = "100%"\n'\
' document.getElementById("zoomin").onclick = zoomTimeline;\n'\
' document.getElementById("zoomout").onclick = zoomTimeline;\n'\
' document.getElementById("zoomdef").onclick = zoomTimeline;\n'\
' var devlist = document.getElementsByClassName("devlist");\n'\
' for (var i = 0; i < devlist.length; i++)\n'\
' devlist[i].onclick = devListWindow;\n'\
' var dev = dmesg.getElementsByClassName("thread");\n'\
' for (var i = 0; i < dev.length; i++) {\n'\
' dev[i].onclick = deviceDetail;\n'\
' dev[i].onmouseover = deviceHover;\n'\
' dev[i].onmouseout = deviceUnhover;\n'\
' }\n'\
' zoomTimeline();\n'\
' });\n'\
'</script>\n'
hf.write(script_code);
# Function: executeSuspend
# Description:
# Execute system suspend through the sysfs interface, then copy the output
# dmesg and ftrace files to the test output directory.
def executeSuspend():
global sysvals
detectUSB(False)
t0 = time.time()*1000
tp = sysvals.tpath
# execute however many s/r runs requested
for count in range(1,sysvals.execcount+1):
# clear the kernel ring buffer just as we start
os.system('dmesg -C')
# enable callgraph ftrace only for the second run
if(sysvals.usecallgraph and count == 2):
# set trace type
os.system('echo function_graph > '+tp+'current_tracer')
os.system('echo "" > '+tp+'set_ftrace_filter')
# set trace format options
os.system('echo funcgraph-abstime > '+tp+'trace_options')
os.system('echo funcgraph-proc > '+tp+'trace_options')
# focus only on device suspend and resume
os.system('cat '+tp+'available_filter_functions | '+\
'grep dpm_run_callback > '+tp+'set_graph_function')
# if this is test2 and there's a delay, start here
if(count > 1 and sysvals.x2delay > 0):
tN = time.time()*1000
while (tN - t0) < sysvals.x2delay:
tN = time.time()*1000
time.sleep(0.001)
# start ftrace
if(sysvals.usecallgraph or sysvals.usetraceevents):
print('START TRACING')
os.system('echo 1 > '+tp+'tracing_on')
# initiate suspend
if(sysvals.usecallgraph or sysvals.usetraceevents):
os.system('echo SUSPEND START > '+tp+'trace_marker')
if(sysvals.rtcwake):
print('SUSPEND START')
print('will autoresume in %d seconds' % sysvals.rtcwaketime)
sysvals.rtcWakeAlarm()
else:
print('SUSPEND START (press a key to resume)')
pf = open(sysvals.powerfile, 'w')
pf.write(sysvals.suspendmode)
# execution will pause here
pf.close()
t0 = time.time()*1000
# return from suspend
print('RESUME COMPLETE')
if(sysvals.usecallgraph or sysvals.usetraceevents):
os.system('echo RESUME COMPLETE > '+tp+'trace_marker')
# see if there's firmware timing data to be had
t = sysvals.postresumetime
if(t > 0):
print('Waiting %d seconds for POST-RESUME trace events...' % t)
time.sleep(t)
# stop ftrace
if(sysvals.usecallgraph or sysvals.usetraceevents):
os.system('echo 0 > '+tp+'tracing_on')
print('CAPTURING TRACE')
writeDatafileHeader(sysvals.ftracefile)
os.system('cat '+tp+'trace >> '+sysvals.ftracefile)
os.system('echo "" > '+tp+'trace')
# grab a copy of the dmesg output
print('CAPTURING DMESG')
writeDatafileHeader(sysvals.dmesgfile)
os.system('dmesg -c >> '+sysvals.dmesgfile)
def writeDatafileHeader(filename):
global sysvals
fw = getFPDT(False)
prt = sysvals.postresumetime
fp = open(filename, 'a')
fp.write(sysvals.teststamp+'\n')
if(fw):
fp.write('# fwsuspend %u fwresume %u\n' % (fw[0], fw[1]))
if(prt > 0):
fp.write('# post resume time %u\n' % prt)
fp.close()
# Function: executeAndroidSuspend
# Description:
# Execute system suspend through the sysfs interface
# on a remote android device, then transfer the output
# dmesg and ftrace files to the local output directory.
def executeAndroidSuspend():
global sysvals
# check to see if the display is currently off
tp = sysvals.tpath
out = os.popen(sysvals.adb+\
' shell dumpsys power | grep mScreenOn').read().strip()
# if so we need to turn it on so we can issue a new suspend
if(out.endswith('false')):
print('Waking the device up for the test...')
# send the KEYPAD_POWER keyevent to wake it up
os.system(sysvals.adb+' shell input keyevent 26')
# wait a few seconds so the user can see the device wake up
time.sleep(3)
# execute however many s/r runs requested
for count in range(1,sysvals.execcount+1):
# clear the kernel ring buffer just as we start
os.system(sysvals.adb+' shell dmesg -c > /dev/null 2>&1')
# start ftrace
if(sysvals.usetraceevents):
print('START TRACING')
os.system(sysvals.adb+" shell 'echo 1 > "+tp+"tracing_on'")
# initiate suspend
for count in range(1,sysvals.execcount+1):
if(sysvals.usetraceevents):
os.system(sysvals.adb+\
" shell 'echo SUSPEND START > "+tp+"trace_marker'")
print('SUSPEND START (press a key on the device to resume)')
os.system(sysvals.adb+" shell 'echo "+sysvals.suspendmode+\
" > "+sysvals.powerfile+"'")
# execution will pause here, then adb will exit
while(True):
check = os.popen(sysvals.adb+\
' shell pwd 2>/dev/null').read().strip()
if(len(check) > 0):
break
time.sleep(1)
if(sysvals.usetraceevents):
os.system(sysvals.adb+" shell 'echo RESUME COMPLETE > "+tp+\
"trace_marker'")
# return from suspend
print('RESUME COMPLETE')
# stop ftrace
if(sysvals.usetraceevents):
os.system(sysvals.adb+" shell 'echo 0 > "+tp+"tracing_on'")
print('CAPTURING TRACE')
os.system('echo "'+sysvals.teststamp+'" > '+sysvals.ftracefile)
os.system(sysvals.adb+' shell cat '+tp+\
'trace >> '+sysvals.ftracefile)
# grab a copy of the dmesg output
print('CAPTURING DMESG')
os.system('echo "'+sysvals.teststamp+'" > '+sysvals.dmesgfile)
os.system(sysvals.adb+' shell dmesg >> '+sysvals.dmesgfile)
# Function: setUSBDevicesAuto
# Description:
# Set the autosuspend control parameter of all USB devices to auto
# This can be dangerous, so use at your own risk, most devices are set
# to always-on since the kernel cant determine if the device can
# properly autosuspend
def setUSBDevicesAuto():
global sysvals
rootCheck()
for dirname, dirnames, filenames in os.walk('/sys/devices'):
if(re.match('.*/usb[0-9]*.*', dirname) and
'idVendor' in filenames and 'idProduct' in filenames):
os.system('echo auto > %s/power/control' % dirname)
name = dirname.split('/')[-1]
desc = os.popen('cat %s/product 2>/dev/null' % \
dirname).read().replace('\n', '')
ctrl = os.popen('cat %s/power/control 2>/dev/null' % \
dirname).read().replace('\n', '')
print('control is %s for %6s: %s' % (ctrl, name, desc))
# Function: yesno
# Description:
# Print out an equivalent Y or N for a set of known parameter values
# Output:
# 'Y', 'N', or ' ' if the value is unknown
def yesno(val):
yesvals = ['auto', 'enabled', 'active', '1']
novals = ['on', 'disabled', 'suspended', 'forbidden', 'unsupported']
if val in yesvals:
return 'Y'
elif val in novals:
return 'N'
return ' '
# Function: ms2nice
# Description:
# Print out a very concise time string in minutes and seconds
# Output:
# The time string, e.g. "1901m16s"
def ms2nice(val):
ms = 0
try:
ms = int(val)
except:
return 0.0
m = ms / 60000
s = (ms / 1000) - (m * 60)
return '%3dm%2ds' % (m, s)
# Function: detectUSB
# Description:
# Detect all the USB hosts and devices currently connected and add
# a list of USB device names to sysvals for better timeline readability
# Arguments:
# output: True to output the info to stdout, False otherwise
def detectUSB(output):
global sysvals
field = {'idVendor':'', 'idProduct':'', 'product':'', 'speed':''}
power = {'async':'', 'autosuspend':'', 'autosuspend_delay_ms':'',
'control':'', 'persist':'', 'runtime_enabled':'',
'runtime_status':'', 'runtime_usage':'',
'runtime_active_time':'',
'runtime_suspended_time':'',
'active_duration':'',
'connected_duration':''}
if(output):
print('LEGEND')
print('---------------------------------------------------------------------------------------------')
print(' A = async/sync PM queue Y/N D = autosuspend delay (seconds)')
print(' S = autosuspend Y/N rACTIVE = runtime active (min/sec)')
print(' P = persist across suspend Y/N rSUSPEN = runtime suspend (min/sec)')
print(' E = runtime suspend enabled/forbidden Y/N ACTIVE = active duration (min/sec)')
print(' R = runtime status active/suspended Y/N CONNECT = connected duration (min/sec)')
print(' U = runtime usage count')
print('---------------------------------------------------------------------------------------------')
print(' NAME ID DESCRIPTION SPEED A S P E R U D rACTIVE rSUSPEN ACTIVE CONNECT')
print('---------------------------------------------------------------------------------------------')
for dirname, dirnames, filenames in os.walk('/sys/devices'):
if(re.match('.*/usb[0-9]*.*', dirname) and
'idVendor' in filenames and 'idProduct' in filenames):
for i in field:
field[i] = os.popen('cat %s/%s 2>/dev/null' % \
(dirname, i)).read().replace('\n', '')
name = dirname.split('/')[-1]
if(len(field['product']) > 0):
sysvals.altdevname[name] = \
'%s [%s]' % (field['product'], name)
else:
sysvals.altdevname[name] = \
'%s:%s [%s]' % (field['idVendor'], \
field['idProduct'], name)
if(output):
for i in power:
power[i] = os.popen('cat %s/power/%s 2>/dev/null' % \
(dirname, i)).read().replace('\n', '')
if(re.match('usb[0-9]*', name)):
first = '%-8s' % name
else:
first = '%8s' % name
print('%s [%s:%s] %-20s %-4s %1s %1s %1s %1s %1s %1s %1s %s %s %s %s' % \
(first, field['idVendor'], field['idProduct'], \
field['product'][0:20], field['speed'], \
yesno(power['async']), \
yesno(power['control']), \
yesno(power['persist']), \
yesno(power['runtime_enabled']), \
yesno(power['runtime_status']), \
power['runtime_usage'], \
power['autosuspend'], \
ms2nice(power['runtime_active_time']), \
ms2nice(power['runtime_suspended_time']), \
ms2nice(power['active_duration']), \
ms2nice(power['connected_duration'])))
# Function: getModes
# Description:
# Determine the supported power modes on this system
# Output:
# A string list of the available modes
def getModes():
global sysvals
modes = ''
if(not sysvals.android):
if(os.path.exists(sysvals.powerfile)):
fp = open(sysvals.powerfile, 'r')
modes = string.split(fp.read())
fp.close()
else:
line = os.popen(sysvals.adb+' shell cat '+\
sysvals.powerfile).read().strip()
modes = string.split(line)
return modes
# Function: getFPDT
# Description:
# Read the acpi bios tables and pull out FPDT, the firmware data
# Arguments:
# output: True to output the info to stdout, False otherwise
def getFPDT(output):
global sysvals
rectype = {}
rectype[0] = 'Firmware Basic Boot Performance Record'
rectype[1] = 'S3 Performance Table Record'
prectype = {}
prectype[0] = 'Basic S3 Resume Performance Record'
prectype[1] = 'Basic S3 Suspend Performance Record'
rootCheck()
if(not os.path.exists(sysvals.fpdtpath)):
if(output):
doError('file doesnt exist: %s' % sysvals.fpdtpath, False)
return False
if(not os.access(sysvals.fpdtpath, os.R_OK)):
if(output):
doError('file isnt readable: %s' % sysvals.fpdtpath, False)
return False
if(not os.path.exists(sysvals.mempath)):
if(output):
doError('file doesnt exist: %s' % sysvals.mempath, False)
return False
if(not os.access(sysvals.mempath, os.R_OK)):
if(output):
doError('file isnt readable: %s' % sysvals.mempath, False)
return False
fp = open(sysvals.fpdtpath, 'rb')
buf = fp.read()
fp.close()
if(len(buf) < 36):
if(output):
doError('Invalid FPDT table data, should '+\
'be at least 36 bytes', False)
return False
table = struct.unpack('4sIBB6s8sI4sI', buf[0:36])
if(output):
print('')
print('Firmware Performance Data Table (%s)' % table[0])
print(' Signature : %s' % table[0])
print(' Table Length : %u' % table[1])
print(' Revision : %u' % table[2])
print(' Checksum : 0x%x' % table[3])
print(' OEM ID : %s' % table[4])
print(' OEM Table ID : %s' % table[5])
print(' OEM Revision : %u' % table[6])
print(' Creator ID : %s' % table[7])
print(' Creator Revision : 0x%x' % table[8])
print('')
if(table[0] != 'FPDT'):
if(output):
doError('Invalid FPDT table')
return False
if(len(buf) <= 36):
return False
i = 0
fwData = [0, 0]
records = buf[36:]
fp = open(sysvals.mempath, 'rb')
while(i < len(records)):
header = struct.unpack('HBB', records[i:i+4])
if(header[0] not in rectype):
continue
if(header[1] != 16):
continue
addr = struct.unpack('Q', records[i+8:i+16])[0]
try:
fp.seek(addr)
first = fp.read(8)
except:
doError('Bad address 0x%x in %s' % (addr, sysvals.mempath), False)
rechead = struct.unpack('4sI', first)
recdata = fp.read(rechead[1]-8)
if(rechead[0] == 'FBPT'):
record = struct.unpack('HBBIQQQQQ', recdata)
if(output):
print('%s (%s)' % (rectype[header[0]], rechead[0]))
print(' Reset END : %u ns' % record[4])
print(' OS Loader LoadImage Start : %u ns' % record[5])
print(' OS Loader StartImage Start : %u ns' % record[6])
print(' ExitBootServices Entry : %u ns' % record[7])
print(' ExitBootServices Exit : %u ns' % record[8])
elif(rechead[0] == 'S3PT'):
if(output):
print('%s (%s)' % (rectype[header[0]], rechead[0]))
j = 0
while(j < len(recdata)):
prechead = struct.unpack('HBB', recdata[j:j+4])
if(prechead[0] not in prectype):
continue
if(prechead[0] == 0):
record = struct.unpack('IIQQ', recdata[j:j+prechead[1]])
fwData[1] = record[2]
if(output):
print(' %s' % prectype[prechead[0]])
print(' Resume Count : %u' % \
record[1])
print(' FullResume : %u ns' % \
record[2])
print(' AverageResume : %u ns' % \
record[3])
elif(prechead[0] == 1):
record = struct.unpack('QQ', recdata[j+4:j+prechead[1]])
fwData[0] = record[1] - record[0]
if(output):
print(' %s' % prectype[prechead[0]])
print(' SuspendStart : %u ns' % \
record[0])
print(' SuspendEnd : %u ns' % \
record[1])
print(' SuspendTime : %u ns' % \
fwData[0])
j += prechead[1]
if(output):
print('')
i += header[1]
fp.close()
return fwData
# Function: statusCheck
# Description:
# Verify that the requested command and options will work, and
# print the results to the terminal
# Output:
# True if the test will work, False if not
def statusCheck():
global sysvals
status = True
if(sysvals.android):
print('Checking the android system ...')
else:
print('Checking this system (%s)...' % platform.node())
# check if adb is connected to a device
if(sysvals.android):
res = 'NO'
out = os.popen(sysvals.adb+' get-state').read().strip()
if(out == 'device'):
res = 'YES'
print(' is android device connected: %s' % res)
if(res != 'YES'):
print(' Please connect the device before using this tool')
return False
# check we have root access
res = 'NO (No features of this tool will work!)'
if(sysvals.android):
out = os.popen(sysvals.adb+' shell id').read().strip()
if('root' in out):
res = 'YES'
else:
if(os.environ['USER'] == 'root'):
res = 'YES'
print(' have root access: %s' % res)
if(res != 'YES'):
if(sysvals.android):
print(' Try running "adb root" to restart the daemon as root')
else:
print(' Try running this script with sudo')
return False
# check sysfs is mounted
res = 'NO (No features of this tool will work!)'
if(sysvals.android):
out = os.popen(sysvals.adb+' shell ls '+\
sysvals.powerfile).read().strip()
if(out == sysvals.powerfile):
res = 'YES'
else:
if(os.path.exists(sysvals.powerfile)):
res = 'YES'
print(' is sysfs mounted: %s' % res)
if(res != 'YES'):
return False
# check target mode is a valid mode
res = 'NO'
modes = getModes()
if(sysvals.suspendmode in modes):
res = 'YES'
else:
status = False
print(' is "%s" a valid power mode: %s' % (sysvals.suspendmode, res))
if(res == 'NO'):
print(' valid power modes are: %s' % modes)
print(' please choose one with -m')
# check if the tool can unlock the device
if(sysvals.android):
res = 'YES'
out1 = os.popen(sysvals.adb+\
' shell dumpsys power | grep mScreenOn').read().strip()
out2 = os.popen(sysvals.adb+\
' shell input').read().strip()
if(not out1.startswith('mScreenOn') or not out2.startswith('usage')):
res = 'NO (wake the android device up before running the test)'
print(' can I unlock the screen: %s' % res)
# check if ftrace is available
res = 'NO'
ftgood = verifyFtrace()
if(ftgood):
res = 'YES'
elif(sysvals.usecallgraph):
status = False
print(' is ftrace supported: %s' % res)
# what data source are we using
res = 'DMESG'
if(ftgood):
sysvals.usetraceeventsonly = True
sysvals.usetraceevents = False
for e in sysvals.traceevents:
check = False
if(sysvals.android):
out = os.popen(sysvals.adb+' shell ls -d '+\
sysvals.epath+e).read().strip()
if(out == sysvals.epath+e):
check = True
else:
if(os.path.exists(sysvals.epath+e)):
check = True
if(not check):
sysvals.usetraceeventsonly = False
if(e == 'suspend_resume' and check):
sysvals.usetraceevents = True
if(sysvals.usetraceevents and sysvals.usetraceeventsonly):
res = 'FTRACE (all trace events found)'
elif(sysvals.usetraceevents):
res = 'DMESG and FTRACE (suspend_resume trace event found)'
print(' timeline data source: %s' % res)
# check if rtcwake
res = 'NO'
if(sysvals.rtcpath != ''):
res = 'YES'
elif(sysvals.rtcwake):
status = False
print(' is rtcwake supported: %s' % res)
return status
# Function: doError
# Description:
# generic error function for catastrphic failures
# Arguments:
# msg: the error message to print
# help: True if printHelp should be called after, False otherwise
def doError(msg, help):
if(help == True):
printHelp()
print('ERROR: %s\n') % msg
sys.exit()
# Function: doWarning
# Description:
# generic warning function for non-catastrophic anomalies
# Arguments:
# msg: the warning message to print
# file: If not empty, a filename to request be sent to the owner for debug
def doWarning(msg, file):
print('/* %s */') % msg
if(file):
print('/* For a fix, please send this'+\
' %s file to <todd.e.brandt@intel.com> */' % file)
# Function: rootCheck
# Description:
# quick check to see if we have root access
def rootCheck():
if(os.environ['USER'] != 'root'):
doError('This script must be run as root', False)
# Function: getArgInt
# Description:
# pull out an integer argument from the command line with checks
def getArgInt(name, args, min, max):
try:
arg = args.next()
except:
doError(name+': no argument supplied', True)
try:
val = int(arg)
except:
doError(name+': non-integer value given', True)
if(val < min or val > max):
doError(name+': value should be between %d and %d' % (min, max), True)
return val
# Function: rerunTest
# Description:
# generate an output from an existing set of ftrace/dmesg logs
def rerunTest():
global sysvals
if(sysvals.ftracefile != ''):
doesTraceLogHaveTraceEvents()
if(sysvals.dmesgfile == '' and not sysvals.usetraceeventsonly):
doError('recreating this html output '+\
'requires a dmesg file', False)
sysvals.setOutputFile()
vprint('Output file: %s' % sysvals.htmlfile)
print('PROCESSING DATA')
if(sysvals.usetraceeventsonly):
testruns = parseTraceLog()
else:
testruns = loadKernelLog()
for data in testruns:
parseKernelLog(data)
if(sysvals.ftracefile != ''):
appendIncompleteTraceLog(testruns)
createHTML(testruns)
# Function: runTest
# Description:
# execute a suspend/resume, gather the logs, and generate the output
def runTest(subdir):
global sysvals
# prepare for the test
if(not sysvals.android):
initFtrace()
else:
initFtraceAndroid()
sysvals.initTestOutput(subdir)
vprint('Output files:\n %s' % sysvals.dmesgfile)
if(sysvals.usecallgraph or
sysvals.usetraceevents or
sysvals.usetraceeventsonly):
vprint(' %s' % sysvals.ftracefile)
vprint(' %s' % sysvals.htmlfile)
# execute the test
if(not sysvals.android):
executeSuspend()
else:
executeAndroidSuspend()
# analyze the data and create the html output
print('PROCESSING DATA')
if(sysvals.usetraceeventsonly):
# data for kernels 3.15 or newer is entirely in ftrace
testruns = parseTraceLog()
else:
# data for kernels older than 3.15 is primarily in dmesg
testruns = loadKernelLog()
for data in testruns:
parseKernelLog(data)
if(sysvals.usecallgraph or sysvals.usetraceevents):
appendIncompleteTraceLog(testruns)
createHTML(testruns)
# Function: runSummary
# Description:
# create a summary of tests in a sub-directory
def runSummary(subdir, output):
global sysvals
# get a list of ftrace output files
files = []
for dirname, dirnames, filenames in os.walk(subdir):
for filename in filenames:
if(re.match('.*_ftrace.txt', filename)):
files.append("%s/%s" % (dirname, filename))
# process the files in order and get an array of data objects
testruns = []
for file in sorted(files):
if output:
print("Test found in %s" % os.path.dirname(file))
sysvals.ftracefile = file
sysvals.dmesgfile = file.replace('_ftrace.txt', '_dmesg.txt')
doesTraceLogHaveTraceEvents()
sysvals.usecallgraph = False
if not sysvals.usetraceeventsonly:
if(not os.path.exists(sysvals.dmesgfile)):
print("Skipping %s: not a valid test input" % file)
continue
else:
if output:
f = os.path.basename(sysvals.ftracefile)
d = os.path.basename(sysvals.dmesgfile)
print("\tInput files: %s and %s" % (f, d))
testdata = loadKernelLog()
data = testdata[0]
parseKernelLog(data)
testdata = [data]
appendIncompleteTraceLog(testdata)
else:
if output:
print("\tInput file: %s" % os.path.basename(sysvals.ftracefile))
testdata = parseTraceLog()
data = testdata[0]
data.normalizeTime(data.tSuspended)
link = file.replace(subdir+'/', '').replace('_ftrace.txt', '.html')
data.outfile = link
testruns.append(data)
createHTMLSummarySimple(testruns, subdir+'/summary.html')
# Function: printHelp
# Description:
# print out the help text
def printHelp():
global sysvals
modes = getModes()
print('')
print('AnalyzeSuspend v%.1f' % sysvals.version)
print('Usage: sudo analyze_suspend.py <options>')
print('')
print('Description:')
print(' This tool is designed to assist kernel and OS developers in optimizing')
print(' their linux stack\'s suspend/resume time. Using a kernel image built')
print(' with a few extra options enabled, the tool will execute a suspend and')
print(' capture dmesg and ftrace data until resume is complete. This data is')
print(' transformed into a device timeline and an optional callgraph to give')
print(' a detailed view of which devices/subsystems are taking the most')
print(' time in suspend/resume.')
print('')
print(' Generates output files in subdirectory: suspend-mmddyy-HHMMSS')
print(' HTML output: <hostname>_<mode>.html')
print(' raw dmesg output: <hostname>_<mode>_dmesg.txt')
print(' raw ftrace output: <hostname>_<mode>_ftrace.txt')
print('')
print('Options:')
print(' [general]')
print(' -h Print this help text')
print(' -v Print the current tool version')
print(' -verbose Print extra information during execution and analysis')
print(' -status Test to see if the system is enabled to run this tool')
print(' -modes List available suspend modes')
print(' -m mode Mode to initiate for suspend %s (default: %s)') % (modes, sysvals.suspendmode)
print(' -rtcwake t Use rtcwake to autoresume after <t> seconds (default: disabled)')
print(' [advanced]')
print(' -f Use ftrace to create device callgraphs (default: disabled)')
print(' -filter "d1 d2 ..." Filter out all but this list of dev names')
print(' -x2 Run two suspend/resumes back to back (default: disabled)')
print(' -x2delay t Minimum millisecond delay <t> between the two test runs (default: 0 ms)')
print(' -postres t Time after resume completion to wait for post-resume events (default: 0 S)')
print(' -multi n d Execute <n> consecutive tests at <d> seconds intervals. The outputs will')
print(' be created in a new subdirectory with a summary page.')
print(' [utilities]')
print(' -fpdt Print out the contents of the ACPI Firmware Performance Data Table')
print(' -usbtopo Print out the current USB topology with power info')
print(' -usbauto Enable autosuspend for all connected USB devices')
print(' [android testing]')
print(' -adb binary Use the given adb binary to run the test on an android device.')
print(' The device should already be connected and with root access.')
print(' Commands will be executed on the device using "adb shell"')
print(' [re-analyze data from previous runs]')
print(' -ftrace ftracefile Create HTML output using ftrace input')
print(' -dmesg dmesgfile Create HTML output using dmesg (not needed for kernel >= 3.15)')
print(' -summary directory Create a summary of all test in this dir')
print('')
return True
# ----------------- MAIN --------------------
# exec start (skipped if script is loaded as library)
if __name__ == '__main__':
cmd = ''
cmdarg = ''
multitest = {'run': False, 'count': 0, 'delay': 0}
# loop through the command line arguments
args = iter(sys.argv[1:])
for arg in args:
if(arg == '-m'):
try:
val = args.next()
except:
doError('No mode supplied', True)
sysvals.suspendmode = val
elif(arg == '-adb'):
try:
val = args.next()
except:
doError('No adb binary supplied', True)
if(not os.path.exists(val)):
doError('file doesnt exist: %s' % val, False)
if(not os.access(val, os.X_OK)):
doError('file isnt executable: %s' % val, False)
try:
check = os.popen(val+' version').read().strip()
except:
doError('adb version failed to execute', False)
if(not re.match('Android Debug Bridge .*', check)):
doError('adb version failed to execute', False)
sysvals.adb = val
sysvals.android = True
elif(arg == '-x2'):
if(sysvals.postresumetime > 0):
doError('-x2 is not compatible with -postres', False)
sysvals.execcount = 2
elif(arg == '-x2delay'):
sysvals.x2delay = getArgInt('-x2delay', args, 0, 60000)
elif(arg == '-postres'):
if(sysvals.execcount != 1):
doError('-x2 is not compatible with -postres', False)
sysvals.postresumetime = getArgInt('-postres', args, 0, 3600)
elif(arg == '-f'):
sysvals.usecallgraph = True
elif(arg == '-modes'):
cmd = 'modes'
elif(arg == '-fpdt'):
cmd = 'fpdt'
elif(arg == '-usbtopo'):
cmd = 'usbtopo'
elif(arg == '-usbauto'):
cmd = 'usbauto'
elif(arg == '-status'):
cmd = 'status'
elif(arg == '-verbose'):
sysvals.verbose = True
elif(arg == '-v'):
print("Version %.1f" % sysvals.version)
sys.exit()
elif(arg == '-rtcwake'):
sysvals.rtcwake = True
sysvals.rtcwaketime = getArgInt('-rtcwake', args, 0, 3600)
elif(arg == '-multi'):
multitest['run'] = True
multitest['count'] = getArgInt('-multi n (exec count)', args, 2, 1000000)
multitest['delay'] = getArgInt('-multi d (delay between tests)', args, 0, 3600)
elif(arg == '-dmesg'):
try:
val = args.next()
except:
doError('No dmesg file supplied', True)
sysvals.notestrun = True
sysvals.dmesgfile = val
if(os.path.exists(sysvals.dmesgfile) == False):
doError('%s doesnt exist' % sysvals.dmesgfile, False)
elif(arg == '-ftrace'):
try:
val = args.next()
except:
doError('No ftrace file supplied', True)
sysvals.notestrun = True
sysvals.usecallgraph = True
sysvals.ftracefile = val
if(os.path.exists(sysvals.ftracefile) == False):
doError('%s doesnt exist' % sysvals.ftracefile, False)
elif(arg == '-summary'):
try:
val = args.next()
except:
doError('No directory supplied', True)
cmd = 'summary'
cmdarg = val
sysvals.notestrun = True
if(os.path.isdir(val) == False):
doError('%s isnt accesible' % val, False)
elif(arg == '-filter'):
try:
val = args.next()
except:
doError('No devnames supplied', True)
sysvals.setDeviceFilter(val)
elif(arg == '-h'):
printHelp()
sys.exit()
else:
doError('Invalid argument: '+arg, True)
# just run a utility command and exit
if(cmd != ''):
if(cmd == 'status'):
statusCheck()
elif(cmd == 'fpdt'):
if(sysvals.android):
doError('cannot read FPDT on android device', False)
getFPDT(True)
elif(cmd == 'usbtopo'):
if(sysvals.android):
doError('cannot read USB topology '+\
'on an android device', False)
detectUSB(True)
elif(cmd == 'modes'):
modes = getModes()
print modes
elif(cmd == 'usbauto'):
setUSBDevicesAuto()
elif(cmd == 'summary'):
print("Generating a summary of folder \"%s\"" % cmdarg)
runSummary(cmdarg, True)
sys.exit()
# run test on android device
if(sysvals.android):
if(sysvals.usecallgraph):
doError('ftrace (-f) is not yet supported '+\
'in the android kernel', False)
if(sysvals.notestrun):
doError('cannot analyze test files on the '+\
'android device', False)
# if instructed, re-analyze existing data files
if(sysvals.notestrun):
rerunTest()
sys.exit()
# verify that we can run a test
if(not statusCheck()):
print('Check FAILED, aborting the test run!')
sys.exit()
if multitest['run']:
# run multiple tests in a separte subdirectory
s = 'x%d' % multitest['count']
subdir = datetime.now().strftime('suspend-'+s+'-%m%d%y-%H%M%S')
os.mkdir(subdir)
for i in range(multitest['count']):
if(i != 0):
print('Waiting %d seconds...' % (multitest['delay']))
time.sleep(multitest['delay'])
print('TEST (%d/%d) START' % (i+1, multitest['count']))
runTest(subdir)
print('TEST (%d/%d) COMPLETE' % (i+1, multitest['count']))
runSummary(subdir, False)
else:
# run the test in the current directory
runTest(".")
| gpl-2.0 |
Designist/sympy | sympy/plotting/intervalmath/interval_arithmetic.py | 98 | 16450 | """
Interval Arithmetic for plotting.
This module does not implement interval arithmetic accurately and
hence cannot be used for purposes other than plotting. If you want
to use interval arithmetic, use mpmath's interval arithmetic.
The module implements interval arithmetic using numpy and
python floating points. The rounding up and down is not handled
and hence this is not an accurate implementation of interval
arithmetic.
The module uses numpy for speed which cannot be achieved with mpmath.
"""
# Q: Why use numpy? Why not simply use mpmath's interval arithmetic?
# A: mpmath's interval arithmetic simulates a floating point unit
# and hence is slow, while numpy evaluations are orders of magnitude
# faster.
# Q: Why create a separate class for intervals? Why not use sympy's
# Interval Sets?
# A: The functionalities that will be required for plotting is quite
# different from what Interval Sets implement.
# Q: Why is rounding up and down according to IEEE754 not handled?
# A: It is not possible to do it in both numpy and python. An external
# library has to used, which defeats the whole purpose i.e., speed. Also
# rounding is handled for very few functions in those libraries.
# Q Will my plots be affected?
# A It will not affect most of the plots. The interval arithmetic
# module based suffers the same problems as that of floating point
# arithmetic.
from __future__ import print_function, division
from sympy.simplify.simplify import nsimplify
class interval(object):
""" Represents an interval containing floating points as start and
end of the interval
The is_valid variable tracks whether the interval obtained as the
result of the function is in the domain and is continuous.
- True: Represents the interval result of a function is continuous and
in the domain of the function.
- False: The interval argument of the function was not in the domain of
the function, hence the is_valid of the result interval is False
- None: The function was not continuous over the interval or
the function's argument interval is partly in the domain of the
function
The comparison of two intervals returns a tuple of two 3-valued logic
values.
The first value determines the comparison as follows:
- True: If the comparison is True throughout the intervals.
- False: If the comparison is False throughout the intervals.
- None: If the comparison is True for some part of the intervals.
The second value is determined as follows:
- True: If both the intervals in comparison are valid.
- False: If at least one of the intervals is False, else
- None
"""
def __init__(self, *args, **kwargs):
self.is_valid = kwargs.pop('is_valid', True)
if len(args) == 1:
if isinstance(args[0], interval):
self.start, self.end = args[0].start, args[0].end
else:
self.start = float(args[0])
self.end = float(args[0])
elif len(args) == 2:
if args[0] < args[1]:
self.start = float(args[0])
self.end = float(args[1])
else:
self.start = float(args[1])
self.end = float(args[0])
else:
raise ValueError("interval takes a maximum of two float values "
"as arguments")
@property
def mid(self):
return (self.start + self.end) / 2.0
@property
def width(self):
return self.end - self.start
def __repr__(self):
return "interval(%f, %f)" % (self.start, self.end)
def __str__(self):
return "[%f, %f]" % (self.start, self.end)
def __lt__(self, other):
if isinstance(other, (int, float)):
if self.end < other:
return (True, self.is_valid)
elif self.start > other:
return (False, self.is_valid)
else:
return (None, self.is_valid)
elif isinstance(other, interval):
if self.is_valid is False or other.is_valid is False:
valid = False
elif self.is_valid is None or other.is_valid is None:
valid = None
else:
valid = True
if self.end < other. start:
return (True, valid)
if self.start > other.end:
return (False, valid)
return (None, valid)
else:
return NotImplemented
def __gt__(self, other):
if isinstance(other, (int, float)):
if self.start > other:
return (True, self.is_valid)
elif self.end < other:
return (False, self.is_valid)
else:
return (None, self.is_valid)
elif isinstance(other, interval):
return other.__lt__(self)
else:
return NotImplemented
def __eq__(self, other):
if isinstance(other, (int, float)):
if self.start == other and self.end == other:
return (True, self.is_valid)
if other in self:
return (None, self.is_valid)
else:
return (False, self.is_valid)
if isinstance(other, interval):
if self.is_valid is False or other.is_valid is False:
valid = False
elif self.is_valid is None or other.is_valid is None:
valid = None
else:
valid = True
if self.start == other.start and self.end == other.end:
return (True, valid)
elif self.__lt__(other)[0] is not None:
return (False, valid)
else:
return (None, valid)
else:
return NotImplemented
def __ne__(self, other):
if isinstance(other, (int, float)):
if self.start == other and self.end == other:
return (False, self.is_valid)
if other in self:
return (None, self.is_valid)
else:
return (True, self.is_valid)
if isinstance(other, interval):
if self.is_valid is False or other.is_valid is False:
valid = False
elif self.is_valid is None or other.is_valid is None:
valid = None
else:
valid = True
if self.start == other.start and self.end == other.end:
return (False, valid)
if not self.__lt__(other)[0] is None:
return (True, valid)
return (None, valid)
else:
return NotImplemented
def __le__(self, other):
if isinstance(other, (int, float)):
if self.end <= other:
return (True, self.is_valid)
if self.start > other:
return (False, self.is_valid)
else:
return (None, self.is_valid)
if isinstance(other, interval):
if self.is_valid is False or other.is_valid is False:
valid = False
elif self.is_valid is None or other.is_valid is None:
valid = None
else:
valid = True
if self.end <= other.start:
return (True, valid)
if self.start > other.end:
return (False, valid)
return (None, valid)
else:
return NotImplemented
def __ge__(self, other):
if isinstance(other, (int, float)):
if self.start >= other:
return (True, self.is_valid)
elif self.end < other:
return (False, self.is_valid)
else:
return (None, self.is_valid)
elif isinstance(other, interval):
return other.__le__(self)
def __add__(self, other):
if isinstance(other, (int, float)):
if self.is_valid:
return interval(self.start + other, self.end + other)
else:
start = self.start + other
end = self.end + other
return interval(start, end, is_valid=self.is_valid)
elif isinstance(other, interval):
start = self.start + other.start
end = self.end + other.end
if self.is_valid and other.is_valid:
return interval(start, end)
elif self.is_valid is False or other.is_valid is False:
return interval(start, end, is_valid=False)
else:
return interval(start, end, is_valid=None)
else:
return NotImplemented
__radd__ = __add__
def __sub__(self, other):
if isinstance(other, (int, float)):
start = self.start - other
end = self.end - other
return interval(start, end, is_valid=self.is_valid)
elif isinstance(other, interval):
start = self.start - other.end
end = self.end - other.start
if self.is_valid and other.is_valid:
return interval(self.start - other.end, self.end - other.start)
elif self.is_valid is False or other.is_valid is False:
return interval(start, end, is_valid=False)
else:
return interval(start, end, is_valid=None)
else:
return NotImplemented
def __rsub__(self, other):
if isinstance(other, (int, float)):
start = other - self.end
end = other - self.start
return interval(start, end, is_valid=self.is_valid)
elif isinstance(other, interval):
return other.__sub__(self)
else:
return NotImplemented
def __neg__(self):
if self.is_valid:
return interval(-self.end, -self.start)
else:
return interval(-self.end, -self.start, is_valid=self.is_valid)
def __mul__(self, other):
if isinstance(other, interval):
if self.is_valid is False or other.is_valid is False:
return interval(-float('inf'), float('inf'), is_valid=False)
elif self.is_valid is None or other.is_valid is None:
return interval(-float('inf'), float('inf'), is_valid=None)
else:
inters = []
inters.append(self.start * other.start)
inters.append(self.end * other.start)
inters.append(self.start * other.end)
inters.append(self.end * other.end)
start = min(inters)
end = max(inters)
return interval(start, end)
elif isinstance(other, (int, float)):
return interval(self.start*other, self.end*other, is_valid=self.is_valid)
else:
return NotImplemented
__rmul__ = __mul__
def __contains__(self, other):
if isinstance(other, (int, float)):
return self.start <= other and self.end >= other
else:
return self.start <= other.start and other.end <= self.end
def __rdiv__(self, other):
if isinstance(other, (int, float)):
other = interval(other)
return other.__div__(self)
elif isinstance(other, interval):
return other.__div__(self)
else:
return NotImplemented
def __div__(self, other):
# Both None and False are handled
if not self.is_valid:
# Don't divide as the value is not valid
return interval(-float('inf'), float('inf'), is_valid=self.is_valid)
if isinstance(other, (int, float)):
if other == 0:
# Divide by zero encountered. valid nowhere
return interval(-float('inf'), float('inf'), is_valid=False)
else:
return interval(self.start / other, self.end / other)
elif isinstance(other, interval):
if other.is_valid is False or self.is_valid is False:
return interval(-float('inf'), float('inf'), is_valid=False)
elif other.is_valid is None or self.is_valid is None:
return interval(-float('inf'), float('inf'), is_valid=None)
else:
# denominator contains both signs, i.e. being divided by zero
# return the whole real line with is_valid = None
if 0 in other:
return interval(-float('inf'), float('inf'), is_valid=None)
# denominator negative
this = self
if other.end < 0:
this = -this
other = -other
# denominator positive
inters = []
inters.append(this.start / other.start)
inters.append(this.end / other.start)
inters.append(this.start / other.end)
inters.append(this.end / other.end)
start = max(inters)
end = min(inters)
return interval(start, end)
else:
return NotImplemented
__truediv__ = __div__
__rtruediv__ = __rdiv__
def __pow__(self, other):
# Implements only power to an integer.
from .lib_interval import exp, log
if not self.is_valid:
return self
if isinstance(other, interval):
return exp(other * log(self))
elif isinstance(other, (float, int)):
if other < 0:
return 1 / self.__pow__(abs(other))
else:
if int(other) == other:
return _pow_int(self, other)
else:
return _pow_float(self, other)
else:
return NotImplemented
def __rpow__(self, other):
if isinstance(other, (float, int)):
if not self.is_valid:
#Don't do anything
return self
elif other < 0:
if self.width > 0:
return interval(-float('inf'), float('inf'), is_valid=False)
else:
power_rational = nsimplify(self.start)
num, denom = power_rational.as_numer_denom()
if denom % 2 == 0:
return interval(-float('inf'), float('inf'),
is_valid=False)
else:
start = -abs(other)**self.start
end = start
return interval(start, end)
else:
return interval(other**self.start, other**self.end)
elif isinstance(other, interval):
return other.__pow__(self)
else:
return NotImplemented
def __hash__(self):
return hash((self.is_valid, self.start, self.end))
def _pow_float(inter, power):
"""Evaluates an interval raised to a floating point."""
power_rational = nsimplify(power)
num, denom = power_rational.as_numer_denom()
if num % 2 == 0:
start = abs(inter.start)**power
end = abs(inter.end)**power
if start < 0:
ret = interval(0, max(start, end))
else:
ret = interval(start, end)
return ret
elif denom % 2 == 0:
if inter.end < 0:
return interval(-float('inf'), float('inf'), is_valid=False)
elif inter.start < 0:
return interval(0, inter.end**power, is_valid=None)
else:
return interval(inter.start**power, inter.end**power)
else:
if inter.start < 0:
start = -abs(inter.start)**power
else:
start = inter.start**power
if inter.end < 0:
end = -abs(inter.end)**power
else:
end = inter.end**power
return interval(start, end, is_valid=inter.is_valid)
def _pow_int(inter, power):
"""Evaluates an interval raised to an integer power"""
power = int(power)
if power & 1:
return interval(inter.start**power, inter.end**power)
else:
if inter.start < 0 and inter.end > 0:
start = 0
end = max(inter.start**power, inter.end**power)
return interval(start, end)
else:
return interval(inter.start**power, inter.end**power)
| bsd-3-clause |
freeJim/monserver | examples/python/mongrel2/request.py | 72 | 1140 | try:
import json
except:
import simplejson as json
from mongrel2 import tnetstrings
class Request(object):
def __init__(self, sender, conn_id, path, headers, body):
self.sender = sender
self.path = path
self.conn_id = conn_id
self.headers = headers
self.body = body
if self.headers['METHOD'] == 'JSON':
self.data = json.loads(body)
else:
self.data = {}
@staticmethod
def parse(msg):
sender, conn_id, path, rest = msg.split(' ', 3)
headers, rest = tnetstrings.parse(rest)
body, _ = tnetstrings.parse(rest)
if type(headers) is str:
headers = json.loads(headers)
return Request(sender, conn_id, path, headers, body)
def is_disconnect(self):
if self.headers.get('METHOD') == 'JSON':
return self.data['type'] == 'disconnect'
def should_close(self):
if self.headers.get('connection') == 'close':
return True
elif self.headers.get('VERSION') == 'HTTP/1.0':
return True
else:
return False
| bsd-3-clause |
oppia/oppia-ml | core/domain/remote_access_services.py | 1 | 4226 | # coding: utf-8
#
# Copyright 2017 The Oppia Authors. All Rights Reserved.
#
# 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.
"""This module provides interface to communicate with Oppia remotely."""
import base64
import hashlib
import hmac
import json
import requests
from core.domain.proto import training_job_response_payload_pb2
from core.platform import platform_services
import utils
import vmconf
metadata_services = platform_services.Registry.import_metadata_services()
def _get_url():
if vmconf.DEV_MODE:
return vmconf.DEFAULT_COMMUNICATION_URL
return vmconf.SERVER_COMMUNICATION_URL
def _get_port():
if vmconf.DEV_MODE:
return vmconf.DEFAULT_COMMUNICATION_PORT
return vmconf.SERVER_COMMUNICATION_PORT
def _get_vm_id():
if vmconf.DEV_MODE:
return vmconf.DEFAULT_VM_ID
# Get VMID dynamically from metadata. HMAC module does not
# support unicode string. Hence we need to cast them to str.
return str(metadata_services.get_metadata_param(
vmconf.METADATA_VM_ID_PARAM_NAME))
def _get_shared_secret():
if vmconf.DEV_MODE:
return vmconf.DEFAULT_VM_SHARED_SECRET
# Get shared secret dynamically from metadata. HMAC module does not
# support unicode string. Hence we need to cast them to str.
return str(metadata_services.get_metadata_param(
vmconf.METADATA_SHARED_SECRET_PARAM_NAME))
def generate_signature(message, vm_id):
"""Generates digital signature for given message combined with vm_id.
Args:
message: bytes. Message string.
vm_id: str. ID of the VM that trained the job.
Returns:
str. The digital signature generated from request data.
"""
encoded_vm_id = vm_id.encode(encoding='utf-8')
msg = b'%s|%s' % (base64.b64encode(message), encoded_vm_id)
key = _get_shared_secret().encode(encoding='utf-8')
# Generate signature and return it.
return hmac.new(key, msg, digestmod=hashlib.sha256).hexdigest()
def fetch_next_job_request():
"""Returns the next job request to be processed.
Returns:
dict. A dict retrieved remotely from database containing
job request data.
"""
request_url = "%s:%s/%s" % (
_get_url(), _get_port(), vmconf.FETCH_NEXT_JOB_REQUEST_HANDLER)
payload = {
'vm_id': _get_vm_id().encode(encoding='utf-8'),
'message': _get_vm_id().encode(encoding='utf-8'),
}
signature = generate_signature(payload['message'], payload['vm_id'])
payload['signature'] = signature
data = {
'payload': json.dumps(payload)
}
response = requests.post(request_url, data=data)
return utils.parse_data_received_from_server(response.text)
def store_trained_classifier_model(job_result):
"""Stores the result of processed job request.
Args:
job_result: TrainingJobResult. Domain object containing result of
training of classifier along with job_id and algorithm_id.
Returns:
int. Status code of the response.
"""
job_result.validate()
payload = training_job_response_payload_pb2.TrainingJobResponsePayload()
payload.job_result.CopyFrom(job_result.to_proto())
payload.vm_id = _get_vm_id().encode(encoding='utf-8')
message = payload.job_result.SerializeToString().encode(encoding='utf-8')
signature = generate_signature(message, payload.vm_id)
payload.signature = signature
data = payload.SerializeToString()
request_url = "%s:%s/%s" % (
_get_url(), _get_port(), vmconf.STORE_TRAINED_CLASSIFIER_MODEL_HANDLER)
response = requests.post(
request_url, data=data,
headers={'Content-Type': 'application/octet-stream'})
return response.status_code
| apache-2.0 |
Bitergia/redhat-rdo-dashboard | templates/apply_template.py | 35 | 1833 | #! /usr/bin/env python
# Copyright (C) 2014 Bitergia
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import argparse
def get_arguments():
parser = argparse.ArgumentParser(description='Parse HTML generator arguments')
parser.add_argument('--template', dest='template_file', help='Template file name')
parser.add_argument('--content', dest='content_file', help='Content file name')
args = parser.parse_args()
#print args.accumulate(args.integers)
return args
def include_webstats(html_body):
"""
Replace string "REPLACE_WEBSTATS" in html_body with JS code from file
webstats.tmpl if present. If not, it just include and empty string
"""
text = "REPLACE_WEBSTATS"
try:
fd = open("webstats.tmpl","r")
jscode = fd.read()
fd.close()
except:
jscode = ""
html_body = html_body.replace(text, jscode)
return html_body
if __name__ == "__main__":
text = "REPLACE_HERE"
arg = get_arguments()
fd = open(arg.template_file, "r")
template = fd.read()
fd.close()
fd2 = open(arg.content_file, "r")
body = fd2.read()
fd2.close()
template = include_webstats(template)
template = template.replace(text, body)
print template
| gpl-3.0 |
Lab603/PicEncyclopedias | jni-build/jni/include/tensorflow/contrib/distributions/python/ops/mvn.py | 3 | 30904 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
"""Multivariate Normal distribution classes."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
from tensorflow.contrib.distributions.python.ops import distribution
from tensorflow.contrib.distributions.python.ops import kullback_leibler
from tensorflow.contrib.distributions.python.ops import operator_pd_cholesky
from tensorflow.contrib.distributions.python.ops import operator_pd_diag
from tensorflow.contrib.distributions.python.ops import operator_pd_full
from tensorflow.contrib.distributions.python.ops import operator_pd_vdvt_update
from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
from tensorflow.python.framework import tensor_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import check_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import random_ops
__all__ = [
"MultivariateNormalDiag",
"MultivariateNormalCholesky",
"MultivariateNormalFull",
"MultivariateNormalDiagPlusVDVT",
]
class MultivariateNormalOperatorPD(distribution.Distribution):
"""The multivariate normal distribution on `R^k`.
This distribution is defined by a 1-D mean `mu` and an instance of
`OperatorPDBase`, which provides access to a symmetric positive definite
operator, which defines the covariance.
#### Mathematical details
With `C` the covariance matrix represented by the operator, the PDF of this
distribution is:
```
f(x) = (2 pi)^(-k/2) |det(C)|^(-1/2) exp(-1/2 (x - mu)^T C^{-1} (x - mu))
```
#### Examples
A single multi-variate Gaussian distribution is defined by a vector of means
of length `k`, and a covariance matrix of shape `k x k`.
Extra leading dimensions, if provided, allow for batches.
```python
# Initialize a single 3-variate Gaussian.
mu = [1, 2, 3]
chol = [[1, 0, 0.], [1, 3, 0], [1, 2, 3]]
cov = tf.contrib.distributions.OperatorPDCholesky(chol)
dist = tf.contrib.distributions.MultivariateNormalOperatorPD(mu, cov)
# Evaluate this on an observation in R^3, returning a scalar.
dist.pdf([-1, 0, 1.])
# Initialize a batch of two 3-variate Gaussians.
mu = [[1, 2, 3], [11, 22, 33.]]
chol = ... # shape 2 x 3 x 3, lower triangular, positive diagonal.
cov = tf.contrib.distributions.OperatorPDCholesky(chol)
dist = tf.contrib.distributions.MultivariateNormalOperatorPD(mu, cov)
# Evaluate this on a two observations, each in R^3, returning a length two
# tensor.
x = [[-1, 0, 1], [-11, 0, 11.]] # Shape 2 x 3.
dist.pdf(x)
```
"""
def __init__(self,
mu,
cov,
validate_args=True,
allow_nan_stats=False,
name="MultivariateNormalCov"):
"""Multivariate Normal distributions on `R^k`.
User must provide means `mu`, and an instance of `OperatorPDBase`, `cov`,
which determines the covariance.
Args:
mu: Floating point tensor with shape `[N1,...,Nb, k]`, `b >= 0`.
cov: Instance of `OperatorPDBase` with same `dtype` as `mu` and shape
`[N1,...,Nb, k, k]`.
validate_args: Whether to validate input with asserts. If `validate_args`
is `False`, and the inputs are invalid, correct behavior is not
guaranteed.
allow_nan_stats: `Boolean`, default `False`. If `False`, raise an
exception if a statistic (e.g. mean/mode/etc...) is undefined for any
batch member If `True`, batch members with valid parameters leading to
undefined statistics will return NaN for this statistic.
name: The name to give Ops created by the initializer.
Raises:
TypeError: If `mu` and `cov` are different dtypes.
"""
self._allow_nan_stats = allow_nan_stats
self._validate_args = validate_args
with ops.name_scope(name):
with ops.op_scope([mu] + cov.inputs, "init"):
self._cov = cov
self._mu = self._check_mu(mu)
self._name = name
def _check_mu(self, mu):
"""Return `mu` after validity checks and possibly with assertations."""
mu = ops.convert_to_tensor(mu)
cov = self._cov
if mu.dtype != cov.dtype:
raise TypeError(
"mu and cov must have the same dtype. Found mu.dtype = %s, "
"cov.dtype = %s"
% (mu.dtype, cov.dtype))
# Try to validate with static checks.
mu_shape = mu.get_shape()
cov_shape = cov.get_shape()
if mu_shape.is_fully_defined() and cov_shape.is_fully_defined():
if mu_shape != cov_shape[:-1]:
raise ValueError(
"mu.shape and cov.shape[:-1] should match. Found: mu.shape=%s, "
"cov.shape=%s" % (mu_shape, cov_shape))
else:
return mu
# Static checks could not be run, so possibly do dynamic checks.
if not self.validate_args:
return mu
else:
assert_same_rank = check_ops.assert_equal(
array_ops.rank(mu) + 1,
cov.rank(),
data=["mu should have rank 1 less than cov. Found: rank(mu) = ",
array_ops.rank(mu), " rank(cov) = ", cov.rank()],
)
with ops.control_dependencies([assert_same_rank]):
assert_same_shape = check_ops.assert_equal(
array_ops.shape(mu),
cov.vector_shape(),
data=["mu.shape and cov.shape[:-1] should match. "
"Found: shape(mu) = "
, array_ops.shape(mu), " shape(cov) = ", cov.shape()],
)
return control_flow_ops.with_dependencies([assert_same_shape], mu)
@property
def validate_args(self):
"""`Boolean` describing behavior on invalid input."""
return self._validate_args
@property
def allow_nan_stats(self):
"""`Boolean` describing behavior when stats are undefined."""
return self._allow_nan_stats
@property
def dtype(self):
return self._mu.dtype
def get_event_shape(self):
"""`TensorShape` available at graph construction time."""
# Recall _check_mu ensures mu and self._cov have same batch shape.
return self._cov.get_shape()[-1:]
def event_shape(self, name="event_shape"):
"""Shape of a sample from a single distribution as a 1-D int32 `Tensor`."""
# Recall _check_mu ensures mu and self._cov have same batch shape.
with ops.name_scope(self.name):
with ops.op_scope(self._cov.inputs, name):
return array_ops.pack([self._cov.vector_space_dimension()])
def batch_shape(self, name="batch_shape"):
"""Batch dimensions of this instance as a 1-D int32 `Tensor`."""
# Recall _check_mu ensures mu and self._cov have same batch shape.
with ops.name_scope(self.name):
with ops.op_scope(self._cov.inputs, name):
return self._cov.batch_shape()
def get_batch_shape(self):
"""`TensorShape` available at graph construction time."""
# Recall _check_mu ensures mu and self._cov have same batch shape.
return self._cov.get_batch_shape()
@property
def mu(self):
return self._mu
@property
def sigma(self):
"""Dense (batch) covariance matrix, if available."""
with ops.name_scope(self.name):
return self._cov.to_dense()
def mean(self, name="mean"):
"""Mean of each batch member."""
with ops.name_scope(self.name):
with ops.op_scope([self._mu], name):
return array_ops.identity(self._mu)
def mode(self, name="mode"):
"""Mode of each batch member."""
with ops.name_scope(self.name):
with ops.op_scope([self._mu], name):
return array_ops.identity(self._mu)
def variance(self, name="variance"):
"""Variance of each batch member."""
with ops.name_scope(self.name):
return self.sigma
def log_sigma_det(self, name="log_sigma_det"):
"""Log of determinant of covariance matrix."""
with ops.name_scope(self.name):
with ops.op_scope(self._cov.inputs, name):
return self._cov.log_det()
def sigma_det(self, name="sigma_det"):
"""Determinant of covariance matrix."""
with ops.name_scope(self.name):
with ops.op_scope(self._cov.inputs, name):
return math_ops.exp(self._cov.log_det())
def log_prob(self, x, name="log_prob"):
"""Log prob of observations `x` given these Multivariate Normals.
`x` is a batch vector with compatible shape if `x` is a `Tensor` whose
shape can be broadcast up to either:
````
self.batch_shape + self.event_shape
OR
[M1,...,Mm] + self.batch_shape + self.event_shape
```
Args:
x: Compatible batch vector with same `dtype` as this distribution.
name: The name to give this op.
Returns:
log_prob: tensor of dtype `dtype`, the log-PDFs of `x`.
"""
# Q: Why are shape requirements as stated above?
# A: The compatible shapes are precisely the ones that will broadcast to
# a shape compatible with self._cov.
# See Operator base class for notes about shapes compatible with self._cov.
with ops.name_scope(self.name):
with ops.op_scope([self._mu, x] + self._cov.inputs, name):
x = ops.convert_to_tensor(x)
contrib_tensor_util.assert_same_float_dtype((self._mu, x))
# _check_mu asserts that self.mu has same batch shape as self.cov.
# so batch shape of self.mu = that of self._cov and self, and the
# batch shape of x_centered is a broadcast version of these. If this
# broadcast results in a shape like
# [M1,...,Mm] + self.batch_shape + self.event_shape
# OR
# self.batch_shape + self.event_shape
# then subsequent operator calls are guaranteed to work.
x_centered = x - self.mu
# Compute the term x^{-1} sigma^{-1} x which appears in the exponent of
# the pdf.
x_whitened_norm = self._cov.inv_quadratic_form_on_vectors(x_centered)
log_sigma_det = self.log_sigma_det()
log_two_pi = constant_op.constant(
math.log(2 * math.pi), dtype=self.dtype)
k = math_ops.cast(self._cov.vector_space_dimension(), self.dtype)
log_prob_value = -(log_sigma_det + k * log_two_pi + x_whitened_norm) / 2
output_static_shape = x_centered.get_shape()[:-1]
log_prob_value.set_shape(output_static_shape)
return log_prob_value
def prob(self, x, name="prob"):
"""The PDF of observations `x` under these Multivariate Normals.
`x` is a batch vector with compatible shape if `x` is a `Tensor` whose
shape can be broadcast up to either:
````
self.batch_shape + self.event_shape
OR
[M1,...,Mm] + self.batch_shape + self.event_shape
```
Args:
x: Compatible batch vector with same `dtype` as this distribution.
name: The name to give this op.
Returns:
prob: tensor of dtype `dtype`, the prob values of `x`.
"""
with ops.name_scope(self.name):
with ops.op_scope([self._mu, x] + self._cov.inputs, name):
return math_ops.exp(self.log_prob(x))
def entropy(self, name="entropy"):
"""The entropies of these Multivariate Normals.
Args:
name: The name to give this op.
Returns:
entropy: tensor of dtype `dtype`, the entropies.
"""
with ops.name_scope(self.name):
with ops.op_scope([self._mu] + self._cov.inputs, name):
log_sigma_det = self.log_sigma_det()
one_plus_log_two_pi = constant_op.constant(1 + math.log(2 * math.pi),
dtype=self.dtype)
# Use broadcasting rules to calculate the full broadcast sigma.
k = math_ops.cast(self._cov.vector_space_dimension(), dtype=self.dtype)
entropy_value = (k * one_plus_log_two_pi + log_sigma_det) / 2
entropy_value.set_shape(log_sigma_det.get_shape())
return entropy_value
def sample_n(self, n, seed=None, name="sample_n"):
"""Sample `n` observations from the Multivariate Normal Distributions.
Args:
n: `Scalar`, type int32, the number of observations to sample.
seed: Python integer, the random seed.
name: The name to give this op.
Returns:
samples: `[n, ...]`, a `Tensor` of `n` samples for each
of the distributions determined by broadcasting the hyperparameters.
"""
with ops.name_scope(self.name):
with ops.op_scope([self._mu, n] + self._cov.inputs, name):
# Recall _check_mu ensures mu and self._cov have same batch shape.
broadcast_shape = self.mu.get_shape()
n = ops.convert_to_tensor(n)
shape = array_ops.concat(0, [self._cov.vector_shape(), [n]])
white_samples = random_ops.random_normal(shape=shape,
mean=0,
stddev=1,
dtype=self.dtype,
seed=seed)
correlated_samples = self._cov.sqrt_matmul(white_samples)
# Move the last dimension to the front
perm = array_ops.concat(0, (
array_ops.pack([array_ops.rank(correlated_samples) - 1]),
math_ops.range(0, array_ops.rank(correlated_samples) - 1)))
# TODO(ebrevdo): Once we get a proper tensor contraction op,
# perform the inner product using that instead of batch_matmul
# and this slow transpose can go away!
correlated_samples = array_ops.transpose(correlated_samples, perm)
samples = correlated_samples + self.mu
# Provide some hints to shape inference
n_val = tensor_util.constant_value(n)
final_shape = tensor_shape.vector(n_val).concatenate(broadcast_shape)
samples.set_shape(final_shape)
return samples
@property
def is_reparameterized(self):
return True
@property
def name(self):
return self._name
@property
def is_continuous(self):
return True
class MultivariateNormalDiag(MultivariateNormalOperatorPD):
"""The multivariate normal distribution on `R^k`.
This distribution is defined by a 1-D mean `mu` and a 1-D diagonal
`diag_stdev`, representing the standard deviations. This distribution
assumes the random variables, `(X_1,...,X_k)` are independent, thus no
non-diagonal terms of the covariance matrix are needed.
This allows for `O(k)` pdf evaluation, sampling, and storage.
#### Mathematical details
The PDF of this distribution is defined in terms of the diagonal covariance
determined by `diag_stdev`: `C_{ii} = diag_stdev[i]**2`.
```
f(x) = (2 pi)^(-k/2) |det(C)|^(-1/2) exp(-1/2 (x - mu)^T C^{-1} (x - mu))
```
#### Examples
A single multi-variate Gaussian distribution is defined by a vector of means
of length `k`, and the square roots of the (independent) random variables.
Extra leading dimensions, if provided, allow for batches.
```python
# Initialize a single 3-variate Gaussian with diagonal standard deviation.
mu = [1, 2, 3.]
diag_stdev = [4, 5, 6.]
dist = tf.contrib.distributions.MultivariateNormalDiag(mu, diag_stdev)
# Evaluate this on an observation in R^3, returning a scalar.
dist.pdf([-1, 0, 1])
# Initialize a batch of two 3-variate Gaussians.
mu = [[1, 2, 3], [11, 22, 33]] # shape 2 x 3
diag_stdev = ... # shape 2 x 3, positive.
dist = tf.contrib.distributions.MultivariateNormalDiag(mu, diag_stdev)
# Evaluate this on a two observations, each in R^3, returning a length two
# tensor.
x = [[-1, 0, 1], [-11, 0, 11]] # Shape 2 x 3.
dist.pdf(x)
```
"""
def __init__(
self,
mu,
diag_stdev,
validate_args=True,
allow_nan_stats=False,
name="MultivariateNormalDiag"):
"""Multivariate Normal distributions on `R^k`.
User must provide means `mu` and standard deviations `diag_stdev`.
Each batch member represents a random vector `(X_1,...,X_k)` of independent
random normals.
The mean of `X_i` is `mu[i]`, and the standard deviation is `diag_stdev[i]`.
Args:
mu: Rank `N + 1` floating point tensor with shape `[N1,...,Nb, k]`,
`b >= 0`.
diag_stdev: Rank `N + 1` `Tensor` with same `dtype` and shape as `mu`,
representing the standard deviations. Must be positive.
validate_args: Whether to validate input with asserts. If `validate_args`
is `False`,
and the inputs are invalid, correct behavior is not guaranteed.
allow_nan_stats: `Boolean`, default `False`. If `False`, raise an
exception if a statistic (e.g. mean/mode/etc...) is undefined for any
batch member If `True`, batch members with valid parameters leading to
undefined statistics will return NaN for this statistic.
name: The name to give Ops created by the initializer.
Raises:
TypeError: If `mu` and `diag_stdev` are different dtypes.
"""
cov = operator_pd_diag.OperatorPDSqrtDiag(
diag_stdev, verify_pd=validate_args)
super(MultivariateNormalDiag, self).__init__(
mu, cov, allow_nan_stats=allow_nan_stats, validate_args=validate_args,
name=name)
class MultivariateNormalDiagPlusVDVT(MultivariateNormalOperatorPD):
"""The multivariate normal distribution on `R^k`.
Every batch member of this distribution is defined by a mean and a lightweight
covariance matrix `C`.
#### Mathematical details
The PDF of this distribution in terms of the mean `mu` and covariance `C` is:
```
f(x) = (2 pi)^(-k/2) |det(C)|^(-1/2) exp(-1/2 (x - mu)^T C^{-1} (x - mu))
```
For every batch member, this distribution represents `k` random variables
`(X_1,...,X_k)`, with mean `E[X_i] = mu[i]`, and covariance matrix
`C_{ij} := E[(X_i - mu[i])(X_j - mu[j])]`
The user initializes this class by providing the mean `mu`, and a lightweight
definition of `C`:
```
C = SS^T = SS = (M + V D V^T) (M + V D V^T)
M is diagonal (k x k)
V = is shape (k x r), typically r << k
D = is diagonal (r x r), optional (defaults to identity).
```
This allows for `O(kr + r^3)` pdf evaluation and determinant, and `O(kr)`
sampling and storage (per batch member).
#### Examples
A single multi-variate Gaussian distribution is defined by a vector of means
of length `k`, and square root of the covariance `S = M + V D V^T`. Extra
leading dimensions, if provided, allow for batches.
```python
# Initialize a single 3-variate Gaussian with covariance square root
# S = M + V D V^T, where V D V^T is a matrix-rank 2 update.
mu = [1, 2, 3.]
diag_large = [1.1, 2.2, 3.3]
v = ... # shape 3 x 2
diag_small = [4., 5.]
dist = tf.contrib.distributions.MultivariateNormalDiagPlusVDVT(
mu, diag_large, v, diag_small=diag_small)
# Evaluate this on an observation in R^3, returning a scalar.
dist.pdf([-1, 0, 1])
# Initialize a batch of two 3-variate Gaussians. This time, don't provide
# diag_small. This means S = M + V V^T.
mu = [[1, 2, 3], [11, 22, 33]] # shape 2 x 3
diag_large = ... # shape 2 x 3
v = ... # shape 2 x 3 x 1, a matrix-rank 1 update.
dist = tf.contrib.distributions.MultivariateNormalDiagPlusVDVT(
mu, diag_large, v)
# Evaluate this on a two observations, each in R^3, returning a length two
# tensor.
x = [[-1, 0, 1], [-11, 0, 11]] # Shape 2 x 3.
dist.pdf(x)
```
"""
def __init__(
self,
mu,
diag_large,
v,
diag_small=None,
validate_args=True,
allow_nan_stats=False,
name="MultivariateNormalDiagPlusVDVT"):
"""Multivariate Normal distributions on `R^k`.
For every batch member, this distribution represents `k` random variables
`(X_1,...,X_k)`, with mean `E[X_i] = mu[i]`, and covariance matrix
`C_{ij} := E[(X_i - mu[i])(X_j - mu[j])]`
The user initializes this class by providing the mean `mu`, and a
lightweight definition of `C`:
```
C = SS^T = SS = (M + V D V^T) (M + V D V^T)
M is diagonal (k x k)
V = is shape (k x r), typically r << k
D = is diagonal (r x r), optional (defaults to identity).
```
Args:
mu: Rank `n + 1` floating point tensor with shape `[N1,...,Nn, k]`,
`n >= 0`. The means.
diag_large: Optional rank `n + 1` floating point tensor, shape
`[N1,...,Nn, k]` `n >= 0`. Defines the diagonal matrix `M`.
v: Rank `n + 1` floating point tensor, shape `[N1,...,Nn, k, r]`
`n >= 0`. Defines the matrix `V`.
diag_small: Rank `n + 1` floating point tensor, shape
`[N1,...,Nn, k]` `n >= 0`. Defines the diagonal matrix `D`. Default
is `None`, which means `D` will be the identity matrix.
validate_args: Whether to validate input with asserts. If `validate_args`
is `False`,
and the inputs are invalid, correct behavior is not guaranteed.
allow_nan_stats: `Boolean`, default `False`. If `False`, raise an
exception if a statistic (e.g. mean/mode/etc...) is undefined for any
batch member If `True`, batch members with valid parameters leading to
undefined statistics will return NaN for this statistic.
name: The name to give Ops created by the initializer.
"""
m = operator_pd_diag.OperatorPDDiag(diag_large, verify_pd=validate_args)
cov = operator_pd_vdvt_update.OperatorPDSqrtVDVTUpdate(
m, v, diag=diag_small, verify_pd=validate_args,
verify_shapes=validate_args)
super(MultivariateNormalDiagPlusVDVT, self).__init__(
mu, cov, allow_nan_stats=allow_nan_stats, validate_args=validate_args,
name=name)
class MultivariateNormalCholesky(MultivariateNormalOperatorPD):
"""The multivariate normal distribution on `R^k`.
This distribution is defined by a 1-D mean `mu` and a Cholesky factor `chol`.
Providing the Cholesky factor allows for `O(k^2)` pdf evaluation and sampling,
and requires `O(k^2)` storage.
#### Mathematical details
The Cholesky factor `chol` defines the covariance matrix: `C = chol chol^T`.
The PDF of this distribution is then:
```
f(x) = (2 pi)^(-k/2) |det(C)|^(-1/2) exp(-1/2 (x - mu)^T C^{-1} (x - mu))
```
#### Examples
A single multi-variate Gaussian distribution is defined by a vector of means
of length `k`, and a covariance matrix of shape `k x k`.
Extra leading dimensions, if provided, allow for batches.
```python
# Initialize a single 3-variate Gaussian with diagonal covariance.
# Note, this would be more efficient with MultivariateNormalDiag.
mu = [1, 2, 3.]
chol = [[1, 0, 0], [0, 3, 0], [0, 0, 2]]
dist = tf.contrib.distributions.MultivariateNormalCholesky(mu, chol)
# Evaluate this on an observation in R^3, returning a scalar.
dist.pdf([-1, 0, 1])
# Initialize a batch of two 3-variate Gaussians.
mu = [[1, 2, 3], [11, 22, 33]]
chol = ... # shape 2 x 3 x 3, lower triangular, positive diagonal.
dist = tf.contrib.distributions.MultivariateNormalCholesky(mu, chol)
# Evaluate this on a two observations, each in R^3, returning a length two
# tensor.
x = [[-1, 0, 1], [-11, 0, 11]] # Shape 2 x 3.
dist.pdf(x)
```
Trainable (batch) Choesky matrices can be created with
`tf.contrib.distributions.batch_matrix_diag_transform()`
"""
def __init__(self,
mu,
chol,
validate_args=True,
allow_nan_stats=False,
name="MultivariateNormalCholesky"):
"""Multivariate Normal distributions on `R^k`.
User must provide means `mu` and `chol` which holds the (batch) Cholesky
factors, such that the covariance of each batch member is `chol chol^T`.
Args:
mu: `(N+1)-D` floating point tensor with shape `[N1,...,Nb, k]`,
`b >= 0`.
chol: `(N+2)-D` `Tensor` with same `dtype` as `mu` and shape
`[N1,...,Nb, k, k]`. The upper triangular part is ignored (treated as
though it is zero), and the diagonal must be positive.
validate_args: Whether to validate input with asserts. If `validate_args`
is `False`, and the inputs are invalid, correct behavior is not
guaranteed.
allow_nan_stats: `Boolean`, default `False`. If `False`, raise an
exception if a statistic (e.g. mean/mode/etc...) is undefined for any
batch member If `True`, batch members with valid parameters leading to
undefined statistics will return NaN for this statistic.
name: The name to give Ops created by the initializer.
Raises:
TypeError: If `mu` and `chol` are different dtypes.
"""
cov = operator_pd_cholesky.OperatorPDCholesky(chol, verify_pd=validate_args)
super(MultivariateNormalCholesky, self).__init__(
mu,
cov,
allow_nan_stats=allow_nan_stats,
validate_args=validate_args,
name=name)
class MultivariateNormalFull(MultivariateNormalOperatorPD):
"""The multivariate normal distribution on `R^k`.
This distribution is defined by a 1-D mean `mu` and covariance matrix `sigma`.
Evaluation of the pdf, determinant, and sampling are all `O(k^3)` operations.
#### Mathematical details
With `C = sigma`, the PDF of this distribution is:
```
f(x) = (2 pi)^(-k/2) |det(C)|^(-1/2) exp(-1/2 (x - mu)^T C^{-1} (x - mu))
```
#### Examples
A single multi-variate Gaussian distribution is defined by a vector of means
of length `k`, and a covariance matrix of shape `k x k`.
Extra leading dimensions, if provided, allow for batches.
```python
# Initialize a single 3-variate Gaussian with diagonal covariance.
mu = [1, 2, 3.]
sigma = [[1, 0, 0], [0, 3, 0], [0, 0, 2.]]
dist = tf.contrib.distributions.MultivariateNormalFull(mu, chol)
# Evaluate this on an observation in R^3, returning a scalar.
dist.pdf([-1, 0, 1])
# Initialize a batch of two 3-variate Gaussians.
mu = [[1, 2, 3], [11, 22, 33.]]
sigma = ... # shape 2 x 3 x 3, positive definite.
dist = tf.contrib.distributions.MultivariateNormalFull(mu, sigma)
# Evaluate this on a two observations, each in R^3, returning a length two
# tensor.
x = [[-1, 0, 1], [-11, 0, 11.]] # Shape 2 x 3.
dist.pdf(x)
```
"""
def __init__(self,
mu,
sigma,
validate_args=True,
allow_nan_stats=False,
name="MultivariateNormalFull"):
"""Multivariate Normal distributions on `R^k`.
User must provide means `mu` and `sigma`, the mean and covariance.
Args:
mu: `(N+1)-D` floating point tensor with shape `[N1,...,Nb, k]`,
`b >= 0`.
sigma: `(N+2)-D` `Tensor` with same `dtype` as `mu` and shape
`[N1,...,Nb, k, k]`. Each batch member must be positive definite.
validate_args: Whether to validate input with asserts. If `validate_args`
is `False`, and the inputs are invalid, correct behavior is not
guaranteed.
allow_nan_stats: `Boolean`, default `False`. If `False`, raise an
exception if a statistic (e.g. mean/mode/etc...) is undefined for any
batch member If `True`, batch members with valid parameters leading to
undefined statistics will return NaN for this statistic.
name: The name to give Ops created by the initializer.
Raises:
TypeError: If `mu` and `sigma` are different dtypes.
"""
cov = operator_pd_full.OperatorPDFull(sigma, verify_pd=validate_args)
super(MultivariateNormalFull, self).__init__(
mu,
cov,
allow_nan_stats=allow_nan_stats,
validate_args=validate_args,
name=name)
def _kl_mvn_mvn_brute_force(mvn_a, mvn_b, name=None):
"""Batched KL divergence `KL(mvn_a || mvn_b)` for multivariate normals.
With `X`, `Y` both multivariate normals in `R^k` with means `mu_x`, `mu_y` and
covariance `C_x`, `C_y` respectively,
```
KL(X || Y) = 0.5 * ( T + Q + - k + L ),
T := trace(C_b^{-1} C_a),
Q := (mu_b - mu_a)^T C_b^{-1} (mu_b - mu_a),
L := Log[Det(C_b)] - Log[Det(C_a)]
```
This `Op` computes the trace by solving `C_b^{-1} C_a`. Although efficient
methods for solving systems with `C_b` may be available, a dense version of
(the square root of) `C_a` is used, so performance is `O(B s k^2)` where `B`
is the batch size, and `s` is the cost of solving `C_b x = y` for vectors `x`
and `y`.
Args:
mvn_a: Instance of subclass of `MultivariateNormalOperatorPD`.
mvn_b: Instance of subclass of `MultivariateNormalOperatorPD`.
name: (optional) name to use for created ops. Default "kl_mvn_mvn".
Returns:
Batchwise `KL(mvn_a || mvn_b)`.
"""
# Access the "private" OperatorPD that each mvn is built from.
cov_a = mvn_a._cov # pylint: disable=protected-access
cov_b = mvn_b._cov # pylint: disable=protected-access
mu_a = mvn_a.mu
mu_b = mvn_b.mu
inputs = [mu_a, mu_b] + cov_a.inputs + cov_b.inputs
with ops.op_scope(inputs, name, "kl_mvn_mvn"):
# If Ca = AA', Cb = BB', then
# tr[inv(Cb) Ca] = tr[inv(B)' inv(B) A A']
# = tr[inv(B) A A' inv(B)']
# = tr[(inv(B) A) (inv(B) A)']
# = sum_{ik} (inv(B) A)_{ik}^2
# The second equality follows from the cyclic permutation property.
b_inv_a = cov_b.sqrt_solve(cov_a.sqrt_to_dense())
t = math_ops.reduce_sum(
math_ops.square(b_inv_a),
reduction_indices=[-1, -2])
q = cov_b.inv_quadratic_form_on_vectors(mu_b - mu_a)
k = math_ops.cast(cov_a.vector_space_dimension(), mvn_a.dtype)
one_half_l = cov_b.sqrt_log_det() - cov_a.sqrt_log_det()
return 0.5 * (t + q - k) + one_half_l
# Register KL divergences.
kl_classes = [
MultivariateNormalFull,
MultivariateNormalCholesky,
MultivariateNormalDiag,
MultivariateNormalDiagPlusVDVT,
]
for mvn_aa in kl_classes:
# Register when they are the same here, and do not register when they are the
# same below because that would result in a repeated registration.
kullback_leibler.RegisterKL(mvn_aa, mvn_aa)(_kl_mvn_mvn_brute_force)
for mvn_bb in kl_classes:
if mvn_bb != mvn_aa:
kullback_leibler.RegisterKL(mvn_aa, mvn_bb)(_kl_mvn_mvn_brute_force)
| mit |
jcpowermac/ansible-modules-extras | clustering/consul_acl.py | 13 | 10484 | #!/usr/bin/python
#
# (c) 2015, Steve Gargan <steve.gargan@gmail.com>
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
DOCUMENTATION = """
module: consul_acl
short_description: "manipulate consul acl keys and rules"
description:
- allows the addition, modification and deletion of ACL keys and associated
rules in a consul cluster via the agent. For more details on using and
configuring ACLs, see https://www.consul.io/docs/internals/acl.html.
requirements:
- "python >= 2.6"
- python-consul
- pyhcl
- requests
version_added: "2.0"
author: "Steve Gargan (@sgargan)"
options:
mgmt_token:
description:
- a management token is required to manipulate the acl lists
state:
description:
- whether the ACL pair should be present or absent, defaults to present
required: false
choices: ['present', 'absent']
type:
description:
- the type of token that should be created, either management or
client, defaults to client
choices: ['client', 'management']
name:
description:
- the name that should be associated with the acl key, this is opaque
to Consul
required: false
token:
description:
- the token key indentifying an ACL rule set. If generated by consul
this will be a UUID.
required: false
rules:
description:
- an list of the rules that should be associated with a given token.
required: false
host:
description:
- host of the consul agent defaults to localhost
required: false
default: localhost
port:
description:
- the port on which the consul agent is running
required: false
default: 8500
"""
EXAMPLES = '''
- name: create an acl token with rules
consul_acl:
mgmt_token: 'some_management_acl'
host: 'consul1.mycluster.io'
name: 'Foo access'
rules:
- key: 'foo'
policy: read
- key: 'private/foo'
policy: deny
- name: create an acl with specific token with both key and serivce rules
consul_acl:
mgmt_token: 'some_management_acl'
name: 'Foo access'
token: 'some_client_token'
rules:
- key: 'foo'
policy: read
- service: ''
policy: write
- service: 'secret-'
policy: deny
- name: remove a token
consul_acl:
mgmt_token: 'some_management_acl'
host: 'consul1.mycluster.io'
token: '172bd5c8-9fe9-11e4-b1b0-3c15c2c9fd5e'
state: absent
'''
import sys
try:
import consul
from requests.exceptions import ConnectionError
python_consul_installed = True
except ImportError, e:
python_consul_installed = False
try:
import hcl
pyhcl_installed = True
except ImportError:
pyhcl_installed = False
from requests.exceptions import ConnectionError
def execute(module):
state = module.params.get('state')
if state == 'present':
update_acl(module)
else:
remove_acl(module)
def update_acl(module):
rules = module.params.get('rules')
state = module.params.get('state')
token = module.params.get('token')
token_type = module.params.get('token_type')
mgmt = module.params.get('mgmt_token')
name = module.params.get('name')
consul = get_consul_api(module, mgmt)
changed = False
try:
if token:
existing_rules = load_rules_for_token(module, consul, token)
supplied_rules = yml_to_rules(module, rules)
changed = not existing_rules == supplied_rules
if changed:
y = supplied_rules.to_hcl()
token = consul.acl.update(
token,
name=name,
type=token_type,
rules=supplied_rules.to_hcl())
else:
try:
rules = yml_to_rules(module, rules)
if rules.are_rules():
rules = rules.to_hcl()
else:
rules = None
token = consul.acl.create(
name=name, type=token_type, rules=rules)
changed = True
except Exception, e:
module.fail_json(
msg="No token returned, check your managment key and that \
the host is in the acl datacenter %s" % e)
except Exception, e:
module.fail_json(msg="Could not create/update acl %s" % e)
module.exit_json(changed=changed,
token=token,
rules=rules,
name=name,
type=token_type)
def remove_acl(module):
state = module.params.get('state')
token = module.params.get('token')
mgmt = module.params.get('mgmt_token')
consul = get_consul_api(module, token=mgmt)
changed = token and consul.acl.info(token)
if changed:
token = consul.acl.destroy(token)
module.exit_json(changed=changed, token=token)
def load_rules_for_token(module, consul_api, token):
try:
rules = Rules()
info = consul_api.acl.info(token)
if info and info['Rules']:
rule_set = hcl.loads(to_ascii(info['Rules']))
for rule_type in rule_set:
for pattern, policy in rule_set[rule_type].iteritems():
rules.add_rule(rule_type, Rule(pattern, policy['policy']))
return rules
except Exception, e:
module.fail_json(
msg="Could not load rule list from retrieved rule data %s, %s" % (
token, e))
return json_to_rules(module, loaded)
def to_ascii(unicode_string):
if isinstance(unicode_string, unicode):
return unicode_string.encode('ascii', 'ignore')
return unicode_string
def yml_to_rules(module, yml_rules):
rules = Rules()
if yml_rules:
for rule in yml_rules:
if ('key' in rule and 'policy' in rule):
rules.add_rule('key', Rule(rule['key'], rule['policy']))
elif ('service' in rule and 'policy' in rule):
rules.add_rule('service', Rule(rule['service'], rule['policy']))
else:
module.fail_json(msg="a rule requires a key/service and a policy.")
return rules
template = '''%s "%s" {
policy = "%s"
}
'''
RULE_TYPES = ['key', 'service']
class Rules:
def __init__(self):
self.rules = {}
for rule_type in RULE_TYPES:
self.rules[rule_type] = {}
def add_rule(self, rule_type, rule):
self.rules[rule_type][rule.pattern] = rule
def are_rules(self):
return len(self) > 0
def to_hcl(self):
rules = ""
for rule_type in RULE_TYPES:
for pattern, rule in self.rules[rule_type].iteritems():
rules += template % (rule_type, pattern, rule.policy)
return to_ascii(rules)
def __len__(self):
count = 0
for rule_type in RULE_TYPES:
count += len(self.rules[rule_type])
return count
def __eq__(self, other):
if not (other or isinstance(other, self.__class__)
or len(other) == len(self)):
return False
for rule_type in RULE_TYPES:
for name, other_rule in other.rules[rule_type].iteritems():
if not name in self.rules[rule_type]:
return False
rule = self.rules[rule_type][name]
if not (rule and rule == other_rule):
return False
return True
def __str__(self):
return self.to_hcl()
class Rule:
def __init__(self, pattern, policy):
self.pattern = pattern
self.policy = policy
def __eq__(self, other):
return (isinstance(other, self.__class__)
and self.pattern == other.pattern
and self.policy == other.policy)
def __hash__(self):
return hash(self.pattern) ^ hash(self.policy)
def __str__(self):
return '%s %s' % (self.pattern, self.policy)
def get_consul_api(module, token=None):
if not token:
token = module.params.get('token')
return consul.Consul(host=module.params.get('host'),
port=module.params.get('port'),
token=token)
def test_dependencies(module):
if not python_consul_installed:
module.fail_json(msg="python-consul required for this module. "\
"see http://python-consul.readthedocs.org/en/latest/#installation")
if not pyhcl_installed:
module.fail_json( msg="pyhcl required for this module."\
" see https://pypi.python.org/pypi/pyhcl")
def main():
argument_spec = dict(
mgmt_token=dict(required=True, no_log=True),
host=dict(default='localhost'),
name=dict(required=False),
port=dict(default=8500, type='int'),
rules=dict(default=None, required=False, type='list'),
state=dict(default='present', choices=['present', 'absent']),
token=dict(required=False, no_log=True),
token_type=dict(
required=False, choices=['client', 'management'], default='client')
)
module = AnsibleModule(argument_spec, supports_check_mode=False)
test_dependencies(module)
try:
execute(module)
except ConnectionError, e:
module.fail_json(msg='Could not connect to consul agent at %s:%s, error was %s' % (
module.params.get('host'), module.params.get('port'), str(e)))
except Exception, e:
module.fail_json(msg=str(e))
# import module snippets
from ansible.module_utils.basic import *
if __name__ == '__main__':
main()
| gpl-3.0 |
DreamerKing/LightweightHtmlWidgets | LightweightHtmlWidgets/bin/Release/Ipy.Lib/wsgiref/simple_server.py | 177 | 4743 | """BaseHTTPServer that implements the Python WSGI protocol (PEP 333, rev 1.21)
This is both an example of how WSGI can be implemented, and a basis for running
simple web applications on a local machine, such as might be done when testing
or debugging an application. It has not been reviewed for security issues,
however, and we strongly recommend that you use a "real" web server for
production use.
For example usage, see the 'if __name__=="__main__"' block at the end of the
module. See also the BaseHTTPServer module docs for other API information.
"""
from BaseHTTPServer import BaseHTTPRequestHandler, HTTPServer
import urllib, sys
from wsgiref.handlers import SimpleHandler
__version__ = "0.1"
__all__ = ['WSGIServer', 'WSGIRequestHandler', 'demo_app', 'make_server']
server_version = "WSGIServer/" + __version__
sys_version = "Python/" + sys.version.split()[0]
software_version = server_version + ' ' + sys_version
class ServerHandler(SimpleHandler):
server_software = software_version
def close(self):
try:
self.request_handler.log_request(
self.status.split(' ',1)[0], self.bytes_sent
)
finally:
SimpleHandler.close(self)
class WSGIServer(HTTPServer):
"""BaseHTTPServer that implements the Python WSGI protocol"""
application = None
def server_bind(self):
"""Override server_bind to store the server name."""
HTTPServer.server_bind(self)
self.setup_environ()
def setup_environ(self):
# Set up base environment
env = self.base_environ = {}
env['SERVER_NAME'] = self.server_name
env['GATEWAY_INTERFACE'] = 'CGI/1.1'
env['SERVER_PORT'] = str(self.server_port)
env['REMOTE_HOST']=''
env['CONTENT_LENGTH']=''
env['SCRIPT_NAME'] = ''
def get_app(self):
return self.application
def set_app(self,application):
self.application = application
class WSGIRequestHandler(BaseHTTPRequestHandler):
server_version = "WSGIServer/" + __version__
def get_environ(self):
env = self.server.base_environ.copy()
env['SERVER_PROTOCOL'] = self.request_version
env['REQUEST_METHOD'] = self.command
if '?' in self.path:
path,query = self.path.split('?',1)
else:
path,query = self.path,''
env['PATH_INFO'] = urllib.unquote(path)
env['QUERY_STRING'] = query
host = self.address_string()
if host != self.client_address[0]:
env['REMOTE_HOST'] = host
env['REMOTE_ADDR'] = self.client_address[0]
if self.headers.typeheader is None:
env['CONTENT_TYPE'] = self.headers.type
else:
env['CONTENT_TYPE'] = self.headers.typeheader
length = self.headers.getheader('content-length')
if length:
env['CONTENT_LENGTH'] = length
for h in self.headers.headers:
k,v = h.split(':',1)
k=k.replace('-','_').upper(); v=v.strip()
if k in env:
continue # skip content length, type,etc.
if 'HTTP_'+k in env:
env['HTTP_'+k] += ','+v # comma-separate multiple headers
else:
env['HTTP_'+k] = v
return env
def get_stderr(self):
return sys.stderr
def handle(self):
"""Handle a single HTTP request"""
self.raw_requestline = self.rfile.readline()
if not self.parse_request(): # An error code has been sent, just exit
return
handler = ServerHandler(
self.rfile, self.wfile, self.get_stderr(), self.get_environ()
)
handler.request_handler = self # backpointer for logging
handler.run(self.server.get_app())
def demo_app(environ,start_response):
from StringIO import StringIO
stdout = StringIO()
print >>stdout, "Hello world!"
print >>stdout
h = environ.items(); h.sort()
for k,v in h:
print >>stdout, k,'=', repr(v)
start_response("200 OK", [('Content-Type','text/plain')])
return [stdout.getvalue()]
def make_server(
host, port, app, server_class=WSGIServer, handler_class=WSGIRequestHandler
):
"""Create a new WSGI server listening on `host` and `port` for `app`"""
server = server_class((host, port), handler_class)
server.set_app(app)
return server
if __name__ == '__main__':
httpd = make_server('', 8000, demo_app)
sa = httpd.socket.getsockname()
print "Serving HTTP on", sa[0], "port", sa[1], "..."
import webbrowser
webbrowser.open('http://localhost:8000/xyz?abc')
httpd.handle_request() # serve one request, then exit
| gpl-3.0 |
google/clif | examples/wrapfunc/python/default_args_test.py | 1 | 1214 | # Copyright 2017 Google Inc.
#
# 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.
"""Tests for clif.examples.wrapfunc.python.default_args."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import unittest
from wrapfunc.python import default_args
class DefaultArgTest(unittest.TestCase):
def testDefaultArgTest(self):
self.assertTrue(default_args.Inc(5), 6)
self.assertTrue(default_args.Inc(5, 2), 7)
self.assertTrue(default_args.Scale(5), 10)
self.assertTrue(default_args.Scale(5, offset=10), 30)
with self.assertRaises(ValueError):
default_args.ScaleWithRatios(5, offset=10)
if __name__ == '__main__':
unittest.main()
| apache-2.0 |
openstack/manila | manila/scheduler/weighers/pool.py | 5 | 1955 | # Copyright 2015 Mirantis Inc.
# All Rights Reserved.
#
# 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.
from oslo_config import cfg
from manila import context
from manila.db import api as db_api
from manila.scheduler.weighers import base_host
from manila.share import utils
pool_weight_opts = [
cfg.FloatOpt('pool_weight_multiplier',
default=1.0,
help='Multiplier used for weighing pools which have '
'existing share servers. Negative numbers mean to spread'
' vs stack.'),
]
CONF = cfg.CONF
CONF.register_opts(pool_weight_opts)
class PoolWeigher(base_host.BaseHostWeigher):
def weight_multiplier(self):
"""Override the weight multiplier."""
return CONF.pool_weight_multiplier
def _weigh_object(self, host_state, weight_properties):
"""Pools with existing share server win."""
pool_mapping = weight_properties.get('server_pools_mapping', {})
if not pool_mapping:
return 0
ctx = context.get_admin_context()
host = utils.extract_host(host_state.host, 'backend')
servers = db_api.share_server_get_all_by_host(ctx, host)
pool = utils.extract_host(host_state.host, 'pool')
for server in servers:
if any(pool == p['pool_name'] for p in pool_mapping.get(
server['id'], [])):
return 1
return 0
| apache-2.0 |
Garrett-R/scikit-learn | sklearn/linear_model/randomized_l1.py | 11 | 23088 | """
Randomized Lasso/Logistic: feature selection based on Lasso and
sparse Logistic Regression
"""
# Author: Gael Varoquaux, Alexandre Gramfort
#
# License: BSD 3 clause
import itertools
from abc import ABCMeta, abstractmethod
import warnings
import numpy as np
from scipy.sparse import issparse
from scipy import sparse
from scipy.interpolate import interp1d
from .base import center_data
from ..base import BaseEstimator, TransformerMixin
from ..externals import six
from ..externals.joblib import Memory, Parallel, delayed
from ..utils import (as_float_array, check_random_state, check_X_y,
check_array, safe_mask, ConvergenceWarning)
from .least_angle import lars_path, LassoLarsIC
from .logistic import LogisticRegression
###############################################################################
# Randomized linear model: feature selection
def _resample_model(estimator_func, X, y, scaling=.5, n_resampling=200,
n_jobs=1, verbose=False, pre_dispatch='3*n_jobs',
random_state=None, sample_fraction=.75, **params):
random_state = check_random_state(random_state)
# We are generating 1 - weights, and not weights
n_samples, n_features = X.shape
if not (0 < scaling < 1):
raise ValueError(
"'scaling' should be between 0 and 1. Got %r instead." % scaling)
scaling = 1. - scaling
scores_ = 0.0
for active_set in Parallel(n_jobs=n_jobs, verbose=verbose,
pre_dispatch=pre_dispatch)(
delayed(estimator_func)(
X, y, weights=scaling * random_state.random_integers(
0, 1, size=(n_features,)),
mask=(random_state.rand(n_samples) < sample_fraction),
verbose=max(0, verbose - 1),
**params)
for _ in range(n_resampling)):
scores_ += active_set
scores_ /= n_resampling
return scores_
class BaseRandomizedLinearModel(six.with_metaclass(ABCMeta, BaseEstimator,
TransformerMixin)):
"""Base class to implement randomized linear models for feature selection
This implements the strategy by Meinshausen and Buhlman:
stability selection with randomized sampling, and random re-weighting of
the penalty.
"""
@abstractmethod
def __init__(self):
pass
_center_data = staticmethod(center_data)
def fit(self, X, y):
"""Fit the model using X, y as training data.
Parameters
----------
X : array-like, sparse matrix shape = [n_samples, n_features]
Training data.
y : array-like, shape = [n_samples]
Target values.
Returns
-------
self : object
Returns an instance of self.
"""
X, y = check_X_y(X, y, ['csr', 'csc', 'coo'])
X = as_float_array(X, copy=False)
n_samples, n_features = X.shape
X, y, X_mean, y_mean, X_std = self._center_data(X, y,
self.fit_intercept,
self.normalize)
estimator_func, params = self._make_estimator_and_params(X, y)
memory = self.memory
if isinstance(memory, six.string_types):
memory = Memory(cachedir=memory)
scores_ = memory.cache(
_resample_model, ignore=['verbose', 'n_jobs', 'pre_dispatch']
)(
estimator_func, X, y,
scaling=self.scaling, n_resampling=self.n_resampling,
n_jobs=self.n_jobs, verbose=self.verbose,
pre_dispatch=self.pre_dispatch, random_state=self.random_state,
sample_fraction=self.sample_fraction, **params)
if scores_.ndim == 1:
scores_ = scores_[:, np.newaxis]
self.all_scores_ = scores_
self.scores_ = np.max(self.all_scores_, axis=1)
return self
def _make_estimator_and_params(self, X, y):
"""Return the parameters passed to the estimator"""
raise NotImplementedError
def get_support(self, indices=False):
"""Return a mask, or list, of the features/indices selected."""
mask = self.scores_ > self.selection_threshold
return mask if not indices else np.where(mask)[0]
# XXX: the two function below are copy/pasted from feature_selection,
# Should we add an intermediate base class?
def transform(self, X):
"""Transform a new matrix using the selected features"""
mask = self.get_support()
X = check_array(X)
if len(mask) != X.shape[1]:
raise ValueError("X has a different shape than during fitting.")
return check_array(X)[:, safe_mask(X, mask)]
def inverse_transform(self, X):
"""Transform a new matrix using the selected features"""
support = self.get_support()
if X.ndim == 1:
X = X[None, :]
Xt = np.zeros((X.shape[0], support.size))
Xt[:, support] = X
return Xt
###############################################################################
# Randomized lasso: regression settings
def _randomized_lasso(X, y, weights, mask, alpha=1., verbose=False,
precompute=False, eps=np.finfo(np.float).eps,
max_iter=500):
X = X[safe_mask(X, mask)]
y = y[mask]
# Center X and y to avoid fit the intercept
X -= X.mean(axis=0)
y -= y.mean()
alpha = np.atleast_1d(np.asarray(alpha, dtype=np.float))
X = (1 - weights) * X
with warnings.catch_warnings():
warnings.simplefilter('ignore', ConvergenceWarning)
alphas_, _, coef_ = lars_path(X, y,
Gram=precompute, copy_X=False,
copy_Gram=False, alpha_min=np.min(alpha),
method='lasso', verbose=verbose,
max_iter=max_iter, eps=eps)
if len(alpha) > 1:
if len(alphas_) > 1: # np.min(alpha) < alpha_min
interpolator = interp1d(alphas_[::-1], coef_[:, ::-1],
bounds_error=False, fill_value=0.)
scores = (interpolator(alpha) != 0.0)
else:
scores = np.zeros((X.shape[1], len(alpha)), dtype=np.bool)
else:
scores = coef_[:, -1] != 0.0
return scores
class RandomizedLasso(BaseRandomizedLinearModel):
"""Randomized Lasso.
Randomized Lasso works by resampling the train data and computing
a Lasso on each resampling. In short, the features selected more
often are good features. It is also known as stability selection.
Parameters
----------
alpha : float, 'aic', or 'bic', optional
The regularization parameter alpha parameter in the Lasso.
Warning: this is not the alpha parameter in the stability selection
article which is scaling.
scaling : float, optional
The alpha parameter in the stability selection article used to
randomly scale the features. Should be between 0 and 1.
sample_fraction : float, optional
The fraction of samples to be used in each randomized design.
Should be between 0 and 1. If 1, all samples are used.
n_resampling : int, optional
Number of randomized models.
selection_threshold: float, optional
The score above which features should be selected.
fit_intercept : boolean, optional
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
verbose : boolean or integer, optional
Sets the verbosity amount
normalize : boolean, optional, default True
If True, the regressors X will be normalized before regression.
precompute : True | False | 'auto'
Whether to use a precomputed Gram matrix to speed up
calculations. If set to 'auto' let us decide. The Gram
matrix can also be passed as argument.
max_iter : integer, optional
Maximum number of iterations to perform in the Lars algorithm.
eps : float, optional
The machine-precision regularization in the computation of the
Cholesky diagonal factors. Increase this for very ill-conditioned
systems. Unlike the 'tol' parameter in some iterative
optimization-based algorithms, this parameter does not control
the tolerance of the optimization.
n_jobs : integer, optional
Number of CPUs to use during the resampling. If '-1', use
all the CPUs
random_state : int, RandomState instance or None, optional (default=None)
If int, random_state is the seed used by the random number generator;
If RandomState instance, random_state is the random number generator;
If None, the random number generator is the RandomState instance used
by `np.random`.
pre_dispatch : int, or string, optional
Controls the number of jobs that get dispatched during parallel
execution. Reducing this number can be useful to avoid an
explosion of memory consumption when more jobs get dispatched
than CPUs can process. This parameter can be:
- None, in which case all the jobs are immediately
created and spawned. Use this for lightweight and
fast-running jobs, to avoid delays due to on-demand
spawning of the jobs
- An int, giving the exact number of total jobs that are
spawned
- A string, giving an expression as a function of n_jobs,
as in '2*n_jobs'
memory : Instance of joblib.Memory or string
Used for internal caching. By default, no caching is done.
If a string is given, it is the path to the caching directory.
Attributes
----------
scores_ : array, shape = [n_features]
Feature scores between 0 and 1.
all_scores_ : array, shape = [n_features, n_reg_parameter]
Feature scores between 0 and 1 for all values of the regularization \
parameter. The reference article suggests ``scores_`` is the max of \
``all_scores_``.
Examples
--------
>>> from sklearn.linear_model import RandomizedLasso
>>> randomized_lasso = RandomizedLasso()
Notes
-----
See examples/linear_model/plot_sparse_recovery.py for an example.
References
----------
Stability selection
Nicolai Meinshausen, Peter Buhlmann
Journal of the Royal Statistical Society: Series B
Volume 72, Issue 4, pages 417-473, September 2010
DOI: 10.1111/j.1467-9868.2010.00740.x
See also
--------
RandomizedLogisticRegression, LogisticRegression
"""
def __init__(self, alpha='aic', scaling=.5, sample_fraction=.75,
n_resampling=200, selection_threshold=.25,
fit_intercept=True, verbose=False,
normalize=True, precompute='auto',
max_iter=500,
eps=np.finfo(np.float).eps, random_state=None,
n_jobs=1, pre_dispatch='3*n_jobs',
memory=Memory(cachedir=None, verbose=0)):
self.alpha = alpha
self.scaling = scaling
self.sample_fraction = sample_fraction
self.n_resampling = n_resampling
self.fit_intercept = fit_intercept
self.max_iter = max_iter
self.verbose = verbose
self.normalize = normalize
self.precompute = precompute
self.eps = eps
self.random_state = random_state
self.n_jobs = n_jobs
self.selection_threshold = selection_threshold
self.pre_dispatch = pre_dispatch
self.memory = memory
def _make_estimator_and_params(self, X, y):
assert self.precompute in (True, False, None, 'auto')
alpha = self.alpha
if alpha in ('aic', 'bic'):
model = LassoLarsIC(precompute=self.precompute,
criterion=self.alpha,
max_iter=self.max_iter,
eps=self.eps)
model.fit(X, y)
self.alpha_ = alpha = model.alpha_
return _randomized_lasso, dict(alpha=alpha, max_iter=self.max_iter,
eps=self.eps,
precompute=self.precompute)
###############################################################################
# Randomized logistic: classification settings
def _randomized_logistic(X, y, weights, mask, C=1., verbose=False,
fit_intercept=True, tol=1e-3):
X = X[safe_mask(X, mask)]
y = y[mask]
if issparse(X):
size = len(weights)
weight_dia = sparse.dia_matrix((1 - weights, 0), (size, size))
X = X * weight_dia
else:
X *= (1 - weights)
C = np.atleast_1d(np.asarray(C, dtype=np.float))
scores = np.zeros((X.shape[1], len(C)), dtype=np.bool)
for this_C, this_scores in zip(C, scores.T):
# XXX : would be great to do it with a warm_start ...
clf = LogisticRegression(C=this_C, tol=tol, penalty='l1', dual=False,
fit_intercept=fit_intercept)
clf.fit(X, y)
this_scores[:] = np.any(
np.abs(clf.coef_) > 10 * np.finfo(np.float).eps, axis=0)
return scores
class RandomizedLogisticRegression(BaseRandomizedLinearModel):
"""Randomized Logistic Regression
Randomized Regression works by resampling the train data and computing
a LogisticRegression on each resampling. In short, the features selected
more often are good features. It is also known as stability selection.
Parameters
----------
C : float, optional, default=1
The regularization parameter C in the LogisticRegression.
scaling : float, optional, default=0.5
The alpha parameter in the stability selection article used to
randomly scale the features. Should be between 0 and 1.
sample_fraction : float, optional, default=0.75
The fraction of samples to be used in each randomized design.
Should be between 0 and 1. If 1, all samples are used.
n_resampling : int, optional, default=200
Number of randomized models.
selection_threshold: float, optional, default=0.25
The score above which features should be selected.
fit_intercept : boolean, optional, default=True
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
verbose : boolean or integer, optional
Sets the verbosity amount
normalize : boolean, optional, default=True
If True, the regressors X will be normalized before regression.
tol : float, optional, default=1e-3
tolerance for stopping criteria of LogisticRegression
n_jobs : integer, optional
Number of CPUs to use during the resampling. If '-1', use
all the CPUs
random_state : int, RandomState instance or None, optional (default=None)
If int, random_state is the seed used by the random number generator;
If RandomState instance, random_state is the random number generator;
If None, the random number generator is the RandomState instance used
by `np.random`.
pre_dispatch : int, or string, optional
Controls the number of jobs that get dispatched during parallel
execution. Reducing this number can be useful to avoid an
explosion of memory consumption when more jobs get dispatched
than CPUs can process. This parameter can be:
- None, in which case all the jobs are immediately
created and spawned. Use this for lightweight and
fast-running jobs, to avoid delays due to on-demand
spawning of the jobs
- An int, giving the exact number of total jobs that are
spawned
- A string, giving an expression as a function of n_jobs,
as in '2*n_jobs'
memory : Instance of joblib.Memory or string
Used for internal caching. By default, no caching is done.
If a string is given, it is the path to the caching directory.
Attributes
----------
scores_ : array, shape = [n_features]
Feature scores between 0 and 1.
all_scores_ : array, shape = [n_features, n_reg_parameter]
Feature scores between 0 and 1 for all values of the regularization \
parameter. The reference article suggests ``scores_`` is the max \
of ``all_scores_``.
Examples
--------
>>> from sklearn.linear_model import RandomizedLogisticRegression
>>> randomized_logistic = RandomizedLogisticRegression()
Notes
-----
See examples/linear_model/plot_sparse_recovery.py for an example.
References
----------
Stability selection
Nicolai Meinshausen, Peter Buhlmann
Journal of the Royal Statistical Society: Series B
Volume 72, Issue 4, pages 417-473, September 2010
DOI: 10.1111/j.1467-9868.2010.00740.x
See also
--------
RandomizedLasso, Lasso, ElasticNet
"""
def __init__(self, C=1, scaling=.5, sample_fraction=.75,
n_resampling=200,
selection_threshold=.25, tol=1e-3,
fit_intercept=True, verbose=False,
normalize=True,
random_state=None,
n_jobs=1, pre_dispatch='3*n_jobs',
memory=Memory(cachedir=None, verbose=0)):
self.C = C
self.scaling = scaling
self.sample_fraction = sample_fraction
self.n_resampling = n_resampling
self.fit_intercept = fit_intercept
self.verbose = verbose
self.normalize = normalize
self.tol = tol
self.random_state = random_state
self.n_jobs = n_jobs
self.selection_threshold = selection_threshold
self.pre_dispatch = pre_dispatch
self.memory = memory
def _make_estimator_and_params(self, X, y):
params = dict(C=self.C, tol=self.tol,
fit_intercept=self.fit_intercept)
return _randomized_logistic, params
def _center_data(self, X, y, fit_intercept, normalize=False):
"""Center the data in X but not in y"""
X, _, Xmean, _, X_std = center_data(X, y, fit_intercept,
normalize=normalize)
return X, y, Xmean, y, X_std
###############################################################################
# Stability paths
def _lasso_stability_path(X, y, mask, weights, eps):
"Inner loop of lasso_stability_path"
X = X * weights[np.newaxis, :]
X = X[safe_mask(X, mask), :]
y = y[mask]
alpha_max = np.max(np.abs(np.dot(X.T, y))) / X.shape[0]
alpha_min = eps * alpha_max # set for early stopping in path
with warnings.catch_warnings():
warnings.simplefilter('ignore', ConvergenceWarning)
alphas, _, coefs = lars_path(X, y, method='lasso', verbose=False,
alpha_min=alpha_min)
# Scale alpha by alpha_max
alphas /= alphas[0]
# Sort alphas in assending order
alphas = alphas[::-1]
coefs = coefs[:, ::-1]
# Get rid of the alphas that are too small
mask = alphas >= eps
# We also want to keep the first one: it should be close to the OLS
# solution
mask[0] = True
alphas = alphas[mask]
coefs = coefs[:, mask]
return alphas, coefs
def lasso_stability_path(X, y, scaling=0.5, random_state=None,
n_resampling=200, n_grid=100,
sample_fraction=0.75,
eps=4 * np.finfo(np.float).eps, n_jobs=1,
verbose=False):
"""Stabiliy path based on randomized Lasso estimates
Parameters
----------
X : array-like, shape = [n_samples, n_features]
training data.
y : array-like, shape = [n_samples]
target values.
scaling : float, optional, default=0.5
The alpha parameter in the stability selection article used to
randomly scale the features. Should be between 0 and 1.
random_state : integer or numpy.random.RandomState, optional
The generator used to randomize the design.
n_resampling : int, optional, default=200
Number of randomized models.
n_grid : int, optional, default=100
Number of grid points. The path is linearly reinterpolated
on a grid between 0 and 1 before computing the scores.
sample_fraction : float, optional, default=0.75
The fraction of samples to be used in each randomized design.
Should be between 0 and 1. If 1, all samples are used.
eps : float, optional
Smallest value of alpha / alpha_max considered
n_jobs : integer, optional
Number of CPUs to use during the resampling. If '-1', use
all the CPUs
verbose : boolean or integer, optional
Sets the verbosity amount
Returns
-------
alphas_grid : array, shape ~ [n_grid]
The grid points between 0 and 1: alpha/alpha_max
scores_path : array, shape = [n_features, n_grid]
The scores for each feature along the path.
Notes
-----
See examples/linear_model/plot_sparse_recovery.py for an example.
"""
rng = check_random_state(random_state)
if not (0 < scaling < 1):
raise ValueError("Parameter 'scaling' should be between 0 and 1."
" Got %r instead." % scaling)
n_samples, n_features = X.shape
paths = Parallel(n_jobs=n_jobs, verbose=verbose)(
delayed(_lasso_stability_path)(
X, y, mask=rng.rand(n_samples) < sample_fraction,
weights=1. - scaling * rng.random_integers(0, 1,
size=(n_features,)),
eps=eps)
for k in range(n_resampling))
all_alphas = sorted(list(set(itertools.chain(*[p[0] for p in paths]))))
# Take approximately n_grid values
stride = int(max(1, int(len(all_alphas) / float(n_grid))))
all_alphas = all_alphas[::stride]
if not all_alphas[-1] == 1:
all_alphas.append(1.)
all_alphas = np.array(all_alphas)
scores_path = np.zeros((n_features, len(all_alphas)))
for alphas, coefs in paths:
if alphas[0] != 0:
alphas = np.r_[0, alphas]
coefs = np.c_[np.ones((n_features, 1)), coefs]
if alphas[-1] != all_alphas[-1]:
alphas = np.r_[alphas, all_alphas[-1]]
coefs = np.c_[coefs, np.zeros((n_features, 1))]
scores_path += (interp1d(alphas, coefs,
kind='nearest', bounds_error=False,
fill_value=0, axis=-1)(all_alphas) != 0)
scores_path /= n_resampling
return all_alphas, scores_path
| bsd-3-clause |
onitake/ansible | lib/ansible/modules/network/cnos/cnos_reload.py | 17 | 3423 | #!/usr/bin/python
# -*- coding: utf-8 -*-
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
#
# Copyright (C) 2017 Lenovo, Inc.
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
#
# Module to reload Lenovo Switches
# Lenovo Networking
#
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = '''
---
module: cnos_reload
author: "Anil Kumar Muraleedharan (@amuraleedhar)"
short_description: Perform switch restart on devices running Lenovo CNOS
description:
- This module allows you to restart the switch using the current startup
configuration. The module is usually invoked after the running
configuration has been saved over the startup configuration.
This module uses SSH to manage network device configuration.
The results of the operation can be viewed in results directory.
version_added: "2.3"
extends_documentation_fragment: cnos
options: {}
'''
EXAMPLES = '''
Tasks : The following are examples of using the module cnos_reload. These are
written in the main.yml file of the tasks directory.
---
- name: Test Reload
cnos_reload:
deviceType: "{{ hostvars[inventory_hostname]['deviceType'] }}"
outputfile: "./results/test_reload_{{ inventory_hostname }}_output.txt"
'''
RETURN = '''
msg:
description: Success or failure message
returned: always
type: string
sample: "Device is Reloading. Please wait..."
'''
import sys
import time
import socket
import array
import json
import time
import re
try:
from ansible.module_utils.network.cnos import cnos
HAS_LIB = True
except:
HAS_LIB = False
from ansible.module_utils.basic import AnsibleModule
from collections import defaultdict
def main():
module = AnsibleModule(
argument_spec=dict(
outputfile=dict(required=True),
host=dict(required=False),
username=dict(required=False),
password=dict(required=False, no_log=True),
enablePassword=dict(required=False, no_log=True),
deviceType=dict(required=True),),
supports_check_mode=False)
command = 'reload'
outputfile = module.params['outputfile']
output = ''
cmd = [{'command': command, 'prompt': 'reboot system? (y/n): ',
'answer': 'y'}]
output = output + str(cnos.run_cnos_commands(module, cmd))
# Save it into the file
file = open(outputfile, "a")
file.write(output)
file.close()
errorMsg = cnos.checkOutputForError(output)
if(errorMsg in "Device Response Timed out"):
module.exit_json(changed=True,
msg="Device is Reloading. Please wait...")
else:
module.fail_json(msg=errorMsg)
if __name__ == '__main__':
main()
| gpl-3.0 |
carolFrohlich/nipype | nipype/interfaces/mrtrix3/preprocess.py | 2 | 7501 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
# -*- coding: utf-8 -*-
"""
Change directory to provide relative paths for doctests
>>> import os
>>> filepath = os.path.dirname(os.path.realpath(__file__ ))
>>> datadir = os.path.realpath(os.path.join(filepath,
... '../../testing/data'))
>>> os.chdir(datadir)
"""
from __future__ import print_function, division, unicode_literals, absolute_import
import os.path as op
from ..traits_extension import isdefined
from ..base import (CommandLineInputSpec, CommandLine, traits, TraitedSpec,
File)
from .base import MRTrix3BaseInputSpec, MRTrix3Base
class ResponseSDInputSpec(MRTrix3BaseInputSpec):
in_file = File(exists=True, argstr='%s', mandatory=True, position=-2,
desc='input diffusion weighted images')
out_file = File(
'response.txt', argstr='%s', mandatory=True, position=-1,
usedefault=True, desc='output file containing SH coefficients')
# DW Shell selection options
shell = traits.List(traits.Float, sep=',', argstr='-shell %s',
desc='specify one or more dw gradient shells')
in_mask = File(exists=True, argstr='-mask %s',
desc='provide initial mask image')
max_sh = traits.Int(8, argstr='-lmax %d',
desc='maximum harmonic degree of response function')
out_sf = File('sf_mask.nii.gz', argstr='-sf %s',
desc='write a mask containing single-fibre voxels')
test_all = traits.Bool(False, argstr='-test_all',
desc='re-test all voxels at every iteration')
# Optimization
iterations = traits.Int(0, argstr='-max_iters %d',
desc='maximum number of iterations per pass')
max_change = traits.Float(
argstr='-max_change %f',
desc=('maximum percentile change in any response function coefficient;'
' if no individual coefficient changes by more than this '
'fraction, the algorithm is terminated.'))
# Thresholds
vol_ratio = traits.Float(
.15, argstr='-volume_ratio %f',
desc=('maximal volume ratio between the sum of all other positive'
' lobes in the voxel and the largest FOD lobe'))
disp_mult = traits.Float(
1., argstr='-dispersion_multiplier %f',
desc=('dispersion of FOD lobe must not exceed some threshold as '
'determined by this multiplier and the FOD dispersion in other '
'single-fibre voxels. The threshold is: (mean + (multiplier * '
'(mean - min))); default = 1.0. Criterion is only applied in '
'second pass of RF estimation.'))
int_mult = traits.Float(
2., argstr='-integral_multiplier %f',
desc=('integral of FOD lobe must not be outside some range as '
'determined by this multiplier and FOD lobe integral in other'
' single-fibre voxels. The range is: (mean +- (multiplier * '
'stdev)); default = 2.0. Criterion is only applied in second '
'pass of RF estimation.'))
class ResponseSDOutputSpec(TraitedSpec):
out_file = File(exists=True, desc='the output response file')
out_sf = File(desc=('mask containing single-fibre voxels'))
class ResponseSD(MRTrix3Base):
"""
Generate an appropriate response function from the image data for
spherical deconvolution.
.. [1] Tax, C. M.; Jeurissen, B.; Vos, S. B.; Viergever, M. A. and
Leemans, A., Recursive calibration of the fiber response function
for spherical deconvolution of diffusion MRI data. NeuroImage,
2014, 86, 67-80
Example
-------
>>> import nipype.interfaces.mrtrix3 as mrt
>>> resp = mrt.ResponseSD()
>>> resp.inputs.in_file = 'dwi.mif'
>>> resp.inputs.in_mask = 'mask.nii.gz'
>>> resp.inputs.grad_fsl = ('bvecs', 'bvals')
>>> resp.cmdline # doctest: +ELLIPSIS +IGNORE_UNICODE
'dwi2response -fslgrad bvecs bvals -mask mask.nii.gz dwi.mif response.txt'
>>> resp.run() # doctest: +SKIP
"""
_cmd = 'dwi2response'
input_spec = ResponseSDInputSpec
output_spec = ResponseSDOutputSpec
def _list_outputs(self):
outputs = self.output_spec().get()
outputs['out_file'] = op.abspath(self.inputs.out_file)
if isdefined(self.inputs.out_sf):
outputs['out_sf'] = op.abspath(self.inputs.out_sf)
return outputs
class ACTPrepareFSLInputSpec(CommandLineInputSpec):
in_file = File(exists=True, argstr='%s', mandatory=True, position=-2,
desc='input anatomical image')
out_file = File(
'act_5tt.mif', argstr='%s', mandatory=True, position=-1,
usedefault=True, desc='output file after processing')
class ACTPrepareFSLOutputSpec(TraitedSpec):
out_file = File(exists=True, desc='the output response file')
class ACTPrepareFSL(CommandLine):
"""
Generate anatomical information necessary for Anatomically
Constrained Tractography (ACT).
Example
-------
>>> import nipype.interfaces.mrtrix3 as mrt
>>> prep = mrt.ACTPrepareFSL()
>>> prep.inputs.in_file = 'T1.nii.gz'
>>> prep.cmdline # doctest: +ELLIPSIS +IGNORE_UNICODE
'act_anat_prepare_fsl T1.nii.gz act_5tt.mif'
>>> prep.run() # doctest: +SKIP
"""
_cmd = 'act_anat_prepare_fsl'
input_spec = ACTPrepareFSLInputSpec
output_spec = ACTPrepareFSLOutputSpec
def _list_outputs(self):
outputs = self.output_spec().get()
outputs['out_file'] = op.abspath(self.inputs.out_file)
return outputs
class ReplaceFSwithFIRSTInputSpec(CommandLineInputSpec):
in_file = File(exists=True, argstr='%s', mandatory=True, position=-4,
desc='input anatomical image')
in_t1w = File(exists=True, argstr='%s', mandatory=True, position=-3,
desc='input T1 image')
in_config = File(exists=True, argstr='%s', position=-2,
desc='connectome configuration file')
out_file = File(
'aparc+first.mif', argstr='%s', mandatory=True, position=-1,
usedefault=True, desc='output file after processing')
class ReplaceFSwithFIRSTOutputSpec(TraitedSpec):
out_file = File(exists=True, desc='the output response file')
class ReplaceFSwithFIRST(CommandLine):
"""
Replace deep gray matter structures segmented with FSL FIRST in a
FreeSurfer parcellation.
Example
-------
>>> import nipype.interfaces.mrtrix3 as mrt
>>> prep = mrt.ReplaceFSwithFIRST()
>>> prep.inputs.in_file = 'aparc+aseg.nii'
>>> prep.inputs.in_t1w = 'T1.nii.gz'
>>> prep.inputs.in_config = 'mrtrix3_labelconfig.txt'
>>> prep.cmdline # doctest: +ELLIPSIS +IGNORE_UNICODE
'fs_parc_replace_sgm_first aparc+aseg.nii T1.nii.gz \
mrtrix3_labelconfig.txt aparc+first.mif'
>>> prep.run() # doctest: +SKIP
"""
_cmd = 'fs_parc_replace_sgm_first'
input_spec = ReplaceFSwithFIRSTInputSpec
output_spec = ReplaceFSwithFIRSTOutputSpec
def _list_outputs(self):
outputs = self.output_spec().get()
outputs['out_file'] = op.abspath(self.inputs.out_file)
return outputs
| bsd-3-clause |
sam-m888/gramps | gramps/plugins/drawreport/ancestortree.py | 1 | 42337 | # Gramps - a GTK+/GNOME based genealogy program
#
# Copyright (C) 2000-2007 Donald N. Allingham
# Copyright (C) 2007-2012 Brian G. Matherly
# Copyright (C) 2010 Jakim Friant
# Copyright (C) 2014 Paul Franklin
# Copyright (C) 2010-2015 Craig J. Anderson
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#
"""Reports/Graphical Reports/Ancestor Tree"""
#------------------------------------------------------------------------
#
# Python modules
#
#------------------------------------------------------------------------
#------------------------------------------------------------------------
#
# Gramps modules
#
#------------------------------------------------------------------------
from gramps.gen.const import GRAMPS_LOCALE as glocale
_ = glocale.translation.sgettext
from gramps.gen.errors import ReportError
from gramps.gen.plug.menu import (TextOption, NumberOption, BooleanOption,
EnumeratedListOption, StringOption,
PersonOption)
from gramps.gen.plug.report import Report, MenuReportOptions, stdoptions
from gramps.gen.plug.docgen import (FontStyle, ParagraphStyle, GraphicsStyle,
FONT_SANS_SERIF, PARA_ALIGN_CENTER)
from gramps.plugins.lib.libtreebase import *
from gramps.plugins.lib.librecurse import AscendPerson
from gramps.gen.proxy import CacheProxyDb
from gramps.gen.display.name import displayer as _nd
PT2CM = utils.pt2cm
#cm2pt = utils.cm2pt
#------------------------------------------------------------------------
#
# Constants
#
#------------------------------------------------------------------------
_BORN = _("birth abbreviation|b."),
_DIED = _("death abbreviation|d."),
_MARR = _("marriage abbreviation|m."),
LVL_GEN, LVL_INDX, LVL_Y = range(3)
#------------------------------------------------------------------------
#
# Box classes
#
#------------------------------------------------------------------------
class PersonBox(BoxBase):
"""
Calculates information about the box that will print on a page
"""
def __init__(self, level):
BoxBase.__init__(self)
self.boxstr = "AC2-box"
#self.level = (level[0]-1, level[1])
self.level = level
def __lt__(self, other):
return self.level[LVL_Y] < other.level[LVL_Y]
class FamilyBox(BoxBase):
"""
Calculates information about the box that will print on a page
"""
def __init__(self, level):
BoxBase.__init__(self)
self.boxstr = "AC2-fam-box"
#self.level = (level[0]-1, level[1])
self.level = level
def __lt__(self, other):
return self.level[LVL_Y] < other.level[LVL_Y]
#------------------------------------------------------------------------
#
# Titles Class(es)
#
#------------------------------------------------------------------------
class TitleN(TitleNoDisplay):
"""No Title class for the report """
def __init__(self, doc, locale):
TitleNoDisplay.__init__(self, doc, "AC2-Title-box")
self._ = locale.translation.sgettext
def calc_title(self, center):
"""Calculate the title of the report"""
#we want no text, but need a text for the TOC in a book!
self.mark_text = self._("Ancestor Graph")
self.text = ''
class TitleA(TitleBox):
"""Title class for the report """
def __init__(self, doc, locale, name_displayer):
self._nd = name_displayer
TitleBox.__init__(self, doc, "AC2-Title-box")
self._ = locale.translation.sgettext
def calc_title(self, center):
"""Calculate the title of the report"""
name = ""
if center is not None:
name = self._nd.display(center)
# feature request 2356: avoid genitive form
self.text = self._("Ancestor Graph for %s") % name
self.set_box_height_width()
#------------------------------------------------------------------------
#
# CalcItems (helper class to calculate text)
# make_ancestor_tree (main recursive functions)
#
#------------------------------------------------------------------------
class CalcItems:
""" A helper class to calculate the default box text
and text for each person / marriage
"""
def __init__(self, dbase):
_gui = GUIConnect()
self._gui = _gui
#calculate the printed lines for each box
#str = ""
#if self.get_val('miss_val'):
# str = "_____"
display_repl = _gui.get_val("replace_list")
self.__calc_l = CalcLines(dbase, display_repl, _gui.locale, _gui.n_d)
self.__blank_father = None
self.__blank_mother = None
self.__blank_father = \
self.__calc_l.calc_lines(None, None, _gui.get_val("father_disp"))
self.__blank_mother = \
self.__calc_l.calc_lines(None, None, _gui.get_val("mother_disp"))
self.center_use = _gui.get_val("center_uses")
self.disp_father = _gui.get_val("father_disp")
self.disp_mother = _gui.get_val("mother_disp")
self.disp_marr = [_gui.get_val("marr_disp")]
self.__blank_marriage = \
self.__calc_l.calc_lines(None, None, self.disp_marr)
def calc_person(self, index, indi_handle, fams_handle):
working_lines = ""
if index[1] % 2 == 0 or (index[1] == 1 and self.center_use == 0):
if indi_handle == fams_handle is None:
working_lines = self.__calc_l.calc_lines(
None, None, self._gui.get_val("father_disp"))
else:
working_lines = self.disp_father
else:
if indi_handle == fams_handle is None:
working_lines = self.__calc_l.calc_lines(
None, None, self._gui.get_val("mother_disp"))
else:
working_lines = self.disp_mother
if indi_handle == fams_handle is None:
return working_lines
else:
return self.__calc_l.calc_lines(indi_handle, fams_handle,
working_lines)
def calc_marriage(self, indi_handle, fams_handle):
if indi_handle == fams_handle is None:
return self.__blank_marriage
else:
return self.__calc_l.calc_lines(indi_handle, fams_handle,
self.disp_marr)
class MakeAncestorTree(AscendPerson):
"""
The main procedure to use recursion to make the tree based off of a person.
order of people inserted into Persons is important.
makes sure that order is done correctly.
"""
def __init__(self, dbase, canvas):
_gui = GUIConnect()
AscendPerson.__init__(self, dbase, _gui.maxgen(), _gui.fill_out())
self.database = dbase
self.canvas = canvas
self.inlc_marr = _gui.inc_marr()
self.inc_sib = _gui.inc_sib()
self.compress_tree = _gui.compress_tree()
self.center_family = None
self.lines = [None] * (_gui.maxgen() + 1)
self.max_generation = 0
self.calc_items = CalcItems(self.database)
def add_person(self, index, indi_handle, fams_handle):
""" Makes a person box and add that person into the Canvas. """
#print str(index) + " add_person " + str(indi_handle)
myself = PersonBox((index[0] - 1,) + index[1:])
if index[LVL_GEN] == 1: # Center Person
self.center_family = fams_handle
if index[LVL_GEN] > self.max_generation:
self.max_generation = index[LVL_GEN]
myself.text = self.calc_items.calc_person(index,
indi_handle, fams_handle)
# myself.text[0] = myself.text[0] + ' ' + repr(index) # for debugging
if indi_handle is not None: # None is legal for an empty box
myself.add_mark(self.database,
self.database.get_person_from_handle(indi_handle))
self.canvas.add_box(myself)
#make the lines
indx = index[LVL_GEN]
self.lines[indx] = myself
if indx > 1:
if self.lines[indx - 1].line_to is None:
line = LineBase(self.lines[indx - 1])
self.lines[indx - 1].line_to = line
self.canvas.add_line(line)
else:
line = self.lines[indx - 1].line_to
line.add_to(myself)
return myself
def add_person_again(self, index, indi_handle, fams_handle):
self.add_person(index, indi_handle, fams_handle)
def add_marriage(self, index, indi_handle, fams_handle):
""" Makes a marriage box and add that person into the Canvas. """
if not self.inlc_marr:
return
myself = FamilyBox((index[0] - 1,) + index[1:])
#calculate the text.
myself.text = self.calc_items.calc_marriage(indi_handle, fams_handle)
self.canvas.add_box(myself)
def y_index(self, x_level, index):
""" Calculate the column or generation that this person is in.
x_level -> 0 to max_gen-1
index -> 1 to (self.max_generation**2)-1
"""
#Calculate which row in the column of people.
tmp_y = index - (2**x_level)
#Calculate which row in the table (yes table) of people.
delta = (2**self.max_generation) // (2**(x_level))
return int((delta / 2) + (tmp_y * delta)) - 1
def do_y_indx(self):
''' Make the y_index for all boxes
first off of a forumula, then remove blank areas around the edges,
then compress the tree if desired
'''
min_y = self.y_index(self.canvas.boxes[0].level[LVL_GEN],
self.canvas.boxes[0].level[LVL_INDX])
for box in self.canvas.boxes:
if "fam" in box.boxstr:
box.level = box.level + \
(self.y_index(box.level[LVL_GEN] - 1,
int(box.level[LVL_INDX] / 2)),)
else:
box.level = box.level + \
(self.y_index(box.level[LVL_GEN], box.level[LVL_INDX]),)
min_y = min(min_y, box.level[LVL_Y])
#print (str(box.level))
#if a last father (of fathers) does not have a father/parents
#Then there could be a gap. Remove this gap
if min_y > 0:
for box in self.canvas.boxes:
box.level = box.level[:LVL_Y] + (box.level[LVL_Y] - min_y,)
#Now that we have y_index, lets see if we need to squish the tree
self.canvas.boxes.sort() # Sort them on the y_index
if not self.compress_tree:
return
#boxes are already in top down [LVL_Y] form so lets
#set the box in the correct y level depending on compress_tree
y_level = 0
current_y = self.canvas.boxes[0].level[LVL_Y]
for box in self.canvas.boxes:
y_index = box.level[LVL_Y]
if y_index > current_y:
current_y = y_index
y_level += 1
box.level = box.level[:LVL_Y] + (y_level,)
def do_sibs(self):
if not self.inc_sib or self.center_family is None:
return
family = self.database.get_family_from_handle(self.center_family)
mykids = [kid.ref for kid in family.get_child_ref_list()]
if len(mykids) == 1: # No other siblings. Don't do anything.
return
# The first person is the center person had he/she has our information
center = self.canvas.boxes.pop(self.canvas.boxes.index(self.lines[1]))
line = center.line_to
level = center.level[LVL_Y]
move = level - (len(mykids) // 2) + ((len(mykids) + 1) % 2)
if move < 0:
# more kids than parents. ran off the page. Move them all down
for box in self.canvas.boxes:
box.level = (box.level[0], box.level[1], box.level[2] - move)
move = 0
line.start = []
rrr = -1 # if len(mykids)%2 == 1 else 0
for kid in mykids:
rrr += 1
mee = self.add_person((1, 1, move + rrr), kid, self.center_family)
line.add_from(mee)
#mee.level = (0, 1, level - (len(mykids)//2)+rrr)
mee.line_to = line
def start(self, person_id):
""" go ahead and make it happen """
center = self.database.get_person_from_gramps_id(person_id)
if center is None:
raise ReportError(
_("Person %s is not in the Database") % person_id)
center_h = center.get_handle()
#Step 1. Get the people
self.recurse(center_h)
#Step 2. Calculate the y_index for everyone
self.do_y_indx()
#Step 3. Siblings of the center person
self.do_sibs()
#------------------------------------------------------------------------
#
# Transform Classes
#
#------------------------------------------------------------------------
#------------------------------------------------------------------------
# Class lr_Transform
#------------------------------------------------------------------------
class LRTransform:
"""
setup all of the boxes on the canvas in for a left/right report
"""
def __init__(self, canvas, max_generations):
self.canvas = canvas
self.rept_opts = canvas.report_opts
self.y_offset = (self.rept_opts.littleoffset * 2 +
self.canvas.title.height)
def _place(self, box):
""" put the box in it's correct spot """
#1. cm_x
box.x_cm = self.rept_opts.littleoffset
box.x_cm += (box.level[LVL_GEN] *
(self.rept_opts.col_width + self.rept_opts.max_box_width))
#2. cm_y
box.y_cm = self.rept_opts.max_box_height + self.rept_opts.box_pgap
box.y_cm *= box.level[LVL_Y]
box.y_cm += self.y_offset
#if box.height < self.rept_opts.max_box_height:
# box.y_cm += ((self.rept_opts.max_box_height - box.height) /2)
def place(self):
""" Step through boxes so they can be put in the right spot """
#prime the pump
self.__last_y_level = self.canvas.boxes[0].level[LVL_Y]
#go
for box in self.canvas.boxes:
self._place(box)
#------------------------------------------------------------------------
#
# class make_report
#
#------------------------------------------------------------------------
class MakeReport:
def __init__(self, dbase, doc, canvas, font_normal):
self.database = dbase
self.doc = doc
self.canvas = canvas
self.font_normal = font_normal
_gui = GUIConnect()
self.inlc_marr = _gui.inc_marr()
self.compress_tree = _gui.compress_tree()
self.mother_ht = self.father_ht = 0
self.max_generations = 0
def get_height_width(self, box):
"""
obtain width information for each level (x)
obtain height information for each item
"""
self.canvas.set_box_height_width(box)
if box.width > self.canvas.report_opts.max_box_width:
self.canvas.report_opts.max_box_width = box.width # + box.shadow
if box.level[LVL_Y] > 0:
if box.level[LVL_INDX] % 2 == 0 and box.height > self.father_ht:
self.father_ht = box.height
elif box.level[LVL_INDX] % 2 == 1 and box.height > self.mother_ht:
self.mother_ht = box.height
if box.level[LVL_GEN] > self.max_generations:
self.max_generations = box.level[LVL_GEN]
def get_generations(self):
return self.max_generations
def start(self):
# __gui = GUIConnect()
# 1.
#set the sizes for each box and get the max_generations.
self.father_ht = 0.0
self.mother_ht = 0.0
for box in self.canvas.boxes:
self.get_height_width(box)
if self.compress_tree and not self.inlc_marr:
self.canvas.report_opts.max_box_height = \
min(self.father_ht, self.mother_ht)
else:
self.canvas.report_opts.max_box_height = \
max(self.father_ht, self.mother_ht)
#At this point we know everything we need to make the report.
#Size of each column of people - self.rept_opt.box_width
#size of each column (or row) of lines - self.rept_opt.col_width
#size of each row - self.rept_opt.box_height
#go ahead and set it now.
for box in self.canvas.boxes:
box.width = self.canvas.report_opts.max_box_width
# 2.
#setup the transform class to move around the boxes on the canvas
transform = LRTransform(self.canvas, self.max_generations)
transform.place()
class GUIConnect:
""" This is a BORG object. There is ONLY one.
This give some common routines that EVERYONE can use like
get the value from a GUI variable
"""
__shared_state = {}
def __init__(self): # We are BORG!
self.__dict__ = self.__shared_state
def set__opts(self, options, locale, name_displayer):
""" Set only once as we are BORG. """
self.__opts = options
self.locale = locale
self.n_d = name_displayer
def get_val(self, val):
""" Get a GUI value. """
value = self.__opts.get_option_by_name(val)
if value:
return value.get_value()
else:
False
def title_class(self, doc):
""" Return a class that holds the proper title based off of the
GUI options """
title_type = self.get_val('report_title')
if title_type:
return TitleA(doc, self.locale, self.n_d)
else:
return TitleN(doc, self.locale)
def inc_marr(self):
return self.get_val("inc_marr")
def inc_sib(self):
return self.get_val("inc_siblings")
def maxgen(self):
return self.get_val("maxgen")
def fill_out(self):
return self.get_val("fill_out")
def compress_tree(self):
return self.get_val("compress_tree")
#------------------------------------------------------------------------
#
# AncestorTree
#
#------------------------------------------------------------------------
class AncestorTree(Report):
""" AncestorTree Report """
def __init__(self, database, options, user):
"""
Create AncestorTree object that produces the report.
The arguments are:
database - the Gramps database instance
options - instance of the Options class for this report
user - a gen.user.User() instance
"""
Report.__init__(self, database, options, user)
self.options = options
self._user = user
self.set_locale(options.menu.get_option_by_name('trans').get_value())
stdoptions.run_date_format_option(self, options.menu)
stdoptions.run_private_data_option(self, options.menu)
stdoptions.run_living_people_option(self, options.menu, self._locale)
self.database = CacheProxyDb(self.database)
stdoptions.run_name_format_option(self, options.menu)
self._nd = self._name_display
def begin_report(self):
"""
This report needs the following parameters (class variables)
that come in the options class.
max_generations - Maximum number of generations to include.
pagebbg - Whether to include page breaks between generations.
dispf - Display format for the output box.
scale_report - Whether to scale the report to fit the width or all.
indblank - Whether to include blank pages.
compress - Whether to compress chart.
incl_private - Whether to include private data
living_people - How to handle living people
years_past_death - Consider as living this many years after death
We will
1. a canvas in its full one-page size
2. a page that we wish to print on
scale up/down either or both of the above as needed/desired.
almost all of this should be moved into Canvas!
"""
database = self.database
self.connect = GUIConnect()
self.connect.set__opts(self.options.menu, self._locale, self._nd)
#Set up the canvas that we will print on.
style_sheet = self.doc.get_style_sheet()
font_normal = style_sheet.get_paragraph_style("AC2-Normal").get_font()
#The canvas that we will put our report on and print off of
self.canvas = Canvas(self.doc,
ReportOptions(self.doc, font_normal, 'AC2-line'))
self.canvas.report_opts.box_shadow *= \
self.connect.get_val('shadowscale')
self.canvas.report_opts.box_pgap *= self.connect.get_val('box_Yscale')
self.canvas.report_opts.box_mgap *= self.connect.get_val('box_Yscale')
with self._user.progress(_('Ancestor Tree'),
_('Making the Tree...'), 4) as step:
#make the tree onto the canvas
# inlc_marr = self.connect.get_val("inc_marr")
self.max_generations = self.connect.get_val('maxgen')
tree = MakeAncestorTree(database, self.canvas)
tree.start(self.connect.get_val('pid'))
tree = None
step()
#Title
title = self.connect.title_class(self.doc)
center = self.database.get_person_from_gramps_id(
self.connect.get_val('pid'))
title.calc_title(center)
self.canvas.add_title(title)
#make the report as big as it wants to be.
report = MakeReport(database, self.doc, self.canvas, font_normal)
report.start()
self.max_generations = report.get_generations() # already know
report = None
step()
#Note?
if self.connect.get_val("inc_note"):
note_box = NoteBox(self.doc, "AC2-note-box",
self.connect.get_val("note_place"))
subst = SubstKeywords(self.database, self._locale, self._nd,
None, None)
note_box.text = subst.replace_and_clean(
self.connect.get_val('note_disp'))
self.canvas.add_note(note_box)
#Now we have the report in its full size.
#Do we want to scale the report?
one_page = self.connect.get_val("resize_page")
scale_report = self.connect.get_val("scale_tree")
scale = self.canvas.scale_report(one_page,
scale_report != 0,
scale_report == 2)
step()
if scale != 1 or self.connect.get_val('shadowscale') != 1.0:
self.scale_styles(scale)
def write_report(self):
one_page = self.connect.get_val("resize_page")
#scale_report = self.connect.get_val("scale_tree")
#inlc_marr = self.connect.get_val("inc_marr")
inc_border = self.connect.get_val('inc_border')
incblank = self.connect.get_val("inc_blank")
prnnum = self.connect.get_val("inc_pagenum")
#####################
#Setup page information
colsperpage = self.doc.get_usable_width()
colsperpage += self.canvas.report_opts.col_width
colsperpage = int(
colsperpage / (self.canvas.report_opts.max_box_width +
self.canvas.report_opts.col_width))
colsperpage = colsperpage or 1
#####################
#Vars
if prnnum:
page_num_box = PageNumberBox(self.doc, 'AC2-box', self._locale)
#TODO - Here
#####################
#ok, everyone is now ready to print on the canvas. Paginate?
self.canvas.paginate(colsperpage, one_page)
#####################
#Yeah!!!
#lets finally make some pages!!!
#####################
pages = self.canvas.page_count(incblank)
with self._user.progress(_('Ancestor Tree'),
_('Printing the Tree...'), pages) as step:
for page in self.canvas.page_iter_gen(incblank):
self.doc.start_page()
#do we need to print a border?
if inc_border:
page.draw_border('AC2-line')
#Do we need to print the page number?
if prnnum:
page_num_box.display(page)
#Print the individual people and lines
page.display()
step()
self.doc.end_page()
def scale_styles(self, scale):
"""
Scale the styles for this report.
"""
style_sheet = self.doc.get_style_sheet()
graph_style = style_sheet.get_draw_style("AC2-box")
graph_style.set_shadow(graph_style.get_shadow(),
self.canvas.report_opts.box_shadow * scale)
graph_style.set_line_width(graph_style.get_line_width() * scale)
style_sheet.add_draw_style("AC2-box", graph_style)
graph_style = style_sheet.get_draw_style("AC2-fam-box")
graph_style.set_shadow(graph_style.get_shadow(),
self.canvas.report_opts.box_shadow * scale)
graph_style.set_line_width(graph_style.get_line_width() * scale)
style_sheet.add_draw_style("AC2-fam-box", graph_style)
graph_style = style_sheet.get_draw_style("AC2-note-box")
#graph_style.set_shadow(graph_style.get_shadow(),
# self.canvas.report_opts.box_shadow * scale)
graph_style.set_line_width(graph_style.get_line_width() * scale)
style_sheet.add_draw_style("AC2-note-box", graph_style)
para_style = style_sheet.get_paragraph_style("AC2-Normal")
font = para_style.get_font()
font.set_size(font.get_size() * scale)
para_style.set_font(font)
style_sheet.add_paragraph_style("AC2-Normal", para_style)
para_style = style_sheet.get_paragraph_style("AC2-Note")
font = para_style.get_font()
font.set_size(font.get_size() * scale)
para_style.set_font(font)
style_sheet.add_paragraph_style("AC2-Note", para_style)
para_style = style_sheet.get_paragraph_style("AC2-Title")
font = para_style.get_font()
font.set_size(font.get_size() * scale)
para_style.set_font(font)
style_sheet.add_paragraph_style("AC2-Title", para_style)
graph_style = GraphicsStyle()
width = graph_style.get_line_width()
width = width * scale
graph_style.set_line_width(width)
style_sheet.add_draw_style("AC2-line", graph_style)
self.doc.set_style_sheet(style_sheet)
#------------------------------------------------------------------------
#
# AncestorTreeOptions
#
#------------------------------------------------------------------------
class AncestorTreeOptions(MenuReportOptions):
"""
Defines options and provides handling interface.
"""
def __init__(self, name, dbase):
self.__db = dbase
self.__pid = None
self.box_Y_sf = None
self.box_shadow_sf = None
MenuReportOptions.__init__(self, name, dbase)
def get_subject(self):
""" Return a string that describes the subject of the report. """
gid = self.__pid.get_value()
person = self.__db.get_person_from_gramps_id(gid)
return _nd.display(person)
def add_menu_options(self, menu):
##################
category_name = _("Tree Options")
self.__pid = PersonOption(_("Center Person"))
self.__pid.set_help(_("The center person for the tree"))
menu.add_option(category_name, "pid", self.__pid)
siblings = BooleanOption(
_('Include siblings of the center person'), False)
siblings.set_help(
_("Whether to only display the center person or all "
"of his/her siblings too"))
menu.add_option(category_name, "inc_siblings", siblings)
self.max_gen = NumberOption(_("Generations"), 10, 1, 50)
self.max_gen.set_help(_("The number of generations to include "
"in the tree"))
menu.add_option(category_name, "maxgen", self.max_gen)
self.fillout = EnumeratedListOption(_("Display unknown\ngenerations"),
0)
self.fillout.set_help(_("The number of generations of empty "
"boxes that will be displayed"))
menu.add_option(category_name, "fill_out", self.fillout)
self.max_gen.connect('value-changed', self.__fillout_vals)
self.__fillout_vals()
compress = BooleanOption(_('Compress tree'), True)
compress.set_help(
_("Whether to remove any extra blank spaces set "
"aside for people that are unknown"))
menu.add_option(category_name, "compress_tree", compress)
#better to 'Show siblings of\nthe center person
#Spouse_disp = EnumeratedListOption(_("Show spouses of\nthe center "
# "person"), 0)
#Spouse_disp.add_item(0, _("No. Do not show Spouses"))
#Spouse_disp.add_item(1, _("Yes, and use the Main Display Format"))
#Spouse_disp.add_item(2, _("Yes, and use the Secondary "
# "Display Format"))
#Spouse_disp.set_help(_("Show spouses of the center person?"))
#menu.add_option(category_name, "Spouse_disp", Spouse_disp)
##################
category_name = _("Report Options")
self.title = EnumeratedListOption(_("Report Title"), 0)
self.title.add_item(0, _("Do not include a title"))
self.title.add_item(1, _("Include Report Title"))
self.title.set_help(_("Choose a title for the report"))
menu.add_option(category_name, "report_title", self.title)
border = BooleanOption(_('Include a border'), False)
border.set_help(_("Whether to make a border around the report."))
menu.add_option(category_name, "inc_border", border)
prnnum = BooleanOption(_('Include Page Numbers'), False)
prnnum.set_help(_("Whether to print page numbers on each page."))
menu.add_option(category_name, "inc_pagenum", prnnum)
self.scale = EnumeratedListOption(_("Scale tree to fit"), 0)
self.scale.add_item(0, _("Do not scale tree"))
self.scale.add_item(1, _("Scale tree to fit page width only"))
self.scale.add_item(2, _("Scale tree to fit the size of the page"))
self.scale.set_help(
_("Whether to scale the tree to fit a specific paper size"))
menu.add_option(category_name, "scale_tree", self.scale)
self.scale.connect('value-changed', self.__check_blank)
if "BKI" not in self.name.split(","):
self.__onepage = BooleanOption(
_("Resize Page to Fit Tree size\n"
"\n"
"Note: Overrides options in the 'Paper Option' tab"
),
False)
self.__onepage.set_help(
_("Whether to resize the page to fit the size \n"
"of the tree. Note: the page will have a \n"
"non standard size.\n"
"\n"
"With this option selected, the following will happen:\n"
"\n"
"With the 'Do not scale tree' option the page\n"
" is resized to the height/width of the tree\n"
"\n"
"With 'Scale tree to fit page width only' the height of\n"
" the page is resized to the height of the tree\n"
"\n"
"With 'Scale tree to fit the size of the page' the page\n"
" is resized to remove any gap in either height or width"
))
menu.add_option(category_name, "resize_page", self.__onepage)
self.__onepage.connect('value-changed', self.__check_blank)
else:
self.__onepage = None
self.__blank = BooleanOption(_('Include Blank Pages'), True)
self.__blank.set_help(_("Whether to include pages that are blank."))
menu.add_option(category_name, "inc_blank", self.__blank)
self.__check_blank()
##################
category_name = _("Report Options (2)")
stdoptions.add_name_format_option(menu, category_name)
stdoptions.add_living_people_option(menu, category_name)
stdoptions.add_private_data_option(menu, category_name)
locale_opt = stdoptions.add_localization_option(menu, category_name)
stdoptions.add_date_format_option(menu, category_name, locale_opt)
##################
category_name = _("Display")
disp = TextOption(_("Father\nDisplay Format"),
["$n",
"%s $b" % _BORN,
"-{%s $d}" % _DIED])
disp.set_help(_("Display format for the fathers box."))
menu.add_option(category_name, "father_disp", disp)
#Will add when libsubstkeyword supports it.
#missing = EnumeratedListOption(_("Replace missing\nplaces\\dates \
# with"), 0)
#missing.add_item(0, _("Does not display anything"))
#missing.add_item(1, _("Displays '_____'"))
#missing.set_help(_("What will print when information is not known"))
#menu.add_option(category_name, "miss_val", missing)
disp_mom = TextOption(_("Mother\nDisplay Format"),
["$n",
"%s $b" % _BORN,
"%s $m" % _MARR,
"-{%s $d}" % _DIED])
disp_mom.set_help(_("Display format for the mothers box."))
menu.add_option(category_name, "mother_disp", disp_mom)
center_disp = EnumeratedListOption(_("Center person uses\n"
"which format"), 0)
center_disp.add_item(0, _("Use Fathers Display format"))
center_disp.add_item(1, _("Use Mothers display format"))
center_disp.set_help(_("The display format for the center person"))
menu.add_option(category_name, "center_uses", center_disp)
self.incmarr = BooleanOption(_('Include Marriage box'), False)
self.incmarr.set_help(
_("Whether to include a separate marital box in the report"))
menu.add_option(category_name, "inc_marr", self.incmarr)
self.incmarr.connect('value-changed', self._incmarr_changed)
self.marrdisp = StringOption(_("Marriage\nDisplay Format"),
"%s $m" % _MARR)
self.marrdisp.set_help(_("Display format for the marital box."))
menu.add_option(category_name, "marr_disp", self.marrdisp)
self._incmarr_changed()
##################
category_name = _("Advanced")
repldisp = TextOption(
_("Replace Display Format:\n'Replace this'/' with this'"),
[])
repldisp.set_help(_("i.e.\nUnited States of America/U.S.A"))
menu.add_option(category_name, "replace_list", repldisp)
# TODO this code is never used and so I conclude it is for future use
# self.__include_images = BooleanOption(
# _('Include thumbnail images of people'), False)
# self.__include_images.set_help(
# _("Whether to include thumbnails of people."))
# menu.add_option(category_name, "includeImages",
# self.__include_images)
self.usenote = BooleanOption(_('Include a note'), False)
self.usenote.set_help(_("Whether to include a note on the report."))
menu.add_option(category_name, "inc_note", self.usenote)
self.usenote.connect('value-changed', self._usenote_changed)
self.notedisp = TextOption(_("Note"), [])
self.notedisp.set_help(_("Add a note\n\n"
"$T inserts today's date"))
menu.add_option(category_name, "note_disp", self.notedisp)
locales = NoteType(0, 1)
self.notelocal = EnumeratedListOption(_("Note Location"), 0)
for num, text in locales.note_locals():
self.notelocal.add_item(num, text)
self.notelocal.set_help(_("Where to place the note."))
menu.add_option(category_name, "note_place", self.notelocal)
self._usenote_changed()
self.box_Y_sf = NumberOption(_("inter-box scale factor"),
1.00, 0.10, 2.00, 0.01)
self.box_Y_sf.set_help(
_("Make the inter-box spacing bigger or smaller"))
menu.add_option(category_name, "box_Yscale", self.box_Y_sf)
self.box_shadow_sf = NumberOption(_("box shadow scale factor"),
1.00, 0.00, 2.00, 0.01) # down to 0
self.box_shadow_sf.set_help(_("Make the box shadow bigger or smaller"))
menu.add_option(category_name, "shadowscale", self.box_shadow_sf)
def _incmarr_changed(self):
"""
If Marriage box is not enabled, disable Marriage Display Format box
"""
value = self.incmarr.get_value()
self.marrdisp.set_available(value)
def _usenote_changed(self):
"""
If Note box is not enabled, disable Note Location box
"""
value = self.usenote.get_value()
self.notelocal.set_available(value)
def __check_blank(self):
if self.__onepage:
value = not self.__onepage.get_value()
else:
value = True
off = value and (self.scale.get_value() != 2)
self.__blank.set_available(off)
def __fillout_vals(self):
max_gen = self.max_gen.get_value()
old_val = self.fillout.get_value()
item_list = []
item_list.append([0, _("No generations of empty boxes "
"for unknown ancestors")])
if max_gen > 1:
item_list.append([1, _("One Generation of empty boxes "
"for unknown ancestors")])
item_list.extend(
[itr, str(itr) +
_(" Generations of empty boxes for unknown ancestors")]
for itr in range(2, max_gen))
self.fillout.set_items(item_list)
if old_val + 2 > len(item_list):
self.fillout.set_value(len(item_list) - 2)
def make_default_style(self, default_style):
"""Make the default output style for the Ancestor Tree."""
# Paragraph Styles:
font = FontStyle()
font.set_size(9)
font.set_type_face(FONT_SANS_SERIF)
para_style = ParagraphStyle()
para_style.set_font(font)
para_style.set_description(
_('The basic style used for the text display.'))
default_style.add_paragraph_style("AC2-Normal", para_style)
box_shadow = PT2CM(font.get_size()) * .6
font = FontStyle()
font.set_size(9)
font.set_type_face(FONT_SANS_SERIF)
para_style = ParagraphStyle()
para_style.set_font(font)
para_style.set_description(
_('The basic style used for the note display.'))
default_style.add_paragraph_style("AC2-Note", para_style)
font = FontStyle()
font.set_size(16)
font.set_type_face(FONT_SANS_SERIF)
para_style = ParagraphStyle()
para_style.set_font(font)
para_style.set_alignment(PARA_ALIGN_CENTER)
para_style.set_description(_('The style used for the title.'))
default_style.add_paragraph_style("AC2-Title", para_style)
# Draw styles
graph_style = GraphicsStyle()
graph_style.set_paragraph_style("AC2-Normal")
graph_style.set_shadow(1, box_shadow) # shadow set by text size
graph_style.set_fill_color((255, 255, 255))
default_style.add_draw_style("AC2-box", graph_style)
graph_style = GraphicsStyle()
graph_style.set_paragraph_style("AC2-Normal")
#graph_style.set_shadow(0, PT2CM(9)) # shadow set by text size
graph_style.set_fill_color((255, 255, 255))
default_style.add_draw_style("AC2-fam-box", graph_style)
graph_style = GraphicsStyle()
graph_style.set_paragraph_style("AC2-Note")
graph_style.set_fill_color((255, 255, 255))
default_style.add_draw_style("AC2-note-box", graph_style)
# TODO this seems meaningless, as only the text is displayed
graph_style = GraphicsStyle()
graph_style.set_paragraph_style("AC2-Title")
graph_style.set_color((0, 0, 0))
graph_style.set_fill_color((255, 255, 255))
graph_style.set_line_width(0)
graph_style.set_description(_("Cannot edit this reference"))
default_style.add_draw_style("AC2-Title-box", graph_style)
graph_style = GraphicsStyle()
default_style.add_draw_style("AC2-line", graph_style)
#=====================================
#But even if you should suffer for what is right, you are blessed.
#"Do not fear what they fear ; do not be frightened."
#Take Courage
#1 Peter 3:14
| gpl-2.0 |
Moriadry/tensorflow | tensorflow/python/ops/control_flow_ops.py | 2 | 124140 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
"""Control Flow Operations.
See the @{$python/control_flow_ops} guide.
@@identity
@@tuple
@@group
@@no_op
@@count_up_to
@@cond
@@case
@@while_loop
@@logical_and
@@logical_not
@@logical_or
@@logical_xor
@@equal
@@not_equal
@@less
@@less_equal
@@greater
@@greater_equal
@@where
@@is_finite
@@is_inf
@@is_nan
@@verify_tensor_all_finite
@@check_numerics
@@add_check_numerics_ops
@@Assert
@@Print
"""
# pylint: disable=g-bad-name
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
import six
from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.core.protobuf import control_flow_pb2
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.framework import tensor_shape
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_array_ops
from tensorflow.python.ops import gen_control_flow_ops
from tensorflow.python.ops import gen_data_flow_ops
from tensorflow.python.ops import gen_logging_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import tensor_array_ops
# go/tf-wildcard-import
# pylint: disable=wildcard-import,undefined-variable
from tensorflow.python.ops.gen_control_flow_ops import *
# pylint: enable=wildcard-import
from tensorflow.python.platform import tf_logging as logging
from tensorflow.python.util import deprecation
from tensorflow.python.util import nest
from tensorflow.python.util import tf_should_use
# We override the 'tuple' for a control flow op, so we keep python's
# existing 'tuple' for later use in this module.
_basetuple = tuple
# pylint: disable=protected-access
# Assert and Print are special symbols in python, so we must
# use an upper-case version of them.
@tf_should_use.should_use_result
def Assert(condition, data, summarize=None, name=None):
"""Asserts that the given condition is true.
If `condition` evaluates to false, print the list of tensors in `data`.
`summarize` determines how many entries of the tensors to print.
NOTE: To ensure that Assert executes, one usually attaches a dependency:
```python
# Ensure maximum element of x is smaller or equal to 1
assert_op = tf.Assert(tf.less_equal(tf.reduce_max(x), 1.), [x])
with tf.control_dependencies([assert_op]):
... code using x ...
```
Args:
condition: The condition to evaluate.
data: The tensors to print out when condition is false.
summarize: Print this many entries of each tensor.
name: A name for this operation (optional).
Returns:
assert_op: An `Operation` that, when executed, raises a
`tf.errors.InvalidArgumentError` if `condition` is not true.
"""
with ops.name_scope(name, "Assert", [condition, data]) as name:
xs = ops.convert_n_to_tensor(data)
if all([x.dtype in {dtypes.string, dtypes.int32} for x in xs]):
# As a simple heuristic, we assume that string and int32 are
# on host to avoid the need to use cond. If it is not case,
# we will pay the price copying the tensor to host memory.
return gen_logging_ops._assert(
condition, data, summarize, name="Assert")
else:
condition = ops.convert_to_tensor(condition, name="Condition")
def true_assert():
return gen_logging_ops._assert(
condition, data, summarize, name="Assert")
guarded_assert = cond(
condition, no_op, true_assert, name="AssertGuard")
return guarded_assert.op
def _Identity(data, name=None):
"""Return a tensor with the same shape and contents as the input tensor.
Args:
data: A Tensor.
name: A name for this operation (optional).
Returns:
A Tensor with the same type and value as the input Tensor.
"""
data = ops.internal_convert_to_tensor_or_indexed_slices(data, as_ref=True)
if isinstance(data, ops.Tensor):
if data.dtype._is_ref_dtype: # pylint: disable=protected-access
return gen_array_ops._ref_identity(data, name=name)
else:
return array_ops.identity(data, name=name)
else:
if not isinstance(data, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(data))
values = _Identity(data.values, name=name)
indices = array_ops.identity(data.indices, name="indices")
if isinstance(data, ops.IndexedSlices):
dense_shape = data.dense_shape
if dense_shape is not None:
dense_shape = array_ops.identity(dense_shape, name="dense_shape")
return ops.IndexedSlices(values, indices, dense_shape)
else:
dense_shape = array_ops.identity(data.dense_shape, name="dense_shape")
return sparse_tensor.SparseTensor(indices, values, dense_shape)
def _NextIteration(data, name=None):
data = ops.internal_convert_to_tensor_or_indexed_slices(data, as_ref=True)
if isinstance(data, ops.Tensor):
if data.dtype._is_ref_dtype: # pylint: disable=protected-access
return ref_next_iteration(data, name=name)
else:
return next_iteration(data, name=name)
else:
if not isinstance(data, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(data))
values = _NextIteration(data.values, name=name)
indices = next_iteration(data.indices, name="indices")
if isinstance(data, ops.IndexedSlices):
dense_shape = data.dense_shape
if dense_shape is not None:
dense_shape = next_iteration(dense_shape, name="dense_shape")
return ops.IndexedSlices(values, indices, dense_shape)
else:
dense_shape = next_iteration(data.dense_shape, name="dense_shape")
return sparse_tensor.SparseTensor(indices, values, dense_shape)
def _Enter(data, frame_name, is_constant=False, parallel_iterations=10,
use_ref=True, use_input_shape=True, name=None):
"""Creates or finds a child frame, and makes `data` available to it.
The unique `frame_name` is used by the `Executor` to identify frames. If
`is_constant` is true, `data` is a constant in the child frame; otherwise
it may be changed in the child frame. At most `parallel_iterations`
iterations are run in parallel in the child frame.
Args:
data: The tensor to be made available to the child frame.
frame_name: The name of the child frame.
is_constant: If true, the output is constant within the child frame.
parallel_iterations: The number of iterations allowed to run in parallel.
use_ref: If true, use ref_enter if data is of ref type.
name: A name for this operation (optional).
Returns:
The same tensor as `data`.
"""
data = ops.internal_convert_to_tensor_or_indexed_slices(data, as_ref=True)
if isinstance(data, ops.Tensor):
if data.dtype._is_ref_dtype and use_ref: # pylint: disable=protected-access
result = ref_enter(data, frame_name, is_constant, parallel_iterations,
name=name)
else:
result = enter(data, frame_name, is_constant, parallel_iterations,
name=name)
if use_input_shape:
result.set_shape(data.get_shape())
return result
else:
if not isinstance(data, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(data))
values = _Enter(data.values, frame_name, is_constant,
parallel_iterations=parallel_iterations,
use_input_shape=use_input_shape, name=name)
indices = enter(data.indices, frame_name, is_constant,
parallel_iterations, name="indices")
if use_input_shape:
indices.set_shape(data.indices.get_shape())
if isinstance(data, ops.IndexedSlices):
dense_shape = data.dense_shape
if dense_shape is not None:
dense_shape = enter(dense_shape, frame_name, is_constant,
parallel_iterations, name="dense_shape")
if use_input_shape:
dense_shape.set_shape(data.dense_shape.get_shape())
return ops.IndexedSlices(values, indices, dense_shape)
else:
dense_shape = enter(data.dense_shape, frame_name, is_constant,
parallel_iterations, name="dense_shape")
if use_input_shape:
dense_shape.set_shape(data.dense_shape.get_shape())
return sparse_tensor.SparseTensor(indices, values, dense_shape)
def exit(data, name=None):
"""Exits the current frame to its parent frame.
Exit makes its input `data` available to the parent frame.
Args:
data: The tensor to be made available to the parent frame.
name: A name for this operation (optional).
Returns:
The same tensor as `data`.
"""
data = ops.internal_convert_to_tensor_or_indexed_slices(data, as_ref=True)
if isinstance(data, ops.Tensor):
if data.dtype._is_ref_dtype: # pylint: disable=protected-access
return gen_control_flow_ops._ref_exit(data, name)
else:
return gen_control_flow_ops._exit(data, name)
else:
if not isinstance(data, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(data))
values = exit(data.values, name=name)
indices = gen_control_flow_ops._exit(data.indices, name="indices")
if isinstance(data, ops.IndexedSlices):
dense_shape = data.dense_shape
if dense_shape is not None:
dense_shape = gen_control_flow_ops._exit(dense_shape, name)
return ops.IndexedSlices(values, indices, dense_shape)
else:
dense_shape = gen_control_flow_ops._exit(data.dense_shape, name)
return sparse_tensor.SparseTensor(indices, values, dense_shape)
def switch(data, pred, dtype=None, name=None):
"""Forwards `data` to an output determined by `pred`.
If `pred` is false, the `data` input is forwarded to the first output.
Otherwise, the data goes to the second output.
This op handles `Tensor`s and `IndexedSlices`.
Args:
data: The tensor to be forwarded to the appropriate output.
pred: A scalar that specifies which output port will receive data.
dtype: Optional element type for the returned tensor. If missing,
the type is inferred from the type of `value`.
name: A name for this operation (optional).
Returns:
`(output_false, output_true)`: If `pred` is true, data will be forwarded
to `output_true`, otherwise it goes to `output_false`.
"""
with ops.name_scope(name, "Switch", [data, pred]) as name:
data = ops.internal_convert_to_tensor_or_indexed_slices(
data, dtype=dtype, name="data", as_ref=True)
pred = ops.convert_to_tensor(pred, name="pred")
if isinstance(data, ops.Tensor):
return gen_control_flow_ops._switch(data, pred, name=name)
else:
if not isinstance(data, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(data))
val, ind = data.values, data.indices
val_f, val_t = gen_control_flow_ops._switch(val, pred, name=name)
ind_f, ind_t = gen_control_flow_ops._switch(ind, pred, name="indices")
if isinstance(data, ops.IndexedSlices):
dense_shape = data.dense_shape
if dense_shape is not None:
dense_shape_f, dense_shape_t = gen_control_flow_ops._switch(
dense_shape, pred, name="dense_shape")
else:
dense_shape_f, dense_shape_t = None, None
return (ops.IndexedSlices(val_f, ind_f, dense_shape_f),
ops.IndexedSlices(val_t, ind_t, dense_shape_t))
else:
dense_shape = data.dense_shape
dense_shape_f, dense_shape_t = gen_control_flow_ops._switch(
data.dense_shape, pred, name="dense_shape")
return (sparse_tensor.SparseTensor(ind_f, val_f, dense_shape_f),
sparse_tensor.SparseTensor(ind_t, val_t, dense_shape_t))
def _SwitchRefOrTensor(data, pred, name="Switch"):
"""Forwards `data` to an output determined by `pred`.
If `pred` is false, the `data` input is forwarded to the first output.
Otherwise, the data goes to the second output.
This op handles `Tensor`s and `IndexedSlices`.
Args:
data: The tensor to be forwarded to the appropriate output.
pred: A scalar that specifies which output port will receive data.
name: A name for this operation (optional).
Returns:
`(output_false, output_true)`: If `pred` is true, data will be forwarded to
`output_true`, otherwise it goes to `output_false`.
Raises:
TypeError: if data is not a Tensor or IndexedSlices
"""
data = ops.convert_to_tensor_or_indexed_slices(data, name="data")
# NOTE(vrv): ops.colocate_with(data, ignore_existing=True) below
# addresses the following scenario.
#
# Assume you execute Optimizer.apply_gradients() in a branch of a cond().
#
# 1. The update op is created inside a `with ops.colocate(var):` block
#
# 2. Some tensor `data` is captured and a switch is created in a
# `with ops.colocate_with(data):` block.
#
# with ops.colocate_with(var):
# with ops.colocate_with(data):
# op = ...
#
# var and data may be pinned to different devices, so we want to ops
# created within ops.colocate_with(data) to ignore the existing stack.
with ops.colocate_with(data, ignore_existing=True):
if isinstance(data, ops.Tensor):
if data.dtype._is_ref_dtype: # pylint: disable=protected-access
return ref_switch(data, pred, name=name)
return switch(data, pred, name=name)
def merge(inputs, name=None):
"""Returns the value of an available element of `inputs`.
This op tests each of the tensors in `inputs` in turn to determine if any of
them is available. If it finds an available tensor, it returns it and its
index in `inputs`.
It is an error if more than one tensor in `inputs` is available. If no tensor
in `inputs` is available, the returned tensor and index are not set.
This op handles both `Tensor`s and `IndexedSlices`. If inputs has a mix of
`Tensor`s and `IndexedSlices`, all inputs are converted to IndexedSlices
before merging.
Args:
inputs: The input tensors, at most one of which is available.
name: A name for this operation (optional).
Returns:
A tuple containing the chosen input tensor and its index in `inputs`.
Raises:
ValueError: If any of the inputs is None, or inputs are IndexedSlices and
some but not all have a dense_shape property.
"""
if any([inp is None for inp in inputs]):
raise ValueError("At least one of the merge inputs is None: %s" % inputs)
with ops.name_scope(name, "Merge", inputs) as name:
inputs = [ops.internal_convert_to_tensor_or_indexed_slices(inp, as_ref=True)
for inp in inputs]
if all([isinstance(v, ops.Tensor) for v in inputs]):
if all([v.dtype._is_ref_dtype for v in inputs]): # pylint: disable=protected-access
return gen_control_flow_ops._ref_merge(inputs, name)
else:
return gen_control_flow_ops._merge(inputs, name)
elif all([isinstance(v, sparse_tensor.SparseTensor) for v in inputs]):
# Only handle the case when all inputs are SparseTensor.
values, _ = merge([inp.values for inp in inputs], name=name)
indices, chosen_index = gen_control_flow_ops._merge(
[inp.indices for inp in inputs], name="indices")
dense_shape, _ = gen_control_flow_ops._merge(
[inp.dense_shape for inp in inputs], name="dense_shape")
return (sparse_tensor.SparseTensor(indices, values, dense_shape),
chosen_index)
else:
# For now convert all the inputs as IndexedSlices.
inputs = math_ops._as_indexed_slices_list(inputs, optimize=False)
values, _ = merge([inp.values for inp in inputs], name=name)
indices, chosen_index = gen_control_flow_ops._merge(
[inp.indices for inp in inputs], name="indices")
if any(inp.dense_shape is not None for inp in inputs):
if any(inp.dense_shape is None for inp in inputs):
raise ValueError("Either all merged IndexedSlices must have a "
"dense_shape, or none must have a dense_shape.")
dense_shape, _ = gen_control_flow_ops._merge(
[inp.dense_shape for inp in inputs], name="dense_shape")
else:
dense_shape = None
return ops.IndexedSlices(values, indices, dense_shape), chosen_index
# pylint: enable=protected-access
def _convert_tensorarray_to_flow(tensor_or_tensor_array):
if isinstance(tensor_or_tensor_array, tensor_array_ops.TensorArray):
return tensor_or_tensor_array.flow
else:
return tensor_or_tensor_array
def _make_tensor_array(ta, t_or_flow):
# pylint: disable=protected-access
new_ta = tensor_array_ops.TensorArray(
dtype=ta.dtype, handle=ta.handle, flow=t_or_flow,
infer_shape=ta._infer_shape,
colocate_with_first_write_call=ta._colocate_with_first_write_call)
new_ta._colocate_with = ta._colocate_with
new_ta._element_shape = ta._element_shape
# pylint: enable=protected-access
return new_ta
def _convert_flows_to_tensorarrays(tensors_or_tensorarrays, tensors_or_flows):
if len(tensors_or_tensorarrays) != len(tensors_or_flows):
raise ValueError(
"Lengths of original Tensor list and new list do not match: %d vs. %d"
% (len(tensors_or_tensorarrays), len(tensors_or_flows)))
return [
_make_tensor_array(ta, t_or_flow)
if isinstance(ta, tensor_array_ops.TensorArray)
else t_or_flow
for (ta, t_or_flow) in zip(tensors_or_tensorarrays, tensors_or_flows)]
def _IsLoopConstantEnter(op):
"""Return true iff op is a loop invariant."""
is_enter = (op.type == "Enter" or op.type == "RefEnter")
return is_enter and op.get_attr("is_constant")
def _GetLoopConstantEnter(value):
"""Return the enter op if we can infer `value` to be a loop invariant."""
id_ops = {"Switch", "RefSwitch", "Identity", "RefIdentity"}
op = value.op
while op.type in id_ops:
op = op.inputs[0].op
return op if _IsLoopConstantEnter(op) else None
def _GetOutputContext(op):
"""Return the control flow context for the output of an op."""
ctxt = op._get_control_flow_context()
if IsLoopExit(op):
ctxt = ctxt.outer_context
return ctxt
def _ShapeLessThanOrEqual(shape1, shape2):
if shape2.dims is None:
return True
if shape1.ndims != shape2.ndims:
return False
for dim1, dim2 in zip(shape1.dims, shape2.dims):
if dim2.value is not None and dim1.value != dim2.value:
return False
return True
def _SetShapeInvariants(input_vars, enter_vars, shapes):
"""Set the shapes of the tensors in `enter_vars` to `shapes`.
Args:
input_vars: A list of tensors that are inputs to `enter_vars`.
enter_vars: A list of tensors whose shapes will be set.
shapes: A (possibly nested) list of shapes.
Raises:
ValueError: If any tensor in `enter_vars` has a less specific shape
than its corresponding shape in `shapes`.
"""
if shapes is None:
return
flat_shapes = nest.flatten(shapes)
if not all([isinstance(s, tensor_shape.TensorShape) for s in flat_shapes]):
raise ValueError("`shapes` must be a (possibly nested) list of shapes.")
# Check that the shapes of the inputs are less than the shape invariants,
# and set the shapes of `enter_vars` to the shape invariants.
for inp, var, shape in zip(input_vars, enter_vars, flat_shapes):
if isinstance(var, ops.Tensor):
if not _ShapeLessThanOrEqual(inp.get_shape(), shape):
raise ValueError(
"The shape invariant specified for %s is not compatible with "
"the initial shape of the loop variable. It enters the loop "
"with shape %s, but the specified shape invariant is %s."
% (inp.name, inp.get_shape(), shape))
var.set_shape(shape)
else:
if not isinstance(var, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(var))
if isinstance(var, ops.IndexedSlices):
if not _ShapeLessThanOrEqual(inp.values.get_shape(), shape):
raise ValueError(
"The shape invariant specified for %s is not compatible with "
"the initial shape of the values tensor of this IndexedSlices. "
"It enters the loop with shape %s, but the specified shape "
"invariant is %s."
% (inp.values.name, inp.values.get_shape(), shape))
var.values.set_shape(shape)
var.indices.set_shape(tensor_shape.TensorShape([shape[0]]))
if var.dense_shape is not None:
var.dense_shape.set_shape(tensor_shape.TensorShape([shape.ndims]))
else:
if not _ShapeLessThanOrEqual(inp.dense_shape.get_shape(), shape):
raise ValueError(
"The shape invariant specified for %s is not compatible with "
"the initial shape of the shape tensor of this SparseTensor. "
"It enters the loop with shape %s, but the specified shape "
"invariant is %s."
% (inp.dense_shape.name, inp.dense_shape.get_shape(), shape))
var.values.set_shape(tensor_shape.TensorShape([None]))
var.indices.set_shape(tensor_shape.TensorShape([None, shape.ndims]))
var.dense_shape.set_shape(shape)
def _EnforceShapeInvariant(merge_var, next_var):
"""Check if the shapes of the loops variables are invariants.
Args:
merge_vars: The list of tensors representing the initial values of the
loop variables.
next_vars: The list of tensors representing the values of the loop
variables after one loop iteration.
Raises:
ValueError: If any tensor in `merge_vars` has a more specific shape than
its correspnding tensor in `next_var`.
"""
if isinstance(merge_var, ops.Tensor):
m_shape = merge_var.get_shape()
n_shape = next_var.get_shape()
if not _ShapeLessThanOrEqual(n_shape, m_shape):
raise ValueError(
"The shape for %s is not an invariant for the loop. It enters "
"the loop with shape %s, but has shape %s after one iteration. "
"Provide shape invariants using either the `shape_invariants` "
"argument of tf.while_loop or set_shape() on the loop variables."
% (merge_var.name, m_shape, n_shape))
else:
if not isinstance(var, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(var))
if isinstance(var, ops.IndexedSlices):
m_values_shape = merge_var.values.get_shape()
m_indices_shape = merge_var.indices.get_shape()
m_shape_shape = tensor_shape.TensorShape(None)
if merge_var.dense_shape is not None:
m_shape_shape = merge_var.dense_shape.get_shape()
n_values_shape = next_var.values.get_shape()
n_indices_shape = next_var.indices.get_shape()
n_shape_shape = tensor_shape.TensorShape(None)
if next_var.dense_shape is not None:
n_shape_shape = next_var.dense_shape.get_shape()
if (not _ShapeLessThanOrEqual(n_values_shape, m_values_shape) or
not _ShapeLessThanOrEqual(n_indices_shape, m_indices_shape)):
if not _ShapeLessThanOrEqual(n_values_shape, m_values_shape):
raise ValueError(
"The shape for %s is not an invariant for the loop. It enters "
"the loop with shape (%s, %s, %s), but has shape (%s, %s, %s) "
"after one iteration. Provide shape invariants using either the "
"`shape_invariants` argument of tf.while_loop or set_shape() "
"on the loop variables."
% (merge_var.name, m_values_shape, m_indices_shape, m_shape_shape,
n_values_shape, n_indices_shape, n_shape_shape))
else:
m_values_shape = merge_var.values.get_shape()
m_indices_shape = merge_var.indices.get_shape()
m_shape_shape = merge_var.dense_shape.get_shape()
n_values_shape = next_var.values.get_shape()
n_indices_shape = next_var.indices.get_shape()
n_shape_shape = next_var.dense_shape.get_shape()
if (not _ShapeLessThanOrEqual(n_values_shape, m_values_shape) or
not _ShapeLessThanOrEqual(n_indices_shape, m_indices_shape) or
not _ShapeLessThanOrEqual(n_shape_shape, m_shape_shape)):
raise ValueError(
"The shape for %s is not an invariant for the loop. It enters "
"the loop with shape (%s, %s, %s), but has shape (%s, %s, %s) "
"after one iteration. Provide shape invariants using either "
"the `shape_invariants` argument of tf.while_loop or set_shape() "
"on the loop variables."
% (merge_var.name, m_values_shape, m_indices_shape, m_shape_shape,
n_values_shape, n_indices_shape, n_shape_shape))
def _AddNextAndBackEdge(m, v):
"""Add NextIteration and back edge from v to m."""
if isinstance(m, ops.Tensor):
v = ops.convert_to_tensor(v)
v = _NextIteration(v)
m.op._update_input(1, v) # pylint: disable=protected-access
elif isinstance(m, ops.IndexedSlices):
# pylint: disable=protected-access
v = math_ops._as_indexed_slices(v, optimize=False)
v = _NextIteration(v)
m.values.op._update_input(1, v.values)
m.indices.op._update_input(1, v.indices)
# pylint: enable=protected-access
if m.dense_shape is not None:
if v.dense_shape is None:
raise ValueError("Must have dense shape: %s" % v.name)
m.dense_shape.op._update_input(1, v.dense_shape)
elif isinstance(m, sparse_tensor.SparseTensor):
if not isinstance(v, sparse_tensor.SparseTensor):
raise ValueError("Must be a sparse tensor: %s" % v.name)
v = _NextIteration(v)
# pylint: disable=protected-access
m.values.op._update_input(1, v.values)
m.indices.op._update_input(1, v.indices)
m.dense_shape.op._update_input(1, v.dense_shape)
# pylint: enable=protected-access
else:
raise TypeError("Type %s not supported" % type(m))
return v
class GradLoopState(object):
"""The state used for constructing the gradient graph for a while loop.
We create a GradLoopState for each while loop in forward and its
corresponding while loop in backprop. This gives us access to both
the forward and the backprop WhileContexts.
During the construction of gradient graph, any time when we detect
a forward value that is needed for backprop, we create a history
accumulator and add it to `history_map`. Any time when we backprop
a loop switch op (in _SwitchGrad), we add the grad merge op in
`switch_map`.
"""
def __init__(self, forward_ctxt, outer_grad_state):
# The grad loop state for the outer while loop.
self._outer_grad_state = None
# The while loop context for forward.
self._forward_context = None
# The loop counter added by AddForwardLoopCounter. It is the value
# of the loop counter for the next iteration.
self._forward_index = None
# A sync op for forward.
self._forward_sync = None
# The while loop context for backprop.
self._grad_context = None
# The loop counter added by AddBackPropLoopCounter. It is the value
# of the loop counter for the current iteration.
self._grad_index = None
# A sync op for backprop.
self._grad_sync = None
# Information needed by backprop.
self._history_map = {}
self._switch_map = {}
self._unused_exits = []
self._deferred_exits = []
self._forward_loop_exits = list(forward_ctxt.loop_exits)
self._pending_exits_count = len(forward_ctxt.loop_exits)
self._outer_grad_state = outer_grad_state
if outer_grad_state:
outer_forward_ctxt = outer_grad_state.forward_context
else:
outer_forward_ctxt = forward_ctxt.outer_context
# Add the forward loop counter.
if outer_forward_ctxt: outer_forward_ctxt.Enter()
cnt, forward_index = forward_ctxt.AddForwardLoopCounter(outer_grad_state)
if outer_forward_ctxt: outer_forward_ctxt.Exit()
self._forward_context = forward_ctxt
self._forward_index = forward_index
# Add the backprop WhileContext, and the backprop loop counter.
if outer_grad_state:
# This is a nested loop. Remember the iteration counts for each
# execution of this inner loop.
outer_forward_ctxt.AddName(cnt.name)
history_cnt = outer_grad_state.AddForwardAccumulator(cnt)
outer_grad_ctxt = outer_grad_state.grad_context
outer_grad_ctxt.Enter()
self._grad_context = WhileContext(forward_ctxt.parallel_iterations,
forward_ctxt.back_prop,
forward_ctxt.swap_memory,
forward_ctxt.name,
self)
real_cnt = outer_grad_state.AddBackPropAccumulatedValue(history_cnt, cnt)
self._grad_index = self._grad_context.AddBackPropLoopCounter(
real_cnt, outer_grad_state)
outer_grad_ctxt.Exit()
else:
if outer_forward_ctxt: outer_forward_ctxt.Enter()
self._grad_context = WhileContext(forward_ctxt.parallel_iterations,
forward_ctxt.back_prop,
forward_ctxt.swap_memory,
forward_ctxt.name,
self)
self._grad_index = self._grad_context.AddBackPropLoopCounter(
cnt, outer_grad_state)
if outer_forward_ctxt: outer_forward_ctxt.Exit()
@property
def outer_grad_state(self):
"""The grad loop state for outer loop."""
return self._outer_grad_state
@property
def forward_context(self):
"""The while loop context for forward."""
return self._forward_context
@property
def forward_index(self):
"""The loop index of forward loop."""
return self._forward_index
@property
def forward_sync(self):
"""A control trigger node for synchronization in the forward loop.
One main use is to keep the push ops of a stack executed in the
iteration order.
"""
if self._forward_sync is None:
with ops.control_dependencies(None):
self._forward_sync = control_trigger(name="f_sync")
self._forward_sync._set_control_flow_context(self._forward_context)
self._forward_index.op._add_control_input(self._forward_sync)
return self._forward_sync
@property
def grad_context(self):
"""The corresponding WhileContext for gradient."""
return self._grad_context
@property
def grad_index(self):
"""The loop index of backprop loop."""
return self._grad_index
@property
def grad_sync(self):
"""A control trigger node for synchronization in the grad loop.
One main use is to keep the pop ops of a stack executed in the
iteration order.
"""
if self._grad_sync is None:
with ops.control_dependencies(None):
self._grad_sync = control_trigger(name="b_sync")
self._grad_sync._set_control_flow_context(self._grad_context)
self._grad_index.op._add_control_input(self._grad_sync)
return self._grad_sync
@property
def history_map(self):
"""The map that records all the tensors needed for backprop."""
return self._history_map
@property
def switch_map(self):
"""The map that records all the Switch ops for the while loop."""
return self._switch_map
@property
def unused_exits(self):
"""The list of "unused" exits."""
return self._unused_exits
@property
def deferred_exits(self):
"""The list of "deferred" exits."""
return self._deferred_exits
@property
def forward_loop_exits(self):
"""The list of exits of the forward loop."""
return self._forward_loop_exits
@property
def pending_exits_count(self):
"""The number of exits we expect to see but haven't."""
return self._pending_exits_count
@pending_exits_count.setter
def pending_exits_count(self, cnt):
"""Set the pending count to cnt."""
self._pending_exits_count = cnt
def AddForwardAccumulator(self, value, dead_branch=False):
"""Add an accumulator for each forward tensor that is needed in backprop.
This is added to the forward loop at the first time when a tensor
in the forward loop is used by backprop gradient computation loop.
We create an accumulator that accumulates the value of tensor at each
iteration. Called in the control flow context where gradients() is called.
The pseudocode is:
```
acc = stack();
while (_pivot) {
acc = stack_push(acc, value);
}
```
We make sure that the stack push op in one iteration is executed before
next iteration. This is achieved by adding a control edge from
`forward_index.op.inputs[0].op` to the push op, and another control
edge from the push op to either `forward_index.op` or `forward_sync`.
Args:
value: The source tensor in forward that is to be accumulated.
dead_branch: True iff the tensor is on a dead branch of a cond.
Returns:
The stack that contains the accumulated history of the tensor.
Raises:
TypeError: For internal errors involving the value condition context.
"""
curr_ctxt = ops.get_default_graph()._get_control_flow_context()
with ops.control_dependencies(None):
if curr_ctxt: curr_ctxt.Enter()
with ops.colocate_with(value):
# pylint: disable=protected-access
acc = gen_data_flow_ops._stack(value.dtype.base_dtype, name="f_acc")
# pylint: enable=protected-access
if curr_ctxt: curr_ctxt.Exit()
# Make acc available in the forward context.
enter_acc = self.forward_context.AddValue(acc)
# Add the stack_push op in the context of value.op.
swap_enabled = self.forward_context.swap_memory
value_ctxt = _GetOutputContext(value.op)
if value_ctxt == self.forward_context:
# value is not nested in the forward context.
self.forward_context.Enter()
push = gen_data_flow_ops._stack_push(
enter_acc, value, swap_memory=swap_enabled)
self.forward_context.Exit()
# Protect stack push and order it before forward_index.
self.forward_index.op._add_control_input(push.op)
else:
# value is in a cond context within the forward context.
if not isinstance(value_ctxt, CondContext):
raise TypeError(
"value_ctxt is not a CondContext: %s" % value_ctxt)
if dead_branch:
# The special case for creating a zero tensor for a dead
# branch of a switch. See ControlFlowState.ZerosLike().
value_ctxt.outer_context.Enter()
push = gen_data_flow_ops._stack_push(
enter_acc, value, swap_memory=swap_enabled)
value_ctxt.outer_context.Exit()
push.op._set_control_flow_context(value_ctxt)
else:
value_ctxt.Enter()
push = gen_data_flow_ops._stack_push(
enter_acc, value, swap_memory=swap_enabled)
value_ctxt.Exit()
# Protect stack push and order it before forward_sync.
self.forward_sync._add_control_input(push.op)
# Order stack push after the successor of forward_index
add_op = self.forward_index.op.inputs[0].op
push.op._add_control_input(add_op)
return acc
def AddBackPropAccumulatedValue(self, history_value, value,
dead_branch=False):
"""Add the getter for an accumulated value in the grad context.
This is added to the backprop loop. Called in the grad context to
get the value of an accumulated value. The stack pop op must be guarded
by the pred of the controlling cond.
Args:
history_value: The history (a stack) of a value.
value: The value that is pushed onto the stack.
dead_branch: True iff the tensor is on a dead branch of a cond.
Returns:
The current value (the top of the stack).
"""
history_ctxt = history_value.op._get_control_flow_context()
# Find the cond context that controls history_value if any.
cond_ctxt = None
value_ctxt = value.op._get_control_flow_context()
while value_ctxt and value_ctxt != history_ctxt:
if isinstance(value_ctxt, CondContext):
cond_ctxt = value_ctxt
break
value_ctxt = value_ctxt.outer_context
with ops.control_dependencies(None):
self.grad_context.Enter()
if cond_ctxt:
# Guard stack pop with a switch if it is controlled by a cond.
grad_state = self
pred = None
while pred is None and grad_state:
pred = grad_state.history_map.get(cond_ctxt.pred.name)
grad_state = grad_state.outer_grad_state
if pred is None:
pred = cond_ctxt.pred
branch = (1 - cond_ctxt.branch) if dead_branch else cond_ctxt.branch
history_value = _SwitchRefOrTensor(history_value, pred)[branch]
pop = gen_data_flow_ops._stack_pop(history_value, value.dtype.base_dtype)
pop.set_shape(value.get_shape())
self.grad_context.Exit()
parallel_iterations = self.grad_context.parallel_iterations
if parallel_iterations > 1:
# All pops are ordered after pivot_for_body and before grad_sync.
self.grad_sync._add_control_input(pop.op)
return pop
def GetRealValue(self, value):
"""Get the real value of `value`.
If backprop "uses" a value produced by forward inference, an accumulator
is added in the forward loop to accumulate its values. We use the
accumulated value. This method must be called in the grad loop context.
`value` must be in forward and needed for backprop.
Args:
value: A tensor to be captured.
Returns:
The same tensor obtained from the saved history.
"""
assert value.op.type not in ["Variable", "VariableV2"]
real_value = self._history_map.get(value.name)
if real_value is None:
cur_value = value
cur_grad_state = self
while True:
enter_op = _GetLoopConstantEnter(cur_value)
if enter_op:
# Special case: cur_value comes from a constant Enter node.
cur_value = enter_op.inputs[0]
cur_grad_state = cur_grad_state.outer_grad_state
if cur_grad_state is None:
# We are now outside all nested loops for this gradient(),
# so `value` is a loop invariant and there is no need to
# save the history of value. Just make cur_value to enter
# the right control flow context.
real_value = self._grad_context.AddValue(cur_value)
break
else:
# Record the history of this value in forward_ctxt.
# TODO(yuanbyu): Avoid recording constants.
self._grad_context.Exit()
history_value = cur_grad_state.AddForwardAccumulator(cur_value)
self._grad_context.Enter()
break
if real_value is None:
# Add the stack pop op in the grad context.
real_value = cur_grad_state.AddBackPropAccumulatedValue(history_value,
cur_value)
if cur_grad_state != self:
real_value = self._grad_context.AddValue(real_value)
self._history_map[value.name] = real_value
return real_value
def _GetWhileContext(op):
"""Get the WhileContext to which this op belongs."""
ctxt = op._get_control_flow_context()
if ctxt:
ctxt = ctxt.GetWhileContext()
return ctxt
class ControlFlowState(object):
"""Maintain the mapping from the loops to their grad states."""
def __init__(self):
self._map = {} # maps forward loop context to GradLoopState
def GetGradState(self, op, before):
"""Return the grad state for this op if it's in a forward loop context."""
if before and IsLoopExit(op):
forward_ctxt = op._get_control_flow_context()
forward_ctxt = forward_ctxt.outer_context
if forward_ctxt:
forward_ctxt = forward_ctxt.GetWhileContext()
else:
forward_ctxt = _GetWhileContext(op)
if forward_ctxt:
return self._map.get(forward_ctxt)
return None
def ProcessUnusedLoopExits(self, pending_count, to_ops_set):
"""Process all the "unused" loop exits.
The "unused" exits of the loops are added to `unused_exits`. An exit is
unused if its pending_count is 0. If there is an exit with real gradient,
all these deferred exits will enter the backprop loop with zero gradient.
Otherwise, they will enter the backprop loop with None. As an example,
people often write:
```
v1, _ = tf.while_loop(p, b, [x1, x2])
result = gradients(v1, x1)
```
The exit node for x2 is not included by the betweenness analysis. But we
need to backprop x2 if x2 is involved in computing v1.
Args:
pending_count: The number of backprop inputs for every op.
to_ops_set: The set of ops for ys in gradients(ys, xs)
Returns:
The set of unused loop exits that we know at this point we need
to backprop.
"""
loop_exits = []
for _, grad_state in self._map.items():
# pylint: disable=protected-access
for y in grad_state.forward_loop_exits:
if pending_count[y.op._id] == 0:
grad_state.pending_exits_count -= 1
if y.op._id not in to_ops_set:
grad_state.unused_exits.append(y)
if grad_state.pending_exits_count == 0:
loop_exits.extend(grad_state.unused_exits)
# Need to include Enters in backprop for higher-order gradients.
for y in grad_state.forward_context.loop_enters:
if pending_count[y.op._id] == 0:
pending_count[y.op._id] = 1
# pylint: enable=protected-access
return loop_exits
def EnterGradWhileContext(self, op, before):
"""Enter the WhileContext for gradient computation."""
grad_state = self.GetGradState(op, before)
if grad_state:
grad_state.grad_context.Enter()
def ExitGradWhileContext(self, op, before):
"""Exit the WhileContext for gradient computation."""
grad_state = self.GetGradState(op, before)
if grad_state:
grad_state.grad_context.Exit()
def AddWhileContext(self, op, between_op_list, between_ops):
"""Add the grad state for the while loop that op belongs to.
Note that op is an Exit, and this method must be called in
the control flow context where gradients() is called.
Note that this method modifies `between_op_list` and `between_ops`.
"""
forward_ctxt = _GetWhileContext(op)
grad_state = self._map.get(forward_ctxt)
if grad_state is None:
# This is a new while loop so create a grad state for it.
outer_forward_ctxt = forward_ctxt.outer_context
if outer_forward_ctxt:
outer_forward_ctxt = outer_forward_ctxt.GetWhileContext()
outer_grad_state = None
if outer_forward_ctxt:
outer_grad_state = self._map.get(outer_forward_ctxt)
grad_state = GradLoopState(forward_ctxt, outer_grad_state)
self._map[forward_ctxt] = grad_state
# We need to include all exits of a loop for backprop.
for loop_exit in grad_state.forward_loop_exits:
if not between_ops[loop_exit.op._id]:
between_ops[loop_exit.op._id] = True
between_op_list.append(loop_exit.op)
def ZerosLikeForExit(self, val):
"""Create zeros_like gradient for a loop exit.
If the result of a loop variable is not used but is involved in
computing the result of some needed loop variable, we create a
zero-valued tensor that is fed as gradient for the Exit node of that
loop variable. Note that val.op is an Exit, and this method must be
called in the control flow context where gradients() is called.
Args:
val: The output tensor of an Exit op.
Returns:
A zero tensor of the same shape of val.
"""
val_shape = val.get_shape()
forward_ctxt = val.op._get_control_flow_context()
outer_forward_ctxt = forward_ctxt.outer_context
if outer_forward_ctxt:
outer_forward_ctxt = outer_forward_ctxt.GetWhileContext()
outer_grad_state = None
if outer_forward_ctxt:
outer_grad_state = self._map.get(outer_forward_ctxt)
if outer_grad_state:
# This is a nested loop.
if val_shape.is_fully_defined():
# If the shape is known statically, just create a zero tensor
# with the right shape in the right context.
outer_grad_state.grad_context.Enter()
result = array_ops.zeros(val_shape.dims, val.dtype)
outer_grad_state.grad_context.Exit()
else:
# Only the shape of value is needed for backprop.
forward_ctxt.outer_context.Enter()
shape = array_ops.shape_internal(val, optimize=False)
forward_ctxt.outer_context.Exit()
# Save the shape to a stack.
history_shape = outer_grad_state.AddForwardAccumulator(shape)
# Get the shape back from the stack.
outer_grad_ctxt = outer_grad_state.grad_context
outer_grad_ctxt.Enter()
real_shape = outer_grad_state.AddBackPropAccumulatedValue(
history_shape, shape)
result = array_ops.zeros(real_shape, val.dtype)
outer_grad_ctxt.Exit()
else:
# This is not a nested loop.
if val_shape.is_fully_defined():
# If the shape is known statically, just create a zero tensor
# with the right shape.
result = array_ops.zeros(val_shape.dims, val.dtype)
else:
result = array_ops.zeros_like(val, optimize=False)
return result
def ZerosLike(self, op, index):
"""Create zeros_like for the specified output of an op.
If op is in a while loop that is part of gradients(), this method
must be called in its grad loop context.
Args:
op: A tensorflow operation.
index: the index for a specific output of the op.
Returns:
A zero tensor of the same shape of op.outputs[index].
"""
if IsLoopSwitch(op): return None
dead_branch = IsSwitch(op)
forward_ctxt = _GetWhileContext(op)
grad_state = self._map.get(forward_ctxt)
if grad_state is None:
# op is not in a while loop that is part of gradients().
return ZerosLikeOutsideLoop(op, index)
op_ctxt = op._get_control_flow_context()
val = ops.convert_to_tensor(op.outputs[index], name="tensor")
shape = val.get_shape()
if shape.is_fully_defined():
# If the shape is known statically, just create a zero tensor with
# the right shape in the grad loop context.
result = constant_op.constant(0, shape=shape.dims, dtype=val.dtype)
if dead_branch:
# op is a cond switch. Guard the zero tensor with a switch.
pred = grad_state.history_map.get(op_ctxt.pred.name)
branch = op_ctxt.branch
result = _SwitchRefOrTensor(result, pred)[1 - branch]
else:
# Unknown shape so keep a history of the shape at runtime.
if dead_branch:
# Need to add a special switch to guard the value.
pred = op_ctxt.pred
branch = op_ctxt.branch
op_ctxt.outer_context.Enter()
val = _SwitchRefOrTensor(op.inputs[0], pred)[1 - branch]
zeros_shape = array_ops.shape_internal(val, optimize=False)
op_ctxt.outer_context.Exit()
val.op._set_control_flow_context(op_ctxt)
zeros_shape.op._set_control_flow_context(op_ctxt)
else:
op_ctxt.Enter()
zeros_shape = array_ops.shape_internal(val, optimize=False)
op_ctxt.Exit()
# Add forward accumulator for shape.
grad_state.grad_context.Exit()
history_zeros_shape = grad_state.AddForwardAccumulator(
zeros_shape, dead_branch=dead_branch)
grad_state.grad_context.Enter()
# Create a zero tensor with the right shape.
shape = grad_state.AddBackPropAccumulatedValue(
history_zeros_shape, zeros_shape, dead_branch)
result = array_ops.zeros(shape, val.dtype)
return result
def PostProcessing(self):
"""Perform postprocessing at the end of gradients().
We have created the gradient graph at this point. So this function
can be used to perform any postprocessing on the gradient graph.
We currently perform the following postprocessing:
1. Patch the gradient graph if the output of a loop variable
doesn't depend on its input.
"""
for _, grad_state in self._map.items():
for _, b_merge in grad_state.switch_map.items():
if b_merge.op.inputs[0] == b_merge.op.inputs[1]:
# The value of this loop variable at iteration i+1 doesn't
# depend on its value at iteration i. So use zeros as the
# gradients for all iterations > 0.
dtype = b_merge.op.inputs[0].dtype
shape = b_merge.op.inputs[0].get_shape()
# pylint: disable=protected-access
if shape.is_fully_defined():
grad_state.grad_context.Enter()
# Create a zeros and use it for iterations > 0.
grad_val = constant_op.constant(0, dtype=dtype, shape=shape)
next_grad_val = _NextIteration(grad_val)
grad_state.grad_context.Exit()
else:
# Create a zeros in the outer grad context.
outer_grad_ctxt = grad_state.grad_context.outer_context
if outer_grad_ctxt: outer_grad_ctxt.Enter()
enter_grad_op = b_merge.op.inputs[0].op
enter_grad = enter_grad_op.inputs[0]
grad_shape = array_ops.shape_internal(enter_grad, optimize=False)
grad_val = array_ops.zeros(grad_shape)
if outer_grad_ctxt: outer_grad_ctxt.Exit()
# Use the zeros for iterations > 0.
grad_state.grad_context.Enter()
next_grad_val = _NextIteration(grad_val)
grad_state.grad_context.Exit()
b_merge.op._update_input(1, next_grad_val)
# pylint: enable=protected-access
def MaybeCreateControlFlowState(between_op_list, between_ops,
colocate_gradients_with_ops):
"""Create the state for all the while loops involved in one gradients().
We create a ControlFlowState when there are while loops involved in
gradients(). In gradients(), control flow logic is only invoked when
the ControlFlowState is not None.
Note that this method modifies `between_op_list` and `between_ops`.
"""
loop_state = None
for op in between_op_list:
if IsLoopExit(op):
if loop_state is None:
loop_state = ControlFlowState()
if colocate_gradients_with_ops:
with ops.colocate_with(op):
loop_state.AddWhileContext(op, between_op_list, between_ops)
else:
loop_state.AddWhileContext(op, between_op_list, between_ops)
return loop_state
def IsSwitch(op):
"""Return true if `op` is a Switch."""
return op.type == "Switch" or op.type == "RefSwitch"
def IsLoopExit(op):
"""Return true if `op` is an Exit."""
return op.type == "Exit" or op.type == "RefExit"
def IsLoopSwitch(op):
"""Return true if `op` is the Switch for a while loop."""
if IsSwitch(op):
ctxt = op._get_control_flow_context()
return ctxt and isinstance(ctxt, WhileContext)
return False
def ZerosLikeOutsideLoop(op, index):
"""Create zeros_like for the specified output of an op."""
val = op.outputs[index]
if not IsSwitch(op):
return array_ops.zeros_like(val, optimize=False)
else:
op_ctxt = op._get_control_flow_context()
if op_ctxt:
# We are in a cond context. Use a switch to create zeros only when needed.
pred = op_ctxt.pred
branch = op_ctxt.branch
switch_val = switch(op.inputs[0], pred)[1 - branch]
zeros_shape = array_ops.shape_internal(switch_val, optimize=False)
return array_ops.zeros(zeros_shape, dtype=val.dtype)
else:
return array_ops.zeros_like(val, optimize=False)
class ControlFlowContext(object):
"""The base class for control flow context.
The usage pattern is a sequence of (Enter, Exit) followed by a final
ExitResult.
We maintain the following state for control flow contexts during graph
construction:
1. graph has _control_flow_context: the current context used to
construct new nodes. Changed by ctxt.Enter() and ctxt.Exit()
2. op has _control_flow_context: the context to which the op belongs.
Set at the time the op is created. Immutable.
3. A ControlFlowContext has _outer_context: the context in which this
context is created. Set at the time a context is created. Immutable.
4. A ControlFlowContext has _context_stack.
Pushed and popped by ctxt.Enter() and ctxt.Exit()
"""
def __init__(self, values_def=None, import_scope=None):
self._outer_context = ops.get_default_graph()._get_control_flow_context()
self._context_stack = []
if values_def:
self._init_values_from_proto(values_def,
import_scope=import_scope)
else:
# Values that have been already seen in this context.
self._values = set()
# Values referenced by but external to this context.
self._external_values = {}
def _init_values_from_proto(self, values_def, import_scope=None):
"""Initializes values and external_values from `ValuesDef` protocol buffer.
Args:
values_def: `ValuesDef` protocol buffer.
import_scope: Optional `string`. Name scope to add.
"""
assert isinstance(values_def, control_flow_pb2.ValuesDef)
self._values = set(
ops.prepend_name_scope(value, import_scope)
for value in values_def.values)
g = ops.get_default_graph()
self._external_values = {}
for k, v in values_def.external_values.items():
k = ops.prepend_name_scope(k, import_scope)
self._external_values[k] = g.as_graph_element(
ops.prepend_name_scope(v, import_scope))
op_names = set([
op.split(":")[0]
for op in self._values - set(self._external_values.keys())
])
for op in op_names:
# pylint: disable=protected-access
g.as_graph_element(op)._set_control_flow_context(self)
# pylint: enable=protected-access
@property
def outer_context(self):
"""Return the context containing this context."""
return self._outer_context
@property
def grad_state(self):
raise NotImplementedError("Abstract method")
@property
def back_prop(self):
raise NotImplementedError("Abstract method")
def _to_proto(self, export_scope=None):
"""Converts the values to a `ValuesDef` protocol buffer.
Args:
export_scope: Optional `string`. Name scope to remove.
Returns:
A `ValuesDef` protocol buffer.
"""
values_def = control_flow_pb2.ValuesDef()
values_def.values.extend(
[ops.strip_name_scope(v, export_scope)
for v in sorted(self._values)])
for k, v in self._external_values.items():
k = ops.strip_name_scope(k, export_scope)
values_def.external_values[k] = ops.strip_name_scope(
v.name, export_scope)
return values_def
@staticmethod
def _from_proto(values_def, import_scope=None):
"""Returns a `ControlFlowContext` created from `values_def`."""
return ControlFlowContext(values_def=values_def,
import_scope=import_scope)
def AddName(self, name):
self._values.add(name)
# pylint: disable=protected-access
def Enter(self):
"""Enter this control flow context."""
graph = ops.get_default_graph()
self._context_stack.append(graph._get_control_flow_context())
graph._set_control_flow_context(self)
def Exit(self):
"""Exit this control flow context."""
graph = ops.get_default_graph()
last_context = self._context_stack.pop()
graph._set_control_flow_context(last_context)
def ExitResult(self, result):
"""Make a list of tensors available in the outer context."""
if self._outer_context:
nest.map_structure(lambda x: self._outer_context.AddName(x.name), result)
def GetWhileContext(self):
"""Return the while context containing this context."""
if self._outer_context:
return self._outer_context.GetWhileContext()
return None
def _IsInOuterContext(self, op):
op_ctxt = _GetOutputContext(op)
outer_ctxt = self.outer_context
while outer_ctxt != op_ctxt:
if outer_ctxt is None:
return False
outer_ctxt = outer_ctxt.outer_context
return True
def _RemoveExternalControlEdges(self, op):
"""Remove any external control dependency on this op."""
while_ctxt = self.GetWhileContext()
# A control input of `op` is internal if it is in the same while
# loop context as the enclosing while loop context of self.
if while_ctxt is None:
internal_control_inputs = op.control_inputs
else:
internal_control_inputs = []
for x in op.control_inputs:
ctxt = _GetOutputContext(x)
if ctxt is not None and ctxt.GetWhileContext() == while_ctxt:
internal_control_inputs.append(x)
if len(internal_control_inputs) != len(op.control_inputs):
del op.control_inputs[:]
op._add_control_inputs(internal_control_inputs)
return internal_control_inputs
# pylint: enable=protected-access
def AddInnerOp(self, op):
"""Notifies a scope about an operator added to an inner scope."""
pass
def GetControlPivot(self):
"""Returns the pivot node for this context, or None."""
return None
class CondContext(ControlFlowContext):
"""The context for the conditional construct."""
def __init__(self, pred=None, pivot=None, branch=None,
name="cond_text", context_def=None, import_scope=None):
"""Creates a `CondContext`.
Args:
pred: The `boolean` tensor for the conditional predicate.
pivot: The predicate tensor in this branch.
branch: 0 or 1 representing this branch.
name: Name of the `CondContext` python object.
context_def: Optional `ContextDef` protocol buffer to initialize the
`CondContext` object from.
import_scope: Optional `string`. Name scope to add. Only used when
initialing from protocol buffer.
"""
self._name = ops.get_default_graph().unique_name(name)
if context_def:
self._init_from_proto(context_def, import_scope=import_scope)
else:
# Initializes the default fields.
ControlFlowContext.__init__(self)
self._pred = pred # The boolean tensor for the cond predicate
self._pivot = pivot # The predicate tensor in this branch
self._branch = branch # 0 or 1 representing this branch
# Values considered to have been already seen in this context.
self._values.add(pred.name)
self._values.add(pivot.name)
def _init_from_proto(self, context_def, import_scope=None):
"""Creates a new `CondContext` from protocol buffer.
Args:
context_def: `CondContextDef` protocol buffer.
import_scope: Optional `string`. Name scope to add.
"""
assert isinstance(context_def, control_flow_pb2.CondContextDef)
# Create from context_def.
g = ops.get_default_graph()
self._name = ops.prepend_name_scope(
context_def.context_name, import_scope)
self._pred = g.as_graph_element(ops.prepend_name_scope(
context_def.pred_name, import_scope))
self._pivot = g.as_graph_element(ops.prepend_name_scope(
context_def.pivot_name, import_scope))
self._branch = context_def.branch
super(CondContext, self).__init__(values_def=context_def.values_def,
import_scope=import_scope)
@property
def name(self):
return self._name
@property
def pred(self):
return self._pred
@property
def pivot(self):
return self._pivot
@property
def branch(self):
return self._branch
@property
def grad_state(self):
if self.GetWhileContext():
return self.GetWhileContext().grad_state
return None
@property
def back_prop(self):
if self.GetWhileContext():
self.GetWhileContext().back_prop
return False
def GetControlPivot(self):
return self._pivot
def to_proto(self, export_scope=None):
"""Converts a `CondContext` to a `CondContextDef` protocol buffer.
Args:
export_scope: Optional `string`. Name scope to remove.
Returns:
A `CondContextDef` protocol buffer.
"""
if (export_scope is None or
self.name.startswith(export_scope)):
context_def = control_flow_pb2.CondContextDef()
context_def.context_name = ops.strip_name_scope(
self.name, export_scope)
context_def.pred_name = ops.strip_name_scope(
self._pred.name, export_scope)
context_def.pivot_name = ops.strip_name_scope(
self._pivot.name, export_scope)
context_def.branch = self._branch
context_def.values_def.MergeFrom(super(CondContext, self)._to_proto(
export_scope))
return context_def
else:
return None
@staticmethod
def from_proto(context_def, import_scope=None):
"""Returns a `CondContext` object created from `context_def`."""
return CondContext(context_def=context_def,
import_scope=import_scope)
def AddValue(self, val):
"""Add `val` to the current context and its outer context recursively."""
if val.name in self._values:
# Use the real value if it comes from outer context. This is needed in
# particular for nested conds.
result = self._external_values.get(val.name)
result = val if result is None else result
else:
result = val
self._values.add(val.name)
if self._outer_context:
result = self._outer_context.AddValue(val)
self._values.add(result.name)
with ops.control_dependencies(None):
result = _SwitchRefOrTensor(result, self._pred)[self._branch]
result.op.graph.prevent_fetching(result.op)
# pylint: disable=protected-access
result.op._set_control_flow_context(self)
# pylint: enable=protected-access
self._values.add(result.name)
self._external_values[val.name] = result
return result
def AddOp(self, op):
self._AddOpInternal(op)
def _AddOpInternal(self, op):
"""Add `op` to the current context."""
if not op.inputs:
# Remove any external control dependency on this op
self._RemoveExternalControlEdges(op)
# pylint: disable=protected-access
op._add_control_input(self._pivot.op)
# pylint: enable=protected-access
for x in op.outputs:
self._values.add(x.name)
else:
for index in range(len(op.inputs)):
x = op.inputs[index]
real_x = self.AddValue(x)
if real_x != x:
# pylint: disable=protected-access
op._update_input(index, real_x)
# pylint: enable=protected-access
# Remove any external control dependency on this op.
self._RemoveExternalControlEdges(op)
for x in op.outputs:
self._values.add(x.name)
# pylint: disable=protected-access
if op.graph._is_function(op.type) or op.type == "SymbolicGradient":
op._add_control_input(self._pivot.op)
# pylint: enable=protected-access
if self._outer_context or not IsLoopExit(op):
op.graph.prevent_fetching(op)
def _ProcessOutputTensor(self, val):
"""Process an output tensor of a conditional branch."""
real_val = val
if val.name not in self._values:
# Handle the special case of lambda: x
self._values.add(val.name)
if self._outer_context:
real_val = self._outer_context.AddValue(val)
self._values.add(real_val.name)
real_val = _SwitchRefOrTensor(real_val, self._pred)[self._branch]
self._external_values[val.name] = real_val
else:
external_val = self._external_values.get(val.name)
if external_val is not None:
real_val = external_val
return real_val
def _BuildCondTensor(self, v):
if isinstance(v, ops.Operation):
# Use pivot as the proxy for this op.
return with_dependencies([v], self._pivot)
elif isinstance(v, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
values = self._ProcessOutputTensor(v.values)
indices = self._ProcessOutputTensor(v.indices)
if isinstance(v, ops.IndexedSlices):
dense_shape = v.dense_shape
if dense_shape is not None:
dense_shape = self._ProcessOutputTensor(dense_shape)
return ops.IndexedSlices(values, indices, dense_shape)
else:
dense_shape = self._ProcessOutputTensor(v.dense_shape)
return sparse_tensor.SparseTensor(indices, values, dense_shape)
else:
v = nest.map_structure(_convert_tensorarray_to_flow, v)
return self._ProcessOutputTensor(ops.convert_to_tensor(v))
def BuildCondBranch(self, fn):
"""Add the subgraph defined by fn() to the graph."""
original_result = fn()
if original_result is None:
return None, None
result = nest.map_structure(self._BuildCondTensor, original_result)
if not isinstance(result, (list, _basetuple)):
result = [result]
return original_result, result
def _UnpackIfSingleton(res):
if isinstance(res, (list, _basetuple)) and len(res) == 1:
return res[0]
else:
return res
# pylint: disable=g-doc-args
@deprecation.deprecated_args(
None,
"fn1/fn2 are deprecated in favor of the true_fn/false_fn arguments.",
"fn1", "fn2")
def cond(pred, true_fn=None, false_fn=None, strict=False, name=None,
fn1=None, fn2=None):
"""Return `true_fn()` if the predicate `pred` is true else `false_fn()`.
`true_fn` and `false_fn` both return lists of output tensors. `true_fn` and
`false_fn` must have the same non-zero number and type of outputs.
Note that the conditional execution applies only to the operations defined in
`true_fn` and `false_fn`. Consider the following simple program:
```python
z = tf.multiply(a, b)
result = tf.cond(x < y, lambda: tf.add(x, z), lambda: tf.square(y))
```
If `x < y`, the `tf.add` operation will be executed and `tf.square`
operation will not be executed. Since `z` is needed for at least one
branch of the `cond`, the `tf.multiply` operation is always executed,
unconditionally.
Although this behavior is consistent with the dataflow model of TensorFlow,
it has occasionally surprised some users who expected a lazier semantics.
Note that `cond` calls `true_fn` and `false_fn` *exactly once* (inside the
call to `cond`, and not at all during `Session.run()`). `cond`
stitches together the graph fragments created during the `true_fn` and
`false_fn` calls with some additional graph nodes to ensure that the right
branch gets executed depending on the value of `pred`.
`tf.cond` supports nested structures as implemented in
`tensorflow.python.util.nest`. Both `true_fn` and `false_fn` must return the
same (possibly nested) value structure of lists, tuples, and/or named tuples.
Singleton lists and tuples form the only exceptions to this: when returned by
`true_fn` and/or `false_fn`, they are implicitly unpacked to single values.
This behavior is disabled by passing `strict=True`.
Args:
pred: A scalar determining whether to return the result of `true_fn` or
`false_fn`.
true_fn: The callable to be performed if pred is true.
false_fn: The callable to be performed if pred is false.
strict: A boolean that enables/disables 'strict' mode; see above.
name: Optional name prefix for the returned tensors.
Returns:
Tensors returned by the call to either `true_fn` or `false_fn`. If the
callables return a singleton list, the element is extracted from the list.
Raises:
TypeError: if `true_fn` or `false_fn` is not callable.
ValueError: if `true_fn` and `false_fn` do not return the same number of
tensors, or return tensors of different types.
Example:
```python
x = tf.constant(2)
y = tf.constant(5)
def f1(): return tf.multiply(x, 17)
def f2(): return tf.add(y, 23)
r = tf.cond(tf.less(x, y), f1, f2)
# r is set to f1().
# Operations in f2 (e.g., tf.add) are not executed.
```
"""
# We needed to make true_fn/false_fn keyword arguments for
# backwards-compatibility. This check exists so that we can convert back to
# having them be positional arguments.
# TODO(josh11b): Make `true_fn` and `false_fn` positional arguments after
# `fn1` and `fn2` are deleted.
if fn1 is not None:
if true_fn is not None:
raise TypeError("cond(): true_fn and fn1 may not be set simultaneously.")
true_fn = fn1
elif true_fn is None:
raise TypeError("cond(): true_fn argument required")
if fn2 is not None:
if false_fn is not None:
raise TypeError("cond(): false_fn and fn2 may not be set simultaneously.")
false_fn = fn2
elif false_fn is None:
raise TypeError("cond(): false_fn argument required")
if not callable(true_fn):
raise TypeError("true_fn must be callable.")
if not callable(false_fn):
raise TypeError("false_fn must be callable.")
with ops.name_scope(name, "cond", [pred]):
# Add the Switch to the graph.
if isinstance(pred, bool):
raise TypeError("pred must not be a Python bool")
p_2, p_1 = switch(pred, pred)
pivot_1 = array_ops.identity(p_1, name="switch_t")
pivot_2 = array_ops.identity(p_2, name="switch_f")
pred = array_ops.identity(pred, name="pred_id")
# Disable the fetching of tensors that are only on one branch of cond.
for tensor in [p_1, p_2, pivot_1, pivot_2, pred]:
tensor.op.graph.prevent_fetching(tensor.op)
# Build the graph for the true branch in a new context.
context_t = CondContext(pred, pivot_1, branch=1)
context_t.Enter()
orig_res_t, res_t = context_t.BuildCondBranch(true_fn)
if orig_res_t is None:
raise ValueError("true_fn must have a return value.")
context_t.ExitResult(res_t)
context_t.Exit()
# Build the graph for the false branch in a new context.
context_f = CondContext(pred, pivot_2, branch=0)
context_f.Enter()
orig_res_f, res_f = context_f.BuildCondBranch(false_fn)
if orig_res_f is None:
raise ValueError("false_fn must have a return value.")
context_f.ExitResult(res_f)
context_f.Exit()
if not strict:
orig_res_t = _UnpackIfSingleton(orig_res_t)
orig_res_f = _UnpackIfSingleton(orig_res_f)
# Check that the return values of the two branches have the same structure.
try:
nest.assert_same_structure(orig_res_t, orig_res_f)
except TypeError as e:
raise TypeError(
"Incompatible return types of true_fn and false_fn: {}".format(e))
except ValueError as e:
raise ValueError(
"Incompatible return values of true_fn and false_fn: {}".format(e))
# Add the final merge to the graph.
if not res_t:
raise ValueError("true_fn and false_fn must return at least one result.")
res_t_flat = nest.flatten(res_t)
res_f_flat = nest.flatten(res_f)
for x, y in zip(res_t_flat, res_f_flat):
assert ((isinstance(x, ops.IndexedSlices) and
isinstance(y, ops.IndexedSlices)) or
(isinstance(x, sparse_tensor.SparseTensor) and
isinstance(y, sparse_tensor.SparseTensor)) or
(isinstance(x, ops.Tensor) and isinstance(y, ops.Tensor)))
val_x = x if isinstance(x, ops.Tensor) else x.values
val_y = y if isinstance(y, ops.Tensor) else y.values
if val_x.dtype.base_dtype != val_y.dtype.base_dtype:
raise ValueError(
"Outputs of true_fn and false_fn must have the same type: %s, %s" %
(val_x.dtype.name, val_y.dtype.name))
merges = [merge(pair)[0] for pair in zip(res_f_flat, res_t_flat)]
merges = _convert_flows_to_tensorarrays(nest.flatten(orig_res_t), merges)
# Add to collections
ops.add_to_collection(ops.GraphKeys.COND_CONTEXT, context_t)
ops.add_to_collection(ops.GraphKeys.COND_CONTEXT, context_f)
merges = nest.pack_sequence_as(structure=orig_res_t, flat_sequence=merges)
# Singleton lists and tuples are automatically unpacked if strict == False.
if not strict:
merges = _UnpackIfSingleton(merges)
return merges
# pylint: enable=g-doc-args
def _resource_safe_shape(t):
"""Returns the shape of t or the variable it points to."""
if t.dtype == dtypes.resource:
while t.op.inputs:
t = t.op.inputs[0]
return tensor_shape.TensorShape(t.op.get_attr("shape"))
return array_ops.shape_internal(t, optimize=False)
# TODO(yuanbyu): Consider having a unified notion of context for
# not only conditionals and loops but also control dependency and
# subgraphs.
class WhileContext(ControlFlowContext):
"""The context for the loop construct."""
def __init__(self, parallel_iterations=10, back_prop=True, swap_memory=False,
name="while_context", grad_state=None, context_def=None,
import_scope=None):
""""Creates a `WhileContext`.
Args:
parallel_iterations: The number of iterations allowed to run in parallel.
back_prop: Whether backprop is enabled for this while loop.
swap_memory: Whether GPU-CPU memory swap is enabled for this loop.
name: Optional name prefix for the returned tensors.
grad_state: The gradient loop state.
context_def: Optional `WhileContextDef` protocol buffer to initialize
the `Whilecontext` python object from.
import_scope: Optional `string`. Name scope to add. Only used when
initialing from protocol buffer.
"""
if context_def:
self._init_from_proto(context_def, import_scope=import_scope)
else:
ControlFlowContext.__init__(self)
self._init_from_args(parallel_iterations, back_prop, swap_memory,
name)
# The gradient loop state.
self._grad_state = grad_state
def _init_from_args(self, parallel_iterations, back_prop, swap_memory,
name):
"""Creates a new `WhileContext` from arguments.
Args:
parallel_iterations: The number of iterations allowed to run in parallel.
back_prop: Whether backprop is enabled for this while loop.
swap_memory: Whether GPU-CPU memory swap is enabled for this loop.
name: Optional name prefix for the returned tensors.
Raises:
ValueError: If `parallel_iterations` has invalid value.
"""
if not isinstance(parallel_iterations, int) or (parallel_iterations <= 0):
raise ValueError("`parallel_iterations` must be a positive integer: "
"%s" % parallel_iterations)
self._name = ops.get_default_graph().unique_name(name)
self._parallel_iterations = parallel_iterations
self._back_prop = back_prop
self._swap_memory = swap_memory
# We use this node to control constants created by the pred lambda.
self._pivot_for_pred = None
# We use this node to control constants created by the body lambda.
self._pivot_for_body = None
# The boolean tensor for loop termination condition. Used in code
# generation for gradient computation
self._pivot = None
# The list of exit tensors for loop variables.
self._loop_exits = []
# The list of enter tensors for loop variables.
self._loop_enters = []
def _init_from_proto(self, context_def, import_scope=None):
"""Creates a new `WhileContext` from protocol buffer.
Args:
context_def: `WhileContextDef` protocol buffer.
import_scope: Optional `string`. Name scope to add.
"""
assert isinstance(context_def, control_flow_pb2.WhileContextDef)
# Create from context_def.
g = ops.get_default_graph()
self._name = ops.prepend_name_scope(
context_def.context_name, import_scope)
self._parallel_iterations = context_def.parallel_iterations
self._back_prop = context_def.back_prop
self._swap_memory = context_def.swap_memory
self._pivot_for_pred = g.as_graph_element(ops.prepend_name_scope(
context_def.pivot_for_pred_name, import_scope))
# We use this node to control constants created by the body lambda.
self._pivot_for_body = g.as_graph_element(ops.prepend_name_scope(
context_def.pivot_for_body_name, import_scope))
# The boolean tensor for loop termination condition. Used in code
# generation for gradient computation.
self._pivot = g.as_graph_element(
ops.prepend_name_scope(context_def.pivot_name, import_scope))
# The list of exit tensors for loop variables.
self._loop_exits = [g.as_graph_element(
ops.prepend_name_scope(exit_name, import_scope))
for exit_name in context_def.loop_exit_names]
# The list of enter tensors for loop variables.
self._loop_enters = [g.as_graph_element(
ops.prepend_name_scope(enter_name, import_scope))
for enter_name in context_def.loop_enter_names]
super(WhileContext, self).__init__(values_def=context_def.values_def,
import_scope=import_scope)
@property
def name(self):
return self._name
@property
def parallel_iterations(self):
"""The number of iterations allowed to run in parallel."""
return self._parallel_iterations
@property
def back_prop(self):
"""True iff backprop is enabled for this while loop."""
return self._back_prop
@property
def swap_memory(self):
"""True iff GPU-CPU memory swap is enabled for this while loop."""
return self._swap_memory
@property
def pivot(self):
"""The boolean tensor representing the loop termination condition."""
return self._pivot
@property
def loop_enters(self):
"""The list of enter tensors for loop variables."""
return self._loop_enters
@property
def loop_exits(self):
"""The list of exit tensors for loop variables."""
return self._loop_exits
@property
def grad_state(self):
"""The gradient loop state."""
return self._grad_state
def to_proto(self, export_scope=None):
"""Converts a `WhileContext` to a `WhileContextDef` protocol buffer.
Args:
export_scope: Optional `string`. Name scope to remove.
Returns:
A `WhileContextDef` protocol buffer.
"""
if (export_scope is None or
self.name.startswith(export_scope)):
context_def = control_flow_pb2.WhileContextDef()
context_def.context_name = ops.strip_name_scope(
self.name, export_scope)
context_def.parallel_iterations = self._parallel_iterations
context_def.back_prop = self._back_prop
context_def.swap_memory = self._swap_memory
context_def.pivot_for_pred_name = ops.strip_name_scope(
self._pivot_for_pred.name, export_scope)
context_def.pivot_for_body_name = ops.strip_name_scope(
self._pivot_for_body.name, export_scope)
context_def.pivot_name = ops.strip_name_scope(
self._pivot.name, export_scope)
context_def.loop_exit_names.extend(
[ops.strip_name_scope(l.name, export_scope)
for l in self._loop_exits])
context_def.loop_enter_names.extend(
[ops.strip_name_scope(l.name, export_scope)
for l in self._loop_enters])
context_def.values_def.MergeFrom(
super(WhileContext, self)._to_proto(
export_scope=export_scope))
return context_def
else:
return None
@staticmethod
def from_proto(context_def, import_scope=None):
"""Returns a `WhileContext` object created from `context_def`.
Args:
context_def: A `WhileContextDef` protocol buffer.
import_scope: Optional `string`. Name scope to add.
Returns:
A `WhileContext` Python object.
"""
return WhileContext(context_def=context_def,
import_scope=import_scope)
def GetWhileContext(self):
return self
def GetControlPivot(self):
if self._pivot_for_body is not None:
return self._pivot_for_body
return self._pivot_for_pred
def AddValue(self, val):
"""Add `val` to the current context and its outer context recursively."""
result = val
if val.name not in self._values:
self._values.add(val.name)
# If we are in a grad context and val is from its forward context,
# use GetRealValue(), which adds the logic to save the history of
# val in forward.
grad_ctxt = ops.get_default_graph()._get_control_flow_context()
if grad_ctxt:
grad_ctxt = grad_ctxt.GetWhileContext()
if grad_ctxt.grad_state:
forward_ctxt = _GetWhileContext(val.op)
if IsLoopExit(val.op):
forward_ctxt = forward_ctxt.outer_context
if forward_ctxt:
forward_ctxt = forward_ctxt.GetWhileContext()
if forward_ctxt == grad_ctxt.grad_state.forward_context:
real_val = grad_ctxt.grad_state.GetRealValue(val)
self._external_values[val.name] = real_val
return real_val
if self._outer_context is not None:
result = self._outer_context.AddValue(val)
# Create an Enter to make `result` known to this loop context.
with ops.control_dependencies(None):
enter = _Enter(result, self._name, is_constant=True,
parallel_iterations=self._parallel_iterations)
enter.graph.prevent_feeding(enter)
if self._outer_context:
self._outer_context.AddInnerOp(enter.op)
# Fix the control inputs and control flow context of these enter ops.
self._FixControlInputsAndContext([enter])
# Add `enter` in this context.
self._values.add(enter.name)
self._external_values[val.name] = enter
result = enter
else:
actual_val = self._external_values.get(val.name)
if actual_val is not None:
result = actual_val
return result
def AddOp(self, op):
"""Add `op` to the current context."""
# For a reduction op, if op is in a grad context and its input is from
# its forward context, moving op to the forward context means we would
# store the tensor after the reduction as opposed to the tensor before
# reduction, and therefore could significantly reduce memory consumption.
# For now, we do this only for a few ops.
if op.type in {"Shape", "Size", "Rank"}:
grad_ctxt = ops.get_default_graph()._get_control_flow_context()
if grad_ctxt:
grad_ctxt = grad_ctxt.GetWhileContext()
if grad_ctxt.grad_state:
op_input_forward_ctxt = _GetWhileContext(op.inputs[0].op)
if op_input_forward_ctxt == grad_ctxt.grad_state.forward_context:
op_input_ctxt = op.inputs[0].op._get_control_flow_context()
op._set_control_flow_context(op_input_ctxt)
op_input_ctxt._AddOpInternal(op)
return
self._AddOpInternal(op)
def _AddOpInternal(self, op):
"""Add `op` to the current context.
In the case that op has only external data inputs, we remove all of its
external control inputs so all its inputs are in the same while loop
context. This is valid because op now has an Enter input that has all
the right control dependency.
"""
if not op.inputs:
# Remove any external control dependency on this op
control_inputs = self._RemoveExternalControlEdges(op)
# Add a control edge from the control pivot to this op.
if not control_inputs:
# pylint: disable=protected-access
op._add_control_input(self.GetControlPivot().op)
# pylint: enable=protected-access
for x in op.outputs:
self._values.add(x.name)
else:
for index in range(len(op.inputs)):
x = op.inputs[index]
real_x = self.AddValue(x)
if real_x != x:
op._update_input(index, real_x)
# Remove any external control dependency on this op.
self._RemoveExternalControlEdges(op)
# Add a control dependency to prevent loop invariants from
# enabling ops that should not be executed.
self._MaybeAddControlDependency(op)
for x in op.outputs:
self._values.add(x.name)
if self._outer_context or not IsLoopExit(op):
op.graph.prevent_fetching(op)
for x in op.outputs:
op.graph.prevent_feeding(x)
if self._outer_context:
self._outer_context.AddInnerOp(op)
def _MaybeAddControlDependency(self, op):
"""Add a control input to the op if it only depends on loop invariants."""
def _IsOpFree(op):
"""Determines if `op` needs a control dependency."""
if op.control_inputs:
return False
# pylint: disable=protected-access
if op.graph._is_function(op.type) or op.type == "SymbolicGradient":
return True
# pylint: enable=protected-access
for x in op.inputs:
if not _IsLoopConstantEnter(x.op):
return False
return True
if _IsOpFree(op):
# pylint: disable=protected-access
op._add_control_input(self.GetControlPivot().op)
# pylint: enable=protected-access
def AddForwardLoopCounter(self, outer_grad_state):
"""Adds a loop that counts the number of iterations.
This is added to the forward loop at the time when we start to
create the loop for backprop gradient computation. Called in
the outer context of this forward context.
The pseudocode is:
`n = 0; while (_pivot) { n++; }`
Note that a control dependency is added to `n` to ensure the correct
execution order of stack push ops.
Args:
outer_grad_state: The outer grad state. None if not nested.
Returns:
The number of iterations taken by the forward loop and the loop index.
"""
n = constant_op.constant(0, name="f_count")
if outer_grad_state is not None:
# Force the stack pushes of i-th execution of an inner loop to be ordered
# before the pushes of (i+1)-th execution of the same inner loop.
outer_add_op = outer_grad_state.forward_index.op.inputs[0].op
n.op._add_control_input(outer_add_op) # pylint: disable=protected-access
self.Enter()
self.AddName(n.name)
enter_n = _Enter(n, self._name, is_constant=False,
parallel_iterations=self._parallel_iterations,
name="f_count")
self.loop_enters.append(enter_n)
merge_n = merge([enter_n, enter_n])[0]
switch_n = switch(merge_n, self._pivot)
index = math_ops.add(switch_n[1], 1)
next_n = _NextIteration(index)
merge_n.op._update_input(1, next_n)
total_iterations = exit(switch_n[0], name="f_count")
self.loop_exits.append(total_iterations)
self.ExitResult([total_iterations])
self.Exit()
return total_iterations, next_n
def AddBackPropLoopCounter(self, count, outer_grad_state):
"""Add the backprop loop that controls the iterations.
This is added to the backprop loop. It is used to control the loop
termination of the backprop loop. Called in the outer context of
this grad context.
The pseudocode is:
`n = count; while (n >= 1) { n--; }`
Note that a control dependency is added to `final_zero` to ensure the
correct execution order of stack pop ops.
Args:
count: The number of iterations for backprop.
outer_grad_state: The outer grad state. None if not nested.
Returns:
The loop index.
"""
one = constant_op.constant(1, name="b_count")
self.Enter()
self.AddName(count.name)
enter_count = _Enter(count, self._name, is_constant=False,
parallel_iterations=self._parallel_iterations,
name="b_count")
self.loop_enters.append(enter_count)
merge_count = merge([enter_count, enter_count])[0]
self._pivot_for_pred = merge_count
pred = math_ops.greater_equal(merge_count, one)
self._pivot = loop_cond(pred, name="b_count")
switch_count = switch(merge_count, self._pivot)
index = math_ops.subtract(switch_count[1], one)
self._pivot_for_body = index
next_count = _NextIteration(index)
merge_count.op._update_input(1, next_count)
final_zero = exit(switch_count[0], name="b_count")
self.loop_exits.append(final_zero)
if outer_grad_state is not None:
# Force the stack pops of i-th execution of an inner loop to be ordered
# before the pops of (i+1)-th execution of the same inner loop.
# pylint: disable=protected-access
outer_grad_state.grad_sync._add_control_input(final_zero.op)
# pylint: enable=protected-access
self.ExitResult([final_zero])
self.Exit()
return next_count
def AddBackPropAccumulator(self, op, grad):
"""Add an accumulation loop for every loop invariant.
This is added to the backprop loop. It is used to accumulate partial
gradients within each loop iteration. Called when in the gradient while
context.
The pseudocode is:
```
acc = 0.0;
while (_pivot) {
acc += grad;
}
```
Args:
op: The Enter op for a loop invariant.
grad: The partial gradient of an iteration for a loop invariant.
Returns:
The gradient for a loop invariant.
"""
self.Exit()
# Create a zeros tensor with the right shape for acc. If we don't
# know the full shape statically, we will have to get the shape
# dynamically from the forward inference. Getting the shape right
# for the zeros is only needed for the base case when the loop exits
# without running any iterations.
shape = grad.get_shape()
if shape.is_fully_defined():
if self.outer_context: self.outer_context.Enter()
acc = constant_op.constant(0, grad.dtype, shape=shape, name="b_acc")
if self.outer_context: self.outer_context.Exit()
else:
value = op.inputs[0]
if (isinstance(self.outer_context, WhileContext) and
self.outer_context.grad_state is not None):
# We are in a nested while loop.
forward_ctxt = self.grad_state.forward_context
forward_ctxt.outer_context.Enter()
zeros_shape = array_ops.shape_internal(value, optimize=False)
forward_ctxt.outer_context.Exit()
outer_grad_state = self.grad_state.outer_grad_state
history_zeros_shape = outer_grad_state.AddForwardAccumulator(
zeros_shape)
self.outer_context.Enter()
real_shape = outer_grad_state.AddBackPropAccumulatedValue(
history_zeros_shape, zeros_shape)
acc = array_ops.zeros(real_shape, grad.dtype)
self.outer_context.Exit()
else:
if self.outer_context: self.outer_context.Enter()
zeros_shape = array_ops.shape_internal(value, optimize=False)
acc = array_ops.zeros(zeros_shape, grad.dtype)
if self.outer_context: self.outer_context.Exit()
acc._shape = grad.get_shape() # pylint: disable=protected-access
self.Enter()
self.AddName(acc.name)
enter_acc = _Enter(acc, self._name, is_constant=False,
parallel_iterations=self._parallel_iterations,
name="b_acc")
self.loop_enters.append(enter_acc)
merge_acc = merge([enter_acc, enter_acc], name="b_acc")[0]
switch_acc_false, switch_acc_true = switch(merge_acc, self._pivot)
add_acc = math_ops.add(switch_acc_true, grad)
next_acc = _NextIteration(add_acc)
merge_acc.op._update_input(1, next_acc) # pylint: disable=protected-access
result_acc = exit(switch_acc_false, name="b_acc")
self.loop_exits.append(result_acc)
self.ExitResult([result_acc])
return result_acc
def AddBackPropIndexedSlicesAccumulator(self, op, grad):
"""This is used for accumulating gradients that are IndexedSlices.
This is essentially the equavalent of AddBackPropAccumulator but optimized
for things like updating embeddings from within a while loop.
Args:
op: The Enter op for a loop invariant.
grad: The partial gradients represented as an IndexedSlices.
Returns:
The accumulated IndexedSlices gradient of the loop invariant.
"""
values = grad.values
indices = grad.indices
dense_shape = grad.dense_shape
self.Exit()
if self.outer_context: self.outer_context.Enter()
if values.get_shape().is_fully_defined():
values_shape = tensor_shape.TensorShape(
[tensor_shape.Dimension(1)] + values.get_shape().dims[1:])
if self.outer_context: self.outer_context.Enter()
values_acc = constant_op.constant(0, values.dtype, shape=values_shape,
name="b_acc")
if self.outer_context: self.outer_context.Exit()
else:
values_shape = _resource_safe_shape(op.inputs[0])[1:]
values_shape = array_ops.concat([[1], values_shape], 0)
values_acc = array_ops.zeros(values_shape, dtype=values.dtype)
indices_acc = constant_op.constant([0], indices.dtype)
shape_acc = None
if dense_shape is not None:
if dense_shape.get_shape().is_fully_defined():
if self.outer_context: self.outer_context.Enter()
shape_acc = constant_op.constant(0, dense_shape.dtype,
shape=dense_shape.get_shape())
if self.outer_context: self.outer_context.Exit()
else:
shape_acc = array_ops.zeros_like(
array_ops.shape_internal(op.inputs[0], optimize=False),
optimize=False)
if self.outer_context: self.outer_context.Exit()
self.Enter()
self.AddName(values_acc.name)
self.AddName(indices_acc.name)
init_acc = [indices_acc, values_acc]
if shape_acc is not None:
self.AddName(shape_acc.name)
init_acc.append(shape_acc)
enter_acc = [_Enter(x, self._name, is_constant=False,
parallel_iterations=self._parallel_iterations,
name="b_acc") for x in init_acc]
self.loop_enters.extend(enter_acc)
merge_acc = [merge([x, x], name="b_acc")[0] for x in enter_acc]
switch_acc = [switch(x, self._pivot) for x in merge_acc]
# The actual accumulation.
acc_indexed_slices = [
array_ops.concat([xa[1], xv], 0)
for xa, xv in zip(switch_acc[:2], [indices, values])
]
if shape_acc is not None:
# For the shape we just keep the maximum
acc_indexed_slices.append(
math_ops.maximum(dense_shape, switch_acc[2][1]))
next_acc = [_NextIteration(x) for x in acc_indexed_slices]
for xm, xn in zip(merge_acc, next_acc):
xm.op._update_input(1, xn) # pylint: disable=protected-access
exit_acc = [exit(x[0], name="b_acc") for x in switch_acc]
self.loop_exits.extend(exit_acc)
self.ExitResult(exit_acc)
return ops.IndexedSlices(
indices=exit_acc[0], values=exit_acc[1],
dense_shape=exit_acc[2] if shape_acc is not None else None)
def _InitializeValues(self, values):
"""Makes the values known to this context."""
self._values = set()
for x in values:
if isinstance(x, ops.Tensor):
self._values.add(x.name)
else:
self._values.add(x.values.name)
self._values.add(x.indices.name)
if isinstance(x, ops.IndexedSlices):
dense_shape = x.dense_shape
elif isinstance(x, sparse_tensor.SparseTensor):
dense_shape = x.dense_shape
else:
raise TypeError("Type %s not supported" % type(x))
if dense_shape is not None:
self._values.add(dense_shape.name)
def _BuildLoop(self, pred, body, original_loop_vars, loop_vars,
shape_invariants):
"""Core: Add the loop termination condition and body to the graph."""
flat_loop_vars = nest.flatten(original_loop_vars)
# Let the context know the loop variables so the loop variables
# would be added in the outer contexts properly.
self._InitializeValues(loop_vars)
real_vars = loop_vars
if self._outer_context:
real_vars = [self._outer_context.AddValue(x) for x in loop_vars]
with ops.control_dependencies(None):
enter_vars = [_Enter(x, self._name, is_constant=False,
parallel_iterations=self._parallel_iterations,
use_input_shape=(shape_invariants is None))
for x in real_vars]
for x in enter_vars:
x.graph.prevent_feeding(x)
if self._outer_context:
self._outer_context.AddInnerOp(x.op)
# Finds the closest enclosing non-None control pivot.
outer_context = self._outer_context
control_pivot = None
while outer_context is not None and control_pivot is None:
control_pivot = outer_context.GetControlPivot()
# pylint: disable=protected-access
outer_context = outer_context._outer_context
# pylint: enable=protected-access
if control_pivot is not None:
for var in enter_vars:
if _IsLoopConstantEnter(var.op.inputs[0].op):
# pylint: disable=protected-access
var.op._add_control_input(control_pivot.op)
# pylint: enable=protected-access
_SetShapeInvariants(real_vars, enter_vars, shape_invariants)
# Fix the control inputs and control flow context of these enter ops.
self._FixControlInputsAndContext(enter_vars)
self._InitializeValues(enter_vars)
self._loop_enters = enter_vars
merge_vars = [merge([x, x])[0] for x in enter_vars]
self._pivot_for_pred = merge_vars[0]
# Build the graph for pred.
merge_vars_with_tensor_arrays = (
_convert_flows_to_tensorarrays(flat_loop_vars, merge_vars))
packed_vars = nest.pack_sequence_as(
structure=original_loop_vars,
flat_sequence=merge_vars_with_tensor_arrays)
c = ops.convert_to_tensor(pred(*packed_vars))
self._pivot = loop_cond(c, name="LoopCond")
switch_vars = [_SwitchRefOrTensor(x, self._pivot) for x in merge_vars]
# Build the graph for body.
vars_for_body = [_Identity(x[1]) for x in switch_vars]
self._pivot_for_body = vars_for_body[0]
# Convert TensorArray flow variables inside the context back into
# their associated TensorArrays for calling the body.
vars_for_body_with_tensor_arrays = (
_convert_flows_to_tensorarrays(flat_loop_vars, vars_for_body))
packed_vars_for_body = nest.pack_sequence_as(
structure=original_loop_vars,
flat_sequence=vars_for_body_with_tensor_arrays)
body_result = body(*packed_vars_for_body)
if not nest.is_sequence(body_result):
body_result = [body_result]
# Compare the structure types of input and output of body.
# For backwards compatibility, the first layer is forced to a list
# during this comparison, because inputs are typically lists and
# outputs of the body are typically tuples.
nest.assert_same_structure(list(packed_vars_for_body), list(body_result))
# Store body_result to keep track of TensorArrays returned by body
original_body_result = body_result
# Convert TensorArrays returned by body into their flow variables
result = nest.map_structure(_convert_tensorarray_to_flow,
nest.flatten(body_result))
result = ops.convert_n_to_tensor_or_indexed_slices(result)
# Add NextIteration and the back edges to complete the loop.
if len(merge_vars) != len(result):
raise ValueError("Number of inputs and outputs of body must match "
"loop_vars: %d, %d" % (len(merge_vars), len(result)))
next_vars = []
for m, v in zip(merge_vars, result):
next_vars.append(_AddNextAndBackEdge(m, v))
# Add the exit ops.
exit_vars = [exit(x[0]) for x in switch_vars]
self._loop_exits = exit_vars
# Make sure the shapes of loop outputs are correct.
for m_var, n_var in zip(merge_vars, next_vars):
if isinstance(m_var, ops.Tensor):
_EnforceShapeInvariant(m_var, n_var)
# Exit the loop.
self.ExitResult(exit_vars)
return original_body_result, exit_vars
def BuildLoop(self, pred, body, loop_vars, shape_invariants):
"""Add the loop termination condition and body to the graph."""
# Keep original_loop_vars to identify which are TensorArrays
original_loop_vars = loop_vars
# Convert TensorArrays to their flow variables
loop_vars = nest.map_structure(_convert_tensorarray_to_flow,
nest.flatten(loop_vars))
loop_vars = ops.convert_n_to_tensor_or_indexed_slices(loop_vars)
try:
self.Enter()
original_body_result, exit_vars = self._BuildLoop(
pred, body, original_loop_vars, loop_vars, shape_invariants)
finally:
self.Exit()
flat_result = nest.flatten(original_body_result)
# Convert TensorArray flow variables outside the context back into
# their associated TensorArrays for returning to caller.
exit_vars_with_tensor_arrays = (
_convert_flows_to_tensorarrays(flat_result, exit_vars))
packed_exit_vars = nest.pack_sequence_as(
structure=original_body_result,
flat_sequence=exit_vars_with_tensor_arrays)
return (packed_exit_vars[0] if len(exit_vars) == 1
else packed_exit_vars)
def _FixControlInputsAndContext(self, enters):
graph = ops.get_default_graph()
# pylint: disable=protected-access
for e in enters:
if isinstance(e, ops.Tensor):
xs = [e]
else:
if not isinstance(e, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
raise TypeError("Type %s not supported" % type(e))
xs = [e.values, e.indices]
shape = e.dense_shape
if shape is not None:
xs.append(shape)
for x in xs:
inp_op = x.op.inputs[0]
control_inputs = graph._control_dependencies_for_inputs([inp_op])
outer_control_inputs = [op for op in control_inputs
if self._IsInOuterContext(op)]
x.op._set_control_flow_context(self)
x.op._add_control_inputs(outer_control_inputs)
graph._record_op_seen_by_control_dependencies(x.op)
# pylint: enable=protected-access
def while_loop(cond, body, loop_vars, shape_invariants=None,
parallel_iterations=10, back_prop=True, swap_memory=False,
name=None):
"""Repeat `body` while the condition `cond` is true.
`cond` is a callable returning a boolean scalar tensor. `body` is a callable
returning a (possibly nested) tuple, namedtuple or list of tensors of the same
arity (length and structure) and types as `loop_vars`. `loop_vars` is a
(possibly nested) tuple, namedtuple or list of tensors that is passed to both
`cond` and `body`. `cond` and `body` both take as many arguments as there are
`loop_vars`.
In addition to regular Tensors or IndexedSlices, the body may accept and
return TensorArray objects. The flows of the TensorArray objects will
be appropriately forwarded between loops and during gradient calculations.
Note that `while_loop` calls `cond` and `body` *exactly once* (inside the
call to `while_loop`, and not at all during `Session.run()`). `while_loop`
stitches together the graph fragments created during the `cond` and `body`
calls with some additional graph nodes to make something the repeats
`body` until `cond` returns false.
For correctness, `tf.while_loop()` strictly enforces shape invariants for
the loop variables. A shape invariant is a (possibly partial) shape that
is unchanged across the iterations of the loop. An error will be raised
if the shape of a loop variable after an iteration is determined to be more
general than or incompatible with its shape invariant. For example, a shape
of [11, None] is more general than a shape of [11, 17], and [11, 21] is not
compatible with [11, 17]. By default (if the argument `shape_invariants` is
not specified), it is assumed that the initial shape of each tensor in
`loop_vars` is the same in every iteration. The `shape_invariants` argument
allows the caller to specify a less specific shape invariant for each loop
variable, which is needed if the shape varies between iterations. The
@{tf.Tensor.set_shape}
function may also be used in the `body` function to indicate that
the output loop variable has a particular shape. The shape invariant for
SparseTensor and IndexedSlices are treated specially as follows:
a) If a loop variable is a SparseTensor, the shape invariant must be
TensorShape([r]) where r is the rank of the dense tensor represented
by the sparse tensor. It means the shapes of the three tensors of the
SparseTensor are ([None], [None, r], [r]). NOTE: The shape invariant here
is the shape of the SparseTensor.dense_shape property. It must be the shape of
a vector.
b) If a loop variable is an IndexedSlices, the shape invariant must be
a shape invariant of the values tensor of the IndexedSlices. It means
the shapes of the three tensors of the IndexedSlices are (shape, [shape[0]],
[shape.ndims]).
`while_loop` implements non-strict semantics, enabling multiple iterations
to run in parallel. The maximum number of parallel iterations can be
controlled by `parallel_iterations`, which gives users some control over
memory consumption and execution order. For correct programs, `while_loop`
should return the same result for any parallel_iterations > 0.
For training, TensorFlow remembers the tensors that are produced in the
forward inference but needed in back propagation. These tensors can be a
main source of memory consumption and often cause OOM problems when training
on GPUs. When the flag swap_memory is true, we swap out these tensors from
GPU to CPU. This for example allows us to train RNN models with very long
sequences and large batches.
Args:
cond: A callable that represents the termination condition of the loop.
body: A callable that represents the loop body.
loop_vars: A (possibly nested) tuple, namedtuple or list of numpy array,
`Tensor`, and `TensorArray` objects.
shape_invariants: The shape invariants for the loop variables.
parallel_iterations: The number of iterations allowed to run in parallel.
It must be a positive integer.
back_prop: Whether backprop is enabled for this while loop.
swap_memory: Whether GPU-CPU memory swap is enabled for this loop.
name: Optional name prefix for the returned tensors.
Returns:
The output tensors for the loop variables after the loop. When the length
of `loop_vars` is 1 this is a Tensor, TensorArray or IndexedSlice and when
the length of `loop_vars` is greater than 1 it returns a list.
Raises:
TypeError: if `cond` or `body` is not callable.
ValueError: if `loop_vars` is empty.
Example:
```python
i = tf.constant(0)
c = lambda i: tf.less(i, 10)
b = lambda i: tf.add(i, 1)
r = tf.while_loop(c, b, [i])
```
Example with nesting and a namedtuple:
```python
import collections
Pair = collections.namedtuple('Pair', 'j, k')
ijk_0 = (tf.constant(0), Pair(tf.constant(1), tf.constant(2)))
c = lambda i, p: i < 10
b = lambda i, p: (i + 1, Pair((p.j + p.k), (p.j - p.k)))
ijk_final = tf.while_loop(c, b, ijk_0)
```
Example using shape_invariants:
```python
i0 = tf.constant(0)
m0 = tf.ones([2, 2])
c = lambda i, m: i < 10
b = lambda i, m: [i+1, tf.concat([m, m], axis=0)]
tf.while_loop(
c, b, loop_vars=[i0, m0],
shape_invariants=[i0.get_shape(), tf.TensorShape([None, 2])])
```
"""
with ops.name_scope(name, "while", loop_vars):
if not loop_vars:
raise ValueError("No loop variables provided")
if not callable(cond):
raise TypeError("cond must be callable.")
if not callable(body):
raise TypeError("body must be callable.")
if parallel_iterations < 1:
raise TypeError("parallel_iterations must be a positive integer.")
if shape_invariants is not None:
nest.assert_same_structure(loop_vars, shape_invariants)
context = WhileContext(parallel_iterations, back_prop, swap_memory)
ops.add_to_collection(ops.GraphKeys.WHILE_CONTEXT, context)
result = context.BuildLoop(cond, body, loop_vars, shape_invariants)
return result
def _AsTensorList(x, p):
"""Return x as a list of Tensors or IndexedSlices.
For entries of `x` that are Operations, this returns an Identity of `p`
with a dependency on the operation.
Args:
x: A Tensor/IndexedSlices/Operation or a list or tuple of them.
p: A Tensor to return for entries in `x` that are Operations.
Returns:
A list of Tensors or IndexedSlices.
"""
if not isinstance(x, (list, _basetuple)):
x = [x]
l = []
for v in x:
if isinstance(v, ops.Operation):
v = with_dependencies([v], p)
v = ops.convert_to_tensor_or_indexed_slices(v)
if isinstance(v, ops.Tensor):
l.append(array_ops.identity(v))
else:
l.append(ops.IndexedSlices(array_ops.identity(v.values),
array_ops.identity(v.indices)))
return l
def _CheckResults(a, b):
assert len(a) == len(b), (
"Values returned by a() and b() must have the same length.")
for x, y in zip(a, b):
assert x.dtype == y.dtype, (
"Values returned by a() [%s] and b() [%s] must have "
"the same type: %s, %s." %
(x.name, y.name, x.dtype.name, y.dtype.name))
def with_dependencies(dependencies, output_tensor, name=None):
"""Produces the content of `output_tensor` only after `dependencies`.
In some cases, a user may want the output of an operation to be
consumed externally only after some other dependencies have run
first. This function ensures returns `output_tensor`, but only after all
operations in `dependencies` have run. Note that this means that there is
no guarantee that `output_tensor` will be evaluated after any `dependencies`
have run.
See also @{tf.tuple$tuple} and @{tf.group$group}.
Args:
dependencies: Iterable of operations to run before this op finishes.
output_tensor: A `Tensor` or `IndexedSlices` that will be returned.
name: (Optional) A name for this operation.
Returns:
Same as `output_tensor`.
Raises:
TypeError: if `output_tensor` is not a `Tensor` or `IndexedSlices`.
"""
with ops.name_scope(name, "control_dependency",
list(dependencies) + [output_tensor]) as name:
with ops.colocate_with(output_tensor):
with ops.control_dependencies(dependencies):
output_tensor = ops.convert_to_tensor_or_indexed_slices(output_tensor)
if isinstance(output_tensor, ops.Tensor):
return _Identity(output_tensor, name=name)
else:
return ops.IndexedSlices(_Identity(output_tensor.values, name=name),
output_tensor.indices,
output_tensor.dense_shape)
def _GroupControlDeps(dev, deps, name=None):
with ops.control_dependencies(deps):
if dev is None:
return no_op(name=name)
else:
with ops.device(dev):
return no_op(name=name)
# TODO(touts): Accept "inputs" as a list.
def group(*inputs, **kwargs):
"""Create an op that groups multiple operations.
When this op finishes, all ops in `input` have finished. This op has no
output.
See also @{tf.tuple$tuple} and
@{tf.control_dependencies$control_dependencies}.
Args:
*inputs: Zero or more tensors to group.
**kwargs: Optional parameters to pass when constructing the NodeDef.
name: A name for this operation (optional).
Returns:
An Operation that executes all its inputs.
Raises:
ValueError: If an unknown keyword argument is provided.
"""
name = kwargs.pop("name", None)
if kwargs:
raise ValueError("Unknown keyword arguments: " + ", ".join(kwargs.keys()))
with ops.name_scope(name, "group_deps", inputs) as name:
# Grouping no inputs means do nothing
if not inputs:
return no_op(name=name)
# Sorts *inputs according to their devices.
ops_on_device = {} # device -> operations specified on the device.
for inp in inputs:
dev = inp.device
if dev in ops_on_device:
ops_on_device[dev].append(inp)
else:
ops_on_device[dev] = [inp]
if len(ops_on_device) == 1:
# 1-level tree. The root node is the returned NoOp node.
(dev, deps), = ops_on_device.items()
return _GroupControlDeps(dev, deps, name=name)
# 2-level tree. The root node is the returned NoOp node.
# deps contains 1 NoOp node for each device.
deps = []
def device_key(dev):
"""A sort key that allows None to be compared to strings."""
return "" if dev is None else dev
for dev in sorted(six.iterkeys(ops_on_device), key=device_key):
deps.append(_GroupControlDeps(dev, ops_on_device[dev]))
with ops.control_dependencies(deps):
return no_op(name=name)
def tuple(tensors, name=None, control_inputs=None):
"""Group tensors together.
This creates a tuple of tensors with the same values as the `tensors`
argument, except that the value of each tensor is only returned after the
values of all tensors have been computed.
`control_inputs` contains additional ops that have to finish before this op
finishes, but whose outputs are not returned.
This can be used as a "join" mechanism for parallel computations: all the
argument tensors can be computed in parallel, but the values of any tensor
returned by `tuple` are only available after all the parallel computations
are done.
See also @{tf.group$group} and
@{tf.control_dependencies$control_dependencies}.
Args:
tensors: A list of `Tensor`s or `IndexedSlices`, some entries can be `None`.
name: (optional) A name to use as a `name_scope` for the operation.
control_inputs: List of additional ops to finish before returning.
Returns:
Same as `tensors`.
Raises:
ValueError: If `tensors` does not contain any `Tensor` or `IndexedSlices`.
TypeError: If `control_inputs` is not a list of `Operation` or `Tensor`
objects.
"""
with ops.name_scope(name, "tuple", tensors) as name:
gating_ops = [t.op for t in tensors if t is not None]
if control_inputs:
for c in control_inputs:
if isinstance(c, ops.Tensor):
c = c.op
elif not isinstance(c, ops.Operation):
raise TypeError("Control input must be Operation or Tensor: %s" % c)
gating_ops.append(c)
# Note that in order to ensure ordering in the pbtxt, we must take care to
# ensure the order here.
gating_ops = sorted(set(gating_ops), key=lambda op: op._id) # Uniquify ops.
if not gating_ops:
raise ValueError("Must have at least one Tensor: %s" % tensors)
gate = group(*gating_ops)
tpl = []
for t in tensors:
if t is not None:
tpl.append(with_dependencies([gate], t))
else:
tpl.append(None)
return tpl
def case(pred_fn_pairs, default, exclusive=False, strict=False, name="case"):
"""Create a case operation.
The `pred_fn_pairs` parameter is a dict or list of pairs of size N.
Each pair contains a boolean scalar tensor and a python callable that
creates the tensors to be returned if the boolean evaluates to True.
`default` is a callable generating a list of tensors. All the callables
in `pred_fn_pairs` as well as `default` should return the same number
and types of tensors.
If `exclusive==True`, all predicates are evaluated, and an exception is
thrown if more than one of the predicates evaluates to `True`.
If `exclusive==False`, execution stops are the first predicate which
evaluates to True, and the tensors generated by the corresponding function
are returned immediately. If none of the predicates evaluate to True, this
operation returns the tensors generated by `default`.
`tf.case` supports nested structures as implemented in
`tensorflow.python.util.nest`. All of the callables must return the same
(possibly nested) value structure of lists, tuples, and/or named tuples.
Singleton lists and tuples form the only exceptions to this: when returned by
a callable, they are implicitly unpacked to single values. This
behavior is disabled by passing `strict=True`.
If an unordered dictionary is used for `pred_fn_pairs`, the order of the
conditional tests is not guaranteed. However, the order is guaranteed to be
deterministic, so that variables created in conditional branches are created
in fixed order across runs.
Example 1:
Pseudocode:
```
if (x < y) return 17;
else return 23;
```
Expressions:
```
f1 = lambda: tf.constant(17)
f2 = lambda: tf.constant(23)
r = case([(tf.less(x, y), f1)], default=f2)
```
Example 2:
Pseudocode:
```
if (x < y && x > z) raise OpError("Only one predicate may evaluate true");
if (x < y) return 17;
else if (x > z) return 23;
else return -1;
```
Expressions:
```
def f1(): return tf.constant(17)
def f2(): return tf.constant(23)
def f3(): return tf.constant(-1)
r = case({tf.less(x, y): f1, tf.greater(x, z): f2},
default=f3, exclusive=True)
```
Args:
pred_fn_pairs: Dict or list of pairs of a boolean scalar tensor and a
callable which returns a list of tensors.
default: A callable that returns a list of tensors.
exclusive: True iff at most one predicate is allowed to evaluate to `True`.
strict: A boolean that enables/disables 'strict' mode; see above.
name: A name for this operation (optional).
Returns:
The tensors returned by the first pair whose predicate evaluated to True, or
those returned by `default` if none does.
Raises:
TypeError: If `pred_fn_pairs` is not a list/dictionary.
TypeError: If `pred_fn_pairs` is a list but does not contain 2-tuples.
TypeError: If `fns[i]` is not callable for any i, or `default` is not
callable.
"""
pfp = pred_fn_pairs # For readability
if not (isinstance(pfp, list) or isinstance(pfp, _basetuple)
or isinstance(pfp, dict)):
raise TypeError("fns must be a list, tuple, or dict")
if isinstance(pfp, dict):
if isinstance(pfp, collections.OrderedDict):
pfp = pfp.items()
else:
pfp = sorted(pfp.items(), key=lambda item: item[0].name)
if not exclusive:
logging.warn("%s: An unordered dictionary of predicate/fn pairs was "
"provided, but exclusive=False. The order of conditional "
"tests is deterministic but not guaranteed.", name)
for tup in pfp:
if not isinstance(tup, _basetuple) or len(tup) != 2:
raise TypeError("Each entry in pred_fn_pairs must be a 2-tuple")
pred, fn = tup
if pred.dtype != dtypes.bool:
raise TypeError("pred must be of type bool: %s", pred.name)
if not callable(fn):
raise TypeError("fn for pred %s must be callable." % pred.name)
if not callable(default):
raise TypeError("default must be callable.")
preds, fns = map(list, zip(*pfp))
with ops.name_scope(name, "case", [preds]):
if not preds:
return default()
not_preds = []
for i, p in enumerate(preds):
with ops.name_scope("not_%d" % i):
not_preds.append(math_ops.logical_not(p))
and_not_preds = [constant_op.constant(True, name="always_true")]
for i, notp in enumerate(not_preds):
with ops.name_scope("and_not_%d" % i):
and_not_preds.append(math_ops.logical_and(and_not_preds[-1], notp))
# preds = [p1, p2, p3]
# fns = [f1, f2, f3]
# not_preds = [~p1, ~p2, ~p3]
# and_not_preds = [True, ~p1, ~p1 & ~p2, ~p1 & ~p2 & ~p3]
# case_preds = [p1,
# p2 & ~p1,
# p3 & ~p2 & ~p1,
# ~p3 & ~p2 & ~p1]
case_preds = []
for i, (p, and_not_p_prev) in enumerate(zip(preds, and_not_preds[:-1])):
with ops.name_scope("case_%d" % i):
case_preds.append(math_ops.logical_and(p, and_not_p_prev))
with ops.name_scope("case_none_are_true"):
case_preds.append(and_not_preds[-1])
# Create an empty tensor, or list, with the right type and shape
with ops.name_scope("case_create_empty"):
def _create_empty_constant(dtype, shape):
value = ("" if dtype == dtypes.string else dtype.as_numpy_dtype())
if shape.ndims is None:
return array_ops.constant(value, dtype=dtype)
else:
temp_shape = [1 if x.value is None else x.value for x in shape]
result = array_ops.constant(value, shape=temp_shape, dtype=dtype)
result._shape = shape # pylint: disable=protected-access
return result
def _correct_empty(v):
if isinstance(v, ops.Operation):
return no_op()
elif isinstance(v, tensor_array_ops.TensorArray):
return v
elif not hasattr(v, "dtype"):
return ops.convert_to_tensor(v)
elif isinstance(v, sparse_tensor.SparseTensor):
return sparse_tensor.SparseTensor(indices=[[0] * len(v.get_shape())],
values=[v.dtype.as_numpy_dtype()],
dense_shape=v.get_shape())
else:
return _create_empty_constant(v.dtype, v.get_shape())
empty = lambda: nest.map_structure(_correct_empty, default())
# case_sequence = [
# cond(~p3 & ~p2 & ~p1, default, empty),
# cond(p3 & ~p2 & ~p1, f3, lambda: case_sequence[0]),
# cond(p2 & ~p1, f2, lambda: case_sequence[1]),
# cond(p1, f1, lambda: case_sequence[2])
# ]
#
# And the return value will be case_sequence[-1]
def _build_case():
all_fns = [fn for fn in fns]
all_fns.append(default)
prev_case = None
for i, (cp, fn) in enumerate(list(zip(case_preds, all_fns))[::-1]):
prev_case = cond(
cp, fn,
empty if i == 0 else lambda: prev_case,
strict=strict, name="If_%d" % i)
return prev_case
if exclusive:
preds_c = array_ops.stack(preds, name="preds_c")
num_true_conditions = math_ops.reduce_sum(
math_ops.cast(preds_c, dtypes.int32), name="num_true_conds")
at_most_one_true_condition = math_ops.less(
num_true_conditions, constant_op.constant(2, name="two_true_conds"))
error_msg = [
("More than one condition evaluated as True but "
"exclusive=True. Conditions: (%s), Values:"
% ", ".join([p.name for p in preds])),
preds_c]
with ops.control_dependencies([
Assert(condition=at_most_one_true_condition,
data=error_msg, summarize=len(preds))]):
case_seq = _build_case()
else:
case_seq = _build_case()
if not strict:
case_seq = _UnpackIfSingleton(case_seq)
return case_seq
ops.register_proto_function(ops.GraphKeys.COND_CONTEXT,
proto_type=control_flow_pb2.CondContextDef,
to_proto=CondContext.to_proto,
from_proto=CondContext.from_proto)
ops.register_proto_function(ops.GraphKeys.WHILE_CONTEXT,
proto_type=control_flow_pb2.WhileContextDef,
to_proto=WhileContext.to_proto,
from_proto=WhileContext.from_proto)
| apache-2.0 |
ImageEngine/gaffer | python/GafferUITest/CollapsibleTest.py | 7 | 4050 | ##########################################################################
#
# Copyright (c) 2011-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above
# copyright notice, this list of conditions and the following
# disclaimer.
#
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided with
# the distribution.
#
# * Neither the name of John Haddon nor the names of
# any other contributors to this software may be used to endorse or
# promote products derived from this software without specific prior
# written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
# IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
# LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
# NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
##########################################################################
import os
import unittest
import GafferUI
import GafferUITest
class CollapsibleTest( GafferUITest.TestCase ) :
def testConstructor( self ) :
b = GafferUI.Button( "Hide Me" )
c = GafferUI.Collapsible( child = b, collapsed=True )
self.assertTrue( c.getChild() is b )
self.assertEqual( c.getCollapsed(), True )
def testSetCollapsed( self ) :
c = GafferUI.Collapsible( collapsed=True )
self.assertEqual( c.getCollapsed(), True )
c.setCollapsed( False )
self.assertEqual( c.getCollapsed(), False )
def testStateChangedSignal( self ) :
self.__states = []
def stateChanged( widget ) :
self.__states.append( widget.getCollapsed( ) )
c = GafferUI.Collapsible( collapsed=True )
stateChangedConnection = c.stateChangedSignal().connect( stateChanged )
c.setCollapsed( False )
self.assertEqual( self.__states, [ False ] )
c.setCollapsed( False ) # shouldn't trigger as state is the same
self.assertEqual( self.__states, [ False ] )
c.setCollapsed( True )
self.assertEqual( self.__states, [ False, True ] )
def testCornerWidget( self ) :
c = GafferUI.Collapsible( collapsed = True )
self.assertEqual( c.getCornerWidget(), None )
b1 = GafferUI.Button()
self.assertEqual( b1.parent(), None )
b2 = GafferUI.Button()
self.assertEqual( b1.parent(), None )
c.setCornerWidget( b1 )
self.assertTrue( c.getCornerWidget() is b1 )
self.assertTrue( b1.parent() is c )
c.setCornerWidget( None )
self.assertIsNone( c.getCornerWidget() )
self.assertIsNone( b1.parent() )
c.setCornerWidget( b1 )
self.assertTrue( c.getCornerWidget() is b1 )
self.assertTrue( b1.parent() is c )
c.setCornerWidget( b2 )
self.assertTrue( c.getCornerWidget() is b2 )
self.assertTrue( b2.parent() is c )
self.assertIsNone( b1.parent() )
c.removeChild( b2 )
self.assertIsNone( c.getCornerWidget() )
self.assertIsNone( b2.parent() )
def testTransferChildren( self ) :
c = GafferUI.Collapsible()
b = GafferUI.Button()
l = GafferUI.ListContainer()
self.assertEqual( b.parent(), None )
l.append( b )
self.assertTrue( b.parent() is l )
c.setChild( b )
self.assertTrue( b.parent() is c )
self.assertEqual( len( l ), 0 )
if __name__ == "__main__":
unittest.main()
| bsd-3-clause |
d/bazel | third_party/py/gflags/tests/gflags_googletest.py | 132 | 4256 | #!/usr/bin/env python
# Copyright (c) 2011, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following disclaimer
# in the documentation and/or other materials provided with the
# distribution.
# * Neither the name of Google Inc. nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""Some simple additions to the unittest framework useful for gflags testing."""
import re
import unittest
def Sorted(lst):
"""Equivalent of sorted(), but not dependent on python version."""
sorted_list = lst[:]
sorted_list.sort()
return sorted_list
def MultiLineEqual(expected, actual):
"""Returns True if expected == actual, or returns False and logs."""
if actual == expected:
return True
print "Error: FLAGS.MainModuleHelp() didn't return the expected result."
print "Got:"
print actual
print "[End of got]"
actual_lines = actual.split("\n")
expected_lines = expected.split("\n")
num_actual_lines = len(actual_lines)
num_expected_lines = len(expected_lines)
if num_actual_lines != num_expected_lines:
print "Number of actual lines = %d, expected %d" % (
num_actual_lines, num_expected_lines)
num_to_match = min(num_actual_lines, num_expected_lines)
for i in range(num_to_match):
if actual_lines[i] != expected_lines[i]:
print "One discrepancy: Got:"
print actual_lines[i]
print "Expected:"
print expected_lines[i]
break
else:
# If we got here, found no discrepancy, print first new line.
if num_actual_lines > num_expected_lines:
print "New help line:"
print actual_lines[num_expected_lines]
elif num_expected_lines > num_actual_lines:
print "Missing expected help line:"
print expected_lines[num_actual_lines]
else:
print "Bug in this test -- discrepancy detected but not found."
return False
class TestCase(unittest.TestCase):
def assertListEqual(self, list1, list2):
"""Asserts that, when sorted, list1 and list2 are identical."""
# This exists in python 2.7, but not previous versions. Use the
# built-in version if possible.
if hasattr(unittest.TestCase, "assertListEqual"):
unittest.TestCase.assertListEqual(self, Sorted(list1), Sorted(list2))
else:
self.assertEqual(Sorted(list1), Sorted(list2))
def assertMultiLineEqual(self, expected, actual):
# This exists in python 2.7, but not previous versions. Use the
# built-in version if possible.
if hasattr(unittest.TestCase, "assertMultiLineEqual"):
unittest.TestCase.assertMultiLineEqual(self, expected, actual)
else:
self.assertTrue(MultiLineEqual(expected, actual))
def assertRaisesWithRegexpMatch(self, exception, regexp, fn, *args, **kwargs):
try:
fn(*args, **kwargs)
except exception, why:
self.assertTrue(re.search(regexp, str(why)),
"'%s' does not match '%s'" % (regexp, why))
return
self.fail(exception.__name__ + " not raised")
def main():
unittest.main()
| apache-2.0 |
mancoast/CPythonPyc_test | cpython/242_test_bisect.py | 8 | 9127 | import unittest
from test import test_support
from bisect import bisect_right, bisect_left, insort_left, insort_right, insort, bisect
from UserList import UserList
class TestBisect(unittest.TestCase):
precomputedCases = [
(bisect_right, [], 1, 0),
(bisect_right, [1], 0, 0),
(bisect_right, [1], 1, 1),
(bisect_right, [1], 2, 1),
(bisect_right, [1, 1], 0, 0),
(bisect_right, [1, 1], 1, 2),
(bisect_right, [1, 1], 2, 2),
(bisect_right, [1, 1, 1], 0, 0),
(bisect_right, [1, 1, 1], 1, 3),
(bisect_right, [1, 1, 1], 2, 3),
(bisect_right, [1, 1, 1, 1], 0, 0),
(bisect_right, [1, 1, 1, 1], 1, 4),
(bisect_right, [1, 1, 1, 1], 2, 4),
(bisect_right, [1, 2], 0, 0),
(bisect_right, [1, 2], 1, 1),
(bisect_right, [1, 2], 1.5, 1),
(bisect_right, [1, 2], 2, 2),
(bisect_right, [1, 2], 3, 2),
(bisect_right, [1, 1, 2, 2], 0, 0),
(bisect_right, [1, 1, 2, 2], 1, 2),
(bisect_right, [1, 1, 2, 2], 1.5, 2),
(bisect_right, [1, 1, 2, 2], 2, 4),
(bisect_right, [1, 1, 2, 2], 3, 4),
(bisect_right, [1, 2, 3], 0, 0),
(bisect_right, [1, 2, 3], 1, 1),
(bisect_right, [1, 2, 3], 1.5, 1),
(bisect_right, [1, 2, 3], 2, 2),
(bisect_right, [1, 2, 3], 2.5, 2),
(bisect_right, [1, 2, 3], 3, 3),
(bisect_right, [1, 2, 3], 4, 3),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 0, 0),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 1, 1),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 1.5, 1),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 2, 3),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 2.5, 3),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 3, 6),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 3.5, 6),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 4, 10),
(bisect_right, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 5, 10),
(bisect_left, [], 1, 0),
(bisect_left, [1], 0, 0),
(bisect_left, [1], 1, 0),
(bisect_left, [1], 2, 1),
(bisect_left, [1, 1], 0, 0),
(bisect_left, [1, 1], 1, 0),
(bisect_left, [1, 1], 2, 2),
(bisect_left, [1, 1, 1], 0, 0),
(bisect_left, [1, 1, 1], 1, 0),
(bisect_left, [1, 1, 1], 2, 3),
(bisect_left, [1, 1, 1, 1], 0, 0),
(bisect_left, [1, 1, 1, 1], 1, 0),
(bisect_left, [1, 1, 1, 1], 2, 4),
(bisect_left, [1, 2], 0, 0),
(bisect_left, [1, 2], 1, 0),
(bisect_left, [1, 2], 1.5, 1),
(bisect_left, [1, 2], 2, 1),
(bisect_left, [1, 2], 3, 2),
(bisect_left, [1, 1, 2, 2], 0, 0),
(bisect_left, [1, 1, 2, 2], 1, 0),
(bisect_left, [1, 1, 2, 2], 1.5, 2),
(bisect_left, [1, 1, 2, 2], 2, 2),
(bisect_left, [1, 1, 2, 2], 3, 4),
(bisect_left, [1, 2, 3], 0, 0),
(bisect_left, [1, 2, 3], 1, 0),
(bisect_left, [1, 2, 3], 1.5, 1),
(bisect_left, [1, 2, 3], 2, 1),
(bisect_left, [1, 2, 3], 2.5, 2),
(bisect_left, [1, 2, 3], 3, 2),
(bisect_left, [1, 2, 3], 4, 3),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 0, 0),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 1, 0),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 1.5, 1),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 2, 1),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 2.5, 3),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 3, 3),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 3.5, 6),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 4, 6),
(bisect_left, [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], 5, 10)
]
def test_precomputed(self):
for func, data, elem, expected in self.precomputedCases:
self.assertEqual(func(data, elem), expected)
self.assertEqual(func(UserList(data), elem), expected)
def test_random(self, n=25):
from random import randrange
for i in xrange(n):
data = [randrange(0, n, 2) for j in xrange(i)]
data.sort()
elem = randrange(-1, n+1)
ip = bisect_left(data, elem)
if ip < len(data):
self.failUnless(elem <= data[ip])
if ip > 0:
self.failUnless(data[ip-1] < elem)
ip = bisect_right(data, elem)
if ip < len(data):
self.failUnless(elem < data[ip])
if ip > 0:
self.failUnless(data[ip-1] <= elem)
def test_optionalSlicing(self):
for func, data, elem, expected in self.precomputedCases:
for lo in xrange(4):
lo = min(len(data), lo)
for hi in xrange(3,8):
hi = min(len(data), hi)
ip = func(data, elem, lo, hi)
self.failUnless(lo <= ip <= hi)
if func is bisect_left and ip < hi:
self.failUnless(elem <= data[ip])
if func is bisect_left and ip > lo:
self.failUnless(data[ip-1] < elem)
if func is bisect_right and ip < hi:
self.failUnless(elem < data[ip])
if func is bisect_right and ip > lo:
self.failUnless(data[ip-1] <= elem)
self.assertEqual(ip, max(lo, min(hi, expected)))
def test_backcompatibility(self):
self.assertEqual(bisect, bisect_right)
#==============================================================================
class TestInsort(unittest.TestCase):
def test_vsBuiltinSort(self, n=500):
from random import choice
for insorted in (list(), UserList()):
for i in xrange(n):
digit = choice("0123456789")
if digit in "02468":
f = insort_left
else:
f = insort_right
f(insorted, digit)
self.assertEqual(sorted(insorted), insorted)
def test_backcompatibility(self):
self.assertEqual(insort, insort_right)
#==============================================================================
class LenOnly:
"Dummy sequence class defining __len__ but not __getitem__."
def __len__(self):
return 10
class GetOnly:
"Dummy sequence class defining __getitem__ but not __len__."
def __getitem__(self, ndx):
return 10
class CmpErr:
"Dummy element that always raises an error during comparison"
def __cmp__(self, other):
raise ZeroDivisionError
class TestErrorHandling(unittest.TestCase):
def test_non_sequence(self):
for f in (bisect_left, bisect_right, insort_left, insort_right):
self.assertRaises(TypeError, f, 10, 10)
def test_len_only(self):
for f in (bisect_left, bisect_right, insort_left, insort_right):
self.assertRaises(AttributeError, f, LenOnly(), 10)
def test_get_only(self):
for f in (bisect_left, bisect_right, insort_left, insort_right):
self.assertRaises(AttributeError, f, GetOnly(), 10)
def test_cmp_err(self):
seq = [CmpErr(), CmpErr(), CmpErr()]
for f in (bisect_left, bisect_right, insort_left, insort_right):
self.assertRaises(ZeroDivisionError, f, seq, 10)
def test_arg_parsing(self):
for f in (bisect_left, bisect_right, insort_left, insort_right):
self.assertRaises(TypeError, f, 10)
#==============================================================================
libreftest = """
Example from the Library Reference: Doc/lib/libbisect.tex
The bisect() function is generally useful for categorizing numeric data.
This example uses bisect() to look up a letter grade for an exam total
(say) based on a set of ordered numeric breakpoints: 85 and up is an `A',
75..84 is a `B', etc.
>>> grades = "FEDCBA"
>>> breakpoints = [30, 44, 66, 75, 85]
>>> from bisect import bisect
>>> def grade(total):
... return grades[bisect(breakpoints, total)]
...
>>> grade(66)
'C'
>>> map(grade, [33, 99, 77, 44, 12, 88])
['E', 'A', 'B', 'D', 'F', 'A']
"""
#------------------------------------------------------------------------------
__test__ = {'libreftest' : libreftest}
def test_main(verbose=None):
from test import test_bisect
from types import BuiltinFunctionType
import sys
test_classes = [TestBisect, TestInsort]
if isinstance(bisect_left, BuiltinFunctionType):
test_classes.append(TestErrorHandling)
test_support.run_unittest(*test_classes)
test_support.run_doctest(test_bisect, verbose)
# verify reference counting
if verbose and hasattr(sys, "gettotalrefcount"):
import gc
counts = [None] * 5
for i in xrange(len(counts)):
test_support.run_unittest(*test_classes)
gc.collect()
counts[i] = sys.gettotalrefcount()
print counts
if __name__ == "__main__":
test_main(verbose=True)
| gpl-3.0 |
redhat-openstack/glance | glance/db/sqlalchemy/migrate_repo/versions/012_id_to_uuid.py | 2 | 20307 | # Copyright 2013 IBM Corp.
# Copyright 2011 OpenStack Foundation
# All Rights Reserved.
#
# 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.
"""
While SQLAlchemy/sqlalchemy-migrate should abstract this correctly,
there are known issues with these libraries so SQLite and non-SQLite
migrations must be done separately.
"""
import uuid
import migrate
import sqlalchemy
meta = sqlalchemy.MetaData()
and_ = sqlalchemy.and_
or_ = sqlalchemy.or_
def upgrade(migrate_engine):
"""
Call the correct dialect-specific upgrade.
"""
meta.bind = migrate_engine
t_images = _get_table('images', meta)
t_image_members = _get_table('image_members', meta)
t_image_properties = _get_table('image_properties', meta)
dialect = migrate_engine.url.get_dialect().name
if dialect == "sqlite":
_upgrade_sqlite(t_images, t_image_members, t_image_properties)
_update_all_ids_to_uuids(t_images, t_image_members, t_image_properties)
elif dialect == "ibm_db_sa":
_upgrade_db2(t_images, t_image_members, t_image_properties)
_update_all_ids_to_uuids(t_images, t_image_members, t_image_properties)
_add_db2_constraints()
else:
_upgrade_other(t_images, t_image_members, t_image_properties, dialect)
def downgrade(migrate_engine):
"""
Call the correct dialect-specific downgrade.
"""
meta.bind = migrate_engine
t_images = _get_table('images', meta)
t_image_members = _get_table('image_members', meta)
t_image_properties = _get_table('image_properties', meta)
dialect = migrate_engine.url.get_dialect().name
if dialect == "sqlite":
_update_all_uuids_to_ids(t_images, t_image_members, t_image_properties)
_downgrade_sqlite(t_images, t_image_members, t_image_properties)
elif dialect == "ibm_db_sa":
_remove_db2_constraints()
_update_all_uuids_to_ids(t_images, t_image_members, t_image_properties)
_downgrade_db2(t_images, t_image_members, t_image_properties)
else:
_downgrade_other(t_images, t_image_members, t_image_properties,
dialect)
def _upgrade_sqlite(t_images, t_image_members, t_image_properties):
"""
Upgrade 011 -> 012 with special SQLite-compatible logic.
"""
sql_commands = [
"""CREATE TABLE images_backup (
id VARCHAR(36) NOT NULL,
name VARCHAR(255),
size INTEGER,
status VARCHAR(30) NOT NULL,
is_public BOOLEAN NOT NULL,
location TEXT,
created_at DATETIME NOT NULL,
updated_at DATETIME,
deleted_at DATETIME,
deleted BOOLEAN NOT NULL,
disk_format VARCHAR(20),
container_format VARCHAR(20),
checksum VARCHAR(32),
owner VARCHAR(255),
min_disk INTEGER NOT NULL,
min_ram INTEGER NOT NULL,
PRIMARY KEY (id),
CHECK (is_public IN (0, 1)),
CHECK (deleted IN (0, 1))
);""",
"""INSERT INTO images_backup
SELECT * FROM images;""",
"""CREATE TABLE image_members_backup (
id INTEGER NOT NULL,
image_id VARCHAR(36) NOT NULL,
member VARCHAR(255) NOT NULL,
can_share BOOLEAN NOT NULL,
created_at DATETIME NOT NULL,
updated_at DATETIME,
deleted_at DATETIME,
deleted BOOLEAN NOT NULL,
PRIMARY KEY (id),
UNIQUE (image_id, member),
CHECK (can_share IN (0, 1)),
CHECK (deleted IN (0, 1)),
FOREIGN KEY(image_id) REFERENCES images (id)
);""",
"""INSERT INTO image_members_backup
SELECT * FROM image_members;""",
"""CREATE TABLE image_properties_backup (
id INTEGER NOT NULL,
image_id VARCHAR(36) NOT NULL,
name VARCHAR(255) NOT NULL,
value TEXT,
created_at DATETIME NOT NULL,
updated_at DATETIME,
deleted_at DATETIME,
deleted BOOLEAN NOT NULL,
PRIMARY KEY (id),
CHECK (deleted IN (0, 1)),
UNIQUE (image_id, name),
FOREIGN KEY(image_id) REFERENCES images (id)
);""",
"""INSERT INTO image_properties_backup
SELECT * FROM image_properties;""",
]
for command in sql_commands:
meta.bind.execute(command)
_sqlite_table_swap(t_image_members, t_image_properties, t_images)
def _upgrade_db2(t_images, t_image_members, t_image_properties):
"""
Upgrade for DB2.
"""
t_images.c.id.alter(sqlalchemy.String(36), primary_key=True)
image_members_backup = sqlalchemy.Table(
'image_members_backup',
meta,
sqlalchemy.Column('id',
sqlalchemy.Integer(),
primary_key=True,
nullable=False),
sqlalchemy.Column('image_id',
sqlalchemy.String(36),
nullable=False,
index=True),
sqlalchemy.Column('member',
sqlalchemy.String(255),
nullable=False),
sqlalchemy.Column('can_share',
sqlalchemy.Boolean(),
nullable=False,
default=False),
sqlalchemy.Column('created_at',
sqlalchemy.DateTime(),
nullable=False),
sqlalchemy.Column('updated_at',
sqlalchemy.DateTime()),
sqlalchemy.Column('deleted_at',
sqlalchemy.DateTime()),
sqlalchemy.Column('deleted',
sqlalchemy.Boolean(),
nullable=False,
default=False,
index=True),
sqlalchemy.UniqueConstraint('image_id', 'member'),
extend_existing=True)
image_properties_backup = sqlalchemy.Table(
'image_properties_backup',
meta,
sqlalchemy.Column('id',
sqlalchemy.Integer(),
primary_key=True,
nullable=False),
sqlalchemy.Column('image_id',
sqlalchemy.String(36),
nullable=False,
index=True),
sqlalchemy.Column('name',
sqlalchemy.String(255),
nullable=False),
sqlalchemy.Column('value',
sqlalchemy.Text()),
sqlalchemy.Column('created_at',
sqlalchemy.DateTime(),
nullable=False),
sqlalchemy.Column('updated_at',
sqlalchemy.DateTime()),
sqlalchemy.Column('deleted_at',
sqlalchemy.DateTime()),
sqlalchemy.Column('deleted',
sqlalchemy.Boolean(),
nullable=False,
default=False,
index=True),
sqlalchemy.UniqueConstraint(
'image_id', 'name',
name='ix_image_properties_image_id_name'),
extend_existing=True)
image_members_backup.create()
image_properties_backup.create()
sql_commands = [
"""INSERT INTO image_members_backup
SELECT * FROM image_members;""",
"""INSERT INTO image_properties_backup
SELECT * FROM image_properties;""",
]
for command in sql_commands:
meta.bind.execute(command)
t_image_members.drop()
t_image_properties.drop()
image_members_backup.rename(name='image_members')
image_properties_backup.rename(name='image_properties')
def _add_db2_constraints():
#Create the foreign keys
sql_commands = [
"""ALTER TABLE image_members ADD CONSTRAINT member_image_id
FOREIGN KEY (image_id)
REFERENCES images (id);""",
"""ALTER TABLE image_properties ADD CONSTRAINT property_image_id
FOREIGN KEY (image_id)
REFERENCES images (id);""",
]
for command in sql_commands:
meta.bind.execute(command)
def _remove_db2_constraints():
#remove the foreign keys constraints
sql_commands = [
"""ALTER TABLE image_members DROP CONSTRAINT member_image_id;""",
"""ALTER TABLE image_properties DROP CONSTRAINT property_image_id;"""
]
for command in sql_commands:
meta.bind.execute(command)
def _downgrade_db2(t_images, t_image_members, t_image_properties):
"""
Downgrade for DB2.
"""
t_images.c.id.alter(sqlalchemy.Integer(), primary_key=True)
image_members_old = sqlalchemy.Table(
'image_members_old',
meta,
sqlalchemy.Column('id',
sqlalchemy.Integer(),
primary_key=True,
nullable=False),
sqlalchemy.Column('image_id',
sqlalchemy.Integer(),
nullable=False,
index=True),
sqlalchemy.Column('member',
sqlalchemy.String(255),
nullable=False),
sqlalchemy.Column('can_share',
sqlalchemy.Boolean(),
nullable=False,
default=False),
sqlalchemy.Column('created_at',
sqlalchemy.DateTime(),
nullable=False),
sqlalchemy.Column('updated_at',
sqlalchemy.DateTime()),
sqlalchemy.Column('deleted_at',
sqlalchemy.DateTime()),
sqlalchemy.Column('deleted',
sqlalchemy.Boolean(),
nullable=False,
default=False,
index=True),
sqlalchemy.UniqueConstraint('image_id', 'member'),
extend_existing=True)
image_properties_old = sqlalchemy.Table(
'image_properties_old',
meta,
sqlalchemy.Column('id',
sqlalchemy.Integer(),
primary_key=True,
nullable=False),
sqlalchemy.Column('image_id',
sqlalchemy.Integer(),
nullable=False,
index=True),
sqlalchemy.Column('name',
sqlalchemy.String(255),
nullable=False),
sqlalchemy.Column('value',
sqlalchemy.Text()),
sqlalchemy.Column('created_at',
sqlalchemy.DateTime(),
nullable=False),
sqlalchemy.Column('updated_at',
sqlalchemy.DateTime()),
sqlalchemy.Column('deleted_at',
sqlalchemy.DateTime()),
sqlalchemy.Column('deleted',
sqlalchemy.Boolean(),
nullable=False,
default=False,
index=True),
sqlalchemy.UniqueConstraint(
'image_id', 'name',
name='ix_image_properties_image_id_name'),
extend_existing=True)
image_members_old.create()
image_properties_old.create()
sql_commands = [
"""INSERT INTO image_members_old
SELECT * FROM image_members;""",
"""INSERT INTO image_properties_old
SELECT * FROM image_properties;""",
]
for command in sql_commands:
meta.bind.execute(command)
t_image_members.drop()
t_image_properties.drop()
image_members_old.rename(name='image_members')
image_properties_old.rename(name='image_properties')
def _downgrade_sqlite(t_images, t_image_members, t_image_properties):
"""
Downgrade 012 -> 011 with special SQLite-compatible logic.
"""
sql_commands = [
"""CREATE TABLE images_backup (
id INTEGER NOT NULL,
name VARCHAR(255),
size INTEGER,
status VARCHAR(30) NOT NULL,
is_public BOOLEAN NOT NULL,
location TEXT,
created_at DATETIME NOT NULL,
updated_at DATETIME,
deleted_at DATETIME,
deleted BOOLEAN NOT NULL,
disk_format VARCHAR(20),
container_format VARCHAR(20),
checksum VARCHAR(32),
owner VARCHAR(255),
min_disk INTEGER NOT NULL,
min_ram INTEGER NOT NULL,
PRIMARY KEY (id),
CHECK (is_public IN (0, 1)),
CHECK (deleted IN (0, 1))
);""",
"""INSERT INTO images_backup
SELECT * FROM images;""",
"""CREATE TABLE image_members_backup (
id INTEGER NOT NULL,
image_id INTEGER NOT NULL,
member VARCHAR(255) NOT NULL,
can_share BOOLEAN NOT NULL,
created_at DATETIME NOT NULL,
updated_at DATETIME,
deleted_at DATETIME,
deleted BOOLEAN NOT NULL,
PRIMARY KEY (id),
UNIQUE (image_id, member),
CHECK (can_share IN (0, 1)),
CHECK (deleted IN (0, 1)),
FOREIGN KEY(image_id) REFERENCES images (id)
);""",
"""INSERT INTO image_members_backup
SELECT * FROM image_members;""",
"""CREATE TABLE image_properties_backup (
id INTEGER NOT NULL,
image_id INTEGER NOT NULL,
name VARCHAR(255) NOT NULL,
value TEXT,
created_at DATETIME NOT NULL,
updated_at DATETIME,
deleted_at DATETIME,
deleted BOOLEAN NOT NULL,
PRIMARY KEY (id),
CHECK (deleted IN (0, 1)),
UNIQUE (image_id, name),
FOREIGN KEY(image_id) REFERENCES images (id)
);""",
"""INSERT INTO image_properties_backup
SELECT * FROM image_properties;""",
]
for command in sql_commands:
meta.bind.execute(command)
_sqlite_table_swap(t_image_members, t_image_properties, t_images)
def _upgrade_other(t_images, t_image_members, t_image_properties, dialect):
"""
Upgrade 011 -> 012 with logic for non-SQLite databases.
"""
foreign_keys = _get_foreign_keys(t_images,
t_image_members,
t_image_properties, dialect)
for fk in foreign_keys:
fk.drop()
t_images.c.id.alter(sqlalchemy.String(36), primary_key=True)
t_image_members.c.image_id.alter(sqlalchemy.String(36))
t_image_properties.c.image_id.alter(sqlalchemy.String(36))
_update_all_ids_to_uuids(t_images, t_image_members, t_image_properties)
for fk in foreign_keys:
fk.create()
def _downgrade_other(t_images, t_image_members, t_image_properties, dialect):
"""
Downgrade 012 -> 011 with logic for non-SQLite databases.
"""
foreign_keys = _get_foreign_keys(t_images,
t_image_members,
t_image_properties, dialect)
for fk in foreign_keys:
fk.drop()
_update_all_uuids_to_ids(t_images, t_image_members, t_image_properties)
t_images.c.id.alter(sqlalchemy.Integer(), primary_key=True)
t_image_members.c.image_id.alter(sqlalchemy.Integer())
t_image_properties.c.image_id.alter(sqlalchemy.Integer())
for fk in foreign_keys:
fk.create()
def _sqlite_table_swap(t_image_members, t_image_properties, t_images):
t_image_members.drop()
t_image_properties.drop()
t_images.drop()
meta.bind.execute("ALTER TABLE images_backup "
"RENAME TO images")
meta.bind.execute("ALTER TABLE image_members_backup "
"RENAME TO image_members")
meta.bind.execute("ALTER TABLE image_properties_backup "
"RENAME TO image_properties")
meta.bind.execute("""CREATE INDEX ix_image_properties_deleted
ON image_properties (deleted);""")
meta.bind.execute("""CREATE INDEX ix_image_properties_name
ON image_properties (name);""")
def _get_table(table_name, metadata):
"""Return a sqlalchemy Table definition with associated metadata."""
return sqlalchemy.Table(table_name, metadata, autoload=True)
def _get_foreign_keys(t_images, t_image_members, t_image_properties, dialect):
"""Retrieve and return foreign keys for members/properties tables."""
foreign_keys = []
if t_image_members.foreign_keys:
img_members_fk_name = list(t_image_members.foreign_keys)[0].name
if dialect == 'mysql':
fk1 = migrate.ForeignKeyConstraint([t_image_members.c.image_id],
[t_images.c.id],
name=img_members_fk_name)
else:
fk1 = migrate.ForeignKeyConstraint([t_image_members.c.image_id],
[t_images.c.id])
foreign_keys.append(fk1)
if t_image_properties.foreign_keys:
img_properties_fk_name = list(t_image_properties.foreign_keys)[0].name
if dialect == 'mysql':
fk2 = migrate.ForeignKeyConstraint([t_image_properties.c.image_id],
[t_images.c.id],
name=img_properties_fk_name)
else:
fk2 = migrate.ForeignKeyConstraint([t_image_properties.c.image_id],
[t_images.c.id])
foreign_keys.append(fk2)
return foreign_keys
def _update_all_ids_to_uuids(t_images, t_image_members, t_image_properties):
"""Transition from INTEGER id to VARCHAR(36) id."""
images = list(t_images.select().execute())
for image in images:
old_id = image["id"]
new_id = str(uuid.uuid4())
t_images.update().\
where(t_images.c.id == old_id).\
values(id=new_id).execute()
t_image_members.update().\
where(t_image_members.c.image_id == old_id).\
values(image_id=new_id).execute()
t_image_properties.update().\
where(t_image_properties.c.image_id == old_id).\
values(image_id=new_id).execute()
t_image_properties.update().\
where(and_(or_(t_image_properties.c.name == 'kernel_id',
t_image_properties.c.name == 'ramdisk_id'),
t_image_properties.c.value == old_id)).\
values(value=new_id).execute()
def _update_all_uuids_to_ids(t_images, t_image_members, t_image_properties):
"""Transition from VARCHAR(36) id to INTEGER id."""
images = list(t_images.select().execute())
new_id = 1
for image in images:
old_id = image["id"]
t_images.update().\
where(t_images.c.id == old_id).\
values(id=str(new_id)).execute()
t_image_members.update().\
where(t_image_members.c.image_id == old_id).\
values(image_id=str(new_id)).execute()
t_image_properties.update().\
where(t_image_properties.c.image_id == old_id).\
values(image_id=str(new_id)).execute()
t_image_properties.update().\
where(and_(or_(t_image_properties.c.name == 'kernel_id',
t_image_properties.c.name == 'ramdisk_id'),
t_image_properties.c.value == old_id)).\
values(value=str(new_id)).execute()
new_id += 1
| apache-2.0 |
lgfausak/sqlbridge | sqlbridge/twisted/dbengine.py | 1 | 6399 | #!/usr/bin/env python
###############################################################################
##
## Copyright (C) 2014 Greg Fausak
##
## 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.
##
###############################################################################
from __future__ import absolute_import
import sys,os,argparse,six
from twisted.python import log
from twisted.internet import reactor
from twisted.internet.defer import inlineCallbacks
from twisted.internet.endpoints import clientFromString
#from myapprunner import MyApplicationRunner
from autobahn.twisted.wamp import ApplicationSession,ApplicationRunner
from autobahn import util
from autobahn.wamp import auth
from autobahn.wamp import types
from autobahn.wamp.exception import ApplicationError
from autobahn.twisted import wamp, websocket
from autobahn.twisted.wamp import ApplicationSession
class DB(ApplicationSession):
"""
An application component providing db access
"""
def __init__(self, *args, **kwargs):
log.msg("__init__")
self.db = {}
self.svar = {}
log.msg("got args {}, kwargs {}".format(args,kwargs))
# reap init variables meant only for us
for i in ( 'engine', 'topic_base', 'dsn', 'authinfo', 'debug', ):
if i in kwargs:
if kwargs[i] is not None:
self.svar[i] = kwargs[i]
del kwargs[i]
log.msg("sending to super.init args {}, kwargs {}".format(args,kwargs))
ApplicationSession.__init__(self, *args, **kwargs)
def onConnect(self):
log.msg("onConnect")
auth_type = 'none'
auth_user = 'anon'
if 'authinfo' in self.svar:
auth_type = self.svar['authinfo']['auth_type']
auth_user = self.svar['authinfo']['auth_user']
log.msg("onConnect with {} {}".format(auth_type, auth_user))
self.join(self.config.realm, [six.u(auth_type)], six.u(auth_user))
def onChallenge(self, challenge):
log.msg("onChallenge - maynard")
password = 'unknown'
if 'authinfo' in self.svar:
password = self.svar['authinfo']['auth_password']
log.msg("onChallenge with password {}".format(password))
if challenge.method == u'wampcra':
if u'salt' in challenge.extra:
key = auth.derive_key(password.encode('utf8'),
challenge.extra['salt'].encode('utf8'),
challenge.extra.get('iterations', None),
challenge.extra.get('keylen', None))
else:
key = password.encode('utf8')
signature = auth.compute_wcs(key, challenge.extra['challenge'].encode('utf8'))
return signature.decode('ascii')
else:
raise Exception("don't know how to compute challenge for authmethod {}".format(challenge.method))
@inlineCallbacks
def onJoin(self, details):
log.msg("db:onJoin session attached {}".format(details))
if 'engine' in self.svar and 'topic_base' in self.svar:
if self.svar['engine'] == 'PG9_4' or self.svar['engine'] == 'PG':
from .db import postgres
dbo = postgres.PG9_4(topic_base = self.svar['topic_base'], app_session = self, debug = self.svar['debug'])
elif self.svar['engine'] == 'MYSQL14_14' or self.svar['engine'] == 'MYSQL':
from .db import mysql
dbo = mysql.MYSQL14_14(topic_base = self.svar['topic_base'], app_session = self, debug = self.svar['debug'])
elif self.svar['engine'] == 'SQLITE3_3_8_2' or self.svar['engine'] == 'SQLITE3' or self.svar['engine'] == 'SQLITE':
from .db import ausqlite3
dbo = ausqlite3.SQLITE3_3_8_2(topic_base = self.svar['topic_base'], app_session = self, debug = self.svar['debug'])
else:
raise Exception("Unsupported dbtype {} ".format(self.svar['engine']))
else:
raise Exception("when instantiating this class DB you must provide engine=X and topic_base=Y")
self.db = { 'instance': dbo }
self.db['registration'] = {}
r = types.RegisterOptions(details_arg = 'details')
self.db['registration']['connect'] = yield self.register(dbo.connect, self.svar['topic_base']+'.connect', options = r)
self.db['registration']['disconnect'] = yield self.register(dbo.disconnect, self.svar['topic_base']+'.disconnect', options = r)
self.db['registration']['query'] = yield self.register(dbo.query, self.svar['topic_base']+'.query', options = r)
self.db['registration']['operation'] = yield self.register(dbo.operation, self.svar['topic_base']+'.operation', options = r)
self.db['registration']['watch'] = yield self.register(dbo.watch, self.svar['topic_base']+'.watch', options = r)
self.db['registration']['info'] = yield self.register(dbo.info, self.svar['topic_base']+'.info', options = r)
if 'dsn' in self.svar:
log.msg("db:onJoin connecting... {}".format(self.svar['dsn']))
yield self.call(self.svar['topic_base'] + '.connect', self.svar['dsn'])
log.msg("db:onJoin connecting established")
log.msg("db bootstrap procedures registered")
def onLeave(self, details):
print("onLeave: {}").format(details)
yield self.db['registration']['connect'].unregister()
yield self.db['registration']['disconnect'].unregister()
yield self.db['registration']['query'].unregister()
yield self.db['registration']['operation'].unregister()
yield self.db['registration']['watch'].unregister()
yield self.db['registration']['info'].unregister()
del self.db
self.disconnect()
return
def onDisconnect(self):
print("onDisconnect:")
reactor.stop()
| apache-2.0 |
matplotlib/cmocean | cmocean/rgb/dense.py | 2 | 13693 |
from matplotlib.colors import ListedColormap
from numpy import nan, inf
# Used to reconstruct the colormap in pycam02ucs.cm.viscm
parameters = {'xp': [16.121891585344997, 33.901145962549492, 5.5873058066040926, -14.703203914141397, -17.875928056390336, -5.3288735306278738],
'yp': [-2.5423728813559308, -13.425925925925895, -42.422027290448327, -35.333333333333314, -8.83264462809916, -2.1686159844054487],
'min_Jp': 15.0,
'max_Jp': 95.0}
cm_data = [[ 0.21298394, 0.05589169, 0.14220951],
[ 0.21780744, 0.0570005 , 0.14665582],
[ 0.22261214, 0.05808842, 0.15115908],
[ 0.22739756, 0.05915624, 0.15572185],
[ 0.23216536, 0.06020099, 0.16034977],
[ 0.23691745, 0.06121879, 0.1650498 ],
[ 0.24164654, 0.06222163, 0.169816 ],
[ 0.24635153, 0.06321115, 0.17465056],
[ 0.25103114, 0.06418929, 0.1795555 ],
[ 0.25568737, 0.06515168, 0.1845388 ],
[ 0.26031556, 0.06610638, 0.18959733],
[ 0.26491272, 0.06705861, 0.19473015],
[ 0.26947709, 0.0680114 , 0.19993831],
[ 0.27400681, 0.06896804, 0.20522255],
[ 0.27849993, 0.06993211, 0.21058327],
[ 0.28295501, 0.07090603, 0.21602205],
[ 0.28737014, 0.0718934 , 0.22153921],
[ 0.29174204, 0.07290112, 0.22713094],
[ 0.29606871, 0.07393344, 0.23279613],
[ 0.30034822, 0.07499465, 0.23853326],
[ 0.30457867, 0.07608911, 0.24434046],
[ 0.30875826, 0.07722111, 0.25021549],
[ 0.31288529, 0.0783949 , 0.25615575],
[ 0.3169582 , 0.07961456, 0.26215837],
[ 0.32097556, 0.08088399, 0.26822019],
[ 0.32493609, 0.08220684, 0.27433782],
[ 0.3288387 , 0.08358647, 0.28050768],
[ 0.33268245, 0.08502593, 0.28672608],
[ 0.33646657, 0.08652789, 0.2929892 ],
[ 0.34019047, 0.08809468, 0.29929318],
[ 0.34385372, 0.08972821, 0.30563417],
[ 0.34745604, 0.09143006, 0.31200825],
[ 0.35099729, 0.0932014 , 0.31841152],
[ 0.35447749, 0.09504303, 0.32484029],
[ 0.35789677, 0.09695535, 0.33129096],
[ 0.36125536, 0.09893846, 0.33776007],
[ 0.36455362, 0.10099212, 0.34424427],
[ 0.36779195, 0.10311585, 0.35074041],
[ 0.37097085, 0.10530889, 0.35724546],
[ 0.37409088, 0.10757029, 0.36375657],
[ 0.37715263, 0.10989888, 0.37027108],
[ 0.38015674, 0.11229336, 0.37678646],
[ 0.38310387, 0.11475229, 0.38330035],
[ 0.38599472, 0.11727411, 0.38981058],
[ 0.38882999, 0.1198572 , 0.3963151 ],
[ 0.39161037, 0.12249987, 0.402812 ],
[ 0.3943366 , 0.12520039, 0.40929955],
[ 0.39700936, 0.12795703, 0.41577611],
[ 0.39962936, 0.13076802, 0.42224018],
[ 0.40219729, 0.13363161, 0.42869038],
[ 0.40471394, 0.13654614, 0.43512488],
[ 0.40717995, 0.13950986, 0.44154258],
[ 0.4095959 , 0.14252107, 0.44794287],
[ 0.41196239, 0.14557814, 0.45432475],
[ 0.41428002, 0.1486795 , 0.4606873 ],
[ 0.41654936, 0.15182361, 0.46702967],
[ 0.41877098, 0.15500903, 0.47335108],
[ 0.4209454 , 0.15823432, 0.4796508 ],
[ 0.42307313, 0.16149814, 0.48592814],
[ 0.42515465, 0.16479918, 0.49218247],
[ 0.42719043, 0.1681362 , 0.49841321],
[ 0.42918111, 0.17150798, 0.50461925],
[ 0.431127 , 0.17491341, 0.5108004 ],
[ 0.43302838, 0.17835141, 0.5169565 ],
[ 0.43488561, 0.18182099, 0.52308708],
[ 0.43669905, 0.18532117, 0.5291917 ],
[ 0.43846903, 0.18885105, 0.53526994],
[ 0.44019583, 0.19240976, 0.54132138],
[ 0.44187976, 0.19599648, 0.54734563],
[ 0.44352106, 0.19961045, 0.5533423 ],
[ 0.44512012, 0.2032509 , 0.55931077],
[ 0.44667705, 0.20691717, 0.56525088],
[ 0.44819199, 0.21060865, 0.57116243],
[ 0.44966511, 0.21432473, 0.57704502],
[ 0.45109659, 0.21806485, 0.58289828],
[ 0.45248658, 0.22182847, 0.58872183],
[ 0.45383521, 0.2256151 , 0.59451528],
[ 0.45514261, 0.22942427, 0.60027826],
[ 0.45640887, 0.23325554, 0.60601037],
[ 0.45763398, 0.23710854, 0.61171135],
[ 0.45881803, 0.24098289, 0.61738074],
[ 0.4599611 , 0.24487823, 0.62301809],
[ 0.46106323, 0.24879421, 0.62862296],
[ 0.46212445, 0.25273054, 0.63419487],
[ 0.46314479, 0.25668693, 0.63973335],
[ 0.46412426, 0.2606631 , 0.6452379 ],
[ 0.46506286, 0.2646588 , 0.650708 ],
[ 0.46596031, 0.26867393, 0.65614343],
[ 0.46681665, 0.27270825, 0.66154354],
[ 0.467632 , 0.27676148, 0.66690758],
[ 0.46840632, 0.28083345, 0.67223496],
[ 0.46913959, 0.28492398, 0.67752502],
[ 0.46983176, 0.28903289, 0.68277713],
[ 0.47048281, 0.29316004, 0.68799058],
[ 0.4710927 , 0.29730529, 0.69316468],
[ 0.47166137, 0.30146848, 0.69829868],
[ 0.47218867, 0.30564956, 0.70339194],
[ 0.47267406, 0.30984863, 0.70844403],
[ 0.47311806, 0.3140653 , 0.71345366],
[ 0.47352067, 0.31829946, 0.71841996],
[ 0.47388188, 0.322551 , 0.72334205],
[ 0.47420168, 0.32681981, 0.728219 ],
[ 0.47448009, 0.33110575, 0.73304987],
[ 0.47471715, 0.33540873, 0.73783366],
[ 0.4749129 , 0.33972863, 0.74256938],
[ 0.47506742, 0.34406531, 0.74725597],
[ 0.4751808 , 0.34841867, 0.75189235],
[ 0.47525316, 0.35278857, 0.75647742],
[ 0.47528466, 0.35717487, 0.76101004],
[ 0.47527514, 0.36157758, 0.76548918],
[ 0.47522479, 0.36599656, 0.76991363],
[ 0.47513427, 0.37043147, 0.77428199],
[ 0.47500393, 0.37488213, 0.77859297],
[ 0.47483412, 0.37934834, 0.7828453 ],
[ 0.4746253 , 0.38382989, 0.78703766],
[ 0.47437795, 0.38832654, 0.7911687 ],
[ 0.47409263, 0.39283807, 0.79523708],
[ 0.47376999, 0.39736419, 0.79924139],
[ 0.47341074, 0.40190463, 0.80318024],
[ 0.47301567, 0.40645908, 0.80705223],
[ 0.47258566, 0.41102721, 0.81085591],
[ 0.47212171, 0.41560865, 0.81458986],
[ 0.4716249 , 0.42020304, 0.81825263],
[ 0.47109642, 0.42480997, 0.82184277],
[ 0.47053758, 0.42942898, 0.82535887],
[ 0.4699498 , 0.43405962, 0.82879947],
[ 0.46933466, 0.43870139, 0.83216318],
[ 0.46869383, 0.44335376, 0.83544858],
[ 0.46802917, 0.44801616, 0.83865432],
[ 0.46734263, 0.45268799, 0.84177905],
[ 0.46663636, 0.45736864, 0.84482148],
[ 0.46591265, 0.46205743, 0.84778034],
[ 0.46517394, 0.46675366, 0.85065444],
[ 0.46442285, 0.47145661, 0.85344263],
[ 0.46366216, 0.4761655 , 0.85614385],
[ 0.46289481, 0.48087955, 0.85875708],
[ 0.46212297, 0.48559831, 0.8612812 ],
[ 0.4613509 , 0.49032052, 0.86371555],
[ 0.46058208, 0.49504528, 0.86605942],
[ 0.45982017, 0.49977167, 0.86831217],
[ 0.45906898, 0.50449872, 0.87047333],
[ 0.4583325 , 0.50922545, 0.87254251],
[ 0.45761487, 0.51395086, 0.87451947],
[ 0.45692037, 0.51867392, 0.87640412],
[ 0.45625342, 0.52339359, 0.87819649],
[ 0.45561856, 0.52810881, 0.87989676],
[ 0.45502044, 0.53281852, 0.88150529],
[ 0.45446291, 0.53752203, 0.8830221 ],
[ 0.45395166, 0.5422179 , 0.88444824],
[ 0.45349173, 0.54690499, 0.88578463],
[ 0.45308803, 0.55158223, 0.88703226],
[ 0.45274551, 0.55624857, 0.8881923 ],
[ 0.45246908, 0.56090297, 0.88926607],
[ 0.45226366, 0.5655444 , 0.89025507],
[ 0.45213406, 0.57017185, 0.89116092],
[ 0.45208461, 0.57478456, 0.89198505],
[ 0.45212047, 0.57938135, 0.89272981],
[ 0.45224622, 0.5839613 , 0.89339735],
[ 0.45246621, 0.58852353, 0.89398987],
[ 0.45278458, 0.59306722, 0.89450974],
[ 0.45320531, 0.59759159, 0.89495941],
[ 0.45373211, 0.60209592, 0.89534144],
[ 0.45436847, 0.60657953, 0.8956585 ],
[ 0.45511768, 0.61104174, 0.89591342],
[ 0.45598269, 0.61548199, 0.89610905],
[ 0.45696613, 0.61989976, 0.89624827],
[ 0.45807033, 0.62429458, 0.89633399],
[ 0.45929732, 0.62866605, 0.89636919],
[ 0.46064879, 0.63301382, 0.89635684],
[ 0.46212629, 0.6373375 , 0.89630027],
[ 0.46373081, 0.6416369 , 0.89620239],
[ 0.46546305, 0.64591186, 0.89606608],
[ 0.46732345, 0.65016224, 0.89589433],
[ 0.46931216, 0.65438798, 0.89569008],
[ 0.47142903, 0.65858902, 0.89545627],
[ 0.47367364, 0.66276538, 0.89519579],
[ 0.47604536, 0.66691708, 0.89491161],
[ 0.47854335, 0.67104413, 0.89460702],
[ 0.48116628, 0.67514678, 0.89428415],
[ 0.48391278, 0.67922522, 0.89394566],
[ 0.48678129, 0.68327963, 0.89359417],
[ 0.48977007, 0.68731025, 0.89323218],
[ 0.4928772 , 0.69131735, 0.89286215],
[ 0.49610063, 0.69530122, 0.89248647],
[ 0.49943822, 0.69926217, 0.89210744],
[ 0.50288765, 0.70320047, 0.89172772],
[ 0.50644655, 0.70711649, 0.89134936],
[ 0.51011248, 0.71101066, 0.8909741 ],
[ 0.51388294, 0.71488334, 0.89060393],
[ 0.51775541, 0.71873493, 0.89024078],
[ 0.52172732, 0.72256583, 0.8898865 ],
[ 0.5257961 , 0.72637645, 0.88954287],
[ 0.52995915, 0.7301672 , 0.8892116 ],
[ 0.53421391, 0.7339385 , 0.88889434],
[ 0.5385578 , 0.73769077, 0.88859267],
[ 0.5429883 , 0.74142444, 0.88830811],
[ 0.54750281, 0.74513991, 0.88804246],
[ 0.5520989 , 0.74883762, 0.88779685],
[ 0.55677422, 0.75251799, 0.88757251],
[ 0.56152638, 0.75618144, 0.88737072],
[ 0.56635309, 0.75982839, 0.88719273],
[ 0.57125208, 0.76345922, 0.88703974],
[ 0.57622118, 0.76707435, 0.8869129 ],
[ 0.58125826, 0.77067417, 0.88681333],
[ 0.58636126, 0.77425906, 0.88674212],
[ 0.59152819, 0.7778294 , 0.88670031],
[ 0.59675713, 0.78138555, 0.88668891],
[ 0.60204624, 0.78492789, 0.88670892],
[ 0.60739371, 0.78845676, 0.88676131],
[ 0.61279785, 0.79197249, 0.886847 ],
[ 0.61825699, 0.79547544, 0.88696697],
[ 0.62376953, 0.79896592, 0.88712212],
[ 0.62933401, 0.80244424, 0.88731328],
[ 0.63494897, 0.80591071, 0.88754133],
[ 0.64061303, 0.80936562, 0.88780715],
[ 0.64632485, 0.81280925, 0.88811162],
[ 0.65208315, 0.81624189, 0.88845562],
[ 0.65788673, 0.81966379, 0.88884001],
[ 0.6637344 , 0.82307522, 0.88926568],
[ 0.66962506, 0.82647642, 0.88973352],
[ 0.67555762, 0.82986764, 0.89024441],
[ 0.68153106, 0.83324911, 0.89079928],
[ 0.68754438, 0.83662105, 0.89139904],
[ 0.69359663, 0.83998369, 0.89204464],
[ 0.69968688, 0.84333724, 0.89273702],
[ 0.70581423, 0.84668191, 0.89347718],
[ 0.71197782, 0.85001791, 0.8942661 ],
[ 0.7181769 , 0.85334541, 0.89510469],
[ 0.72441053, 0.85666464, 0.89599414],
[ 0.73067788, 0.8599758 , 0.89693553],
[ 0.73697811, 0.8632791 , 0.89793 ],
[ 0.74331039, 0.86657473, 0.89897869],
[ 0.74967389, 0.86986292, 0.90008279],
[ 0.75606778, 0.87314387, 0.90124351],
[ 0.76249117, 0.87641781, 0.90246212],
[ 0.7689432 , 0.87968498, 0.90373988],
[ 0.77542295, 0.88294564, 0.9050781 ],
[ 0.78192947, 0.88620003, 0.90647814],
[ 0.78846179, 0.88944845, 0.90794134],
[ 0.79501887, 0.89269119, 0.9094691 ],
[ 0.80159965, 0.89592859, 0.91106281],
[ 0.80820295, 0.899161 , 0.91272391],
[ 0.81482754, 0.90238881, 0.91445386],
[ 0.82147215, 0.90561245, 0.91625407],
[ 0.82813543, 0.90883237, 0.91812595],
[ 0.83481598, 0.91204906, 0.92007088],
[ 0.84151229, 0.91526306, 0.92209023],
[ 0.84822279, 0.91847494, 0.92418529],
[ 0.85494584, 0.92168533, 0.92635732],
[ 0.8616797 , 0.9248949 , 0.92860749],
[ 0.86842255, 0.92810438, 0.9309369 ],
[ 0.87517248, 0.93131455, 0.93334654],
[ 0.88192751, 0.93452625, 0.93583728],
[ 0.88868558, 0.93774038, 0.93840987],
[ 0.89544454, 0.94095789, 0.94106488],
[ 0.90220216, 0.9441798 , 0.94380273]]
test_cm = ListedColormap(cm_data, name=__file__)
if __name__ == "__main__":
import matplotlib.pyplot as plt
import numpy as np
try:
from viscm import viscm
viscm(test_cm)
except ImportError:
print("viscm not found, falling back on simple display")
plt.imshow(np.linspace(0, 100, 256)[None, :], aspect='auto',
cmap=test_cm)
plt.show()
| mit |
cjaymes/pyscap | src/scap/model/ocil_2_0/ItemBaseType.py | 1 | 1052 | # Copyright 2016 Casey Jaymes
# This file is part of PySCAP.
#
# PySCAP is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# PySCAP is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with PySCAP. If not, see <http://www.gnu.org/licenses/>.
from scap.Model import Model
import logging
logger = logging.getLogger(__name__)
class ItemBaseType(Model):
MODEL_MAP = {
'elements': [
{'tag_name': 'notes', 'list': 'notes', 'type': 'StringType', 'min': 0, 'max': None},
],
'attributes': {
'revision': {'type': 'NonNegativeIntegerType', 'default': 0},
}
}
| gpl-3.0 |
jmehnle/ansible | lib/ansible/modules/network/nxos/nxos_vtp_password.py | 46 | 8006 | #!/usr/bin/python
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
#
ANSIBLE_METADATA = {'metadata_version': '1.0',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = '''
---
module: nxos_vtp_password
extends_documentation_fragment: nxos
version_added: "2.2"
short_description: Manages VTP password configuration.
description:
- Manages VTP password configuration.
author:
- Gabriele Gerbino (@GGabriele)
notes:
- VTP feature must be active on the device to use this module.
- This module is used to manage only VTP passwords.
- Use this in combination with M(nxos_vtp_domain) and M(nxos_vtp_version)
to fully manage VTP operations.
- You can set/remove password only if a VTP domain already exist.
- If C(state=absent) and no C(vtp_password) is provided, it remove the current
VTP password.
- If C(state=absent) and C(vtp_password) is provided, the proposed C(vtp_password)
has to match the existing one in order to remove it.
options:
vtp_password:
description:
- VTP password
required: false
default: null
state:
description:
- Manage the state of the resource
required: false
default: present
choices: ['present','absent']
'''
EXAMPLES = '''
# ENSURE VTP PASSWORD IS SET
- nxos_vtp_password:
password: ntc
state: present
host: "{{ inventory_hostname }}"
username: "{{ un }}"
password: "{{ pwd }}"
# ENSURE VTP PASSWORD IS REMOVED
- nxos_vtp_password:
password: ntc
state: absent
host: "{{ inventory_hostname }}"
username: "{{ un }}"
password: "{{ pwd }}"
'''
RETURN = '''
proposed:
description: k/v pairs of parameters passed into module
returned: always
type: dict
sample: {"vtp_password": "new_ntc"}
existing:
description:
- k/v pairs of existing vtp
returned: always
type: dict
sample: {"domain": "ntc", "version": "1", "vtp_password": "ntc"}
end_state:
description: k/v pairs of vtp after module execution
returned: always
type: dict
sample: {"domain": "ntc", "version": "1", "vtp_password": "new_ntc"}
updates:
description: command sent to the device
returned: always
type: list
sample: ["vtp password new_ntc"]
changed:
description: check to see if a change was made on the device
returned: always
type: boolean
sample: true
'''
from ansible.module_utils.nxos import get_config, load_config, run_commands
from ansible.module_utils.nxos import nxos_argument_spec, check_args
from ansible.module_utils.basic import AnsibleModule
import re
def execute_show_command(command, module, command_type='cli_show'):
if module.params['transport'] == 'cli':
if 'show run' not in command:
command += ' | json'
cmds = [command]
body = run_commands(module, cmds)
elif module.params['transport'] == 'nxapi':
cmds = [command]
body = run_commands(module, cmds)
return body
def flatten_list(command_lists):
flat_command_list = []
for command in command_lists:
if isinstance(command, list):
flat_command_list.extend(command)
else:
flat_command_list.append(command)
return flat_command_list
def apply_key_map(key_map, table):
new_dict = {}
for key, value in table.items():
new_key = key_map.get(key)
if new_key:
value = table.get(key)
if value:
new_dict[new_key] = str(value)
else:
new_dict[new_key] = value
return new_dict
def get_vtp_config(module):
command = 'show vtp status'
body = execute_show_command(
command, module, command_type='cli_show_ascii')[0]
vtp_parsed = {}
if body:
version_regex = '.*VTP version running\s+:\s+(?P<version>\d).*'
domain_regex = '.*VTP Domain Name\s+:\s+(?P<domain>\S+).*'
try:
match_version = re.match(version_regex, body, re.DOTALL)
version = match_version.groupdict()['version']
except AttributeError:
version = ''
try:
match_domain = re.match(domain_regex, body, re.DOTALL)
domain = match_domain.groupdict()['domain']
except AttributeError:
domain = ''
if domain and version:
vtp_parsed['domain'] = domain
vtp_parsed['version'] = version
vtp_parsed['vtp_password'] = get_vtp_password(module)
return vtp_parsed
def get_vtp_password(module):
command = 'show vtp password'
body = execute_show_command(command, module)[0]
password = body['passwd']
if password:
return str(password)
else:
return ""
def main():
argument_spec = dict(
vtp_password=dict(type='str', no_log=True),
state=dict(choices=['absent', 'present'],
default='present'),
)
argument_spec.update(nxos_argument_spec)
module = AnsibleModule(argument_spec=argument_spec,
supports_check_mode=True)
warnings = list()
check_args(module, warnings)
vtp_password = module.params['vtp_password'] or None
state = module.params['state']
existing = get_vtp_config(module)
end_state = existing
args = dict(vtp_password=vtp_password)
changed = False
proposed = dict((k, v) for k, v in args.items() if v is not None)
delta = dict(set(proposed.items()).difference(existing.items()))
commands = []
if state == 'absent':
if vtp_password is not None:
if existing['vtp_password'] == proposed['vtp_password']:
commands.append(['no vtp password'])
else:
module.fail_json(msg="Proposed vtp password doesn't match "
"current vtp password. It cannot be "
"removed when state=absent. If you are "
"trying to change the vtp password, use "
"state=present.")
else:
if not existing.get('domain'):
module.fail_json(msg='Cannot remove a vtp password '
'before vtp domain is set.')
elif existing['vtp_password'] != ('\\'):
commands.append(['no vtp password'])
elif state == 'present':
if delta:
if not existing.get('domain'):
module.fail_json(msg='Cannot set vtp password '
'before vtp domain is set.')
else:
commands.append(['vtp password {0}'.format(vtp_password)])
cmds = flatten_list(commands)
if cmds:
if module.check_mode:
module.exit_json(changed=True, commands=cmds)
else:
changed = True
load_config(module, cmds)
end_state = get_vtp_config(module)
if 'configure' in cmds:
cmds.pop(0)
results = {}
results['proposed'] = proposed
results['existing'] = existing
results['end_state'] = end_state
results['updates'] = cmds
results['changed'] = changed
results['warnings'] = warnings
module.exit_json(**results)
if __name__ == '__main__':
main()
| gpl-3.0 |
bnkr/suds | suds/sudsobject.py | 201 | 11165 | # This program is free software; you can redistribute it and/or modify
# it under the terms of the (LGPL) GNU Lesser General Public License as
# published by the Free Software Foundation; either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library Lesser General Public License for more details at
# ( http://www.gnu.org/licenses/lgpl.html ).
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
# written by: Jeff Ortel ( jortel@redhat.com )
"""
The I{sudsobject} module provides a collection of suds objects
that are primarily used for the highly dynamic interactions with
wsdl/xsd defined types.
"""
from logging import getLogger
from suds import *
from new import classobj
log = getLogger(__name__)
def items(sobject):
"""
Extract the I{items} from a suds object much like the
items() method works on I{dict}.
@param sobject: A suds object
@type sobject: L{Object}
@return: A list of items contained in I{sobject}.
@rtype: [(key, value),...]
"""
for item in sobject:
yield item
def asdict(sobject):
"""
Convert a sudsobject into a dictionary.
@param sobject: A suds object
@type sobject: L{Object}
@return: A python dictionary containing the
items contained in I{sobject}.
@rtype: dict
"""
return dict(items(sobject))
def merge(a, b):
"""
Merge all attributes and metadata from I{a} to I{b}.
@param a: A I{source} object
@type a: L{Object}
@param b: A I{destination} object
@type b: L{Object}
"""
for item in a:
setattr(b, item[0], item[1])
b.__metadata__ = b.__metadata__
return b
def footprint(sobject):
"""
Get the I{virtual footprint} of the object.
This is really a count of the attributes in the branch with a significant value.
@param sobject: A suds object.
@type sobject: L{Object}
@return: The branch footprint.
@rtype: int
"""
n = 0
for a in sobject.__keylist__:
v = getattr(sobject, a)
if v is None: continue
if isinstance(v, Object):
n += footprint(v)
continue
if hasattr(v, '__len__'):
if len(v): n += 1
continue
n +=1
return n
class Factory:
cache = {}
@classmethod
def subclass(cls, name, bases, dict={}):
if not isinstance(bases, tuple):
bases = (bases,)
name = name.encode('utf-8')
key = '.'.join((name, str(bases)))
subclass = cls.cache.get(key)
if subclass is None:
subclass = classobj(name, bases, dict)
cls.cache[key] = subclass
return subclass
@classmethod
def object(cls, classname=None, dict={}):
if classname is not None:
subclass = cls.subclass(classname, Object)
inst = subclass()
else:
inst = Object()
for a in dict.items():
setattr(inst, a[0], a[1])
return inst
@classmethod
def metadata(cls):
return Metadata()
@classmethod
def property(cls, name, value=None):
subclass = cls.subclass(name, Property)
return subclass(value)
class Object:
def __init__(self):
self.__keylist__ = []
self.__printer__ = Printer()
self.__metadata__ = Metadata()
def __setattr__(self, name, value):
builtin = name.startswith('__') and name.endswith('__')
if not builtin and \
name not in self.__keylist__:
self.__keylist__.append(name)
self.__dict__[name] = value
def __delattr__(self, name):
try:
del self.__dict__[name]
builtin = name.startswith('__') and name.endswith('__')
if not builtin:
self.__keylist__.remove(name)
except:
cls = self.__class__.__name__
raise AttributeError, "%s has no attribute '%s'" % (cls, name)
def __getitem__(self, name):
if isinstance(name, int):
name = self.__keylist__[int(name)]
return getattr(self, name)
def __setitem__(self, name, value):
setattr(self, name, value)
def __iter__(self):
return Iter(self)
def __len__(self):
return len(self.__keylist__)
def __contains__(self, name):
return name in self.__keylist__
def __repr__(self):
return str(self)
def __str__(self):
return unicode(self).encode('utf-8')
def __unicode__(self):
return self.__printer__.tostr(self)
class Iter:
def __init__(self, sobject):
self.sobject = sobject
self.keylist = self.__keylist(sobject)
self.index = 0
def next(self):
keylist = self.keylist
nkeys = len(self.keylist)
while self.index < nkeys:
k = keylist[self.index]
self.index += 1
if hasattr(self.sobject, k):
v = getattr(self.sobject, k)
return (k, v)
raise StopIteration()
def __keylist(self, sobject):
keylist = sobject.__keylist__
try:
keyset = set(keylist)
ordering = sobject.__metadata__.ordering
ordered = set(ordering)
if not ordered.issuperset(keyset):
log.debug(
'%s must be superset of %s, ordering ignored',
keylist,
ordering)
raise KeyError()
return ordering
except:
return keylist
def __iter__(self):
return self
class Metadata(Object):
def __init__(self):
self.__keylist__ = []
self.__printer__ = Printer()
class Facade(Object):
def __init__(self, name):
Object.__init__(self)
md = self.__metadata__
md.facade = name
class Property(Object):
def __init__(self, value):
Object.__init__(self)
self.value = value
def items(self):
for item in self:
if item[0] != 'value':
yield item
def get(self):
return self.value
def set(self, value):
self.value = value
return self
class Printer:
"""
Pretty printing of a Object object.
"""
@classmethod
def indent(cls, n): return '%*s'%(n*3,' ')
def tostr(self, object, indent=-2):
""" get s string representation of object """
history = []
return self.process(object, history, indent)
def process(self, object, h, n=0, nl=False):
""" print object using the specified indent (n) and newline (nl). """
if object is None:
return 'None'
if isinstance(object, Object):
if len(object) == 0:
return '<empty>'
else:
return self.print_object(object, h, n+2, nl)
if isinstance(object, dict):
if len(object) == 0:
return '<empty>'
else:
return self.print_dictionary(object, h, n+2, nl)
if isinstance(object, (list,tuple)):
if len(object) == 0:
return '<empty>'
else:
return self.print_collection(object, h, n+2)
if isinstance(object, basestring):
return '"%s"' % tostr(object)
return '%s' % tostr(object)
def print_object(self, d, h, n, nl=False):
""" print complex using the specified indent (n) and newline (nl). """
s = []
cls = d.__class__
md = d.__metadata__
if d in h:
s.append('(')
s.append(cls.__name__)
s.append(')')
s.append('...')
return ''.join(s)
h.append(d)
if nl:
s.append('\n')
s.append(self.indent(n))
if cls != Object:
s.append('(')
if isinstance(d, Facade):
s.append(md.facade)
else:
s.append(cls.__name__)
s.append(')')
s.append('{')
for item in d:
if self.exclude(d, item):
continue
item = self.unwrap(d, item)
s.append('\n')
s.append(self.indent(n+1))
if isinstance(item[1], (list,tuple)):
s.append(item[0])
s.append('[]')
else:
s.append(item[0])
s.append(' = ')
s.append(self.process(item[1], h, n, True))
s.append('\n')
s.append(self.indent(n))
s.append('}')
h.pop()
return ''.join(s)
def print_dictionary(self, d, h, n, nl=False):
""" print complex using the specified indent (n) and newline (nl). """
if d in h: return '{}...'
h.append(d)
s = []
if nl:
s.append('\n')
s.append(self.indent(n))
s.append('{')
for item in d.items():
s.append('\n')
s.append(self.indent(n+1))
if isinstance(item[1], (list,tuple)):
s.append(tostr(item[0]))
s.append('[]')
else:
s.append(tostr(item[0]))
s.append(' = ')
s.append(self.process(item[1], h, n, True))
s.append('\n')
s.append(self.indent(n))
s.append('}')
h.pop()
return ''.join(s)
def print_collection(self, c, h, n):
""" print collection using the specified indent (n) and newline (nl). """
if c in h: return '[]...'
h.append(c)
s = []
for item in c:
s.append('\n')
s.append(self.indent(n))
s.append(self.process(item, h, n-2))
s.append(',')
h.pop()
return ''.join(s)
def unwrap(self, d, item):
""" translate (unwrap) using an optional wrapper function """
nopt = ( lambda x: x )
try:
md = d.__metadata__
pmd = getattr(md, '__print__', None)
if pmd is None:
return item
wrappers = getattr(pmd, 'wrappers', {})
fn = wrappers.get(item[0], nopt)
return (item[0], fn(item[1]))
except:
pass
return item
def exclude(self, d, item):
""" check metadata for excluded items """
try:
md = d.__metadata__
pmd = getattr(md, '__print__', None)
if pmd is None:
return False
excludes = getattr(pmd, 'excludes', [])
return ( item[0] in excludes )
except:
pass
return False | lgpl-3.0 |
edespino/gpdb | gpAux/extensions/gphdfs/regression/input/regression/createData.py | 23 | 7087 | #!/usr/bin/env python
"""
Copyright (C) 2004-2015 Pivotal Software, Inc. All rights reserved.
This program and the accompanying materials are made available under
the terms of the 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.
"""
############################################################################
# Set up some globals, and import gptest
# [YOU DO NOT NEED TO CHANGE THESE]
#
import sys,string, os, subprocess, signal,time
#MYD = os.path.abspath(os.path.dirname(__file__))
#mkpath = lambda *x: os.path.join(MYD, *x)
#UPD = os.path.abspath(mkpath('..'))
#if UPD not in sys.path:
# sys.path.append(UPD)
#import gptest
#from gptest import psql, shell
#import re
#from time import sleep
if len(sys.argv) < 2:
print "usage: createData.py <number of lines> <datatype>\n"
print "datatype:"
print "all:regression:time:timestamp:date:bigint:int:smallest:real:float:boolean:varchar:bpchar:numeric:text\n"
sys.exit()
LINE_NUM=int(sys.argv[1])
DATATYPE=sys.argv[2]
def printtimestr(x, datatype):
HH=str(x % 24).zfill(2)
MM=str(x % 60).zfill(2)
SS=str(x % 60).zfill(2)
sss=str(x % 999)
h=str(x % 12).zfill(2)
ampm=x % 2
ampmlist= ['AM','PM']
timezone= x % 5
#timezonelist= ['ACDT','ACT','PST','ADT','ACWST','GMT0','EST5EDT','zulu']
timezonelist= ['ACT','PST','ADT','GMT0','zulu']
year = str((x % 1000) + 1).zfill(4)
month = str((x % 12) + 1).zfill(2)
monthindex = x%24
monthlist = ['January','Jan','February','Feb','March','Mar','April','Apr','May','May','June','Jun','July','Jul','August','Aug','September','Sept','October','Oct','November','Nov','December','Dec']
day = str((x % 30) + 1).zfill(2)
daynofill = str((x % 30) + 1)
if (datatype == 'time'):
#col1 - HH:MM:SS
col1 = HH+ ':' +MM+ ':' +SS
#col2 - HH:MM:SS.sss
col2 = col1+ '.' +sss
#col3 - HHMMSS
col3 = HH+MM+SS
#col4 - HH:MM AM/PM
col4 = h+ ':' +MM+ ' ' +ampmlist[ampm]
#col5 - HH:MM:SS.sss-h (timeoffset)
col5 = col2+ '-' +str(timezone)
#col6 - HH:MM:SS-HH:MM(timeoffset)
col6 = col1+ '-' +h+ ':00'
#col7 - HH:MM-HH:MM(timeoffset)
col7 = HH+':'+MM+ '-' +h+ ':00'
#col8 - HHMMSS-HH(timeoffset)
col8 = col3+ '-' +h
#col9 - HH:MM:SS XXX(timezone)
col9 = col1+ " " +timezonelist[timezone]
return col1+'\t'+col2+'\t'+col3+'\t'+col4+'\t'+col5+'\t'+col6+'\t'+col7+'\t'+col8+'\t'+col9+'\t\\N'
elif (datatype == 'timestamp'):
#1999-01-08 04:05:06
col1 = year+'-' +month+ '-' +day+ ' ' +HH+ ':' +MM+ ':' +SS
#1999-01-08 04:05:06 -8:00
col2 = col1+ ' -' +str(timezone)+ ':00'
#January 8 04:05:06 1999 PST
col3 = monthlist[monthindex]+ ' ' +daynofill+ ' ' +HH+ ':' +MM+ ':' +SS+ ' ' +year+ ' ' +timezonelist[timezone]
return col1+'\t'+col2+'\t'+col3+'\t\\N'
elif (datatype == 'date'):
#1900-01-01
col1 = year+ '-' +month+ '-' +day
#September 01, 1999
col2 = monthlist[monthindex]+ ' ' +day+ ', ' +year
#1/8/1999
col3 = month+ '/' +day+ '/' +year
#1999-Jan-08
col4 = year+ '-' +monthlist[monthindex]+ '-' +day
#Jan-08-1999
col5 = monthlist[monthindex]+ '-' +month+ '-' +year
#08-Jan-1999
col6 = month+ '-' +monthlist[monthindex]+ '-' +year
#January 8, 99 BC
col7 = monthlist[monthindex]+' ' +month+ ', ' +year+ ' BC'
return col1+'\t'+col2+'\t'+col3+'\t'+col4+'\t'+col5+'\t'+col6+'\t'+col7+'\t\\N'
def regression(x):
numRecipes = str(1664525 * x + 1013904223)
Borland = str(22695477 * x + 1)
glibc = str(1103515245 * x + 12345)
appCarbonLib = str((16807 * x) % 2147483647)
vax = str(69069 * x + 1)
javaRandomClass = str(25214903917 * x + 11)
return str(x)+'\t'+str(hex(x))+'\t'+numRecipes+'\t'+Borland+'\t'+glibc+'\t'+appCarbonLib+'\t'+vax+'\t'+javaRandomClass
def printintstr(x, max, min):
if (x < max):
m = x
else:
m = 0
maxsubx = max - m
minplusx = min + m
return str(max)+'\t'+str(min)+'\t'+str(m)+'\t'+str(maxsubx)+'\t'+str(minplusx)+'\t\\N'
def printfloatstr(x,max,min):
pi = float(22)/float(7)
pimulti = pi*x
return str(max)+'\t'+str(min)+'\t'+str(pi)+'\t'+str(pimulti)+'\t\\N'
def printbool(x):
n = x % 2
if n == 0:
return 'true\t\\N'
else:
return 'false\t\\N'
def printchar(x):
strx = ''
currentchar = x%128
for m in range(currentchar):
strx = strx+chr(currentchar)
if (currentchar == 9 or currentchar == 13 or currentchar == 10):
strx = 'skip'
return str(x)+'\t'+strx+'\t\\N'
for x in range(LINE_NUM):
if (DATATYPE == 'regression'):
print regression(x)
elif (DATATYPE == 'time'):
print 'time\t'+printtimestr(x,'time')
elif (DATATYPE == 'timestamp'):
print 'timestamp\t'+printtimestr(x,'timestamp')
elif (DATATYPE == 'date'):
print 'date\t'+printtimestr(x,'date')
elif (DATATYPE == 'bigint'):
print 'bigint\t'+printintstr(x,9223372036854775807,-9223372036854775808)
elif (DATATYPE == 'int'):
print 'int\t'+printintstr(x,2147483647,-2147483648)
elif (DATATYPE == 'smallint'):
print 'smallint\t'+printintstr(x,32767,-32768)
elif (DATATYPE == 'real'):
print 'real\t'+printfloatstr(x, 3.4028235E+38, -3.4028234E+38)
elif (DATATYPE == 'float'):
print 'float\t'+printfloatstr(x,+1.797693134862315E+308, -1.797693134862315E+308)
elif (DATATYPE == 'boolean'):
print 'boolean\t'+printbool(x)
elif (DATATYPE == 'varchar'):
print 'varchar\t'+printchar(x)
elif (DATATYPE == 'bpchar'):
print 'bpchar\t'+printchar(x)
elif (DATATYPE == 'numeric'):
print 'numeric\t'+printintstr(x, 9223372036854775807000, -9223372036854775808000)
elif (DATATYPE == 'text'):
print 'text\t'+printchar(x)
elif (DATATYPE == 'all'):
print regression(x)+ '\t' +printtimestr(x,'time')+ '\t' +printtimestr(x,'timestamp')+ '\t' +printtimestr(x,'date')+ '\t' +printintstr(x,9223372036854775807,-9223372036854775808)+ '\t' +printintstr(x,2147483647,-2147483648)+ '\t' +printintstr(x,32767,-32768)+ '\t' +printfloatstr(x, 3.4028235E+38, -3.4028234E+38)+ '\t' +printfloatstr(x, +1.797693134862315E+308, -1.797693134862315E+308)+ '\t' +printbool(x)+ '\t' +printchar(x)+ '\t'+printchar(x)+ '\t'+printintstr(x,9223372036854775807000,-9223372036854775808000)+ '\t'+printchar(x)
| apache-2.0 |
drawks/ansible | lib/ansible/modules/network/aci/aci_firmware_source.py | 27 | 7594 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright: (c) 2018, Dag Wieers (dagwieers) <dag@wieers.com>
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'certified'}
DOCUMENTATION = r'''
---
module: aci_firmware_source
short_description: Manage firmware image sources (firmware:OSource)
description:
- Manage firmware image sources on Cisco ACI fabrics.
version_added: '2.5'
options:
source:
description:
- The identifying name for the outside source of images, such as an HTTP or SCP server.
type: str
required: yes
aliases: [ name, source_name ]
polling_interval:
description:
- Polling interval in minutes.
type: int
url_protocol:
description:
- The Firmware download protocol.
type: str
choices: [ http, local, scp, usbkey ]
default: scp
aliases: [ url_proto ]
url:
description:
The firmware URL for the image(s) on the source.
type: str
url_password:
description:
The Firmware password or key string.
type: str
url_username:
description:
The username for the source.
type: str
state:
description:
- Use C(present) or C(absent) for adding or removing.
- Use C(query) for listing an object or multiple objects.
type: str
choices: [ absent, present, query ]
default: present
extends_documentation_fragment: aci
seealso:
- name: APIC Management Information Model reference
description: More information about the internal APIC class B(firmware:OSource).
link: https://developer.cisco.com/docs/apic-mim-ref/
author:
- Dag Wieers (@dagwieers)
'''
EXAMPLES = r'''
- name: Add firmware source
aci_firmware_source:
host: apic
username: admin
password: SomeSecretPassword
source: aci-msft-pkg-3.1.1i.zip
url: foo.bar.cisco.com/download/cisco/aci/aci-msft-pkg-3.1.1i.zip
url_protocol: http
state: present
delegate_to: localhost
- name: Remove firmware source
aci_firmware_source:
host: apic
username: admin
password: SomeSecretPassword
source: aci-msft-pkg-3.1.1i.zip
state: absent
delegate_to: localhost
- name: Query a specific firmware source
aci_firmware_source:
host: apic
username: admin
password: SomeSecretPassword
source: aci-msft-pkg-3.1.1i.zip
state: query
delegate_to: localhost
register: query_result
- name: Query all firmware sources
aci_firmware_source:
host: apic
username: admin
password: SomeSecretPassword
state: query
delegate_to: localhost
register: query_result
'''
RETURN = r'''
current:
description: The existing configuration from the APIC after the module has finished
returned: success
type: list
sample:
[
{
"fvTenant": {
"attributes": {
"descr": "Production environment",
"dn": "uni/tn-production",
"name": "production",
"nameAlias": "",
"ownerKey": "",
"ownerTag": ""
}
}
}
]
error:
description: The error information as returned from the APIC
returned: failure
type: dict
sample:
{
"code": "122",
"text": "unknown managed object class foo"
}
raw:
description: The raw output returned by the APIC REST API (xml or json)
returned: parse error
type: str
sample: '<?xml version="1.0" encoding="UTF-8"?><imdata totalCount="1"><error code="122" text="unknown managed object class foo"/></imdata>'
sent:
description: The actual/minimal configuration pushed to the APIC
returned: info
type: list
sample:
{
"fvTenant": {
"attributes": {
"descr": "Production environment"
}
}
}
previous:
description: The original configuration from the APIC before the module has started
returned: info
type: list
sample:
[
{
"fvTenant": {
"attributes": {
"descr": "Production",
"dn": "uni/tn-production",
"name": "production",
"nameAlias": "",
"ownerKey": "",
"ownerTag": ""
}
}
}
]
proposed:
description: The assembled configuration from the user-provided parameters
returned: info
type: dict
sample:
{
"fvTenant": {
"attributes": {
"descr": "Production environment",
"name": "production"
}
}
}
filter_string:
description: The filter string used for the request
returned: failure or debug
type: str
sample: ?rsp-prop-include=config-only
method:
description: The HTTP method used for the request to the APIC
returned: failure or debug
type: str
sample: POST
response:
description: The HTTP response from the APIC
returned: failure or debug
type: str
sample: OK (30 bytes)
status:
description: The HTTP status from the APIC
returned: failure or debug
type: int
sample: 200
url:
description: The HTTP url used for the request to the APIC
returned: failure or debug
type: str
sample: https://10.11.12.13/api/mo/uni/tn-production.json
'''
from ansible.module_utils.basic import AnsibleModule
from ansible.module_utils.network.aci.aci import ACIModule, aci_argument_spec
def main():
argument_spec = aci_argument_spec()
argument_spec.update(
source=dict(type='str', aliases=['name', 'source_name']), # Not required for querying all objects
polling_interval=dict(type='int'),
url=dict(type='str'),
url_username=dict(type='str'),
url_password=dict(type='str', no_log=True),
url_protocol=dict(type='str', default='scp', choices=['http', 'local', 'scp', 'usbkey'], aliases=['url_proto']),
state=dict(type='str', default='present', choices=['absent', 'present', 'query']),
)
module = AnsibleModule(
argument_spec=argument_spec,
supports_check_mode=True,
required_if=[
['state', 'absent', ['source']],
['state', 'present', ['url_protocol', 'source', 'url']],
],
)
polling_interval = module.params['polling_interval']
url_protocol = module.params['url_protocol']
state = module.params['state']
source = module.params['source']
url = module.params['url']
url_password = module.params['url_password']
url_username = module.params['url_username']
aci = ACIModule(module)
aci.construct_url(
root_class=dict(
aci_class='firmwareOSource',
aci_rn='fabric/fwrepop',
module_object=source,
target_filter={'name': source},
),
)
aci.get_existing()
if state == 'present':
aci.payload(
aci_class='firmwareOSource',
class_config=dict(
name=source,
url=url,
password=url_password,
pollingInterval=polling_interval,
proto=url_protocol,
user=url_username,
),
)
aci.get_diff(aci_class='firmwareOSource')
aci.post_config()
elif state == 'absent':
aci.delete_config()
aci.exit_json()
if __name__ == "__main__":
main()
| gpl-3.0 |
shitolepriya/test-erp | erpnext/accounts/doctype/bank_reconciliation/bank_reconciliation.py | 23 | 2290 | # Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors
# License: GNU General Public License v3. See license.txt
from __future__ import unicode_literals
import frappe
from frappe.utils import flt, getdate, nowdate
from frappe import msgprint, _
from frappe.model.document import Document
class BankReconciliation(Document):
def get_details(self):
if not (self.bank_account and self.from_date and self.to_date):
msgprint("Bank Account, From Date and To Date are Mandatory")
return
condition = ""
if not self.include_reconciled_entries:
condition = "and ifnull(clearance_date, '') in ('', '0000-00-00')"
dl = frappe.db.sql("""select t1.name, t1.cheque_no, t1.cheque_date, t2.debit,
t2.credit, t1.posting_date, t2.against_account, t1.clearance_date
from
`tabJournal Entry` t1, `tabJournal Entry Account` t2
where
t2.parent = t1.name and t2.account = %s
and t1.posting_date >= %s and t1.posting_date <= %s and t1.docstatus=1
and ifnull(t1.is_opening, 'No') = 'No' %s
order by t1.posting_date""" %
('%s', '%s', '%s', condition), (self.bank_account, self.from_date, self.to_date), as_dict=1)
self.set('journal_entries', [])
self.total_amount = 0.0
for d in dl:
nl = self.append('journal_entries', {})
nl.posting_date = d.posting_date
nl.voucher_id = d.name
nl.cheque_number = d.cheque_no
nl.cheque_date = d.cheque_date
nl.debit = d.debit
nl.credit = d.credit
nl.against_account = d.against_account
nl.clearance_date = d.clearance_date
self.total_amount += flt(d.debit) - flt(d.credit)
def update_details(self):
vouchers = []
for d in self.get('journal_entries'):
if d.clearance_date:
if d.cheque_date and getdate(d.clearance_date) < getdate(d.cheque_date):
frappe.throw(_("Clearance date cannot be before check date in row {0}").format(d.idx))
frappe.db.set_value("Journal Entry", d.voucher_id, "clearance_date", d.clearance_date)
frappe.db.sql("""update `tabJournal Entry` set clearance_date = %s, modified = %s
where name=%s""", (d.clearance_date, nowdate(), d.voucher_id))
vouchers.append(d.voucher_id)
if vouchers:
msgprint("Clearance Date updated in: {0}".format(", ".join(vouchers)))
else:
msgprint(_("Clearance Date not mentioned"))
| agpl-3.0 |
mancoast/CPythonPyc_test | fail/311_test_funcattrs.py | 1 | 9974 | from test import support
import types
import unittest
class FuncAttrsTest(unittest.TestCase):
def setUp(self):
class F:
def a(self):
pass
def b():
return 3
self.fi = F()
self.F = F
self.b = b
def cannot_set_attr(self, obj, name, value, exceptions):
try:
setattr(obj, name, value)
except exceptions:
pass
else:
self.fail("shouldn't be able to set %s to %r" % (name, value))
try:
delattr(obj, name)
except exceptions:
pass
else:
self.fail("shouldn't be able to del %s" % name)
class FunctionPropertiesTest(FuncAttrsTest):
# Include the external setUp method that is common to all tests
def test_module(self):
self.assertEqual(self.b.__module__, __name__)
def test_dir_includes_correct_attrs(self):
self.b.known_attr = 7
self.assertTrue('known_attr' in dir(self.b),
"set attributes not in dir listing of method")
# Test on underlying function object of method
self.F.a.known_attr = 7
self.assertTrue('known_attr' in dir(self.fi.a), "set attribute on function "
"implementations, should show up in next dir")
def test_duplicate_function_equality(self):
# Body of `duplicate' is the exact same as self.b
def duplicate():
'my docstring'
return 3
self.assertNotEqual(self.b, duplicate)
def test_copying___code__(self):
def test(): pass
self.assertEqual(test(), None)
test.__code__ = self.b.__code__
self.assertEqual(test(), 3) # self.b always returns 3, arbitrarily
def test___globals__(self):
self.assertEqual(self.b.__globals__, globals())
self.cannot_set_attr(self.b, '__globals__', 2, (AttributeError, TypeError))
def test___name__(self):
self.assertEqual(self.b.__name__, 'b')
self.b.__name__ = 'c'
self.assertEqual(self.b.__name__, 'c')
self.b.__name__ = 'd'
self.assertEqual(self.b.__name__, 'd')
# __name__ and __name__ must be a string
self.cannot_set_attr(self.b, '__name__', 7, TypeError)
# __name__ must be available when in restricted mode. Exec will raise
# AttributeError if __name__ is not available on f.
s = """def f(): pass\nf.__name__"""
exec(s, {'__builtins__': {}})
# Test on methods, too
self.assertEqual(self.fi.a.__name__, 'a')
self.cannot_set_attr(self.fi.a, "__name__", 'a', AttributeError)
def test___code__(self):
num_one, num_two = 7, 8
def a(): pass
def b(): return 12
def c(): return num_one
def d(): return num_two
def e(): return num_one, num_two
for func in [a, b, c, d, e]:
self.assertEqual(type(func.__code__), types.CodeType)
self.assertEqual(c(), 7)
self.assertEqual(d(), 8)
d.__code__ = c.__code__
self.assertEqual(c.__code__, d.__code__)
self.assertEqual(c(), 7)
# self.assertEqual(d(), 7)
try: b.__code__ = c.__code__
except ValueError: pass
else: self.fail(
"__code__ with different numbers of free vars should not be "
"possible")
try: e.__code__ = d.__code__
except ValueError: pass
else: self.fail(
"__code__ with different numbers of free vars should not be "
"possible")
def test_blank_func_defaults(self):
self.assertEqual(self.b.__defaults__, None)
del self.b.__defaults__
self.assertEqual(self.b.__defaults__, None)
def test_func_default_args(self):
def first_func(a, b):
return a+b
def second_func(a=1, b=2):
return a+b
self.assertEqual(first_func.__defaults__, None)
self.assertEqual(second_func.__defaults__, (1, 2))
first_func.__defaults__ = (1, 2)
self.assertEqual(first_func.__defaults__, (1, 2))
self.assertEqual(first_func(), 3)
self.assertEqual(first_func(3), 5)
self.assertEqual(first_func(3, 5), 8)
del second_func.__defaults__
self.assertEqual(second_func.__defaults__, None)
try: second_func()
except TypeError: pass
else: self.fail(
"func_defaults does not update; deleting it does not remove "
"requirement")
class ImplicitReferencesTest(FuncAttrsTest):
def test___class__(self):
self.assertEqual(self.fi.a.__self__.__class__, self.F)
self.cannot_set_attr(self.fi.a, "__class__", self.F, TypeError)
def test___func__(self):
self.assertEqual(self.fi.a.__func__, self.F.a)
self.cannot_set_attr(self.fi.a, "__func__", self.F.a, AttributeError)
def test___self__(self):
self.assertEqual(self.fi.a.__self__, self.fi)
self.cannot_set_attr(self.fi.a, "__self__", self.fi, AttributeError)
def test___func___non_method(self):
# Behavior should be the same when a method is added via an attr
# assignment
self.fi.id = types.MethodType(id, self.fi)
self.assertEqual(self.fi.id(), id(self.fi))
# Test usage
try: self.fi.id.unknown_attr
except AttributeError: pass
else: self.fail("using unknown attributes should raise AttributeError")
# Test assignment and deletion
self.cannot_set_attr(self.fi.id, 'unknown_attr', 2, AttributeError)
class ArbitraryFunctionAttrTest(FuncAttrsTest):
def test_set_attr(self):
self.b.known_attr = 7
self.assertEqual(self.b.known_attr, 7)
try: self.fi.a.known_attr = 7
except AttributeError: pass
else: self.fail("setting attributes on methods should raise error")
def test_delete_unknown_attr(self):
try: del self.b.unknown_attr
except AttributeError: pass
else: self.fail("deleting unknown attribute should raise TypeError")
def test_unset_attr(self):
for func in [self.b, self.fi.a]:
try: func.non_existent_attr
except AttributeError: pass
else: self.fail("using unknown attributes should raise "
"AttributeError")
class FunctionDictsTest(FuncAttrsTest):
def test_setting_dict_to_invalid(self):
self.cannot_set_attr(self.b, '__dict__', None, TypeError)
from collections import UserDict
d = UserDict({'known_attr': 7})
self.cannot_set_attr(self.fi.a.__func__, '__dict__', d, TypeError)
def test_setting_dict_to_valid(self):
d = {'known_attr': 7}
self.b.__dict__ = d
# Test assignment
self.assertEqual(d, self.b.__dict__)
# ... and on all the different ways of referencing the method's func
self.F.a.__dict__ = d
self.assertEqual(d, self.fi.a.__func__.__dict__)
self.assertEqual(d, self.fi.a.__dict__)
# Test value
self.assertEqual(self.b.known_attr, 7)
self.assertEqual(self.b.__dict__['known_attr'], 7)
# ... and again, on all the different method's names
self.assertEqual(self.fi.a.__func__.known_attr, 7)
self.assertEqual(self.fi.a.known_attr, 7)
def test_delete___dict__(self):
try: del self.b.__dict__
except TypeError: pass
else: self.fail("deleting function dictionary should raise TypeError")
def test_unassigned_dict(self):
self.assertEqual(self.b.__dict__, {})
def test_func_as_dict_key(self):
value = "Some string"
d = {}
d[self.b] = value
self.assertEqual(d[self.b], value)
class FunctionDocstringTest(FuncAttrsTest):
def test_set_docstring_attr(self):
self.assertEqual(self.b.__doc__, None)
docstr = "A test method that does nothing"
self.b.__doc__ = docstr
self.F.a.__doc__ = docstr
self.assertEqual(self.b.__doc__, docstr)
self.assertEqual(self.fi.a.__doc__, docstr)
self.cannot_set_attr(self.fi.a, "__doc__", docstr, AttributeError)
def test_delete_docstring(self):
self.b.__doc__ = "The docstring"
del self.b.__doc__
self.assertEqual(self.b.__doc__, None)
def cell(value):
"""Create a cell containing the given value."""
def f():
print(a)
a = value
return f.__closure__[0]
def empty_cell(empty=True):
"""Create an empty cell."""
def f():
print(a)
# the intent of the following line is simply "if False:"; it's
# spelt this way to avoid the danger that a future optimization
# might simply remove an "if False:" code block.
if not empty:
a = 1729
return f.__closure__[0]
class CellTest(unittest.TestCase):
def test_comparison(self):
# These tests are here simply to exercise the comparison code;
# their presence should not be interpreted as providing any
# guarantees about the semantics (or even existence) of cell
# comparisons in future versions of CPython.
self.assertTrue(cell(2) < cell(3))
self.assertTrue(empty_cell() < cell('saturday'))
self.assertTrue(empty_cell() == empty_cell())
self.assertTrue(cell(-36) == cell(-36.0))
self.assertTrue(cell(True) > empty_cell())
class StaticMethodAttrsTest(unittest.TestCase):
def test_func_attribute(self):
def f():
pass
c = classmethod(f)
self.assertTrue(c.__func__ is f)
s = staticmethod(f)
self.assertTrue(s.__func__ is f)
def test_main():
support.run_unittest(FunctionPropertiesTest, ImplicitReferencesTest,
ArbitraryFunctionAttrTest, FunctionDictsTest,
FunctionDocstringTest, CellTest,
StaticMethodAttrsTest)
if __name__ == "__main__":
test_main()
| gpl-3.0 |
wezhang/vim-setup | bundle/python-mode/pymode/libs3/rope/refactor/occurrences.py | 91 | 10704 | import re
import rope.base.pynames
from rope.base import pynames, pyobjects, codeanalyze, evaluate, exceptions, utils, worder
class Finder(object):
"""For finding occurrences of a name
The constructor takes a `filters` argument. It should be a list
of functions that take a single argument. For each possible
occurrence, these functions are called in order with the an
instance of `Occurrence`:
* If it returns `None` other filters are tried.
* If it returns `True`, the occurrence will be a match.
* If it returns `False`, the occurrence will be skipped.
* If all of the filters return `None`, it is skipped also.
"""
def __init__(self, pycore, name, filters=[lambda o: True], docs=False):
self.pycore = pycore
self.name = name
self.docs = docs
self.filters = filters
self._textual_finder = _TextualFinder(name, docs=docs)
def find_occurrences(self, resource=None, pymodule=None):
"""Generate `Occurrence` instances"""
tools = _OccurrenceToolsCreator(self.pycore, resource=resource,
pymodule=pymodule, docs=self.docs)
for offset in self._textual_finder.find_offsets(tools.source_code):
occurrence = Occurrence(tools, offset)
for filter in self.filters:
result = filter(occurrence)
if result is None:
continue
if result:
yield occurrence
break
def create_finder(pycore, name, pyname, only_calls=False, imports=True,
unsure=None, docs=False, instance=None, in_hierarchy=False):
"""A factory for `Finder`
Based on the arguments it creates a list of filters. `instance`
argument is needed only when you want implicit interfaces to be
considered.
"""
pynames = set([pyname])
filters = []
if only_calls:
filters.append(CallsFilter())
if not imports:
filters.append(NoImportsFilter())
if isinstance(instance, rope.base.pynames.ParameterName):
for pyobject in instance.get_objects():
try:
pynames.add(pyobject[name])
except exceptions.AttributeNotFoundError:
pass
for pyname in pynames:
filters.append(PyNameFilter(pyname))
if in_hierarchy:
filters.append(InHierarchyFilter(pyname))
if unsure:
filters.append(UnsureFilter(unsure))
return Finder(pycore, name, filters=filters, docs=docs)
class Occurrence(object):
def __init__(self, tools, offset):
self.tools = tools
self.offset = offset
self.resource = tools.resource
@utils.saveit
def get_word_range(self):
return self.tools.word_finder.get_word_range(self.offset)
@utils.saveit
def get_primary_range(self):
return self.tools.word_finder.get_primary_range(self.offset)
@utils.saveit
def get_pyname(self):
try:
return self.tools.name_finder.get_pyname_at(self.offset)
except exceptions.BadIdentifierError:
pass
@utils.saveit
def get_primary_and_pyname(self):
try:
return self.tools.name_finder.get_primary_and_pyname_at(self.offset)
except exceptions.BadIdentifierError:
pass
@utils.saveit
def is_in_import_statement(self):
return (self.tools.word_finder.is_from_statement(self.offset) or
self.tools.word_finder.is_import_statement(self.offset))
def is_called(self):
return self.tools.word_finder.is_a_function_being_called(self.offset)
def is_defined(self):
return self.tools.word_finder.is_a_class_or_function_name_in_header(self.offset)
def is_a_fixed_primary(self):
return self.tools.word_finder.is_a_class_or_function_name_in_header(self.offset) or \
self.tools.word_finder.is_a_name_after_from_import(self.offset)
def is_written(self):
return self.tools.word_finder.is_assigned_here(self.offset)
def is_unsure(self):
return unsure_pyname(self.get_pyname())
@property
@utils.saveit
def lineno(self):
offset = self.get_word_range()[0]
return self.tools.pymodule.lines.get_line_number(offset)
def same_pyname(expected, pyname):
"""Check whether `expected` and `pyname` are the same"""
if expected is None or pyname is None:
return False
if expected == pyname:
return True
if type(expected) not in (pynames.ImportedModule, pynames.ImportedName) and \
type(pyname) not in (pynames.ImportedModule, pynames.ImportedName):
return False
return expected.get_definition_location() == pyname.get_definition_location() and \
expected.get_object() == pyname.get_object()
def unsure_pyname(pyname, unbound=True):
"""Return `True` if we don't know what this name references"""
if pyname is None:
return True
if unbound and not isinstance(pyname, pynames.UnboundName):
return False
if pyname.get_object() == pyobjects.get_unknown():
return True
class PyNameFilter(object):
"""For finding occurrences of a name"""
def __init__(self, pyname):
self.pyname = pyname
def __call__(self, occurrence):
if same_pyname(self.pyname, occurrence.get_pyname()):
return True
class InHierarchyFilter(object):
"""For finding occurrences of a name"""
def __init__(self, pyname, implementations_only=False):
self.pyname = pyname
self.impl_only = implementations_only
self.pyclass = self._get_containing_class(pyname)
if self.pyclass is not None:
self.name = pyname.get_object().get_name()
self.roots = self._get_root_classes(self.pyclass, self.name)
else:
self.roots = None
def __call__(self, occurrence):
if self.roots is None:
return
pyclass = self._get_containing_class(occurrence.get_pyname())
if pyclass is not None:
roots = self._get_root_classes(pyclass, self.name)
if self.roots.intersection(roots):
return True
def _get_containing_class(self, pyname):
if isinstance(pyname, pynames.DefinedName):
scope = pyname.get_object().get_scope()
parent = scope.parent
if parent is not None and parent.get_kind() == 'Class':
return parent.pyobject
def _get_root_classes(self, pyclass, name):
if self.impl_only and pyclass == self.pyclass:
return set([pyclass])
result = set()
for superclass in pyclass.get_superclasses():
if name in superclass:
result.update(self._get_root_classes(superclass, name))
if not result:
return set([pyclass])
return result
class UnsureFilter(object):
def __init__(self, unsure):
self.unsure = unsure
def __call__(self, occurrence):
if occurrence.is_unsure() and self.unsure(occurrence):
return True
class NoImportsFilter(object):
def __call__(self, occurrence):
if occurrence.is_in_import_statement():
return False
class CallsFilter(object):
def __call__(self, occurrence):
if not occurrence.is_called():
return False
class _TextualFinder(object):
def __init__(self, name, docs=False):
self.name = name
self.docs = docs
self.comment_pattern = _TextualFinder.any('comment', [r'#[^\n]*'])
self.string_pattern = _TextualFinder.any(
'string', [codeanalyze.get_string_pattern()])
self.pattern = self._get_occurrence_pattern(self.name)
def find_offsets(self, source):
if not self._fast_file_query(source):
return
if self.docs:
searcher = self._normal_search
else:
searcher = self._re_search
for matched in searcher(source):
yield matched
def _re_search(self, source):
for match in self.pattern.finditer(source):
for key, value in match.groupdict().items():
if value and key == 'occurrence':
yield match.start(key)
def _normal_search(self, source):
current = 0
while True:
try:
found = source.index(self.name, current)
current = found + len(self.name)
if (found == 0 or not self._is_id_char(source[found - 1])) and \
(current == len(source) or not self._is_id_char(source[current])):
yield found
except ValueError:
break
def _is_id_char(self, c):
return c.isalnum() or c == '_'
def _fast_file_query(self, source):
try:
source.index(self.name)
return True
except ValueError:
return False
def _get_source(self, resource, pymodule):
if resource is not None:
return resource.read()
else:
return pymodule.source_code
def _get_occurrence_pattern(self, name):
occurrence_pattern = _TextualFinder.any('occurrence',
['\\b' + name + '\\b'])
pattern = re.compile(occurrence_pattern + '|' + self.comment_pattern +
'|' + self.string_pattern)
return pattern
@staticmethod
def any(name, list_):
return '(?P<%s>' % name + '|'.join(list_) + ')'
class _OccurrenceToolsCreator(object):
def __init__(self, pycore, resource=None, pymodule=None, docs=False):
self.pycore = pycore
self.__resource = resource
self.__pymodule = pymodule
self.docs = docs
@property
@utils.saveit
def name_finder(self):
return evaluate.ScopeNameFinder(self.pymodule)
@property
@utils.saveit
def source_code(self):
if self.__resource is not None:
return self.resource.read()
else:
return self.pymodule.source_code
@property
@utils.saveit
def word_finder(self):
return worder.Worder(self.source_code, self.docs)
@property
@utils.saveit
def resource(self):
if self.__resource is not None:
return self.__resource
if self.__pymodule is not None:
return self.__pymodule.resource
@property
@utils.saveit
def pymodule(self):
if self.__pymodule is not None:
return self.__pymodule
return self.pycore.resource_to_pyobject(self.resource)
| apache-2.0 |
daniel1yuan/Persist | Persist/webapp/views.py | 1 | 6162 | from django.shortcuts import redirect,render
from django.http import Http404, JsonResponse, HttpResponseForbidden, HttpResponse
from django.contrib.auth import authenticate, login, logout
from webapp.models import User, Customer, Habit
from django.core import serializers
from django.views.decorators.csrf import csrf_exempt
from django.utils import timezone
from datetime import datetime
from webapp.helper import habits_arr, arr_str
import json
import os
# Create your views here.
def index(request):
context = {
'title': 'Persist'
}
if request.user.is_authenticated():
return redirect("home")
else:
return render(request, 'webapp/landing.html', context)
def home(request):
if request.user.is_authenticated():
return render(request, 'webapp/home.html')
else:
return redirect("login_page")
def login_page(request):
if request.user.is_authenticated():
return redirect("home")
context = {
'title': 'Persist'
}
return render(request, 'webapp/login.html', context)
#Authentication Views
@csrf_exempt
def login_user(request):
username = request.POST['username']
password = request.POST['password']
user = authenticate(username=username, password=password)
if user is not None:
login(request, user)
return HttpResponse(json.dumps({"success": True}))
else:
return HttpResponse(json.dumps({"success": False}))
def logout_user(request):
logout(request)
return HttpResponse(json.dumps({"success": True}))
@csrf_exempt
def add_user(request):
username = request.POST['username']
password = request.POST['password']
user = User.objects.create_user(username=username, password=password)
customer = Customer(user=user, habits="")
customer.save()
user.save()
return HttpResponse(json.dumps({"success": True}))
def del_cur_user(request):
if request.user.is_authenticated():
user = request.user
user.delete()
return HttpResponse(json.dumps({"success": True}))
else:
return HttpResponse(json.dumps({"success": False}))
def del_user(request):
user = request.user
#Check if the admin is logged on
if user.is_authenticated() and user.has_perm('webapp'):
username = request.POST['username']
user = User.objects.get(username=username)
user.delete()
return HttpResponse(json.dumps({"success": True}))
return HttpResponse(json.dumps({"success": False}))
def is_logged_in(request):
if (request.user.is_authenticated()):
return HttpResponse(json.dumps({"success": True, "logged_in": True}))
else:
return HttpResponse(json.dumps({"success": True, "logged_in": False}))
return HttpResponse(json.dumps({"success": False}))
def get_habit(request):
habit_id = int(request.POST['habit_id'])
try:
habit_obj = Habit.objects.get(pk=habit_id)
print habit_obj.monetary_amount
habit_serial = serializers.serialize('json', [habit_obj])
#[1:-1] to remove brackets?
return HttpResponse(json.dumps(habit_serial[1:-1]), content_type='application/json')
except Habit.DoesNotExist:
return HttpResponse(json.dumps({"pk": -1}))
def create_habit(request):
name = request.POST['name']
description = request.POST['description']
monetary_amount = int(request.POST['monetary_amount'])
end_date = int(int((request.POST['end_date']))/(1000.0))
start_date = int((datetime.utcnow()-datetime(1970,1,1)).total_seconds())
last_clicked = int((datetime.utcnow()-datetime(1970,1,1)).total_seconds())
status = int(request.POST['success_status'])
charity = int(request.POST['charity'])
user = request.user
if (not user.is_authenticated()):
return HttpResponse(json.dumps({"success": False}))
habit = Habit(name=name,description=description,monetary_amount=monetary_amount,end_date=end_date,status=status,charity=charity,user=user,start_date=start_date,last_clicked=last_clicked)
print habit.start_date
habit.save()
user.customer.habits += "," + str(habit.pk)
user.customer.save()
return HttpResponse(json.dumps({"success": True,"pk":habit.pk}))
def delete_habit(request):
try:
user = request.user
customer = user.customer
pk = request.POST['id']
habit = Habit.objects.get(pk=pk)
habits = habits_arr(customer.habits)
index = habits.index(int(pk))
del(habits[index])
customer.habits = arr_str(habits)
customer.save()
habit.delete()
return HttpResponse(json.dumps({"success": True}))
except:
return HttpResponse(json.dumps({"success": False}))
def change_habit(request):
pk = request.POST['id']
habit = Habit.objects.get(pk=pk)
if habit is None:
return HttpResponse(json.dumps({"success": False}))
else:
try:
habit.name = request.POST['name']
except:
habit.name = habit.name
try:
habit.description = request.POST['description']
except:
habit.description = habit.description
try:
habit.monetary_amount = request.POST['monetary_amount']
except:
habit.monetary_amount = habit.monetary_amount
try:
habit.end_date = int((request.POST['end_date']))/(1000.0)
except:
habit.end_date = habit.end_date
try:
habit.last_clicked = int((request.POST['last_clicked']))/(1000.0)
except:
habit.last_clicked = habit.last_clicked
try:
habit.status = request.POST['success_status']
except:
habit.status = habit.status
try:
habit.charity = request.POST['charity']
except:
habit.charity = habit.charity
habit.save()
return HttpResponse(json.dumps({"success": True}))
def get_all_habits(request):
if request.user.is_authenticated():
habits = habits_arr(request.user.customer.habits)
json_dict = {}
for idx in habits:
cur_habit = Habit.objects.get(pk=idx)
cur_serial = serializers.serialize('json',[cur_habit])[1:-1]
json_dict[idx] = cur_serial
return HttpResponse(json.dumps(json_dict))
else:
return HttpResponse(json.dumps({"success": False}))
def get_username(request):
if request.user.is_authenticated():
return HttpResponse(json.dumps({"success": True, "username": request.user.username}))
else:
return HttpResponse(json.dumps({"success": False}))
| mit |
matmutant/sl4a | python-build/python-libs/gdata/tests/gdata_test.py | 87 | 14634 | #!/usr/bin/python
#
# Copyright (C) 2006 Google Inc.
#
# 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.
__author__ = 'j.s@google.com (Jeff Scudder)'
import unittest
try:
from xml.etree import ElementTree
except ImportError:
from elementtree import ElementTree
import gdata
import atom
from gdata import test_data
import gdata.test_config as conf
class StartIndexTest(unittest.TestCase):
def setUp(self):
self.start_index = gdata.StartIndex()
def testToAndFromString(self):
self.start_index.text = '1'
self.assert_(self.start_index.text == '1')
new_start_index = gdata.StartIndexFromString(self.start_index.ToString())
self.assert_(self.start_index.text == new_start_index.text)
class ItemsPerPageTest(unittest.TestCase):
def setUp(self):
self.items_per_page = gdata.ItemsPerPage()
def testToAndFromString(self):
self.items_per_page.text = '10'
self.assert_(self.items_per_page.text == '10')
new_items_per_page = gdata.ItemsPerPageFromString(
self.items_per_page.ToString())
self.assert_(self.items_per_page.text == new_items_per_page.text)
class GDataEntryTest(unittest.TestCase):
def testIdShouldBeCleaned(self):
entry = gdata.GDataEntryFromString(test_data.XML_ENTRY_1)
element_tree = ElementTree.fromstring(test_data.XML_ENTRY_1)
self.assert_(element_tree.findall(
'{http://www.w3.org/2005/Atom}id')[0].text != entry.id.text)
self.assert_(entry.id.text == 'http://www.google.com/test/id/url')
def testGeneratorShouldBeCleaned(self):
feed = gdata.GDataFeedFromString(test_data.GBASE_FEED)
element_tree = ElementTree.fromstring(test_data.GBASE_FEED)
self.assert_(element_tree.findall('{http://www.w3.org/2005/Atom}generator'
)[0].text != feed.generator.text)
self.assert_(feed.generator.text == 'GoogleBase')
def testAllowsEmptyId(self):
entry = gdata.GDataEntry()
try:
entry.id = atom.Id()
except AttributeError:
self.fail('Empty id should not raise an attribute error.')
class LinkFinderTest(unittest.TestCase):
def setUp(self):
self.entry = gdata.GDataEntryFromString(test_data.XML_ENTRY_1)
def testLinkFinderGetsLicenseLink(self):
self.assertEquals(isinstance(self.entry.GetLicenseLink(), atom.Link),
True)
self.assertEquals(self.entry.GetLicenseLink().href,
'http://creativecommons.org/licenses/by-nc/2.5/rdf')
self.assertEquals(self.entry.GetLicenseLink().rel, 'license')
def testLinkFinderGetsAlternateLink(self):
self.assertEquals(isinstance(self.entry.GetAlternateLink(), atom.Link),
True)
self.assertEquals(self.entry.GetAlternateLink().href,
'http://www.provider-host.com/123456789')
self.assertEquals(self.entry.GetAlternateLink().rel, 'alternate')
class GDataFeedTest(unittest.TestCase):
def testCorrectConversionToElementTree(self):
test_feed = gdata.GDataFeedFromString(test_data.GBASE_FEED)
self.assert_(test_feed.total_results is not None)
element_tree = test_feed._ToElementTree()
feed = element_tree.find('{http://www.w3.org/2005/Atom}feed')
self.assert_(element_tree.find(
'{http://a9.com/-/spec/opensearchrss/1.0/}totalResults') is not None)
def testAllowsEmptyId(self):
feed = gdata.GDataFeed()
try:
feed.id = atom.Id()
except AttributeError:
self.fail('Empty id should not raise an attribute error.')
class BatchEntryTest(unittest.TestCase):
def testCorrectConversionFromAndToString(self):
batch_entry = gdata.BatchEntryFromString(test_data.BATCH_ENTRY)
self.assertEquals(batch_entry.batch_id.text, 'itemB')
self.assertEquals(batch_entry.id.text,
'http://www.google.com/base/feeds/items/'
'2173859253842813008')
self.assertEquals(batch_entry.batch_operation.type, 'insert')
self.assertEquals(batch_entry.batch_status.code, '201')
self.assertEquals(batch_entry.batch_status.reason, 'Created')
new_entry = gdata.BatchEntryFromString(str(batch_entry))
self.assertEquals(batch_entry.batch_id.text, new_entry.batch_id.text)
self.assertEquals(batch_entry.id.text, new_entry.id.text)
self.assertEquals(batch_entry.batch_operation.type,
new_entry.batch_operation.type)
self.assertEquals(batch_entry.batch_status.code,
new_entry.batch_status.code)
self.assertEquals(batch_entry.batch_status.reason,
new_entry.batch_status.reason)
class BatchFeedTest(unittest.TestCase):
def setUp(self):
self.batch_feed = gdata.BatchFeed()
self.example_entry = gdata.BatchEntry(
atom_id=atom.Id(text='http://example.com/1'), text='This is a test')
def testConvertRequestFeed(self):
batch_feed = gdata.BatchFeedFromString(test_data.BATCH_FEED_REQUEST)
self.assertEquals(len(batch_feed.entry), 4)
for entry in batch_feed.entry:
self.assert_(isinstance(entry, gdata.BatchEntry))
self.assertEquals(batch_feed.title.text, 'My Batch Feed')
new_feed = gdata.BatchFeedFromString(str(batch_feed))
self.assertEquals(len(new_feed.entry), 4)
for entry in new_feed.entry:
self.assert_(isinstance(entry, gdata.BatchEntry))
self.assertEquals(new_feed.title.text, 'My Batch Feed')
def testConvertResultFeed(self):
batch_feed = gdata.BatchFeedFromString(test_data.BATCH_FEED_RESULT)
self.assertEquals(len(batch_feed.entry), 4)
for entry in batch_feed.entry:
self.assert_(isinstance(entry, gdata.BatchEntry))
if entry.id.text == ('http://www.google.com/base/feeds/items/'
'2173859253842813008'):
self.assertEquals(entry.batch_operation.type, 'insert')
self.assertEquals(entry.batch_id.text, 'itemB')
self.assertEquals(entry.batch_status.code, '201')
self.assertEquals(entry.batch_status.reason, 'Created')
self.assertEquals(batch_feed.title.text, 'My Batch')
new_feed = gdata.BatchFeedFromString(str(batch_feed))
self.assertEquals(len(new_feed.entry), 4)
for entry in new_feed.entry:
self.assert_(isinstance(entry, gdata.BatchEntry))
if entry.id.text == ('http://www.google.com/base/feeds/items/'
'2173859253842813008'):
self.assertEquals(entry.batch_operation.type, 'insert')
self.assertEquals(entry.batch_id.text, 'itemB')
self.assertEquals(entry.batch_status.code, '201')
self.assertEquals(entry.batch_status.reason, 'Created')
self.assertEquals(new_feed.title.text, 'My Batch')
def testAddBatchEntry(self):
try:
self.batch_feed.AddBatchEntry(batch_id_string='a')
self.fail('AddBatchEntry with neither entry or URL should raise Error')
except gdata.MissingRequiredParameters:
pass
new_entry = self.batch_feed.AddBatchEntry(
id_url_string='http://example.com/1')
self.assertEquals(len(self.batch_feed.entry), 1)
self.assertEquals(self.batch_feed.entry[0].id.text,
'http://example.com/1')
self.assertEquals(self.batch_feed.entry[0].batch_id.text, '0')
self.assertEquals(new_entry.id.text, 'http://example.com/1')
self.assertEquals(new_entry.batch_id.text, '0')
to_add = gdata.BatchEntry(atom_id=atom.Id(text='originalId'))
new_entry = self.batch_feed.AddBatchEntry(entry=to_add,
batch_id_string='foo')
self.assertEquals(new_entry.batch_id.text, 'foo')
self.assertEquals(new_entry.id.text, 'originalId')
to_add = gdata.BatchEntry(atom_id=atom.Id(text='originalId'),
batch_id=gdata.BatchId(text='bar'))
new_entry = self.batch_feed.AddBatchEntry(entry=to_add,
id_url_string='newId',
batch_id_string='foo')
self.assertEquals(new_entry.batch_id.text, 'foo')
self.assertEquals(new_entry.id.text, 'originalId')
to_add = gdata.BatchEntry(atom_id=atom.Id(text='originalId'),
batch_id=gdata.BatchId(text='bar'))
new_entry = self.batch_feed.AddBatchEntry(entry=to_add,
id_url_string='newId')
self.assertEquals(new_entry.batch_id.text, 'bar')
self.assertEquals(new_entry.id.text, 'originalId')
to_add = gdata.BatchEntry(atom_id=atom.Id(text='originalId'),
batch_id=gdata.BatchId(text='bar'),
batch_operation=gdata.BatchOperation(
op_type=gdata.BATCH_INSERT))
self.assertEquals(to_add.batch_operation.type, gdata.BATCH_INSERT)
new_entry = self.batch_feed.AddBatchEntry(entry=to_add,
id_url_string='newId', batch_id_string='foo',
operation_string=gdata.BATCH_UPDATE)
self.assertEquals(new_entry.batch_operation.type, gdata.BATCH_UPDATE)
def testAddInsert(self):
first_entry = gdata.BatchEntry(
atom_id=atom.Id(text='http://example.com/1'), text='This is a test1')
self.batch_feed.AddInsert(first_entry)
self.assertEquals(self.batch_feed.entry[0].batch_operation.type,
gdata.BATCH_INSERT)
self.assertEquals(self.batch_feed.entry[0].batch_id.text, '0')
second_entry = gdata.BatchEntry(
atom_id=atom.Id(text='http://example.com/2'), text='This is a test2')
self.batch_feed.AddInsert(second_entry, batch_id_string='foo')
self.assertEquals(self.batch_feed.entry[1].batch_operation.type,
gdata.BATCH_INSERT)
self.assertEquals(self.batch_feed.entry[1].batch_id.text, 'foo')
third_entry = gdata.BatchEntry(
atom_id=atom.Id(text='http://example.com/3'), text='This is a test3')
third_entry.batch_operation = gdata.BatchOperation(
op_type=gdata.BATCH_DELETE)
# Add an entry with a delete operation already assigned.
self.batch_feed.AddInsert(third_entry)
# The batch entry should not have the original operation, it should
# have been changed to an insert.
self.assertEquals(self.batch_feed.entry[2].batch_operation.type,
gdata.BATCH_INSERT)
self.assertEquals(self.batch_feed.entry[2].batch_id.text, '2')
def testAddDelete(self):
# Try deleting an entry
delete_entry = gdata.BatchEntry(
atom_id=atom.Id(text='http://example.com/1'), text='This is a test')
self.batch_feed.AddDelete(entry=delete_entry)
self.assertEquals(self.batch_feed.entry[0].batch_operation.type,
gdata.BATCH_DELETE)
self.assertEquals(self.batch_feed.entry[0].id.text,
'http://example.com/1')
self.assertEquals(self.batch_feed.entry[0].text, 'This is a test')
# Try deleting a URL
self.batch_feed.AddDelete(url_string='http://example.com/2')
self.assertEquals(self.batch_feed.entry[0].batch_operation.type,
gdata.BATCH_DELETE)
self.assertEquals(self.batch_feed.entry[1].id.text,
'http://example.com/2')
self.assert_(self.batch_feed.entry[1].text is None)
def testAddQuery(self):
# Try querying with an existing batch entry
delete_entry = gdata.BatchEntry(
atom_id=atom.Id(text='http://example.com/1'))
self.batch_feed.AddQuery(entry=delete_entry)
self.assertEquals(self.batch_feed.entry[0].batch_operation.type,
gdata.BATCH_QUERY)
self.assertEquals(self.batch_feed.entry[0].id.text,
'http://example.com/1')
# Try querying a URL
self.batch_feed.AddQuery(url_string='http://example.com/2')
self.assertEquals(self.batch_feed.entry[0].batch_operation.type,
gdata.BATCH_QUERY)
self.assertEquals(self.batch_feed.entry[1].id.text,
'http://example.com/2')
def testAddUpdate(self):
# Try updating an entry
delete_entry = gdata.BatchEntry(
atom_id=atom.Id(text='http://example.com/1'), text='This is a test')
self.batch_feed.AddUpdate(entry=delete_entry)
self.assertEquals(self.batch_feed.entry[0].batch_operation.type,
gdata.BATCH_UPDATE)
self.assertEquals(self.batch_feed.entry[0].id.text,
'http://example.com/1')
self.assertEquals(self.batch_feed.entry[0].text, 'This is a test')
class ExtendedPropertyTest(unittest.TestCase):
def testXmlBlobRoundTrip(self):
ep = gdata.ExtendedProperty(name='blobby')
ep.SetXmlBlob('<some_xml attr="test"/>')
extension = ep.GetXmlBlobExtensionElement()
self.assertEquals(extension.tag, 'some_xml')
self.assert_(extension.namespace is None)
self.assertEquals(extension.attributes['attr'], 'test')
ep2 = gdata.ExtendedPropertyFromString(ep.ToString())
extension = ep2.GetXmlBlobExtensionElement()
self.assertEquals(extension.tag, 'some_xml')
self.assert_(extension.namespace is None)
self.assertEquals(extension.attributes['attr'], 'test')
def testGettersShouldReturnNoneWithNoBlob(self):
ep = gdata.ExtendedProperty(name='no blob')
self.assert_(ep.GetXmlBlobExtensionElement() is None)
self.assert_(ep.GetXmlBlobString() is None)
def testGettersReturnCorrectTypes(self):
ep = gdata.ExtendedProperty(name='has blob')
ep.SetXmlBlob('<some_xml attr="test"/>')
self.assert_(isinstance(ep.GetXmlBlobExtensionElement(),
atom.ExtensionElement))
self.assert_(isinstance(ep.GetXmlBlobString(), str))
class FeedLinkTest(unittest.TestCase):
def testCorrectFromStringType(self):
link = gdata.FeedLinkFromString(
'<feedLink xmlns="http://schemas.google.com/g/2005" countHint="5"/>')
self.assertTrue(isinstance(link, gdata.FeedLink))
self.assertEqual(link.count_hint, '5')
def suite():
return conf.build_suite([StartIndexTest, StartIndexTest, GDataEntryTest,
LinkFinderTest, GDataFeedTest, BatchEntryTest, BatchFeedTest,
ExtendedPropertyTest, FeedLinkTest])
if __name__ == '__main__':
unittest.main()
| apache-2.0 |
RafaelPalomar/girder | plugins/provenance/server/__init__.py | 3 | 1966 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
###############################################################################
# Copyright 2014 Kitware Inc.
#
# 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.
###############################################################################
import six
from girder import events
from girder.models.model_base import ValidationException
from girder.utility import setting_utilities
from . import constants
from .resource import ResourceExt
@setting_utilities.validator(constants.PluginSettings.PROVENANCE_RESOURCES)
def validateProvenanceResources(doc):
val = doc['value']
if val:
if not isinstance(val, six.string_types):
raise ValidationException('Provenance Resources must be a string.', 'value')
# accept comma or space separated lists
resources = val.replace(',', ' ').strip().split()
# reformat to a comma-separated list
doc['value'] = ','.join(resources)
def load(info):
ext = ResourceExt(info)
events.bind('model.setting.save.after', 'provenanceMain', ext.bindModels)
events.bind('provenance.initialize', 'provenanceMain', ext.bindModels)
events.trigger('provenance.initialize', info={})
events.bind('model.file.save', 'provenanceMain', ext.fileSaveHandler)
events.bind('model.file.save.created', 'provenanceMain', ext.fileSaveCreatedHandler)
events.bind('model.file.remove', 'provenance', ext.fileRemoveHandler)
| apache-2.0 |
MackZxh/OCA-Choice | account-invoicing/account_invoice_rounding/__openerp__.py | 12 | 2100 | # -*- coding: utf-8 -*-
##############################################################################
#
# Author: Yannick Vaucher
# Copyright 2013 Camptocamp SA
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
##############################################################################
{'name': 'Unit rounded invoice',
'version': '8.0.1.0.0',
'category': 'Accounting',
'description': """
Unit rounded invoice (_`Swedish rounding`)
==========================================
Add a parameter to give a unit for rounding such as CHF 0.05 for Swiss
invoices
In Settings -> Configuration -> Accounting you will find 2 new types of
rounding
- `Swedish Round globally`
To round your invoice total amount, this option will do the adjustment in
the most important tax line of your invoice.
- `Swedish Round by adding an invoice line`
To round your invoice total amount, this option create a invoice line without
taxes on it. This invoice line is tagged as `is_rounding`
You can choose the account on which the invoice line will be written
.. _Swedish rounding : https://en.wikipedia.org/wiki/Swedish_rounding
""",
'author': "Camptocamp,Odoo Community Association (OCA)",
'maintainer': 'Camptocamp',
'website': 'http://www.camptocamp.com/',
'license': 'AGPL-3',
'depends': ['account'],
'data': ['res_config_view.xml'],
'test': ['test/test_invoice_rounding.yml'],
'installable': True,
'auto_install': False,
'application': True,
}
| lgpl-3.0 |
ctozlm/Dato-Core | src/unity/python/graphlab/data_structures/sframe.py | 13 | 196438 | """
This module defines the SFrame class which provides the
ability to create, access and manipulate a remote scalable dataframe object.
SFrame acts similarly to pandas.DataFrame, but the data is completely immutable
and is stored column wise on the GraphLab Server side.
"""
'''
Copyright (C) 2015 Dato, Inc.
All rights reserved.
This software may be modified and distributed under the terms
of the BSD license. See the DATO-PYTHON-LICENSE file for details.
'''
import graphlab.connect as _mt
import graphlab.connect.main as glconnect
from graphlab.cython.cy_type_utils import infer_type_of_list
from graphlab.cython.context import debug_trace as cython_context
from graphlab.cython.cy_sframe import UnitySFrameProxy
from graphlab.util import _check_canvas_enabled, _make_internal_url, _is_callable
from graphlab.data_structures.sarray import SArray, _create_sequential_sarray
import graphlab.aggregate
import graphlab
import array
from prettytable import PrettyTable
from textwrap import wrap
import datetime
import inspect
from graphlab.deps import pandas, HAS_PANDAS
import time
import itertools
import os
import subprocess
import uuid
import platform
__all__ = ['SFrame']
SFRAME_GARBAGE_COLLECTOR = []
FOOTER_STRS = ['Note: Only the head of the SFrame is printed.',
'You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.']
LAZY_FOOTER_STRS = ['Note: Only the head of the SFrame is printed. This SFrame is lazily evaluated.',
'You can use len(sf) to force materialization.']
SFRAME_ROOTS = [# Binary/lib location in production egg
os.path.abspath(os.path.join(os.path.dirname(
os.path.realpath(__file__)), '..')),
# Build tree location of SFrame binaries
os.path.abspath(os.path.join(os.path.dirname(
os.path.realpath(__file__)),
'..', '..', '..', '..', 'sframe')),
# Location of python sources
os.path.abspath(os.path.join(os.path.dirname(
os.path.realpath(__file__)),
'..', '..', '..', '..', 'unity', 'python', 'graphlab')),
# Build tree dependency location
os.path.abspath(os.path.join(os.path.dirname(
os.path.realpath(__file__)),
'..', '..', '..', '..', '..', '..', 'deps', 'local', 'lib'))
]
RDD_SFRAME_PICKLE = "rddtosf_pickle"
RDD_SFRAME_NONPICKLE = "rddtosf_nonpickle"
SFRAME_RDD_PICKLE = "sftordd_pickle"
HDFS_LIB = "libhdfs.so"
RDD_JAR_FILE = "graphlab-create-spark-integration.jar"
SYS_UTIL_PY = "sys_util.py"
RDD_SUPPORT_INITED = False
BINARY_PATHS = {}
STAGING_DIR = None
RDD_SUPPORT = True
PRODUCTION_RUN = False
YARN_OS = None
SPARK_SUPPORT_NAMES = {'RDD_SFRAME_PATH':'rddtosf_pickle',
'RDD_SFRAME_NONPICKLE_PATH':'rddtosf_nonpickle',
'SFRAME_RDD_PATH':'sftordd_pickle',
'HDFS_LIB_PATH':'libhdfs.so',
'RDD_JAR_PATH':'graphlab-create-spark-integration.jar',
'SYS_UTIL_PY_PATH':'sys_util.py',
'SPARK_PIPE_WRAPPER_PATH':'spark_pipe_wrapper'}
first = True
for i in SFRAME_ROOTS:
for key,val in SPARK_SUPPORT_NAMES.iteritems():
tmp_path = os.path.join(i, val)
if key not in BINARY_PATHS and os.path.isfile(tmp_path):
BINARY_PATHS[key] = tmp_path
if all(name in BINARY_PATHS for name in SPARK_SUPPORT_NAMES.keys()):
if first:
PRODUCTION_RUN = True
break
first = False
if not all(name in BINARY_PATHS for name in SPARK_SUPPORT_NAMES.keys()):
RDD_SUPPORT = False
def get_spark_integration_jar_path():
"""
The absolute path of the jar file required to enable GraphLab Create's
integration with Apache Spark.
"""
if 'RDD_JAR_PATH' not in BINARY_PATHS:
raise RuntimeError("Could not find a spark integration jar. "\
"Does your version of GraphLab Create support Spark Integration (is it >= 1.0)?")
return BINARY_PATHS['RDD_JAR_PATH']
def __rdd_support_init__(sprk_ctx):
global YARN_OS
global RDD_SUPPORT_INITED
global STAGING_DIR
global BINARY_PATHS
if not RDD_SUPPORT or RDD_SUPPORT_INITED:
return
# Make sure our GraphLabUtil scala functions are accessible from the driver
try:
tmp = sprk_ctx._jvm.org.graphlab.create.GraphLabUtil.EscapeString(sprk_ctx._jvm.java.lang.String("1,2,3,4"))
except:
raise RuntimeError("Could not execute RDD translation functions. "\
"Please make sure you have started Spark "\
"(either with spark-submit or pyspark) with the following flag set:\n"\
"'--driver-class-path " + BINARY_PATHS['RDD_JAR_PATH']+"'\n"\
"OR set the property spark.driver.extraClassPath in spark-defaults.conf")
dummy_rdd = sprk_ctx.parallelize([1])
if PRODUCTION_RUN and sprk_ctx.master == 'yarn-client':
# Get cluster operating system
os_rdd = dummy_rdd.map(lambda x: platform.system())
YARN_OS = os_rdd.collect()[0]
# Set binary path
for i in BINARY_PATHS.keys():
s = BINARY_PATHS[i]
if os.path.basename(s) == SPARK_SUPPORT_NAMES['SYS_UTIL_PY_PATH']:
continue
if YARN_OS == 'Linux':
BINARY_PATHS[i] = os.path.join(os.path.dirname(s), 'linux', os.path.basename(s))
elif YARN_OS == 'Darwin':
BINARY_PATHS[i] = os.path.join(os.path.dirname(s), 'osx', os.path.basename(s))
else:
raise RuntimeError("YARN cluster has unsupported operating system "\
"(something other than Linux or Mac OS X). "\
"Cannot convert RDDs on this cluster to SFrame.")
# Create staging directory
staging_dir = '.graphlabStaging'
if sprk_ctx.master == 'yarn-client':
tmp_loc = None
# Get that staging directory's full name
tmp_loc = dummy_rdd.map(
lambda x: subprocess.check_output(
["hdfs", "getconf", "-confKey", "fs.defaultFS"]).rstrip()).collect()[0]
STAGING_DIR = os.path.join(tmp_loc, "user", sprk_ctx.sparkUser(), staging_dir)
if STAGING_DIR is None:
raise RuntimeError("Failed to create a staging directory on HDFS. "\
"Do your cluster nodes have a working hdfs client?")
# Actually create the staging dir
unity = glconnect.get_unity()
unity.__mkdir__(STAGING_DIR)
unity.__chmod__(STAGING_DIR, 0777)
elif sprk_ctx.master[0:5] == 'local':
# Save the output sframes to the same temp workspace this engine is
# using
#TODO: Consider cases where server and client aren't on the same machine
unity = glconnect.get_unity()
STAGING_DIR = unity.get_current_cache_file_location()
if STAGING_DIR is None:
raise RuntimeError("Could not retrieve local staging directory! \
Please contact us on http://forum.dato.com.")
else:
raise RuntimeError("Your spark context's master is '" +
str(sprk_ctx.master) +
"'. Only 'local' and 'yarn-client' are supported.")
if sprk_ctx.master == 'yarn-client':
sprk_ctx.addFile(BINARY_PATHS['RDD_SFRAME_PATH'])
sprk_ctx.addFile(BINARY_PATHS['HDFS_LIB_PATH'])
sprk_ctx.addFile(BINARY_PATHS['SFRAME_RDD_PATH'])
sprk_ctx.addFile(BINARY_PATHS['RDD_SFRAME_NONPICKLE_PATH'])
sprk_ctx.addFile(BINARY_PATHS['SYS_UTIL_PY_PATH'])
sprk_ctx.addFile(BINARY_PATHS['SPARK_PIPE_WRAPPER_PATH'])
sprk_ctx._jsc.addJar(BINARY_PATHS['RDD_JAR_PATH'])
RDD_SUPPORT_INITED = True
def load_sframe(filename):
"""
Load an SFrame. The filename extension is used to determine the format
automatically. This function is particularly useful for SFrames previously
saved in binary format. For CSV imports the ``SFrame.read_csv`` function
provides greater control. If the SFrame is in binary format, ``filename`` is
actually a directory, created when the SFrame is saved.
Parameters
----------
filename : string
Location of the file to load. Can be a local path or a remote URL.
Returns
-------
out : SFrame
See Also
--------
SFrame.save, SFrame.read_csv
Examples
--------
>>> sf = graphlab.SFrame({'id':[1,2,3], 'val':['A','B','C']})
>>> sf.save('my_sframe') # 'my_sframe' is a directory
>>> sf_loaded = graphlab.load_sframe('my_sframe')
"""
sf = SFrame(data=filename)
return sf
class SFrame(object):
"""
A tabular, column-mutable dataframe object that can scale to big data. The
data in SFrame is stored column-wise on the GraphLab Server side, and is
stored on persistent storage (e.g. disk) to avoid being constrained by
memory size. Each column in an SFrame is a size-immutable
:class:`~graphlab.SArray`, but SFrames are mutable in that columns can be
added and subtracted with ease. An SFrame essentially acts as an ordered
dict of SArrays.
Currently, we support constructing an SFrame from the following data
formats:
* csv file (comma separated value)
* sframe directory archive (A directory where an sframe was saved
previously)
* general text file (with csv parsing options, See :py:meth:`read_csv()`)
* a Python dictionary
* pandas.DataFrame
* JSON
* Apache Avro
* PySpark RDD
and from the following sources:
* your local file system
* the GraphLab Server's file system
* HDFS
* Amazon S3
* HTTP(S).
Only basic examples of construction are covered here. For more information
and examples, please see the `User Guide <https://dato.com/learn/user
guide/index.html#Working_with_data_Tabular_data>`_, `API Translator
<https://dato.com/learn/translator>`_, `How-Tos
<https://dato.com/learn/how-to>`_, and data science `Gallery
<https://dato.com/learn/gallery>`_.
Parameters
----------
data : array | pandas.DataFrame | string | dict, optional
The actual interpretation of this field is dependent on the ``format``
parameter. If ``data`` is an array or Pandas DataFrame, the contents are
stored in the SFrame. If ``data`` is a string, it is interpreted as a
file. Files can be read from local file system or urls (local://,
hdfs://, s3://, http://).
format : string, optional
Format of the data. The default, "auto" will automatically infer the
input data format. The inference rules are simple: If the data is an
array or a dataframe, it is associated with 'array' and 'dataframe'
respectively. If the data is a string, it is interpreted as a file, and
the file extension is used to infer the file format. The explicit
options are:
- "auto"
- "array"
- "dict"
- "sarray"
- "dataframe"
- "csv"
- "tsv"
- "sframe".
See Also
--------
read_csv:
Create a new SFrame from a csv file. Preferred for text and CSV formats,
because it has a lot more options for controlling the parser.
save : Save an SFrame for later use.
Notes
-----
- When working with the GraphLab EC2 instance (see
:py:func:`graphlab.aws.launch_EC2()`), an SFrame cannot be constructed
using local file path, because it involves a potentially large amount of
data transfer from client to server. However, it is still okay to use a
remote file path. See the examples below. A similar restriction applies to
:py:class:`graphlab.SGraph` and :py:class:`graphlab.SArray`.
- When reading from HDFS on Linux we must guess the location of your java
installation. By default, we will use the location pointed to by the
JAVA_HOME environment variable. If this is not set, we check many common
installation paths. You may use two environment variables to override
this behavior. GRAPHLAB_JAVA_HOME allows you to specify a specific java
installation and overrides JAVA_HOME. GRAPHLAB_LIBJVM_DIRECTORY
overrides all and expects the exact directory that your preferred
libjvm.so file is located. Use this ONLY if you'd like to use a
non-standard JVM.
Examples
--------
>>> import graphlab
>>> from graphlab import SFrame
**Construction**
Construct an SFrame from a dataframe and transfers the dataframe object
across the network.
>>> df = pandas.DataFrame()
>>> sf = SFrame(data=df)
Construct an SFrame from a local csv file (only works for local server).
>>> sf = SFrame(data='~/mydata/foo.csv')
Construct an SFrame from a csv file on Amazon S3. This requires the
environment variables: *AWS_ACCESS_KEY_ID* and *AWS_SECRET_ACCESS_KEY* to be
set before the python session started. Alternatively, you can use
:py:func:`graphlab.aws.set_credentials()` to set the credentials after
python is started and :py:func:`graphlab.aws.get_credentials()` to verify
these environment variables.
>>> sf = SFrame(data='s3://mybucket/foo.csv')
Read from HDFS using a specific java installation (environment variable
only applies when using Linux)
>>> import os
>>> os.environ['GRAPHLAB_JAVA_HOME'] = '/my/path/to/java'
>>> from graphlab import SFrame
>>> sf = SFrame("hdfs://mycluster.example.com:8020/user/myname/coolfile.txt")
An SFrame can be constructed from a dictionary of values or SArrays:
>>> sf = gl.SFrame({'id':[1,2,3],'val':['A','B','C']})
>>> sf
Columns:
id int
val str
Rows: 3
Data:
id val
0 1 A
1 2 B
2 3 C
Or equivalently:
>>> ids = SArray([1,2,3])
>>> vals = SArray(['A','B','C'])
>>> sf = SFrame({'id':ids,'val':vals})
It can also be constructed from an array of SArrays in which case column
names are automatically assigned.
>>> ids = SArray([1,2,3])
>>> vals = SArray(['A','B','C'])
>>> sf = SFrame([ids, vals])
>>> sf
Columns:
X1 int
X2 str
Rows: 3
Data:
X1 X2
0 1 A
1 2 B
2 3 C
If the SFrame is constructed from a list of values, an SFrame of a single
column is constructed.
>>> sf = SFrame([1,2,3])
>>> sf
Columns:
X1 int
Rows: 3
Data:
X1
0 1
1 2
2 3
**Parsing**
The :py:func:`graphlab.SFrame.read_csv()` is quite powerful and, can be
used to import a variety of row-based formats.
First, some simple cases:
>>> !cat ratings.csv
user_id,movie_id,rating
10210,1,1
10213,2,5
10217,2,2
10102,1,3
10109,3,4
10117,5,2
10122,2,4
10114,1,5
10125,1,1
>>> gl.SFrame.read_csv('ratings.csv')
Columns:
user_id int
movie_id int
rating int
Rows: 9
Data:
+---------+----------+--------+
| user_id | movie_id | rating |
+---------+----------+--------+
| 10210 | 1 | 1 |
| 10213 | 2 | 5 |
| 10217 | 2 | 2 |
| 10102 | 1 | 3 |
| 10109 | 3 | 4 |
| 10117 | 5 | 2 |
| 10122 | 2 | 4 |
| 10114 | 1 | 5 |
| 10125 | 1 | 1 |
+---------+----------+--------+
[9 rows x 3 columns]
Delimiters can be specified, if "," is not the delimiter, for instance
space ' ' in this case. Only single character delimiters are supported.
>>> !cat ratings.csv
user_id movie_id rating
10210 1 1
10213 2 5
10217 2 2
10102 1 3
10109 3 4
10117 5 2
10122 2 4
10114 1 5
10125 1 1
>>> gl.SFrame.read_csv('ratings.csv', delimiter=' ')
By default, "NA" or a missing element are interpreted as missing values.
>>> !cat ratings2.csv
user,movie,rating
"tom",,1
harry,5,
jack,2,2
bill,,
>>> gl.SFrame.read_csv('ratings2.csv')
Columns:
user str
movie int
rating int
Rows: 4
Data:
+---------+-------+--------+
| user | movie | rating |
+---------+-------+--------+
| tom | None | 1 |
| harry | 5 | None |
| jack | 2 | 2 |
| missing | None | None |
+---------+-------+--------+
[4 rows x 3 columns]
Furthermore due to the dictionary types and list types, can handle parsing
of JSON-like formats.
>>> !cat ratings3.csv
business, categories, ratings
"Restaurant 1", [1 4 9 10], {"funny":5, "cool":2}
"Restaurant 2", [], {"happy":2, "sad":2}
"Restaurant 3", [2, 11, 12], {}
>>> gl.SFrame.read_csv('ratings3.csv')
Columns:
business str
categories array
ratings dict
Rows: 3
Data:
+--------------+--------------------------------+-------------------------+
| business | categories | ratings |
+--------------+--------------------------------+-------------------------+
| Restaurant 1 | array('d', [1.0, 4.0, 9.0, ... | {'funny': 5, 'cool': 2} |
| Restaurant 2 | array('d') | {'sad': 2, 'happy': 2} |
| Restaurant 3 | array('d', [2.0, 11.0, 12.0]) | {} |
+--------------+--------------------------------+-------------------------+
[3 rows x 3 columns]
The list and dictionary parsers are quite flexible and can absorb a
variety of purely formatted inputs. Also, note that the list and dictionary
types are recursive, allowing for arbitrary values to be contained.
All these are valid lists:
>>> !cat interesting_lists.csv
list
[]
[1,2,3]
[1;2,3]
[1 2 3]
[{a:b}]
["c",d, e]
[[a]]
>>> gl.SFrame.read_csv('interesting_lists.csv')
Columns:
list list
Rows: 7
Data:
+-----------------+
| list |
+-----------------+
| [] |
| [1, 2, 3] |
| [1, 2, 3] |
| [1, 2, 3] |
| [{'a': 'b'}] |
| ['c', 'd', 'e'] |
| [['a']] |
+-----------------+
[7 rows x 1 columns]
All these are valid dicts:
>>> !cat interesting_dicts.csv
dict
{"classic":1,"dict":1}
{space:1 seperated:1}
{emptyvalue:}
{}
{:}
{recursive1:[{a:b}]}
{:[{:[a]}]}
>>> gl.SFrame.read_csv('interesting_dicts.csv')
Columns:
dict dict
Rows: 7
Data:
+------------------------------+
| dict |
+------------------------------+
| {'dict': 1, 'classic': 1} |
| {'seperated': 1, 'space': 1} |
| {'emptyvalue': None} |
| {} |
| {None: None} |
| {'recursive1': [{'a': 'b'}]} |
| {None: [{None: array('d')}]} |
+------------------------------+
[7 rows x 1 columns]
**Saving**
Save and load the sframe in native format.
>>> sf.save('mysframedir')
>>> sf2 = graphlab.load_sframe('mysframedir')
**Column Manipulation **
An SFrame is composed of a collection of columns of SArrays, and individual
SArrays can be extracted easily. For instance given an SFrame:
>>> sf = SFrame({'id':[1,2,3],'val':['A','B','C']})
>>> sf
Columns:
id int
val str
Rows: 3
Data:
id val
0 1 A
1 2 B
2 3 C
The "id" column can be extracted using:
>>> sf["id"]
dtype: int
Rows: 3
[1, 2, 3]
And can be deleted using:
>>> del sf["id"]
Multiple columns can be selected by passing a list of column names:
>>> sf = SFrame({'id':[1,2,3],'val':['A','B','C'],'val2':[5,6,7]})
>>> sf
Columns:
id int
val str
val2 int
Rows: 3
Data:
id val val2
0 1 A 5
1 2 B 6
2 3 C 7
>>> sf2 = sf[['id','val']]
>>> sf2
Columns:
id int
val str
Rows: 3
Data:
id val
0 1 A
1 2 B
2 3 C
The same mechanism can be used to re-order columns:
>>> sf = SFrame({'id':[1,2,3],'val':['A','B','C']})
>>> sf
Columns:
id int
val str
Rows: 3
Data:
id val
0 1 A
1 2 B
2 3 C
>>> sf[['val','id']]
>>> sf
Columns:
val str
id int
Rows: 3
Data:
val id
0 A 1
1 B 2
2 C 3
**Element Access and Slicing**
SFrames can be accessed by integer keys just like a regular python list.
Such operations may not be fast on large datasets so looping over an SFrame
should be avoided.
>>> sf = SFrame({'id':[1,2,3],'val':['A','B','C']})
>>> sf[0]
{'id': 1, 'val': 'A'}
>>> sf[2]
{'id': 3, 'val': 'C'}
>>> sf[5]
IndexError: SFrame index out of range
Negative indices can be used to access elements from the tail of the array
>>> sf[-1] # returns the last element
{'id': 3, 'val': 'C'}
>>> sf[-2] # returns the second to last element
{'id': 2, 'val': 'B'}
The SFrame also supports the full range of python slicing operators:
>>> sf[1000:] # Returns an SFrame containing rows 1000 to the end
>>> sf[:1000] # Returns an SFrame containing rows 0 to row 999 inclusive
>>> sf[0:1000:2] # Returns an SFrame containing rows 0 to row 1000 in steps of 2
>>> sf[-100:] # Returns an SFrame containing last 100 rows
>>> sf[-100:len(sf):2] # Returns an SFrame containing last 100 rows in steps of 2
**Logical Filter**
An SFrame can be filtered using
>>> sframe[binary_filter]
where sframe is an SFrame and binary_filter is an SArray of the same length.
The result is a new SFrame which contains only rows of the SFrame where its
matching row in the binary_filter is non zero.
This permits the use of boolean operators that can be used to perform
logical filtering operations. For instance, given an SFrame
>>> sf
Columns:
id int
val str
Rows: 3
Data:
id val
0 1 A
1 2 B
2 3 C
>>> sf[(sf['id'] >= 1) & (sf['id'] <= 2)]
Columns:
id int
val str
Rows: 3
Data:
id val
0 1 A
1 2 B
See :class:`~graphlab.SArray` for more details on the use of the logical
filter.
This can also be used more generally to provide filtering capability which
is otherwise not expressible with simple boolean functions. For instance:
>>> sf[sf['id'].apply(lambda x: math.log(x) <= 1)]
Columns:
id int
val str
Rows: 3
Data:
id val
0 1 A
1 2 B
Or alternatively:
>>> sf[sf.apply(lambda x: math.log(x['id']) <= 1)]
Create an SFrame from a Python dictionary.
>>> from graphlab import SFrame
>>> sf = SFrame({'id':[1,2,3], 'val':['A','B','C']})
>>> sf
Columns:
id int
val str
Rows: 3
Data:
id val
0 1 A
1 2 B
2 3 C
"""
__slots__ = ['shape', '__proxy__', '_proxy']
def __init__(self, data=None,
format='auto',
_proxy=None):
"""__init__(data=list(), format='auto')
Construct a new SFrame from a url or a pandas.DataFrame.
"""
# emit metrics for num_rows, num_columns, and type (local://, s3, hdfs, http)
tracker = _mt._get_metric_tracker()
if (_proxy):
self.__proxy__ = _proxy
else:
self.__proxy__ = UnitySFrameProxy(glconnect.get_client())
_format = None
if (format == 'auto'):
if (HAS_PANDAS and isinstance(data, pandas.DataFrame)):
_format = 'dataframe'
tracker.track('sframe.location.memory', value=1)
elif (isinstance(data, str) or isinstance(data, unicode)):
if data.find('://') == -1:
suffix = 'local'
else:
suffix = data.split('://')[0]
tracker.track(('sframe.location.%s' % (suffix)), value=1)
if data.endswith(('.csv', '.csv.gz')):
_format = 'csv'
elif data.endswith(('.tsv', '.tsv.gz')):
_format = 'tsv'
elif data.endswith(('.txt', '.txt.gz')):
print "Assuming file is csv. For other delimiters, " + \
"please use `SFrame.read_csv`."
_format = 'csv'
else:
_format = 'sframe'
elif type(data) == SArray:
_format = 'sarray'
elif isinstance(data, SFrame):
_format = 'sframe_obj'
elif (hasattr(data, 'iteritems')):
_format = 'dict'
tracker.track('sframe.location.memory', value=1)
elif hasattr(data, '__iter__'):
_format = 'array'
tracker.track('sframe.location.memory', value=1)
elif data is None:
_format = 'empty'
else:
raise ValueError('Cannot infer input type for data ' + str(data))
else:
_format = format
tracker.track(('sframe.format.%s' % _format), value=1)
with cython_context():
if (_format == 'dataframe'):
self.__proxy__.load_from_dataframe(data)
elif (_format == 'sframe_obj'):
for col in data.column_names():
self.__proxy__.add_column(data[col].__proxy__, col)
elif (_format == 'sarray'):
self.__proxy__.add_column(data.__proxy__, "")
elif (_format == 'array'):
if len(data) > 0:
unique_types = set([type(x) for x in data if x is not None])
if len(unique_types) == 1 and SArray in unique_types:
for arr in data:
self.add_column(arr)
elif SArray in unique_types:
raise ValueError("Cannot create SFrame from mix of regular values and SArrays")
else:
self.__proxy__.add_column(SArray(data).__proxy__, "")
elif (_format == 'dict'):
for key,val in iter(sorted(data.iteritems())):
if (type(val) == SArray):
self.__proxy__.add_column(val.__proxy__, key)
else:
self.__proxy__.add_column(SArray(val).__proxy__, key)
elif (_format == 'csv'):
url = _make_internal_url(data)
tmpsf = SFrame.read_csv(url, delimiter=',', header=True)
self.__proxy__ = tmpsf.__proxy__
elif (_format == 'tsv'):
url = _make_internal_url(data)
tmpsf = SFrame.read_csv(url, delimiter='\t', header=True)
self.__proxy__ = tmpsf.__proxy__
elif (_format == 'sframe'):
url = _make_internal_url(data)
self.__proxy__.load_from_sframe_index(url)
elif (_format == 'empty'):
pass
else:
raise ValueError('Unknown input type: ' + format)
sframe_size = -1
if self.__has_size__():
sframe_size = self.num_rows()
tracker.track('sframe.row.size', value=sframe_size)
tracker.track('sframe.col.size', value=self.num_cols())
@staticmethod
def _infer_column_types_from_lines(first_rows):
if (len(first_rows.column_names()) < 1):
print "Insufficient number of columns to perform type inference"
raise RuntimeError("Insufficient columns ")
if len(first_rows) < 1:
print "Insufficient number of rows to perform type inference"
raise RuntimeError("Insufficient rows")
# gets all the values column-wise
all_column_values_transposed = [list(first_rows[col])
for col in first_rows.column_names()]
# transpose
all_column_values = [list(x) for x in zip(*all_column_values_transposed)]
all_column_type_hints = [[type(t) for t in vals] for vals in all_column_values]
# collect the hints
# if every line was inferred to have a different number of elements, die
if len(set(len(x) for x in all_column_type_hints)) != 1:
print "Unable to infer column types. Defaulting to str"
return str
import types
column_type_hints = all_column_type_hints[0]
# now perform type combining across rows
for i in range(1, len(all_column_type_hints)):
currow = all_column_type_hints[i]
for j in range(len(column_type_hints)):
# combine types
d = set([currow[j], column_type_hints[j]])
if (len(d) == 1):
# easy case. both agree on the type
continue
if ((int in d) and (float in d)):
# one is an int, one is a float. its a float
column_type_hints[j] = float
elif ((array.array in d) and (list in d)):
# one is an array , one is a list. its a list
column_type_hints[j] = list
elif types.NoneType in d:
# one is a NoneType. assign to other type
if currow[j] != types.NoneType:
column_type_hints[j] = currow[j]
else:
column_type_hints[j] = str
# final pass. everything whih is still NoneType is now a str
for i in range(len(column_type_hints)):
if column_type_hints[i] == types.NoneType:
column_type_hints[i] = str
return column_type_hints
@classmethod
def _read_csv_impl(cls,
url,
delimiter=',',
header=True,
error_bad_lines=False,
comment_char='',
escape_char='\\',
double_quote=True,
quote_char='\"',
skip_initial_space=True,
column_type_hints=None,
na_values=["NA"],
nrows=None,
verbose=True,
store_errors=True):
"""
Constructs an SFrame from a CSV file or a path to multiple CSVs, and
returns a pair containing the SFrame and optionally
(if store_errors=True) a dict of filenames to SArrays
indicating for each file, what are the incorrectly parsed lines
encountered.
Parameters
----------
store_errors : bool
If true, the output errors dict will be filled.
See `read_csv` for the rest of the parameters.
"""
parsing_config = dict()
parsing_config["delimiter"] = delimiter
parsing_config["use_header"] = header
parsing_config["continue_on_failure"] = not error_bad_lines
parsing_config["comment_char"] = comment_char
parsing_config["escape_char"] = escape_char
parsing_config["double_quote"] = double_quote
parsing_config["quote_char"] = quote_char
parsing_config["skip_initial_space"] = skip_initial_space
parsing_config["store_errors"] = store_errors
if type(na_values) is str:
na_values = [na_values]
if na_values is not None and len(na_values) > 0:
parsing_config["na_values"] = na_values
if nrows != None:
parsing_config["row_limit"] = nrows
proxy = UnitySFrameProxy(glconnect.get_client())
internal_url = _make_internal_url(url)
if (not verbose):
glconnect.get_client().set_log_progress(False)
# Attempt to automatically detect the column types. Either produce a
# list of types; otherwise default to all str types.
column_type_inference_was_used = False
if column_type_hints is None:
try:
# Get the first 100 rows (using all the desired arguments).
first_rows = graphlab.SFrame.read_csv(url, nrows=100,
column_type_hints=type(None),
header=header,
delimiter=delimiter,
comment_char=comment_char,
escape_char=escape_char,
double_quote=double_quote,
quote_char=quote_char,
skip_initial_space=skip_initial_space,
na_values = na_values)
column_type_hints = SFrame._infer_column_types_from_lines(first_rows)
typelist = '[' + ','.join(t.__name__ for t in column_type_hints) + ']'
print "------------------------------------------------------"
print "Inferred types from first line of file as "
print "column_type_hints="+ typelist
print "If parsing fails due to incorrect types, you can correct"
print "the inferred type list above and pass it to read_csv in"
print "the column_type_hints argument"
print "------------------------------------------------------"
column_type_inference_was_used = True
except Exception as e:
if type(e) == RuntimeError and "CSV parsing cancelled" in e.message:
raise e
# If the above fails, default back to str for all columns.
column_type_hints = str
print 'Could not detect types. Using str for each column.'
if type(column_type_hints) is type:
type_hints = {'__all_columns__': column_type_hints}
elif type(column_type_hints) is list:
type_hints = dict(zip(['__X%d__' % i for i in range(len(column_type_hints))], column_type_hints))
elif type(column_type_hints) is dict:
type_hints = column_type_hints
else:
raise TypeError("Invalid type for column_type_hints. Must be a dictionary, list or a single type.")
_mt._get_metric_tracker().track('sframe.csv.parse')
suffix=''
if url.find('://') == -1:
suffix = 'local'
else:
suffix = url.split('://')[0]
_mt._get_metric_tracker().track(('sframe.location.%s' % (suffix)), value=1)
try:
with cython_context():
errors = proxy.load_from_csvs(internal_url, parsing_config, type_hints)
except Exception as e:
if type(e) == RuntimeError and "CSV parsing cancelled" in e.message:
raise e
if column_type_inference_was_used:
# try again
print "Unable to parse the file with automatic type inference."
print "Defaulting to column_type_hints=str"
type_hints = {'__all_columns__': str}
try:
with cython_context():
errors = proxy.load_from_csvs(internal_url, parsing_config, type_hints)
except:
raise
else:
raise
glconnect.get_client().set_log_progress(True)
return (cls(_proxy=proxy), { f: SArray(_proxy = es) for (f, es) in errors.iteritems() })
@classmethod
def read_csv_with_errors(cls,
url,
delimiter=',',
header=True,
comment_char='',
escape_char='\\',
double_quote=True,
quote_char='\"',
skip_initial_space=True,
column_type_hints=None,
na_values=["NA"],
nrows=None,
verbose=True):
"""
Constructs an SFrame from a CSV file or a path to multiple CSVs, and
returns a pair containing the SFrame and a dict of filenames to SArrays
indicating for each file, what are the incorrectly parsed lines
encountered.
Parameters
----------
url : string
Location of the CSV file or directory to load. If URL is a directory
or a "glob" pattern, all matching files will be loaded.
delimiter : string, optional
This describes the delimiter used for parsing csv files.
header : bool, optional
If true, uses the first row as the column names. Otherwise use the
default column names: 'X1, X2, ...'.
comment_char : string, optional
The character which denotes that the
remainder of the line is a comment.
escape_char : string, optional
Character which begins a C escape sequence
double_quote : bool, optional
If True, two consecutive quotes in a string are parsed to a single
quote.
quote_char : string, optional
Character sequence that indicates a quote.
skip_initial_space : bool, optional
Ignore extra spaces at the start of a field
column_type_hints : None, type, list[type], dict[string, type], optional
This provides type hints for each column. By default, this method
attempts to detect the type of each column automatically.
Supported types are int, float, str, list, dict, and array.array.
* If a single type is provided, the type will be
applied to all columns. For instance, column_type_hints=float
will force all columns to be parsed as float.
* If a list of types is provided, the types applies
to each column in order, e.g.[int, float, str]
will parse the first column as int, second as float and third as
string.
* If a dictionary of column name to type is provided,
each type value in the dictionary is applied to the key it
belongs to.
For instance {'user':int} will hint that the column called "user"
should be parsed as an integer, and the rest will default to
string.
na_values : str | list of str, optional
A string or list of strings to be interpreted as missing values.
nrows : int, optional
If set, only this many rows will be read from the file.
verbose : bool, optional
If True, print the progress.
Returns
-------
out : tuple
The first element is the SFrame with good data. The second element
is a dictionary of filenames to SArrays indicating for each file,
what are the incorrectly parsed lines encountered.
See Also
--------
read_csv, SFrame
Examples
--------
>>> bad_url = 'https://s3.amazonaws.com/gl-testdata/bad_csv_example.csv'
>>> (sf, bad_lines) = graphlab.SFrame.read_csv_with_errors(bad_url)
>>> sf
+---------+----------+--------+
| user_id | movie_id | rating |
+---------+----------+--------+
| 25904 | 1663 | 3 |
| 25907 | 1663 | 3 |
| 25923 | 1663 | 3 |
| 25924 | 1663 | 3 |
| 25928 | 1663 | 2 |
| ... | ... | ... |
+---------+----------+--------+
[98 rows x 3 columns]
>>> bad_lines
{'https://s3.amazonaws.com/gl-testdata/bad_csv_example.csv': dtype: str
Rows: 1
['x,y,z,a,b,c']}
"""
return cls._read_csv_impl(url,
delimiter=delimiter,
header=header,
error_bad_lines=False, # we are storing errors,
# thus we must not fail
# on bad lines
comment_char=comment_char,
escape_char=escape_char,
double_quote=double_quote,
quote_char=quote_char,
skip_initial_space=skip_initial_space,
column_type_hints=column_type_hints,
na_values=na_values,
nrows=nrows,
verbose=verbose,
store_errors=True)
@classmethod
def read_csv(cls,
url,
delimiter=',',
header=True,
error_bad_lines=False,
comment_char='',
escape_char='\\',
double_quote=True,
quote_char='\"',
skip_initial_space=True,
column_type_hints=None,
na_values=["NA"],
nrows=None,
verbose=True):
"""
Constructs an SFrame from a CSV file or a path to multiple CSVs.
Parameters
----------
url : string
Location of the CSV file or directory to load. If URL is a directory
or a "glob" pattern, all matching files will be loaded.
delimiter : string, optional
This describes the delimiter used for parsing csv files.
header : bool, optional
If true, uses the first row as the column names. Otherwise use the
default column names : 'X1, X2, ...'.
error_bad_lines : bool
If true, will fail upon encountering a bad line. If false, will
continue parsing skipping lines which fail to parse correctly.
A sample of the first 10 encountered bad lines will be printed.
comment_char : string, optional
The character which denotes that the remainder of the line is a
comment.
escape_char : string, optional
Character which begins a C escape sequence
double_quote : bool, optional
If True, two consecutive quotes in a string are parsed to a single
quote.
quote_char : string, optional
Character sequence that indicates a quote.
skip_initial_space : bool, optional
Ignore extra spaces at the start of a field
column_type_hints : None, type, list[type], dict[string, type], optional
This provides type hints for each column. By default, this method
attempts to detect the type of each column automatically.
Supported types are int, float, str, list, dict, and array.array.
* If a single type is provided, the type will be
applied to all columns. For instance, column_type_hints=float
will force all columns to be parsed as float.
* If a list of types is provided, the types applies
to each column in order, e.g.[int, float, str]
will parse the first column as int, second as float and third as
string.
* If a dictionary of column name to type is provided,
each type value in the dictionary is applied to the key it
belongs to.
For instance {'user':int} will hint that the column called "user"
should be parsed as an integer, and the rest will default to
string.
na_values : str | list of str, optional
A string or list of strings to be interpreted as missing values.
nrows : int, optional
If set, only this many rows will be read from the file.
verbose : bool, optional
If True, print the progress.
Returns
-------
out : SFrame
See Also
--------
read_csv_with_errors, SFrame
Examples
--------
Read a regular csv file, with all default options, automatically
determine types:
>>> url = 'http://s3.amazonaws.com/gl-testdata/rating_data_example.csv'
>>> sf = graphlab.SFrame.read_csv(url)
>>> sf
Columns:
user_id int
movie_id int
rating int
Rows: 10000
+---------+----------+--------+
| user_id | movie_id | rating |
+---------+----------+--------+
| 25904 | 1663 | 3 |
| 25907 | 1663 | 3 |
| 25923 | 1663 | 3 |
| 25924 | 1663 | 3 |
| 25928 | 1663 | 2 |
| ... | ... | ... |
+---------+----------+--------+
[10000 rows x 3 columns]
Read only the first 100 lines of the csv file:
>>> sf = graphlab.SFrame.read_csv(url, nrows=100)
>>> sf
Columns:
user_id int
movie_id int
rating int
Rows: 100
+---------+----------+--------+
| user_id | movie_id | rating |
+---------+----------+--------+
| 25904 | 1663 | 3 |
| 25907 | 1663 | 3 |
| 25923 | 1663 | 3 |
| 25924 | 1663 | 3 |
| 25928 | 1663 | 2 |
| ... | ... | ... |
+---------+----------+--------+
[100 rows x 3 columns]
Read all columns as str type
>>> sf = graphlab.SFrame.read_csv(url, column_type_hints=str)
>>> sf
Columns:
user_id str
movie_id str
rating str
Rows: 10000
+---------+----------+--------+
| user_id | movie_id | rating |
+---------+----------+--------+
| 25904 | 1663 | 3 |
| 25907 | 1663 | 3 |
| 25923 | 1663 | 3 |
| 25924 | 1663 | 3 |
| 25928 | 1663 | 2 |
| ... | ... | ... |
+---------+----------+--------+
[10000 rows x 3 columns]
Specify types for a subset of columns and leave the rest to be str.
>>> sf = graphlab.SFrame.read_csv(url,
... column_type_hints={
... 'user_id':int, 'rating':float
... })
>>> sf
Columns:
user_id str
movie_id str
rating float
Rows: 10000
+---------+----------+--------+
| user_id | movie_id | rating |
+---------+----------+--------+
| 25904 | 1663 | 3.0 |
| 25907 | 1663 | 3.0 |
| 25923 | 1663 | 3.0 |
| 25924 | 1663 | 3.0 |
| 25928 | 1663 | 2.0 |
| ... | ... | ... |
+---------+----------+--------+
[10000 rows x 3 columns]
Not treat first line as header:
>>> sf = graphlab.SFrame.read_csv(url, header=False)
>>> sf
Columns:
X1 str
X2 str
X3 str
Rows: 10001
+---------+----------+--------+
| X1 | X2 | X3 |
+---------+----------+--------+
| user_id | movie_id | rating |
| 25904 | 1663 | 3 |
| 25907 | 1663 | 3 |
| 25923 | 1663 | 3 |
| 25924 | 1663 | 3 |
| 25928 | 1663 | 2 |
| ... | ... | ... |
+---------+----------+--------+
[10001 rows x 3 columns]
Treat '3' as missing value:
>>> sf = graphlab.SFrame.read_csv(url, na_values=['3'], column_type_hints=str)
>>> sf
Columns:
user_id str
movie_id str
rating str
Rows: 10000
+---------+----------+--------+
| user_id | movie_id | rating |
+---------+----------+--------+
| 25904 | 1663 | None |
| 25907 | 1663 | None |
| 25923 | 1663 | None |
| 25924 | 1663 | None |
| 25928 | 1663 | 2 |
| ... | ... | ... |
+---------+----------+--------+
[10000 rows x 3 columns]
Throw error on parse failure:
>>> bad_url = 'https://s3.amazonaws.com/gl-testdata/bad_csv_example.csv'
>>> sf = graphlab.SFrame.read_csv(bad_url, error_bad_lines=True)
RuntimeError: Runtime Exception. Unable to parse line "x,y,z,a,b,c"
Set error_bad_lines=False to skip bad lines
"""
return cls._read_csv_impl(url,
delimiter=delimiter,
header=header,
error_bad_lines=error_bad_lines,
comment_char=comment_char,
escape_char=escape_char,
double_quote=double_quote,
quote_char=quote_char,
skip_initial_space=skip_initial_space,
column_type_hints=column_type_hints,
na_values=na_values,
nrows=nrows,
verbose=verbose,
store_errors=False)[0]
def to_schema_rdd(self,sc,sql,number_of_partitions=4):
"""
Convert the current SFrame to the Spark SchemaRDD.
To enable this function, you must add the jar file bundled with GraphLab
Create to the Spark driver's classpath. This must happen BEFORE Spark
launches its JVM, or else it will have no effect. To do this, first get
the location of the packaged jar with
`graphlab.get_spark_integration_jar_path`. You then have two options:
1. Add the path to the jar to your spark-defaults.conf file. The
property to set is 'spark.driver.extraClassPath'.
OR
2. Add the jar's path as a command line option to your favorite way to
start pyspark (either spark-submit or pyspark). For this, use the
command line option '--driver-class-path'.
Parameters
----------
sc : SparkContext
sc is an existing SparkContext.
sql : SQLContext
sql is an existing SQLContext.
number_of_partitions : int
number of partitions for the output rdd
Returns
----------
out: SchemaRDD
Examples
--------
>>> from pyspark import SparkContext, SQLContext
>>> from graphlab import SFrame
>>> sc = SparkContext('local')
>>> sqlc = SQLContext(sc)
>>> sf = SFrame({'x': [1,2,3], 'y': ['fish', 'chips', 'salad']})
>>> rdd = sf.to_schema_rdd(sc, sqlc)
>>> rdd.collect()
[Row(x=1, y=u'fish'), Row(x=2, y=u'chips'), Row(x=3, y=u'salad')]
"""
def homogeneous_type(seq):
if seq is None or len(seq) == 0:
return True
iseq = iter(seq)
first_type = type(next(iseq))
return True if all( (type(x) is first_type) for x in iseq ) else False
if len(self) == 0:
raise ValueError("SFrame is empty")
column_names = self.column_names()
first_row = self.head(1)[0]
for name in column_names:
if hasattr(first_row[name],'__iter__') and homogeneous_type(first_row[name]) is not True:
raise TypeError("Support for translation to Spark SchemaRDD not enabled for heterogeneous iterable type (column: %s). Use SFrame.to_rdd()." % name)
for _type in self.column_types():
if(_type.__name__ == 'datetime'):
raise TypeError("Support for translation to Spark SchemaRDD not enabled for datetime type. Use SFrame.to_rdd() ")
rdd = self.to_rdd(sc,number_of_partitions);
from pyspark.sql import Row
rowRdd = rdd.map(lambda x: Row(**x))
return sql.inferSchema(rowRdd)
def to_rdd(self, sc, number_of_partitions=4):
"""
Convert the current SFrame to the Spark RDD.
To enable this function, you must add the jar file bundled with GraphLab
Create to the Spark driver's classpath. This must happen BEFORE Spark
launches its JVM, or else it will have no effect. To do this, first get
the location of the packaged jar with
`graphlab.get_spark_integration_jar_path`. You then have two options:
1. Add the path to the jar to your spark-defaults.conf file. The
property to set is 'spark.driver.extraClassPath'.
OR
2. Add the jar's path as a command line option to your favorite way to
start pyspark (either spark-submit or pyspark). For this, use the
command line option '--driver-class-path'.
Parameters
----------
sc : SparkContext
sc is an existing SparkContext.
number_of_partitions: int
number of partitions for the output rdd
Returns
----------
out: RDD
Examples
--------
>>> from pyspark import SparkContext
>>> from graphlab import SFrame
>>> sc = SparkContext('local')
>>> sf = SFrame({'x': [1,2,3], 'y': ['fish', 'chips', 'salad']})
>>> rdd = sf.to_rdd(sc)
>>> rdd.collect()
[{'x': 1L, 'y': 'fish'}, {'x': 2L, 'y': 'chips'}, {'x': 3L, 'y': 'salad'}]
"""
_mt._get_metric_tracker().track('sframe.to_rdd')
if not RDD_SUPPORT:
raise Exception("Support for translation to Spark RDDs not enabled.")
for _type in self.column_types():
if(_type.__name__ == 'Image'):
raise TypeError("Support for translation to Spark RDDs not enabled for Image type.")
if type(number_of_partitions) is not int:
raise ValueError("number_of_partitions parameter expects an integer type")
if number_of_partitions == 0:
raise ValueError("number_of_partitions can not be initialized to zero")
# Save SFrame in a temporary place
tmp_loc = self.__get_staging_dir__(sc)
sf_loc = os.path.join(tmp_loc, str(uuid.uuid4()))
self.save(sf_loc)
# Keep track of the temporary sframe that is saved(). We need to delete it eventually.
dummysf = load_sframe(sf_loc)
dummysf.__proxy__.delete_on_close()
SFRAME_GARBAGE_COLLECTOR.append(dummysf)
sframe_len = self.__len__()
small_partition_size = sframe_len/number_of_partitions
big_partition_size = small_partition_size + 1
num_big_partition_size = sframe_len % number_of_partitions
num_small_partition_size = number_of_partitions - num_big_partition_size
count = 0
start_index = 0
ranges = []
while(count < number_of_partitions):
if(count < num_big_partition_size):
ranges.append((str(start_index)+":"+str(start_index + big_partition_size)))
start_index = start_index + big_partition_size
else:
ranges.append((str(start_index)+":"+str(start_index + small_partition_size)))
start_index = start_index + small_partition_size
count+=1
from pyspark import RDD
rdd = sc.parallelize(ranges,number_of_partitions)
if sc.master[0:5] == 'local':
pipeRdd = sc._jvm.org.graphlab.create.GraphLabUtil.pythonToJava(
rdd._jrdd).pipe(
BINARY_PATHS['SPARK_PIPE_WRAPPER_PATH'] + \
" " + BINARY_PATHS['SFRAME_RDD_PATH'] + " " + sf_loc)
elif sc.master == 'yarn-client':
pipeRdd = sc._jvm.org.graphlab.create.GraphLabUtil.pythonToJava(
rdd._jrdd).pipe(
"./" + SPARK_SUPPORT_NAMES['SPARK_PIPE_WRAPPER_PATH'] + \
" " + "./" + SPARK_SUPPORT_NAMES['SFRAME_RDD_PATH'] + \
" " + sf_loc)
serializedRdd = sc._jvm.org.graphlab.create.GraphLabUtil.stringToByte(pipeRdd)
import pyspark
output_rdd = RDD(serializedRdd,sc,pyspark.serializers.PickleSerializer())
return output_rdd
@classmethod
def __get_staging_dir__(cls,cur_sc):
if not RDD_SUPPORT_INITED:
__rdd_support_init__(cur_sc)
return STAGING_DIR
@classmethod
def from_rdd(cls, rdd):
"""
Convert a Spark RDD into a GraphLab Create SFrame.
To enable this function, you must add the jar file bundled with GraphLab
Create to the Spark driver's classpath. This must happen BEFORE Spark
launches its JVM, or else it will have no effect. To do this, first get
the location of the packaged jar with
`graphlab.get_spark_integration_jar_path`. You then have two options:
1. Add the path to the jar to your spark-defaults.conf file. The
property to set is 'spark.driver.extraClassPath'.
OR
2. Add the jar's path as a command line option to your favorite way to
start pyspark (either spark-submit or pyspark). For this, use the
command line option '--driver-class-path'.
Parameters
----------
rdd : pyspark.rdd.RDD
Returns
-------
out : SFrame
Examples
--------
>>> from pyspark import SparkContext
>>> from graphlab import SFrame
>>> sc = SparkContext('local')
>>> rdd = sc.parallelize([1,2,3])
>>> sf = SFrame.from_rdd(rdd)
>>> sf
Data:
+-----+
| X1 |
+-----+
| 1.0 |
| 2.0 |
| 3.0 |
+-----+
[3 rows x 1 columns]
"""
_mt._get_metric_tracker().track('sframe.from_rdd')
if not RDD_SUPPORT:
raise Exception("Support for translation to Spark RDDs not enabled.")
checkRes = rdd.take(1);
if len(checkRes) > 0 and checkRes[0].__class__.__name__ == 'Row' and rdd.__class__.__name__ not in {'SchemaRDD','DataFrame'}:
raise Exception("Conversion from RDD(pyspark.sql.Row) to SFrame not supported. Please call inferSchema(RDD) first.")
if(rdd._jrdd_deserializer.__class__.__name__ == 'UTF8Deserializer'):
return SFrame.__from_UTF8Deserialized_rdd__(rdd)
sf_names = None
rdd_type = "rdd"
if rdd.__class__.__name__ in {'SchemaRDD','DataFrame'}:
rdd_type = "schemardd"
first_row = rdd.take(1)[0]
if hasattr(first_row, 'keys'):
sf_names = first_row.keys()
else:
sf_names = first_row.__FIELDS__
sf_names = [str(i) for i in sf_names]
cur_sc = rdd.ctx
tmp_loc = SFrame.__get_staging_dir__(cur_sc)
if tmp_loc is None:
raise RuntimeError("Could not determine staging directory for SFrame files.")
mode = "batch"
if(rdd._jrdd_deserializer.__class__.__name__ == 'PickleSerializer'):
mode = "pickle"
if cur_sc.master[0:5] == 'local':
t = cur_sc._jvm.org.graphlab.create.GraphLabUtil.byteToString(
rdd._jrdd).pipe(
BINARY_PATHS['SPARK_PIPE_WRAPPER_PATH'] + " " + \
BINARY_PATHS['RDD_SFRAME_PATH'] + " " + tmp_loc +\
" " + mode + " " + rdd_type)
else:
t = cur_sc._jvm.org.graphlab.create.GraphLabUtil.byteToString(
rdd._jrdd).pipe(
"./" + SPARK_SUPPORT_NAMES['SPARK_PIPE_WRAPPER_PATH'] +\
" " + "./" + SPARK_SUPPORT_NAMES['RDD_SFRAME_PATH'] + " " +\
tmp_loc + " " + mode + " " + rdd_type)
# We get the location of an SFrame index file per Spark partition in
# the result. We assume that this is in partition order.
res = t.collect()
out_sf = cls()
sframe_list = []
for url in res:
sf = SFrame()
sf.__proxy__.load_from_sframe_index(_make_internal_url(url))
sf.__proxy__.delete_on_close()
out_sf_coltypes = out_sf.column_types()
if(len(out_sf_coltypes) != 0):
sf_coltypes = sf.column_types()
sf_temp_names = sf.column_names()
out_sf_temp_names = out_sf.column_names()
for i in range(len(sf_coltypes)):
if sf_coltypes[i] != out_sf_coltypes[i]:
print "mismatch for types %s and %s" % (sf_coltypes[i],out_sf_coltypes[i])
sf[sf_temp_names[i]] = sf[sf_temp_names[i]].astype(str)
out_sf[out_sf_temp_names[i]] = out_sf[out_sf_temp_names[i]].astype(str)
out_sf = out_sf.append(sf)
out_sf.__proxy__.delete_on_close()
if sf_names is not None:
out_names = out_sf.column_names()
if(set(out_names) != set(sf_names)):
out_sf = out_sf.rename(dict(zip(out_names, sf_names)))
return out_sf
@classmethod
def __from_UTF8Deserialized_rdd__(cls, rdd):
_mt._get_metric_tracker().track('sframe.__from_UTF8Deserialized_rdd__')
if not RDD_SUPPORT:
raise Exception("Support for translation to Spark RDDs not enabled.")
cur_sc = rdd.ctx
sf_names = None
sf_types = None
tmp_loc = SFrame.__get_staging_dir__(cur_sc)
if tmp_loc is None:
raise RuntimeError("Could not determine staging directory for SFrame files.")
if(rdd.__class__.__name__ in {'SchemaRDD','DataFrame'}):
first_row = rdd.take(1)[0]
if hasattr(first_row, 'keys'):
sf_names = first_row.keys()
sf_types = [type(i) for i in first_row.values()]
else:
sf_names = first_row.__FIELDS__
sf_types = [type(i) for i in first_row]
sf_names = [str(i) for i in sf_names]
for _type in sf_types:
if(_type != int and _type != str and _type != float and _type != unicode):
raise TypeError("Only int, str, and float are supported for now")
types = ""
for i in sf_types:
types += i.__name__ + ","
if cur_sc.master[0:5] == 'local':
t = rdd._jschema_rdd.toJavaStringOfValues().pipe(
BINARY_PATHS['SPARK_PIPE_WRAPPER_PATH'] + " " +\
BINARY_PATHS['RDD_SFRAME_NONPICKLE_PATH'] + " " + tmp_loc +\
" " + types)
else:
t = cur_sc._jvm.org.graphlab.create.GraphLabUtil.toJavaStringOfValues(
rdd._jschema_rdd).pipe(
"./" + SPARK_SUPPORT_NAMES['SPARK_PIPE_WRAPPER_PATH'] +\
" " + "./" +\
SPARK_SUPPORT_NAMES['RDD_SFRAME_NONPICKLE_PATH'] + " " +\
tmp_loc + " " + types)
else:
if cur_sc.master[0:5] == 'local':
t = cur_sc._jvm.org.graphlab.create.GraphLabUtil.pythonToJava(
rdd._jrdd).pipe(
BINARY_PATHS['SPARK_PIPE_WRAPPER_PATH'] + " " +\
BINARY_PATHS['RDD_SFRAME_NONPICKLE_PATH'] + " " +\
tmp_loc)
else:
t = cur_sc._jvm.org.graphlab.create.GraphLabUtil.pythonToJava(
rdd._jrdd).pipe(
"./" + SPARK_SUPPORT_NAMES['SPARK_PIPE_WRAPPER_PATH'] +\
" " + "./" +\
SPARK_SUPPORT_NAMES['RDD_SFRAME_NONPICKLE_PATH'] + " " +\
tmp_loc)
# We get the location of an SFrame index file per Spark partition in
# the result. We assume that this is in partition order.
res = t.collect()
out_sf = cls()
sframe_list = []
for url in res:
sf = SFrame()
sf.__proxy__.load_from_sframe_index(_make_internal_url(url))
sf.__proxy__.delete_on_close()
out_sf = out_sf.append(sf)
out_sf.__proxy__.delete_on_close()
if sf_names is not None:
out_names = out_sf.column_names()
if(set(out_names) != set(sf_names)):
out_sf = out_sf.rename(dict(zip(out_names, sf_names)))
return out_sf
@classmethod
def from_odbc(cls, db, sql, verbose=False):
"""
Convert a table or query from a database to an SFrame.
This function does not do any checking on the given SQL query, and
cannot know what effect it will have on the database. Any side effects
from the query will be reflected on the database. If no result
rows are returned, an empty SFrame is created.
Keep in mind the default case your database stores table names in. In
some cases, you may need to add quotation marks (or whatever character
your database uses to quote identifiers), especially if you created the
table using `to_odbc`.
Parameters
----------
db : `graphlab.extensions._odbc_connection.unity_odbc_connection`
An ODBC connection object. This can only be obtained by calling
`graphlab.connect_odbc`. Check that documentation for how to create
this object.
sql : str
A SQL query. The query must be acceptable by the ODBC driver used by
`graphlab.extensions._odbc_connection.unity_odbc_connection`.
Returns
-------
out : SFrame
Notes
-----
This functionality is only supported when using GraphLab Create
entirely on your local machine. Therefore, GraphLab Create's EC2 and
Hadoop execution modes will not be able to use ODBC. Note that this
does not apply to the machine your database is running, which can (and
often will) be running on a separate machine.
Examples
--------
>>> db = graphlab.connect_odbc("DSN=my_awesome_dsn;UID=user;PWD=mypassword")
>>> a_table = graphlab.SFrame.from_odbc(db, "SELECT * FROM a_table")
>>> join_result = graphlab.SFrame.from_odbc(db, 'SELECT * FROM "MyTable" a, "AnotherTable" b WHERE a.id=b.id')
"""
result = db.execute_query(sql)
if not isinstance(result, SFrame):
raise RuntimeError("Cannot create an SFrame for query. No result set.")
cls = result
return cls
def to_odbc(self, db, table_name, append_if_exists=False, verbose=True):
"""
Convert an SFrame to a table in a database.
By default, searches for a table in the database with the given name.
If found, this will attempt to append all the rows of the SFrame to the
end of the table. If not, this will create a new table with the given
name. This behavior is toggled with the `append_if_exists` flag.
When creating a new table, GraphLab Create uses a heuristic approach to
pick a corresponding type for each column in the SFrame using the type
information supplied by the database's ODBC driver. Your driver must
support giving this type information for GraphLab Create to support
writing to the database.
To allow more expressive and accurate naming, `to_odbc` puts quotes
around each identifier (table names and column names). Depending on
your database, you may need to refer to the created table with quote
characters around the name. This character is not the same for all
databases, but '"' is the most common.
Parameters
----------
db : `graphlab.extensions._odbc_connection.unity_odbc_connection`
An ODBC connection object. This can only be obtained by calling
`graphlab.connect_odbc`. Check that documentation for how to create
this object.
table_name : str
The name of the table you would like to create/append to.
append_if_exists : bool
If True, this will attempt to append to the table named `table_name`
if it is found to exist in the database.
verbose : bool
Print progress updates on the insertion process.
Notes
-----
This functionality is only supported when using GraphLab Create
entirely on your local machine. Therefore, GraphLab Create's EC2 and
Hadoop execution modes will not be able to use ODBC. Note that this
"local machine" rule does not apply to the machine your database is
running on, which can (and often will) be running on a separate
machine.
Examples
--------
>>> db = graphlab.connect_odbc("DSN=my_awesome_dsn;UID=user;PWD=mypassword")
>>> sf = graphlab.SFrame({'a':[1,2,3],'b':['hi','pika','bye']})
>>> sf.to_odbc(db, 'a_cool_table')
"""
if (not verbose):
glconnect.get_client().set_log_progress(False)
db._insert_sframe(self, table_name, append_if_exists)
if (not verbose):
glconnect.get_client().set_log_progress(True)
def __repr__(self):
"""
Returns a string description of the frame
"""
printed_sf = self._imagecols_to_stringcols()
ret = self.__get_column_description__()
if self.__has_size__():
ret = ret + "Rows: " + str(len(self)) + "\n\n"
else:
ret = ret + "Rows: Unknown" + "\n\n"
ret = ret + "Data:\n"
if (len(printed_sf.head()) > 0):
ret = ret + str(self)
else:
ret = ret + "\t[]"
return ret
def __get_column_description__(self):
colnames = self.column_names()
coltypes = self.column_types()
ret = "Columns:\n"
if len(colnames) > 0:
for i in range(len(colnames)):
ret = ret + "\t" + colnames[i] + "\t" + coltypes[i].__name__ + "\n"
ret = ret + "\n"
else:
ret = ret + "\tNone\n\n"
return ret
def __get_pretty_tables__(self, wrap_text=False, max_row_width=80,
max_column_width=30, max_columns=20,
max_rows_to_display=60):
"""
Returns a list of pretty print tables representing the current SFrame.
If the number of columns is larger than max_columns, the last pretty
table will contain an extra column of "...".
Parameters
----------
wrap_text : bool, optional
max_row_width : int, optional
Max number of characters per table.
max_column_width : int, optional
Max number of characters per column.
max_columns : int, optional
Max number of columns per table.
max_rows_to_display : int, optional
Max number of rows to display.
Returns
-------
out : list[PrettyTable]
"""
headsf = self.head(max_rows_to_display)
if headsf.shape == (0, 0):
return [PrettyTable()]
# convert array.array column to list column so they print like [...]
# and not array('d', ...)
for col in headsf.column_names():
if headsf[col].dtype() is array.array:
headsf[col] = headsf[col].astype(list)
def _value_to_str(value):
if (type(value) is array.array):
return str(list(value))
elif (type(value) is list):
return '[' + ", ".join(_value_to_str(x) for x in value) + ']'
else:
return str(value)
def _escape_space(s):
return "".join([ch.encode('string_escape') if ch.isspace() else ch for ch in s])
def _truncate_respect_unicode(s, max_length):
if (len(s) <= max_length):
return s
else:
u = unicode(s, 'utf-8', errors='replace')
return u[:max_length].encode('utf-8')
def _truncate_str(s, wrap_str=False):
"""
Truncate and optionally wrap the input string as unicode, replace
unconvertible character with a diamond ?.
"""
s = _escape_space(s)
if len(s) <= max_column_width:
return unicode(s, 'utf-8', errors='replace')
else:
ret = ''
# if wrap_str is true, wrap the text and take at most 2 rows
if wrap_str:
wrapped_lines = wrap(s, max_column_width)
if len(wrapped_lines) == 1:
return wrapped_lines[0]
last_line = wrapped_lines[1]
if len(last_line) >= max_column_width:
last_line = _truncate_respect_unicode(last_line, max_column_width - 4)
ret = wrapped_lines[0] + '\n' + last_line + ' ...'
else:
ret = _truncate_respect_unicode(s, max_column_width - 4) + '...'
return unicode(ret, 'utf-8', errors='replace')
columns = self.column_names()[:max_columns]
columns.reverse() # reverse the order of columns and we will pop from the end
num_column_of_last_table = 0
row_of_tables = []
# let's build a list of tables with max_columns
# each table should satisfy, max_row_width, and max_column_width
while len(columns) > 0:
tbl = PrettyTable()
table_width = 0
num_column_of_last_table = 0
while len(columns) > 0:
col = columns.pop()
# check the max length of element in the column
if len(headsf) > 0:
col_width = min(max_column_width, max(len(str(x)) for x in headsf[col]))
else:
col_width = max_column_width
if (table_width + col_width < max_row_width):
# truncate the header if necessary
header = _truncate_str(col, wrap_text)
tbl.add_column(header, [_truncate_str(_value_to_str(x), wrap_text) for x in headsf[col]])
table_width = str(tbl).find('\n')
num_column_of_last_table += 1
else:
# the column does not fit in the current table, push it back to columns
columns.append(col)
break
tbl.align = 'c'
row_of_tables.append(tbl)
# add a column of all "..." if there are more columns than displayed
if self.num_cols() > max_columns:
row_of_tables[-1].add_column('...', ['...'] * len(headsf))
num_column_of_last_table += 1
# add a row of all "..." if there are more rows than displayed
if self.__has_size__() and self.num_rows() > headsf.num_rows():
row_of_tables[-1].add_row(['...'] * num_column_of_last_table)
return row_of_tables
def print_rows(self, num_rows=10, num_columns=40, max_column_width=30,
max_row_width=80):
"""
Print the first M rows and N columns of the SFrame in human readable
format.
Parameters
----------
num_rows : int, optional
Number of rows to print.
num_columns : int, optional
Number of columns to print.
max_column_width : int, optional
Maximum width of a column. Columns use fewer characters if possible.
max_row_width : int, optional
Maximum width of a printed row. Columns beyond this width wrap to a
new line. `max_row_width` is automatically reset to be the
larger of itself and `max_column_width`.
See Also
--------
head, tail
"""
max_row_width = max(max_row_width, max_column_width + 1)
printed_sf = self._imagecols_to_stringcols(num_rows)
row_of_tables = printed_sf.__get_pretty_tables__(wrap_text=False,
max_rows_to_display=num_rows,
max_columns=num_columns,
max_column_width=max_column_width,
max_row_width=max_row_width)
footer = "[%d rows x %d columns]\n" % self.shape
print '\n'.join([str(tb) for tb in row_of_tables]) + "\n" + footer
def _imagecols_to_stringcols(self, num_rows=10):
# A list of column types
types = self.column_types()
# A list of indexable column names
names = self.column_names()
# Constructing names of sframe columns that are of image type
image_column_names = [names[i] for i in range(len(names)) if types[i] == graphlab.Image]
#If there are image-type columns, copy the SFrame and cast the top MAX_NUM_ROWS_TO_DISPLAY of those columns to string
if len(image_column_names) > 0:
printed_sf = SFrame()
for t in names:
if t in image_column_names:
printed_sf[t] = self[t]._head_str(num_rows)
else:
printed_sf[t] = self[t].head(num_rows)
else:
printed_sf = self
return printed_sf
def __str__(self, num_rows=10, footer=True):
"""
Returns a string containing the first 10 elements of the frame, along
with a description of the frame.
"""
MAX_ROWS_TO_DISPLAY = num_rows
printed_sf = self._imagecols_to_stringcols(MAX_ROWS_TO_DISPLAY)
row_of_tables = printed_sf.__get_pretty_tables__(wrap_text=False, max_rows_to_display=MAX_ROWS_TO_DISPLAY)
if (not footer):
return '\n'.join([str(tb) for tb in row_of_tables])
if self.__has_size__():
footer = '[%d rows x %d columns]\n' % self.shape
if (self.num_rows() > MAX_ROWS_TO_DISPLAY):
footer += '\n'.join(FOOTER_STRS)
else:
footer = '[? rows x %d columns]\n' % self.num_columns()
footer += '\n'.join(LAZY_FOOTER_STRS)
return '\n'.join([str(tb) for tb in row_of_tables]) + "\n" + footer
def _repr_html_(self):
MAX_ROWS_TO_DISPLAY = 10
printed_sf = self._imagecols_to_stringcols(MAX_ROWS_TO_DISPLAY)
row_of_tables = printed_sf.__get_pretty_tables__(wrap_text=True, max_row_width=120, max_columns=40, max_column_width=25, max_rows_to_display=MAX_ROWS_TO_DISPLAY)
if self.__has_size__():
footer = '[%d rows x %d columns]<br/>' % self.shape
if (self.num_rows() > MAX_ROWS_TO_DISPLAY):
footer += '<br/>'.join(FOOTER_STRS)
else:
footer = '[? rows x %d columns]<br/>' % self.num_columns()
footer += '<br/>'.join(LAZY_FOOTER_STRS)
begin = '<div style="max-height:1000px;max-width:1500px;overflow:auto;">'
end = '\n</div>'
return begin + '\n'.join([tb.get_html_string(format=True) for tb in row_of_tables]) + "\n" + footer + end
def __nonzero__(self):
"""
Returns true if the frame is not empty.
"""
return self.num_rows() != 0
def __len__(self):
"""
Returns the number of rows of the sframe.
"""
return self.num_rows()
def __copy__(self):
"""
Returns a shallow copy of the sframe.
"""
return self.select_columns(self.column_names())
def __eq__(self, other):
raise NotImplementedError
def __ne__(self, other):
raise NotImplementedError
def _row_selector(self, other):
"""
Where other is an SArray of identical length as the current Frame,
this returns a selection of a subset of rows in the current SFrame
where the corresponding row in the selector is non-zero.
"""
if type(other) is SArray:
if len(other) != len(self):
raise IndexError("Cannot perform logical indexing on arrays of different length.")
with cython_context():
return SFrame(_proxy=self.__proxy__.logical_filter(other.__proxy__))
def dtype(self):
"""
The type of each column.
Returns
-------
out : list[type]
Column types of the SFrame.
See Also
--------
column_types
"""
return self.column_types()
def num_rows(self):
"""
The number of rows in this SFrame.
Returns
-------
out : int
Number of rows in the SFrame.
See Also
--------
num_columns
"""
return self.__proxy__.num_rows()
def num_cols(self):
"""
The number of columns in this SFrame.
Returns
-------
out : int
Number of columns in the SFrame.
See Also
--------
num_columns, num_rows
"""
return self.__proxy__.num_columns()
def num_columns(self):
"""
The number of columns in this SFrame.
Returns
-------
out : int
Number of columns in the SFrame.
See Also
--------
num_cols, num_rows
"""
return self.__proxy__.num_columns()
def column_names(self):
"""
The name of each column in the SFrame.
Returns
-------
out : list[string]
Column names of the SFrame.
See Also
--------
rename
"""
return self.__proxy__.column_names()
def column_types(self):
"""
The type of each column in the SFrame.
Returns
-------
out : list[type]
Column types of the SFrame.
See Also
--------
dtype
"""
return self.__proxy__.dtype()
def head(self, n=10):
"""
The first n rows of the SFrame.
Parameters
----------
n : int, optional
The number of rows to fetch.
Returns
-------
out : SFrame
A new SFrame which contains the first n rows of the current SFrame
See Also
--------
tail, print_rows
"""
return SFrame(_proxy=self.__proxy__.head(n))
def to_dataframe(self):
"""
Convert this SFrame to pandas.DataFrame.
This operation will construct a pandas.DataFrame in memory. Care must
be taken when size of the returned object is big.
Returns
-------
out : pandas.DataFrame
The dataframe which contains all rows of SFrame
"""
assert HAS_PANDAS
df = pandas.DataFrame()
for i in range(self.num_columns()):
column_name = self.column_names()[i]
df[column_name] = list(self[column_name])
if len(df[column_name]) == 0:
df[column_name] = df[column_name].astype(self.column_types()[i])
return df
def tail(self, n=10):
"""
The last n rows of the SFrame.
Parameters
----------
n : int, optional
The number of rows to fetch.
Returns
-------
out : SFrame
A new SFrame which contains the last n rows of the current SFrame
See Also
--------
head, print_rows
"""
return SFrame(_proxy=self.__proxy__.tail(n))
def apply(self, fn, dtype=None, seed=None):
"""
Transform each row to an :class:`~graphlab.SArray` according to a
specified function. Returns a new SArray of ``dtype`` where each element
in this SArray is transformed by `fn(x)` where `x` is a single row in
the sframe represented as a dictionary. The ``fn`` should return
exactly one value which can be cast into type ``dtype``. If ``dtype`` is
not specified, the first 100 rows of the SFrame are used to make a guess
of the target data type.
Parameters
----------
fn : function
The function to transform each row of the SFrame. The return
type should be convertible to `dtype` if `dtype` is not None.
This can also be a toolkit extension function which is compiled
as a native shared library using SDK.
dtype : dtype, optional
The dtype of the new SArray. If None, the first 100
elements of the array are used to guess the target
data type.
seed : int, optional
Used as the seed if a random number generator is included in `fn`.
Returns
-------
out : SArray
The SArray transformed by fn. Each element of the SArray is of
type ``dtype``
Examples
--------
Concatenate strings from several columns:
>>> sf = graphlab.SFrame({'user_id': [1, 2, 3], 'movie_id': [3, 3, 6],
'rating': [4, 5, 1]})
>>> sf.apply(lambda x: str(x['user_id']) + str(x['movie_id']) + str(x['rating']))
dtype: str
Rows: 3
['134', '235', '361']
Using native toolkit extension function:
.. code-block:: c++
#include <graphlab/sdk/toolkit_function_macros.hpp>
double mean(const std::map<flexible_type, flexible_type>& dict) {
double sum = 0.0;
for (const auto& kv: dict) sum += (double)kv.second;
return sum / dict.size();
}
BEGIN_FUNCTION_REGISTRATION
REGISTER_FUNCTION(mean, "row");
END_FUNCTION_REGISTRATION
compiled into example.so
>>> import example
>>> sf = graphlab.SFrame({'x0': [1, 2, 3], 'x1': [2, 3, 1],
... 'x2': [3, 1, 2]})
>>> sf.apply(example.mean)
dtype: float
Rows: 3
[2.0,2.0,2.0]
"""
assert _is_callable(fn), "Input must be a function"
test_sf = self[:10]
dryrun = [fn(row) for row in test_sf]
if dtype is None:
dtype = SArray(dryrun).dtype()
if not seed:
seed = int(time.time())
_mt._get_metric_tracker().track('sframe.apply')
nativefn = None
try:
import graphlab.extensions as extensions
nativefn = extensions._build_native_function_call(fn)
except:
pass
if nativefn is not None:
# this is a toolkit lambda. We can do something about it
with cython_context():
return SArray(_proxy=self.__proxy__.transform_native(nativefn, dtype, seed))
with cython_context():
return SArray(_proxy=self.__proxy__.transform(fn, dtype, seed))
def flat_map(self, column_names, fn, column_types='auto', seed=None):
"""
Map each row of the SFrame to multiple rows in a new SFrame via a
function.
The output of `fn` must have type List[List[...]]. Each inner list
will be a single row in the new output, and the collection of these
rows within the outer list make up the data for the output SFrame.
All rows must have the same length and the same order of types to
make sure the result columns are homogeneously typed. For example, if
the first element emitted into in the outer list by `fn` is
[43, 2.3, 'string'], then all other elements emitted into the outer
list must be a list with three elements, where the first is an int,
second is a float, and third is a string. If column_types is not
specified, the first 10 rows of the SFrame are used to determine the
column types of the returned sframe.
Parameters
----------
column_names : list[str]
The column names for the returned SFrame.
fn : function
The function that maps each of the sframe row into multiple rows,
returning List[List[...]]. All outputted rows must have the same
length and order of types.
column_types : list[type], optional
The column types of the output SFrame. Default value will be
automatically inferred by running `fn` on the first 10 rows of the
input. If the types cannot be inferred from the first 10 rows, an
error is raised.
seed : int, optional
Used as the seed if a random number generator is included in `fn`.
Returns
-------
out : SFrame
A new SFrame containing the results of the flat_map of the
original SFrame.
Examples
---------
Repeat each row according to the value in the 'number' column.
>>> sf = graphlab.SFrame({'letter': ['a', 'b', 'c'],
... 'number': [1, 2, 3]})
>>> sf.flat_map(['number', 'letter'],
... lambda x: [list(x.itervalues()) for i in range(0, x['number'])])
+--------+--------+
| number | letter |
+--------+--------+
| 1 | a |
| 2 | b |
| 2 | b |
| 3 | c |
| 3 | c |
| 3 | c |
+--------+--------+
[6 rows x 2 columns]
"""
assert inspect.isfunction(fn), "Input must be a function"
if not seed:
seed = int(time.time())
_mt._get_metric_tracker().track('sframe.flat_map')
# determine the column_types
if column_types == 'auto':
types = set()
sample = self[0:10]
results = [fn(row) for row in sample]
for rows in results:
if type(rows) is not list:
raise TypeError("Output type of the lambda function must be a list of lists")
# note: this skips empty lists
for row in rows:
if type(row) is not list:
raise TypeError("Output type of the lambda function must be a list of lists")
types.add(tuple([type(v) for v in row]))
if len(types) == 0:
raise TypeError, \
"Could not infer output column types from the first ten rows " +\
"of the SFrame. Please use the 'column_types' parameter to " +\
"set the types."
if len(types) > 1:
raise TypeError("Mapped rows must have the same length and types")
column_types = list(types.pop())
assert type(column_types) is list
assert len(column_types) == len(column_names), "Number of output columns must match the size of column names"
with cython_context():
return SFrame(_proxy=self.__proxy__.flat_map(fn, column_names, column_types, seed))
def sample(self, fraction, seed=None):
"""
Sample the current SFrame's rows.
Parameters
----------
fraction : float
Approximate fraction of the rows to fetch. Must be between 0 and 1.
The number of rows returned is approximately the fraction times the
number of rows.
seed : int, optional
Seed for the random number generator used to sample.
Returns
-------
out : SFrame
A new SFrame containing sampled rows of the current SFrame.
Examples
--------
Suppose we have an SFrame with 6,145 rows.
>>> import random
>>> sf = SFrame({'id': range(0, 6145)})
Retrieve about 30% of the SFrame rows with repeatable results by
setting the random seed.
>>> len(sf.sample(.3, seed=5))
1783
"""
if not seed:
seed = int(time.time())
if (fraction > 1 or fraction < 0):
raise ValueError('Invalid sampling rate: ' + str(fraction))
_mt._get_metric_tracker().track('sframe.sample')
if (self.num_rows() == 0 or self.num_cols() == 0):
return self
else:
with cython_context():
return SFrame(_proxy=self.__proxy__.sample(fraction, seed))
def random_split(self, fraction, seed=None):
"""
Randomly split the rows of an SFrame into two SFrames. The first SFrame
contains *M* rows, sampled uniformly (without replacement) from the
original SFrame. *M* is approximately the fraction times the original
number of rows. The second SFrame contains the remaining rows of the
original SFrame.
Parameters
----------
fraction : float
Approximate fraction of the rows to fetch for the first returned
SFrame. Must be between 0 and 1.
seed : int, optional
Seed for the random number generator used to split.
Returns
-------
out : tuple [SFrame]
Two new SFrames.
Examples
--------
Suppose we have an SFrame with 1,024 rows and we want to randomly split
it into training and testing datasets with about a 90%/10% split.
>>> sf = graphlab.SFrame({'id': range(1024)})
>>> sf_train, sf_test = sf.random_split(.9, seed=5)
>>> print len(sf_train), len(sf_test)
922 102
"""
if (fraction > 1 or fraction < 0):
raise ValueError('Invalid sampling rate: ' + str(fraction))
if (self.num_rows() == 0 or self.num_cols() == 0):
return (SFrame(), SFrame())
if not seed:
seed = int(time.time())
# The server side requires this to be an int, so cast if we can
try:
seed = int(seed)
except ValueError:
raise ValueError('The \'seed\' parameter must be of type int.')
_mt._get_metric_tracker().track('sframe.random_split')
with cython_context():
proxy_pair = self.__proxy__.random_split(fraction, seed)
return (SFrame(data=[], _proxy=proxy_pair[0]), SFrame(data=[], _proxy=proxy_pair[1]))
def topk(self, column_name, k=10, reverse=False):
"""
Get top k rows according to the given column. Result is according to and
sorted by `column_name` in the given order (default is descending).
When `k` is small, `topk` is more efficient than `sort`.
Parameters
----------
column_name : string
The column to sort on
k : int, optional
The number of rows to return
reverse : bool, optional
If True, return the top k rows in ascending order, otherwise, in
descending order.
Returns
-------
out : SFrame
an SFrame containing the top k rows sorted by column_name.
See Also
--------
sort
Examples
--------
>>> sf = graphlab.SFrame({'id': range(1000)})
>>> sf['value'] = -sf['id']
>>> sf.topk('id', k=3)
+--------+--------+
| id | value |
+--------+--------+
| 999 | -999 |
| 998 | -998 |
| 997 | -997 |
+--------+--------+
[3 rows x 2 columns]
>>> sf.topk('value', k=3)
+--------+--------+
| id | value |
+--------+--------+
| 1 | -1 |
| 2 | -2 |
| 3 | -3 |
+--------+--------+
[3 rows x 2 columns]
"""
if type(column_name) is not str:
raise TypeError("column_name must be a string")
_mt._get_metric_tracker().track('sframe.topk')
sf = self[self[column_name].topk_index(k, reverse)]
return sf.sort(column_name, ascending=reverse)
def save(self, filename, format=None):
"""
Save the SFrame to a file system for later use.
Parameters
----------
filename : string
The location to save the SFrame. Either a local directory or a
remote URL. If the format is 'binary', a directory will be created
at the location which will contain the sframe.
format : {'binary', 'csv'}, optional
Format in which to save the SFrame. Binary saved SFrames can be
loaded much faster and without any format conversion losses. If not
given, will try to infer the format from filename given. If file
name ends with 'csv' or '.csv.gz', then save as 'csv' format,
otherwise save as 'binary' format.
See Also
--------
load_sframe, SFrame
Examples
--------
>>> # Save the sframe into binary format
>>> sf.save('data/training_data_sframe')
>>> # Save the sframe into csv format
>>> sf.save('data/training_data.csv', format='csv')
"""
_mt._get_metric_tracker().track('sframe.save', properties={'format':format})
if format == None:
if filename.endswith(('.csv', '.csv.gz')):
format = 'csv'
else:
format = 'binary'
else:
if format is 'csv':
if not filename.endswith(('.csv', '.csv.gz')):
filename = filename + '.csv'
elif format is not 'binary':
raise ValueError("Invalid format: {}. Supported formats are 'csv' and 'binary'".format(format))
## Save the SFrame
url = _make_internal_url(filename)
with cython_context():
if format is 'binary':
self.__proxy__.save(url)
elif format is 'csv':
assert filename.endswith(('.csv', '.csv.gz'))
self.__proxy__.save_as_csv(url, {})
else:
raise ValueError("Unsupported format: {}".format(format))
def select_column(self, key):
"""
Get a reference to the :class:`~graphlab.SArray` that corresponds with
the given key. Throws an exception if the key is something other than a
string or if the key is not found.
Parameters
----------
key : str
The column name.
Returns
-------
out : SArray
The SArray that is referred by ``key``.
See Also
--------
select_columns
Examples
--------
>>> sf = graphlab.SFrame({'user_id': [1,2,3],
... 'user_name': ['alice', 'bob', 'charlie']})
>>> # This line is equivalent to `sa = sf['user_name']`
>>> sa = sf.select_column('user_name')
>>> sa
dtype: str
Rows: 3
['alice', 'bob', 'charlie']
"""
if not isinstance(key, str):
raise TypeError("Invalid key type: must be str")
with cython_context():
return SArray(data=[], _proxy=self.__proxy__.select_column(key))
def select_columns(self, keylist):
"""
Get SFrame composed only of the columns referred to in the given list of
keys. Throws an exception if ANY of the keys are not in this SFrame or
if ``keylist`` is anything other than a list of strings.
Parameters
----------
keylist : list[str]
The list of column names.
Returns
-------
out : SFrame
A new SFrame that is made up of the columns referred to in
``keylist`` from the current SFrame.
See Also
--------
select_column
Examples
--------
>>> sf = graphlab.SFrame({'user_id': [1,2,3],
... 'user_name': ['alice', 'bob', 'charlie'],
... 'zipcode': [98101, 98102, 98103]
... })
>>> # This line is equivalent to `sf2 = sf[['user_id', 'zipcode']]`
>>> sf2 = sf.select_columns(['user_id', 'zipcode'])
>>> sf2
+---------+---------+
| user_id | zipcode |
+---------+---------+
| 1 | 98101 |
| 2 | 98102 |
| 3 | 98103 |
+---------+---------+
[3 rows x 2 columns]
"""
if not hasattr(keylist, '__iter__'):
raise TypeError("keylist must be an iterable")
if not all([isinstance(x, str) for x in keylist]):
raise TypeError("Invalid key type: must be str")
key_set = set(keylist)
if (len(key_set)) != len(keylist):
for key in key_set:
if keylist.count(key) > 1:
raise ValueError("There are duplicate keys in key list: '" + key + "'")
with cython_context():
return SFrame(data=[], _proxy=self.__proxy__.select_columns(keylist))
def add_column(self, data, name=""):
"""
Add a column to this SFrame. The number of elements in the data given
must match the length of every other column of the SFrame. This
operation modifies the current SFrame in place and returns self. If no
name is given, a default name is chosen.
Parameters
----------
data : SArray
The 'column' of data to add.
name : string, optional
The name of the column. If no name is given, a default name is
chosen.
Returns
-------
out : SFrame
The current SFrame.
See Also
--------
add_columns
Examples
--------
>>> sf = graphlab.SFrame({'id': [1, 2, 3], 'val': ['A', 'B', 'C']})
>>> sa = graphlab.SArray(['cat', 'dog', 'fossa'])
>>> # This line is equivalant to `sf['species'] = sa`
>>> sf.add_column(sa, name='species')
>>> sf
+----+-----+---------+
| id | val | species |
+----+-----+---------+
| 1 | A | cat |
| 2 | B | dog |
| 3 | C | fossa |
+----+-----+---------+
[3 rows x 3 columns]
"""
# Check type for pandas dataframe or SArray?
if not isinstance(data, SArray):
raise TypeError("Must give column as SArray")
if not isinstance(name, str):
raise TypeError("Invalid column name: must be str")
with cython_context():
self.__proxy__.add_column(data.__proxy__, name)
return self
def add_columns(self, data, namelist=None):
"""
Adds multiple columns to this SFrame. The number of elements in all
columns must match the length of every other column of the SFrame. This
operation modifies the current SFrame in place and returns self.
Parameters
----------
data : list[SArray] or SFrame
The columns to add.
namelist : list of string, optional
A list of column names. All names must be specified. ``namelist`` is
ignored if data is an SFrame.
Returns
-------
out : SFrame
The current SFrame.
See Also
--------
add_column
Examples
--------
>>> sf = graphlab.SFrame({'id': [1, 2, 3], 'val': ['A', 'B', 'C']})
>>> sf2 = graphlab.SFrame({'species': ['cat', 'dog', 'fossa'],
... 'age': [3, 5, 9]})
>>> sf.add_columns(sf2)
>>> sf
+----+-----+-----+---------+
| id | val | age | species |
+----+-----+-----+---------+
| 1 | A | 3 | cat |
| 2 | B | 5 | dog |
| 3 | C | 9 | fossa |
+----+-----+-----+---------+
[3 rows x 4 columns]
"""
datalist = data
if isinstance(data, SFrame):
other = data
datalist = [other.select_column(name) for name in other.column_names()]
namelist = other.column_names()
my_columns = set(self.column_names())
for name in namelist:
if name in my_columns:
raise ValueError("Column '" + name + "' already exists in current SFrame")
else:
if not hasattr(datalist, '__iter__'):
raise TypeError("datalist must be an iterable")
if not hasattr(namelist, '__iter__'):
raise TypeError("namelist must be an iterable")
if not all([isinstance(x, SArray) for x in datalist]):
raise TypeError("Must give column as SArray")
if not all([isinstance(x, str) for x in namelist]):
raise TypeError("Invalid column name in list : must all be str")
with cython_context():
self.__proxy__.add_columns([x.__proxy__ for x in datalist], namelist)
return self
def remove_column(self, name):
"""
Remove a column from this SFrame. This operation modifies the current
SFrame in place and returns self.
Parameters
----------
name : string
The name of the column to remove.
Returns
-------
out : SFrame
The SFrame with given column removed.
Examples
--------
>>> sf = graphlab.SFrame({'id': [1, 2, 3], 'val': ['A', 'B', 'C']})
>>> # This is equivalent to `del sf['val']`
>>> sf.remove_column('val')
>>> sf
+----+
| id |
+----+
| 1 |
| 2 |
| 3 |
+----+
[3 rows x 1 columns]
"""
if name not in self.column_names():
raise KeyError('Cannot find column %s' % name)
colid = self.column_names().index(name)
with cython_context():
self.__proxy__.remove_column(colid)
return self
def remove_columns(self, column_names):
"""
Remove one or more columns from this SFrame. This operation modifies the current
SFrame in place and returns self.
Parameters
----------
column_names : list or iterable
A list or iterable of column names.
Returns
-------
out : SFrame
The SFrame with given columns removed.
Examples
--------
>>> sf = graphlab.SFrame({'id': [1, 2, 3], 'val1': ['A', 'B', 'C'], 'val2' : [10, 11, 12]})
>>> sf.remove_columns(['val1', 'val2'])
>>> sf
+----+
| id |
+----+
| 1 |
| 2 |
| 3 |
+----+
[3 rows x 1 columns]
"""
column_names = list(column_names)
existing_columns = dict((k, i) for i, k in enumerate(self.column_names()))
for name in column_names:
if name not in existing_columns:
raise KeyError('Cannot find column %s' % name)
# Delete it going backwards so we don't invalidate indices
deletion_indices = sorted(existing_columns[name] for name in column_names)
for colid in reversed(deletion_indices):
with cython_context():
self.__proxy__.remove_column(colid)
return self
def swap_columns(self, column_1, column_2):
"""
Swap the columns with the given names. This operation modifies the
current SFrame in place and returns self.
Parameters
----------
column_1 : string
Name of column to swap
column_2 : string
Name of other column to swap
Returns
-------
out : SFrame
The SFrame with swapped columns.
Examples
--------
>>> sf = graphlab.SFrame({'id': [1, 2, 3], 'val': ['A', 'B', 'C']})
>>> sf.swap_columns('id', 'val')
>>> sf
+-----+-----+
| val | id |
+-----+-----+
| A | 1 |
| B | 2 |
| C | 3 |
+----+-----+
[3 rows x 2 columns]
"""
colnames = self.column_names()
colid_1 = colnames.index(column_1)
colid_2 = colnames.index(column_2)
with cython_context():
self.__proxy__.swap_columns(colid_1, colid_2)
return self
def rename(self, names):
"""
Rename the given columns. ``names`` is expected to be a dict specifying
the old and new names. This changes the names of the columns given as
the keys and replaces them with the names given as the values. This
operation modifies the current SFrame in place and returns self.
Parameters
----------
names : dict [string, string]
Dictionary of [old_name, new_name]
Returns
-------
out : SFrame
The current SFrame.
See Also
--------
column_names
Examples
--------
>>> sf = SFrame({'X1': ['Alice','Bob'],
... 'X2': ['123 Fake Street','456 Fake Street']})
>>> sf.rename({'X1': 'name', 'X2':'address'})
>>> sf
+-------+-----------------+
| name | address |
+-------+-----------------+
| Alice | 123 Fake Street |
| Bob | 456 Fake Street |
+-------+-----------------+
[2 rows x 2 columns]
"""
if (type(names) is not dict):
raise TypeError('names must be a dictionary: oldname -> newname')
all_columns = set(self.column_names())
for k in names:
if not k in all_columns:
raise ValueError('Cannot find column %s in the SFrame' % k)
with cython_context():
for k in names:
colid = self.column_names().index(k)
self.__proxy__.set_column_name(colid, names[k])
return self
def __getitem__(self, key):
"""
This method does things based on the type of `key`.
If `key` is:
* str
Calls `select_column` on `key`
* SArray
Performs a logical filter. Expects given SArray to be the same
length as all columns in current SFrame. Every row
corresponding with an entry in the given SArray that is
equivalent to False is filtered from the result.
* int
Returns a single row of the SFrame (the `key`th one) as a dictionary.
* slice
Returns an SFrame including only the sliced rows.
"""
if type(key) is SArray:
return self._row_selector(key)
elif type(key) is list:
return self.select_columns(key)
elif type(key) is str:
return self.select_column(key)
elif type(key) is int:
if key < 0:
key = len(self) + key
if key >= len(self):
raise IndexError("SFrame index out of range")
return list(SFrame(_proxy = self.__proxy__.copy_range(key, 1, key+1)))[0]
elif type(key) is slice:
start = key.start
stop = key.stop
step = key.step
if start is None:
start = 0
if stop is None:
stop = len(self)
if step is None:
step = 1
# handle negative indices
if start < 0:
start = len(self) + start
if stop < 0:
stop = len(self) + stop
return SFrame(_proxy = self.__proxy__.copy_range(start, step, stop))
else:
raise TypeError("Invalid index type: must be SArray, list, or str")
def __setitem__(self, key, value):
"""
A wrapper around add_column(s). Key can be either a list or a str. If
value is an SArray, it is added to the SFrame as a column. If it is a
constant value (int, str, or float), then a column is created where
every entry is equal to the constant value. Existing columns can also
be replaced using this wrapper.
"""
if type(key) is list:
self.add_columns(value, key)
elif type(key) is str:
sa_value = None
if (type(value) is SArray):
sa_value = value
elif hasattr(value, '__iter__'): # wrap list, array... to sarray
sa_value = SArray(value)
else: # create an sarray of constant value
sa_value = SArray.from_const(value, self.num_rows())
# set new column
if not key in self.column_names():
with cython_context():
self.add_column(sa_value, key)
else:
# special case if replacing the only column.
# server would fail the replacement if the new column has different
# length than current one, which doesn't make sense if we are replacing
# the only column. To support this, we first take out the only column
# and then put it back if exception happens
single_column = (self.num_cols() == 1)
if (single_column):
tmpname = key
saved_column = self.select_column(key)
self.remove_column(key)
else:
# add the column to a unique column name.
tmpname = '__' + '-'.join(self.column_names())
try:
self.add_column(sa_value, tmpname)
except Exception as e:
if (single_column):
self.add_column(saved_column, key)
raise
if (not single_column):
# if add succeeded, remove the column name and rename tmpname->columnname.
self.swap_columns(key, tmpname)
self.remove_column(key)
self.rename({tmpname: key})
else:
raise TypeError('Cannot set column with key type ' + str(type(key)))
def __delitem__(self, key):
"""
Wrapper around remove_column.
"""
self.remove_column(key)
def __materialize__(self):
"""
For an SFrame that is lazily evaluated, force the persistence of the
SFrame to disk, committing all lazy evaluated operations.
"""
with cython_context():
self.__proxy__.materialize()
def __is_materialized__(self):
"""
Returns whether or not the SFrame has been materialized.
"""
return self.__proxy__.is_materialized()
def __has_size__(self):
"""
Returns whether or not the size of the SFrame is known.
"""
return self.__proxy__.has_size()
def __iter__(self):
"""
Provides an iterator to the rows of the SFrame.
"""
_mt._get_metric_tracker().track('sframe.__iter__')
def generator():
elems_at_a_time = 262144
self.__proxy__.begin_iterator()
ret = self.__proxy__.iterator_get_next(elems_at_a_time)
column_names = self.column_names()
while(True):
for j in ret:
yield dict(zip(column_names, j))
if len(ret) == elems_at_a_time:
ret = self.__proxy__.iterator_get_next(elems_at_a_time)
else:
break
return generator()
def append(self, other):
"""
Add the rows of an SFrame to the end of this SFrame.
Both SFrames must have the same set of columns with the same column
names and column types.
Parameters
----------
other : SFrame
Another SFrame whose rows are appended to the current SFrame.
Returns
-------
out : SFrame
The result SFrame from the append operation.
Examples
--------
>>> sf = graphlab.SFrame({'id': [4, 6, 8], 'val': ['D', 'F', 'H']})
>>> sf2 = graphlab.SFrame({'id': [1, 2, 3], 'val': ['A', 'B', 'C']})
>>> sf = sf.append(sf2)
>>> sf
+----+-----+
| id | val |
+----+-----+
| 4 | D |
| 6 | F |
| 8 | H |
| 1 | A |
| 2 | B |
| 3 | C |
+----+-----+
[6 rows x 2 columns]
"""
_mt._get_metric_tracker().track('sframe.append')
if type(other) is not SFrame:
raise RuntimeError("SFrame append can only work with SFrame")
left_empty = len(self.column_names()) == 0
right_empty = len(other.column_names()) == 0
if (left_empty and right_empty):
return SFrame()
if (left_empty or right_empty):
non_empty_sframe = self if right_empty else other
return non_empty_sframe
my_column_names = self.column_names()
my_column_types = self.column_types()
other_column_names = other.column_names()
if (len(my_column_names) != len(other_column_names)):
raise RuntimeError("Two SFrames have to have the same number of columns")
# check if the order of column name is the same
column_name_order_match = True
for i in range(len(my_column_names)):
if other_column_names[i] != my_column_names[i]:
column_name_order_match = False
break;
processed_other_frame = other
if not column_name_order_match:
# we allow name order of two sframes to be different, so we create a new sframe from
# "other" sframe to make it has exactly the same shape
processed_other_frame = SFrame()
for i in range(len(my_column_names)):
col_name = my_column_names[i]
if(col_name not in other_column_names):
raise RuntimeError("Column " + my_column_names[i] + " does not exist in second SFrame")
other_column = other.select_column(col_name);
processed_other_frame.add_column(other_column, col_name)
# check column type
if my_column_types[i] != other_column.dtype():
raise RuntimeError("Column " + my_column_names[i] + " type is not the same in two SFrames, one is " + str(my_column_types[i]) + ", the other is " + str(other_column.dtype()))
with cython_context():
processed_other_frame.__materialize__()
return SFrame(_proxy=self.__proxy__.append(processed_other_frame.__proxy__))
def groupby(self, key_columns, operations, *args):
"""
Perform a group on the key_columns followed by aggregations on the
columns listed in operations.
The operations parameter is a dictionary that indicates which
aggregation operators to use and which columns to use them on. The
available operators are SUM, MAX, MIN, COUNT, AVG, VAR, STDV, CONCAT,
SELECT_ONE, ARGMIN, ARGMAX, and QUANTILE. For convenience, aggregators
MEAN, STD, and VARIANCE are available as synonyms for AVG, STDV, and
VAR. See :mod:`~graphlab.aggregate` for more detail on the aggregators.
Parameters
----------
key_columns : string | list[string]
Column(s) to group by. Key columns can be of any type other than
dictionary.
operations : dict, list
Dictionary of columns and aggregation operations. Each key is a
output column name and each value is an aggregator. This can also
be a list of aggregators, in which case column names will be
automatically assigned.
*args
All other remaining arguments will be interpreted in the same
way as the operations argument.
Returns
-------
out_sf : SFrame
A new SFrame, with a column for each groupby column and each
aggregation operation.
See Also
--------
aggregate
Examples
--------
Suppose we have an SFrame with movie ratings by many users.
>>> import graphlab.aggregate as agg
>>> url = 'http://s3.amazonaws.com/gl-testdata/rating_data_example.csv'
>>> sf = graphlab.SFrame.read_csv(url)
>>> sf
+---------+----------+--------+
| user_id | movie_id | rating |
+---------+----------+--------+
| 25904 | 1663 | 3 |
| 25907 | 1663 | 3 |
| 25923 | 1663 | 3 |
| 25924 | 1663 | 3 |
| 25928 | 1663 | 2 |
| 25933 | 1663 | 4 |
| 25934 | 1663 | 4 |
| 25935 | 1663 | 4 |
| 25936 | 1663 | 5 |
| 25937 | 1663 | 2 |
| ... | ... | ... |
+---------+----------+--------+
[10000 rows x 3 columns]
Compute the number of occurrences of each user.
>>> user_count = sf.groupby(key_columns='user_id',
... operations={'count': agg.COUNT()})
>>> user_count
+---------+-------+
| user_id | count |
+---------+-------+
| 62361 | 1 |
| 30727 | 1 |
| 40111 | 1 |
| 50513 | 1 |
| 35140 | 1 |
| 42352 | 1 |
| 29667 | 1 |
| 46242 | 1 |
| 58310 | 1 |
| 64614 | 1 |
| ... | ... |
+---------+-------+
[9852 rows x 2 columns]
Compute the mean and standard deviation of ratings per user.
>>> user_rating_stats = sf.groupby(key_columns='user_id',
... operations={
... 'mean_rating': agg.MEAN('rating'),
... 'std_rating': agg.STD('rating')
... })
>>> user_rating_stats
+---------+-------------+------------+
| user_id | mean_rating | std_rating |
+---------+-------------+------------+
| 62361 | 5.0 | 0.0 |
| 30727 | 4.0 | 0.0 |
| 40111 | 2.0 | 0.0 |
| 50513 | 4.0 | 0.0 |
| 35140 | 4.0 | 0.0 |
| 42352 | 5.0 | 0.0 |
| 29667 | 4.0 | 0.0 |
| 46242 | 5.0 | 0.0 |
| 58310 | 2.0 | 0.0 |
| 64614 | 2.0 | 0.0 |
| ... | ... | ... |
+---------+-------------+------------+
[9852 rows x 3 columns]
Compute the movie with the minimum rating per user.
>>> chosen_movies = sf.groupby(key_columns='user_id',
... operations={
... 'worst_movies': agg.ARGMIN('rating','movie_id')
... })
>>> chosen_movies
+---------+-------------+
| user_id | worst_movies |
+---------+-------------+
| 62361 | 1663 |
| 30727 | 1663 |
| 40111 | 1663 |
| 50513 | 1663 |
| 35140 | 1663 |
| 42352 | 1663 |
| 29667 | 1663 |
| 46242 | 1663 |
| 58310 | 1663 |
| 64614 | 1663 |
| ... | ... |
+---------+-------------+
[9852 rows x 2 columns]
Compute the movie with the max rating per user and also the movie with
the maximum imdb-ranking per user.
>>> sf['imdb-ranking'] = sf['rating'] * 10
>>> chosen_movies = sf.groupby(key_columns='user_id',
... operations={('max_rating_movie','max_imdb_ranking_movie'): agg.ARGMAX(('rating','imdb-ranking'),'movie_id')})
>>> chosen_movies
+---------+------------------+------------------------+
| user_id | max_rating_movie | max_imdb_ranking_movie |
+---------+------------------+------------------------+
| 62361 | 1663 | 16630 |
| 30727 | 1663 | 16630 |
| 40111 | 1663 | 16630 |
| 50513 | 1663 | 16630 |
| 35140 | 1663 | 16630 |
| 42352 | 1663 | 16630 |
| 29667 | 1663 | 16630 |
| 46242 | 1663 | 16630 |
| 58310 | 1663 | 16630 |
| 64614 | 1663 | 16630 |
| ... | ... | ... |
+---------+------------------+------------------------+
[9852 rows x 3 columns]
Compute the movie with the max rating per user.
>>> chosen_movies = sf.groupby(key_columns='user_id',
operations={'best_movies': agg.ARGMAX('rating','movie')})
Compute the movie with the max rating per user and also the movie with the maximum imdb-ranking per user.
>>> chosen_movies = sf.groupby(key_columns='user_id',
operations={('max_rating_movie','max_imdb_ranking_movie'): agg.ARGMAX(('rating','imdb-ranking'),'movie')})
Compute the count, mean, and standard deviation of ratings per (user,
time), automatically assigning output column names.
>>> sf['time'] = sf.apply(lambda x: (x['user_id'] + x['movie_id']) % 11 + 2000)
>>> user_rating_stats = sf.groupby(['user_id', 'time'],
... [agg.COUNT(),
... agg.AVG('rating'),
... agg.STDV('rating')])
>>> user_rating_stats
+------+---------+-------+---------------+----------------+
| time | user_id | Count | Avg of rating | Stdv of rating |
+------+---------+-------+---------------+----------------+
| 2006 | 61285 | 1 | 4.0 | 0.0 |
| 2000 | 36078 | 1 | 4.0 | 0.0 |
| 2003 | 47158 | 1 | 3.0 | 0.0 |
| 2007 | 34446 | 1 | 3.0 | 0.0 |
| 2010 | 47990 | 1 | 3.0 | 0.0 |
| 2003 | 42120 | 1 | 5.0 | 0.0 |
| 2007 | 44940 | 1 | 4.0 | 0.0 |
| 2008 | 58240 | 1 | 4.0 | 0.0 |
| 2002 | 102 | 1 | 1.0 | 0.0 |
| 2009 | 52708 | 1 | 3.0 | 0.0 |
| ... | ... | ... | ... | ... |
+------+---------+-------+---------------+----------------+
[10000 rows x 5 columns]
The groupby function can take a variable length list of aggregation
specifiers so if we want the count and the 0.25 and 0.75 quantiles of
ratings:
>>> user_rating_stats = sf.groupby(['user_id', 'time'], agg.COUNT(),
... {'rating_quantiles': agg.QUANTILE('rating',[0.25, 0.75])})
>>> user_rating_stats
+------+---------+-------+------------------------+
| time | user_id | Count | rating_quantiles |
+------+---------+-------+------------------------+
| 2006 | 61285 | 1 | array('d', [4.0, 4.0]) |
| 2000 | 36078 | 1 | array('d', [4.0, 4.0]) |
| 2003 | 47158 | 1 | array('d', [3.0, 3.0]) |
| 2007 | 34446 | 1 | array('d', [3.0, 3.0]) |
| 2010 | 47990 | 1 | array('d', [3.0, 3.0]) |
| 2003 | 42120 | 1 | array('d', [5.0, 5.0]) |
| 2007 | 44940 | 1 | array('d', [4.0, 4.0]) |
| 2008 | 58240 | 1 | array('d', [4.0, 4.0]) |
| 2002 | 102 | 1 | array('d', [1.0, 1.0]) |
| 2009 | 52708 | 1 | array('d', [3.0, 3.0]) |
| ... | ... | ... | ... |
+------+---------+-------+------------------------+
[10000 rows x 4 columns]
To put all items a user rated into one list value by their star rating:
>>> user_rating_stats = sf.groupby(["user_id", "rating"],
... {"rated_movie_ids":agg.CONCAT("movie_id")})
>>> user_rating_stats
+--------+---------+----------------------+
| rating | user_id | rated_movie_ids |
+--------+---------+----------------------+
| 3 | 31434 | array('d', [1663.0]) |
| 5 | 25944 | array('d', [1663.0]) |
| 4 | 38827 | array('d', [1663.0]) |
| 4 | 51437 | array('d', [1663.0]) |
| 4 | 42549 | array('d', [1663.0]) |
| 4 | 49532 | array('d', [1663.0]) |
| 3 | 26124 | array('d', [1663.0]) |
| 4 | 46336 | array('d', [1663.0]) |
| 4 | 52133 | array('d', [1663.0]) |
| 5 | 62361 | array('d', [1663.0]) |
| ... | ... | ... |
+--------+---------+----------------------+
[9952 rows x 3 columns]
To put all items and rating of a given user together into a dictionary
value:
>>> user_rating_stats = sf.groupby("user_id",
... {"movie_rating":agg.CONCAT("movie_id", "rating")})
>>> user_rating_stats
+---------+--------------+
| user_id | movie_rating |
+---------+--------------+
| 62361 | {1663: 5} |
| 30727 | {1663: 4} |
| 40111 | {1663: 2} |
| 50513 | {1663: 4} |
| 35140 | {1663: 4} |
| 42352 | {1663: 5} |
| 29667 | {1663: 4} |
| 46242 | {1663: 5} |
| 58310 | {1663: 2} |
| 64614 | {1663: 2} |
| ... | ... |
+---------+--------------+
[9852 rows x 2 columns]
"""
# some basic checking first
# make sure key_columns is a list
if isinstance(key_columns, str):
key_columns = [key_columns]
# check that every column is a string, and is a valid column name
my_column_names = self.column_names()
key_columns_array = []
for column in key_columns:
if not isinstance(column, str):
raise TypeError("Column name must be a string")
if column not in my_column_names:
raise KeyError("Column " + column + " does not exist in SFrame")
if self[column].dtype() == dict:
raise TypeError("Cannot group on a dictionary column.")
key_columns_array.append(column)
group_output_columns = []
group_columns = []
group_ops = []
all_ops = [operations] + list(args)
for op_entry in all_ops:
# if it is not a dict, nor a list, it is just a single aggregator
# element (probably COUNT). wrap it in a list so we can reuse the
# list processing code
operation = op_entry
if not(isinstance(operation, list) or isinstance(operation, dict)):
operation = [operation]
if isinstance(operation, dict):
# now sweep the dict and add to group_columns and group_ops
for key in operation:
val = operation[key]
if type(val) is tuple:
(op, column) = val
if (op == '__builtin__avg__' and self[column[0]].dtype() is array.array):
op = '__builtin__vector__avg__'
if (op == '__builtin__sum__' and self[column[0]].dtype() is array.array):
op = '__builtin__vector__sum__'
if (op == '__builtin__argmax__' or op == '__builtin__argmin__') and ((type(column[0]) is tuple) != (type(key) is tuple)):
raise TypeError("Output column(s) and aggregate column(s) for aggregate operation should be either all tuple or all string.")
if (op == '__builtin__argmax__' or op == '__builtin__argmin__') and type(column[0]) is tuple:
for (col,output) in zip(column[0],key):
group_columns = group_columns + [[col,column[1]]]
group_ops = group_ops + [op]
group_output_columns = group_output_columns + [output]
else:
group_columns = group_columns + [column]
group_ops = group_ops + [op]
group_output_columns = group_output_columns + [key]
elif val == graphlab.aggregate.COUNT:
group_output_columns = group_output_columns + [key]
val = graphlab.aggregate.COUNT()
(op, column) = val
group_columns = group_columns + [column]
group_ops = group_ops + [op]
else:
raise TypeError("Unexpected type in aggregator definition of output column: " + key)
elif isinstance(operation, list):
# we will be using automatically defined column names
for val in operation:
if type(val) is tuple:
(op, column) = val
if (op == '__builtin__avg__' and self[column[0]].dtype() is array.array):
op = '__builtin__vector__avg__'
if (op == '__builtin__sum__' and self[column[0]].dtype() is array.array):
op = '__builtin__vector__sum__'
if (op == '__builtin__argmax__' or op == '__builtin__argmin__') and type(column[0]) is tuple:
for col in column[0]:
group_columns = group_columns + [[col,column[1]]]
group_ops = group_ops + [op]
group_output_columns = group_output_columns + [""]
else:
group_columns = group_columns + [column]
group_ops = group_ops + [op]
group_output_columns = group_output_columns + [""]
elif val == graphlab.aggregate.COUNT:
group_output_columns = group_output_columns + [""]
val = graphlab.aggregate.COUNT()
(op, column) = val
group_columns = group_columns + [column]
group_ops = group_ops + [op]
else:
raise TypeError("Unexpected type in aggregator definition.")
# let's validate group_columns and group_ops are valid
for (cols, op) in zip(group_columns, group_ops):
for col in cols:
if not isinstance(col, str):
raise TypeError("Column name must be a string")
if not isinstance(op, str):
raise TypeError("Operation type not recognized.")
if op is not graphlab.aggregate.COUNT()[0]:
for col in cols:
if col not in my_column_names:
raise KeyError("Column " + col + " does not exist in SFrame")
_mt._get_metric_tracker().track('sframe.groupby', properties={'operator':op})
with cython_context():
return SFrame(_proxy=self.__proxy__.groupby_aggregate(key_columns_array, group_columns,
group_output_columns, group_ops))
def join(self, right, on=None, how='inner'):
"""
Merge two SFrames. Merges the current (left) SFrame with the given
(right) SFrame using a SQL-style equi-join operation by columns.
Parameters
----------
right : SFrame
The SFrame to join.
on : None | str | list | dict, optional
The column name(s) representing the set of join keys. Each row that
has the same value in this set of columns will be merged together.
* If 'None' is given, join will use all columns that have the same
name as the set of join keys.
* If a str is given, this is interpreted as a join using one column,
where both SFrames have the same column name.
* If a list is given, this is interpreted as a join using one or
more column names, where each column name given exists in both
SFrames.
* If a dict is given, each dict key is taken as a column name in the
left SFrame, and each dict value is taken as the column name in
right SFrame that will be joined together. e.g.
{'left_col_name':'right_col_name'}.
how : {'left', 'right', 'outer', 'inner'}, optional
The type of join to perform. 'inner' is default.
* inner: Equivalent to a SQL inner join. Result consists of the
rows from the two frames whose join key values match exactly,
merged together into one SFrame.
* left: Equivalent to a SQL left outer join. Result is the union
between the result of an inner join and the rest of the rows from
the left SFrame, merged with missing values.
* right: Equivalent to a SQL right outer join. Result is the union
between the result of an inner join and the rest of the rows from
the right SFrame, merged with missing values.
* outer: Equivalent to a SQL full outer join. Result is
the union between the result of a left outer join and a right
outer join.
Returns
-------
out : SFrame
Examples
--------
>>> animals = graphlab.SFrame({'id': [1, 2, 3, 4],
... 'name': ['dog', 'cat', 'sheep', 'cow']})
>>> sounds = graphlab.SFrame({'id': [1, 3, 4, 5],
... 'sound': ['woof', 'baa', 'moo', 'oink']})
>>> animals.join(sounds, how='inner')
+----+-------+-------+
| id | name | sound |
+----+-------+-------+
| 1 | dog | woof |
| 3 | sheep | baa |
| 4 | cow | moo |
+----+-------+-------+
[3 rows x 3 columns]
>>> animals.join(sounds, on='id', how='left')
+----+-------+-------+
| id | name | sound |
+----+-------+-------+
| 1 | dog | woof |
| 3 | sheep | baa |
| 4 | cow | moo |
| 2 | cat | None |
+----+-------+-------+
[4 rows x 3 columns]
>>> animals.join(sounds, on=['id'], how='right')
+----+-------+-------+
| id | name | sound |
+----+-------+-------+
| 1 | dog | woof |
| 3 | sheep | baa |
| 4 | cow | moo |
| 5 | None | oink |
+----+-------+-------+
[4 rows x 3 columns]
>>> animals.join(sounds, on={'id':'id'}, how='outer')
+----+-------+-------+
| id | name | sound |
+----+-------+-------+
| 1 | dog | woof |
| 3 | sheep | baa |
| 4 | cow | moo |
| 5 | None | oink |
| 2 | cat | None |
+----+-------+-------+
[5 rows x 3 columns]
"""
_mt._get_metric_tracker().track('sframe.join', properties={'type':how})
available_join_types = ['left','right','outer','inner']
if not isinstance(right, SFrame):
raise TypeError("Can only join two SFrames")
if how not in available_join_types:
raise ValueError("Invalid join type")
join_keys = dict()
if on is None:
left_names = self.column_names()
right_names = right.column_names()
common_columns = [name for name in left_names if name in right_names]
for name in common_columns:
join_keys[name] = name
elif type(on) is str:
join_keys[on] = on
elif type(on) is list:
for name in on:
if type(name) is not str:
raise TypeError("Join keys must each be a str.")
join_keys[name] = name
elif type(on) is dict:
join_keys = on
else:
raise TypeError("Must pass a str, list, or dict of join keys")
with cython_context():
return SFrame(_proxy=self.__proxy__.join(right.__proxy__, how, join_keys))
def filter_by(self, values, column_name, exclude=False):
"""
Filter an SFrame by values inside an iterable object. Result is an
SFrame that only includes (or excludes) the rows that have a column
with the given ``column_name`` which holds one of the values in the
given ``values`` :class:`~graphlab.SArray`. If ``values`` is not an
SArray, we attempt to convert it to one before filtering.
Parameters
----------
values : SArray | list | numpy.ndarray | pandas.Series | str
The values to use to filter the SFrame. The resulting SFrame will
only include rows that have one of these values in the given
column.
column_name : str
The column of the SFrame to match with the given `values`.
exclude : bool
If True, the result SFrame will contain all rows EXCEPT those that
have one of ``values`` in ``column_name``.
Returns
-------
out : SFrame
The filtered SFrame.
Examples
--------
>>> sf = graphlab.SFrame({'id': [1, 2, 3, 4],
... 'animal_type': ['dog', 'cat', 'cow', 'horse'],
... 'name': ['bob', 'jim', 'jimbob', 'bobjim']})
>>> household_pets = ['cat', 'hamster', 'dog', 'fish', 'bird', 'snake']
>>> sf.filter_by(household_pets, 'animal_type')
+-------------+----+------+
| animal_type | id | name |
+-------------+----+------+
| dog | 1 | bob |
| cat | 2 | jim |
+-------------+----+------+
[2 rows x 3 columns]
>>> sf.filter_by(household_pets, 'animal_type', exclude=True)
+-------------+----+--------+
| animal_type | id | name |
+-------------+----+--------+
| horse | 4 | bobjim |
| cow | 3 | jimbob |
+-------------+----+--------+
[2 rows x 3 columns]
"""
_mt._get_metric_tracker().track('sframe.filter_by')
if type(column_name) is not str:
raise TypeError("Must pass a str as column_name")
if type(values) is not SArray:
# If we were given a single element, try to put in list and convert
# to SArray
if not hasattr(values, '__iter__'):
values = [values]
values = SArray(values)
value_sf = SFrame()
value_sf.add_column(values, column_name)
# Make sure the values list has unique values, or else join will not
# filter.
value_sf = value_sf.groupby(column_name, {})
existing_columns = self.column_names()
if column_name not in existing_columns:
raise KeyError("Column '" + column_name + "' not in SFrame.")
existing_type = self.column_types()[self.column_names().index(column_name)]
given_type = value_sf.column_types()[0]
if given_type != existing_type:
raise TypeError("Type of given values does not match type of column '" +
column_name + "' in SFrame.")
with cython_context():
if exclude:
id_name = "id"
# Make sure this name is unique so we know what to remove in
# the result
while id_name in existing_columns:
id_name += "1"
value_sf = value_sf.add_row_number(id_name)
tmp = SFrame(_proxy=self.__proxy__.join(value_sf.__proxy__,
'left',
{column_name:column_name}))
ret_sf = tmp[tmp[id_name] == None]
del ret_sf[id_name]
return ret_sf
else:
return SFrame(_proxy=self.__proxy__.join(value_sf.__proxy__,
'inner',
{column_name:column_name}))
@_check_canvas_enabled
def show(self, columns=None, view=None, x=None, y=None):
"""
show(columns=None, view=None, x=None, y=None)
Visualize the SFrame with GraphLab Create :mod:`~graphlab.canvas`. This function
starts Canvas if it is not already running. If the SFrame has already been plotted,
this function will update the plot.
Parameters
----------
columns : list of str, optional
The columns of this SFrame to show in the SFrame view. In an
interactive browser target of Canvas, the columns will be selectable
and reorderable through the UI as well. If not specified, the
SFrame view will use all columns of the SFrame.
view : str, optional
The name of the SFrame view to show. Can be one of:
- None: Use the default (depends on which Canvas target is set).
- 'Table': Show a scrollable, tabular view of the data in the
SFrame.
- 'Summary': Show a list of columns with some summary statistics
and plots for each column.
- 'Scatter Plot': Show a scatter plot of two numeric columns.
- 'Heat Map': Show a heat map of two numeric columns.
- 'Bar Chart': Show a bar chart of one numeric and one categorical
column.
- 'Line Chart': Show a line chart of one numeric and one
categorical column.
x : str, optional
The column to use for the X axis in a Scatter Plot, Heat Map, Bar
Chart, or Line Chart view. Must be the name of one of the columns
in this SFrame. For Scatter Plot and Heat Map, the column must be
numeric (int or float). If not set, defaults to the first available
valid column.
y : str, optional
The column to use for the Y axis in a Scatter Plot, Heat Map, Bar
Chart, or Line Chart view. Must be the name of one of the numeric
columns in this SFrame. If not set, defaults to the second
available numeric column.
Returns
-------
view : graphlab.canvas.view.View
An object representing the GraphLab Canvas view.
See Also
--------
canvas
Examples
--------
Suppose 'sf' is an SFrame, we can view it in GraphLab Canvas using:
>>> sf.show()
To choose a column filter (applied to all SFrame views):
>>> sf.show(columns=["Foo", "Bar"]) # use only columns 'Foo' and 'Bar'
>>> sf.show(columns=sf.column_names()[3:7]) # use columns 3-7
To choose a specific view of the SFrame:
>>> sf.show(view="Summary")
>>> sf.show(view="Table")
>>> sf.show(view="Bar Chart", x="col1", y="col2")
>>> sf.show(view="Line Chart", x="col1", y="col2")
>>> sf.show(view="Scatter Plot", x="col1", y="col2")
>>> sf.show(view="Heat Map", x="col1", y="col2")
"""
import graphlab.canvas
import graphlab.canvas.inspect
import graphlab.canvas.views.sframe
graphlab.canvas.inspect.find_vars(self)
return graphlab.canvas.show(graphlab.canvas.views.sframe.SFrameView(self, params={
'view': view,
'columns': columns,
'x': x,
'y': y
}))
def pack_columns(self, columns=None, column_prefix=None, dtype=list,
fill_na=None, remove_prefix=True, new_column_name=None):
"""
Pack two or more columns of the current SFrame into one single
column.The result is a new SFrame with the unaffected columns from the
original SFrame plus the newly created column.
The list of columns that are packed is chosen through either the
``columns`` or ``column_prefix`` parameter. Only one of the parameters
is allowed to be provided. ``columns`` explicitly specifies the list of
columns to pack, while ``column_prefix`` specifies that all columns that
have the given prefix are to be packed.
The type of the resulting column is decided by the ``dtype`` parameter.
Allowed values for ``dtype`` are dict, array.array and list:
- *dict*: pack to a dictionary SArray where column name becomes
dictionary key and column value becomes dictionary value
- *array.array*: pack all values from the packing columns into an array
- *list*: pack all values from the packing columns into a list.
Parameters
----------
columns : list[str], optional
A list of column names to be packed. There needs to have at least
two columns to pack. If omitted and `column_prefix` is not
specified, all columns from current SFrame are packed. This
parameter is mutually exclusive with the `column_prefix` parameter.
column_prefix : str, optional
Pack all columns with the given `column_prefix`.
This parameter is mutually exclusive with the `columns` parameter.
dtype : dict | array.array | list, optional
The resulting packed column type. If not provided, dtype is list.
fill_na : value, optional
Value to fill into packed column if missing value is encountered.
If packing to dictionary, `fill_na` is only applicable to dictionary
values; missing keys are not replaced.
remove_prefix : bool, optional
If True and `column_prefix` is specified, the dictionary key will
be constructed by removing the prefix from the column name.
This option is only applicable when packing to dict type.
new_column_name : str, optional
Packed column name. If not given and `column_prefix` is given,
then the prefix will be used as the new column name, otherwise name
is generated automatically.
Returns
-------
out : SFrame
An SFrame that contains columns that are not packed, plus the newly
packed column.
See Also
--------
unpack
Notes
-----
- There must be at least two columns to pack.
- If packing to dictionary, missing key is always dropped. Missing
values are dropped if fill_na is not provided, otherwise, missing
value is replaced by 'fill_na'. If packing to list or array, missing
values will be kept. If 'fill_na' is provided, the missing value is
replaced with 'fill_na' value.
Examples
--------
Suppose 'sf' is an an SFrame that maintains business category
information:
>>> sf = graphlab.SFrame({'business': range(1, 5),
... 'category.retail': [1, None, 1, None],
... 'category.food': [1, 1, None, None],
... 'category.service': [None, 1, 1, None],
... 'category.shop': [1, 1, None, 1]})
>>> sf
+----------+-----------------+---------------+------------------+---------------+
| business | category.retail | category.food | category.service | category.shop |
+----------+-----------------+---------------+------------------+---------------+
| 1 | 1 | 1 | None | 1 |
| 2 | None | 1 | 1 | 1 |
| 3 | 1 | None | 1 | None |
| 4 | None | 1 | None | 1 |
+----------+-----------------+---------------+------------------+---------------+
[4 rows x 5 columns]
To pack all category columns into a list:
>>> sf.pack_columns(column_prefix='category')
+----------+--------------------+
| business | X2 |
+----------+--------------------+
| 1 | [1, 1, None, 1] |
| 2 | [None, 1, 1, 1] |
| 3 | [1, None, 1, None] |
| 4 | [None, 1, None, 1] |
+----------+--------------------+
[4 rows x 2 columns]
To pack all category columns into a dictionary, with new column name:
>>> sf.pack_columns(column_prefix='category', dtype=dict,
... new_column_name='category')
+----------+--------------------------------+
| business | category |
+----------+--------------------------------+
| 1 | {'food': 1, 'shop': 1, 're ... |
| 2 | {'food': 1, 'shop': 1, 'se ... |
| 3 | {'retail': 1, 'service': 1} |
| 4 | {'food': 1, 'shop': 1} |
+----------+--------------------------------+
[4 rows x 2 columns]
To keep column prefix in the resulting dict key:
>>> sf.pack_columns(column_prefix='category', dtype=dict,
remove_prefix=False)
+----------+--------------------------------+
| business | X2 |
+----------+--------------------------------+
| 1 | {'category.retail': 1, 'ca ... |
| 2 | {'category.food': 1, 'cate ... |
| 3 | {'category.retail': 1, 'ca ... |
| 4 | {'category.food': 1, 'cate ... |
+----------+--------------------------------+
[4 rows x 2 columns]
To explicitly pack a set of columns:
>>> sf.pack_columns(columns = ['business', 'category.retail',
'category.food', 'category.service',
'category.shop'])
+-----------------------+
| X1 |
+-----------------------+
| [1, 1, 1, None, 1] |
| [2, None, 1, 1, 1] |
| [3, 1, None, 1, None] |
| [4, None, 1, None, 1] |
+-----------------------+
[4 rows x 1 columns]
To pack all columns with name starting with 'category' into an array
type, and with missing value replaced with 0:
>>> sf.pack_columns(column_prefix="category", dtype=array.array,
... fill_na=0)
+----------+--------------------------------+
| business | X2 |
+----------+--------------------------------+
| 1 | array('d', [1.0, 1.0, 0.0, ... |
| 2 | array('d', [0.0, 1.0, 1.0, ... |
| 3 | array('d', [1.0, 0.0, 1.0, ... |
| 4 | array('d', [0.0, 1.0, 0.0, ... |
+----------+--------------------------------+
[4 rows x 2 columns]
"""
if columns != None and column_prefix != None:
raise ValueError("'columns' and 'column_prefix' parameter cannot be given at the same time.")
if new_column_name == None and column_prefix != None:
new_column_name = column_prefix
if column_prefix != None:
if type(column_prefix) != str:
raise TypeError("'column_prefix' must be a string")
columns = [name for name in self.column_names() if name.startswith(column_prefix)]
if len(columns) == 0:
raise ValueError("There is no column starts with prefix '" + column_prefix + "'")
elif columns == None:
columns = self.column_names()
else:
if not hasattr(columns, '__iter__'):
raise TypeError("columns must be an iterable type")
column_names = set(self.column_names())
for column in columns:
if (column not in column_names):
raise ValueError("Current SFrame has no column called '" + str(column) + "'.")
# check duplicate names
if len(set(columns)) != len(columns):
raise ValueError("There is duplicate column names in columns parameter")
if (len(columns) <= 1):
raise ValueError("Please provide at least two columns to pack")
if (dtype not in (dict, list, array.array)):
raise ValueError("Resulting dtype has to be one of dict/array.array/list type")
# fill_na value for array needs to be numeric
if dtype == array.array:
if (fill_na != None) and (type(fill_na) not in (int, float)):
raise ValueError("fill_na value for array needs to be numeric type")
# all columns have to be numeric type
for column in columns:
if self[column].dtype() not in (int, float):
raise TypeError("Column '" + column + "' type is not numeric, cannot pack into array type")
# generate dict key names if pack to dictionary
# we try to be smart here
# if all column names are like: a.b, a.c, a.d,...
# we then use "b", "c", "d", etc as the dictionary key during packing
if (dtype == dict) and (column_prefix != None) and (remove_prefix == True):
size_prefix = len(column_prefix)
first_char = set([c[size_prefix:size_prefix+1] for c in columns])
if ((len(first_char) == 1) and first_char.pop() in ['.','-','_']):
dict_keys = [name[size_prefix+1:] for name in columns]
else:
dict_keys = [name[size_prefix:] for name in columns]
else:
dict_keys = columns
rest_columns = [name for name in self.column_names() if name not in columns]
if new_column_name != None:
if type(new_column_name) != str:
raise TypeError("'new_column_name' has to be a string")
if new_column_name in rest_columns:
raise KeyError("Current SFrame already contains a column name " + new_column_name)
else:
new_column_name = ""
_mt._get_metric_tracker().track('sframe.pack_columns')
ret_sa = None
with cython_context():
ret_sa = SArray(_proxy=self.__proxy__.pack_columns(columns, dict_keys, dtype, fill_na))
new_sf = self.select_columns(rest_columns)
new_sf.add_column(ret_sa, new_column_name)
return new_sf
def split_datetime(self, expand_column, column_name_prefix=None, limit=None, tzone=False):
"""
Splits a datetime column of SFrame to multiple columns, with each value in a
separate column. Returns a new SFrame with the expanded column replaced with
a list of new columns. The expanded column must be of datetime type.
For more details regarding name generation and
other, refer to :py:func:`graphlab.SArray.split_datetim()`
Parameters
----------
expand_column : str
Name of the unpacked column.
column_name_prefix : str, optional
If provided, expanded column names would start with the given prefix.
If not provided, the default value is the name of the expanded column.
limit : list[str], optional
Limits the set of datetime elements to expand.
Elements are 'year','month','day','hour','minute',
and 'second'.
tzone : bool, optional
A boolean parameter that determines whether to show the timezone
column or not. Defaults to False.
Returns
-------
out : SFrame
A new SFrame that contains rest of columns from original SFrame with
the given column replaced with a collection of expanded columns.
Examples
---------
>>> sf
Columns:
id int
submission datetime
Rows: 2
Data:
+----+-------------------------------------------------+
| id | submission |
+----+-------------------------------------------------+
| 1 | datetime(2011, 1, 21, 7, 17, 21, tzinfo=GMT(+1))|
| 2 | datetime(2011, 1, 21, 5, 43, 21, tzinfo=GMT(+1))|
+----+-------------------------------------------------+
>>> sf.split_datetime('submission',limit=['hour','minute'])
Columns:
id int
submission.hour int
submission.minute int
Rows: 2
Data:
+----+-----------------+-------------------+
| id | submission.hour | submission.minute |
+----+-----------------+-------------------+
| 1 | 7 | 17 |
| 2 | 5 | 43 |
+----+-----------------+-------------------+
"""
if expand_column not in self.column_names():
raise KeyError("column '" + expand_column + "' does not exist in current SFrame")
if column_name_prefix == None:
column_name_prefix = expand_column
new_sf = self[expand_column].split_datetime(column_name_prefix, limit, tzone)
# construct return SFrame, check if there is conflict
rest_columns = [name for name in self.column_names() if name != expand_column]
new_names = new_sf.column_names()
while set(new_names).intersection(rest_columns):
new_names = [name + ".1" for name in new_names]
new_sf.rename(dict(zip(new_sf.column_names(), new_names)))
_mt._get_metric_tracker().track('sframe.split_datetime')
ret_sf = self.select_columns(rest_columns)
ret_sf.add_columns(new_sf)
return ret_sf
def unpack(self, unpack_column, column_name_prefix=None, column_types=None,
na_value=None, limit=None):
"""
Expand one column of this SFrame to multiple columns with each value in
a separate column. Returns a new SFrame with the unpacked column
replaced with a list of new columns. The column must be of
list/array/dict type.
For more details regarding name generation, missing value handling and
other, refer to the SArray version of
:py:func:`~graphlab.SArray.unpack()`.
Parameters
----------
unpack_column : str
Name of the unpacked column
column_name_prefix : str, optional
If provided, unpacked column names would start with the given
prefix. If not provided, default value is the name of the unpacked
column.
column_types : [type], optional
Column types for the unpacked columns.
If not provided, column types are automatically inferred from first
100 rows. For array type, default column types are float. If
provided, column_types also restricts how many columns to unpack.
na_value : flexible_type, optional
If provided, convert all values that are equal to "na_value" to
missing value (None).
limit : list[str] | list[int], optional
Control unpacking only a subset of list/array/dict value. For
dictionary SArray, `limit` is a list of dictionary keys to restrict.
For list/array SArray, `limit` is a list of integers that are
indexes into the list/array value.
Returns
-------
out : SFrame
A new SFrame that contains rest of columns from original SFrame with
the given column replaced with a collection of unpacked columns.
See Also
--------
pack_columns, SArray.unpack
Examples
---------
>>> sf = graphlab.SFrame({'id': [1,2,3],
... 'wc': [{'a': 1}, {'b': 2}, {'a': 1, 'b': 2}]})
+----+------------------+
| id | wc |
+----+------------------+
| 1 | {'a': 1} |
| 2 | {'b': 2} |
| 3 | {'a': 1, 'b': 2} |
+----+------------------+
[3 rows x 2 columns]
>>> sf.unpack('wc')
+----+------+------+
| id | wc.a | wc.b |
+----+------+------+
| 1 | 1 | None |
| 2 | None | 2 |
| 3 | 1 | 2 |
+----+------+------+
[3 rows x 3 columns]
To not have prefix in the generated column name:
>>> sf.unpack('wc', column_name_prefix="")
+----+------+------+
| id | a | b |
+----+------+------+
| 1 | 1 | None |
| 2 | None | 2 |
| 3 | 1 | 2 |
+----+------+------+
[3 rows x 3 columns]
To limit subset of keys to unpack:
>>> sf.unpack('wc', limit=['b'])
+----+------+
| id | wc.b |
+----+------+
| 1 | None |
| 2 | 2 |
| 3 | 2 |
+----+------+
[3 rows x 3 columns]
To unpack an array column:
>>> sf = graphlab.SFrame({'id': [1,2,3],
... 'friends': [array.array('d', [1.0, 2.0, 3.0]),
... array.array('d', [2.0, 3.0, 4.0]),
... array.array('d', [3.0, 4.0, 5.0])]})
>>> sf
+----+-----------------------------+
| id | friends |
+----+-----------------------------+
| 1 | array('d', [1.0, 2.0, 3.0]) |
| 2 | array('d', [2.0, 3.0, 4.0]) |
| 3 | array('d', [3.0, 4.0, 5.0]) |
+----+-----------------------------+
[3 rows x 2 columns]
>>> sf.unpack('friends')
+----+-----------+-----------+-----------+
| id | friends.0 | friends.1 | friends.2 |
+----+-----------+-----------+-----------+
| 1 | 1.0 | 2.0 | 3.0 |
| 2 | 2.0 | 3.0 | 4.0 |
| 3 | 3.0 | 4.0 | 5.0 |
+----+-----------+-----------+-----------+
[3 rows x 4 columns]
"""
if unpack_column not in self.column_names():
raise KeyError("column '" + unpack_column + "' does not exist in current SFrame")
if column_name_prefix == None:
column_name_prefix = unpack_column
new_sf = self[unpack_column].unpack(column_name_prefix, column_types, na_value, limit)
# construct return SFrame, check if there is conflict
rest_columns = [name for name in self.column_names() if name != unpack_column]
new_names = new_sf.column_names()
while set(new_names).intersection(rest_columns):
new_names = [name + ".1" for name in new_names]
new_sf.rename(dict(zip(new_sf.column_names(), new_names)))
_mt._get_metric_tracker().track('sframe.unpack')
ret_sf = self.select_columns(rest_columns)
ret_sf.add_columns(new_sf)
return ret_sf
def stack(self, column_name, new_column_name=None, drop_na=False):
"""
Convert a "wide" column of an SFrame to one or two "tall" columns by
stacking all values.
The stack works only for columns of dict, list, or array type. If the
column is dict type, two new columns are created as a result of
stacking: one column holds the key and another column holds the value.
The rest of the columns are repeated for each key/value pair.
If the column is array or list type, one new column is created as a
result of stacking. With each row holds one element of the array or list
value, and the rest columns from the same original row repeated.
The new SFrame includes the newly created column and all columns other
than the one that is stacked.
Parameters
--------------
column_name : str
The column to stack. This column must be of dict/list/array type
new_column_name : str | list of str, optional
The new column name(s). If original column is list/array type,
new_column_name must a string. If original column is dict type,
new_column_name must be a list of two strings. If not given, column
names are generated automatically.
drop_na : boolean, optional
If True, missing values and empty list/array/dict are all dropped
from the resulting column(s). If False, missing values are
maintained in stacked column(s).
Returns
-------
out : SFrame
A new SFrame that contains newly stacked column(s) plus columns in
original SFrame other than the stacked column.
See Also
--------
unstack
Examples
---------
Suppose 'sf' is an SFrame that contains a column of dict type:
>>> sf = graphlab.SFrame({'topic':[1,2,3,4],
... 'words': [{'a':3, 'cat':2},
... {'a':1, 'the':2},
... {'the':1, 'dog':3},
... {}]
... })
+-------+----------------------+
| topic | words |
+-------+----------------------+
| 1 | {'a': 3, 'cat': 2} |
| 2 | {'a': 1, 'the': 2} |
| 3 | {'the': 1, 'dog': 3} |
| 4 | {} |
+-------+----------------------+
[4 rows x 2 columns]
Stack would stack all keys in one column and all values in another
column:
>>> sf.stack('words', new_column_name=['word', 'count'])
+-------+------+-------+
| topic | word | count |
+-------+------+-------+
| 1 | a | 3 |
| 1 | cat | 2 |
| 2 | a | 1 |
| 2 | the | 2 |
| 3 | the | 1 |
| 3 | dog | 3 |
| 4 | None | None |
+-------+------+-------+
[7 rows x 3 columns]
Observe that since topic 4 had no words, an empty row is inserted.
To drop that row, set dropna=True in the parameters to stack.
Suppose 'sf' is an SFrame that contains a user and his/her friends,
where 'friends' columns is an array type. Stack on 'friends' column
would create a user/friend list for each user/friend pair:
>>> sf = graphlab.SFrame({'topic':[1,2,3],
... 'friends':[[2,3,4], [5,6],
... [4,5,10,None]]
... })
>>> sf
+-------+------------------+
| topic | friends |
+-------+------------------+
| 1 | [2, 3, 4] |
| 2 | [5, 6] |
| 3 | [4, 5, 10, None] |
+----- -+------------------+
[3 rows x 2 columns]
>>> sf.stack('friends', new_column_name='friend')
+------+--------+
| user | friend |
+------+--------+
| 1 | 2 |
| 1 | 3 |
| 1 | 4 |
| 2 | 5 |
| 2 | 6 |
| 3 | 4 |
| 3 | 5 |
| 3 | 10 |
| 3 | None |
+------+--------+
[9 rows x 2 columns]
"""
# validate column_name
column_name = str(column_name)
if column_name not in self.column_names():
raise ValueError("Cannot find column '" + str(column_name) + "' in the SFrame.")
stack_column_type = self[column_name].dtype()
if (stack_column_type not in [dict, array.array, list]):
raise TypeError("Stack is only supported for column of dict/list/array type.")
if (new_column_name != None):
if stack_column_type == dict:
if (type(new_column_name) is not list):
raise TypeError("new_column_name has to be a list to stack dict type")
elif (len(new_column_name) != 2):
raise TypeError("new_column_name must have length of two")
else:
if (type(new_column_name) != str):
raise TypeError("new_column_name has to be a str")
new_column_name = [new_column_name]
# check if the new column name conflicts with existing ones
for name in new_column_name:
if (name in self.column_names()) and (name != column_name):
raise ValueError("Column with name '" + name + "' already exists, pick a new column name")
else:
if stack_column_type == dict:
new_column_name = ["",""]
else:
new_column_name = [""]
# infer column types
head_row = SArray(self[column_name].head(100)).dropna()
if (len(head_row) == 0):
raise ValueError("Cannot infer column type because there is not enough rows to infer value")
if stack_column_type == dict:
# infer key/value type
keys = []; values = []
for row in head_row:
for val in row:
keys.append(val)
if val != None: values.append(row[val])
new_column_type = [
infer_type_of_list(keys),
infer_type_of_list(values)
]
else:
values = [v for v in itertools.chain.from_iterable(head_row)]
new_column_type = [infer_type_of_list(values)]
_mt._get_metric_tracker().track('sframe.stack')
with cython_context():
return SFrame(_proxy=self.__proxy__.stack(column_name, new_column_name, new_column_type, drop_na))
def unstack(self, column, new_column_name=None):
"""
Concatenate values from one or two columns into one column, grouping by
all other columns. The resulting column could be of type list, array or
dictionary. If ``column`` is a numeric column, the result will be of
array.array type. If ``column`` is a non-numeric column, the new column
will be of list type. If ``column`` is a list of two columns, the new
column will be of dict type where the keys are taken from the first
column in the list.
Parameters
----------
column : str | [str, str]
The column(s) that is(are) to be concatenated.
If str, then collapsed column type is either array or list.
If [str, str], then collapsed column type is dict
new_column_name : str, optional
New column name. If not given, a name is generated automatically.
Returns
-------
out : SFrame
A new SFrame containing the grouped columns as well as the new
column.
See Also
--------
stack : The inverse of unstack.
groupby : ``unstack`` is a special version of ``groupby`` that uses the
:mod:`~graphlab.aggregate.CONCAT` aggregator
Notes
-----
- There is no guarantee the resulting SFrame maintains the same order as
the original SFrame.
- Missing values are maintained during unstack.
- When unstacking into a dictionary, if there is more than one instance
of a given key for a particular group, an arbitrary value is selected.
Examples
--------
>>> sf = graphlab.SFrame({'count':[4, 2, 1, 1, 2, None],
... 'topic':['cat', 'cat', 'dog', 'elephant', 'elephant', 'fish'],
... 'word':['a', 'c', 'c', 'a', 'b', None]})
>>> sf.unstack(column=['word', 'count'], new_column_name='words')
+----------+------------------+
| topic | words |
+----------+------------------+
| elephant | {'a': 1, 'b': 2} |
| dog | {'c': 1} |
| cat | {'a': 4, 'c': 2} |
| fish | None |
+----------+------------------+
[4 rows x 2 columns]
>>> sf = graphlab.SFrame({'friend': [2, 3, 4, 5, 6, 4, 5, 2, 3],
... 'user': [1, 1, 1, 2, 2, 2, 3, 4, 4]})
>>> sf.unstack('friend', new_column_name='friends')
+------+-----------------------------+
| user | friends |
+------+-----------------------------+
| 3 | array('d', [5.0]) |
| 1 | array('d', [2.0, 4.0, 3.0]) |
| 2 | array('d', [5.0, 6.0, 4.0]) |
| 4 | array('d', [2.0, 3.0]) |
+------+-----------------------------+
[4 rows x 2 columns]
"""
if (type(column) != str and len(column) != 2):
raise TypeError("'column' parameter has to be either a string or a list of two strings.")
_mt._get_metric_tracker().track('sframe.unstack')
with cython_context():
if type(column) == str:
key_columns = [i for i in self.column_names() if i != column]
if new_column_name != None:
return self.groupby(key_columns, {new_column_name : graphlab.aggregate.CONCAT(column)})
else:
return self.groupby(key_columns, graphlab.aggregate.CONCAT(column))
elif len(column) == 2:
key_columns = [i for i in self.column_names() if i not in column]
if new_column_name != None:
return self.groupby(key_columns, {new_column_name:graphlab.aggregate.CONCAT(column[0], column[1])})
else:
return self.groupby(key_columns, graphlab.aggregate.CONCAT(column[0], column[1]))
def unique(self):
"""
Remove duplicate rows of the SFrame. Will not necessarily preserve the
order of the given SFrame in the new SFrame.
Returns
-------
out : SFrame
A new SFrame that contains the unique rows of the current SFrame.
Raises
------
TypeError
If any column in the SFrame is a dictionary type.
See Also
--------
SArray.unique
Examples
--------
>>> sf = graphlab.SFrame({'id':[1,2,3,3,4], 'value':[1,2,3,3,4]})
>>> sf
+----+-------+
| id | value |
+----+-------+
| 1 | 1 |
| 2 | 2 |
| 3 | 3 |
| 3 | 3 |
| 4 | 4 |
+----+-------+
[5 rows x 2 columns]
>>> sf.unique()
+----+-------+
| id | value |
+----+-------+
| 2 | 2 |
| 4 | 4 |
| 3 | 3 |
| 1 | 1 |
+----+-------+
[4 rows x 2 columns]
"""
return self.groupby(self.column_names(),{})
def sort(self, sort_columns, ascending=True):
"""
Sort current SFrame by the given columns, using the given sort order.
Only columns that are type of str, int and float can be sorted.
Parameters
----------
sort_columns : str | list of str | list of (str, bool) pairs
Names of columns to be sorted. The result will be sorted first by
first column, followed by second column, and so on. All columns will
be sorted in the same order as governed by the `ascending`
parameter. To control the sort ordering for each column
individually, `sort_columns` must be a list of (str, bool) pairs.
Given this case, the first value is the column name and the second
value is a boolean indicating whether the sort order is ascending.
ascending : bool, optional
Sort all columns in the given order.
Returns
-------
out : SFrame
A new SFrame that is sorted according to given sort criteria
See Also
--------
topk
Examples
--------
Suppose 'sf' is an sframe that has three columns 'a', 'b', 'c'.
To sort by column 'a', ascending
>>> sf = graphlab.SFrame({'a':[1,3,2,1],
... 'b':['a','c','b','b'],
... 'c':['x','y','z','y']})
>>> sf
+---+---+---+
| a | b | c |
+---+---+---+
| 1 | a | x |
| 3 | c | y |
| 2 | b | z |
| 1 | b | y |
+---+---+---+
[4 rows x 3 columns]
>>> sf.sort('a')
+---+---+---+
| a | b | c |
+---+---+---+
| 1 | a | x |
| 1 | b | y |
| 2 | b | z |
| 3 | c | y |
+---+---+---+
[4 rows x 3 columns]
To sort by column 'a', descending
>>> sf.sort('a', ascending = False)
+---+---+---+
| a | b | c |
+---+---+---+
| 3 | c | y |
| 2 | b | z |
| 1 | a | x |
| 1 | b | y |
+---+---+---+
[4 rows x 3 columns]
To sort by column 'a' and 'b', all ascending
>>> sf.sort(['a', 'b'])
+---+---+---+
| a | b | c |
+---+---+---+
| 1 | a | x |
| 1 | b | y |
| 2 | b | z |
| 3 | c | y |
+---+---+---+
[4 rows x 3 columns]
To sort by column 'a' ascending, and then by column 'c' descending
>>> sf.sort([('a', True), ('c', False)])
+---+---+---+
| a | b | c |
+---+---+---+
| 1 | b | y |
| 1 | a | x |
| 2 | b | z |
| 3 | c | y |
+---+---+---+
[4 rows x 3 columns]
"""
sort_column_names = []
sort_column_orders = []
# validate sort_columns
if (type(sort_columns) == str):
sort_column_names = [sort_columns]
elif (type(sort_columns) == list):
if (len(sort_columns) == 0):
raise ValueError("Please provide at least one column to sort")
first_param_types = set([type(i) for i in sort_columns])
if (len(first_param_types) != 1):
raise ValueError("sort_columns element are not of the same type")
first_param_type = first_param_types.pop()
if (first_param_type == tuple):
sort_column_names = [i[0] for i in sort_columns]
sort_column_orders = [i[1] for i in sort_columns]
elif(first_param_type == str):
sort_column_names = sort_columns
else:
raise TypeError("sort_columns type is not supported")
else:
raise TypeError("sort_columns type is not correct. Supported types are str, list of str or list of (str,bool) pair.")
# use the second parameter if the sort order is not given
if (len(sort_column_orders) == 0):
sort_column_orders = [ascending for i in sort_column_names]
# make sure all column exists
my_column_names = set(self.column_names())
for column in sort_column_names:
if (type(column) != str):
raise TypeError("Only string parameter can be passed in as column names")
if (column not in my_column_names):
raise ValueError("SFrame has no column named: '" + str(column) + "'")
if (self[column].dtype() not in (str, int, float,datetime.datetime)):
raise TypeError("Only columns of type (str, int, float) can be sorted")
_mt._get_metric_tracker().track('sframe.sort')
with cython_context():
return SFrame(_proxy=self.__proxy__.sort(sort_column_names, sort_column_orders))
def dropna(self, columns=None, how='any'):
"""
Remove missing values from an SFrame. A missing value is either ``None``
or ``NaN``. If ``how`` is 'any', a row will be removed if any of the
columns in the ``columns`` parameter contains at least one missing
value. If ``how`` is 'all', a row will be removed if all of the columns
in the ``columns`` parameter are missing values.
If the ``columns`` parameter is not specified, the default is to
consider all columns when searching for missing values.
Parameters
----------
columns : list or str, optional
The columns to use when looking for missing values. By default, all
columns are used.
how : {'any', 'all'}, optional
Specifies whether a row should be dropped if at least one column
has missing values, or if all columns have missing values. 'any' is
default.
Returns
-------
out : SFrame
SFrame with missing values removed (according to the given rules).
See Also
--------
dropna_split : Drops missing rows from the SFrame and returns them.
Examples
--------
Drop all missing values.
>>> sf = graphlab.SFrame({'a': [1, None, None], 'b': ['a', 'b', None]})
>>> sf.dropna()
+---+---+
| a | b |
+---+---+
| 1 | a |
+---+---+
[1 rows x 2 columns]
Drop rows where every value is missing.
>>> sf.dropna(any="all")
+------+---+
| a | b |
+------+---+
| 1 | a |
| None | b |
+------+---+
[2 rows x 2 columns]
Drop rows where column 'a' has a missing value.
>>> sf.dropna('a', any="all")
+---+---+
| a | b |
+---+---+
| 1 | a |
+---+---+
[1 rows x 2 columns]
"""
_mt._get_metric_tracker().track('sframe.dropna')
# If the user gives me an empty list (the indicator to use all columns)
# NA values being dropped would not be the expected behavior. This
# is a NOOP, so let's not bother the server
if type(columns) is list and len(columns) == 0:
return SFrame(_proxy=self.__proxy__)
(columns, all_behavior) = self.__dropna_errchk(columns, how)
with cython_context():
return SFrame(_proxy=self.__proxy__.drop_missing_values(columns, all_behavior, False))
def dropna_split(self, columns=None, how='any'):
"""
Split rows with missing values from this SFrame. This function has the
same functionality as :py:func:`~graphlab.SFrame.dropna`, but returns a
tuple of two SFrames. The first item is the expected output from
:py:func:`~graphlab.SFrame.dropna`, and the second item contains all the
rows filtered out by the `dropna` algorithm.
Parameters
----------
columns : list or str, optional
The columns to use when looking for missing values. By default, all
columns are used.
how : {'any', 'all'}, optional
Specifies whether a row should be dropped if at least one column
has missing values, or if all columns have missing values. 'any' is
default.
Returns
-------
out : (SFrame, SFrame)
(SFrame with missing values removed,
SFrame with the removed missing values)
See Also
--------
dropna
Examples
--------
>>> sf = graphlab.SFrame({'a': [1, None, None], 'b': ['a', 'b', None]})
>>> good, bad = sf.dropna_split()
>>> good
+---+---+
| a | b |
+---+---+
| 1 | a |
+---+---+
[1 rows x 2 columns]
>>> bad
+------+------+
| a | b |
+------+------+
| None | b |
| None | None |
+------+------+
[2 rows x 2 columns]
"""
_mt._get_metric_tracker().track('sframe.dropna_split')
# If the user gives me an empty list (the indicator to use all columns)
# NA values being dropped would not be the expected behavior. This
# is a NOOP, so let's not bother the server
if type(columns) is list and len(columns) == 0:
return (SFrame(_proxy=self.__proxy__), SFrame())
(columns, all_behavior) = self.__dropna_errchk(columns, how)
sframe_tuple = self.__proxy__.drop_missing_values(columns, all_behavior, True)
if len(sframe_tuple) != 2:
raise RuntimeError("Did not return two SFrames!")
with cython_context():
return (SFrame(_proxy=sframe_tuple[0]), SFrame(_proxy=sframe_tuple[1]))
def __dropna_errchk(self, columns, how):
if columns is None:
# Default behavior is to consider every column, specified to
# the server by an empty list (to avoid sending all the column
# in this case, since it is the most common)
columns = list()
elif type(columns) is str:
columns = [columns]
elif type(columns) is not list:
raise TypeError("Must give columns as a list, str, or 'None'")
else:
# Verify that we are only passing strings in our list
list_types = set([type(i) for i in columns])
if (str not in list_types) or (len(list_types) > 1):
raise TypeError("All columns must be of 'str' type")
if how not in ['any','all']:
raise ValueError("Must specify 'any' or 'all'")
if how == 'all':
all_behavior = True
else:
all_behavior = False
return (columns, all_behavior)
def fillna(self, column, value):
"""
Fill all missing values with a given value in a given column. If the
``value`` is not the same type as the values in ``column``, this method
attempts to convert the value to the original column's type. If this
fails, an error is raised.
Parameters
----------
column : str
The name of the column to modify.
value : type convertible to SArray's type
The value used to replace all missing values.
Returns
-------
out : SFrame
A new SFrame with the specified value in place of missing values.
See Also
--------
dropna
Examples
--------
>>> sf = graphlab.SFrame({'a':[1, None, None],
... 'b':['13.1', '17.2', None]})
>>> sf = sf.fillna('a', 0)
>>> sf
+---+------+
| a | b |
+---+------+
| 1 | 13.1 |
| 0 | 17.2 |
| 0 | None |
+---+------+
[3 rows x 2 columns]
"""
# Normal error checking
if type(column) is not str:
raise TypeError("Must give column name as a str")
ret = self[self.column_names()]
ret[column] = ret[column].fillna(value)
return ret
def add_row_number(self, column_name='id', start=0):
"""
Returns a new SFrame with a new column that numbers each row
sequentially. By default the count starts at 0, but this can be changed
to a positive or negative number. The new column will be named with
the given column name. An error will be raised if the given column
name already exists in the SFrame.
Parameters
----------
column_name : str, optional
The name of the new column that will hold the row numbers.
start : int, optional
The number used to start the row number count.
Returns
-------
out : SFrame
The new SFrame with a column name
Notes
-----
The range of numbers is constrained by a signed 64-bit integer, so
beware of overflow if you think the results in the row number column
will be greater than 9 quintillion.
Examples
--------
>>> sf = graphlab.SFrame({'a': [1, None, None], 'b': ['a', 'b', None]})
>>> sf.add_row_number()
+----+------+------+
| id | a | b |
+----+------+------+
| 0 | 1 | a |
| 1 | None | b |
| 2 | None | None |
+----+------+------+
[3 rows x 3 columns]
"""
_mt._get_metric_tracker().track('sframe.add_row_number')
if type(column_name) is not str:
raise TypeError("Must give column_name as strs")
if type(start) is not int:
raise TypeError("Must give start as int")
if column_name in self.column_names():
raise RuntimeError("Column '" + column_name + "' already exists in the current SFrame")
the_col = _create_sequential_sarray(self.num_rows(), start)
# Make sure the row number column is the first column
new_sf = SFrame()
new_sf.add_column(the_col, column_name)
new_sf.add_columns(self)
return new_sf
@property
def shape(self):
"""
The shape of the SFrame, in a tuple. The first entry is the number of
rows, the second is the number of columns.
Examples
--------
>>> sf = graphlab.SFrame({'id':[1,2,3], 'val':['A','B','C']})
>>> sf.shape
(3, 2)
"""
return (self.num_rows(), self.num_cols())
@property
def __proxy__(self):
return self._proxy
@__proxy__.setter
def __proxy__(self, value):
assert type(value) is UnitySFrameProxy
self._proxy = value
| agpl-3.0 |
vrv/tensorflow | tensorflow/python/kernel_tests/distributions/categorical_test.py | 12 | 11556 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
"""Tests for Categorical distribution."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import tensor_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gradients_impl
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import nn_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops.distributions import categorical
from tensorflow.python.ops.distributions import kullback_leibler
from tensorflow.python.platform import test
def make_categorical(batch_shape, num_classes, dtype=dtypes.int32):
logits = random_ops.random_uniform(
list(batch_shape) + [num_classes], -10, 10, dtype=dtypes.float32) - 50.
return categorical.Categorical(logits, dtype=dtype)
class CategoricalTest(test.TestCase):
def testP(self):
p = [0.2, 0.8]
dist = categorical.Categorical(probs=p)
with self.test_session():
self.assertAllClose(p, dist.probs.eval())
self.assertAllEqual([2], dist.logits.get_shape())
def testLogits(self):
p = np.array([0.2, 0.8], dtype=np.float32)
logits = np.log(p) - 50.
dist = categorical.Categorical(logits=logits)
with self.test_session():
self.assertAllEqual([2], dist.probs.get_shape())
self.assertAllEqual([2], dist.logits.get_shape())
self.assertAllClose(dist.probs.eval(), p)
self.assertAllClose(dist.logits.eval(), logits)
def testShapes(self):
with self.test_session():
for batch_shape in ([], [1], [2, 3, 4]):
dist = make_categorical(batch_shape, 10)
self.assertAllEqual(batch_shape, dist.batch_shape)
self.assertAllEqual(batch_shape, dist.batch_shape_tensor().eval())
self.assertAllEqual([], dist.event_shape)
self.assertAllEqual([], dist.event_shape_tensor().eval())
self.assertEqual(10, dist.event_size.eval())
# event_size is available as a constant because the shape is
# known at graph build time.
self.assertEqual(10, tensor_util.constant_value(dist.event_size))
for batch_shape in ([], [1], [2, 3, 4]):
dist = make_categorical(
batch_shape, constant_op.constant(
10, dtype=dtypes.int32))
self.assertAllEqual(len(batch_shape), dist.batch_shape.ndims)
self.assertAllEqual(batch_shape, dist.batch_shape_tensor().eval())
self.assertAllEqual([], dist.event_shape)
self.assertAllEqual([], dist.event_shape_tensor().eval())
self.assertEqual(10, dist.event_size.eval())
def testDtype(self):
dist = make_categorical([], 5, dtype=dtypes.int32)
self.assertEqual(dist.dtype, dtypes.int32)
self.assertEqual(dist.dtype, dist.sample(5).dtype)
self.assertEqual(dist.dtype, dist.mode().dtype)
dist = make_categorical([], 5, dtype=dtypes.int64)
self.assertEqual(dist.dtype, dtypes.int64)
self.assertEqual(dist.dtype, dist.sample(5).dtype)
self.assertEqual(dist.dtype, dist.mode().dtype)
self.assertEqual(dist.probs.dtype, dtypes.float32)
self.assertEqual(dist.logits.dtype, dtypes.float32)
self.assertEqual(dist.logits.dtype, dist.entropy().dtype)
self.assertEqual(
dist.logits.dtype, dist.prob(np.array(
0, dtype=np.int64)).dtype)
self.assertEqual(
dist.logits.dtype, dist.log_prob(np.array(
0, dtype=np.int64)).dtype)
def testUnknownShape(self):
with self.test_session():
logits = array_ops.placeholder(dtype=dtypes.float32)
dist = categorical.Categorical(logits)
sample = dist.sample()
# Will sample class 1.
sample_value = sample.eval(feed_dict={logits: [-1000.0, 1000.0]})
self.assertEqual(1, sample_value)
# Batch entry 0 will sample class 1, batch entry 1 will sample class 0.
sample_value_batch = sample.eval(
feed_dict={logits: [[-1000.0, 1000.0], [1000.0, -1000.0]]})
self.assertAllEqual([1, 0], sample_value_batch)
def testPMFWithBatch(self):
histograms = [[0.2, 0.8], [0.6, 0.4]]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
with self.test_session():
self.assertAllClose(dist.prob([0, 1]).eval(), [0.2, 0.4])
def testPMFNoBatch(self):
histograms = [0.2, 0.8]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
with self.test_session():
self.assertAllClose(dist.prob(0).eval(), 0.2)
def testLogPMF(self):
logits = np.log([[0.2, 0.8], [0.6, 0.4]]) - 50.
dist = categorical.Categorical(logits)
with self.test_session():
self.assertAllClose(dist.log_prob([0, 1]).eval(), np.log([0.2, 0.4]))
def testEntropyNoBatch(self):
logits = np.log([0.2, 0.8]) - 50.
dist = categorical.Categorical(logits)
with self.test_session():
self.assertAllClose(dist.entropy().eval(),
-(0.2 * np.log(0.2) + 0.8 * np.log(0.8)))
def testEntropyWithBatch(self):
logits = np.log([[0.2, 0.8], [0.6, 0.4]]) - 50.
dist = categorical.Categorical(logits)
with self.test_session():
self.assertAllClose(dist.entropy().eval(), [
-(0.2 * np.log(0.2) + 0.8 * np.log(0.8)),
-(0.6 * np.log(0.6) + 0.4 * np.log(0.4))
])
def testEntropyGradient(self):
with self.test_session() as sess:
logits = constant_op.constant([[1., 2., 3.], [2., 5., 1.]])
probabilities = nn_ops.softmax(logits)
log_probabilities = nn_ops.log_softmax(logits)
true_entropy = - math_ops.reduce_sum(
probabilities * log_probabilities, axis=-1)
categorical_distribution = categorical.Categorical(probs=probabilities)
categorical_entropy = categorical_distribution.entropy()
# works
true_entropy_g = gradients_impl.gradients(true_entropy, [logits])
categorical_entropy_g = gradients_impl.gradients(
categorical_entropy, [logits])
res = sess.run({"true_entropy": true_entropy,
"categorical_entropy": categorical_entropy,
"true_entropy_g": true_entropy_g,
"categorical_entropy_g": categorical_entropy_g})
self.assertAllClose(res["true_entropy"],
res["categorical_entropy"])
self.assertAllClose(res["true_entropy_g"],
res["categorical_entropy_g"])
def testSample(self):
with self.test_session():
histograms = [[[0.2, 0.8], [0.4, 0.6]]]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
n = 10000
samples = dist.sample(n, seed=123)
samples.set_shape([n, 1, 2])
self.assertEqual(samples.dtype, dtypes.int32)
sample_values = samples.eval()
self.assertFalse(np.any(sample_values < 0))
self.assertFalse(np.any(sample_values > 1))
self.assertAllClose(
[[0.2, 0.4]], np.mean(
sample_values == 0, axis=0), atol=1e-2)
self.assertAllClose(
[[0.8, 0.6]], np.mean(
sample_values == 1, axis=0), atol=1e-2)
def testSampleWithSampleShape(self):
with self.test_session():
histograms = [[[0.2, 0.8], [0.4, 0.6]]]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
samples = dist.sample((100, 100), seed=123)
prob = dist.prob(samples)
prob_val = prob.eval()
self.assertAllClose(
[0.2**2 + 0.8**2], [prob_val[:, :, :, 0].mean()], atol=1e-2)
self.assertAllClose(
[0.4**2 + 0.6**2], [prob_val[:, :, :, 1].mean()], atol=1e-2)
def testLogPMFBroadcasting(self):
with self.test_session():
histograms = [[[0.2, 0.8], [0.4, 0.6]]]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
prob = dist.prob(1)
self.assertAllClose([[0.8, 0.6]], prob.eval())
prob = dist.prob([1])
self.assertAllClose([[0.8, 0.6]], prob.eval())
prob = dist.prob([0, 1])
self.assertAllClose([[0.2, 0.6]], prob.eval())
prob = dist.prob([[0, 1]])
self.assertAllClose([[0.2, 0.6]], prob.eval())
prob = dist.prob([[[0, 1]]])
self.assertAllClose([[[0.2, 0.6]]], prob.eval())
prob = dist.prob([[1, 0], [0, 1]])
self.assertAllClose([[0.8, 0.4], [0.2, 0.6]], prob.eval())
prob = dist.prob([[[1, 1], [1, 0]], [[1, 0], [0, 1]]])
self.assertAllClose([[[0.8, 0.6], [0.8, 0.4]], [[0.8, 0.4], [0.2, 0.6]]],
prob.eval())
def testLogPMFShape(self):
with self.test_session():
# shape [1, 2, 2]
histograms = [[[0.2, 0.8], [0.4, 0.6]]]
dist = categorical.Categorical(math_ops.log(histograms))
log_prob = dist.log_prob([0, 1])
self.assertEqual(2, log_prob.get_shape().ndims)
self.assertAllEqual([1, 2], log_prob.get_shape())
log_prob = dist.log_prob([[[1, 1], [1, 0]], [[1, 0], [0, 1]]])
self.assertEqual(3, log_prob.get_shape().ndims)
self.assertAllEqual([2, 2, 2], log_prob.get_shape())
def testLogPMFShapeNoBatch(self):
histograms = [0.2, 0.8]
dist = categorical.Categorical(math_ops.log(histograms))
log_prob = dist.log_prob(0)
self.assertEqual(0, log_prob.get_shape().ndims)
self.assertAllEqual([], log_prob.get_shape())
log_prob = dist.log_prob([[[1, 1], [1, 0]], [[1, 0], [0, 1]]])
self.assertEqual(3, log_prob.get_shape().ndims)
self.assertAllEqual([2, 2, 2], log_prob.get_shape())
def testMode(self):
with self.test_session():
histograms = [[[0.2, 0.8], [0.6, 0.4]]]
dist = categorical.Categorical(math_ops.log(histograms) - 50.)
self.assertAllEqual(dist.mode().eval(), [[1, 0]])
def testCategoricalCategoricalKL(self):
def np_softmax(logits):
exp_logits = np.exp(logits)
return exp_logits / exp_logits.sum(axis=-1, keepdims=True)
with self.test_session() as sess:
for categories in [2, 4]:
for batch_size in [1, 10]:
a_logits = np.random.randn(batch_size, categories)
b_logits = np.random.randn(batch_size, categories)
a = categorical.Categorical(logits=a_logits)
b = categorical.Categorical(logits=b_logits)
kl = kullback_leibler.kl_divergence(a, b)
kl_val = sess.run(kl)
# Make sure KL(a||a) is 0
kl_same = sess.run(kullback_leibler.kl_divergence(a, a))
prob_a = np_softmax(a_logits)
prob_b = np_softmax(b_logits)
kl_expected = np.sum(prob_a * (np.log(prob_a) - np.log(prob_b)),
axis=-1)
self.assertEqual(kl.get_shape(), (batch_size,))
self.assertAllClose(kl_val, kl_expected)
self.assertAllClose(kl_same, np.zeros_like(kl_expected))
if __name__ == "__main__":
test.main()
| apache-2.0 |
revmischa/boto | boto/services/__init__.py | 782 | 1108 | # Copyright (c) 2006,2007 Mitch Garnaat http://garnaat.org/
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish, dis-
# tribute, sublicense, and/or sell copies of the Software, and to permit
# persons to whom the Software is furnished to do so, subject to the fol-
# lowing conditions:
#
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABIL-
# ITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
# SHALL THE AUTHOR BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
# IN THE SOFTWARE.
#
| mit |
marratj/ansible | lib/ansible/modules/windows/win_domain.py | 31 | 2009 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# (c) 2017, Red Hat, Inc.
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'core'}
DOCUMENTATION = '''
module: win_domain
short_description: Ensures the existence of a Windows domain.
version_added: 2.3
description:
- Ensure that the domain named by C(dns_domain_name) exists and is reachable. If the domain is not reachable, the domain is created in a new forest
on the target Windows Server 2012R2+ host. This module may require subsequent use of the M(win_reboot) action if changes are made.
options:
dns_domain_name:
description:
- the DNS name of the domain which should exist and be reachable or reside on the target Windows host
required: true
safe_mode_password:
description:
- safe mode password for the domain controller
required: true
author:
- Matt Davis (@nitzmahone)
'''
RETURN = '''
reboot_required:
description: True if changes were made that require a reboot.
returned: always
type: boolean
sample: true
'''
EXAMPLES = r'''
# ensure the named domain is reachable from the target host; if not, create the domain in a new forest residing on the target host
- win_domain:
dns_domain_name: ansible.vagrant
safe_mode_password: password123!
'''
| gpl-3.0 |
clebergnu/avocado-vt | virttest/nfs.py | 2 | 18942 | """
Basic nfs support for Linux host. It can support the remote
nfs mount and the local nfs set up and mount.
"""
import re
import aexpect
import logging
from avocado.utils import path
from avocado.utils import process
from avocado.utils import distro
from avocado.utils.astring import to_text
from avocado.core import exceptions
from virttest import utils_misc
from virttest import test_setup
from virttest.utils_iptables import Iptables
from virttest.utils_conn import SSHConnection
from virttest.staging import service
def nfs_exported(session=None):
"""
Get the list for nfs file system already exported
:param session: ShellSessionObject of remote/guest
:return: a list of nfs that is already exported in system
:rtype: a lit of nfs file system exported
"""
func = process.system_output
if session:
func = session.cmd_output
exportfs = to_text(func("exportfs -v"))
if not exportfs:
return {}
nfs_exported_dict = {}
for fs_info in re.findall("[/\w+]+.*?\(.*?\)", exportfs, re.S):
fs_info = fs_info.strip().split()
if len(fs_info) == 2:
nfs_src = fs_info[0]
access_ip = re.findall(r"(.*)\(", fs_info[1])[0]
if "world" in access_ip:
access_ip = "*"
nfs_tag = "%s_%s" % (nfs_src, access_ip)
permission = re.findall(r"\((.*)\)", fs_info[1])[0]
nfs_exported_dict[nfs_tag] = permission
return nfs_exported_dict
class Exportfs(object):
"""
Add or remove one entry to exported nfs file system.
"""
def __init__(self, path, client="*", options="", ori_exported=None, session=None):
if ori_exported is None:
ori_exported = []
self.path = path
self.client = client
self.options = options.split(",")
self.ori_exported = ori_exported
self.entry_tag = "%s_%s" % (self.path, self.client)
self.already_exported = False
self.ori_options = ""
self.session = session
self.func = process.getoutput
if self.session:
self.func = self.session.cmd_output
def is_exported(self):
"""
Check if the directory is already exported.
:return: If the entry is exported
:rtype: Boolean
"""
ori_exported = self.ori_exported or nfs_exported(session=self.session)
if self.entry_tag in list(ori_exported.keys()):
return True
return False
def need_reexport(self):
"""
Check if the entry is already exported but the options are not
the same as we required.
:return: Need re export the entry or not
:rtype: Boolean
"""
ori_exported = self.ori_exported or nfs_exported(session=self.session)
if self.is_exported():
exported_options = ori_exported[self.entry_tag]
options = [_ for _ in self.options if _ not in exported_options]
if options:
self.ori_options = exported_options
return True
return False
def unexport(self):
"""
Unexport an entry.
"""
if self.is_exported():
unexport_cmd = "exportfs -u %s:%s" % (self.client, self.path)
self.func(unexport_cmd)
else:
logging.warn("Target %s %s is not exported yet."
"Can not unexport it." % (self.client, self.path))
def reset_export(self):
"""
Reset the exportfs to the original status before we export the
specific entry.
"""
self.unexport()
if self.ori_options:
tmp_options = self.options
self.options = self.ori_options.split(",")
self.export()
self.options = tmp_options
def export(self):
"""
Export one directory if it is not in exported list.
:return: Export nfs file system succeed or not
"""
if self.is_exported():
if self.need_reexport():
self.unexport()
else:
self.already_exported = True
logging.warn("Already exported target."
" Don't need export it again")
return True
export_cmd = "exportfs"
if self.options:
export_cmd += " -o %s" % ",".join(self.options)
export_cmd += " %s:%s" % (self.client, self.path)
try:
self.func(export_cmd)
except (process.CmdError, aexpect.ShellTimeoutError) as export_failed_err:
logging.error("Can not export target: %s" % export_failed_err)
return False
return True
class Nfs(object):
"""
Nfs class for handle nfs mount and umount. If a local nfs service is
required, it will configure a local nfs server accroding the params.
"""
def __init__(self, params):
self.mount_dir = params.get("nfs_mount_dir")
self.mount_options = params.get("nfs_mount_options")
self.mount_src = params.get("nfs_mount_src")
self.nfs_setup = False
path.find_command("mount")
self.rm_mount_dir = False
self.rm_export_dir = False
self.unexportfs_in_clean = False
distro_details = distro.detect().name
self.session = None
self.setup_nfs_ip = params.get("nfs_server_ip", "127.0.0.1")
self.export_dir = (params.get("export_dir") or
self.mount_src.split(":")[-1])
self.export_ip = params.get("export_ip", "*")
self.export_options = params.get("export_options", "").strip()
if params.get("setup_remote_nfs") == "yes":
self.nfs_setup = True
self.setup_nfs_ip = params["nfs_server_ip"]
nfs_server_params = {'server_ip': self.setup_nfs_ip,
'server_pwd': params["nfs_server_pwd"],
'server_user': params.get("nfs_server_user",
"root")}
self.session = test_setup.remote_session(nfs_server_params)
distro_details = utils_misc.get_distro(self.session)
if self.session.cmd_status("exportfs -h") != 0:
logging.error("exportfs cmd not available in remote host")
elif params.get("setup_local_nfs") == "yes":
self.nfs_setup = True
self.setup_nfs_ip = "127.0.0.1"
path.find_command("service")
path.find_command("exportfs")
if(params.get("setup_remote_nfs") == "yes" or
params.get("setup_local_nfs") == "yes"):
if 'Ubuntu' in distro_details or 'rhel' in distro_details:
self.nfs_service = service.Service("nfs-server",
session=self.session)
else:
self.nfs_service = service.Service("nfs", session=self.session)
self.rpcbind_service = service.Service("rpcbind", session=self.session)
self.exportfs = Exportfs(self.export_dir, self.export_ip,
self.export_options, session=self.session)
self.mount_src = "%s:%s" % (self.setup_nfs_ip, self.export_dir)
def is_mounted(self):
"""
Check the NFS is mounted or not.
:return: If the src is mounted as expect
:rtype: Boolean
"""
return utils_misc.is_mounted(self.mount_src, self.mount_dir, "nfs")
def mount(self):
"""
Mount source into given mount point.
"""
return utils_misc.mount(self.mount_src, self.mount_dir, "nfs",
perm=self.mount_options)
def umount(self):
"""
Umount the given mount point.
"""
return utils_misc.umount(self.mount_src, self.mount_dir, "nfs")
def setup(self):
"""
Setup NFS in host.
Mount NFS as configured. If a local nfs is requested, setup the NFS
service and exportfs too.
"""
if self.nfs_setup:
if not self.nfs_service.status():
logging.debug("Restart NFS service.")
self.rpcbind_service.restart()
self.nfs_service.restart()
if not utils_misc.check_isdir(self.export_dir, session=self.session):
utils_misc.make_dirs(self.export_dir, session=self.session)
self.rm_export_dir = True
self.exportfs.export()
self.unexportfs_in_clean = not self.exportfs.already_exported
logging.debug("Mount %s to %s" % (self.mount_src, self.mount_dir))
if(utils_misc.check_exists(self.mount_dir, session=self.session)
and not utils_misc.check_isdir(self.mount_dir, session=self.session)):
raise OSError(
"Mount point %s is not a directory, check your setup." %
self.mount_dir)
if not utils_misc.check_isdir(self.mount_dir, session=self.session):
utils_misc.make_dirs(self.mount_dir, session=self.session)
self.rm_mount_dir = True
self.mount()
def cleanup(self):
"""
Clean up the host env.
Umount NFS from the mount point. If there has some change for exported
file system in host when setup, also clean up that.
"""
self.umount()
if self.nfs_setup and self.unexportfs_in_clean:
self.exportfs.reset_export()
if self.rm_export_dir and utils_misc.check_isdir(self.export_dir,
session=self.session):
utils_misc.safe_rmdir(self.export_dir)
if self.rm_mount_dir and utils_misc.check_isdir(self.mount_dir,
session=self.session):
utils_misc.safe_rmdir(self.mount_dir, session=self.session)
class NFSClient(object):
"""
NFSClient class for handle nfs remotely mount and umount.
"""
def __init__(self, params):
self.nfs_client_ip = params.get("nfs_client_ip")
# To Avoid host key verification failure
ret = process.run("ssh-keygen -R %s" % self.nfs_client_ip,
ignore_status=True)
stderr = ret.stderr_text
if ret.exit_status and "No such file or directory" not in stderr:
raise exceptions.TestFail("Failed to update host key: %s" %
stderr)
# Setup SSH connection
self.ssh_obj = SSHConnection(params)
ssh_timeout = int(params.get("ssh_timeout", 10))
self.ssh_obj.conn_setup(timeout=ssh_timeout)
self.params = params
self.mkdir_mount_remote = False
self.mount_dir = params.get("nfs_mount_dir")
self.mount_options = params.get("nfs_mount_options")
self.mount_src = params.get("nfs_mount_src")
self.nfs_server_ip = params.get("nfs_server_ip")
self.ssh_user = params.get("ssh_username", "root")
self.remote_nfs_mount = params.get("remote_nfs_mount", "yes")
self.ssh_hostkey_check = params.get("ssh_hostkey_check", "no") == "yes"
self.ssh_cmd = "ssh %s@%s " % (self.ssh_user, self.nfs_client_ip)
if not self.ssh_hostkey_check:
self.ssh_cmd += "-o StrictHostKeyChecking=no "
def is_mounted(self):
"""
Check the NFS is mounted or not.
:return: If the src is mounted as expect
:rtype: Boolean
"""
find_mountpoint_cmd = "mount | grep -E '.*%s.*%s.*'" % (self.mount_src,
self.mount_dir)
cmd = self.ssh_cmd + "'%s'" % find_mountpoint_cmd
logging.debug("The command: %s", cmd)
status, output = process.getstatusoutput(cmd)
if status:
logging.debug("The command result: <%s:%s>", status, output)
return False
return True
def setup(self):
"""
Setup NFS client.
"""
# Mount sharing directory to local host
# it has been covered by class Nfs
# Mount sharing directory to remote host
if self.remote_nfs_mount == "yes":
# stale file mounted causes test to fail instead
# unmount it and perform the setup
if self.is_mounted():
self.umount()
self.setup_remote()
def umount(self):
"""
Unmount the mount directory in remote host
"""
logging.debug("Umount %s from %s" %
(self.mount_dir, self.nfs_client_ip))
umount_cmd = self.ssh_cmd + "'umount -l %s'" % self.mount_dir
try:
process.system(umount_cmd, verbose=True)
except process.CmdError:
raise exceptions.TestFail("Failed to run: %s" % umount_cmd)
def cleanup(self, ssh_auto_recover=False):
"""
Cleanup NFS client.
"""
self.umount()
if self.mkdir_mount_remote:
rmdir_cmd = self.ssh_cmd + "'rm -rf %s'" % self.mount_dir
try:
process.system(rmdir_cmd, verbose=True)
except process.CmdError:
raise exceptions.TestFail("Failed to run: %s" % rmdir_cmd)
if self.is_mounted():
raise exceptions.TestFail("Failed to umount %s" % self.mount_dir)
# Recover SSH connection
if ssh_auto_recover:
self.ssh_obj.auto_recover = ssh_auto_recover
del self.ssh_obj
def firewall_to_permit_nfs(self):
"""
Method to configure firewall to permit NFS to be mounted
from remote host
"""
# Check firewall in host permit nfs service to mount from remote server
try:
firewalld = service.Factory.create_service("firewalld")
if not firewalld.status():
firewalld.start()
firewall_cmd = "firewall-cmd --list-all | grep services:"
try:
ret = process.run(firewall_cmd, shell=True)
if not ret.exit_status:
firewall_services = ret.stdout_text.split(':')[1].strip().split(' ')
if 'nfs' not in firewall_services:
service_cmd = "firewall-cmd --permanent --zone=public "
service_cmd += "--add-service=nfs"
ret = process.run(service_cmd, shell=True)
if ret.exit_status:
logging.error("nfs service not added in firewall: "
"%s", ret.stdout_text)
else:
logging.debug("nfs service added to firewall "
"sucessfully")
firewalld.restart()
else:
logging.debug("nfs service already permitted by firewall")
except process.CmdError:
# For RHEL 6 based system firewall-cmd is not available
logging.debug("Using iptables to permit NFS service")
nfs_ports = []
rule_list = []
nfsd = service.Factory.create_service("nfs")
rpcd = service.Factory.create_service("rpcbind")
iptables = service.Factory.create_service("iptables")
nfs_sysconfig = self.params.get("nfs_sysconfig_path",
"/etc/sysconfig/nfs")
tcp_port = self.params.get("nfs_tcp_port", "32803")
udp_port = self.params.get("nfs_udp_port", "32769")
mountd_port = self.params.get("nfs_mountd_port", "892")
subnet_mask = self.params.get("priv_subnet", "192.168.2.0/24")
nfs_ports.append("LOCKD_TCPPORT=%s" % tcp_port)
nfs_ports.append("LOCKD_UDPPORT=%s" % udp_port)
nfs_ports.append("MOUNTD_PORT=%s" % mountd_port)
cmd_output = process.run("cat %s" % nfs_sysconfig,
shell=True).stdout_text
exist_ports = cmd_output.strip().split('\n')
# check if the ports are already configured, if not then add it
for each_port in nfs_ports:
if each_port not in exist_ports:
process.run("echo '%s' >> %s" %
(each_port, nfs_sysconfig), shell=True)
rpcd.restart()
nfsd.restart()
rule_temp = "INPUT -m state --state NEW -p %s -m multiport "
rule_temp += "--dport 111,892,2049,%s -s %s -j ACCEPT"
rule = rule_temp % ("tcp", tcp_port, subnet_mask)
rule_list.append(rule)
rule = rule_temp % ("udp", udp_port, subnet_mask)
rule_list.append(rule)
Iptables.setup_or_cleanup_iptables_rules(rule_list)
iptables.restart()
except Exception as info:
logging.error("Firewall setting to add nfs service "
"failed: %s", info)
def setup_remote(self):
"""
Mount sharing directory to remote host.
"""
check_mount_dir_cmd = self.ssh_cmd + "'ls -d %s'" % self.mount_dir
logging.debug("To check if the %s exists", self.mount_dir)
output = process.getoutput(check_mount_dir_cmd)
if re.findall("No such file or directory", output, re.M):
mkdir_cmd = self.ssh_cmd + "'mkdir -p %s'" % self.mount_dir
logging.debug("Prepare to create %s", self.mount_dir)
s, o = process.getstatusoutput(mkdir_cmd)
if s != 0:
raise exceptions.TestFail("Failed to run %s: %s" %
(mkdir_cmd, o))
self.mkdir_mount_remote = True
if self.params.get("firewall_to_permit_nfs", "yes") == "yes":
if distro.detect().name != "Ubuntu":
self.firewall_to_permit_nfs()
self.mount_src = "%s:%s" % (self.nfs_server_ip, self.mount_src)
logging.debug("Mount %s to %s" % (self.mount_src, self.mount_dir))
mount_cmd = "mount -t nfs %s %s" % (self.mount_src, self.mount_dir)
if self.mount_options:
mount_cmd += " -o %s" % self.mount_options
try:
cmd = "%s '%s'" % (self.ssh_cmd, mount_cmd)
process.system(cmd, verbose=True)
except process.CmdError:
raise exceptions.TestFail("Failed to run: %s" % cmd)
# Check if the sharing directory is mounted
if not self.is_mounted():
raise exceptions.TestFail("Failed to mount from %s to %s" %
self.mount_src, self.mount_dir)
| gpl-2.0 |
jelugbo/tundex | common/lib/xmodule/xmodule/modulestore/tests/test_modulestore.py | 25 | 2199 | from nose.tools import assert_equals, assert_true, assert_false # pylint: disable=E0611
def check_has_course_method(modulestore, locator, locator_key_fields):
error_message = "Called has_course with query {0} and ignore_case is {1}."
for ignore_case in [True, False]:
# should find the course with exact locator
assert_true(modulestore.has_course(locator, ignore_case))
for key_field in locator_key_fields:
if getattr(locator, key_field):
locator_changes_that_should_not_be_found = [ # pylint: disable=invalid-name
# replace value for one of the keys
{key_field: 'fake'},
# add a character at the end
{key_field: getattr(locator, key_field) + 'X'},
# add a character in the beginning
{key_field: 'X' + getattr(locator, key_field)},
]
for changes in locator_changes_that_should_not_be_found:
search_locator = locator.replace(**changes)
assert_false(
modulestore.has_course(search_locator),
error_message.format(search_locator, ignore_case)
)
# test case [in]sensitivity
locator_case_changes = [
{key_field: getattr(locator, key_field).upper()},
{key_field: getattr(locator, key_field).capitalize()},
{key_field: getattr(locator, key_field).capitalize().swapcase()},
]
for changes in locator_case_changes:
search_locator = locator.replace(**changes)
# if ignore_case is true, the course would be found with a different-cased course locator.
# if ignore_case is false, the course should NOT found given an incorrectly-cased locator.
assert_equals(
modulestore.has_course(search_locator, ignore_case) is not None,
ignore_case,
error_message.format(search_locator, ignore_case)
)
| agpl-3.0 |
dmarcosgon/linux | tools/perf/scripts/python/sctop.py | 1996 | 2102 | # system call top
# (c) 2010, Tom Zanussi <tzanussi@gmail.com>
# Licensed under the terms of the GNU GPL License version 2
#
# Periodically displays system-wide system call totals, broken down by
# syscall. If a [comm] arg is specified, only syscalls called by
# [comm] are displayed. If an [interval] arg is specified, the display
# will be refreshed every [interval] seconds. The default interval is
# 3 seconds.
import os, sys, thread, time
sys.path.append(os.environ['PERF_EXEC_PATH'] + \
'/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
from perf_trace_context import *
from Core import *
from Util import *
usage = "perf script -s sctop.py [comm] [interval]\n";
for_comm = None
default_interval = 3
interval = default_interval
if len(sys.argv) > 3:
sys.exit(usage)
if len(sys.argv) > 2:
for_comm = sys.argv[1]
interval = int(sys.argv[2])
elif len(sys.argv) > 1:
try:
interval = int(sys.argv[1])
except ValueError:
for_comm = sys.argv[1]
interval = default_interval
syscalls = autodict()
def trace_begin():
thread.start_new_thread(print_syscall_totals, (interval,))
pass
def raw_syscalls__sys_enter(event_name, context, common_cpu,
common_secs, common_nsecs, common_pid, common_comm,
common_callchain, id, args):
if for_comm is not None:
if common_comm != for_comm:
return
try:
syscalls[id] += 1
except TypeError:
syscalls[id] = 1
def syscalls__sys_enter(event_name, context, common_cpu,
common_secs, common_nsecs, common_pid, common_comm,
id, args):
raw_syscalls__sys_enter(**locals())
def print_syscall_totals(interval):
while 1:
clear_term()
if for_comm is not None:
print "\nsyscall events for %s:\n\n" % (for_comm),
else:
print "\nsyscall events:\n\n",
print "%-40s %10s\n" % ("event", "count"),
print "%-40s %10s\n" % ("----------------------------------------", \
"----------"),
for id, val in sorted(syscalls.iteritems(), key = lambda(k, v): (v, k), \
reverse = True):
try:
print "%-40s %10d\n" % (syscall_name(id), val),
except TypeError:
pass
syscalls.clear()
time.sleep(interval)
| gpl-2.0 |
mtrbean/scipy | scipy/io/matlab/mio.py | 64 | 8782 | """
Module for reading and writing matlab (TM) .mat files
"""
# Authors: Travis Oliphant, Matthew Brett
from __future__ import division, print_function, absolute_import
import numpy as np
from scipy._lib.six import string_types
from .miobase import get_matfile_version, docfiller
from .mio4 import MatFile4Reader, MatFile4Writer
from .mio5 import MatFile5Reader, MatFile5Writer
__all__ = ['mat_reader_factory', 'loadmat', 'savemat', 'whosmat']
def _open_file(file_like, appendmat):
''' Open `file_like` and return as file-like object '''
if isinstance(file_like, string_types):
try:
return open(file_like, 'rb')
except IOError as e:
if appendmat and not file_like.endswith('.mat'):
file_like += '.mat'
try:
return open(file_like, 'rb')
except IOError:
pass # Rethrow the original exception.
raise
# not a string - maybe file-like object
try:
file_like.read(0)
except AttributeError:
raise IOError('Reader needs file name or open file-like object')
return file_like
@docfiller
def mat_reader_factory(file_name, appendmat=True, **kwargs):
"""Create reader for matlab .mat format files
Parameters
----------
%(file_arg)s
%(append_arg)s
%(load_args)s
%(struct_arg)s
Returns
-------
matreader : MatFileReader object
Initialized instance of MatFileReader class matching the mat file
type detected in `filename`.
"""
byte_stream = _open_file(file_name, appendmat)
mjv, mnv = get_matfile_version(byte_stream)
if mjv == 0:
return MatFile4Reader(byte_stream, **kwargs)
elif mjv == 1:
return MatFile5Reader(byte_stream, **kwargs)
elif mjv == 2:
raise NotImplementedError('Please use HDF reader for matlab v7.3 files')
else:
raise TypeError('Did not recognize version %s' % mjv)
@docfiller
def loadmat(file_name, mdict=None, appendmat=True, **kwargs):
"""
Load MATLAB file
Parameters
----------
file_name : str
Name of the mat file (do not need .mat extension if
appendmat==True) Can also pass open file-like object.
m_dict : dict, optional
Dictionary in which to insert matfile variables.
appendmat : bool, optional
True to append the .mat extension to the end of the given
filename, if not already present.
byte_order : str or None, optional
None by default, implying byte order guessed from mat
file. Otherwise can be one of ('native', '=', 'little', '<',
'BIG', '>').
mat_dtype : bool, optional
If True, return arrays in same dtype as would be loaded into
MATLAB (instead of the dtype with which they are saved).
squeeze_me : bool, optional
Whether to squeeze unit matrix dimensions or not.
chars_as_strings : bool, optional
Whether to convert char arrays to string arrays.
matlab_compatible : bool, optional
Returns matrices as would be loaded by MATLAB (implies
squeeze_me=False, chars_as_strings=False, mat_dtype=True,
struct_as_record=True).
struct_as_record : bool, optional
Whether to load MATLAB structs as numpy record arrays, or as
old-style numpy arrays with dtype=object. Setting this flag to
False replicates the behavior of scipy version 0.7.x (returning
numpy object arrays). The default setting is True, because it
allows easier round-trip load and save of MATLAB files.
verify_compressed_data_integrity : bool, optional
Whether the length of compressed sequences in the MATLAB file
should be checked, to ensure that they are not longer than we expect.
It is advisable to enable this (the default) because overlong
compressed sequences in MATLAB files generally indicate that the
files have experienced some sort of corruption.
variable_names : None or sequence
If None (the default) - read all variables in file. Otherwise
`variable_names` should be a sequence of strings, giving names of the
matlab variables to read from the file. The reader will skip any
variable with a name not in this sequence, possibly saving some read
processing.
Returns
-------
mat_dict : dict
dictionary with variable names as keys, and loaded matrices as
values
Notes
-----
v4 (Level 1.0), v6 and v7 to 7.2 matfiles are supported.
You will need an HDF5 python library to read matlab 7.3 format mat
files. Because scipy does not supply one, we do not implement the
HDF5 / 7.3 interface here.
"""
variable_names = kwargs.pop('variable_names', None)
MR = mat_reader_factory(file_name, appendmat, **kwargs)
matfile_dict = MR.get_variables(variable_names)
if mdict is not None:
mdict.update(matfile_dict)
else:
mdict = matfile_dict
if isinstance(file_name, string_types):
MR.mat_stream.close()
return mdict
@docfiller
def savemat(file_name, mdict,
appendmat=True,
format='5',
long_field_names=False,
do_compression=False,
oned_as='row'):
"""
Save a dictionary of names and arrays into a MATLAB-style .mat file.
This saves the array objects in the given dictionary to a MATLAB-
style .mat file.
Parameters
----------
file_name : str or file-like object
Name of the .mat file (.mat extension not needed if ``appendmat ==
True``).
Can also pass open file_like object.
mdict : dict
Dictionary from which to save matfile variables.
appendmat : bool, optional
True (the default) to append the .mat extension to the end of the
given filename, if not already present.
format : {'5', '4'}, string, optional
'5' (the default) for MATLAB 5 and up (to 7.2),
'4' for MATLAB 4 .mat files
long_field_names : bool, optional
False (the default) - maximum field name length in a structure is
31 characters which is the documented maximum length.
True - maximum field name length in a structure is 63 characters
which works for MATLAB 7.6+
do_compression : bool, optional
Whether or not to compress matrices on write. Default is False.
oned_as : {'row', 'column'}, optional
If 'column', write 1-D numpy arrays as column vectors.
If 'row', write 1-D numpy arrays as row vectors.
See also
--------
mio4.MatFile4Writer
mio5.MatFile5Writer
"""
file_is_string = isinstance(file_name, string_types)
if file_is_string:
if appendmat and file_name[-4:] != ".mat":
file_name = file_name + ".mat"
file_stream = open(file_name, 'wb')
else:
if not hasattr(file_name, 'write'):
raise IOError('Writer needs file name or writeable '
'file-like object')
file_stream = file_name
if format == '4':
if long_field_names:
raise ValueError("Long field names are not available for version 4 files")
MW = MatFile4Writer(file_stream, oned_as)
elif format == '5':
MW = MatFile5Writer(file_stream,
do_compression=do_compression,
unicode_strings=True,
long_field_names=long_field_names,
oned_as=oned_as)
else:
raise ValueError("Format should be '4' or '5'")
MW.put_variables(mdict)
if file_is_string:
file_stream.close()
@docfiller
def whosmat(file_name, appendmat=True, **kwargs):
"""
List variables inside a MATLAB file
Parameters
----------
%(file_arg)s
%(append_arg)s
%(load_args)s
%(struct_arg)s
Returns
-------
variables : list of tuples
A list of tuples, where each tuple holds the matrix name (a string),
its shape (tuple of ints), and its data class (a string).
Possible data classes are: int8, uint8, int16, uint16, int32, uint32,
int64, uint64, single, double, cell, struct, object, char, sparse,
function, opaque, logical, unknown.
Notes
-----
v4 (Level 1.0), v6 and v7 to 7.2 matfiles are supported.
You will need an HDF5 python library to read matlab 7.3 format mat
files. Because scipy does not supply one, we do not implement the
HDF5 / 7.3 interface here.
.. versionadded:: 0.12.0
"""
ML = mat_reader_factory(file_name, **kwargs)
variables = ML.list_variables()
if isinstance(file_name, string_types):
ML.mat_stream.close()
return variables
| bsd-3-clause |
Bforartists/scons | scons-local/SCons/Scanner/Prog.py | 7 | 3233 | #
# Copyright (c) 2001 - 2014 The SCons Foundation
#
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# distribute, sublicense, and/or sell copies of the Software, and to
# permit persons to whom the Software is furnished to do so, subject to
# the following conditions:
#
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY
# KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE
# WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
# LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
# WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
#
__revision__ = "src/engine/SCons/Scanner/Prog.py 2014/07/05 09:42:21 garyo"
import SCons.Node
import SCons.Node.FS
import SCons.Scanner
import SCons.Util
# global, set by --debug=findlibs
print_find_libs = None
def ProgramScanner(**kw):
"""Return a prototype Scanner instance for scanning executable
files for static-lib dependencies"""
kw['path_function'] = SCons.Scanner.FindPathDirs('LIBPATH')
ps = SCons.Scanner.Base(scan, "ProgramScanner", **kw)
return ps
def scan(node, env, libpath = ()):
"""
This scanner scans program files for static-library
dependencies. It will search the LIBPATH environment variable
for libraries specified in the LIBS variable, returning any
files it finds as dependencies.
"""
try:
libs = env['LIBS']
except KeyError:
# There are no LIBS in this environment, so just return a null list:
return []
if SCons.Util.is_String(libs):
libs = libs.split()
else:
libs = SCons.Util.flatten(libs)
try:
prefix = env['LIBPREFIXES']
if not SCons.Util.is_List(prefix):
prefix = [ prefix ]
except KeyError:
prefix = [ '' ]
try:
suffix = env['LIBSUFFIXES']
if not SCons.Util.is_List(suffix):
suffix = [ suffix ]
except KeyError:
suffix = [ '' ]
pairs = []
for suf in map(env.subst, suffix):
for pref in map(env.subst, prefix):
pairs.append((pref, suf))
result = []
if callable(libpath):
libpath = libpath()
find_file = SCons.Node.FS.find_file
adjustixes = SCons.Util.adjustixes
for lib in libs:
if SCons.Util.is_String(lib):
lib = env.subst(lib)
for pref, suf in pairs:
l = adjustixes(lib, pref, suf)
l = find_file(l, libpath, verbose=print_find_libs)
if l:
result.append(l)
else:
result.append(lib)
return result
# Local Variables:
# tab-width:4
# indent-tabs-mode:nil
# End:
# vim: set expandtab tabstop=4 shiftwidth=4:
| mit |
jonathanlurie/Tubular | lib/python/gooey/gui/widgets/components.py | 2 | 7463 |
from gooey.gui.widgets import widget_pack
__author__ = 'Chris'
import wx
from gooey.gui import styling
class BaseGuiComponent(object):
def __init__(self, data, widget_pack):
self.data = data
# parent
self.panel = None
# Widgets
self.title = None
self.help_msg = None
# Internal WidgetPack
self.widget_pack = widget_pack
# used to throttle resizing (to avoid widget jiggle)
# TODO: figure out anti-jiggle technology
# self.event_stack = []
def build(self, parent):
return self.do_layout(parent)
def do_layout(self, parent):
self.panel = wx.Panel(parent)
self.title = self.createTitle(self.panel)
self.help_msg = self.createHelpMsgWidget(self.panel)
self.help_msg.SetMinSize((0, -1))
core_widget_set = self.widget_pack.build(self.panel, self.data)
vertical_container = wx.BoxSizer(wx.VERTICAL)
vertical_container.Add(self.title)
vertical_container.AddSpacer(2)
if self.help_msg.GetLabelText():
vertical_container.Add(self.help_msg, 1, wx.EXPAND)
vertical_container.AddSpacer(2)
else:
vertical_container.AddStretchSpacer(1)
vertical_container.Add(core_widget_set, 0, wx.EXPAND)
self.panel.SetSizer(vertical_container)
self.panel.Bind(wx.EVT_SIZE, self.onResize)
return self.panel
def createHelpMsgWidget(self, parent):
label_text = (self.formatExtendedHelpMsg(self.data)
if self.data['nargs']
else self.data['help'])
base_text = wx.StaticText(parent, label=label_text or '')
styling.MakeDarkGrey(base_text)
return base_text
def createTitle(self, parent):
text = wx.StaticText(parent, label=self.data['display_name'].title())
styling.MakeBold(text)
return text
def formatExtendedHelpMsg(self, data):
base_text = data.get('help', '')
nargs = data['nargs']
if isinstance(nargs, int):
return '{base}\n(Note: exactly {nargs} arguments are required)'.format(base=base_text, nargs=nargs)
elif nargs == '+':
return '{base}\n(Note: at least 1 or more arguments are required)'.format(base=base_text)
return base_text
def onResize(self, evt):
# handle internal widgets
self.panel.Freeze()
self._onResize(evt)
# propagate event to child widgets
self.widget_pack.onResize(evt)
evt.Skip()
self.panel.Thaw()
def _onResize(self, evt):
if not self.help_msg:
return
self.panel.Size = evt.GetSize()
container_width, _ = self.panel.Size
text_width, _ = self.help_msg.Size
if text_width != container_width:
self.help_msg.SetLabel(self.help_msg.GetLabelText().replace('\n', ' '))
self.help_msg.Wrap(container_width)
evt.Skip()
def GetValue(self):
return self.widget_pack.getValue()
def _GetWidget(self):
# used only for unittesting
return self.widget_pack.widget
class CheckBox(BaseGuiComponent):
def __init__(self, data, widget_pack=None):
BaseGuiComponent.__init__(self, data, widget_pack)
self.widget = None
# data
self.option_strings = data['commands'][0]
def build(self, parent):
return self.do_layout(parent)
def do_layout(self, parent):
self.panel = wx.Panel(parent)
self.widget = wx.CheckBox(self.panel)
self.title = self.createTitle(self.panel)
self.help_msg = self.createHelpMsgWidget(self.panel)
self.help_msg.SetMinSize((0, -1))
vertical_container = wx.BoxSizer(wx.VERTICAL)
vertical_container.Add(self.title)
horizontal_sizer = wx.BoxSizer(wx.HORIZONTAL)
horizontal_sizer.Add(self.widget, 0, wx.EXPAND | wx.RIGHT, 10)
horizontal_sizer.Add(self.help_msg, 1, wx.EXPAND)
vertical_container.Add(horizontal_sizer, 0, wx.EXPAND)
self.panel.SetSizer(vertical_container)
self.panel.Bind(wx.EVT_SIZE, self.onResize)
return self.panel
def onSetter(self, evt):
self.getValue()
def onResize(self, evt):
msg = self.help_msg
container_width, _ = self.panel.Size
text_width, _ = msg.Size
if text_width != container_width:
msg.SetLabel(msg.GetLabelText().replace('\n', ' '))
msg.Wrap(container_width)
evt.Skip()
def GetValue(self):
return self.option_strings if self.widget.GetValue() else ''
def _GetWidget(self):
return self.widget
class RadioGroup(object):
def __init__(self, data):
self.panel = None
self.data = data
self.radio_buttons = []
self.option_stings = []
self.help_msgs = []
self.btn_names = []
def build(self, parent):
return self.do_layout(parent)
def do_layout(self, parent):
self.panel = wx.Panel(parent)
self.radio_buttons = [wx.RadioButton(self.panel, -1) for _ in self.data]
self.btn_names = [wx.StaticText(self.panel, label=btn_data['display_name'].title()) for btn_data in self.data]
self.help_msgs = [wx.StaticText(self.panel, label=btn_data['help'].title()) for btn_data in self.data]
self.option_stings = [btn_data['commands'] for btn_data in self.data]
# box = wx.StaticBox(self.panel, -1, label=self.data['group_name'])
box = wx.StaticBox(self.panel, -1, label='Set Verbosity Level')
vertical_container = wx.StaticBoxSizer(box, wx.VERTICAL)
for button, name, help in zip(self.radio_buttons, self.btn_names, self.help_msgs):
hbox = wx.BoxSizer(wx.HORIZONTAL)
hbox.Add(button, 0, wx.ALIGN_TOP | wx.ALIGN_LEFT)
hbox.Add(name, 0, wx.LEFT, 10)
vertical_container.Add(hbox, 0, wx.EXPAND)
vertical_container.Add(help, 1, wx.EXPAND | wx.LEFT, 25)
vertical_container.AddSpacer(5)
# self.panel.Bind(wx.EVT_RADIOBUTTON, self.onSetter, button)
self.panel.SetSizer(vertical_container)
self.panel.Bind(wx.EVT_SIZE, self.onResize)
return self.panel
def onSetter(self, evt):
self.getValue()
def onResize(self, evt):
msg = self.help_msgs[0]
container_width, _ = self.panel.Size
text_width, _ = msg.Size
if text_width != container_width:
msg.SetLabel(msg.GetLabelText().replace('\n', ' '))
msg.Wrap(container_width)
evt.Skip()
def GetValue(self):
vals = [button.GetValue() for button in self.radio_buttons]
# print self.option_stings[vals.index(True)]
try:
opts = self.option_stings[vals.index(True)][0]
except:
return ''
def _GetWidget(self):
return self.radio_buttons
FileChooser = lambda data: BaseGuiComponent(data=data, widget_pack=widget_pack.FileChooserPayload())
MultiFileChooser = lambda data: BaseGuiComponent(data=data, widget_pack=widget_pack.MultiFileSaverPayload())
DirChooser = lambda data: BaseGuiComponent(data=data, widget_pack=widget_pack.DirChooserPayload())
FileSaver = lambda data: BaseGuiComponent(data=data, widget_pack=widget_pack.FileSaverPayload())
DateChooser = lambda data: BaseGuiComponent(data=data, widget_pack=widget_pack.DateChooserPayload())
TextField = lambda data: BaseGuiComponent(data=data, widget_pack=widget_pack.TextInputPayload())
Dropdown = lambda data: BaseGuiComponent(data=data, widget_pack=widget_pack.DropdownPayload())
Counter = lambda data: BaseGuiComponent(data=data, widget_pack=widget_pack.CounterPayload())
| mit |
TeamTwisted/external_chromium_org | third_party/markdown/extensions/meta.py | 109 | 4514 | # markdown is released under the BSD license
# Copyright 2007, 2008 The Python Markdown Project (v. 1.7 and later)
# Copyright 2004, 2005, 2006 Yuri Takhteyev (v. 0.2-1.6b)
# Copyright 2004 Manfred Stienstra (the original version)
#
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the <organization> nor the
# names of its contributors may be used to endorse or promote products
# derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE PYTHON MARKDOWN PROJECT ''AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL ANY CONTRIBUTORS TO THE PYTHON MARKDOWN PROJECT
# BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
"""
Meta Data Extension for Python-Markdown
=======================================
This extension adds Meta Data handling to markdown.
Basic Usage:
>>> import markdown
>>> text = '''Title: A Test Doc.
... Author: Waylan Limberg
... John Doe
... Blank_Data:
...
... The body. This is paragraph one.
... '''
>>> md = markdown.Markdown(['meta'])
>>> print md.convert(text)
<p>The body. This is paragraph one.</p>
>>> print md.Meta
{u'blank_data': [u''], u'author': [u'Waylan Limberg', u'John Doe'], u'title': [u'A Test Doc.']}
Make sure text without Meta Data still works (markdown < 1.6b returns a <p>).
>>> text = ' Some Code - not extra lines of meta data.'
>>> md = markdown.Markdown(['meta'])
>>> print md.convert(text)
<pre><code>Some Code - not extra lines of meta data.
</code></pre>
>>> md.Meta
{}
Copyright 2007-2008 [Waylan Limberg](http://achinghead.com).
Project website: <http://packages.python.org/Markdown/meta_data.html>
Contact: markdown@freewisdom.org
License: BSD (see ../LICENSE.md for details)
"""
from __future__ import absolute_import
from __future__ import unicode_literals
from . import Extension
from ..preprocessors import Preprocessor
import re
# Global Vars
META_RE = re.compile(r'^[ ]{0,3}(?P<key>[A-Za-z0-9_-]+):\s*(?P<value>.*)')
META_MORE_RE = re.compile(r'^[ ]{4,}(?P<value>.*)')
class MetaExtension (Extension):
""" Meta-Data extension for Python-Markdown. """
def extendMarkdown(self, md, md_globals):
""" Add MetaPreprocessor to Markdown instance. """
md.preprocessors.add("meta", MetaPreprocessor(md), "_begin")
class MetaPreprocessor(Preprocessor):
""" Get Meta-Data. """
def run(self, lines):
""" Parse Meta-Data and store in Markdown.Meta. """
meta = {}
key = None
while 1:
line = lines.pop(0)
if line.strip() == '':
break # blank line - done
m1 = META_RE.match(line)
if m1:
key = m1.group('key').lower().strip()
value = m1.group('value').strip()
try:
meta[key].append(value)
except KeyError:
meta[key] = [value]
else:
m2 = META_MORE_RE.match(line)
if m2 and key:
# Add another line to existing key
meta[key].append(m2.group('value').strip())
else:
lines.insert(0, line)
break # no meta data - done
self.markdown.Meta = meta
return lines
def makeExtension(configs={}):
return MetaExtension(configs=configs)
| bsd-3-clause |
enigmamarketing/csf-allow-domains | usr/local/csf/bin/csf-allow-domains/dns/rdtypes/ANY/SSHFP.py | 44 | 3129 | # Copyright (C) 2005-2007, 2009-2011 Nominum, Inc.
#
# Permission to use, copy, modify, and distribute this software and its
# documentation for any purpose with or without fee is hereby granted,
# provided that the above copyright notice and this permission notice
# appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND NOMINUM DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL NOMINUM BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT
# OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
import struct
import dns.rdata
import dns.rdatatype
class SSHFP(dns.rdata.Rdata):
"""SSHFP record
@ivar algorithm: the algorithm
@type algorithm: int
@ivar fp_type: the digest type
@type fp_type: int
@ivar fingerprint: the fingerprint
@type fingerprint: string
@see: draft-ietf-secsh-dns-05.txt"""
__slots__ = ['algorithm', 'fp_type', 'fingerprint']
def __init__(self, rdclass, rdtype, algorithm, fp_type,
fingerprint):
super(SSHFP, self).__init__(rdclass, rdtype)
self.algorithm = algorithm
self.fp_type = fp_type
self.fingerprint = fingerprint
def to_text(self, origin=None, relativize=True, **kw):
return '%d %d %s' % (self.algorithm,
self.fp_type,
dns.rdata._hexify(self.fingerprint,
chunksize=128))
def from_text(cls, rdclass, rdtype, tok, origin = None, relativize = True):
algorithm = tok.get_uint8()
fp_type = tok.get_uint8()
chunks = []
while 1:
t = tok.get().unescape()
if t.is_eol_or_eof():
break
if not t.is_identifier():
raise dns.exception.SyntaxError
chunks.append(t.value)
fingerprint = ''.join(chunks)
fingerprint = fingerprint.decode('hex_codec')
return cls(rdclass, rdtype, algorithm, fp_type, fingerprint)
from_text = classmethod(from_text)
def to_wire(self, file, compress = None, origin = None):
header = struct.pack("!BB", self.algorithm, self.fp_type)
file.write(header)
file.write(self.fingerprint)
def from_wire(cls, rdclass, rdtype, wire, current, rdlen, origin = None):
header = struct.unpack("!BB", wire[current : current + 2])
current += 2
rdlen -= 2
fingerprint = wire[current : current + rdlen].unwrap()
return cls(rdclass, rdtype, header[0], header[1], fingerprint)
from_wire = classmethod(from_wire)
def _cmp(self, other):
hs = struct.pack("!BB", self.algorithm, self.fp_type)
ho = struct.pack("!BB", other.algorithm, other.fp_type)
v = cmp(hs, ho)
if v == 0:
v = cmp(self.fingerprint, other.fingerprint)
return v
| mit |
alertedsnake/pycrust | pycrust/__init__.py | 1 | 5061 | """
Pycrust
A collection of CherryPy extensions
See also the following submodules:
pycrust.auth
pycrust.saplugin
pycrust.satool
pycrust.tools
"""
__author__ = 'Michael Stella <pycrust@thismetalsky.org>'
__version__ = '1.0.0'
import inspect, logging, os, sys
import cherrypy
import codecs
class BaseHandler(object):
"""A Base class for web handler objects."""
_cp_config = {}
def log(self, msg, severity=logging.INFO, context=None):
"""Logs to the Cherrypy error log but in a much more pretty way,
with the handler name and line number
"""
if not context:
context = inspect.getouterframes(inspect.currentframe())[1]
cherrypy.log.error(msg=msg.strip().replace('\n', '; '), severity=severity,
context='HANDLER ({}:{}:{})'.format(
self.__class__.__name__, context[3], context[2]))
def log_debug(self, msg):
return self.log(msg, severity=logging.DEBUG,
context=inspect.getouterframes(inspect.currentframe())[1])
def log_info(self, msg):
return self.log(msg, severity=logging.INFO,
context=inspect.getouterframes(inspect.currentframe())[1])
def log_warn(self, msg):
return self.log(msg, severity=logging.WARN,
context=inspect.getouterframes(inspect.currentframe())[1])
def log_error(self, msg):
return self.log(msg, severity=logging.ERROR,
context=inspect.getouterframes(inspect.currentframe())[1])
def log_fatal(self, msg):
return self.log(msg, severity=logging.FATAL,
context=inspect.getouterframes(inspect.currentframe())[1])
def url(*args, **kwargs):
"""Find the given URL using routes. Throws an exception
if you're not using routes.
"""
import routes
if 'absolute' in kwargs and kwargs['absolute']:
del(kwargs['absolute'])
return cherrypy.url(routes.url_for(*args, **kwargs))
return routes.url_for(*args, **kwargs)
def dump_request(*args, **kwargs):
"""Dumps the request out to a file in /tmp, for debugging
Enable by setting, in your config file:
tools.debug_request.on = True
"""
with codecs.open('/tmp/request.%s.txt' % cherrypy.request.method, 'w', encoding='utf-8') as f:
f.write(cherrypy.request.request_line)
f.write("\n")
# write headers
for (k,v) in cherrypy.request.headers.items():
f.write('%s: %s\n' % (k,v))
f.write("\n")
# dump out the POST data when submitted
if ('Content-Type' in cherrypy.request.headers and
'application/x-www-form-urlencoded' in cherrypy.request.headers['Content-Type']):
for (k,v) in cherrypy.request.params.items():
f.write('%s: %s\n' % (k,v))
# otherwise, dump the body
elif cherrypy.request.body:
with cherrypy.request.body.make_file() as fin:
f.write(str(fin.read()))
def dump_response(*args, **kwargs):
"""Dumps the response out to a file in /tmp, for debugging.
Enable by setting, in your config file:
tools.debug_response.on = True
"""
# when a 500 error is displayed, cherrypy handles this
# differently, and we don't really need to dump it out
if not cherrypy.response.status:
return
status = 200
if isinstance(cherrypy.response.status, int):
status = cherrypy.response.status
elif isinstance(cherrypy.response.status, str):
status = int(cherrypy.response.status.split(' ', 1)[0])
with codecs.open('/tmp/response.%d.txt' % status, 'w', encoding='utf-8') as f:
f.write("HTTP/1.1 %s\n" % cherrypy.response.status)
for (k,v) in cherrypy.response.headers.items():
f.write('%s: %s\n' % (k,v))
f.write("Status: %d\n\n" % status)
if cherrypy.response.body:
if sys.version < '3':
f.write(str(cherrypy.response.collapse_body().decode()))
else:
f.write(str(cherrypy.response.collapse_body()))
cherrypy.tools.debug_request = cherrypy.Tool('before_handler', dump_request, priority=1)
cherrypy.tools.debug_response = cherrypy.Tool('on_end_resource', dump_response)
def load_class(fullname):
"""Loads a class given the full dotted class name"""
assert fullname is not None, "fullname must not be None"
modulename, classname = fullname.rsplit('.', 1)
try:
module = __import__(modulename, globals(), locals(), [classname])
except ImportError as e:
cherrypy.log("Error loading module {}".format(modulename), context='ENGINE', severity=loging.ERROR)
raise
try:
cls = getattr(module, classname)
except AttributeError as e:
cherrypy.log("Error loading class {} from module {}".format(classname, modulename),
context='ENGINE', severity=logging.ERROR)
return None
return cls
| mit |
kmkolasinski/Quantulaba | plots/plot_lattice.py | 2 | 1492 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
import csv
from matplotlib.collections import LineCollection
file = "lattice.dat"
#ax = plt.gca(projection='3d')
pscale=1.0
lscale=10.0
fig, ax = plt. subplots()
ax.set_aspect('equal')
desired=[1,2]
with open(file, 'r') as fin:
reader=csv.reader(fin)
result=[[(s) for s in row] for i,row in enumerate(reader) if i in desired]
minCorner = map(float,result[0][0].split())
maxCorner = map(float,result[1][0].split())
xWidth = abs(minCorner[0]-maxCorner[0])
yWidth = abs(minCorner[1]-maxCorner[1])
zWidth = abs(minCorner[2]-maxCorner[2])
ax.scatter(minCorner[0],minCorner[1],s=0)
ax.scatter(maxCorner[0],maxCorner[1],s=0)
ax.margins(0.1)
data = np.loadtxt(file,skiprows=4)
no_lines = np.size(data[:,0])
wlist = []
lines = []
for i in range(no_lines):
lines.append([ (data[i,0],data[i,1]) , (data[i,3],data[i,4]) ])
wlist.extend([data[i,6]*lscale])
lc = LineCollection(lines, linewidths=wlist,colors='black',lw=1.0)
ax.add_collection(lc)
wlist = []
points = []
for i in range(no_lines):
if(data[i,6] > 1.0):
points.append([data[i,0],data[i,1] ])
wlist.extend([data[i,6]*pscale])
points = np.array(points)
wlist = np.array(wlist)
if(np.size(points) > 0):
ax.scatter(points[:,0],points[:,1], cmap='PuBu', c=wlist , s=50 , edgecolors='k' , zorder=2 )
plt.savefig("lattice.pdf") | mit |
onitake/ansible | test/units/modules/network/f5/test_bigip_firewall_rule.py | 21 | 4718 | # -*- coding: utf-8 -*-
#
# Copyright: (c) 2018, F5 Networks Inc.
# GNU General Public License v3.0 (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import os
import json
import pytest
import sys
if sys.version_info < (2, 7):
pytestmark = pytest.mark.skip("F5 Ansible modules require Python >= 2.7")
from ansible.module_utils.basic import AnsibleModule
try:
from library.modules.bigip_firewall_rule import ApiParameters
from library.modules.bigip_firewall_rule import ModuleParameters
from library.modules.bigip_firewall_rule import ModuleManager
from library.modules.bigip_firewall_rule import ArgumentSpec
# In Ansible 2.8, Ansible changed import paths.
from test.units.compat import unittest
from test.units.compat.mock import Mock
from test.units.compat.mock import patch
from test.units.modules.utils import set_module_args
except ImportError:
from ansible.modules.network.f5.bigip_firewall_rule import ApiParameters
from ansible.modules.network.f5.bigip_firewall_rule import ModuleParameters
from ansible.modules.network.f5.bigip_firewall_rule import ModuleManager
from ansible.modules.network.f5.bigip_firewall_rule import ArgumentSpec
# Ansible 2.8 imports
from units.compat import unittest
from units.compat.mock import Mock
from units.compat.mock import patch
from units.modules.utils import set_module_args
fixture_path = os.path.join(os.path.dirname(__file__), 'fixtures')
fixture_data = {}
def load_fixture(name):
path = os.path.join(fixture_path, name)
if path in fixture_data:
return fixture_data[path]
with open(path) as f:
data = f.read()
try:
data = json.loads(data)
except Exception:
pass
fixture_data[path] = data
return data
class TestParameters(unittest.TestCase):
def test_module_parameters(self):
args = dict(
name='foo',
parent_policy='policy1',
protocol='tcp',
source=[
dict(address='1.2.3.4'),
dict(address='::1'),
dict(address_list='foo-list1'),
dict(address_range='1.1.1.1-2.2.2.2.'),
dict(vlan='vlan1'),
dict(country='US'),
dict(port='22'),
dict(port_list='port-list1'),
dict(port_range='80-443'),
],
destination=[
dict(address='1.2.3.4'),
dict(address='::1'),
dict(address_list='foo-list1'),
dict(address_range='1.1.1.1-2.2.2.2.'),
dict(country='US'),
dict(port='22'),
dict(port_list='port-list1'),
dict(port_range='80-443'),
],
irule='irule1',
action='accept',
logging=True,
)
p = ModuleParameters(params=args)
assert p.irule == '/Common/irule1'
assert p.action == 'accept'
assert p.logging is True
class TestManager(unittest.TestCase):
def setUp(self):
self.spec = ArgumentSpec()
def test_create_monitor(self, *args):
set_module_args(dict(
name='foo',
parent_policy='policy1',
protocol='tcp',
source=[
dict(address='1.2.3.4'),
dict(address='::1'),
dict(address_list='foo-list1'),
dict(address_range='1.1.1.1-2.2.2.2.'),
dict(vlan='vlan1'),
dict(country='US'),
dict(port='22'),
dict(port_list='port-list1'),
dict(port_range='80-443'),
],
destination=[
dict(address='1.2.3.4'),
dict(address='::1'),
dict(address_list='foo-list1'),
dict(address_range='1.1.1.1-2.2.2.2.'),
dict(country='US'),
dict(port='22'),
dict(port_list='port-list1'),
dict(port_range='80-443'),
],
irule='irule1',
action='accept',
logging='yes',
))
module = AnsibleModule(
argument_spec=self.spec.argument_spec,
supports_check_mode=self.spec.supports_check_mode
)
# Override methods in the specific type of manager
mm = ModuleManager(module=module)
mm.exists = Mock(side_effect=[False, True])
mm.create_on_device = Mock(return_value=True)
results = mm.exec_module()
assert results['changed'] is True
| gpl-3.0 |
Sumith1896/sympy | sympy/physics/quantum/matrixcache.py | 124 | 3519 | """A cache for storing small matrices in multiple formats."""
from __future__ import print_function, division
from sympy import Matrix, I, Pow, Rational, exp, pi
from sympy.physics.quantum.matrixutils import (
to_sympy, to_numpy, to_scipy_sparse
)
class MatrixCache(object):
"""A cache for small matrices in different formats.
This class takes small matrices in the standard ``sympy.Matrix`` format,
and then converts these to both ``numpy.matrix`` and
``scipy.sparse.csr_matrix`` matrices. These matrices are then stored for
future recovery.
"""
def __init__(self, dtype='complex'):
self._cache = {}
self.dtype = dtype
def cache_matrix(self, name, m):
"""Cache a matrix by its name.
Parameters
----------
name : str
A descriptive name for the matrix, like "identity2".
m : list of lists
The raw matrix data as a sympy Matrix.
"""
try:
self._sympy_matrix(name, m)
except ImportError:
pass
try:
self._numpy_matrix(name, m)
except ImportError:
pass
try:
self._scipy_sparse_matrix(name, m)
except ImportError:
pass
def get_matrix(self, name, format):
"""Get a cached matrix by name and format.
Parameters
----------
name : str
A descriptive name for the matrix, like "identity2".
format : str
The format desired ('sympy', 'numpy', 'scipy.sparse')
"""
m = self._cache.get((name, format))
if m is not None:
return m
raise NotImplementedError(
'Matrix with name %s and format %s is not available.' %
(name, format)
)
def _store_matrix(self, name, format, m):
self._cache[(name, format)] = m
def _sympy_matrix(self, name, m):
self._store_matrix(name, 'sympy', to_sympy(m))
def _numpy_matrix(self, name, m):
m = to_numpy(m, dtype=self.dtype)
self._store_matrix(name, 'numpy', m)
def _scipy_sparse_matrix(self, name, m):
# TODO: explore different sparse formats. But sparse.kron will use
# coo in most cases, so we use that here.
m = to_scipy_sparse(m, dtype=self.dtype)
self._store_matrix(name, 'scipy.sparse', m)
sqrt2_inv = Pow(2, Rational(-1, 2), evaluate=False)
# Save the common matrices that we will need
matrix_cache = MatrixCache()
matrix_cache.cache_matrix('eye2', Matrix([[1, 0], [0, 1]]))
matrix_cache.cache_matrix('op11', Matrix([[0, 0], [0, 1]])) # |1><1|
matrix_cache.cache_matrix('op00', Matrix([[1, 0], [0, 0]])) # |0><0|
matrix_cache.cache_matrix('op10', Matrix([[0, 0], [1, 0]])) # |1><0|
matrix_cache.cache_matrix('op01', Matrix([[0, 1], [0, 0]])) # |0><1|
matrix_cache.cache_matrix('X', Matrix([[0, 1], [1, 0]]))
matrix_cache.cache_matrix('Y', Matrix([[0, -I], [I, 0]]))
matrix_cache.cache_matrix('Z', Matrix([[1, 0], [0, -1]]))
matrix_cache.cache_matrix('S', Matrix([[1, 0], [0, I]]))
matrix_cache.cache_matrix('T', Matrix([[1, 0], [0, exp(I*pi/4)]]))
matrix_cache.cache_matrix('H', sqrt2_inv*Matrix([[1, 1], [1, -1]]))
matrix_cache.cache_matrix('Hsqrt2', Matrix([[1, 1], [1, -1]]))
matrix_cache.cache_matrix(
'SWAP', Matrix([[1, 0, 0, 0], [0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 1]]))
matrix_cache.cache_matrix('ZX', sqrt2_inv*Matrix([[1, 1], [1, -1]]))
matrix_cache.cache_matrix('ZY', Matrix([[I, 0], [0, -I]]))
| bsd-3-clause |
WarrenWeckesser/numpy | numpy/distutils/msvccompiler.py | 17 | 1928 | import os
from distutils.msvccompiler import MSVCCompiler as _MSVCCompiler
from .system_info import platform_bits
def _merge(old, new):
"""Concatenate two environment paths avoiding repeats.
Here `old` is the environment string before the base class initialize
function is called and `new` is the string after the call. The new string
will be a fixed string if it is not obtained from the current environment,
or the same as the old string if obtained from the same environment. The aim
here is not to append the new string if it is already contained in the old
string so as to limit the growth of the environment string.
Parameters
----------
old : string
Previous environment string.
new : string
New environment string.
Returns
-------
ret : string
Updated environment string.
"""
if new in old:
return old
if not old:
return new
# Neither new nor old is empty. Give old priority.
return ';'.join([old, new])
class MSVCCompiler(_MSVCCompiler):
def __init__(self, verbose=0, dry_run=0, force=0):
_MSVCCompiler.__init__(self, verbose, dry_run, force)
def initialize(self):
# The 'lib' and 'include' variables may be overwritten
# by MSVCCompiler.initialize, so save them for later merge.
environ_lib = os.getenv('lib', '')
environ_include = os.getenv('include', '')
_MSVCCompiler.initialize(self)
# Merge current and previous values of 'lib' and 'include'
os.environ['lib'] = _merge(environ_lib, os.environ['lib'])
os.environ['include'] = _merge(environ_include, os.environ['include'])
# msvc9 building for 32 bits requires SSE2 to work around a
# compiler bug.
if platform_bits == 32:
self.compile_options += ['/arch:SSE2']
self.compile_options_debug += ['/arch:SSE2']
| bsd-3-clause |
Serag8/Bachelor | google_appengine/google/appengine/dist/py_imp.py | 6 | 3739 | #!/usr/bin/env python
#
# Copyright 2007 Google Inc.
#
# 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.
#
"""Stub replacement for Python's imp module."""
import os
import sys
PY_SOURCE, PY_COMPILED, C_EXTENSION = 1, 2, 3
PKG_DIRECTORY, C_BUILTIN, PY_FROZEN = 5, 6, 7
def get_magic():
"""Return the magic string used to recognize byte-compiled code files."""
return '\xb3\xf2\r\n'
_PY_SOURCE_SUFFIX = ('.py', 'U', PY_SOURCE)
_PKG_DIRECTORY_SUFFIX = ('', '', PKG_DIRECTORY)
def get_suffixes():
"""Return a list that describes the files that find_module() looks for."""
return [_PY_SOURCE_SUFFIX]
def find_module(name, path=None):
"""Try to find the named module on the given search path or sys.path."""
if path == None:
path = sys.path
for directory in path:
filename = os.path.join(directory, '%s.py' % name)
if os.path.exists(filename):
return open(filename, 'U'), filename, _PY_SOURCE_SUFFIX
dirname = os.path.join(directory, name)
filename = os.path.join(dirname, '__init__.py')
if os.path.exists(filename):
return None, dirname, _PKG_DIRECTORY_SUFFIX
raise ImportError('No module named %s' % name)
def load_module(name, file_, pathname, description):
"""Load or reload the specified module.
Please note that this function has only rudimentary supported on App Engine:
Only loading packages is supported.
"""
suffix, mode, type_ = description
if type_ == PKG_DIRECTORY:
if name in sys.modules:
mod = sys.modules[name]
else:
mod = new_module(name)
sys.modules[name] = mod
filename = os.path.join(pathname, '__init__.py')
mod.__file__ = filename
execfile(filename, mod.__dict__, mod.__dict__)
return mod
else:
raise NotImplementedError('Only importing packages is supported on '
'App Engine')
def new_module(name):
"""Return a new empty module object."""
return type(sys)(name)
def lock_held():
"""Return False since threading is not supported."""
return False
def acquire_lock():
"""Acquiring the lock is a no-op since no threading is supported."""
pass
def release_lock():
"""There is no lock to release since acquiring is a no-op when there is no
threading."""
pass
def init_builtin(name):
raise NotImplementedError('This function is not supported on App Engine.')
def init_frozen(name):
raise NotImplementedError('This function is not supported on App Engine.')
def is_builtin(name):
return name in sys.builtin_module_names
def is_frozen(name):
return False
def load_compiled(name, pathname, file_=None):
raise NotImplementedError('This function is not supported on App Engine.')
def load_dynamic(name, pathname, file_=None):
raise NotImplementedError('This function is not supported on App Engine.')
def load_source(name, pathname, file_=None):
raise NotImplementedError('This function is not supported on App Engine.')
class NullImporter(object):
"""Null importer object"""
def __init__(self, path_string):
if not path_string:
raise ImportError("empty pathname")
elif os.path.isdir(path_string):
raise ImportError("existing directory")
def find_module(self, fullname):
return None
| mit |
PauloSantos13/android | user_manual/conf.py | 2 | 9666 | # -*- coding: utf-8 -*-
#
# ownCloud Documentation documentation build configuration file, created by
# sphinx-quickstart on Mon Oct 22 23:16:40 2012.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import sys, os, inspect
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#sys.path.insert(0, os.path.abspath('.'))
#path to this script
scriptpath = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
# -- General configuration -----------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = ['sphinx.ext.todo']
# Add any paths that contain templates here, relative to this directory.
templates_path = [scriptpath+'/ocdoc/_shared_assets/templates']
# The suffix of source filenames.
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = 'index'
# The short X.Y.Z version.
version = '2.0.0'
# The full version, including alpha/beta/rc tags.
release = '2.0.0'
# General information about the project.
project = u'ownCloud Android App %s Manual' % (version)
copyright = u'2013-2016, The ownCloud developers'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = ['_build','scripts/*', 'ocdoc/*']
# The reST default role (used for this markup: `text`) to use for all documents.
#default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
#add_function_parentheses = True
2
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
#add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
#show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# -- Options for HTML output ---------------------------------------------------
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
#html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
html_theme_path = [scriptpath+'/ocdoc/_shared_assets/themes']
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#html_theme = 'bootstrap'
html_theme = 'default'
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
#html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
html_short_title = "Android App Manual"
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
#html_logo = None
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = [scriptpath+'/ocdoc/_shared_assets/static']
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
#html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
#html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
#html_additional_pages = {}
# If false, no module index is generated.
#html_domain_indices = True
# If false, no index is generated.
#html_use_index = True
# If true, the index is split into individual pages for each letter.
#html_split_index = False
# If true, links to the reST sources are added to the pages.
#html_show_sourcelink = True
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
html_show_sphinx = False
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
#html_show_copyright = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
#html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
#html_file_suffix = None
# Output file base name for HTML help builder.
htmlhelp_basename = 'ownCloudAndroidAppManual'
# -- Options for LaTeX output --------------------------------------------------
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
#'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
#'preamble': '',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title, author, documentclass [howto/manual]).
latex_documents = [
('index', 'ownCloudAndroidAppManual.tex', u'ownCloud Android App Manual',
u'The ownCloud developers', 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
# the title page.
#latex_logo = None
# For "manual" documents, if this is true, then toplevel headings are parts,
# not chapters.
#latex_use_parts = False
# If true, show page references after internal links.
#latex_show_pagerefs = False
# If true, show URL addresses after external links.
#latex_show_urls = False
# Documents to append as an appendix to all manuals.
#latex_appendices = []
# If false, no module index is generated.
#latex_domain_indices = True
# -- Options for manual page output --------------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
('owncloud.1', 'owncloud', u'Android synchronisation and file management utility.',
[u'The ownCloud developers'], 1),
('owncloudcmd.1', 'owncloudcmd', u'ownCloud Android app.',
[u'The ownCloud developers'], 1),
]
# If true, show URL addresses after external links.
man_show_urls = True
# -- Options for Texinfo output ------------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
('index', 'ownCloudClientManual', u'ownCloud Android App Manual',
u'The ownCloud developers', 'ownCloud', 'The ownCloud Android App Manual.',
'Miscellaneous'),
]
# Documents to append as an appendix to all manuals.
#texinfo_appendices = []
# If false, no module index is generated.
#texinfo_domain_indices = True
# How to display URL addresses: 'footnote', 'no', or 'inline'.
#texinfo_show_urls = 'footnote'
# -- Options for Epub output ---------------------------------------------------
# Bibliographic Dublin Core info.
epub_title = u'ownCloud Android App Manual'
epub_author = u'The ownCloud developers'
epub_publisher = u'The ownCloud developers'
epub_copyright = u'2013-2015, The ownCloud developers'
# The language of the text. It defaults to the language option
# or en if the language is not set.
#epub_language = ''
# The scheme of the identifier. Typical schemes are ISBN or URL.
#epub_scheme = ''
# The unique identifier of the text. This can be a ISBN number
# or the project homepage.
#epub_identifier = ''
# A unique identification for the text.
#epub_uid = ''
# A tuple containing the cover image and cover page html template filenames.
#epub_cover = ()
# HTML files that should be inserted before the pages created by sphinx.
# The format is a list of tuples containing the path and title.
#epub_pre_files = []
# HTML files shat should be inserted after the pages created by sphinx.
# The format is a list of tuples containing the path and title.
#epub_post_files = []
# A list of files that should not be packed into the epub file.
#epub_exclude_files = []
# The depth of the table of contents in toc.ncx.
#epub_tocdepth = 3
# Allow duplicate toc entries.
#epub_tocdup = True
# Include todos?
todo_include_todos = True
| gpl-2.0 |
ayseyo/oclapi | django-nonrel/ocl/oclapi/settings/common.py | 1 | 10523 | import os
from configurations import Configuration
BASE_DIR = os.path.dirname(os.path.dirname(__file__))
class Common(Configuration):
DEBUG = True
TEMPLATE_DEBUG = DEBUG
ADMINS = (
('Jon Payne', 'paynejd@gmail.com'),
('PK Shiu', 'pk@pkshiu.com'),
)
MANAGERS = ADMINS
DEFAULT_FROM_EMAIL = 'no-reply@openconceptlab.org'
EMAIL_HOST = 'openconceptlab.org'
EMAIL_SUBJECT_PREFIX = '[openconceptlab.org] '
# Hosts/domain names that are valid for this site; required if DEBUG is False
# See https://docs.djangoproject.com/en/1.3/ref/settings/#allowed-hosts
ALLOWED_HOSTS = []
# Local time zone for this installation. Choices can be found here:
# http://en.wikipedia.org/wiki/List_of_tz_zones_by_name
# although not all choices may be available on all operating systems.
# On Unix systems, a value of None will cause Django to use the same
# timezone as the operating system.
# If running in a Windows environment this must be set to the same as your
# system time zone.
TIME_ZONE = 'America/New_York'
# Language code for this installation. All choices can be found here:
# http://www.i18nguy.com/unicode/language-identifiers.html
LANGUAGE_CODE = 'en-us'
# If you set this to False, Django will make some optimizations so as not
# to load the internationalization machinery.
USE_I18N = True
# If you set this to False, Django will not format dates, numbers and
# calendars according to the current locale
USE_L10N = True
DEFAULT_LOCALE = 'en'
# Absolute filesystem path to the directory that will hold user-uploaded files.
# Example: "/home/media/media.lawrence.com/media/"
MEDIA_ROOT = ''
# URL that handles the media served from MEDIA_ROOT. Make sure to use a
# trailing slash.
# Examples: "http://media.lawrence.com/media/", "http://example.com/media/"
MEDIA_URL = ''
# Absolute path to the directory static files should be collected to.
# Don't put anything in this directory yourself; store your static files
# in apps' "static/" subdirectories and in STATICFILES_DIRS.
# Example: "/home/media/media.lawrence.com/static/"
STATIC_ROOT = ''
# In the deployment environment, comment out the above line, and uncomment the one below
#STATIC_ROOT = '/usr/local/wsgi/static/'
# URL prefix for static files.
# Example: "http://media.lawrence.com/static/"
STATIC_URL = '/static/'
# URL prefix for admin static files -- CSS, JavaScript and images.
# Make sure to use a trailing slash.
# Examples: "http://foo.com/static/admin/", "/static/admin/".
ADMIN_MEDIA_PREFIX = '/static/admin/'
# Additional locations of static files
STATICFILES_DIRS = (
# Put strings here, like "/home/html/static" or "C:/www/django/static".
# Always use forward slashes, even on Windows.
# Don't forget to use absolute paths, not relative paths.
)
# List of finder classes that know how to find static files in
# various locations.
STATICFILES_FINDERS = (
'django.contrib.staticfiles.finders.FileSystemFinder',
'django.contrib.staticfiles.finders.AppDirectoriesFinder',
# 'django.contrib.staticfiles.finders.DefaultStorageFinder',
)
# Make this unique, and don't share it with anybody.
SECRET_KEY = '+p+lx2*o3ywq+z)%f7929b6)93)^mcc9-0eu9ynq77gc+pe=ck'
# List of callables that know how to import templates from various sources.
TEMPLATE_LOADERS = (
'django.template.loaders.filesystem.Loader',
'django.template.loaders.app_directories.Loader',
# 'django.template.loaders.eggs.Loader',
)
MIDDLEWARE_CLASSES = (
'django.middleware.common.CommonMiddleware',
'corsheaders.middleware.CorsMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'oclapi.middlewares.RequestLogMiddleware',
)
ROOT_URLCONF = 'urls'
TEMPLATE_DIRS = (
# Put strings here, like "/home/html/django_templates" or "C:/www/django/templates".
# Always use forward slashes, even on Windows.
# Don't forget to use absolute paths, not relative paths.
)
INSTALLED_APPS = (
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
# Uncomment the next line to enable the admin:
'django.contrib.admin',
'corsheaders',
# Uncomment the next line to enable admin documentation:
# 'django.contrib.admindocs',
# Core OCL app
'oclapi',
# Third-party apps:
'djangotoolbox',
'django_mongodb_engine',
'rest_framework',
'rest_framework.authtoken',
'haystack',
# Project-specific apps:
'users',
'orgs',
'sources',
'concepts',
'collection',
'mappings',
'integration_tests',
)
# Django Rest Framework configuration
REST_FRAMEWORK = {
# Default to token-based authentication; fall back on session-based
# A user gets a unique token upon account creation (residing in the authtoken_token data store).
# To pass an authentication token along with your request, include the following header:
# Authorization: Token [TOKEN_VALUE]
# e.g.
# Authorization: Token ad73f481096c3b6202bce395820199
'DEFAULT_AUTHENTICATION_CLASSES': (
'rest_framework.authentication.TokenAuthentication',
'rest_framework.authentication.SessionAuthentication',
),
'DEFAULT_RENDERER_CLASSES': (
'rest_framework.renderers.JSONRenderer',
'rest_framework.renderers.BrowsableAPIRenderer',
'oclapi.renderers.ZippedJSONRenderer',
),
'DEFAULT_CONTENT_NEGOTIATION_CLASS': 'oclapi.negotiation.OptionallyCompressContentNegotiation',
# Use hyperlinked styles by default.
# Only used if the `serializer_class` attribute is not set on a view.
'DEFAULT_MODEL_SERIALIZER_CLASS':
'rest_framework.serializers.HyperlinkedModelSerializer',
'DEFAULT_PAGINATION_SERIALIZER_CLASS':
'oclapi.serializers.HeaderPaginationSerializer',
# Use Django's standard `django.contrib.auth` permissions,
# or allow read-only access for unauthenticated users.
'DEFAULT_PERMISSION_CLASSES': [
#'rest_framework.permissions.DjangoModelPermissionsOrAnonReadOnly',
'rest_framework.permissions.IsAuthenticated',
],
'PAGINATE_BY': 10, # Default to 10
'PAGINATE_BY_PARAM': 'limit', # Allow client to override, using `?limit=xxx`.
'MAX_PAGINATE_BY': 100 # Maximum limit allowed when using `?limit=xxx`.
}
HAYSTACK_CONNECTIONS = {
'default': {
'ENGINE': 'oclapi.search_backends.OCLSolrEngine',
'URL': 'http://solr.openconceptlab.org:8983/solr/collection1'
# ...or for multicore...
# 'URL': 'http://127.0.0.1:8983/solr/mysite',
},
}
DATABASES = {
'default': {
'ENGINE': 'django_mongodb_engine',
'HOST': 'mongo.openconceptlab.org',
'NAME': 'ocl',
}
}
BROKER_URL = 'redis://redis.openconceptlab.org:6379/0'
CORS_ORIGIN_ALLOW_ALL = True
CORS_ALLOW_METHODS = (
'GET',
)
# CORS_ORIGIN_WHITELIST = (
# 'google.com',
# 'hostname.example.com',
# )
# Haystack processor determines when/how updates to mongo are indexed by Solr
# RealtimeSignalProcessor will update the index for every mongo update, sometimes at
# the cost of performance. BaseSignalProcessor does not update the index at all, which
# means the index must be updated manually (e.g. using the haystack update_index command).
HAYSTACK_SIGNAL_PROCESSOR = 'haystack.signals.RealtimeSignalProcessor'
HAYSTACK_ITERATOR_LOAD_PER_QUERY = 25
HAYSTACK_SEARCH_RESULTS_PER_PAGE = 25
# Celery settings
CELERY_RESULT_BACKEND = 'redis://redis.openconceptlab.org:6379/0'
# Set these in your postactivate hook if you use virtualenvwrapper
AWS_ACCESS_KEY_ID=os.environ.get('AWS_ACCESS_KEY_ID', '')
AWS_SECRET_ACCESS_KEY=os.environ.get('AWS_SECRET_ACCESS_KEY', '')
AWS_STORAGE_BUCKET_NAME=os.environ.get('AWS_STORAGE_BUCKET_NAME', '')
# Model that stores auxiliary user profile attributes.
# A user must have a profile in order to access the system.
# (A profile is created automatically for any user created using the 'POST /users' endpoint.)
AUTH_PROFILE_MODULE = 'users.UserProfile'
LOGGING = {
'version': 1,
'disable_existing_loggers': False,
'filters': {
'require_debug_false': {
'()': 'django.utils.log.RequireDebugFalse'
}
},
'formatters': {
'normal': {
'format': "[%(asctime)s] %(levelname)-8s: %(message)s",
'datefmt': "%Y/%m/%d %H:%M:%S"
},
},
'handlers': {
'mail_admins': {
'level': 'ERROR',
'filters': ['require_debug_false'],
'class': 'django.utils.log.AdminEmailHandler'
},
'null': {
'class': 'django.utils.log.NullHandler',
},
'console': {
'class': 'logging.StreamHandler',
'formatter': 'normal',
},
'logfile': {
'level': 'DEBUG',
'class': 'logging.handlers.TimedRotatingFileHandler',
'when': 'midnight',
'filename': os.path.join(BASE_DIR, 'ocl_api.log'),
'formatter': 'normal',
},
},
'loggers': {
'django.request': {
'handlers': ['mail_admins'],
'level': 'ERROR',
'propagate': True,
},
'oclapi': {
'handlers': ['console', 'logfile'],
'level': 'DEBUG',
},
'request_logger': {
'handlers': ['console', 'logfile'],
'level': 'INFO',
},
}
}
| mpl-2.0 |
xeddmc/PyBitmessage | src/bitmessageqt/connect.py | 19 | 2951 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'connect.ui'
#
# Created: Wed Jul 24 12:42:01 2013
# by: PyQt4 UI code generator 4.10
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore, QtGui
try:
_fromUtf8 = QtCore.QString.fromUtf8
except AttributeError:
def _fromUtf8(s):
return s
try:
_encoding = QtGui.QApplication.UnicodeUTF8
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig, _encoding)
except AttributeError:
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig)
class Ui_connectDialog(object):
def setupUi(self, connectDialog):
connectDialog.setObjectName(_fromUtf8("connectDialog"))
connectDialog.resize(400, 124)
self.gridLayout = QtGui.QGridLayout(connectDialog)
self.gridLayout.setObjectName(_fromUtf8("gridLayout"))
self.label = QtGui.QLabel(connectDialog)
self.label.setObjectName(_fromUtf8("label"))
self.gridLayout.addWidget(self.label, 0, 0, 1, 2)
self.radioButtonConnectNow = QtGui.QRadioButton(connectDialog)
self.radioButtonConnectNow.setChecked(True)
self.radioButtonConnectNow.setObjectName(_fromUtf8("radioButtonConnectNow"))
self.gridLayout.addWidget(self.radioButtonConnectNow, 1, 0, 1, 2)
self.radioButtonConfigureNetwork = QtGui.QRadioButton(connectDialog)
self.radioButtonConfigureNetwork.setObjectName(_fromUtf8("radioButtonConfigureNetwork"))
self.gridLayout.addWidget(self.radioButtonConfigureNetwork, 2, 0, 1, 2)
spacerItem = QtGui.QSpacerItem(185, 24, QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Minimum)
self.gridLayout.addItem(spacerItem, 3, 0, 1, 1)
self.buttonBox = QtGui.QDialogButtonBox(connectDialog)
self.buttonBox.setOrientation(QtCore.Qt.Horizontal)
self.buttonBox.setStandardButtons(QtGui.QDialogButtonBox.Ok)
self.buttonBox.setObjectName(_fromUtf8("buttonBox"))
self.gridLayout.addWidget(self.buttonBox, 3, 1, 1, 1)
self.retranslateUi(connectDialog)
QtCore.QObject.connect(self.buttonBox, QtCore.SIGNAL(_fromUtf8("accepted()")), connectDialog.accept)
QtCore.QObject.connect(self.buttonBox, QtCore.SIGNAL(_fromUtf8("rejected()")), connectDialog.reject)
QtCore.QMetaObject.connectSlotsByName(connectDialog)
def retranslateUi(self, connectDialog):
connectDialog.setWindowTitle(_translate("connectDialog", "Bitmessage", None))
self.label.setText(_translate("connectDialog", "Bitmessage won\'t connect to anyone until you let it. ", None))
self.radioButtonConnectNow.setText(_translate("connectDialog", "Connect now", None))
self.radioButtonConfigureNetwork.setText(_translate("connectDialog", "Let me configure special network settings first", None))
| mit |
jbonofre/beam | sdks/python/apache_beam/runners/test/__init__.py | 25 | 1243 | #
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You 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.
#
"""Test runner objects that's only for end-to-end tests.
This package defines runners, which are used to execute test pipeline and
verify results.
"""
# Protect against environments where dataflow runner is not available.
# pylint: disable=wrong-import-order, wrong-import-position
try:
from apache_beam.runners.dataflow.test_dataflow_runner import TestDataflowRunner
except ImportError:
pass
# pylint: enable=wrong-import-order, wrong-import-position
| apache-2.0 |
stuart-knock/tvb-framework | tvb_test/adapters/visualizers/eegmonitor_test.py | 1 | 4412 | # -*- coding: utf-8 -*-
#
#
# TheVirtualBrain-Framework Package. This package holds all Data Management, and
# Web-UI helpful to run brain-simulations. To use it, you also need do download
# TheVirtualBrain-Scientific Package (for simulators). See content of the
# documentation-folder for more details. See also http://www.thevirtualbrain.org
#
# (c) 2012-2013, Baycrest Centre for Geriatric Care ("Baycrest")
#
# This program is free software; you can redistribute it and/or modify it under
# the terms of the GNU General Public License version 2 as published by the Free
# Software Foundation. This program is distributed in the hope that it will be
# useful, but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
# License for more details. You should have received a copy of the GNU General
# Public License along with this program; if not, you can download it here
# http://www.gnu.org/licenses/old-licenses/gpl-2.0
#
#
# CITATION:
# When using The Virtual Brain for scientific publications, please cite it as follows:
#
# Paula Sanz Leon, Stuart A. Knock, M. Marmaduke Woodman, Lia Domide,
# Jochen Mersmann, Anthony R. McIntosh, Viktor Jirsa (2013)
# The Virtual Brain: a simulator of primate brain network dynamics.
# Frontiers in Neuroinformatics (7:10. doi: 10.3389/fninf.2013.00010)
#
#
"""
.. moduleauthor:: Bogdan Neacsa <bogdan.neacsa@codemart.ro>
"""
import os
import unittest
import demo_data.sensors as sensors_dataset
from tvb.core.entities.file.files_helper import FilesHelper
from tvb.adapters.visualizers.eeg_monitor import EegMonitor
from tvb.datatypes.surfaces import CorticalSurface
from tvb.datatypes.connectivity import Connectivity
from tvb.datatypes.sensors import SensorsEEG
from tvb_test.core.test_factory import TestFactory
from tvb_test.datatypes.datatypes_factory import DatatypesFactory
from tvb_test.core.base_testcase import TransactionalTestCase
class EEGMonitorTest(TransactionalTestCase):
"""
Unit-tests for EEG Viewer.
"""
def setUp(self):
"""
Sets up the environment for running the tests;
creates a test user, a test project, a connectivity and a surface;
imports a CFF data-set
"""
self.datatypeFactory = DatatypesFactory()
self.test_project = self.datatypeFactory.get_project()
self.test_user = self.datatypeFactory.get_user()
TestFactory.import_cff(test_user=self.test_user, test_project=self.test_project)
self.connectivity = TestFactory.get_entity(self.test_project, Connectivity())
self.assertTrue(self.connectivity is not None)
self.surface = TestFactory.get_entity(self.test_project, CorticalSurface())
self.assertTrue(self.surface is not None)
def tearDown(self):
"""
Clean-up tests data
"""
FilesHelper().remove_project_structure(self.test_project.name)
def test_launch(self):
"""
Check that all required keys are present in output from BrainViewer launch.
"""
zip_path = os.path.join(os.path.dirname(sensors_dataset.__file__),
'EEG_unit_vectors_BrainProducts_62.txt.bz2')
TestFactory.import_sensors(self.test_user, self.test_project, zip_path, 'EEG Sensors')
sensors = TestFactory.get_entity(self.test_project, SensorsEEG())
time_series = self.datatypeFactory.create_timeseries(self.connectivity, 'EEG', sensors)
viewer = EegMonitor()
result = viewer.launch(time_series)
expected_keys = ['tsStateVars', 'tsModes', 'translationStep', 'total_length', 'title',
'timeSetPaths', 'number_of_visible_points', 'normalizedSteps', 'noOfChannels',
'labelsForCheckBoxes', 'label_x', 'graphLabels', 'entities', 'channelsPage']
for key in expected_keys:
self.assertTrue(key in result)
def suite():
"""
Gather all the tests in a test suite.
"""
test_suite = unittest.TestSuite()
test_suite.addTest(unittest.makeSuite(EEGMonitorTest))
return test_suite
if __name__ == "__main__":
#So you can run tests from this package individually.
TEST_RUNNER = unittest.TextTestRunner()
TEST_SUITE = suite()
TEST_RUNNER.run(TEST_SUITE) | gpl-2.0 |
sammerry/ansible | lib/ansible/plugins/lookup/dict.py | 84 | 1113 | # (c) 2014, Kent R. Spillner <kspillner@acm.org>
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
from ansible.errors import AnsibleError
from ansible.plugins.lookup import LookupBase
class LookupModule(LookupBase):
def run(self, terms, varibles=None, **kwargs):
if not isinstance(terms, dict):
raise AnsibleError("with_dict expects a dict")
return self._flatten_hash_to_list(terms)
| gpl-3.0 |
lshain-android-source/external-chromium_org-tools-grit | grit/test_suite_all.py | 8 | 6803 | #!/usr/bin/env python
# Copyright (c) 2011 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
'''Unit test suite that collects all test cases for GRIT.'''
import os
import sys
if __name__ == '__main__':
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import unittest
# TODO(joi) Use unittest.defaultTestLoader to automatically load tests
# from modules. Iterating over the directory and importing could then
# automate this all the way, if desired.
class TestSuiteAll(unittest.TestSuite):
def __init__(self):
super(TestSuiteAll, self).__init__()
# Imports placed here to prevent circular imports.
# pylint: disable-msg=C6204
import grit.clique_unittest
import grit.grd_reader_unittest
import grit.grit_runner_unittest
import grit.lazy_re_unittest
import grit.shortcuts_unittests
import grit.tclib_unittest
import grit.util_unittest
import grit.xtb_reader_unittest
import grit.format.android_xml_unittest
import grit.format.c_format_unittest
import grit.format.chrome_messages_json_unittest
import grit.format.data_pack_unittest
import grit.format.html_inline_unittest
import grit.format.js_map_format_unittest
import grit.format.rc_header_unittest
import grit.format.rc_unittest
import grit.format.resource_map_unittest
import grit.format.policy_templates.policy_template_generator_unittest
import grit.format.policy_templates.writers.adm_writer_unittest
import grit.format.policy_templates.writers.doc_writer_unittest
import grit.format.policy_templates.writers.json_writer_unittest
import grit.format.policy_templates.writers.plist_strings_writer_unittest
import grit.format.policy_templates.writers.plist_writer_unittest
import grit.format.policy_templates.writers.reg_writer_unittest
import grit.format.policy_templates.writers.template_writer_unittest
import grit.format.policy_templates.writers.xml_writer_base_unittest
import grit.gather.admin_template_unittest
import grit.gather.chrome_html_unittest
import grit.gather.chrome_scaled_image_unittest
import grit.gather.igoogle_strings_unittest
import grit.gather.muppet_strings_unittest
import grit.gather.policy_json_unittest
import grit.gather.rc_unittest
import grit.gather.tr_html_unittest
import grit.gather.txt_unittest
import grit.node.base_unittest
import grit.node.io_unittest
import grit.node.include_unittest
import grit.node.message_unittest
import grit.node.misc_unittest
import grit.node.structure_unittest #
import grit.node.custom.filename_unittest
import grit.tool.android2grd_unittest
import grit.tool.build_unittest
import grit.tool.buildinfo_unittest
import grit.tool.postprocess_unittest
import grit.tool.preprocess_unittest
import grit.tool.rc2grd_unittest
import grit.tool.transl2tc_unittest
import grit.tool.xmb_unittest
test_classes = [
grit.clique_unittest.MessageCliqueUnittest,
grit.grd_reader_unittest.GrdReaderUnittest,
grit.grit_runner_unittest.OptionArgsUnittest,
grit.lazy_re_unittest.LazyReUnittest,
grit.shortcuts_unittests.ShortcutsUnittest,
grit.tclib_unittest.TclibUnittest,
grit.util_unittest.UtilUnittest,
grit.xtb_reader_unittest.XtbReaderUnittest,
grit.format.android_xml_unittest.AndroidXmlUnittest,
grit.format.c_format_unittest.CFormatUnittest,
grit.format.chrome_messages_json_unittest.
ChromeMessagesJsonFormatUnittest,
grit.format.data_pack_unittest.FormatDataPackUnittest,
grit.format.html_inline_unittest.HtmlInlineUnittest,
grit.format.js_map_format_unittest.JsMapFormatUnittest,
grit.format.rc_header_unittest.RcHeaderFormatterUnittest,
grit.format.rc_unittest.FormatRcUnittest,
grit.format.resource_map_unittest.FormatResourceMapUnittest,
grit.format.policy_templates.policy_template_generator_unittest.
PolicyTemplateGeneratorUnittest,
grit.format.policy_templates.writers.adm_writer_unittest.
AdmWriterUnittest,
grit.format.policy_templates.writers.doc_writer_unittest.
DocWriterUnittest,
grit.format.policy_templates.writers.json_writer_unittest.
JsonWriterUnittest,
grit.format.policy_templates.writers.plist_strings_writer_unittest.
PListStringsWriterUnittest,
grit.format.policy_templates.writers.plist_writer_unittest.
PListWriterUnittest,
grit.format.policy_templates.writers.reg_writer_unittest.
RegWriterUnittest,
grit.format.policy_templates.writers.template_writer_unittest.
TemplateWriterUnittests,
grit.format.policy_templates.writers.xml_writer_base_unittest.
XmlWriterBaseTest,
grit.gather.admin_template_unittest.AdmGathererUnittest,
grit.gather.chrome_html_unittest.ChromeHtmlUnittest,
grit.gather.chrome_scaled_image_unittest.ChromeScaledImageUnittest,
grit.gather.igoogle_strings_unittest.IgoogleStringsUnittest,
grit.gather.muppet_strings_unittest.MuppetStringsUnittest,
grit.gather.policy_json_unittest.PolicyJsonUnittest,
grit.gather.rc_unittest.RcUnittest,
grit.gather.tr_html_unittest.ParserUnittest,
grit.gather.tr_html_unittest.TrHtmlUnittest,
grit.gather.txt_unittest.TxtUnittest,
grit.node.base_unittest.NodeUnittest,
grit.node.io_unittest.FileNodeUnittest,
grit.node.include_unittest.IncludeNodeUnittest,
grit.node.message_unittest.MessageUnittest,
grit.node.misc_unittest.GritNodeUnittest,
grit.node.misc_unittest.IfNodeUnittest,
grit.node.misc_unittest.ReleaseNodeUnittest,
grit.node.structure_unittest.StructureUnittest,
grit.node.custom.filename_unittest.WindowsFilenameUnittest,
grit.tool.android2grd_unittest.Android2GrdUnittest,
grit.tool.build_unittest.BuildUnittest,
grit.tool.buildinfo_unittest.BuildInfoUnittest,
grit.tool.postprocess_unittest.PostProcessingUnittest,
grit.tool.preprocess_unittest.PreProcessingUnittest,
grit.tool.rc2grd_unittest.Rc2GrdUnittest,
grit.tool.transl2tc_unittest.TranslationToTcUnittest,
grit.tool.xmb_unittest.XmbUnittest,
# add test classes here, in alphabetical order...
]
for test_class in test_classes:
self.addTest(unittest.makeSuite(test_class))
if __name__ == '__main__':
test_result = unittest.TextTestRunner(verbosity=2).run(TestSuiteAll())
sys.exit(len(test_result.errors) + len(test_result.failures))
| bsd-2-clause |
lilydjwg/you-get | src/you_get/extractors/netease.py | 1 | 9738 | #!/usr/bin/env python
from json import loads
import hashlib
import base64
import os
import binascii
try:
from Crypto.Cipher import AES
import xml.etree.ElementTree as ET
has_crypto = True
except ImportError:
has_crypto = False
from ..common import *
from ..extractor import VideoExtractor
from ..util import log
def netease_hymn():
return """
player's Game Over,
u can abandon.
u get pissed,
get pissed,
Hallelujah my King!
errr oh! fuck ohhh!!!!
"""
def encrypted_id(dfsId):
x = [ord(i[0]) for i in netease_hymn().split()]
y = ''.join([chr(i - 61) if i > 96 else chr(i + 32) for i in x])
byte1 = bytearray(y, encoding='ascii')
byte2 = bytearray(str(dfsId), encoding='ascii')
for i in range(len(byte2)):
byte2[i] ^= byte1[i % len(byte1)]
m = hashlib.md5()
m.update(byte2)
result = base64.b64encode(m.digest()).decode('ascii')
result = result.replace('/', '_')
result = result.replace('+', '-')
return result
def make_url(songNet, dfsId):
encId = encrypted_id(dfsId)
mp3_url = "http://%s/%s/%s.mp3" % (songNet, encId, dfsId)
return mp3_url
# for http://open.163.com/movie/2014/12/I/9/MAD7EMDVE_MAD7K95I9.html
keys = ["4fxGZqoGmesXqg2o", "3fxVNqoPmesAqg2o"]
def decrypto_video_url(data, whichkey):
key = keys[whichkey - 1]
cipher = AES.new(key, mode=AES.MODE_ECB)
ciphertext = binascii.a2b_hex(data)
cleartext = cipher.decrypt(ciphertext)
padding = cleartext[-1]
cleartext = cleartext[:-padding]
return cleartext.decode('ascii')
class NetEase(VideoExtractor):
# test URLs:
# http://live.ws.126.net/movie/I/9/2_MAD7EMDVE_MAD7K95I9.xml
# http://live.ws.126.net/movie/V/H/2_MB3M6LDG1_MB3OBKTVH.xml
name = '网易'
if has_crypto:
stream_types = [
{'id': 'SHD', 'video_profile': '超清'},
{'id': 'HD', 'video_profile': '高清'},
{'id': 'SD', 'video_profile': '标清'},
]
else:
stream_types = [
{'id': 'default'},
]
def prepare(self, **kwargs):
# compatibility for _cloud_music_prepare
self.output_dir = kwargs.get('output_dir')
self.info_only = kwargs.get('info_only')
self.subs = []
self.lyrics = None
url = self.url
if "163.fm" in url:
url = get_location(url)
if "music.163.com" in url:
self._cloud_music_prepare(url)
elif has_crypto:
self._crypto_prepare(url)
else:
log.w('PyCrypto not found, '
'high resolution videos may be unavailable.')
self._legacy_prepare(url)
def _crypto_prepare(self, url):
if url.startswith('http://swf.ws.126.net/openplayer/'):
video_id = url.split('-')[2]
assert video_id.startswith('2_')
video_id = video_id[2:]
else:
# http://open.163.com/movie/2015/10/V/H/MB3M6LDG1_MB3OBKTVH.html
video_id = url.split('/')[-1].split('.')[0]
xml = self._get_xml_for_video_id(video_id)
encrypt_key = int(xml.find('encrypt').text)
playurl = xml.find('playurl_origin')
if len(playurl) == 0:
playurl = xml.find('playurl')
streams = {}
for stream in self.stream_types:
e = playurl.find('./%s/mp4' % stream['id'])
if e is not None:
url = decrypto_video_url(e.text, encrypt_key)
streams[stream['id']] = {
'url': url,
'video_profile': stream['video_profile'],
'size': url_size(url),
}
self.streams = streams
for sub in xml.findall('subs/*'):
name = sub.find('name').text
url = sub.find('url').text
self.subs.append((name, url))
def _legacy_prepare(self, url):
if url.startswith('http://swf.ws.126.net/openplayer/'):
video_id = url.split('-')[2]
assert video_id.startswith('2_')
video_id = video_id[2:]
xml = self._get_xml_for_video_id(video_id)
url = xml.find('pageUrl').text
html = get_decoded_html(url)
title = match1(html, "movieDescription='([^']+)'") or \
match1(html, '<title>(.+)</title>')
self.title = title.strip()
src = match1(html, r'<source src="([^"]+)"') or \
match1(html, r'<source type="[^"]+" src="([^"]+)"')
if src:
url = src
else:
url = (match1(html, r'["\'](.+)-list.m3u8["\']') or
match1(html, r'["\'](.+).m3u8["\']')) + ".mp4"
self.streams['default'] = {
'url': url,
}
def _cloud_music_prepare(self, url):
rid = match1(url, r'id=(.*)')
output_dir = self.output_dir
info_only = self.info_only
if rid is None:
rid = match1(url, r'/(\d+)/?$')
if "album" in url:
# FIXME: only last is processed
j = loads(get_content("http://music.163.com/api/album/%s?id=%s&csrf_token=" % (rid, rid), headers={"Referer": "http://music.163.com/"}))
artist_name = j['album']['artists'][0]['name']
album_name = j['album']['name']
new_dir = output_dir + '/' + "%s - %s" % (artist_name, album_name)
if not os.path.exists(new_dir):
os.mkdir(new_dir)
if not info_only:
cover_url = j['album']['picUrl']
download_urls([cover_url], "cover", "jpg", 0, new_dir)
for i in j['album']['songs']:
self._song_prepare(i)
try: # download lyrics
assert kwargs['caption']
l = loads(get_content("http://music.163.com/api/song/lyric/?id=%s&lv=-1&csrf_token=" % i['id'], headers={"Referer": "http://music.163.com/"}))
self._lyrics_prepare(i, l["lrc"]["lyric"])
except: pass
elif "playlist" in url:
# FIXME: only last is processed
j = loads(get_content("http://music.163.com/api/playlist/detail?id=%s&csrf_token=" % rid, headers={"Referer": "http://music.163.com/"}))
new_dir = output_dir + '/' + j['result']['name']
if not os.path.exists(new_dir):
os.mkdir(new_dir)
if not info_only:
cover_url = j['result']['coverImgUrl']
download_urls([cover_url], "cover", "jpg", 0, new_dir)
for i in j['result']['tracks']:
self._song_prepare(i)
try: # download lyrics
assert kwargs['caption']
l = loads(get_content("http://music.163.com/api/song/lyric/?id=%s&lv=-1&csrf_token=" % i['id'], headers={"Referer": "http://music.163.com/"}))
self._lyrics_prepare(i, l["lrc"]["lyric"])
except: pass
elif "song" in url:
j = loads(get_content("http://music.163.com/api/song/detail/?id=%s&ids=[%s]&csrf_token=" % (rid, rid), headers={"Referer": "http://music.163.com/"}))
self._song_prepare(j["songs"][0])
try: # download lyrics
l = loads(get_content("http://music.163.com/api/song/lyric/?id=%s&lv=-1&csrf_token=" % rid, headers={"Referer": "http://music.163.com/"}))
self._lyrics_prepare(j["songs"][0], l["lrc"]["lyric"])
except:
pass
elif "mv" in url:
j = loads(get_content("http://music.163.com/api/mv/detail/?id=%s&ids=[%s]&csrf_token=" % (rid, rid), headers={"Referer": "http://music.163.com/"}))
self._video_prepare(j['data'])
def _song_prepare(self, song):
# test URL: http://music.163.com/#/song?id=29043459
self.title = "%s. %s" % (song['position'], song['name'])
songNet = 'p' + song['mp3Url'].split('/')[2][1:]
s = self.streams
if 'hMusic' in song and song['hMusic'] is not None:
s['hMusic'] = {'url': make_url(songNet, song['hMusic']['dfsId'])}
if 'mp3Url' in song:
s['mp3Url'] = {'url': song['mp3Url']}
if 'bMusic' in song:
s['bMusic'] = {'url': make_url(songNet, song['bMusic']['dfsId'])}
self.stream_types = [
{'id': x} for x in ['hMusic', 'mp3Url', 'bMusic']
]
def _video_prepare(self, vinfo):
# test URL: http://music.163.com/#/mv/343100/
self.title = "%s - %s" % (vinfo['name'], vinfo['artistName'])
s = self.streams
for bitrate, url in vinfo['brs'].items():
s[bitrate] = {'url': url}
self.stream_types = [
{'id': x} for x in sorted(s, key=int, reverse=True)
]
def _lyrics_prepare(self, song, lyrics):
# test URL: http://music.163.com/#/song?id=29043459
title = "%s. %s" % (song['position'], song['name'])
filename = '%s.lrc' % get_filename(title)
self.plain_files.append({
'filename': filename,
'content': lyrics,
})
def _get_xml_for_video_id(self, vid):
xml_url = 'http://live.ws.126.net/movie/%s/%s/2_%s.xml' % (
vid[-2], vid[-1], vid)
xml = get_content(xml_url)
e = ET.fromstring(xml)
self.title = e.find('title').text
return e
def extract(self, **kwargs):
for i in self.streams:
s = self.streams[i]
_, s['container'], s['size'] = url_info(s['url'])
s['src'] = [s['url']]
for name, url in self.subs:
self.caption_tracks[name] = get_content(url)
site = NetEase()
download = site.download_by_url
| mit |
gregdek/ansible | test/units/modules/network/slxos/test_slxos_vlan.py | 30 | 4622 | #
# (c) 2018 Extreme Networks Inc.
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
#
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import re
import json
from units.compat.mock import patch
from ansible.modules.network.slxos import slxos_vlan
from units.modules.utils import set_module_args
from .slxos_module import TestSlxosModule, load_fixture
class TestSlxosVlanModule(TestSlxosModule):
module = slxos_vlan
def setUp(self):
super(TestSlxosVlanModule, self).setUp()
self._patch_run_commands = patch(
'ansible.modules.network.slxos.slxos_vlan.run_commands'
)
self._patch_load_config = patch(
'ansible.modules.network.slxos.slxos_vlan.load_config'
)
self._run_commands = self._patch_run_commands.start()
self._load_config = self._patch_load_config.start()
def tearDown(self):
super(TestSlxosVlanModule, self).tearDown()
self._patch_run_commands.stop()
self._patch_load_config.stop()
def load_fixtures(self, commands=None):
config_file = 'show_vlan_brief'
self._run_commands.return_value = [load_fixture(config_file)]
self._load_config.return_value = None
def test_slxos_vlan_id_with_name(self, *args, **kwargs):
load_fixture('show_vlan_brief')
set_module_args(dict(
vlan_id=100,
name='ONEHUNDRED'
))
result = self.execute_module(changed=True)
self.assertEqual(
result,
{
'commands': [
'vlan 100',
'name ONEHUNDRED'
],
'changed': True
}
)
def test_slxos_vlan_with_members(self, *args, **kwargs):
set_module_args(dict(
vlan_id=100,
name='ONEHUNDRED',
interfaces=[
'Ethernet 0/1',
'Ethernet 0/2'
]
))
result = self.execute_module(changed=True)
self.assertEqual(
result,
{
'commands': [
'vlan 100',
'name ONEHUNDRED',
'interface Ethernet 0/1',
'switchport',
'switchport mode access',
'switchport access vlan 100',
'interface Ethernet 0/2',
'switchport',
'switchport mode access',
'switchport access vlan 100'
],
'changed': True
}
)
def test_slxos_vlan_state_absent(self, *args, **kwargs):
set_module_args(dict(
vlan_id=200,
state='absent'
))
result = self.execute_module(changed=True)
self.assertEqual(
result,
{
'commands': [
'no vlan 200'
],
'changed': True
}
)
def test_slxos_vlan_state_absent_nonexistant_vlan(self, *args, **kwargs):
set_module_args(dict(
vlan_id=100,
state='absent'
))
result = self.execute_module()
self.assertEqual(
result,
{
'commands': [],
'changed': False
}
)
def test_slxos_interface_invalid_argument(self, *args, **kwargs):
set_module_args(dict(
name='Ethernet 0/1',
shawshank='Redemption'
))
result = self.execute_module(failed=True)
self.assertEqual(result['failed'], True)
self.assertTrue(re.match(
r'Unsupported parameters for \((basic.py|basic.pyc)\) module: '
'shawshank Supported parameters include: aggregate, delay, '
'interfaces, name, purge, state, vlan_id',
result['msg']
), 'Result did not match expected output. Got: %s' % result['msg'])
| gpl-3.0 |
ar7z1/ansible | lib/ansible/modules/network/f5/bigip_iapplx_package.py | 9 | 11731 | #!/usr/bin/python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2017 F5 Networks Inc.
# GNU General Public License v3.0 (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'certified'}
DOCUMENTATION = r'''
---
module: bigip_iapplx_package
short_description: Manages Javascript iApp packages on a BIG-IP
description:
- Manages Javascript iApp packages on a BIG-IP. This module will allow
you to deploy iAppLX packages to the BIG-IP and manage their lifecycle.
version_added: 2.5
options:
package:
description:
- The iAppLX package that you want to upload or remove. When C(state) is C(present),
and you intend to use this module in a C(role), it is recommended that you use
the C({{ role_path }}) variable. An example is provided in the C(EXAMPLES) section.
- When C(state) is C(absent), it is not necessary for the package to exist on the
Ansible controller. If the full path to the package is provided, the fileame will
specifically be cherry picked from it to properly remove the package.
state:
description:
- Whether the iAppLX package should exist or not.
default: present
choices:
- present
- absent
notes:
- Requires the rpm tool be installed on the host. This can be accomplished through
different ways on each platform. On Debian based systems with C(apt);
C(apt-get install rpm). On Mac with C(brew); C(brew install rpm).
This command is already present on RedHat based systems.
- Requires BIG-IP >= 12.1.0 because the required functionality is missing
on versions earlier than that.
requirements:
- Requires BIG-IP >= 12.1.0
- The 'rpm' tool installed on the Ansible controller
extends_documentation_fragment: f5
author:
- Tim Rupp (@caphrim007)
'''
EXAMPLES = r'''
- name: Add an iAppLX package
bigip_iapplx_package:
package: MyApp-0.1.0-0001.noarch.rpm
password: secret
server: lb.mydomain.com
state: present
user: admin
delegate_to: localhost
- name: Add an iAppLX package stored in a role
bigip_iapplx_package:
package: "{{ roles_path }}/files/MyApp-0.1.0-0001.noarch.rpm'"
password: secret
server: lb.mydomain.com
state: present
user: admin
delegate_to: localhost
- name: Remove an iAppLX package
bigip_iapplx_package:
package: MyApp-0.1.0-0001.noarch.rpm
password: secret
server: lb.mydomain.com
state: absent
user: admin
delegate_to: localhost
'''
RETURN = r'''
# only common fields returned
'''
import os
import time
from ansible.module_utils.basic import AnsibleModule
from distutils.version import LooseVersion
try:
from library.module_utils.network.f5.bigip import HAS_F5SDK
from library.module_utils.network.f5.bigip import F5Client
from library.module_utils.network.f5.common import F5ModuleError
from library.module_utils.network.f5.common import AnsibleF5Parameters
from library.module_utils.network.f5.common import cleanup_tokens
from library.module_utils.network.f5.common import f5_argument_spec
try:
from library.module_utils.network.f5.common import iControlUnexpectedHTTPError
except ImportError:
HAS_F5SDK = False
except ImportError:
from ansible.module_utils.network.f5.bigip import HAS_F5SDK
from ansible.module_utils.network.f5.bigip import F5Client
from ansible.module_utils.network.f5.common import F5ModuleError
from ansible.module_utils.network.f5.common import AnsibleF5Parameters
from ansible.module_utils.network.f5.common import cleanup_tokens
from ansible.module_utils.network.f5.common import f5_argument_spec
try:
from ansible.module_utils.network.f5.common import iControlUnexpectedHTTPError
except ImportError:
HAS_F5SDK = False
class Parameters(AnsibleF5Parameters):
api_attributes = []
returnables = []
@property
def package(self):
if self._values['package'] is None:
return None
return self._values['package']
@property
def package_file(self):
if self._values['package'] is None:
return None
return os.path.basename(self._values['package'])
@property
def package_name(self):
"""Return a valid name for the package
BIG-IP determines the package name by the content of the RPM info.
It does not use the filename. Therefore, we do the same. This method
is only used though when the file actually exists on your Ansible
controller.
If the package does not exist, then we instead use the filename
portion of the 'package' argument that is provided.
Non-existence typically occurs when using 'state' = 'absent'
:return:
"""
cmd = ['rpm', '-qp', '--queryformat', '%{NAME}-%{VERSION}-%{RELEASE}.%{ARCH}', self.package]
rc, out, err = self._module.run_command(cmd)
if not out:
return str(self.package_file)
return out
@property
def package_root(self):
if self._values['package'] is None:
return None
base = os.path.basename(self._values['package'])
result = os.path.splitext(base)
return result[0]
def to_return(self):
result = {}
try:
for returnable in self.returnables:
result[returnable] = getattr(self, returnable)
result = self._filter_params(result)
except Exception:
pass
return result
class ModuleManager(object):
def __init__(self, *args, **kwargs):
self.module = kwargs.get('module', None)
self.client = kwargs.get('client', None)
self.want = Parameters(module=self.module, params=self.module.params)
self.changes = Parameters()
def exec_module(self):
result = dict()
changed = False
state = self.want.state
version = self.client.api.tmos_version
if LooseVersion(version) <= LooseVersion('12.0.0'):
raise F5ModuleError(
"This version of BIG-IP is not supported."
)
try:
if state == "present":
changed = self.present()
elif state == "absent":
changed = self.absent()
except iControlUnexpectedHTTPError as e:
raise F5ModuleError(str(e))
changes = self.changes.to_return()
result.update(**changes)
result.update(dict(changed=changed))
return result
def present(self):
if self.exists():
return False
else:
return self.create()
def absent(self):
changed = False
if self.exists():
changed = self.remove()
return changed
def exists(self):
exists = False
packages = self.get_installed_packages_on_device()
if os.path.exists(self.want.package):
exists = True
for package in packages:
if exists:
if self.want.package_name == package['packageName']:
return True
else:
if self.want.package_root == package['packageName']:
return True
return False
def get_installed_packages_on_device(self):
collection = self.client.api.shared.iapp.package_management_tasks_s
task = collection.package_management_task.create(
operation='QUERY'
)
status = self._wait_for_task(task)
if status == 'FINISHED':
return task.queryResponse
raise F5ModuleError(
"Failed to find the installed packages on the device"
)
def create(self):
if self.module.check_mode:
return True
if not os.path.exists(self.want.package):
if self.want.package.startswith('/'):
raise F5ModuleError(
"The specified iAppLX package was not found at {0}.".format(self.want.package)
)
else:
raise F5ModuleError(
"The specified iAppLX package was not found in {0}.".format(os.getcwd())
)
self.upload_to_device()
self.create_on_device()
self.enable_iapplx_on_device()
self.remove_package_file_from_device()
if self.exists():
return True
else:
raise F5ModuleError("Failed to create the iApp template")
def upload_to_device(self):
upload = self.client.api.shared.file_transfer.uploads
upload.upload_file(
self.want.package
)
def remove_package_file_from_device(self):
self.client.api.tm.util.unix_rm.exec_cmd(
'run',
utilCmdArgs="/var/config/rest/downloads/{0}".format(self.want.package_file)
)
def create_on_device(self):
remote_path = "/var/config/rest/downloads/{0}".format(self.want.package_file)
collection = self.client.api.shared.iapp.package_management_tasks_s
task = collection.package_management_task.create(
operation='INSTALL',
packageFilePath=remote_path
)
status = self._wait_for_task(task)
if status == 'FINISHED':
return True
else:
raise F5ModuleError(task.errorMessage)
def remove(self):
if self.module.check_mode:
return True
self.remove_from_device()
if self.exists():
raise F5ModuleError("Failed to delete the iAppLX package")
return True
def remove_from_device(self):
collection = self.client.api.shared.iapp.package_management_tasks_s
task = collection.package_management_task.create(
operation='UNINSTALL',
packageName=self.want.package_root
)
status = self._wait_for_task(task)
if status == 'FINISHED':
return True
return False
def _wait_for_task(self, task):
for x in range(0, 60):
task.refresh()
if task.status in ['FINISHED', 'FAILED']:
return task.status
time.sleep(1)
return task.status
def enable_iapplx_on_device(self):
self.client.api.tm.util.bash.exec_cmd(
'run',
utilCmdArgs='-c "touch /var/config/rest/iapps/enable"'
)
class ArgumentSpec(object):
def __init__(self):
self.supports_check_mode = True
argument_spec = dict(
state=dict(
default='present',
choices=['present', 'absent']
),
package=dict()
)
self.argument_spec = {}
self.argument_spec.update(f5_argument_spec)
self.argument_spec.update(argument_spec)
self.required_if = [
['state', 'present', ['package']]
]
def main():
spec = ArgumentSpec()
module = AnsibleModule(
argument_spec=spec.argument_spec,
supports_check_mode=spec.supports_check_mode,
required_if=spec.required_if
)
if not HAS_F5SDK:
module.fail_json(msg="The python f5-sdk module is required")
try:
client = F5Client(**module.params)
mm = ModuleManager(module=module, client=client)
results = mm.exec_module()
cleanup_tokens(client)
module.exit_json(**results)
except F5ModuleError as e:
cleanup_tokens(client)
module.fail_json(msg=str(e))
if __name__ == '__main__':
main()
| gpl-3.0 |
heeraj123/oh-mainline | vendor/packages/zope.interface/setup.py | 16 | 4974 | ##############################################################################
#
# Copyright (c) 2004-2007 Zope Foundation and Contributors.
# All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED
# WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS
# FOR A PARTICULAR PURPOSE.
#
##############################################################################
# This package is developed by the Zope Toolkit project, documented here:
# http://docs.zope.org/zopetoolkit
# When developing and releasing this package, please follow the documented
# Zope Toolkit policies as described by this documentation.
##############################################################################
"""Setup for zope.interface package
"""
import os
import platform
import sys
try:
from setuptools import setup, Extension, Feature
except ImportError:
# do we need to support plain distutils for building when even
# the package itself requires setuptools for installing?
from distutils.core import setup, Extension
if sys.version_info[:2] >= (2, 4):
extra = dict(
package_data={
'zope.interface': ['*.txt'],
'zope.interface.tests': ['*.txt'],
}
)
else:
extra = {}
else:
codeoptimization_c = os.path.join('src', 'zope', 'interface',
'_zope_interface_coptimizations.c')
codeoptimization = Feature(
"Optional code optimizations",
standard = True,
ext_modules = [Extension(
"zope.interface._zope_interface_coptimizations",
[os.path.normcase(codeoptimization_c)]
)])
py_impl = getattr(platform, 'python_implementation', lambda: None)
is_pypy = py_impl() == 'PyPy'
is_jython = 'java' in sys.platform
# Jython cannot build the C optimizations, while on PyPy they are
# anti-optimizations (the C extension compatibility layer is known-slow,
# and defeats JIT opportunities).
if is_pypy or is_jython:
features = {}
else:
features = {'codeoptimization': codeoptimization}
extra = dict(
namespace_packages=["zope"],
include_package_data = True,
zip_safe = False,
tests_require = ['zope.event'],
install_requires = ['setuptools'],
extras_require={'docs': ['z3c.recipe.sphinxdoc'],
'test': ['zope.event']},
features = features
)
def read(*rnames):
return open(os.path.join(os.path.dirname(__file__), *rnames)).read()
long_description=(
read('README.txt')
+ '\n' +
read('CHANGES.txt')
)
try: # Zope setuptools versions
from build_ext_3 import optional_build_ext
# This is Python 3. Setuptools is now required, and so is zope.fixers.
extra['install_requires'] = ['setuptools']
extra['setup_requires'] = ['zope.fixers']
extra['use_2to3'] = True
extra['convert_2to3_doctests'] = [
'src/zope/interface/README.ru.txt',
'src/zope/interface/README.txt',
'src/zope/interface/adapter.ru.txt',
'src/zope/interface/adapter.txt',
'src/zope/interface/human.ru.txt',
'src/zope/interface/human.txt',
'src/zope/interface/index.txt',
'src/zope/interface/verify.txt',
]
extra['use_2to3_fixers'] = ['zope.fixers']
except (ImportError, SyntaxError):
from build_ext_2 import optional_build_ext
setup(name='zope.interface',
version='3.8.0',
url='http://pypi.python.org/pypi/zope.interface',
license='ZPL 2.1',
description='Interfaces for Python',
author='Zope Foundation and Contributors',
author_email='zope-dev@zope.org',
long_description=long_description,
classifiers=[
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"License :: OSI Approved :: Zope Public License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 2.4",
"Programming Language :: Python :: 2.5",
"Programming Language :: Python :: 2.6",
"Programming Language :: Python :: 2.7",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.1",
"Programming Language :: Python :: 3.2",
"Topic :: Software Development :: Libraries :: Python Modules",
],
packages = ['zope', 'zope.interface', 'zope.interface.tests'],
package_dir = {'': 'src'},
cmdclass = {'build_ext': optional_build_ext,
},
test_suite = 'zope.interface.tests',
**extra)
| agpl-3.0 |
p0psicles/SickRage | lib/feedparser/parsers/loose.py | 43 | 3425 | # The loose feed parser that interfaces with an SGML parsing library
# Copyright 2010-2015 Kurt McKee <contactme@kurtmckee.org>
# Copyright 2002-2008 Mark Pilgrim
# All rights reserved.
#
# This file is a part of feedparser.
#
# Redistribution and use in source and binary forms, with or without modification,
# are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 'AS IS'
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
from __future__ import absolute_import, unicode_literals
class _LooseFeedParser(object):
def __init__(self, baseuri=None, baselang=None, encoding=None, entities=None):
self.baseuri = baseuri or ''
self.lang = baselang or None
self.encoding = encoding or 'utf-8' # character encoding
self.entities = entities or {}
super(_LooseFeedParser, self).__init__()
def _normalize_attributes(self, kv):
k = kv[0].lower()
v = k in ('rel', 'type') and kv[1].lower() or kv[1]
# the sgml parser doesn't handle entities in attributes, nor
# does it pass the attribute values through as unicode, while
# strict xml parsers do -- account for this difference
v = v.replace('&', '&')
return (k, v)
def decodeEntities(self, element, data):
data = data.replace('<', '<')
data = data.replace('<', '<')
data = data.replace('<', '<')
data = data.replace('>', '>')
data = data.replace('>', '>')
data = data.replace('>', '>')
data = data.replace('&', '&')
data = data.replace('&', '&')
data = data.replace('"', '"')
data = data.replace('"', '"')
data = data.replace(''', ''')
data = data.replace(''', ''')
if not self.contentparams.get('type', 'xml').endswith('xml'):
data = data.replace('<', '<')
data = data.replace('>', '>')
data = data.replace('&', '&')
data = data.replace('"', '"')
data = data.replace(''', "'")
data = data.replace('/', '/')
data = data.replace('/', '/')
return data
def strattrs(self, attrs):
return ''.join([' %s="%s"' % (n,v.replace('"','"')) for n,v in attrs])
| gpl-3.0 |
jnovinger/django | tests/lookup/tests.py | 153 | 37208 | from __future__ import unicode_literals
from datetime import datetime
from operator import attrgetter
from unittest import skipUnless
from django.core.exceptions import FieldError
from django.db import connection
from django.test import TestCase, TransactionTestCase, skipUnlessDBFeature
from .models import Article, Author, Game, MyISAMArticle, Player, Season, Tag
class LookupTests(TestCase):
def setUp(self):
# Create a few Authors.
self.au1 = Author(name='Author 1')
self.au1.save()
self.au2 = Author(name='Author 2')
self.au2.save()
# Create a couple of Articles.
self.a1 = Article(headline='Article 1', pub_date=datetime(2005, 7, 26), author=self.au1)
self.a1.save()
self.a2 = Article(headline='Article 2', pub_date=datetime(2005, 7, 27), author=self.au1)
self.a2.save()
self.a3 = Article(headline='Article 3', pub_date=datetime(2005, 7, 27), author=self.au1)
self.a3.save()
self.a4 = Article(headline='Article 4', pub_date=datetime(2005, 7, 28), author=self.au1)
self.a4.save()
self.a5 = Article(headline='Article 5', pub_date=datetime(2005, 8, 1, 9, 0), author=self.au2)
self.a5.save()
self.a6 = Article(headline='Article 6', pub_date=datetime(2005, 8, 1, 8, 0), author=self.au2)
self.a6.save()
self.a7 = Article(headline='Article 7', pub_date=datetime(2005, 7, 27), author=self.au2)
self.a7.save()
# Create a few Tags.
self.t1 = Tag(name='Tag 1')
self.t1.save()
self.t1.articles.add(self.a1, self.a2, self.a3)
self.t2 = Tag(name='Tag 2')
self.t2.save()
self.t2.articles.add(self.a3, self.a4, self.a5)
self.t3 = Tag(name='Tag 3')
self.t3.save()
self.t3.articles.add(self.a5, self.a6, self.a7)
def test_exists(self):
# We can use .exists() to check that there are some
self.assertTrue(Article.objects.exists())
for a in Article.objects.all():
a.delete()
# There should be none now!
self.assertFalse(Article.objects.exists())
def test_lookup_int_as_str(self):
# Integer value can be queried using string
self.assertQuerysetEqual(Article.objects.filter(id__iexact=str(self.a1.id)),
['<Article: Article 1>'])
@skipUnlessDBFeature('supports_date_lookup_using_string')
def test_lookup_date_as_str(self):
# A date lookup can be performed using a string search
self.assertQuerysetEqual(Article.objects.filter(pub_date__startswith='2005'),
[
'<Article: Article 5>',
'<Article: Article 6>',
'<Article: Article 4>',
'<Article: Article 2>',
'<Article: Article 3>',
'<Article: Article 7>',
'<Article: Article 1>',
])
def test_iterator(self):
# Each QuerySet gets iterator(), which is a generator that "lazily"
# returns results using database-level iteration.
self.assertQuerysetEqual(Article.objects.iterator(),
[
'Article 5',
'Article 6',
'Article 4',
'Article 2',
'Article 3',
'Article 7',
'Article 1',
],
transform=attrgetter('headline'))
# iterator() can be used on any QuerySet.
self.assertQuerysetEqual(
Article.objects.filter(headline__endswith='4').iterator(),
['Article 4'],
transform=attrgetter('headline'))
def test_count(self):
# count() returns the number of objects matching search criteria.
self.assertEqual(Article.objects.count(), 7)
self.assertEqual(Article.objects.filter(pub_date__exact=datetime(2005, 7, 27)).count(), 3)
self.assertEqual(Article.objects.filter(headline__startswith='Blah blah').count(), 0)
# count() should respect sliced query sets.
articles = Article.objects.all()
self.assertEqual(articles.count(), 7)
self.assertEqual(articles[:4].count(), 4)
self.assertEqual(articles[1:100].count(), 6)
self.assertEqual(articles[10:100].count(), 0)
# Date and date/time lookups can also be done with strings.
self.assertEqual(Article.objects.filter(pub_date__exact='2005-07-27 00:00:00').count(), 3)
def test_in_bulk(self):
# in_bulk() takes a list of IDs and returns a dictionary mapping IDs to objects.
arts = Article.objects.in_bulk([self.a1.id, self.a2.id])
self.assertEqual(arts[self.a1.id], self.a1)
self.assertEqual(arts[self.a2.id], self.a2)
self.assertEqual(Article.objects.in_bulk([self.a3.id]), {self.a3.id: self.a3})
self.assertEqual(Article.objects.in_bulk({self.a3.id}), {self.a3.id: self.a3})
self.assertEqual(Article.objects.in_bulk(frozenset([self.a3.id])), {self.a3.id: self.a3})
self.assertEqual(Article.objects.in_bulk((self.a3.id,)), {self.a3.id: self.a3})
self.assertEqual(Article.objects.in_bulk([1000]), {})
self.assertEqual(Article.objects.in_bulk([]), {})
self.assertEqual(Article.objects.in_bulk(iter([self.a1.id])), {self.a1.id: self.a1})
self.assertEqual(Article.objects.in_bulk(iter([])), {})
self.assertRaises(TypeError, Article.objects.in_bulk)
self.assertRaises(TypeError, Article.objects.in_bulk, headline__startswith='Blah')
def test_values(self):
# values() returns a list of dictionaries instead of object instances --
# and you can specify which fields you want to retrieve.
identity = lambda x: x
self.assertQuerysetEqual(Article.objects.values('headline'),
[
{'headline': 'Article 5'},
{'headline': 'Article 6'},
{'headline': 'Article 4'},
{'headline': 'Article 2'},
{'headline': 'Article 3'},
{'headline': 'Article 7'},
{'headline': 'Article 1'},
],
transform=identity)
self.assertQuerysetEqual(
Article.objects.filter(pub_date__exact=datetime(2005, 7, 27)).values('id'),
[{'id': self.a2.id}, {'id': self.a3.id}, {'id': self.a7.id}],
transform=identity)
self.assertQuerysetEqual(Article.objects.values('id', 'headline'),
[
{'id': self.a5.id, 'headline': 'Article 5'},
{'id': self.a6.id, 'headline': 'Article 6'},
{'id': self.a4.id, 'headline': 'Article 4'},
{'id': self.a2.id, 'headline': 'Article 2'},
{'id': self.a3.id, 'headline': 'Article 3'},
{'id': self.a7.id, 'headline': 'Article 7'},
{'id': self.a1.id, 'headline': 'Article 1'},
],
transform=identity)
# You can use values() with iterator() for memory savings,
# because iterator() uses database-level iteration.
self.assertQuerysetEqual(Article.objects.values('id', 'headline').iterator(),
[
{'headline': 'Article 5', 'id': self.a5.id},
{'headline': 'Article 6', 'id': self.a6.id},
{'headline': 'Article 4', 'id': self.a4.id},
{'headline': 'Article 2', 'id': self.a2.id},
{'headline': 'Article 3', 'id': self.a3.id},
{'headline': 'Article 7', 'id': self.a7.id},
{'headline': 'Article 1', 'id': self.a1.id},
],
transform=identity)
# The values() method works with "extra" fields specified in extra(select).
self.assertQuerysetEqual(
Article.objects.extra(select={'id_plus_one': 'id + 1'}).values('id', 'id_plus_one'),
[
{'id': self.a5.id, 'id_plus_one': self.a5.id + 1},
{'id': self.a6.id, 'id_plus_one': self.a6.id + 1},
{'id': self.a4.id, 'id_plus_one': self.a4.id + 1},
{'id': self.a2.id, 'id_plus_one': self.a2.id + 1},
{'id': self.a3.id, 'id_plus_one': self.a3.id + 1},
{'id': self.a7.id, 'id_plus_one': self.a7.id + 1},
{'id': self.a1.id, 'id_plus_one': self.a1.id + 1},
],
transform=identity)
data = {
'id_plus_one': 'id+1',
'id_plus_two': 'id+2',
'id_plus_three': 'id+3',
'id_plus_four': 'id+4',
'id_plus_five': 'id+5',
'id_plus_six': 'id+6',
'id_plus_seven': 'id+7',
'id_plus_eight': 'id+8',
}
self.assertQuerysetEqual(
Article.objects.filter(id=self.a1.id).extra(select=data).values(*data.keys()),
[{
'id_plus_one': self.a1.id + 1,
'id_plus_two': self.a1.id + 2,
'id_plus_three': self.a1.id + 3,
'id_plus_four': self.a1.id + 4,
'id_plus_five': self.a1.id + 5,
'id_plus_six': self.a1.id + 6,
'id_plus_seven': self.a1.id + 7,
'id_plus_eight': self.a1.id + 8,
}], transform=identity)
# You can specify fields from forward and reverse relations, just like filter().
self.assertQuerysetEqual(
Article.objects.values('headline', 'author__name'),
[
{'headline': self.a5.headline, 'author__name': self.au2.name},
{'headline': self.a6.headline, 'author__name': self.au2.name},
{'headline': self.a4.headline, 'author__name': self.au1.name},
{'headline': self.a2.headline, 'author__name': self.au1.name},
{'headline': self.a3.headline, 'author__name': self.au1.name},
{'headline': self.a7.headline, 'author__name': self.au2.name},
{'headline': self.a1.headline, 'author__name': self.au1.name},
], transform=identity)
self.assertQuerysetEqual(
Author.objects.values('name', 'article__headline').order_by('name', 'article__headline'),
[
{'name': self.au1.name, 'article__headline': self.a1.headline},
{'name': self.au1.name, 'article__headline': self.a2.headline},
{'name': self.au1.name, 'article__headline': self.a3.headline},
{'name': self.au1.name, 'article__headline': self.a4.headline},
{'name': self.au2.name, 'article__headline': self.a5.headline},
{'name': self.au2.name, 'article__headline': self.a6.headline},
{'name': self.au2.name, 'article__headline': self.a7.headline},
], transform=identity)
self.assertQuerysetEqual(
Author.objects.values('name', 'article__headline', 'article__tag__name').order_by('name', 'article__headline', 'article__tag__name'),
[
{'name': self.au1.name, 'article__headline': self.a1.headline, 'article__tag__name': self.t1.name},
{'name': self.au1.name, 'article__headline': self.a2.headline, 'article__tag__name': self.t1.name},
{'name': self.au1.name, 'article__headline': self.a3.headline, 'article__tag__name': self.t1.name},
{'name': self.au1.name, 'article__headline': self.a3.headline, 'article__tag__name': self.t2.name},
{'name': self.au1.name, 'article__headline': self.a4.headline, 'article__tag__name': self.t2.name},
{'name': self.au2.name, 'article__headline': self.a5.headline, 'article__tag__name': self.t2.name},
{'name': self.au2.name, 'article__headline': self.a5.headline, 'article__tag__name': self.t3.name},
{'name': self.au2.name, 'article__headline': self.a6.headline, 'article__tag__name': self.t3.name},
{'name': self.au2.name, 'article__headline': self.a7.headline, 'article__tag__name': self.t3.name},
], transform=identity)
# However, an exception FieldDoesNotExist will be thrown if you specify
# a non-existent field name in values() (a field that is neither in the
# model nor in extra(select)).
self.assertRaises(FieldError,
Article.objects.extra(select={'id_plus_one': 'id + 1'}).values,
'id', 'id_plus_two')
# If you don't specify field names to values(), all are returned.
self.assertQuerysetEqual(Article.objects.filter(id=self.a5.id).values(),
[{
'id': self.a5.id,
'author_id': self.au2.id,
'headline': 'Article 5',
'pub_date': datetime(2005, 8, 1, 9, 0)
}], transform=identity)
def test_values_list(self):
# values_list() is similar to values(), except that the results are
# returned as a list of tuples, rather than a list of dictionaries.
# Within each tuple, the order of the elements is the same as the order
# of fields in the values_list() call.
identity = lambda x: x
self.assertQuerysetEqual(Article.objects.values_list('headline'),
[
('Article 5',),
('Article 6',),
('Article 4',),
('Article 2',),
('Article 3',),
('Article 7',),
('Article 1',),
], transform=identity)
self.assertQuerysetEqual(Article.objects.values_list('id').order_by('id'),
[(self.a1.id,), (self.a2.id,), (self.a3.id,), (self.a4.id,), (self.a5.id,), (self.a6.id,), (self.a7.id,)],
transform=identity)
self.assertQuerysetEqual(
Article.objects.values_list('id', flat=True).order_by('id'),
[self.a1.id, self.a2.id, self.a3.id, self.a4.id, self.a5.id, self.a6.id, self.a7.id],
transform=identity)
self.assertQuerysetEqual(
Article.objects.extra(select={'id_plus_one': 'id+1'})
.order_by('id').values_list('id'),
[(self.a1.id,), (self.a2.id,), (self.a3.id,), (self.a4.id,), (self.a5.id,), (self.a6.id,), (self.a7.id,)],
transform=identity)
self.assertQuerysetEqual(
Article.objects.extra(select={'id_plus_one': 'id+1'})
.order_by('id').values_list('id_plus_one', 'id'),
[
(self.a1.id + 1, self.a1.id),
(self.a2.id + 1, self.a2.id),
(self.a3.id + 1, self.a3.id),
(self.a4.id + 1, self.a4.id),
(self.a5.id + 1, self.a5.id),
(self.a6.id + 1, self.a6.id),
(self.a7.id + 1, self.a7.id)
],
transform=identity)
self.assertQuerysetEqual(
Article.objects.extra(select={'id_plus_one': 'id+1'})
.order_by('id').values_list('id', 'id_plus_one'),
[
(self.a1.id, self.a1.id + 1),
(self.a2.id, self.a2.id + 1),
(self.a3.id, self.a3.id + 1),
(self.a4.id, self.a4.id + 1),
(self.a5.id, self.a5.id + 1),
(self.a6.id, self.a6.id + 1),
(self.a7.id, self.a7.id + 1)
],
transform=identity)
self.assertQuerysetEqual(
Author.objects.values_list('name', 'article__headline', 'article__tag__name').order_by('name', 'article__headline', 'article__tag__name'),
[
(self.au1.name, self.a1.headline, self.t1.name),
(self.au1.name, self.a2.headline, self.t1.name),
(self.au1.name, self.a3.headline, self.t1.name),
(self.au1.name, self.a3.headline, self.t2.name),
(self.au1.name, self.a4.headline, self.t2.name),
(self.au2.name, self.a5.headline, self.t2.name),
(self.au2.name, self.a5.headline, self.t3.name),
(self.au2.name, self.a6.headline, self.t3.name),
(self.au2.name, self.a7.headline, self.t3.name),
], transform=identity)
self.assertRaises(TypeError, Article.objects.values_list, 'id', 'headline', flat=True)
def test_get_next_previous_by(self):
# Every DateField and DateTimeField creates get_next_by_FOO() and
# get_previous_by_FOO() methods. In the case of identical date values,
# these methods will use the ID as a fallback check. This guarantees
# that no records are skipped or duplicated.
self.assertEqual(repr(self.a1.get_next_by_pub_date()),
'<Article: Article 2>')
self.assertEqual(repr(self.a2.get_next_by_pub_date()),
'<Article: Article 3>')
self.assertEqual(repr(self.a2.get_next_by_pub_date(headline__endswith='6')),
'<Article: Article 6>')
self.assertEqual(repr(self.a3.get_next_by_pub_date()),
'<Article: Article 7>')
self.assertEqual(repr(self.a4.get_next_by_pub_date()),
'<Article: Article 6>')
self.assertRaises(Article.DoesNotExist, self.a5.get_next_by_pub_date)
self.assertEqual(repr(self.a6.get_next_by_pub_date()),
'<Article: Article 5>')
self.assertEqual(repr(self.a7.get_next_by_pub_date()),
'<Article: Article 4>')
self.assertEqual(repr(self.a7.get_previous_by_pub_date()),
'<Article: Article 3>')
self.assertEqual(repr(self.a6.get_previous_by_pub_date()),
'<Article: Article 4>')
self.assertEqual(repr(self.a5.get_previous_by_pub_date()),
'<Article: Article 6>')
self.assertEqual(repr(self.a4.get_previous_by_pub_date()),
'<Article: Article 7>')
self.assertEqual(repr(self.a3.get_previous_by_pub_date()),
'<Article: Article 2>')
self.assertEqual(repr(self.a2.get_previous_by_pub_date()),
'<Article: Article 1>')
def test_escaping(self):
# Underscores, percent signs and backslashes have special meaning in the
# underlying SQL code, but Django handles the quoting of them automatically.
a8 = Article(headline='Article_ with underscore', pub_date=datetime(2005, 11, 20))
a8.save()
self.assertQuerysetEqual(Article.objects.filter(headline__startswith='Article'),
[
'<Article: Article_ with underscore>',
'<Article: Article 5>',
'<Article: Article 6>',
'<Article: Article 4>',
'<Article: Article 2>',
'<Article: Article 3>',
'<Article: Article 7>',
'<Article: Article 1>',
])
self.assertQuerysetEqual(Article.objects.filter(headline__startswith='Article_'),
['<Article: Article_ with underscore>'])
a9 = Article(headline='Article% with percent sign', pub_date=datetime(2005, 11, 21))
a9.save()
self.assertQuerysetEqual(Article.objects.filter(headline__startswith='Article'),
[
'<Article: Article% with percent sign>',
'<Article: Article_ with underscore>',
'<Article: Article 5>',
'<Article: Article 6>',
'<Article: Article 4>',
'<Article: Article 2>',
'<Article: Article 3>',
'<Article: Article 7>',
'<Article: Article 1>',
])
self.assertQuerysetEqual(Article.objects.filter(headline__startswith='Article%'),
['<Article: Article% with percent sign>'])
a10 = Article(headline='Article with \\ backslash', pub_date=datetime(2005, 11, 22))
a10.save()
self.assertQuerysetEqual(Article.objects.filter(headline__contains='\\'),
['<Article: Article with \ backslash>'])
def test_exclude(self):
Article.objects.create(headline='Article_ with underscore', pub_date=datetime(2005, 11, 20))
Article.objects.create(headline='Article% with percent sign', pub_date=datetime(2005, 11, 21))
Article.objects.create(headline='Article with \\ backslash', pub_date=datetime(2005, 11, 22))
# exclude() is the opposite of filter() when doing lookups:
self.assertQuerysetEqual(
Article.objects.filter(headline__contains='Article').exclude(headline__contains='with'),
[
'<Article: Article 5>',
'<Article: Article 6>',
'<Article: Article 4>',
'<Article: Article 2>',
'<Article: Article 3>',
'<Article: Article 7>',
'<Article: Article 1>',
])
self.assertQuerysetEqual(Article.objects.exclude(headline__startswith="Article_"),
[
'<Article: Article with \\ backslash>',
'<Article: Article% with percent sign>',
'<Article: Article 5>',
'<Article: Article 6>',
'<Article: Article 4>',
'<Article: Article 2>',
'<Article: Article 3>',
'<Article: Article 7>',
'<Article: Article 1>',
])
self.assertQuerysetEqual(Article.objects.exclude(headline="Article 7"),
[
'<Article: Article with \\ backslash>',
'<Article: Article% with percent sign>',
'<Article: Article_ with underscore>',
'<Article: Article 5>',
'<Article: Article 6>',
'<Article: Article 4>',
'<Article: Article 2>',
'<Article: Article 3>',
'<Article: Article 1>',
])
def test_none(self):
# none() returns a QuerySet that behaves like any other QuerySet object
self.assertQuerysetEqual(Article.objects.none(), [])
self.assertQuerysetEqual(
Article.objects.none().filter(headline__startswith='Article'), [])
self.assertQuerysetEqual(
Article.objects.filter(headline__startswith='Article').none(), [])
self.assertEqual(Article.objects.none().count(), 0)
self.assertEqual(
Article.objects.none().update(headline="This should not take effect"), 0)
self.assertQuerysetEqual(
[article for article in Article.objects.none().iterator()],
[])
def test_in(self):
# using __in with an empty list should return an empty query set
self.assertQuerysetEqual(Article.objects.filter(id__in=[]), [])
self.assertQuerysetEqual(Article.objects.exclude(id__in=[]),
[
'<Article: Article 5>',
'<Article: Article 6>',
'<Article: Article 4>',
'<Article: Article 2>',
'<Article: Article 3>',
'<Article: Article 7>',
'<Article: Article 1>',
])
def test_error_messages(self):
# Programming errors are pointed out with nice error messages
try:
Article.objects.filter(pub_date_year='2005').count()
self.fail('FieldError not raised')
except FieldError as ex:
self.assertEqual(str(ex), "Cannot resolve keyword 'pub_date_year' "
"into field. Choices are: author, author_id, headline, "
"id, pub_date, tag")
try:
Article.objects.filter(headline__starts='Article')
self.fail('FieldError not raised')
except FieldError as ex:
self.assertEqual(
str(ex), "Unsupported lookup 'starts' for CharField "
"or join on the field not permitted.")
def test_regex(self):
# Create some articles with a bit more interesting headlines for testing field lookups:
for a in Article.objects.all():
a.delete()
now = datetime.now()
a1 = Article(pub_date=now, headline='f')
a1.save()
a2 = Article(pub_date=now, headline='fo')
a2.save()
a3 = Article(pub_date=now, headline='foo')
a3.save()
a4 = Article(pub_date=now, headline='fooo')
a4.save()
a5 = Article(pub_date=now, headline='hey-Foo')
a5.save()
a6 = Article(pub_date=now, headline='bar')
a6.save()
a7 = Article(pub_date=now, headline='AbBa')
a7.save()
a8 = Article(pub_date=now, headline='baz')
a8.save()
a9 = Article(pub_date=now, headline='baxZ')
a9.save()
# zero-or-more
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'fo*'),
['<Article: f>', '<Article: fo>', '<Article: foo>', '<Article: fooo>'])
self.assertQuerysetEqual(Article.objects.filter(headline__iregex=r'fo*'),
[
'<Article: f>',
'<Article: fo>',
'<Article: foo>',
'<Article: fooo>',
'<Article: hey-Foo>',
])
# one-or-more
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'fo+'),
['<Article: fo>', '<Article: foo>', '<Article: fooo>'])
# wildcard
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'fooo?'),
['<Article: foo>', '<Article: fooo>'])
# leading anchor
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'^b'),
['<Article: bar>', '<Article: baxZ>', '<Article: baz>'])
self.assertQuerysetEqual(Article.objects.filter(headline__iregex=r'^a'),
['<Article: AbBa>'])
# trailing anchor
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'z$'),
['<Article: baz>'])
self.assertQuerysetEqual(Article.objects.filter(headline__iregex=r'z$'),
['<Article: baxZ>', '<Article: baz>'])
# character sets
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'ba[rz]'),
['<Article: bar>', '<Article: baz>'])
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'ba.[RxZ]'),
['<Article: baxZ>'])
self.assertQuerysetEqual(Article.objects.filter(headline__iregex=r'ba[RxZ]'),
['<Article: bar>', '<Article: baxZ>', '<Article: baz>'])
# and more articles:
a10 = Article(pub_date=now, headline='foobar')
a10.save()
a11 = Article(pub_date=now, headline='foobaz')
a11.save()
a12 = Article(pub_date=now, headline='ooF')
a12.save()
a13 = Article(pub_date=now, headline='foobarbaz')
a13.save()
a14 = Article(pub_date=now, headline='zoocarfaz')
a14.save()
a15 = Article(pub_date=now, headline='barfoobaz')
a15.save()
a16 = Article(pub_date=now, headline='bazbaRFOO')
a16.save()
# alternation
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'oo(f|b)'),
[
'<Article: barfoobaz>',
'<Article: foobar>',
'<Article: foobarbaz>',
'<Article: foobaz>',
])
self.assertQuerysetEqual(Article.objects.filter(headline__iregex=r'oo(f|b)'),
[
'<Article: barfoobaz>',
'<Article: foobar>',
'<Article: foobarbaz>',
'<Article: foobaz>',
'<Article: ooF>',
])
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'^foo(f|b)'),
['<Article: foobar>', '<Article: foobarbaz>', '<Article: foobaz>'])
# greedy matching
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'b.*az'),
[
'<Article: barfoobaz>',
'<Article: baz>',
'<Article: bazbaRFOO>',
'<Article: foobarbaz>',
'<Article: foobaz>',
])
self.assertQuerysetEqual(Article.objects.filter(headline__iregex=r'b.*ar'),
[
'<Article: bar>',
'<Article: barfoobaz>',
'<Article: bazbaRFOO>',
'<Article: foobar>',
'<Article: foobarbaz>',
])
@skipUnlessDBFeature('supports_regex_backreferencing')
def test_regex_backreferencing(self):
# grouping and backreferences
now = datetime.now()
a10 = Article(pub_date=now, headline='foobar')
a10.save()
a11 = Article(pub_date=now, headline='foobaz')
a11.save()
a12 = Article(pub_date=now, headline='ooF')
a12.save()
a13 = Article(pub_date=now, headline='foobarbaz')
a13.save()
a14 = Article(pub_date=now, headline='zoocarfaz')
a14.save()
a15 = Article(pub_date=now, headline='barfoobaz')
a15.save()
a16 = Article(pub_date=now, headline='bazbaRFOO')
a16.save()
self.assertQuerysetEqual(Article.objects.filter(headline__regex=r'b(.).*b\1'),
['<Article: barfoobaz>', '<Article: bazbaRFOO>', '<Article: foobarbaz>'])
def test_regex_null(self):
"""
Ensure that a regex lookup does not fail on null/None values
"""
Season.objects.create(year=2012, gt=None)
self.assertQuerysetEqual(Season.objects.filter(gt__regex=r'^$'), [])
def test_regex_non_string(self):
"""
Ensure that a regex lookup does not fail on non-string fields
"""
Season.objects.create(year=2013, gt=444)
self.assertQuerysetEqual(Season.objects.filter(gt__regex=r'^444$'),
['<Season: 2013>'])
def test_regex_non_ascii(self):
"""
Ensure that a regex lookup does not trip on non-ASCII characters.
"""
Player.objects.create(name='\u2660')
Player.objects.get(name__regex='\u2660')
def test_nonfield_lookups(self):
"""
Ensure that a lookup query containing non-fields raises the proper
exception.
"""
with self.assertRaises(FieldError):
Article.objects.filter(headline__blahblah=99)
with self.assertRaises(FieldError):
Article.objects.filter(headline__blahblah__exact=99)
with self.assertRaises(FieldError):
Article.objects.filter(blahblah=99)
def test_lookup_collision(self):
"""
Ensure that genuine field names don't collide with built-in lookup
types ('year', 'gt', 'range', 'in' etc.).
Refs #11670.
"""
# Here we're using 'gt' as a code number for the year, e.g. 111=>2009.
season_2009 = Season.objects.create(year=2009, gt=111)
season_2009.games.create(home="Houston Astros", away="St. Louis Cardinals")
season_2010 = Season.objects.create(year=2010, gt=222)
season_2010.games.create(home="Houston Astros", away="Chicago Cubs")
season_2010.games.create(home="Houston Astros", away="Milwaukee Brewers")
season_2010.games.create(home="Houston Astros", away="St. Louis Cardinals")
season_2011 = Season.objects.create(year=2011, gt=333)
season_2011.games.create(home="Houston Astros", away="St. Louis Cardinals")
season_2011.games.create(home="Houston Astros", away="Milwaukee Brewers")
hunter_pence = Player.objects.create(name="Hunter Pence")
hunter_pence.games = Game.objects.filter(season__year__in=[2009, 2010])
pudge = Player.objects.create(name="Ivan Rodriquez")
pudge.games = Game.objects.filter(season__year=2009)
pedro_feliz = Player.objects.create(name="Pedro Feliz")
pedro_feliz.games = Game.objects.filter(season__year__in=[2011])
johnson = Player.objects.create(name="Johnson")
johnson.games = Game.objects.filter(season__year__in=[2011])
# Games in 2010
self.assertEqual(Game.objects.filter(season__year=2010).count(), 3)
self.assertEqual(Game.objects.filter(season__year__exact=2010).count(), 3)
self.assertEqual(Game.objects.filter(season__gt=222).count(), 3)
self.assertEqual(Game.objects.filter(season__gt__exact=222).count(), 3)
# Games in 2011
self.assertEqual(Game.objects.filter(season__year=2011).count(), 2)
self.assertEqual(Game.objects.filter(season__year__exact=2011).count(), 2)
self.assertEqual(Game.objects.filter(season__gt=333).count(), 2)
self.assertEqual(Game.objects.filter(season__gt__exact=333).count(), 2)
self.assertEqual(Game.objects.filter(season__year__gt=2010).count(), 2)
self.assertEqual(Game.objects.filter(season__gt__gt=222).count(), 2)
# Games played in 2010 and 2011
self.assertEqual(Game.objects.filter(season__year__in=[2010, 2011]).count(), 5)
self.assertEqual(Game.objects.filter(season__year__gt=2009).count(), 5)
self.assertEqual(Game.objects.filter(season__gt__in=[222, 333]).count(), 5)
self.assertEqual(Game.objects.filter(season__gt__gt=111).count(), 5)
# Players who played in 2009
self.assertEqual(Player.objects.filter(games__season__year=2009).distinct().count(), 2)
self.assertEqual(Player.objects.filter(games__season__year__exact=2009).distinct().count(), 2)
self.assertEqual(Player.objects.filter(games__season__gt=111).distinct().count(), 2)
self.assertEqual(Player.objects.filter(games__season__gt__exact=111).distinct().count(), 2)
# Players who played in 2010
self.assertEqual(Player.objects.filter(games__season__year=2010).distinct().count(), 1)
self.assertEqual(Player.objects.filter(games__season__year__exact=2010).distinct().count(), 1)
self.assertEqual(Player.objects.filter(games__season__gt=222).distinct().count(), 1)
self.assertEqual(Player.objects.filter(games__season__gt__exact=222).distinct().count(), 1)
# Players who played in 2011
self.assertEqual(Player.objects.filter(games__season__year=2011).distinct().count(), 2)
self.assertEqual(Player.objects.filter(games__season__year__exact=2011).distinct().count(), 2)
self.assertEqual(Player.objects.filter(games__season__gt=333).distinct().count(), 2)
self.assertEqual(Player.objects.filter(games__season__year__gt=2010).distinct().count(), 2)
self.assertEqual(Player.objects.filter(games__season__gt__gt=222).distinct().count(), 2)
def test_chain_date_time_lookups(self):
self.assertQuerysetEqual(
Article.objects.filter(pub_date__month__gt=7),
['<Article: Article 5>', '<Article: Article 6>'],
ordered=False
)
self.assertQuerysetEqual(
Article.objects.filter(pub_date__day__gte=27),
['<Article: Article 2>', '<Article: Article 3>',
'<Article: Article 4>', '<Article: Article 7>'],
ordered=False
)
self.assertQuerysetEqual(
Article.objects.filter(pub_date__hour__lt=8),
['<Article: Article 1>', '<Article: Article 2>',
'<Article: Article 3>', '<Article: Article 4>',
'<Article: Article 7>'],
ordered=False
)
self.assertQuerysetEqual(
Article.objects.filter(pub_date__minute__lte=0),
['<Article: Article 1>', '<Article: Article 2>',
'<Article: Article 3>', '<Article: Article 4>',
'<Article: Article 5>', '<Article: Article 6>',
'<Article: Article 7>'],
ordered=False
)
class LookupTransactionTests(TransactionTestCase):
available_apps = ['lookup']
@skipUnless(connection.vendor == 'mysql', 'requires MySQL')
def test_mysql_lookup_search(self):
# To use fulltext indexes on MySQL either version 5.6 is needed, or one must use
# MyISAM tables. Neither of these combinations is currently available on CI, so
# lets manually create a MyISAM table for Article model.
with connection.cursor() as cursor:
cursor.execute(
"CREATE TEMPORARY TABLE myisam_article ("
" id INTEGER PRIMARY KEY AUTO_INCREMENT, "
" headline VARCHAR(100) NOT NULL "
") ENGINE MYISAM")
dr = MyISAMArticle.objects.create(headline='Django Reinhardt')
MyISAMArticle.objects.create(headline='Ringo Star')
# NOTE: Needs to be created after the article has been saved.
cursor.execute(
'CREATE FULLTEXT INDEX myisam_article_ft ON myisam_article (headline)')
self.assertQuerysetEqual(
MyISAMArticle.objects.filter(headline__search='Reinhardt'),
[dr], lambda x: x)
| bsd-3-clause |
wemanuel/smry | server-auth/ls/google-cloud-sdk/lib/requests/packages/urllib3/contrib/ntlmpool.py | 1010 | 4507 | """
NTLM authenticating pool, contributed by erikcederstran
Issue #10, see: http://code.google.com/p/urllib3/issues/detail?id=10
"""
try:
from http.client import HTTPSConnection
except ImportError:
from httplib import HTTPSConnection
from logging import getLogger
from ntlm import ntlm
from urllib3 import HTTPSConnectionPool
log = getLogger(__name__)
class NTLMConnectionPool(HTTPSConnectionPool):
"""
Implements an NTLM authentication version of an urllib3 connection pool
"""
scheme = 'https'
def __init__(self, user, pw, authurl, *args, **kwargs):
"""
authurl is a random URL on the server that is protected by NTLM.
user is the Windows user, probably in the DOMAIN\\username format.
pw is the password for the user.
"""
super(NTLMConnectionPool, self).__init__(*args, **kwargs)
self.authurl = authurl
self.rawuser = user
user_parts = user.split('\\', 1)
self.domain = user_parts[0].upper()
self.user = user_parts[1]
self.pw = pw
def _new_conn(self):
# Performs the NTLM handshake that secures the connection. The socket
# must be kept open while requests are performed.
self.num_connections += 1
log.debug('Starting NTLM HTTPS connection no. %d: https://%s%s' %
(self.num_connections, self.host, self.authurl))
headers = {}
headers['Connection'] = 'Keep-Alive'
req_header = 'Authorization'
resp_header = 'www-authenticate'
conn = HTTPSConnection(host=self.host, port=self.port)
# Send negotiation message
headers[req_header] = (
'NTLM %s' % ntlm.create_NTLM_NEGOTIATE_MESSAGE(self.rawuser))
log.debug('Request headers: %s' % headers)
conn.request('GET', self.authurl, None, headers)
res = conn.getresponse()
reshdr = dict(res.getheaders())
log.debug('Response status: %s %s' % (res.status, res.reason))
log.debug('Response headers: %s' % reshdr)
log.debug('Response data: %s [...]' % res.read(100))
# Remove the reference to the socket, so that it can not be closed by
# the response object (we want to keep the socket open)
res.fp = None
# Server should respond with a challenge message
auth_header_values = reshdr[resp_header].split(', ')
auth_header_value = None
for s in auth_header_values:
if s[:5] == 'NTLM ':
auth_header_value = s[5:]
if auth_header_value is None:
raise Exception('Unexpected %s response header: %s' %
(resp_header, reshdr[resp_header]))
# Send authentication message
ServerChallenge, NegotiateFlags = \
ntlm.parse_NTLM_CHALLENGE_MESSAGE(auth_header_value)
auth_msg = ntlm.create_NTLM_AUTHENTICATE_MESSAGE(ServerChallenge,
self.user,
self.domain,
self.pw,
NegotiateFlags)
headers[req_header] = 'NTLM %s' % auth_msg
log.debug('Request headers: %s' % headers)
conn.request('GET', self.authurl, None, headers)
res = conn.getresponse()
log.debug('Response status: %s %s' % (res.status, res.reason))
log.debug('Response headers: %s' % dict(res.getheaders()))
log.debug('Response data: %s [...]' % res.read()[:100])
if res.status != 200:
if res.status == 401:
raise Exception('Server rejected request: wrong '
'username or password')
raise Exception('Wrong server response: %s %s' %
(res.status, res.reason))
res.fp = None
log.debug('Connection established')
return conn
def urlopen(self, method, url, body=None, headers=None, retries=3,
redirect=True, assert_same_host=True):
if headers is None:
headers = {}
headers['Connection'] = 'Keep-Alive'
return super(NTLMConnectionPool, self).urlopen(method, url, body,
headers, retries,
redirect,
assert_same_host)
| apache-2.0 |
jlaunonen/kirppu | kirppu/views/csv_utils.py | 1 | 1469 | # -*- coding: utf-8 -*-
import functools
import html
import io
from urllib.parse import quote
from django.conf import settings
from django.http import HttpResponse, StreamingHttpResponse
def strip_generator(fn):
@functools.wraps(fn)
def inner(output, event, generator=False):
if generator:
# Return the generator object only when using StringIO.
return fn(output, event)
for _ in fn(output, event):
pass
return inner
def csv_streamer_view(request, generator, filename_base):
debug = settings.DEBUG and request.GET.get("debug") is not None
def streamer():
if debug:
yield "<!DOCTYPE html>\n<html>\n<body>\n<pre>"
output = io.StringIO()
for a_string in generator(output):
val = output.getvalue()
if debug:
yield html.escape(val, quote=False)
else:
yield val
output.truncate(0)
output.seek(0)
if debug:
yield "</pre>\n</body>\n</html>"
if debug:
response = HttpResponse("".join(streamer()))
else:
response = StreamingHttpResponse(streamer(), content_type="text/plain; charset=utf-8")
if request.GET.get("download") is not None:
response["Content-Disposition"] = 'attachment; filename="%s.csv"' % quote(filename_base, safe="")
response["Content-Type"] = "text/csv; charset=utf-8"
return response
| mit |
marziyeah/Medhacks_admin | full/node_modules/node-gyp/gyp/gyptest.py | 1752 | 8019 | #!/usr/bin/env python
# Copyright (c) 2012 Google Inc. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
__doc__ = """
gyptest.py -- test runner for GYP tests.
"""
import os
import optparse
import subprocess
import sys
class CommandRunner(object):
"""
Executor class for commands, including "commands" implemented by
Python functions.
"""
verbose = True
active = True
def __init__(self, dictionary={}):
self.subst_dictionary(dictionary)
def subst_dictionary(self, dictionary):
self._subst_dictionary = dictionary
def subst(self, string, dictionary=None):
"""
Substitutes (via the format operator) the values in the specified
dictionary into the specified command.
The command can be an (action, string) tuple. In all cases, we
perform substitution on strings and don't worry if something isn't
a string. (It's probably a Python function to be executed.)
"""
if dictionary is None:
dictionary = self._subst_dictionary
if dictionary:
try:
string = string % dictionary
except TypeError:
pass
return string
def display(self, command, stdout=None, stderr=None):
if not self.verbose:
return
if type(command) == type(()):
func = command[0]
args = command[1:]
s = '%s(%s)' % (func.__name__, ', '.join(map(repr, args)))
if type(command) == type([]):
# TODO: quote arguments containing spaces
# TODO: handle meta characters?
s = ' '.join(command)
else:
s = self.subst(command)
if not s.endswith('\n'):
s += '\n'
sys.stdout.write(s)
sys.stdout.flush()
def execute(self, command, stdout=None, stderr=None):
"""
Executes a single command.
"""
if not self.active:
return 0
if type(command) == type(''):
command = self.subst(command)
cmdargs = shlex.split(command)
if cmdargs[0] == 'cd':
command = (os.chdir,) + tuple(cmdargs[1:])
if type(command) == type(()):
func = command[0]
args = command[1:]
return func(*args)
else:
if stdout is sys.stdout:
# Same as passing sys.stdout, except python2.4 doesn't fail on it.
subout = None
else:
# Open pipe for anything else so Popen works on python2.4.
subout = subprocess.PIPE
if stderr is sys.stderr:
# Same as passing sys.stderr, except python2.4 doesn't fail on it.
suberr = None
elif stderr is None:
# Merge with stdout if stderr isn't specified.
suberr = subprocess.STDOUT
else:
# Open pipe for anything else so Popen works on python2.4.
suberr = subprocess.PIPE
p = subprocess.Popen(command,
shell=(sys.platform == 'win32'),
stdout=subout,
stderr=suberr)
p.wait()
if stdout is None:
self.stdout = p.stdout.read()
elif stdout is not sys.stdout:
stdout.write(p.stdout.read())
if stderr not in (None, sys.stderr):
stderr.write(p.stderr.read())
return p.returncode
def run(self, command, display=None, stdout=None, stderr=None):
"""
Runs a single command, displaying it first.
"""
if display is None:
display = command
self.display(display)
return self.execute(command, stdout, stderr)
class Unbuffered(object):
def __init__(self, fp):
self.fp = fp
def write(self, arg):
self.fp.write(arg)
self.fp.flush()
def __getattr__(self, attr):
return getattr(self.fp, attr)
sys.stdout = Unbuffered(sys.stdout)
sys.stderr = Unbuffered(sys.stderr)
def is_test_name(f):
return f.startswith('gyptest') and f.endswith('.py')
def find_all_gyptest_files(directory):
result = []
for root, dirs, files in os.walk(directory):
if '.svn' in dirs:
dirs.remove('.svn')
result.extend([ os.path.join(root, f) for f in files if is_test_name(f) ])
result.sort()
return result
def main(argv=None):
if argv is None:
argv = sys.argv
usage = "gyptest.py [-ahlnq] [-f formats] [test ...]"
parser = optparse.OptionParser(usage=usage)
parser.add_option("-a", "--all", action="store_true",
help="run all tests")
parser.add_option("-C", "--chdir", action="store", default=None,
help="chdir to the specified directory")
parser.add_option("-f", "--format", action="store", default='',
help="run tests with the specified formats")
parser.add_option("-G", '--gyp_option', action="append", default=[],
help="Add -G options to the gyp command line")
parser.add_option("-l", "--list", action="store_true",
help="list available tests and exit")
parser.add_option("-n", "--no-exec", action="store_true",
help="no execute, just print the command line")
parser.add_option("--passed", action="store_true",
help="report passed tests")
parser.add_option("--path", action="append", default=[],
help="additional $PATH directory")
parser.add_option("-q", "--quiet", action="store_true",
help="quiet, don't print test command lines")
opts, args = parser.parse_args(argv[1:])
if opts.chdir:
os.chdir(opts.chdir)
if opts.path:
extra_path = [os.path.abspath(p) for p in opts.path]
extra_path = os.pathsep.join(extra_path)
os.environ['PATH'] = extra_path + os.pathsep + os.environ['PATH']
if not args:
if not opts.all:
sys.stderr.write('Specify -a to get all tests.\n')
return 1
args = ['test']
tests = []
for arg in args:
if os.path.isdir(arg):
tests.extend(find_all_gyptest_files(os.path.normpath(arg)))
else:
if not is_test_name(os.path.basename(arg)):
print >>sys.stderr, arg, 'is not a valid gyp test name.'
sys.exit(1)
tests.append(arg)
if opts.list:
for test in tests:
print test
sys.exit(0)
CommandRunner.verbose = not opts.quiet
CommandRunner.active = not opts.no_exec
cr = CommandRunner()
os.environ['PYTHONPATH'] = os.path.abspath('test/lib')
if not opts.quiet:
sys.stdout.write('PYTHONPATH=%s\n' % os.environ['PYTHONPATH'])
passed = []
failed = []
no_result = []
if opts.format:
format_list = opts.format.split(',')
else:
# TODO: not duplicate this mapping from pylib/gyp/__init__.py
format_list = {
'aix5': ['make'],
'freebsd7': ['make'],
'freebsd8': ['make'],
'openbsd5': ['make'],
'cygwin': ['msvs'],
'win32': ['msvs', 'ninja'],
'linux2': ['make', 'ninja'],
'linux3': ['make', 'ninja'],
'darwin': ['make', 'ninja', 'xcode', 'xcode-ninja'],
}[sys.platform]
for format in format_list:
os.environ['TESTGYP_FORMAT'] = format
if not opts.quiet:
sys.stdout.write('TESTGYP_FORMAT=%s\n' % format)
gyp_options = []
for option in opts.gyp_option:
gyp_options += ['-G', option]
if gyp_options and not opts.quiet:
sys.stdout.write('Extra Gyp options: %s\n' % gyp_options)
for test in tests:
status = cr.run([sys.executable, test] + gyp_options,
stdout=sys.stdout,
stderr=sys.stderr)
if status == 2:
no_result.append(test)
elif status:
failed.append(test)
else:
passed.append(test)
if not opts.quiet:
def report(description, tests):
if tests:
if len(tests) == 1:
sys.stdout.write("\n%s the following test:\n" % description)
else:
fmt = "\n%s the following %d tests:\n"
sys.stdout.write(fmt % (description, len(tests)))
sys.stdout.write("\t" + "\n\t".join(tests) + "\n")
if opts.passed:
report("Passed", passed)
report("Failed", failed)
report("No result from", no_result)
if failed:
return 1
else:
return 0
if __name__ == "__main__":
sys.exit(main())
| mit |
doomsterinc/odoo | openerp/tests/common.py | 50 | 13675 | # -*- coding: utf-8 -*-
"""
The module :mod:`openerp.tests.common` provides unittest2 test cases and a few
helpers and classes to write tests.
"""
import errno
import glob
import json
import logging
import os
import select
import subprocess
import threading
import time
import itertools
import unittest2
import urllib2
import xmlrpclib
from contextlib import contextmanager
from datetime import datetime, timedelta
import werkzeug
import openerp
from openerp import api
from openerp.modules.registry import RegistryManager
_logger = logging.getLogger(__name__)
# The openerp library is supposed already configured.
ADDONS_PATH = openerp.tools.config['addons_path']
HOST = '127.0.0.1'
PORT = openerp.tools.config['xmlrpc_port']
# Useless constant, tests are aware of the content of demo data
ADMIN_USER_ID = openerp.SUPERUSER_ID
def get_db_name():
db = openerp.tools.config['db_name']
# If the database name is not provided on the command-line,
# use the one on the thread (which means if it is provided on
# the command-line, this will break when installing another
# database from XML-RPC).
if not db and hasattr(threading.current_thread(), 'dbname'):
return threading.current_thread().dbname
return db
# For backwards-compatibility - get_db_name() should be used instead
DB = get_db_name()
def at_install(flag):
""" Sets the at-install state of a test, the flag is a boolean specifying
whether the test should (``True``) or should not (``False``) run during
module installation.
By default, tests are run right after installing the module, before
starting the installation of the next module.
"""
def decorator(obj):
obj.at_install = flag
return obj
return decorator
def post_install(flag):
""" Sets the post-install state of a test. The flag is a boolean
specifying whether the test should or should not run after a set of
module installations.
By default, tests are *not* run after installation of all modules in the
current installation set.
"""
def decorator(obj):
obj.post_install = flag
return obj
return decorator
class BaseCase(unittest2.TestCase):
"""
Subclass of TestCase for common OpenERP-specific code.
This class is abstract and expects self.registry, self.cr and self.uid to be
initialized by subclasses.
"""
def cursor(self):
return self.registry.cursor()
def ref(self, xid):
""" Returns database ID for the provided :term:`external identifier`,
shortcut for ``get_object_reference``
:param xid: fully-qualified :term:`external identifier`, in the form
:samp:`{module}.{identifier}`
:raise: ValueError if not found
:returns: registered id
"""
assert "." in xid, "this method requires a fully qualified parameter, in the following form: 'module.identifier'"
module, xid = xid.split('.')
_, id = self.registry('ir.model.data').get_object_reference(self.cr, self.uid, module, xid)
return id
def browse_ref(self, xid):
""" Returns a record object for the provided
:term:`external identifier`
:param xid: fully-qualified :term:`external identifier`, in the form
:samp:`{module}.{identifier}`
:raise: ValueError if not found
:returns: :class:`~openerp.models.BaseModel`
"""
assert "." in xid, "this method requires a fully qualified parameter, in the following form: 'module.identifier'"
module, xid = xid.split('.')
return self.registry('ir.model.data').get_object(self.cr, self.uid, module, xid)
@contextmanager
def _assertRaises(self, exception):
""" Context manager that clears the environment upon failure. """
with super(BaseCase, self).assertRaises(exception) as cm:
with self.env.clear_upon_failure():
yield cm
def assertRaises(self, exception, func=None, *args, **kwargs):
if func:
with self._assertRaises(exception):
func(*args, **kwargs)
else:
return self._assertRaises(exception)
class TransactionCase(BaseCase):
""" TestCase in which each test method is run in its own transaction,
and with its own cursor. The transaction is rolled back and the cursor
is closed after each test.
"""
def setUp(self):
self.registry = RegistryManager.get(get_db_name())
#: current transaction's cursor
self.cr = self.cursor()
self.uid = openerp.SUPERUSER_ID
#: :class:`~openerp.api.Environment` for the current test case
self.env = api.Environment(self.cr, self.uid, {})
def tearDown(self):
# rollback and close the cursor, and reset the environments
self.env.reset()
self.cr.rollback()
self.cr.close()
class SingleTransactionCase(BaseCase):
""" TestCase in which all test methods are run in the same transaction,
the transaction is started with the first test method and rolled back at
the end of the last.
"""
@classmethod
def setUpClass(cls):
cls.registry = RegistryManager.get(get_db_name())
cls.cr = cls.registry.cursor()
cls.uid = openerp.SUPERUSER_ID
cls.env = api.Environment(cls.cr, cls.uid, {})
@classmethod
def tearDownClass(cls):
# rollback and close the cursor, and reset the environments
cls.env.reset()
cls.cr.rollback()
cls.cr.close()
savepoint_seq = itertools.count()
class SavepointCase(SingleTransactionCase):
""" Similar to :class:`SingleTransactionCase` in that all test methods
are run in a single transaction *but* each test case is run inside a
rollbacked savepoint (sub-transaction).
Useful for test cases containing fast tests but with significant database
setup common to all cases (complex in-db test data): :meth:`~.setUpClass`
can be used to generate db test data once, then all test cases use the
same data without influencing one another but without having to recreate
the test data either.
"""
def setUp(self):
self._savepoint_id = next(savepoint_seq)
self.cr.execute('SAVEPOINT test_%d' % self._savepoint_id)
def tearDown(self):
self.cr.execute('ROLLBACK TO SAVEPOINT test_%d' % self._savepoint_id)
self.env.clear()
self.registry.clear_caches()
class RedirectHandler(urllib2.HTTPRedirectHandler):
"""
HTTPRedirectHandler is predicated upon HTTPErrorProcessor being used and
works by intercepting 3xy "errors".
Inherit from it to handle 3xy non-error responses instead, as we're not
using the error processor
"""
def http_response(self, request, response):
code, msg, hdrs = response.code, response.msg, response.info()
if 300 <= code < 400:
return self.parent.error(
'http', request, response, code, msg, hdrs)
return response
https_response = http_response
class HttpCase(TransactionCase):
""" Transactional HTTP TestCase with url_open and phantomjs helpers.
"""
def __init__(self, methodName='runTest'):
super(HttpCase, self).__init__(methodName)
# v8 api with correct xmlrpc exception handling.
self.xmlrpc_url = url_8 = 'http://%s:%d/xmlrpc/2/' % (HOST, PORT)
self.xmlrpc_common = xmlrpclib.ServerProxy(url_8 + 'common')
self.xmlrpc_db = xmlrpclib.ServerProxy(url_8 + 'db')
self.xmlrpc_object = xmlrpclib.ServerProxy(url_8 + 'object')
def setUp(self):
super(HttpCase, self).setUp()
self.registry.enter_test_mode()
# setup a magic session_id that will be rollbacked
self.session = openerp.http.root.session_store.new()
self.session_id = self.session.sid
self.session.db = get_db_name()
openerp.http.root.session_store.save(self.session)
# setup an url opener helper
self.opener = urllib2.OpenerDirector()
self.opener.add_handler(urllib2.UnknownHandler())
self.opener.add_handler(urllib2.HTTPHandler())
self.opener.add_handler(urllib2.HTTPSHandler())
self.opener.add_handler(urllib2.HTTPCookieProcessor())
self.opener.add_handler(RedirectHandler())
self.opener.addheaders.append(('Cookie', 'session_id=%s' % self.session_id))
def tearDown(self):
self.registry.leave_test_mode()
super(HttpCase, self).tearDown()
def url_open(self, url, data=None, timeout=10):
if url.startswith('/'):
url = "http://localhost:%s%s" % (PORT, url)
return self.opener.open(url, data, timeout)
def authenticate(self, user, password):
if user is not None:
url = '/login?%s' % werkzeug.urls.url_encode({'db': get_db_name(),'login': user, 'key': password})
auth = self.url_open(url)
assert auth.getcode() < 400, "Auth failure %d" % auth.getcode()
def phantom_poll(self, phantom, timeout):
""" Phantomjs Test protocol.
Use console.log in phantomjs to output test results:
- for a success: console.log("ok")
- for an error: console.log("error")
Other lines are relayed to the test log.
"""
t0 = datetime.now()
td = timedelta(seconds=timeout)
buf = bytearray()
while True:
# timeout
self.assertLess(datetime.now() - t0, td,
"PhantomJS tests should take less than %s seconds" % timeout)
# read a byte
try:
ready, _, _ = select.select([phantom.stdout], [], [], 0.5)
except select.error, e:
# In Python 2, select.error has no relation to IOError or
# OSError, and no errno/strerror/filename, only a pair of
# unnamed arguments (matching errno and strerror)
err, _ = e.args
if err == errno.EINTR:
continue
raise
if ready:
s = phantom.stdout.read(1)
if not s:
break
buf.append(s)
# process lines
if '\n' in buf:
line, buf = buf.split('\n', 1)
line = str(line)
# relay everything from console.log, even 'ok' or 'error...' lines
_logger.info("phantomjs: %s", line)
if line == "ok":
break
if line.startswith("error"):
line_ = line[6:]
# when error occurs the execution stack may be sent as as JSON
try:
line_ = json.loads(line_)
except ValueError:
pass
self.fail(line_ or "phantomjs test failed")
def phantom_run(self, cmd, timeout):
_logger.info('phantom_run executing %s', ' '.join(cmd))
ls_glob = os.path.expanduser('~/.qws/share/data/Ofi Labs/PhantomJS/http_localhost_%s.*'%PORT)
for i in glob.glob(ls_glob):
_logger.info('phantomjs unlink localstorage %s', i)
os.unlink(i)
try:
phantom = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=None)
except OSError:
raise unittest2.SkipTest("PhantomJS not found")
try:
self.phantom_poll(phantom, timeout)
finally:
# kill phantomjs if phantom.exit() wasn't called in the test
if phantom.poll() is None:
phantom.terminate()
phantom.wait()
self._wait_remaining_requests()
# we ignore phantomjs return code as we kill it as soon as we have ok
_logger.info("phantom_run execution finished")
def _wait_remaining_requests(self):
t0 = int(time.time())
for thread in threading.enumerate():
if thread.name.startswith('openerp.service.http.request.'):
while thread.isAlive():
# Need a busyloop here as thread.join() masks signals
# and would prevent the forced shutdown.
thread.join(0.05)
time.sleep(0.05)
t1 = int(time.time())
if t0 != t1:
_logger.info('remaining requests')
openerp.tools.misc.dumpstacks()
t0 = t1
def phantom_js(self, url_path, code, ready="window", login=None, timeout=60, **kw):
""" Test js code running in the browser
- optionnally log as 'login'
- load page given by url_path
- wait for ready object to be available
- eval(code) inside the page
To signal success test do:
console.log('ok')
To signal failure do:
console.log('error')
If neither are done before timeout test fails.
"""
options = {
'port': PORT,
'db': get_db_name(),
'url_path': url_path,
'code': code,
'ready': ready,
'timeout' : timeout,
'login' : login,
'session_id': self.session_id,
}
options.update(kw)
options.setdefault('password', options.get('login'))
phantomtest = os.path.join(os.path.dirname(__file__), 'phantomtest.js')
cmd = ['phantomjs', phantomtest, json.dumps(options)]
self.phantom_run(cmd, timeout)
# vim:expandtab:smartindent:tabstop=4:softtabstop=4:shiftwidth=4:
| agpl-3.0 |
cyc805/FTRerouting | .waf-1.7.11-edc6ccb516c5e3f9b892efc9f53a610f/waflib/Context.py | 70 | 8431 | #! /usr/bin/env python
# encoding: utf-8
# WARNING! Do not edit! http://waf.googlecode.com/git/docs/wafbook/single.html#_obtaining_the_waf_file
import os,imp,sys
from waflib import Utils,Errors,Logs
import waflib.Node
HEXVERSION=0x1070b00
WAFVERSION="1.7.11"
WAFREVISION="50f631bc5e00bdda966c68094229b99be9a21084"
ABI=98
DBFILE='.wafpickle-%s-%d-%d'%(sys.platform,sys.hexversion,ABI)
APPNAME='APPNAME'
VERSION='VERSION'
TOP='top'
OUT='out'
WSCRIPT_FILE='wscript'
launch_dir=''
run_dir=''
top_dir=''
out_dir=''
waf_dir=''
local_repo=''
remote_repo='http://waf.googlecode.com/git/'
remote_locs=['waflib/extras','waflib/Tools']
g_module=None
STDOUT=1
STDERR=-1
BOTH=0
classes=[]
def create_context(cmd_name,*k,**kw):
global classes
for x in classes:
if x.cmd==cmd_name:
return x(*k,**kw)
ctx=Context(*k,**kw)
ctx.fun=cmd_name
return ctx
class store_context(type):
def __init__(cls,name,bases,dict):
super(store_context,cls).__init__(name,bases,dict)
name=cls.__name__
if name=='ctx'or name=='Context':
return
try:
cls.cmd
except AttributeError:
raise Errors.WafError('Missing command for the context class %r (cmd)'%name)
if not getattr(cls,'fun',None):
cls.fun=cls.cmd
global classes
classes.insert(0,cls)
ctx=store_context('ctx',(object,),{})
class Context(ctx):
errors=Errors
tools={}
def __init__(self,**kw):
try:
rd=kw['run_dir']
except KeyError:
global run_dir
rd=run_dir
class node_class(waflib.Node.Node):
pass
self.node_class=node_class
self.node_class.__module__="waflib.Node"
self.node_class.__name__="Nod3"
self.node_class.ctx=self
self.root=self.node_class('',None)
self.cur_script=None
self.path=self.root.find_dir(rd)
self.stack_path=[]
self.exec_dict={'ctx':self,'conf':self,'bld':self,'opt':self}
self.logger=None
def __hash__(self):
return id(self)
def load(self,tool_list,*k,**kw):
tools=Utils.to_list(tool_list)
path=Utils.to_list(kw.get('tooldir',''))
for t in tools:
module=load_tool(t,path)
fun=getattr(module,kw.get('name',self.fun),None)
if fun:
fun(self)
def execute(self):
global g_module
self.recurse([os.path.dirname(g_module.root_path)])
def pre_recurse(self,node):
self.stack_path.append(self.cur_script)
self.cur_script=node
self.path=node.parent
def post_recurse(self,node):
self.cur_script=self.stack_path.pop()
if self.cur_script:
self.path=self.cur_script.parent
def recurse(self,dirs,name=None,mandatory=True,once=True):
try:
cache=self.recurse_cache
except AttributeError:
cache=self.recurse_cache={}
for d in Utils.to_list(dirs):
if not os.path.isabs(d):
d=os.path.join(self.path.abspath(),d)
WSCRIPT=os.path.join(d,WSCRIPT_FILE)
WSCRIPT_FUN=WSCRIPT+'_'+(name or self.fun)
node=self.root.find_node(WSCRIPT_FUN)
if node and(not once or node not in cache):
cache[node]=True
self.pre_recurse(node)
try:
function_code=node.read('rU')
exec(compile(function_code,node.abspath(),'exec'),self.exec_dict)
finally:
self.post_recurse(node)
elif not node:
node=self.root.find_node(WSCRIPT)
tup=(node,name or self.fun)
if node and(not once or tup not in cache):
cache[tup]=True
self.pre_recurse(node)
try:
wscript_module=load_module(node.abspath())
user_function=getattr(wscript_module,(name or self.fun),None)
if not user_function:
if not mandatory:
continue
raise Errors.WafError('No function %s defined in %s'%(name or self.fun,node.abspath()))
user_function(self)
finally:
self.post_recurse(node)
elif not node:
if not mandatory:
continue
raise Errors.WafError('No wscript file in directory %s'%d)
def exec_command(self,cmd,**kw):
subprocess=Utils.subprocess
kw['shell']=isinstance(cmd,str)
Logs.debug('runner: %r'%cmd)
Logs.debug('runner_env: kw=%s'%kw)
if self.logger:
self.logger.info(cmd)
if'stdout'not in kw:
kw['stdout']=subprocess.PIPE
if'stderr'not in kw:
kw['stderr']=subprocess.PIPE
try:
if kw['stdout']or kw['stderr']:
p=subprocess.Popen(cmd,**kw)
(out,err)=p.communicate()
ret=p.returncode
else:
out,err=(None,None)
ret=subprocess.Popen(cmd,**kw).wait()
except Exception ,e:
raise Errors.WafError('Execution failure: %s'%str(e),ex=e)
if out:
if not isinstance(out,str):
out=out.decode(sys.stdout.encoding or'iso8859-1')
if self.logger:
self.logger.debug('out: %s'%out)
else:
sys.stdout.write(out)
if err:
if not isinstance(err,str):
err=err.decode(sys.stdout.encoding or'iso8859-1')
if self.logger:
self.logger.error('err: %s'%err)
else:
sys.stderr.write(err)
return ret
def cmd_and_log(self,cmd,**kw):
subprocess=Utils.subprocess
kw['shell']=isinstance(cmd,str)
Logs.debug('runner: %r'%cmd)
if'quiet'in kw:
quiet=kw['quiet']
del kw['quiet']
else:
quiet=None
if'output'in kw:
to_ret=kw['output']
del kw['output']
else:
to_ret=STDOUT
kw['stdout']=kw['stderr']=subprocess.PIPE
if quiet is None:
self.to_log(cmd)
try:
p=subprocess.Popen(cmd,**kw)
(out,err)=p.communicate()
except Exception ,e:
raise Errors.WafError('Execution failure: %s'%str(e),ex=e)
if not isinstance(out,str):
out=out.decode(sys.stdout.encoding or'iso8859-1')
if not isinstance(err,str):
err=err.decode(sys.stdout.encoding or'iso8859-1')
if out and quiet!=STDOUT and quiet!=BOTH:
self.to_log('out: %s'%out)
if err and quiet!=STDERR and quiet!=BOTH:
self.to_log('err: %s'%err)
if p.returncode:
e=Errors.WafError('Command %r returned %r'%(cmd,p.returncode))
e.returncode=p.returncode
e.stderr=err
e.stdout=out
raise e
if to_ret==BOTH:
return(out,err)
elif to_ret==STDERR:
return err
return out
def fatal(self,msg,ex=None):
if self.logger:
self.logger.info('from %s: %s'%(self.path.abspath(),msg))
try:
msg='%s\n(complete log in %s)'%(msg,self.logger.handlers[0].baseFilename)
except Exception:
pass
raise self.errors.ConfigurationError(msg,ex=ex)
def to_log(self,msg):
if not msg:
return
if self.logger:
self.logger.info(msg)
else:
sys.stderr.write(str(msg))
sys.stderr.flush()
def msg(self,msg,result,color=None):
self.start_msg(msg)
if not isinstance(color,str):
color=result and'GREEN'or'YELLOW'
self.end_msg(result,color)
def start_msg(self,msg):
try:
if self.in_msg:
self.in_msg+=1
return
except AttributeError:
self.in_msg=0
self.in_msg+=1
try:
self.line_just=max(self.line_just,len(msg))
except AttributeError:
self.line_just=max(40,len(msg))
for x in(self.line_just*'-',msg):
self.to_log(x)
Logs.pprint('NORMAL',"%s :"%msg.ljust(self.line_just),sep='')
def end_msg(self,result,color=None):
self.in_msg-=1
if self.in_msg:
return
defcolor='GREEN'
if result==True:
msg='ok'
elif result==False:
msg='not found'
defcolor='YELLOW'
else:
msg=str(result)
self.to_log(msg)
Logs.pprint(color or defcolor,msg)
def load_special_tools(self,var,ban=[]):
global waf_dir
lst=self.root.find_node(waf_dir).find_node('waflib/extras').ant_glob(var)
for x in lst:
if not x.name in ban:
load_tool(x.name.replace('.py',''))
cache_modules={}
def load_module(path):
try:
return cache_modules[path]
except KeyError:
pass
module=imp.new_module(WSCRIPT_FILE)
try:
code=Utils.readf(path,m='rU')
except(IOError,OSError):
raise Errors.WafError('Could not read the file %r'%path)
module_dir=os.path.dirname(path)
sys.path.insert(0,module_dir)
exec(compile(code,path,'exec'),module.__dict__)
sys.path.remove(module_dir)
cache_modules[path]=module
return module
def load_tool(tool,tooldir=None):
if tool=='java':
tool='javaw'
elif tool=='compiler_cc':
tool='compiler_c'
else:
tool=tool.replace('++','xx')
if tooldir:
assert isinstance(tooldir,list)
sys.path=tooldir+sys.path
try:
__import__(tool)
ret=sys.modules[tool]
Context.tools[tool]=ret
return ret
finally:
for d in tooldir:
sys.path.remove(d)
else:
global waf_dir
try:
os.stat(os.path.join(waf_dir,'waflib','extras',tool+'.py'))
except OSError:
try:
os.stat(os.path.join(waf_dir,'waflib','Tools',tool+'.py'))
except OSError:
d=tool
else:
d='waflib.Tools.%s'%tool
else:
d='waflib.extras.%s'%tool
__import__(d)
ret=sys.modules[d]
Context.tools[tool]=ret
return ret
| gpl-2.0 |
jsocol/django-authority | authority/templatetags/permissions.py | 6 | 15531 | from django import template
from django.core.urlresolvers import reverse
from django.core.exceptions import ImproperlyConfigured
from django.contrib.auth.models import User, AnonymousUser
from django.core.urlresolvers import reverse
from authority import get_check
from authority import permissions
from authority.models import Permission
from authority.forms import UserPermissionForm
register = template.Library()
@register.simple_tag
def url_for_obj(view_name, obj):
return reverse(view_name, kwargs={
'app_label': obj._meta.app_label,
'module_name': obj._meta.module_name,
'pk': obj.pk})
@register.simple_tag
def add_url_for_obj(obj):
return url_for_obj('authority-add-permission', obj)
@register.simple_tag
def request_url_for_obj(obj):
return url_for_obj('authority-add-permission-request', obj)
class ResolverNode(template.Node):
"""
A small wrapper that adds a convenient resolve method.
"""
def resolve(self, var, context):
"""Resolves a variable out of context if it's not in quotes"""
if var is None:
return var
if var[0] in ('"', "'") and var[-1] == var[0]:
return var[1:-1]
else:
return template.Variable(var).resolve(context)
@classmethod
def next_bit_for(cls, bits, key, if_none=None):
try:
return bits[bits.index(key)+1]
except ValueError:
return if_none
class PermissionComparisonNode(ResolverNode):
"""
Implements a node to provide an "if user/group has permission on object"
"""
@classmethod
def handle_token(cls, parser, token):
bits = token.contents.split()
if 5 < len(bits) < 3:
raise template.TemplateSyntaxError("'%s' tag takes three, "
"four or five arguments" % bits[0])
end_tag = 'endifhasperm'
nodelist_true = parser.parse(('else', end_tag))
token = parser.next_token()
if token.contents == 'else': # there is an 'else' clause in the tag
nodelist_false = parser.parse((end_tag,))
parser.delete_first_token()
else:
nodelist_false = template.NodeList()
if len(bits) == 3: # this tag requires at most 2 objects . None is given
objs = (None, None)
elif len(bits) == 4:# one is given
objs = (bits[3], None)
else: #two are given
objs = (bits[3], bits[4])
return cls(bits[2], bits[1], nodelist_true, nodelist_false, *objs)
def __init__(self, user, perm, nodelist_true, nodelist_false, *objs):
self.user = user
self.objs = objs
self.perm = perm
self.nodelist_true = nodelist_true
self.nodelist_false = nodelist_false
def render(self, context):
try:
user = self.resolve(self.user, context)
perm = self.resolve(self.perm, context)
if self.objs:
objs = []
for obj in self.objs:
if obj is not None:
objs.append(self.resolve(obj, context))
else:
objs = None
check = get_check(user, perm)
if check is not None:
if check(*objs):
# return True if check was successful
return self.nodelist_true.render(context)
# If the app couldn't be found
except (ImproperlyConfigured, ImportError):
return ''
# If either variable fails to resolve, return nothing.
except template.VariableDoesNotExist:
return ''
# If the types don't permit comparison, return nothing.
except (TypeError, AttributeError):
return ''
return self.nodelist_false.render(context)
@register.tag
def ifhasperm(parser, token):
"""
This function provides functionality for the 'ifhasperm' template tag
Syntax::
{% ifhasperm PERMISSION_LABEL.CHECK_NAME USER *OBJS %}
lalala
{% else %}
meh
{% endifhasperm %}
{% if hasperm "poll_permission.change_poll" request.user %}
lalala
{% else %}
meh
{% endifhasperm %}
"""
return PermissionComparisonNode.handle_token(parser, token)
class PermissionFormNode(ResolverNode):
@classmethod
def handle_token(cls, parser, token, approved):
bits = token.contents.split()
tag_name = bits[0]
kwargs = {
'obj': cls.next_bit_for(bits, 'for'),
'perm': cls.next_bit_for(bits, 'using', None),
'template_name': cls.next_bit_for(bits, 'with', ''),
'approved': approved,
}
return cls(**kwargs)
def __init__(self, obj, perm=None, approved=False, template_name=None):
self.obj = obj
self.perm = perm
self.approved = approved
self.template_name = template_name
def render(self, context):
obj = self.resolve(self.obj, context)
perm = self.resolve(self.perm, context)
if self.template_name:
template_name = [self.resolve(obj, context) for obj in self.template_name.split(',')]
else:
template_name = 'authority/permission_form.html'
request = context['request']
extra_context = {}
if self.approved:
if (request.user.is_authenticated() and
request.user.has_perm('authority.add_permission')):
extra_context = {
'form_url': url_for_obj('authority-add-permission', obj),
'next': request.build_absolute_uri(),
'approved': self.approved,
'form': UserPermissionForm(perm, obj, approved=self.approved,
initial=dict(codename=perm)),
}
else:
if request.user.is_authenticated() and not request.user.is_superuser:
extra_context = {
'form_url': url_for_obj('authority-add-permission-request', obj),
'next': request.build_absolute_uri(),
'approved': self.approved,
'form': UserPermissionForm(perm, obj,
approved=self.approved, initial=dict(
codename=perm, user=request.user.username)),
}
return template.loader.render_to_string(template_name, extra_context,
context_instance=template.RequestContext(request))
@register.tag
def permission_form(parser, token):
"""
Renders an "add permissions" form for the given object. If no object
is given it will render a select box to choose from.
Syntax::
{% permission_form for OBJ using PERMISSION_LABEL.CHECK_NAME [with TEMPLATE] %}
{% permission_form for lesson using "lesson_permission.add_lesson" %}
"""
return PermissionFormNode.handle_token(parser, token, approved=True)
@register.tag
def permission_request_form(parser, token):
"""
Renders an "add permissions" form for the given object. If no object
is given it will render a select box to choose from.
Syntax::
{% permission_request_form for OBJ and PERMISSION_LABEL.CHECK_NAME [with TEMPLATE] %}
{% permission_request_form for lesson using "lesson_permission.add_lesson" with "authority/permission_request_form.html" %}
"""
return PermissionFormNode.handle_token(parser, token, approved=False)
class PermissionsForObjectNode(ResolverNode):
@classmethod
def handle_token(cls, parser, token, approved, name):
bits = token.contents.split()
tag_name = bits[0]
kwargs = {
'obj': cls.next_bit_for(bits, tag_name),
'user': cls.next_bit_for(bits, 'for'),
'var_name': cls.next_bit_for(bits, 'as', name),
'approved': approved,
}
return cls(**kwargs)
def __init__(self, obj, user, var_name, approved, perm=None):
self.obj = obj
self.user = user
self.perm = perm
self.var_name = var_name
self.approved = approved
def render(self, context):
obj = self.resolve(self.obj, context)
var_name = self.resolve(self.var_name, context)
user = self.resolve(self.user, context)
perms = []
if not isinstance(user, AnonymousUser):
perms = Permission.objects.for_object(obj, self.approved)
if isinstance(user, User):
perms = perms.filter(user=user)
context[var_name] = perms
return ''
@register.tag
def get_permissions(parser, token):
"""
Retrieves all permissions associated with the given obj and user
and assigns the result to a context variable.
Syntax::
{% get_permissions obj %}
{% for perm in permissions %}
{{ perm }}
{% endfor %}
{% get_permissions obj as "my_permissions" %}
{% get_permissions obj for request.user as "my_permissions" %}
"""
return PermissionsForObjectNode.handle_token(parser, token, approved=True,
name='"permissions"')
@register.tag
def get_permission_requests(parser, token):
"""
Retrieves all permissions requests associated with the given obj and user
and assigns the result to a context variable.
Syntax::
{% get_permission_requests obj %}
{% for perm in permissions %}
{{ perm }}
{% endfor %}
{% get_permission_requests obj as "my_permissions" %}
{% get_permission_requests obj for request.user as "my_permissions" %}
"""
return PermissionsForObjectNode.handle_token(parser, token,
approved=False,
name='"permission_requests"')
class PermissionForObjectNode(ResolverNode):
@classmethod
def handle_token(cls, parser, token, approved, name):
bits = token.contents.split()
tag_name = bits[0]
kwargs = {
'perm': cls.next_bit_for(bits, tag_name),
'user': cls.next_bit_for(bits, 'for'),
'objs': cls.next_bit_for(bits, 'and'),
'var_name': cls.next_bit_for(bits, 'as', name),
'approved': approved,
}
return cls(**kwargs)
def __init__(self, perm, user, objs, approved, var_name):
self.perm = perm
self.user = user
self.objs = objs
self.var_name = var_name
self.approved = approved
def render(self, context):
objs = [self.resolve(obj, context) for obj in self.objs.split(',')]
var_name = self.resolve(self.var_name, context)
perm = self.resolve(self.perm, context)
user = self.resolve(self.user, context)
granted = False
if not isinstance(user, AnonymousUser):
if self.approved:
check = get_check(user, perm)
if check is not None:
granted = check(*objs)
else:
check = permissions.BasePermission(user=user)
for obj in objs:
granted = check.requested_perm(perm, obj)
if granted:
break
context[var_name] = granted
return ''
@register.tag
def get_permission(parser, token):
"""
Performs a permission check with the given signature, user and objects
and assigns the result to a context variable.
Syntax::
{% get_permission PERMISSION_LABEL.CHECK_NAME for USER and *OBJS [as VARNAME] %}
{% get_permission "poll_permission.change_poll" for request.user and poll as "is_allowed" %}
{% get_permission "poll_permission.change_poll" for request.user and poll,second_poll as "is_allowed" %}
{% if is_allowed %}
I've got ze power to change ze pollllllzzz. Muahahaa.
{% else %}
Meh. No power for meeeee.
{% endif %}
"""
return PermissionForObjectNode.handle_token(parser, token,
approved=True,
name='"permission"')
@register.tag
def get_permission_request(parser, token):
"""
Performs a permission request check with the given signature, user and objects
and assigns the result to a context variable.
Syntax::
{% get_permission_request PERMISSION_LABEL.CHECK_NAME for USER and *OBJS [as VARNAME] %}
{% get_permission_request "poll_permission.change_poll" for request.user and poll as "asked_for_permissio" %}
{% get_permission_request "poll_permission.change_poll" for request.user and poll,second_poll as "asked_for_permissio" %}
{% if asked_for_permissio %}
Dude, you already asked for permission!
{% else %}
Oh, please fill out this 20 page form and sign here.
{% endif %}
"""
return PermissionForObjectNode.handle_token(parser, token,
approved=False,
name='"permission_request"')
def base_link(context, perm, view_name):
return {
'next': context['request'].build_absolute_uri(),
'url': reverse(view_name, kwargs={'permission_pk': perm.pk,}),
}
@register.inclusion_tag('authority/permission_delete_link.html', takes_context=True)
def permission_delete_link(context, perm):
"""
Renders a html link to the delete view of the given permission. Returns
no content if the request-user has no permission to delete foreign
permissions.
"""
user = context['request'].user
if user.is_authenticated():
if user.has_perm('authority.delete_foreign_permissions') \
or user.pk == perm.creator.pk:
return base_link(context, perm, 'authority-delete-permission')
return {'url': None}
@register.inclusion_tag('authority/permission_request_delete_link.html', takes_context=True)
def permission_request_delete_link(context, perm):
"""
Renders a html link to the delete view of the given permission request.
Returns no content if the request-user has no permission to delete foreign
permissions.
"""
user = context['request'].user
if user.is_authenticated():
link_kwargs = base_link(context, perm,
'authority-delete-permission-request')
if user.has_perm('authority.delete_permission'):
link_kwargs['is_requestor'] = False
return link_kwargs
if not perm.approved and perm.user == user:
link_kwargs['is_requestor'] = True
return link_kwargs
return {'url': None}
@register.inclusion_tag('authority/permission_request_approve_link.html', takes_context=True)
def permission_request_approve_link(context, perm):
"""
Renders a html link to the approve view of the given permission request.
Returns no content if the request-user has no permission to delete foreign
permissions.
"""
user = context['request'].user
if user.is_authenticated():
if user.has_perm('authority.approve_permission_requests'):
return base_link(context, perm,
'authority-approve-permission-request')
return {'url': None}
| bsd-3-clause |
bossjones/scarlett | scarlett/listener/gstlistenerfsm.py | 1 | 17131 | # -*- coding: UTF-8 -*-
import scarlett
import pygst
pygst.require('0.10')
import gobject
gobject.threads_init()
import dbus
import dbus.service
# TODO: Figure out if we need this or not, re dbus threading
# from dbus.mainloop.glib import DBusGMainLoop
# dbus_loop = DBusGMainLoop(set_as_default=True)
# dsession = SessionBus(mainloop=dbus_loop)
dbus.mainloop.glib.threads_init()
import gst
import os
import threading
import time
import logging
from transitions import Machine
from scarlett.events import scarlett_event
from colorama import init, Fore, Back, Style
from scarlett.constants import (
EVENT_SCARLETT_START,
EVENT_SCARLETT_STOP,
EVENT_STATE_CHANGED,
EVENT_TIME_CHANGED,
EVENT_CALL_SERVICE,
EVENT_SERVICE_EXECUTED,
EVENT_SERVICE_REGISTER,
EVENT_PLATFORM_DISCOVERED,
EVENT_SCARLETT_SAY,
EVENT_BRAIN_UPDATE,
EVENT_BRAIN_CHECK
)
SCARLETT_ROLE = 'listener'
CORE_OBJECT = 'GstlistenerFSM'
_INSTANCE = None
logging.basicConfig(level=logging.DEBUG,
format='(%(threadName)-9s) %(message)s',)
def setup_core(ss):
# logging.info("attempting to setup GstlistenerFSM")
global _INSTANCE
if _INSTANCE is None:
_INSTANCE = GstlistenerFSM()
return _INSTANCE
class GstlistenerFSM(gobject.GObject):
"""GstListener with FSM. Preforms pocketsphinx speech recognition.
"""
__gproperties__ = {
'override_parse': (
gobject.TYPE_STRING, # type
'Override parse', # nick name
# description
'Allows you to override what the gst parse line looks like',
'', # default value
gobject.PARAM_READWRITE
),
'failed': (
gobject.TYPE_INT, # type
'Failed', # nick name
'Number of times recognition failed', # description
0, # min value
5, # max value
0, # default value
gobject.PARAM_READWRITE
),
'kw_found': (
gobject.TYPE_INT, # type
'Keyword Match', # nick name
'int value for keyword', # description
0, # min value
5, # max value
0, # default value
gobject.PARAM_READWRITE
)
}
__gsignals__ = {
'gst-started': (
gobject.SIGNAL_RUN_LAST,
gobject.TYPE_NONE,
(gobject.TYPE_STRING,)
),
'kw-found-ps': (
gobject.SIGNAL_RUN_LAST,
gobject.TYPE_NONE,
(gobject.TYPE_STRING,)
),
'failed-ps': (
gobject.SIGNAL_RUN_LAST,
gobject.TYPE_NONE,
(gobject.TYPE_STRING,)
)
}
capability = []
states = ['initalize', 'ready', 'running',
'is_checking_states', 'time_change', 'done_checking_states']
DBUS_NAME = 'org.scarlettapp.scarlettdaemon'
DBUS_PATH = '/org/scarlettapp/scarlettdaemon'
def __init__(self, *args, **kwargs):
gobject.GObject.__init__(self)
# managed by gproperties
self.override_parse = ''
self.failed = 0
self.kw_found = 0
self.wit_thread = None
self.loop = None
self.config = scarlett.config
self.name = 'GstlistenerFSM'
# Initalize the state machine
self.machine = Machine(
model=self,
# TODO: Fix this, its def not working
states=self.states,
initial='initalize')
# startup transition
self.machine.add_transition(
trigger='startup',
source='initalize',
dest='ready')
# checking_states transition
self.machine.add_transition(
trigger='checking_states',
source='ready',
dest='is_checking_states',
conditions=['is_ready'])
# array / dict of state machines connected to scarlett
self._machines = {}
# Check interval, in seconds
self.interval = 1
# bus = dbus.SessionBus()
# self.remote = bus.get_object(GstlistenerFSM.DBUS_NAME,
# GstlistenerFSM.DBUS_PATH)
# "/usr/local/share/pocketsphinx/model/hmm/en_US/hub4wsj_sc_8k"
self.ps_hmm = self.get_hmm_full_path()
self.ps_dict = self.get_dict_full_path()
self.ps_lm = self.get_lm_full_path()
self.ps_device = self.config.get('audio', 'usb_input_device')
self.speech_system = self.config.get('speech', 'system')
# default, use what we have set
self.parse_launch_array = self._get_pocketsphinx_definition(
self.override_parse)
scarlett.log.debug(
Fore.YELLOW +
'Initializing gst-parse-launch -------->')
self.pipeline = gst.parse_launch(
' ! '.join(self.parse_launch_array))
listener = self.pipeline.get_by_name('listener')
listener.connect('result', self.__result__)
listener.set_property('configured', True)
scarlett.log.debug(
Fore.YELLOW +
"Initializing connection to vader element -------->")
# TODO: Play with vader object some more
# vader = self.pipeline.get_by_name("vader")
# vader.connect("vader-start", self._on_vader_start)
# vader.connect("vader-stop", self._on_vader_stop)
scarlett.log.debug(Fore.YELLOW + "Initializing Bus -------->")
bus = self.pipeline.get_bus()
bus.add_signal_watch()
scarlett.log.debug(Fore.YELLOW + "Sending Message to Bus ---------->")
bus.connect('message::application', self.__application_message__)
# logging.debug('running with %s and %s', args, kwargs)
# TODO: Uncomment this when we're ready to try this
ss_listener = threading.Thread(name='Scarlett Listener',target=self.start_listener)
ss_listener.daemon = True
ss_listener.start()
# GObject translates all the underscore characters to hyphen
# characters so if you have a property called background_color,
# its internal and valid name will be background-color.
def do_get_property(self, property):
if property.name == 'kw-found':
return self.kw_found
elif property.name == 'failed':
return self.failed
elif property.name == 'override-parse':
return self.override_parse
else:
raise AttributeError('unknown property %s' % property.name)
def do_set_property(self, property, value):
if property == 'kw-found':
self.kw_found = value
elif property == 'failed':
self.failed = value
elif property == 'override-parse':
self.override_parse = value
else:
raise AttributeError('unknown property %s' % property)
def start_listener(self):
global CORE_OBJECT
# register service start
listener_connect = scarlett_event(
'service_state',
data=CORE_OBJECT
)
# idle_emit since this is something with low priority
gobject.idle_add(
self.emit,
'gst-started', listener_connect
)
self.pipeline.set_state(gst.STATE_PLAYING)
scarlett.log.debug(
Fore.YELLOW +
'KEYWORD: ' +
self.config.get('scarlett', 'owner')
)
self.loop = gobject.MainLoop()
self.loop.run()
def stop(self):
self.pipeline.set_state(gst.STATE_NULL)
if self.loop is not None:
self.loop.quit()
def scarlett_start_listen(self):
self.pipeline.set_state(gst.STATE_PLAYING)
def scarlett_stop_listen(self):
self.pipeline.set_state(gst.STATE_READY)
def scarlett_pause_listen(self):
self.pipeline.set_state(gst.STATE_PAUSED)
def scarlett_reset_listen(self):
self.do_set_property('failed', 0)
self.do_set_property('kw-found', 0)
def partial_result(self, asr, text, uttid):
"""Forward partial result signals on the bus to the main thread."""
pass
def result(self, hyp, uttid):
"""Forward result signals on the bus to the main thread."""
scarlett.log.debug(Fore.YELLOW + "Inside result function")
if hyp in self.config.get('scarlett', 'keywords'):
scarlett.log.debug(
Fore.YELLOW +
"HYP-IS-SOMETHING: " +
hyp +
"\n\n\n")
scarlett.log.debug(
Fore.YELLOW +
"UTTID-IS-SOMETHING:" +
uttid +
"\n")
self.do_set_property('failed', 0)
self.do_set_property('kw-found', 1)
# TODO: Change this to emit to main thread
# scarlett.basics.voice.play_block('pi-listening')
else:
failed_temp = self.do_get_property('failed') + 1
self.do_set_property('failed', failed_temp)
scarlett.log.debug(
Fore.YELLOW +
"self.failed = %i" %
(self.do_get_property('failed')))
if self.do_get_property('failed') > 4:
# reset pipline
self.scarlett_reset_listen()
# TODO: Change this to emit text data to main thread
# ScarlettTalk.speak(
# " %s , if you need me, just say my name." %
# (self.config.get('scarlett', 'owner')))
def run_cmd(self, hyp, uttid):
scarlett.log.debug(Fore.YELLOW + "Inside run_cmd function")
scarlett.log.debug(Fore.YELLOW + "KEYWORD IDENTIFIED BABY")
scarlett.log.debug(
Fore.RED +
"self.kw_found = %i" %
(self.do_get_property('kw-found')))
if hyp == 'CANCEL':
self.cancel_listening()
else:
# TODO: Change this into emit hypothesis instead
hyp_event = scarlett_event(
"listener_hyp",
data=hyp
)
self.emit('kw-found-ps', hyp_event)
current_kw_identified = self.do_get_property('kw-found')
self.do_set_property('kw-found', current_kw_identified)
scarlett.log.debug(
Fore.RED +
"AFTER run_cmd, self.kw_found = %i" %
(self.do_get_property('kw-found')))
def hello(self):
print 'hello hello hello!'
def listen(self, valve, vader):
scarlett.log.debug(Fore.YELLOW + "Inside listen function")
# TODO: have this emit pi-listening to mainthread
# scarlett.basics.voice.play_block('pi-listening')
valve.set_property('drop', False)
valve.set_property('drop', True)
def cancel_listening(self):
scarlett.log.debug(Fore.YELLOW + "Inside cancel_listening function")
self.scarlett_reset_listen()
scarlett.log.debug(Fore.YELLOW + "self.failed = %i" % (self.failed))
scarlett.log.debug(
Fore.RED +
"self.keyword_identified = %i" %
(self.do_get_property('kw-found')))
def get_hmm_full_path(self):
if os.environ.get('SCARLETT_HMM'):
_hmm_full_path = os.environ.get('SCARLETT_HMM')
else:
_hmm_full_path = self.config.get('pocketsphinx', 'hmm')
return _hmm_full_path
def get_lm_full_path(self):
if os.environ.get('SCARLETT_LM'):
_lm_full_path = os.environ.get('SCARLETT_LM')
else:
_lm_full_path = self.config.get('pocketsphinx', 'lm')
return _lm_full_path
def get_dict_full_path(self):
if os.environ.get('SCARLETT_DICT'):
_dict_full_path = os.environ.get('SCARLETT_DICT')
else:
_dict_full_path = self.config.get('pocketsphinx', 'dict')
return _dict_full_path
def get_pipeline(self):
scarlett.log.debug(Fore.YELLOW + "Inside get_pipeline")
return self.pipeline
def get_voice(self):
scarlett.log.debug(Fore.YELLOW + "Inside get_voice")
return self.voice
def get_pipeline_state(self):
return self.pipeline.get_state()
def _get_pocketsphinx_definition(self, override_parse):
scarlett.log.debug(Fore.YELLOW + "Inside _get_pocketsphinx_definition")
"""Return ``pocketsphinx`` definition for :func:`gst.parse_launch`."""
# default, use what we have set
if override_parse == '':
return [
'alsasrc device=' +
self.ps_device,
'queue silent=false leaky=2 max-size-buffers=0 max-size-time=0 max-size-bytes=0', # noqa
'audioconvert',
'audioresample',
'audio/x-raw-int, rate=16000, width=16, depth=16, channels=1',
'audioresample',
'audio/x-raw-int, rate=8000',
'vader name=vader auto-threshold=true',
'pocketsphinx lm=' +
self.ps_lm +
' dict=' +
self.ps_dict +
' hmm=' +
self.ps_hmm +
' name=listener',
'fakesink dump=1']
# NOTE, I commented out the refrence to the tee
# 'fakesink dump=1 t.'
else:
return override_parse
def _get_vader_definition(self):
scarlett.log.debug(Fore.YELLOW + "Inside _get_vader_definition")
"""Return ``vader`` definition for :func:`gst.parse_launch`."""
# source: https://github.com/bossjones/eshayari/blob/master/eshayari/application.py # noqa
# Convert noise level from spin button range [0,32768] to gstreamer
# element's range [0,1]. Likewise, convert silence from spin button's
# milliseconds to gstreamer element's nanoseconds.
# MY DEFAULT VADER DEFINITON WAS: vader name=vader auto-threshold=true
# vader name=vader auto-threshold=true
noise = 256 / 32768
silence = 300 * 1000000
return ("vader "
+ "name=vader "
+ "auto-threshold=false "
+ "threshold=%.9f " % noise
+ "run-length=%d " % silence
)
def _on_vader_start(self, vader, pos):
scarlett.log.debug(Fore.YELLOW + "Inside _on_vader_start")
"""Send start position as a message on the bus."""
import gst
struct = gst.Structure("start")
pos = pos / 1000000000 # ns to s
struct.set_value("start", pos)
vader.post_message(gst.message_new_application(vader, struct))
def _on_vader_stop(self, vader, pos):
scarlett.log.debug(Fore.YELLOW + "Inside _on_vader_stop")
"""Send stop position as a message on the bus."""
import gst
struct = gst.Structure("stop")
pos = pos / 1000000000 # ns to s
struct.set_value("stop", pos)
def __result__(self, listener, text, uttid):
"""We're inside __result__"""
scarlett.log.debug(Fore.YELLOW + "Inside __result__")
import gst
struct = gst.Structure('result')
struct.set_value('hyp', text)
struct.set_value('uttid', uttid)
listener.post_message(gst.message_new_application(listener, struct))
def __partial_result__(self, listener, text, uttid):
"""We're inside __partial_result__"""
scarlett.log.debug(Fore.YELLOW + "Inside __partial_result__")
struct = gst.Structure('partial_result')
struct.set_value('hyp', text)
struct.set_value('uttid', uttid)
listener.post_message(gst.message_new_application(listener, struct))
def __run_cmd__(self, listener, text, uttid):
"""We're inside __run_cmd__"""
import gst
scarlett.log.debug(Fore.YELLOW + "Inside __run_cmd__")
struct = gst.Structure('result')
struct.set_value('hyp', text)
struct.set_value('uttid', uttid)
listener.post_message(gst.message_new_application(listener, struct))
def __application_message__(self, bus, msg):
msgtype = msg.structure.get_name()
scarlett.log.debug(Fore.YELLOW + "msgtype: " + msgtype)
if msgtype == 'partial_result':
self.partial_result(msg.structure['hyp'], msg.structure['uttid'])
elif msgtype == 'result':
if self.do_get_property('kw-found') == 1:
self.run_cmd(msg.structure['hyp'], msg.structure['uttid'])
else:
self.result(msg.structure['hyp'], msg.structure['uttid'])
elif msgtype == 'run_cmd':
self.run_cmd(msg.structure['hyp'], msg.structure['uttid'])
elif msgtype == gst.MESSAGE_EOS:
pass
# TODO: SEE IF WE NEED THIS
# self.pipeline.set_state(gst.STATE_NULL)
elif msgtype == gst.MESSAGE_ERROR:
(err, debug) = msgtype.parse_error()
scarlett.log.debug(Fore.RED + "Error: %s" % err, debug)
pass
# Register to be able to emit signals
gobject.type_register(GstlistenerFSM)
| mit |
bsmr-ansible/ansible-modules-extras | windows/win_iis_webapppool.py | 153 | 3531 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# (c) 2015, Henrik Wallström <henrik@wallstroms.nu>
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
DOCUMENTATION = '''
---
module: win_iis_webapppool
version_added: "2.0"
short_description: Configures a IIS Web Application Pool.
description:
- Creates, Removes and configures a IIS Web Application Pool
options:
name:
description:
- Names of application pool
required: true
default: null
aliases: []
state:
description:
- State of the binding
choices:
- absent
- stopped
- started
- restarted
required: false
default: null
aliases: []
attributes:
description:
- Application Pool attributes from string where attributes are seperated by a pipe and attribute name/values by colon Ex. "foo:1|bar:2"
required: false
default: null
aliases: []
author: Henrik Wallström
'''
EXAMPLES = '''
# This return information about an existing application pool
$ansible -i inventory -m win_iis_webapppool -a "name='DefaultAppPool'" windows
host | success >> {
"attributes": {},
"changed": false,
"info": {
"attributes": {
"CLRConfigFile": "",
"applicationPoolSid": "S-1-5-82-3006700770-424185619-1745488364-794895919-4004696415",
"autoStart": true,
"enable32BitAppOnWin64": false,
"enableConfigurationOverride": true,
"managedPipelineMode": 0,
"managedRuntimeLoader": "webengine4.dll",
"managedRuntimeVersion": "v4.0",
"name": "DefaultAppPool",
"passAnonymousToken": true,
"queueLength": 1000,
"startMode": 0,
"state": 1
},
"name": "DefaultAppPool",
"state": "Started"
}
}
# This creates a new application pool in 'Started' state
$ ansible -i inventory -m win_iis_webapppool -a "name='AppPool' state=started" windows
# This stoppes an application pool
$ ansible -i inventory -m win_iis_webapppool -a "name='AppPool' state=stopped" windows
# This restarts an application pool
$ ansible -i inventory -m win_iis_webapppool -a "name='AppPool' state=restart" windows
# This restarts an application pool
$ ansible -i inventory -m win_iis_webapppool -a "name='AppPool' state=restart" windows
# This change application pool attributes without touching state
$ ansible -i inventory -m win_iis_webapppool -a "name='AppPool' attributes='managedRuntimeVersion:v4.0|autoStart:false'" windows
# This creates an application pool and sets attributes
$ ansible -i inventory -m win_iis_webapppool -a "name='AnotherAppPool' state=started attributes='managedRuntimeVersion:v4.0|autoStart:false'" windows
# Playbook example
---
- name: App Pool with .NET 4.0
win_iis_webapppool:
name: 'AppPool'
state: started
attributes: managedRuntimeVersion:v4.0
register: webapppool
'''
| gpl-3.0 |
sexmachine/msm | Documentation/target/tcm_mod_builder.py | 2358 | 40707 | #!/usr/bin/python
# The TCM v4 multi-protocol fabric module generation script for drivers/target/$NEW_MOD
#
# Copyright (c) 2010 Rising Tide Systems
# Copyright (c) 2010 Linux-iSCSI.org
#
# Author: nab@kernel.org
#
import os, sys
import subprocess as sub
import string
import re
import optparse
tcm_dir = ""
fabric_ops = []
fabric_mod_dir = ""
fabric_mod_port = ""
fabric_mod_init_port = ""
def tcm_mod_err(msg):
print msg
sys.exit(1)
def tcm_mod_create_module_subdir(fabric_mod_dir_var):
if os.path.isdir(fabric_mod_dir_var) == True:
return 1
print "Creating fabric_mod_dir: " + fabric_mod_dir_var
ret = os.mkdir(fabric_mod_dir_var)
if ret:
tcm_mod_err("Unable to mkdir " + fabric_mod_dir_var)
return
def tcm_mod_build_FC_include(fabric_mod_dir_var, fabric_mod_name):
global fabric_mod_port
global fabric_mod_init_port
buf = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_base.h"
print "Writing file: " + f
p = open(f, 'w');
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "#define " + fabric_mod_name.upper() + "_VERSION \"v0.1\"\n"
buf += "#define " + fabric_mod_name.upper() + "_NAMELEN 32\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_nacl {\n"
buf += " /* Binary World Wide unique Port Name for FC Initiator Nport */\n"
buf += " u64 nport_wwpn;\n"
buf += " /* ASCII formatted WWPN for FC Initiator Nport */\n"
buf += " char nport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_nodeacl() */\n"
buf += " struct se_node_acl se_node_acl;\n"
buf += "};\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_tpg {\n"
buf += " /* FC lport target portal group tag for TCM */\n"
buf += " u16 lport_tpgt;\n"
buf += " /* Pointer back to " + fabric_mod_name + "_lport */\n"
buf += " struct " + fabric_mod_name + "_lport *lport;\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tpg() */\n"
buf += " struct se_portal_group se_tpg;\n"
buf += "};\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_lport {\n"
buf += " /* SCSI protocol the lport is providing */\n"
buf += " u8 lport_proto_id;\n"
buf += " /* Binary World Wide unique Port Name for FC Target Lport */\n"
buf += " u64 lport_wwpn;\n"
buf += " /* ASCII formatted WWPN for FC Target Lport */\n"
buf += " char lport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_lport() */\n"
buf += " struct se_wwn lport_wwn;\n"
buf += "};\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
fabric_mod_port = "lport"
fabric_mod_init_port = "nport"
return
def tcm_mod_build_SAS_include(fabric_mod_dir_var, fabric_mod_name):
global fabric_mod_port
global fabric_mod_init_port
buf = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_base.h"
print "Writing file: " + f
p = open(f, 'w');
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "#define " + fabric_mod_name.upper() + "_VERSION \"v0.1\"\n"
buf += "#define " + fabric_mod_name.upper() + "_NAMELEN 32\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_nacl {\n"
buf += " /* Binary World Wide unique Port Name for SAS Initiator port */\n"
buf += " u64 iport_wwpn;\n"
buf += " /* ASCII formatted WWPN for Sas Initiator port */\n"
buf += " char iport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_nodeacl() */\n"
buf += " struct se_node_acl se_node_acl;\n"
buf += "};\n\n"
buf += "struct " + fabric_mod_name + "_tpg {\n"
buf += " /* SAS port target portal group tag for TCM */\n"
buf += " u16 tport_tpgt;\n"
buf += " /* Pointer back to " + fabric_mod_name + "_tport */\n"
buf += " struct " + fabric_mod_name + "_tport *tport;\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tpg() */\n"
buf += " struct se_portal_group se_tpg;\n"
buf += "};\n\n"
buf += "struct " + fabric_mod_name + "_tport {\n"
buf += " /* SCSI protocol the tport is providing */\n"
buf += " u8 tport_proto_id;\n"
buf += " /* Binary World Wide unique Port Name for SAS Target port */\n"
buf += " u64 tport_wwpn;\n"
buf += " /* ASCII formatted WWPN for SAS Target port */\n"
buf += " char tport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tport() */\n"
buf += " struct se_wwn tport_wwn;\n"
buf += "};\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
fabric_mod_port = "tport"
fabric_mod_init_port = "iport"
return
def tcm_mod_build_iSCSI_include(fabric_mod_dir_var, fabric_mod_name):
global fabric_mod_port
global fabric_mod_init_port
buf = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_base.h"
print "Writing file: " + f
p = open(f, 'w');
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "#define " + fabric_mod_name.upper() + "_VERSION \"v0.1\"\n"
buf += "#define " + fabric_mod_name.upper() + "_NAMELEN 32\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_nacl {\n"
buf += " /* ASCII formatted InitiatorName */\n"
buf += " char iport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_nodeacl() */\n"
buf += " struct se_node_acl se_node_acl;\n"
buf += "};\n\n"
buf += "struct " + fabric_mod_name + "_tpg {\n"
buf += " /* iSCSI target portal group tag for TCM */\n"
buf += " u16 tport_tpgt;\n"
buf += " /* Pointer back to " + fabric_mod_name + "_tport */\n"
buf += " struct " + fabric_mod_name + "_tport *tport;\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tpg() */\n"
buf += " struct se_portal_group se_tpg;\n"
buf += "};\n\n"
buf += "struct " + fabric_mod_name + "_tport {\n"
buf += " /* SCSI protocol the tport is providing */\n"
buf += " u8 tport_proto_id;\n"
buf += " /* ASCII formatted TargetName for IQN */\n"
buf += " char tport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tport() */\n"
buf += " struct se_wwn tport_wwn;\n"
buf += "};\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
fabric_mod_port = "tport"
fabric_mod_init_port = "iport"
return
def tcm_mod_build_base_includes(proto_ident, fabric_mod_dir_val, fabric_mod_name):
if proto_ident == "FC":
tcm_mod_build_FC_include(fabric_mod_dir_val, fabric_mod_name)
elif proto_ident == "SAS":
tcm_mod_build_SAS_include(fabric_mod_dir_val, fabric_mod_name)
elif proto_ident == "iSCSI":
tcm_mod_build_iSCSI_include(fabric_mod_dir_val, fabric_mod_name)
else:
print "Unsupported proto_ident: " + proto_ident
sys.exit(1)
return
def tcm_mod_build_configfs(proto_ident, fabric_mod_dir_var, fabric_mod_name):
buf = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_configfs.c"
print "Writing file: " + f
p = open(f, 'w');
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "#include <linux/module.h>\n"
buf += "#include <linux/moduleparam.h>\n"
buf += "#include <linux/version.h>\n"
buf += "#include <generated/utsrelease.h>\n"
buf += "#include <linux/utsname.h>\n"
buf += "#include <linux/init.h>\n"
buf += "#include <linux/slab.h>\n"
buf += "#include <linux/kthread.h>\n"
buf += "#include <linux/types.h>\n"
buf += "#include <linux/string.h>\n"
buf += "#include <linux/configfs.h>\n"
buf += "#include <linux/ctype.h>\n"
buf += "#include <asm/unaligned.h>\n\n"
buf += "#include <target/target_core_base.h>\n"
buf += "#include <target/target_core_fabric.h>\n"
buf += "#include <target/target_core_fabric_configfs.h>\n"
buf += "#include <target/target_core_configfs.h>\n"
buf += "#include <target/configfs_macros.h>\n\n"
buf += "#include \"" + fabric_mod_name + "_base.h\"\n"
buf += "#include \"" + fabric_mod_name + "_fabric.h\"\n\n"
buf += "/* Local pointer to allocated TCM configfs fabric module */\n"
buf += "struct target_fabric_configfs *" + fabric_mod_name + "_fabric_configfs;\n\n"
buf += "static struct se_node_acl *" + fabric_mod_name + "_make_nodeacl(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " struct config_group *group,\n"
buf += " const char *name)\n"
buf += "{\n"
buf += " struct se_node_acl *se_nacl, *se_nacl_new;\n"
buf += " struct " + fabric_mod_name + "_nacl *nacl;\n"
if proto_ident == "FC" or proto_ident == "SAS":
buf += " u64 wwpn = 0;\n"
buf += " u32 nexus_depth;\n\n"
buf += " /* " + fabric_mod_name + "_parse_wwn(name, &wwpn, 1) < 0)\n"
buf += " return ERR_PTR(-EINVAL); */\n"
buf += " se_nacl_new = " + fabric_mod_name + "_alloc_fabric_acl(se_tpg);\n"
buf += " if (!se_nacl_new)\n"
buf += " return ERR_PTR(-ENOMEM);\n"
buf += "//#warning FIXME: Hardcoded nexus depth in " + fabric_mod_name + "_make_nodeacl()\n"
buf += " nexus_depth = 1;\n"
buf += " /*\n"
buf += " * se_nacl_new may be released by core_tpg_add_initiator_node_acl()\n"
buf += " * when converting a NodeACL from demo mode -> explict\n"
buf += " */\n"
buf += " se_nacl = core_tpg_add_initiator_node_acl(se_tpg, se_nacl_new,\n"
buf += " name, nexus_depth);\n"
buf += " if (IS_ERR(se_nacl)) {\n"
buf += " " + fabric_mod_name + "_release_fabric_acl(se_tpg, se_nacl_new);\n"
buf += " return se_nacl;\n"
buf += " }\n"
buf += " /*\n"
buf += " * Locate our struct " + fabric_mod_name + "_nacl and set the FC Nport WWPN\n"
buf += " */\n"
buf += " nacl = container_of(se_nacl, struct " + fabric_mod_name + "_nacl, se_node_acl);\n"
if proto_ident == "FC" or proto_ident == "SAS":
buf += " nacl->" + fabric_mod_init_port + "_wwpn = wwpn;\n"
buf += " /* " + fabric_mod_name + "_format_wwn(&nacl->" + fabric_mod_init_port + "_name[0], " + fabric_mod_name.upper() + "_NAMELEN, wwpn); */\n\n"
buf += " return se_nacl;\n"
buf += "}\n\n"
buf += "static void " + fabric_mod_name + "_drop_nodeacl(struct se_node_acl *se_acl)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_nacl *nacl = container_of(se_acl,\n"
buf += " struct " + fabric_mod_name + "_nacl, se_node_acl);\n"
buf += " core_tpg_del_initiator_node_acl(se_acl->se_tpg, se_acl, 1);\n"
buf += " kfree(nacl);\n"
buf += "}\n\n"
buf += "static struct se_portal_group *" + fabric_mod_name + "_make_tpg(\n"
buf += " struct se_wwn *wwn,\n"
buf += " struct config_group *group,\n"
buf += " const char *name)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + "*" + fabric_mod_port + " = container_of(wwn,\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + ", " + fabric_mod_port + "_wwn);\n\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg;\n"
buf += " unsigned long tpgt;\n"
buf += " int ret;\n\n"
buf += " if (strstr(name, \"tpgt_\") != name)\n"
buf += " return ERR_PTR(-EINVAL);\n"
buf += " if (strict_strtoul(name + 5, 10, &tpgt) || tpgt > UINT_MAX)\n"
buf += " return ERR_PTR(-EINVAL);\n\n"
buf += " tpg = kzalloc(sizeof(struct " + fabric_mod_name + "_tpg), GFP_KERNEL);\n"
buf += " if (!tpg) {\n"
buf += " printk(KERN_ERR \"Unable to allocate struct " + fabric_mod_name + "_tpg\");\n"
buf += " return ERR_PTR(-ENOMEM);\n"
buf += " }\n"
buf += " tpg->" + fabric_mod_port + " = " + fabric_mod_port + ";\n"
buf += " tpg->" + fabric_mod_port + "_tpgt = tpgt;\n\n"
buf += " ret = core_tpg_register(&" + fabric_mod_name + "_fabric_configfs->tf_ops, wwn,\n"
buf += " &tpg->se_tpg, (void *)tpg,\n"
buf += " TRANSPORT_TPG_TYPE_NORMAL);\n"
buf += " if (ret < 0) {\n"
buf += " kfree(tpg);\n"
buf += " return NULL;\n"
buf += " }\n"
buf += " return &tpg->se_tpg;\n"
buf += "}\n\n"
buf += "static void " + fabric_mod_name + "_drop_tpg(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n\n"
buf += " core_tpg_deregister(se_tpg);\n"
buf += " kfree(tpg);\n"
buf += "}\n\n"
buf += "static struct se_wwn *" + fabric_mod_name + "_make_" + fabric_mod_port + "(\n"
buf += " struct target_fabric_configfs *tf,\n"
buf += " struct config_group *group,\n"
buf += " const char *name)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + ";\n"
if proto_ident == "FC" or proto_ident == "SAS":
buf += " u64 wwpn = 0;\n\n"
buf += " /* if (" + fabric_mod_name + "_parse_wwn(name, &wwpn, 1) < 0)\n"
buf += " return ERR_PTR(-EINVAL); */\n\n"
buf += " " + fabric_mod_port + " = kzalloc(sizeof(struct " + fabric_mod_name + "_" + fabric_mod_port + "), GFP_KERNEL);\n"
buf += " if (!" + fabric_mod_port + ") {\n"
buf += " printk(KERN_ERR \"Unable to allocate struct " + fabric_mod_name + "_" + fabric_mod_port + "\");\n"
buf += " return ERR_PTR(-ENOMEM);\n"
buf += " }\n"
if proto_ident == "FC" or proto_ident == "SAS":
buf += " " + fabric_mod_port + "->" + fabric_mod_port + "_wwpn = wwpn;\n"
buf += " /* " + fabric_mod_name + "_format_wwn(&" + fabric_mod_port + "->" + fabric_mod_port + "_name[0], " + fabric_mod_name.upper() + "_NAMELEN, wwpn); */\n\n"
buf += " return &" + fabric_mod_port + "->" + fabric_mod_port + "_wwn;\n"
buf += "}\n\n"
buf += "static void " + fabric_mod_name + "_drop_" + fabric_mod_port + "(struct se_wwn *wwn)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = container_of(wwn,\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + ", " + fabric_mod_port + "_wwn);\n"
buf += " kfree(" + fabric_mod_port + ");\n"
buf += "}\n\n"
buf += "static ssize_t " + fabric_mod_name + "_wwn_show_attr_version(\n"
buf += " struct target_fabric_configfs *tf,\n"
buf += " char *page)\n"
buf += "{\n"
buf += " return sprintf(page, \"" + fabric_mod_name.upper() + " fabric module %s on %s/%s\"\n"
buf += " \"on \"UTS_RELEASE\"\\n\", " + fabric_mod_name.upper() + "_VERSION, utsname()->sysname,\n"
buf += " utsname()->machine);\n"
buf += "}\n\n"
buf += "TF_WWN_ATTR_RO(" + fabric_mod_name + ", version);\n\n"
buf += "static struct configfs_attribute *" + fabric_mod_name + "_wwn_attrs[] = {\n"
buf += " &" + fabric_mod_name + "_wwn_version.attr,\n"
buf += " NULL,\n"
buf += "};\n\n"
buf += "static struct target_core_fabric_ops " + fabric_mod_name + "_ops = {\n"
buf += " .get_fabric_name = " + fabric_mod_name + "_get_fabric_name,\n"
buf += " .get_fabric_proto_ident = " + fabric_mod_name + "_get_fabric_proto_ident,\n"
buf += " .tpg_get_wwn = " + fabric_mod_name + "_get_fabric_wwn,\n"
buf += " .tpg_get_tag = " + fabric_mod_name + "_get_tag,\n"
buf += " .tpg_get_default_depth = " + fabric_mod_name + "_get_default_depth,\n"
buf += " .tpg_get_pr_transport_id = " + fabric_mod_name + "_get_pr_transport_id,\n"
buf += " .tpg_get_pr_transport_id_len = " + fabric_mod_name + "_get_pr_transport_id_len,\n"
buf += " .tpg_parse_pr_out_transport_id = " + fabric_mod_name + "_parse_pr_out_transport_id,\n"
buf += " .tpg_check_demo_mode = " + fabric_mod_name + "_check_false,\n"
buf += " .tpg_check_demo_mode_cache = " + fabric_mod_name + "_check_true,\n"
buf += " .tpg_check_demo_mode_write_protect = " + fabric_mod_name + "_check_true,\n"
buf += " .tpg_check_prod_mode_write_protect = " + fabric_mod_name + "_check_false,\n"
buf += " .tpg_alloc_fabric_acl = " + fabric_mod_name + "_alloc_fabric_acl,\n"
buf += " .tpg_release_fabric_acl = " + fabric_mod_name + "_release_fabric_acl,\n"
buf += " .tpg_get_inst_index = " + fabric_mod_name + "_tpg_get_inst_index,\n"
buf += " .release_cmd = " + fabric_mod_name + "_release_cmd,\n"
buf += " .shutdown_session = " + fabric_mod_name + "_shutdown_session,\n"
buf += " .close_session = " + fabric_mod_name + "_close_session,\n"
buf += " .stop_session = " + fabric_mod_name + "_stop_session,\n"
buf += " .fall_back_to_erl0 = " + fabric_mod_name + "_reset_nexus,\n"
buf += " .sess_logged_in = " + fabric_mod_name + "_sess_logged_in,\n"
buf += " .sess_get_index = " + fabric_mod_name + "_sess_get_index,\n"
buf += " .sess_get_initiator_sid = NULL,\n"
buf += " .write_pending = " + fabric_mod_name + "_write_pending,\n"
buf += " .write_pending_status = " + fabric_mod_name + "_write_pending_status,\n"
buf += " .set_default_node_attributes = " + fabric_mod_name + "_set_default_node_attrs,\n"
buf += " .get_task_tag = " + fabric_mod_name + "_get_task_tag,\n"
buf += " .get_cmd_state = " + fabric_mod_name + "_get_cmd_state,\n"
buf += " .queue_data_in = " + fabric_mod_name + "_queue_data_in,\n"
buf += " .queue_status = " + fabric_mod_name + "_queue_status,\n"
buf += " .queue_tm_rsp = " + fabric_mod_name + "_queue_tm_rsp,\n"
buf += " .is_state_remove = " + fabric_mod_name + "_is_state_remove,\n"
buf += " /*\n"
buf += " * Setup function pointers for generic logic in target_core_fabric_configfs.c\n"
buf += " */\n"
buf += " .fabric_make_wwn = " + fabric_mod_name + "_make_" + fabric_mod_port + ",\n"
buf += " .fabric_drop_wwn = " + fabric_mod_name + "_drop_" + fabric_mod_port + ",\n"
buf += " .fabric_make_tpg = " + fabric_mod_name + "_make_tpg,\n"
buf += " .fabric_drop_tpg = " + fabric_mod_name + "_drop_tpg,\n"
buf += " .fabric_post_link = NULL,\n"
buf += " .fabric_pre_unlink = NULL,\n"
buf += " .fabric_make_np = NULL,\n"
buf += " .fabric_drop_np = NULL,\n"
buf += " .fabric_make_nodeacl = " + fabric_mod_name + "_make_nodeacl,\n"
buf += " .fabric_drop_nodeacl = " + fabric_mod_name + "_drop_nodeacl,\n"
buf += "};\n\n"
buf += "static int " + fabric_mod_name + "_register_configfs(void)\n"
buf += "{\n"
buf += " struct target_fabric_configfs *fabric;\n"
buf += " int ret;\n\n"
buf += " printk(KERN_INFO \"" + fabric_mod_name.upper() + " fabric module %s on %s/%s\"\n"
buf += " \" on \"UTS_RELEASE\"\\n\"," + fabric_mod_name.upper() + "_VERSION, utsname()->sysname,\n"
buf += " utsname()->machine);\n"
buf += " /*\n"
buf += " * Register the top level struct config_item_type with TCM core\n"
buf += " */\n"
buf += " fabric = target_fabric_configfs_init(THIS_MODULE, \"" + fabric_mod_name[4:] + "\");\n"
buf += " if (IS_ERR(fabric)) {\n"
buf += " printk(KERN_ERR \"target_fabric_configfs_init() failed\\n\");\n"
buf += " return PTR_ERR(fabric);\n"
buf += " }\n"
buf += " /*\n"
buf += " * Setup fabric->tf_ops from our local " + fabric_mod_name + "_ops\n"
buf += " */\n"
buf += " fabric->tf_ops = " + fabric_mod_name + "_ops;\n"
buf += " /*\n"
buf += " * Setup default attribute lists for various fabric->tf_cit_tmpl\n"
buf += " */\n"
buf += " TF_CIT_TMPL(fabric)->tfc_wwn_cit.ct_attrs = " + fabric_mod_name + "_wwn_attrs;\n"
buf += " TF_CIT_TMPL(fabric)->tfc_tpg_base_cit.ct_attrs = NULL;\n"
buf += " TF_CIT_TMPL(fabric)->tfc_tpg_attrib_cit.ct_attrs = NULL;\n"
buf += " TF_CIT_TMPL(fabric)->tfc_tpg_param_cit.ct_attrs = NULL;\n"
buf += " TF_CIT_TMPL(fabric)->tfc_tpg_np_base_cit.ct_attrs = NULL;\n"
buf += " TF_CIT_TMPL(fabric)->tfc_tpg_nacl_base_cit.ct_attrs = NULL;\n"
buf += " TF_CIT_TMPL(fabric)->tfc_tpg_nacl_attrib_cit.ct_attrs = NULL;\n"
buf += " TF_CIT_TMPL(fabric)->tfc_tpg_nacl_auth_cit.ct_attrs = NULL;\n"
buf += " TF_CIT_TMPL(fabric)->tfc_tpg_nacl_param_cit.ct_attrs = NULL;\n"
buf += " /*\n"
buf += " * Register the fabric for use within TCM\n"
buf += " */\n"
buf += " ret = target_fabric_configfs_register(fabric);\n"
buf += " if (ret < 0) {\n"
buf += " printk(KERN_ERR \"target_fabric_configfs_register() failed\"\n"
buf += " \" for " + fabric_mod_name.upper() + "\\n\");\n"
buf += " return ret;\n"
buf += " }\n"
buf += " /*\n"
buf += " * Setup our local pointer to *fabric\n"
buf += " */\n"
buf += " " + fabric_mod_name + "_fabric_configfs = fabric;\n"
buf += " printk(KERN_INFO \"" + fabric_mod_name.upper() + "[0] - Set fabric -> " + fabric_mod_name + "_fabric_configfs\\n\");\n"
buf += " return 0;\n"
buf += "};\n\n"
buf += "static void __exit " + fabric_mod_name + "_deregister_configfs(void)\n"
buf += "{\n"
buf += " if (!" + fabric_mod_name + "_fabric_configfs)\n"
buf += " return;\n\n"
buf += " target_fabric_configfs_deregister(" + fabric_mod_name + "_fabric_configfs);\n"
buf += " " + fabric_mod_name + "_fabric_configfs = NULL;\n"
buf += " printk(KERN_INFO \"" + fabric_mod_name.upper() + "[0] - Cleared " + fabric_mod_name + "_fabric_configfs\\n\");\n"
buf += "};\n\n"
buf += "static int __init " + fabric_mod_name + "_init(void)\n"
buf += "{\n"
buf += " int ret;\n\n"
buf += " ret = " + fabric_mod_name + "_register_configfs();\n"
buf += " if (ret < 0)\n"
buf += " return ret;\n\n"
buf += " return 0;\n"
buf += "};\n\n"
buf += "static void __exit " + fabric_mod_name + "_exit(void)\n"
buf += "{\n"
buf += " " + fabric_mod_name + "_deregister_configfs();\n"
buf += "};\n\n"
buf += "MODULE_DESCRIPTION(\"" + fabric_mod_name.upper() + " series fabric driver\");\n"
buf += "MODULE_LICENSE(\"GPL\");\n"
buf += "module_init(" + fabric_mod_name + "_init);\n"
buf += "module_exit(" + fabric_mod_name + "_exit);\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
return
def tcm_mod_scan_fabric_ops(tcm_dir):
fabric_ops_api = tcm_dir + "include/target/target_core_fabric.h"
print "Using tcm_mod_scan_fabric_ops: " + fabric_ops_api
process_fo = 0;
p = open(fabric_ops_api, 'r')
line = p.readline()
while line:
if process_fo == 0 and re.search('struct target_core_fabric_ops {', line):
line = p.readline()
continue
if process_fo == 0:
process_fo = 1;
line = p.readline()
# Search for function pointer
if not re.search('\(\*', line):
continue
fabric_ops.append(line.rstrip())
continue
line = p.readline()
# Search for function pointer
if not re.search('\(\*', line):
continue
fabric_ops.append(line.rstrip())
p.close()
return
def tcm_mod_dump_fabric_ops(proto_ident, fabric_mod_dir_var, fabric_mod_name):
buf = ""
bufi = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_fabric.c"
print "Writing file: " + f
p = open(f, 'w')
if not p:
tcm_mod_err("Unable to open file: " + f)
fi = fabric_mod_dir_var + "/" + fabric_mod_name + "_fabric.h"
print "Writing file: " + fi
pi = open(fi, 'w')
if not pi:
tcm_mod_err("Unable to open file: " + fi)
buf = "#include <linux/slab.h>\n"
buf += "#include <linux/kthread.h>\n"
buf += "#include <linux/types.h>\n"
buf += "#include <linux/list.h>\n"
buf += "#include <linux/types.h>\n"
buf += "#include <linux/string.h>\n"
buf += "#include <linux/ctype.h>\n"
buf += "#include <asm/unaligned.h>\n"
buf += "#include <scsi/scsi.h>\n"
buf += "#include <scsi/scsi_host.h>\n"
buf += "#include <scsi/scsi_device.h>\n"
buf += "#include <scsi/scsi_cmnd.h>\n"
buf += "#include <scsi/libfc.h>\n\n"
buf += "#include <target/target_core_base.h>\n"
buf += "#include <target/target_core_fabric.h>\n"
buf += "#include <target/target_core_configfs.h>\n\n"
buf += "#include \"" + fabric_mod_name + "_base.h\"\n"
buf += "#include \"" + fabric_mod_name + "_fabric.h\"\n\n"
buf += "int " + fabric_mod_name + "_check_true(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " return 1;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_check_true(struct se_portal_group *);\n"
buf += "int " + fabric_mod_name + "_check_false(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_check_false(struct se_portal_group *);\n"
total_fabric_ops = len(fabric_ops)
i = 0
while i < total_fabric_ops:
fo = fabric_ops[i]
i += 1
# print "fabric_ops: " + fo
if re.search('get_fabric_name', fo):
buf += "char *" + fabric_mod_name + "_get_fabric_name(void)\n"
buf += "{\n"
buf += " return \"" + fabric_mod_name[4:] + "\";\n"
buf += "}\n\n"
bufi += "char *" + fabric_mod_name + "_get_fabric_name(void);\n"
continue
if re.search('get_fabric_proto_ident', fo):
buf += "u8 " + fabric_mod_name + "_get_fabric_proto_ident(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n"
buf += " u8 proto_id;\n\n"
buf += " switch (" + fabric_mod_port + "->" + fabric_mod_port + "_proto_id) {\n"
if proto_ident == "FC":
buf += " case SCSI_PROTOCOL_FCP:\n"
buf += " default:\n"
buf += " proto_id = fc_get_fabric_proto_ident(se_tpg);\n"
buf += " break;\n"
elif proto_ident == "SAS":
buf += " case SCSI_PROTOCOL_SAS:\n"
buf += " default:\n"
buf += " proto_id = sas_get_fabric_proto_ident(se_tpg);\n"
buf += " break;\n"
elif proto_ident == "iSCSI":
buf += " case SCSI_PROTOCOL_ISCSI:\n"
buf += " default:\n"
buf += " proto_id = iscsi_get_fabric_proto_ident(se_tpg);\n"
buf += " break;\n"
buf += " }\n\n"
buf += " return proto_id;\n"
buf += "}\n\n"
bufi += "u8 " + fabric_mod_name + "_get_fabric_proto_ident(struct se_portal_group *);\n"
if re.search('get_wwn', fo):
buf += "char *" + fabric_mod_name + "_get_fabric_wwn(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n\n"
buf += " return &" + fabric_mod_port + "->" + fabric_mod_port + "_name[0];\n"
buf += "}\n\n"
bufi += "char *" + fabric_mod_name + "_get_fabric_wwn(struct se_portal_group *);\n"
if re.search('get_tag', fo):
buf += "u16 " + fabric_mod_name + "_get_tag(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " return tpg->" + fabric_mod_port + "_tpgt;\n"
buf += "}\n\n"
bufi += "u16 " + fabric_mod_name + "_get_tag(struct se_portal_group *);\n"
if re.search('get_default_depth', fo):
buf += "u32 " + fabric_mod_name + "_get_default_depth(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " return 1;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_get_default_depth(struct se_portal_group *);\n"
if re.search('get_pr_transport_id\)\(', fo):
buf += "u32 " + fabric_mod_name + "_get_pr_transport_id(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " struct se_node_acl *se_nacl,\n"
buf += " struct t10_pr_registration *pr_reg,\n"
buf += " int *format_code,\n"
buf += " unsigned char *buf)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n"
buf += " int ret = 0;\n\n"
buf += " switch (" + fabric_mod_port + "->" + fabric_mod_port + "_proto_id) {\n"
if proto_ident == "FC":
buf += " case SCSI_PROTOCOL_FCP:\n"
buf += " default:\n"
buf += " ret = fc_get_pr_transport_id(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code, buf);\n"
buf += " break;\n"
elif proto_ident == "SAS":
buf += " case SCSI_PROTOCOL_SAS:\n"
buf += " default:\n"
buf += " ret = sas_get_pr_transport_id(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code, buf);\n"
buf += " break;\n"
elif proto_ident == "iSCSI":
buf += " case SCSI_PROTOCOL_ISCSI:\n"
buf += " default:\n"
buf += " ret = iscsi_get_pr_transport_id(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code, buf);\n"
buf += " break;\n"
buf += " }\n\n"
buf += " return ret;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_get_pr_transport_id(struct se_portal_group *,\n"
bufi += " struct se_node_acl *, struct t10_pr_registration *,\n"
bufi += " int *, unsigned char *);\n"
if re.search('get_pr_transport_id_len\)\(', fo):
buf += "u32 " + fabric_mod_name + "_get_pr_transport_id_len(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " struct se_node_acl *se_nacl,\n"
buf += " struct t10_pr_registration *pr_reg,\n"
buf += " int *format_code)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n"
buf += " int ret = 0;\n\n"
buf += " switch (" + fabric_mod_port + "->" + fabric_mod_port + "_proto_id) {\n"
if proto_ident == "FC":
buf += " case SCSI_PROTOCOL_FCP:\n"
buf += " default:\n"
buf += " ret = fc_get_pr_transport_id_len(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code);\n"
buf += " break;\n"
elif proto_ident == "SAS":
buf += " case SCSI_PROTOCOL_SAS:\n"
buf += " default:\n"
buf += " ret = sas_get_pr_transport_id_len(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code);\n"
buf += " break;\n"
elif proto_ident == "iSCSI":
buf += " case SCSI_PROTOCOL_ISCSI:\n"
buf += " default:\n"
buf += " ret = iscsi_get_pr_transport_id_len(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code);\n"
buf += " break;\n"
buf += " }\n\n"
buf += " return ret;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_get_pr_transport_id_len(struct se_portal_group *,\n"
bufi += " struct se_node_acl *, struct t10_pr_registration *,\n"
bufi += " int *);\n"
if re.search('parse_pr_out_transport_id\)\(', fo):
buf += "char *" + fabric_mod_name + "_parse_pr_out_transport_id(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " const char *buf,\n"
buf += " u32 *out_tid_len,\n"
buf += " char **port_nexus_ptr)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n"
buf += " char *tid = NULL;\n\n"
buf += " switch (" + fabric_mod_port + "->" + fabric_mod_port + "_proto_id) {\n"
if proto_ident == "FC":
buf += " case SCSI_PROTOCOL_FCP:\n"
buf += " default:\n"
buf += " tid = fc_parse_pr_out_transport_id(se_tpg, buf, out_tid_len,\n"
buf += " port_nexus_ptr);\n"
elif proto_ident == "SAS":
buf += " case SCSI_PROTOCOL_SAS:\n"
buf += " default:\n"
buf += " tid = sas_parse_pr_out_transport_id(se_tpg, buf, out_tid_len,\n"
buf += " port_nexus_ptr);\n"
elif proto_ident == "iSCSI":
buf += " case SCSI_PROTOCOL_ISCSI:\n"
buf += " default:\n"
buf += " tid = iscsi_parse_pr_out_transport_id(se_tpg, buf, out_tid_len,\n"
buf += " port_nexus_ptr);\n"
buf += " }\n\n"
buf += " return tid;\n"
buf += "}\n\n"
bufi += "char *" + fabric_mod_name + "_parse_pr_out_transport_id(struct se_portal_group *,\n"
bufi += " const char *, u32 *, char **);\n"
if re.search('alloc_fabric_acl\)\(', fo):
buf += "struct se_node_acl *" + fabric_mod_name + "_alloc_fabric_acl(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_nacl *nacl;\n\n"
buf += " nacl = kzalloc(sizeof(struct " + fabric_mod_name + "_nacl), GFP_KERNEL);\n"
buf += " if (!nacl) {\n"
buf += " printk(KERN_ERR \"Unable to allocate struct " + fabric_mod_name + "_nacl\\n\");\n"
buf += " return NULL;\n"
buf += " }\n\n"
buf += " return &nacl->se_node_acl;\n"
buf += "}\n\n"
bufi += "struct se_node_acl *" + fabric_mod_name + "_alloc_fabric_acl(struct se_portal_group *);\n"
if re.search('release_fabric_acl\)\(', fo):
buf += "void " + fabric_mod_name + "_release_fabric_acl(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " struct se_node_acl *se_nacl)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_nacl *nacl = container_of(se_nacl,\n"
buf += " struct " + fabric_mod_name + "_nacl, se_node_acl);\n"
buf += " kfree(nacl);\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_release_fabric_acl(struct se_portal_group *,\n"
bufi += " struct se_node_acl *);\n"
if re.search('tpg_get_inst_index\)\(', fo):
buf += "u32 " + fabric_mod_name + "_tpg_get_inst_index(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " return 1;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_tpg_get_inst_index(struct se_portal_group *);\n"
if re.search('\*release_cmd\)\(', fo):
buf += "void " + fabric_mod_name + "_release_cmd(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_release_cmd(struct se_cmd *);\n"
if re.search('shutdown_session\)\(', fo):
buf += "int " + fabric_mod_name + "_shutdown_session(struct se_session *se_sess)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_shutdown_session(struct se_session *);\n"
if re.search('close_session\)\(', fo):
buf += "void " + fabric_mod_name + "_close_session(struct se_session *se_sess)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_close_session(struct se_session *);\n"
if re.search('stop_session\)\(', fo):
buf += "void " + fabric_mod_name + "_stop_session(struct se_session *se_sess, int sess_sleep , int conn_sleep)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_stop_session(struct se_session *, int, int);\n"
if re.search('fall_back_to_erl0\)\(', fo):
buf += "void " + fabric_mod_name + "_reset_nexus(struct se_session *se_sess)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_reset_nexus(struct se_session *);\n"
if re.search('sess_logged_in\)\(', fo):
buf += "int " + fabric_mod_name + "_sess_logged_in(struct se_session *se_sess)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_sess_logged_in(struct se_session *);\n"
if re.search('sess_get_index\)\(', fo):
buf += "u32 " + fabric_mod_name + "_sess_get_index(struct se_session *se_sess)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_sess_get_index(struct se_session *);\n"
if re.search('write_pending\)\(', fo):
buf += "int " + fabric_mod_name + "_write_pending(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_write_pending(struct se_cmd *);\n"
if re.search('write_pending_status\)\(', fo):
buf += "int " + fabric_mod_name + "_write_pending_status(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_write_pending_status(struct se_cmd *);\n"
if re.search('set_default_node_attributes\)\(', fo):
buf += "void " + fabric_mod_name + "_set_default_node_attrs(struct se_node_acl *nacl)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_set_default_node_attrs(struct se_node_acl *);\n"
if re.search('get_task_tag\)\(', fo):
buf += "u32 " + fabric_mod_name + "_get_task_tag(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_get_task_tag(struct se_cmd *);\n"
if re.search('get_cmd_state\)\(', fo):
buf += "int " + fabric_mod_name + "_get_cmd_state(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_get_cmd_state(struct se_cmd *);\n"
if re.search('queue_data_in\)\(', fo):
buf += "int " + fabric_mod_name + "_queue_data_in(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_queue_data_in(struct se_cmd *);\n"
if re.search('queue_status\)\(', fo):
buf += "int " + fabric_mod_name + "_queue_status(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_queue_status(struct se_cmd *);\n"
if re.search('queue_tm_rsp\)\(', fo):
buf += "int " + fabric_mod_name + "_queue_tm_rsp(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_queue_tm_rsp(struct se_cmd *);\n"
if re.search('is_state_remove\)\(', fo):
buf += "int " + fabric_mod_name + "_is_state_remove(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_is_state_remove(struct se_cmd *);\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
ret = pi.write(bufi)
if ret:
tcm_mod_err("Unable to write fi: " + fi)
pi.close()
return
def tcm_mod_build_kbuild(fabric_mod_dir_var, fabric_mod_name):
buf = ""
f = fabric_mod_dir_var + "/Makefile"
print "Writing file: " + f
p = open(f, 'w')
if not p:
tcm_mod_err("Unable to open file: " + f)
buf += fabric_mod_name + "-objs := " + fabric_mod_name + "_fabric.o \\\n"
buf += " " + fabric_mod_name + "_configfs.o\n"
buf += "obj-$(CONFIG_" + fabric_mod_name.upper() + ") += " + fabric_mod_name + ".o\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
return
def tcm_mod_build_kconfig(fabric_mod_dir_var, fabric_mod_name):
buf = ""
f = fabric_mod_dir_var + "/Kconfig"
print "Writing file: " + f
p = open(f, 'w')
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "config " + fabric_mod_name.upper() + "\n"
buf += " tristate \"" + fabric_mod_name.upper() + " fabric module\"\n"
buf += " depends on TARGET_CORE && CONFIGFS_FS\n"
buf += " default n\n"
buf += " ---help---\n"
buf += " Say Y here to enable the " + fabric_mod_name.upper() + " fabric module\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
return
def tcm_mod_add_kbuild(tcm_dir, fabric_mod_name):
buf = "obj-$(CONFIG_" + fabric_mod_name.upper() + ") += " + fabric_mod_name.lower() + "/\n"
kbuild = tcm_dir + "/drivers/target/Makefile"
f = open(kbuild, 'a')
f.write(buf)
f.close()
return
def tcm_mod_add_kconfig(tcm_dir, fabric_mod_name):
buf = "source \"drivers/target/" + fabric_mod_name.lower() + "/Kconfig\"\n"
kconfig = tcm_dir + "/drivers/target/Kconfig"
f = open(kconfig, 'a')
f.write(buf)
f.close()
return
def main(modname, proto_ident):
# proto_ident = "FC"
# proto_ident = "SAS"
# proto_ident = "iSCSI"
tcm_dir = os.getcwd();
tcm_dir += "/../../"
print "tcm_dir: " + tcm_dir
fabric_mod_name = modname
fabric_mod_dir = tcm_dir + "drivers/target/" + fabric_mod_name
print "Set fabric_mod_name: " + fabric_mod_name
print "Set fabric_mod_dir: " + fabric_mod_dir
print "Using proto_ident: " + proto_ident
if proto_ident != "FC" and proto_ident != "SAS" and proto_ident != "iSCSI":
print "Unsupported proto_ident: " + proto_ident
sys.exit(1)
ret = tcm_mod_create_module_subdir(fabric_mod_dir)
if ret:
print "tcm_mod_create_module_subdir() failed because module already exists!"
sys.exit(1)
tcm_mod_build_base_includes(proto_ident, fabric_mod_dir, fabric_mod_name)
tcm_mod_scan_fabric_ops(tcm_dir)
tcm_mod_dump_fabric_ops(proto_ident, fabric_mod_dir, fabric_mod_name)
tcm_mod_build_configfs(proto_ident, fabric_mod_dir, fabric_mod_name)
tcm_mod_build_kbuild(fabric_mod_dir, fabric_mod_name)
tcm_mod_build_kconfig(fabric_mod_dir, fabric_mod_name)
input = raw_input("Would you like to add " + fabric_mod_name + "to drivers/target/Makefile..? [yes,no]: ")
if input == "yes" or input == "y":
tcm_mod_add_kbuild(tcm_dir, fabric_mod_name)
input = raw_input("Would you like to add " + fabric_mod_name + "to drivers/target/Kconfig..? [yes,no]: ")
if input == "yes" or input == "y":
tcm_mod_add_kconfig(tcm_dir, fabric_mod_name)
return
parser = optparse.OptionParser()
parser.add_option('-m', '--modulename', help='Module name', dest='modname',
action='store', nargs=1, type='string')
parser.add_option('-p', '--protoident', help='Protocol Ident', dest='protoident',
action='store', nargs=1, type='string')
(opts, args) = parser.parse_args()
mandatories = ['modname', 'protoident']
for m in mandatories:
if not opts.__dict__[m]:
print "mandatory option is missing\n"
parser.print_help()
exit(-1)
if __name__ == "__main__":
main(str(opts.modname), opts.protoident)
| gpl-2.0 |
jcftang/ansible | lib/ansible/modules/windows/win_template.py | 35 | 3126 | # this is a virtual module that is entirely implemented server side
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
ANSIBLE_METADATA = {'status': ['stableinterface'],
'supported_by': 'core',
'version': '1.0'}
DOCUMENTATION = r'''
---
module: win_template
version_added: "1.9.2"
short_description: Templates a file out to a remote server.
description:
- Templates are processed by the Jinja2 templating language
(U(http://jinja.pocoo.org/docs/)) - documentation on the template
formatting can be found in the Template Designer Documentation
(U(http://jinja.pocoo.org/docs/templates/)).
- "Six additional variables can be used in templates: C(ansible_managed)
(configurable via the C(defaults) section of C(ansible.cfg)) contains a string
which can be used to describe the template name, host, modification time of the
template file and the owner uid, C(template_host) contains the node name of
the template's machine, C(template_uid) the owner, C(template_path) the
absolute path of the template, C(template_fullpath) is the absolute path of the
template, and C(template_run_date) is the date that the template was rendered. Note that including
a string that uses a date in the template will result in the template being marked 'changed'
each time."
options:
src:
description:
- Path of a Jinja2 formatted template on the local server. This can be a relative or absolute path.
required: true
dest:
description:
- Location to render the template to on the remote machine.
required: true
notes:
- "templates are loaded with C(trim_blocks=True)."
- By default, windows line endings are not created in the generated file.
- "In order to ensure windows line endings are in the generated file, add the following header
as the first line of your template: ``#jinja2: newline_sequence:'\\r\\n'`` and ensure each line
of the template ends with \\\\r\\\\n"
- Beware fetching files from windows machines when creating templates
because certain tools, such as Powershell ISE, and regedit's export facility
add a Byte Order Mark as the first character of the file, which can cause tracebacks.
- Use "od -cx" to examine your templates for Byte Order Marks.
author: "Jon Hawkesworth (@jhawkesworth)"
'''
EXAMPLES = r'''
- name: Create a file from a Jinja2 template
win_template:
src: /mytemplates/file.conf.j2
dest: C:\temp\file.conf
'''
| gpl-3.0 |
destijl/grr | grr/client/stdlib.py | 2 | 8367 | #!/usr/bin/env python
"""This file imports the Python std lib so it can be used by components."""
# pylint: disable=g-import-not-at-top, unused-import, using-constant-test
if False:
import BaseHTTPServer
import CGIHTTPServer
import ConfigParser
import Cookie
import DocXMLRPCServer
import HTMLParser
import MimeWriter
import Queue
import SimpleHTTPServer
import SimpleXMLRPCServer
import SocketServer
import StringIO
import UserDict
import UserList
import UserString
import _LWPCookieJar
import _abcoll
# https://github.com/pyinstaller/pyinstaller/issues/1425
import _cffi_backend
import _osx_support
import _pyio
import _strptime
import _sysconfigdata
import _threading_local
import _weakrefset
import abc
import aifc
import anydbm
import argparse
import ast
import asynchat
import asyncore
import atexit
import audiodev
import base64
import bdb
import binhex
import bisect
import bsddb.db
import bsddb.dbobj
import bsddb.dbrecio
import bsddb.dbshelve
import bsddb.dbtables
import bsddb.dbutils
import cProfile
import calendar
import cgi
import cgitb
import chunk
import cmd
import code
import codecs
import codeop
import collections
import colorsys
import commands
import compileall
import compiler.ast
import compiler.consts
import compiler.future
import compiler.misc
import compiler.pyassem
import compiler.pycodegen
import compiler.symbols
import compiler.syntax
import compiler.transformer
import compiler.visitor
import contextlib
import cookielib
import copy
import copy_reg
import csv
import ctypes._endian
import ctypes.util
import curses.ascii
import curses.has_key
import curses.panel
import curses.textpad
import curses.wrapper
import dbhash
import decimal
import difflib
import dircache
import dis
import distutils.archive_util
import distutils.bcppcompiler
import distutils.ccompiler
import distutils.cmd
import distutils.command.bdist
import distutils.command.bdist_dumb
import distutils.command.bdist_rpm
import distutils.command.bdist_wininst
import distutils.command.build
import distutils.command.build_clib
import distutils.command.build_ext
import distutils.command.build_py
import distutils.command.build_scripts
import distutils.command.check
import distutils.command.clean
import distutils.command.config
import distutils.command.install
import distutils.command.install_data
import distutils.command.install_egg_info
import distutils.command.install_headers
import distutils.command.install_lib
import distutils.command.install_scripts
import distutils.command.register
import distutils.command.sdist
import distutils.command.upload
import distutils.config
import distutils.core
import distutils.cygwinccompiler
import distutils.debug
import distutils.dep_util
import distutils.dir_util
import distutils.dist
import distutils.emxccompiler
import distutils.errors
import distutils.extension
import distutils.fancy_getopt
import distutils.file_util
import distutils.filelist
import distutils.log
import distutils.spawn
import distutils.sysconfig
import distutils.text_file
import distutils.unixccompiler
import distutils.util
import distutils.version
import distutils.versionpredicate
import doctest
import dumbdbm
import dummy_thread
import dummy_threading
import email._parseaddr
import email.base64mime
import email.charset
import email.encoders
import email.errors
import email.feedparser
import email.generator
import email.header
import email.iterators
import email.message
import email.mime.application
import email.mime.audio
import email.mime.base
import email.mime.image
import email.mime.message
import email.mime.multipart
import email.mime.nonmultipart
import email.mime.text
import email.parser
import email.quoprimime
import email.utils
import filecmp
import fileinput
import fnmatch
import formatter
import fpformat
import fractions
import ftplib
import functools
import genericpath
import getopt
import getpass
import gettext
import glob
import gzip
import hashlib
import heapq
import hmac
import hotshot.log
import hotshot.stats
import hotshot.stones
import htmlentitydefs
import htmllib
import httplib
import ihooks
import imaplib
import imghdr
import imputil
import inspect
import io
import json.decoder
import json.encoder
import json.scanner
import json.tool
import keyword
import linecache
import locale
import logging.config
import logging.handlers
import macpath
import macurl2path
import mailbox
import mailcap
import markupbase
import md5
import mhlib
import mimetools
import mimetypes
import mimify
import modulefinder
import multifile
import multiprocessing.connection
import multiprocessing.dummy.connection
import multiprocessing.forking
import multiprocessing.heap
import multiprocessing.managers
import multiprocessing.pool
import multiprocessing.process
import multiprocessing.queues
import multiprocessing.reduction
import multiprocessing.sharedctypes
import multiprocessing.synchronize
import multiprocessing.util
import mutex
import netrc
import new
import nntplib
import ntpath
import nturl2path
import numbers
import opcode
import optparse
import os
import os2emxpath
import pdb
import pickle
import pickletools
import pipes
import pkgutil
import platform
import plistlib
import popen2
import poplib
import posixfile
import posixpath
import pprint
import profile
import pstats
import pty
import py_compile
import pyclbr
import pydoc
import pydoc_data.topics
import quopri
import random
import re
import rfc822
import rlcompleter
import robotparser
import runpy
import sched
import sets
import sgmllib
import sha
import shelve
import shlex
import shutil
import site
import smtpd
import smtplib
import sndhdr
import socket
import sqlite3.dbapi2
import sqlite3.dump
import sre
import sre_compile
import sre_constants
import sre_parse
import ssl
import stat
import statvfs
import string
import stringold
import stringprep
import struct
import subprocess
import sunau
import sunaudio
import symbol
import symtable
import sysconfig
import tabnanny
import tarfile
import telnetlib
import tempfile
import test.pystone
import test.regrtest
import test.test_support
import textwrap
import this
import threading
import timeit
import toaiff
import token
import tokenize
import trace
import traceback
import tty
import types
import urllib
import urllib2
import urlparse
import user
import uu
import uuid
import warnings
import wave
import weakref
import whichdb
import wsgiref.handlers
import wsgiref.headers
import wsgiref.simple_server
import wsgiref.util
import wsgiref.validate
import xdrlib
import xml.dom.NodeFilter
import xml.dom.domreg
import xml.dom.expatbuilder
import xml.dom.minicompat
import xml.dom.minidom
import xml.dom.pulldom
import xml.dom.xmlbuilder
import xml.etree.ElementInclude
import xml.etree.ElementPath
import xml.etree.ElementTree
import xml.etree.cElementTree
import xml.parsers.expat
import xml.sax._exceptions
import xml.sax.expatreader
import xml.sax.handler
import xml.sax.saxutils
import xml.sax.xmlreader
import xmllib
import xmlrpclib
import zipfile
# lib-dynload
import audioop
import _bsddb
import bz2
import _codecs_cn
import _codecs_hk
import _codecs_iso2022
import _codecs_jp
import _codecs_kr
import _codecs_tw
import crypt
import _csv
import _ctypes_test
import _ctypes
import _curses_panel
import _curses
import datetime
import dbm
import _elementtree
import fpectl
import future_builtins
import gdbm
import _hashlib
import _hotshot
import _json
import linuxaudiodev
import _lsprof
import mmap
import _multibytecodec
import _multiprocessing
import nis
import ossaudiodev
import parser
import pyexpat
import readline
import resource
import _sqlite3
import _ssl
import termios
import _testcapi
import _tkinter
| apache-2.0 |
walteryang47/ovirt-engine | packaging/setup/plugins/ovirt-engine-common/base/network/firewall_manager_iptables.py | 7 | 8581 | #
# ovirt-engine-setup -- ovirt engine setup
# Copyright (C) 2013-2015 Red Hat, Inc.
#
# 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.
#
"""
Firewall manager iptables plugin.
"""
import difflib
import gettext
import os
from otopi import constants as otopicons
from otopi import filetransaction, plugin, util
from ovirt_engine import util as outil
from ovirt_engine_setup import constants as osetupcons
from ovirt_engine_setup import dialog, firewall_manager_base
from . import process_firewalld_services
def _(m):
return gettext.dgettext(message=m, domain='ovirt-engine-setup')
@util.export
class Plugin(plugin.PluginBase):
"""
Firewall manager iptables plugin.
"""
class _IpTablesManager(firewall_manager_base.FirewallManagerBase):
_SERVICE = 'iptables'
def _get_rules(self):
if self._rules is None:
self._rules = outil.processTemplate(
osetupcons.FileLocations.OVIRT_IPTABLES_DEFAULT,
subst={
'@CUSTOM_RULES@': (
process_firewalld_services.Process.getInstance(
environment=self.environment,
).parseFirewalld(
format=(
'-A INPUT -p {protocol} -m state '
'--state NEW -m {protocol} '
'--dport {port} -j ACCEPT\n'
),
portSeparator=':',
)
),
}
)
return self._rules
def __init__(self, plugin):
super(Plugin._IpTablesManager, self).__init__(plugin)
self._rules = None
@property
def name(self):
return osetupcons.Const.FIREWALL_MANAGER_IPTABLES
def detect(self):
return self.plugin.services.exists(self._SERVICE)
def active(self):
return self.plugin.services.status(self._SERVICE)
def prepare_examples(self):
content = self._get_rules()
self.environment[otopicons.CoreEnv.MAIN_TRANSACTION].append(
filetransaction.FileTransaction(
name=osetupcons.FileLocations.OVIRT_IPTABLES_EXAMPLE,
content=content,
modifiedList=self.environment[
otopicons.CoreEnv.MODIFIED_FILES
],
)
)
def enable(self):
self.environment[otopicons.NetEnv.IPTABLES_ENABLE] = True
self.environment[
otopicons.NetEnv.IPTABLES_RULES
] = self._get_rules()
# This file is updated by otopi. Here we just prevent it from
# being deleted on cleanup.
# TODO: copy/move some uninstall code from the engine to otopi
# to allow just adding lines to iptables instead of replacing
# the file and also remove these lines on cleanup.
self.environment[
osetupcons.CoreEnv.UNINSTALL_UNREMOVABLE_FILES
].append(
osetupcons.FileLocations.SYSCONFIG_IPTABLES,
)
def print_manual_configuration_instructions(self):
self.plugin.dialog.note(
text=_(
'An example of the required configuration for iptables '
'can be found at:\n'
' {example}'
).format(
example=osetupcons.FileLocations.OVIRT_IPTABLES_EXAMPLE
)
)
def review_config(self):
diff_lines = ''
current_rules = ''
current_modified_since_prev_setup = False
interactive = True
if os.path.isfile(osetupcons.FileLocations.SYSCONFIG_IPTABLES):
with open(
osetupcons.FileLocations.SYSCONFIG_IPTABLES,
'r'
) as current:
current_rules = current.read().splitlines()
if os.path.isfile(osetupcons.FileLocations.OVIRT_IPTABLES_EXAMPLE):
with open(
osetupcons.FileLocations.OVIRT_IPTABLES_EXAMPLE,
'r'
) as prev_setup_example:
prev_setup_rules = prev_setup_example.read().splitlines()
diff_prev_cur = difflib.unified_diff(
current_rules,
prev_setup_rules,
lineterm='',
)
diff_lines = '\n'.join(diff_prev_cur)
if len(diff_lines) > 0:
current_modified_since_prev_setup = True
diff = difflib.unified_diff(
current_rules,
self._get_rules().splitlines(),
lineterm='',
fromfile=_('current'),
tofile=_('proposed'),
)
diff_lines = '\n'.join(diff)
if len(diff_lines) > 0:
if current_modified_since_prev_setup:
self.logger.warning(
_(
"It seams that previously generated iptables "
"configuration was manually edited,\n"
"please carefully review the proposed "
"configuration"
)
)
if self.environment[
osetupcons.ConfigEnv.FIREWALL_CHANGES_REVIEW
] is None:
self.environment[
osetupcons.ConfigEnv.FIREWALL_CHANGES_REVIEW
] = dialog.queryBoolean(
dialog=self.plugin.dialog,
name='OVESETUP_REVIEW_IPTABLES_CHANGES',
note=_(
'Generated iptables rules are different '
'from current ones.\n'
'Do you want to review them? '
'(@VALUES@) [@DEFAULT@]: '
),
prompt=True,
true=_('Yes'),
false=_('No'),
default=False,
)
else:
interactive = False
if self.environment[
osetupcons.ConfigEnv.FIREWALL_CHANGES_REVIEW
] and interactive:
confirmed = dialog.queryBoolean(
dialog=self.plugin.dialog,
name='OVESETUP_CONFIRM_IPTABLES_CHANGES',
note=_(
'Please review the changes:\n\n'
'{diff}\n\n'
'Do you want to proceed with firewall '
'configuration? '
'(@VALUES@) [@DEFAULT@]: '
).format(
diff=diff_lines
),
prompt=True,
true=_('Yes'),
false=_('No'),
default=True,
)
if not confirmed:
raise RuntimeError(
_(
'iptables proposed configuration '
'was rejected by user'
)
)
@plugin.event(
stage=plugin.Stages.STAGE_SETUP,
before=(
osetupcons.Stages.KEEP_ONLY_VALID_FIREWALL_MANAGERS,
),
)
def _setup(self):
self.environment[
osetupcons.ConfigEnv.FIREWALL_MANAGERS
].append(Plugin._IpTablesManager(self))
# vim: expandtab tabstop=4 shiftwidth=4
| apache-2.0 |
wbrp/dnsimple-zoneimport | setup.py | 1 | 1349 | # -*- coding: utf-8 -*-
from setuptools import setup, find_packages
from dnsimple_zoneimport import meta
f = open('requirements.txt', 'r')
lines = f.readlines()
requirements = [l.strip().strip('\n') for l in lines if l.strip() and not l.strip().startswith('#')]
readme = open('README.rst').read()
setup(name='dnsimple-zoneimport',
version=meta.version,
description=meta.description,
author=meta.author,
author_email=meta.author_email,
url='https://github.com/wbrp/dnsimple-zoneimport',
packages=find_packages(),
zip_safe=False,
include_package_data=True,
license=meta.license,
keywords='dnsimple dns "zone files" bind import api',
long_description=readme,
install_requires=requirements,
entry_points={
'console_scripts': [
'%s = dnsimple_zoneimport.importer:main' % meta.title.replace('-', '_'),
]
},
classifiers=[
'Development Status :: 4 - Beta',
'Environment :: Console',
'License :: OSI Approved :: MIT License',
'Natural Language :: English',
'Operating System :: MacOS',
'Operating System :: POSIX :: Linux',
'Programming Language :: Python :: 2.7',
'Topic :: Internet :: Name Service (DNS)',
'Topic :: Terminals',
],
)
| mit |
Antiun/stock-logistics-workflow | product_customer_code_picking/__init__.py | 25 | 1043 | # -*- coding: utf-8 -*-
##############################################################################
#
# Copyright (C) 2013 Agile Business Group sagl (<http://www.agilebg.com>)
# Author: Nicola Malcontenti <nicola.malcontenti@agilebg.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
##############################################################################
from . import stock_picking
| agpl-3.0 |
flavour/cedarbluff | modules/eden/project.py | 1 | 132447 | # -*- coding: utf-8 -*-
""" Sahana Eden Project Model
@copyright: 2011-2012 (c) Sahana Software Foundation
@license: MIT
Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"), to deal in the Software without
restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following
conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
"""
__all__ = ["S3ProjectModel",
"S3ProjectDRRModel",
"S3ProjectTaskModel",
"S3ProjectTaskHRMModel",
"S3ProjectTaskIReportModel",
"project_rheader",
"S3ProjectTaskVirtualfields"]
import datetime
from gluon import *
from gluon.dal import Row
from gluon.storage import Storage
from gluon.sqlhtml import CheckboxesWidget
from ..s3 import *
try:
from lxml import etree, html
except ImportError:
import sys
print >> sys.stderr, "ERROR: lxml module needed for XML handling"
raise
# =============================================================================
class S3ProjectModel(S3Model):
"""
Project Model
Note: This module operates in 2 quite different modes:
- 'drr': suitable for use by multinational organisations tracking
projects at a high level
- non-drr: suitable for use by a smaller organsiation tracking tasks
at a detailed level
This class contains the tables common to both uses
There are additional tabels in S3ProjectDRRModel and S3ProjectTaskModel
for the other 2 use cases
There are also additional Classes for optional Link Tables
"""
names = ["project_theme",
"project_hazard",
"project_project",
"project_activity_type",
"project_activity",
"project_activity_contact",
"project_project_id",
"project_activity_id",
"project_hfa_opts",
"project_project_represent",
]
def model(self):
T = current.T
db = current.db
request = current.request
s3 = current.response.s3
settings = current.deployment_settings
currency_type = s3.currency_type
person_id = self.pr_person_id
location_id = self.gis_location_id
countries_id = self.gis_countries_id
organisation_id = self.org_organisation_id
sector_id = self.org_sector_id
human_resource_id = self.hrm_human_resource_id
s3_date_format = settings.get_L10n_date_format()
s3_date_represent = lambda dt: S3DateTime.date_represent(dt, utc=True)
# Enable DRR extensions?
drr = settings.get_project_drr()
pca = settings.get_project_community_activity()
# Shortcuts
add_component = self.add_component
comments = s3.comments
configure = self.configure
crud_strings = s3.crud_strings
define_table = self.define_table
meta_fields = s3.meta_fields
super_link = self.super_link
# ---------------------------------------------------------------------
# Theme
# @ToDo: Move to link table to move to S3ProjectDRRModel
#
tablename = "project_theme"
table = define_table(tablename,
Field("name",
length=128,
notnull=True,
unique=True),
Field("comments"),
format = "%(name)s",
*meta_fields())
# Field configuration?
# CRUD Strings?
# Search Method?
# Resource Configuration?
# Reusable Field
multi_theme_id = S3ReusableField("multi_theme_id",
"list:reference project_theme",
label = T("Themes"),
sortby = "name",
requires = IS_NULL_OR(IS_ONE_OF(db,
"project_theme.id",
"%(name)s",
sort=True,
multiple=True)),
represent = lambda opt, row=None: \
self.multiref_represent(opt, "project_theme"),
default = [],
ondelete = "RESTRICT",
widget = lambda f, v: \
CheckboxesWidgetS3.widget(f, v, cols = 3))
# ---------------------------------------------------------------------
# Hazard
# @ToDo: Move to link table to move to S3ProjectDRRModel
#
tablename = "project_hazard"
table = define_table(tablename,
Field("name",
length=128,
notnull=True,
unique=True),
Field("comments"),
format="%(name)s",
*meta_fields())
# Field configuration?
# CRUD Strings?
# Search Method?
# Resource Configuration?
# Reusable Field
multi_hazard_id = S3ReusableField("multi_hazard_id",
"list:reference project_hazard",
sortby = "name",
label = T("Hazards"),
requires = IS_NULL_OR(IS_ONE_OF(db,
"project_hazard.id",
"%(name)s",
sort=True,
multiple=True)),
represent = lambda opt, row=None: \
self.multiref_represent(opt, "project_hazard"),
ondelete = "RESTRICT",
widget = lambda f, v: CheckboxesWidgetS3.widget(f, v, cols = 3))
# ---------------------------------------------------------------------
# Project
#
# HFA
# @todo: localization?
project_hfa_opts = {
1: "HFA1: Ensure that disaster risk reduction is a national and a local priority with a strong institutional basis for implementation.",
2: "HFA2: Identify, assess and monitor disaster risks and enhance early warning.",
3: "HFA3: Use knowledge, innovation and education to build a culture of safety and resilience at all levels.",
4: "HFA4: Reduce the underlying risk factors.",
5: "HFA5: Strengthen disaster preparedness for effective response at all levels.",
}
tablename = "project_project"
table = define_table(tablename,
super_link("doc_id", "doc_entity"),
# drr uses the separate project_organisation table
organisation_id(
readable=False if drr else True,
writable=False if drr else True,
),
Field("name",
label = T("Name"),
# Require unique=True if using IS_NOT_ONE_OF like here (same table,
# no filter) in order to allow both automatic indexing (faster)
# and key-based de-duplication (i.e. before field validation)
unique = True,
requires = [IS_NOT_EMPTY(error_message=T("Please fill this!")),
IS_NOT_ONE_OF(db, "project_project.name")]
),
Field("code",
label = T("Code"),
readable=False,
writable=False,
),
Field("description", "text",
label = T("Description")),
# NB There is additional client-side validation for start/end date in the Controller
Field("start_date", "date",
label = T("Start date"),
represent = s3_date_represent,
requires = IS_NULL_OR(IS_DATE(format = s3_date_format)),
widget = S3DateWidget()
),
Field("end_date", "date",
label = T("End date"),
represent = s3_date_represent,
requires = IS_NULL_OR(IS_DATE(format = s3_date_format)),
widget = S3DateWidget()
),
Field("duration",
readable=False,
writable=False,
label = T("Duration")),
Field("calendar",
readable=False if drr else True,
writable=False if drr else True,
label = T("Calendar"),
requires = IS_NULL_OR(IS_URL()),
comment = DIV(_class="tooltip",
_title="%s|%s" % (T("Calendar"),
T("URL to a Google Calendar to display on the project timeline.")))),
currency_type(
readable=False if drr else True,
writable=False if drr else True,
),
Field("budget", "double",
# DRR handles on the Organisations Tab
readable=False if drr else True,
writable=False if drr else True,
label = T("Budget")),
sector_id(
#readable=False,
#writable=False,
widget=lambda f, v: \
CheckboxesWidget.widget(f, v, cols=3)),
countries_id(
readable=drr,
writable=drr
),
multi_hazard_id(
readable=drr,
writable=drr
),
multi_theme_id(
readable=drr,
writable=drr
),
Field("hfa", "list:integer",
label = T("HFA Priorities"),
readable=drr,
writable=drr,
requires = IS_NULL_OR(IS_IN_SET(project_hfa_opts,
multiple = True)),
represent = self.hfa_opts_represent,
widget = CheckboxesWidgetS3.widget),
Field("objectives", "text",
readable = drr,
writable = drr,
label = T("Objectives")),
human_resource_id(label=T("Contact Person")),
comments(comment=DIV(_class="tooltip",
_title="%s|%s" % (T("Comments"),
T("Outcomes, Impact, Challenges")))),
format="%(name)s",
*meta_fields())
# Field configuration?
# CRUD Strings
ADD_PROJECT = T("Add Project")
crud_strings[tablename] = Storage(
title_create = ADD_PROJECT,
title_display = T("Project Details"),
title_list = T("List Projects"),
title_update = T("Edit Project"),
title_search = T("Search Projects"),
title_upload = T("Import Project List"),
subtitle_create = T("Add New Project"),
subtitle_list = T("Projects"),
subtitle_upload = T("Upload Project List"),
label_list_button = T("List Projects"),
label_create_button = ADD_PROJECT,
label_delete_button = T("Delete Project"),
msg_record_created = T("Project added"),
msg_record_modified = T("Project updated"),
msg_record_deleted = T("Project deleted"),
msg_list_empty = T("No Projects currently registered"))
# Search Method
if settings.get_ui_cluster():
sector = T("Cluster")
else:
sector = T("Sector")
if drr:
project_search = S3Search(
advanced = (
S3SearchSimpleWidget(
name = "project_search_text_advanced",
label = T("Description"),
comment = T("Search for a Project by description."),
field = [ "name",
"description",
]
),
S3SearchOptionsWidget(
name = "project_search_sector",
label = sector,
field = ["sector_id"],
cols = 4
),
S3SearchOptionsWidget(
name = "project_search_hazard",
label = T("Hazard"),
field = ["multi_hazard_id"],
cols = 4
),
S3SearchOptionsWidget(
name = "project_search_theme",
label = T("Theme"),
field = ["multi_theme_id"],
cols = 4
),
S3SearchOptionsWidget(
name = "project_search_hfa",
label = T("HFA"),
field = ["hfa"],
cols = 4
),
)
)
else:
project_search = S3Search(
advanced = (
S3SearchSimpleWidget(
name = "project_search_text_advanced",
label = T("Description"),
comment = T("Search for a Project by description."),
field = [ "name",
"description",
]
),
S3SearchOptionsWidget(
name = "project_search_sector",
label = sector,
field = ["sector_id"],
cols = 4
),
)
)
# Resource Configuration
if drr:
next = "organisation"
else:
next = "activity"
if drr:
table.virtualfields.append(S3ProjectVirtualfields())
list_fields=["id",
"name",
(T("Lead Organisation"), "organisation"),
"sector_id",
"start_date",
"end_date",
"countries_id",
"multi_hazard_id",
"multi_theme_id",
]
else:
list_fields=["id",
"name",
"organisation_id",
"start_date",
"end_date",
]
configure(tablename,
super_entity="doc_entity",
deduplicate=self.project_project_deduplicate,
onvalidation=self.project_project_onvalidation,
onaccept=self.project_project_onaccept,
create_next=URL(c="project", f="project",
args=["[id]", next]),
search_method=project_search,
list_fields=list_fields)
# Reusable Field
project_id = S3ReusableField("project_id", db.project_project,
sortby="name",
requires = IS_NULL_OR(IS_ONE_OF(db, "project_project.id",
"%(name)s")),
represent = self.project_represent,
comment = s3_popup_comment(c="project",
f="project",
title=ADD_PROJECT,
tooltip=T("If you don't see the project in the list, you can add a new one by clicking link 'Add Project'.")),
label = T("Project"),
ondelete = "CASCADE")
# ---------------------------------------------------------------------
# Custom Methods
self.set_method(tablename,
method="timeline",
action=self.project_timeline)
# Components
# Organisations
add_component("project_organisation", project_project="project_id")
# Sites
add_component("project_site", project_project="project_id")
# Activities
add_component("project_activity", project_project="project_id")
# Milestones
add_component("project_milestone", project_project="project_id")
# Beneficiaries
add_component("project_beneficiary", project_project="project_id")
# Tasks
add_component("project_task",
project_project=Storage(
link="project_task_project",
joinby="project_id",
key="task_id",
actuate="replace",
autocomplete="name",
autodelete=False))
# ---------------------------------------------------------------------
# Activity Type
#
tablename = "project_activity_type"
table = define_table(tablename,
Field("name", length=128,
notnull=True, unique=True),
format="%(name)s",
*meta_fields())
# Field configuration?
# CRUD Strings
ADD_ACTIVITY_TYPE = T("Add Activity Type")
LIST_ACTIVITY_TYPES = T("List of Activity Types")
crud_strings[tablename] = Storage(
title_create = ADD_ACTIVITY_TYPE,
title_display = T("Activity Type"),
title_list = LIST_ACTIVITY_TYPES,
title_update = T("Edit Activity Type"),
title_search = T("Search for Activity Type"),
subtitle_create = T("Add New Activity Type"),
subtitle_list = T("All Activity Types"),
label_list_button = LIST_ACTIVITY_TYPES,
label_create_button = ADD_ACTIVITY_TYPE,
msg_record_created = T("Activity Type Added"),
msg_record_modified = T("Activity Type Updated"),
msg_record_deleted = T("Activity Type Deleted"),
msg_list_empty = T("No Activity Types Found")
)
# Search Method?
# Resource Configuration?
# Reusable Fields
activity_type_id = S3ReusableField("activity_type_id",
db.project_activity_type,
sortby="name",
requires = IS_NULL_OR(IS_ONE_OF(db,
"project_activity_type.id",
"%(name)s",
sort=True)),
represent = lambda id, row=None: \
s3_get_db_field_value(tablename = "project_activity_type",
fieldname = "name",
look_up_value = id),
label = T("Activity Type"),
comment = s3_popup_comment(c="project",
f="activity_type",
title=ADD_ACTIVITY_TYPE,
tooltip=T("If you don't see the type in the list, you can add a new one by clicking link 'Add Activity Type'.")),
ondelete = "RESTRICT")
multi_activity_type_id = S3ReusableField("multi_activity_type_id",
"list:reference project_activity_type",
sortby = "name",
label = T("Types of Activities"),
requires = IS_NULL_OR(IS_ONE_OF(db,
"project_activity_type.id",
"%(name)s",
sort=True,
multiple=True)),
represent = lambda opt, row=None: \
self.multiref_represent(opt,
"project_activity_type"),
#comment = skill_help,
default = [],
widget = lambda f, v: \
CheckboxesWidgetS3.widget(f, v, col=3),
ondelete = "RESTRICT")
# ---------------------------------------------------------------------
# Project Activity
#
tablename = "project_activity"
table = define_table(tablename,
super_link("doc_id", "doc_entity"),
project_id(),
Field("name",
label = T("Short Description"),
requires=IS_NOT_EMPTY()),
location_id(
readable = drr,
writable = drr,
widget = S3LocationSelectorWidget(hide_address=True)),
multi_activity_type_id(),
Field("time_estimated", "double",
readable=False if drr else True,
writable=False if drr else True,
label = "%s (%s)" % (T("Time Estimate"),
T("hours"))),
Field("time_actual", "double",
readable=False if drr else True,
# Gets populated from constituent Tasks
writable=False,
label = "%s (%s)" % (T("Time Taken"),
T("hours"))),
comments(),
format="%(name)s",
*meta_fields())
# Field configuration
if pca:
table.name.label = T("Name") # for list_fields
table.name.readable = False
table.name.writable = False
table.name.requires = None
# CRUD Strings
if pca:
ACTIVITY = T("Community")
ACTIVITY_TOOLTIP = T("If you don't see the community in the list, you can add a new one by clicking link 'Add Community'.")
ADD_ACTIVITY = T("Add Community")
LIST_ACTIVITIES = T("List Communities")
crud_strings[tablename] = Storage(
title_create = ADD_ACTIVITY,
title_display = T("Community Details"),
title_list = LIST_ACTIVITIES,
title_update = T("Edit Community Details"),
title_search = T("Search Community"),
title_upload = T("Import Community Data"),
title_report = T("Who is doing What Where"),
subtitle_create = T("Add New Community"),
subtitle_list = T("Communities"),
subtitle_report = T("Communities"),
label_list_button = LIST_ACTIVITIES,
label_create_button = ADD_ACTIVITY,
msg_record_created = T("Community Added"),
msg_record_modified = T("Community Updated"),
msg_record_deleted = T("Community Deleted"),
msg_list_empty = T("No Communities Found")
)
else:
ACTIVITY = T("Activity")
ACTIVITY_TOOLTIP = T("If you don't see the activity in the list, you can add a new one by clicking link 'Add Activity'.")
ADD_ACTIVITY = T("Add Activity")
LIST_ACTIVITIES = T("List Activities")
crud_strings[tablename] = Storage(
title_create = ADD_ACTIVITY,
title_display = T("Activity Details"),
title_list = LIST_ACTIVITIES,
title_update = T("Edit Activity"),
title_search = T("Search Activities"),
title_upload = T("Import Activity Data"),
title_report = T("Who is doing What Where") if drr else T("Activity Report"),
subtitle_create = T("Add New Activity"),
subtitle_list = T("Activities"),
subtitle_report = T("Activities"),
label_list_button = LIST_ACTIVITIES,
label_create_button = ADD_ACTIVITY,
msg_record_created = T("Activity Added"),
msg_record_modified = T("Activity Updated"),
msg_record_deleted = T("Activity Deleted"),
msg_list_empty = T("No Activities Found")
)
# Virtual Fields
if drr:
table.virtualfields.append(S3ProjectActivityVirtualfields())
# Search Method
if pca:
project_activity_search = S3Search(field="location_id$name")
else:
project_activity_search = S3Search(field="name")
# Resource Configuration
report_fields = []
append = report_fields.append
if drr:
append((T("Organization"), "organisation"))
append((T("Project"), "project_id"))
if not pca:
append((T("Activity"), "name"))
append((T("Activity Type"), "multi_activity_type_id"))
if drr:
append((T("Sector"), "project_id$sector_id"))
append((T("Theme"), "project_id$multi_theme_id"))
append((T("Hazard"), "project_id$multi_hazard_id"))
append((T("HFA"), "project_id$hfa"))
lh = current.gis.get_location_hierarchy()
lh = [(lh[opt], opt) for opt in lh]
report_fields.extend(lh)
append("location_id")
list_fields = ["name",
"project_id",
"multi_activity_type_id",
"comments"
]
else:
append((T("Time Estimated"), "time_estimated"))
append((T("Time Actual"), "time_actual"))
list_fields = ["name",
"project_id",
"location_id",
"multi_activity_type_id",
"comments"
]
if drr:
next = "beneficiary"
else:
next = "task"
configure(tablename,
super_entity="doc_entity",
create_next=URL(c="project", f="activity",
args=["[id]", next]),
search_method=project_activity_search,
onvalidation=self.project_activity_onvalidation,
deduplicate=self.project_activity_deduplicate,
report_rows=report_fields,
report_cols=report_fields,
report_fact=report_fields,
list_fields = list_fields,
)
# Reusable Field
activity_id = S3ReusableField("activity_id", db.project_activity,
sortby="name",
requires = IS_NULL_OR(IS_ONE_OF(db,
"project_activity.id",
"%(name)s",
sort=True)),
represent = lambda id, row=None: \
s3_get_db_field_value(tablename = "project_activity",
fieldname = "name",
look_up_value = id),
label = ACTIVITY,
comment = s3_popup_comment(c="project",
f="activity",
title=ADD_ACTIVITY,
tooltip=ACTIVITY_TOOLTIP),
ondelete = "CASCADE")
# Components
# Contact Persons
add_component("pr_person",
project_activity=Storage(
name="contact",
link="project_activity_contact",
joinby="activity_id",
key="person_id",
actuate="hide",
autodelete=False))
# Beneficiaries
add_component("project_beneficiary",
project_activity="activity_id")
# Tasks
add_component("project_task",
project_activity=Storage(
link="project_task_activity",
joinby="activity_id",
key="task_id",
actuate="replace",
autocomplete="name",
autodelete=False))
# ---------------------------------------------------------------------
# Project Activity Contact Person
#
# @ToDo: This is a Community Contact nmot an Activity contact,l so
# should be renamed when we add proper Communities
#
tablename = "project_activity_contact"
table = define_table(tablename,
activity_id(),
person_id(widget=S3AddPersonWidget(controller="pr"),
requires=IS_ADD_PERSON_WIDGET(),
comment=None),
*meta_fields())
table.virtualfields.append(S3ProjectActivityContactVirtualFields())
# CRUD Strings
ADD_CONTACT = T("Add Contact")
LIST_CONTACTS = T("List Contacts")
if pca:
LIST_OF_CONTACTS = T("Community Contacts")
else:
LIST_OF_CONTACTS = T("Contacts")
crud_strings[tablename] = Storage(
title_create = ADD_CONTACT,
title_display = T("Contact Details"),
title_list = LIST_CONTACTS,
title_update = T("Edit Contact Details"),
title_search = T("Search Contacts"),
subtitle_create = T("Add New Contact"),
subtitle_list = LIST_OF_CONTACTS,
label_list_button = LIST_CONTACTS,
label_create_button = ADD_CONTACT,
msg_record_created = T("Contact Added"),
msg_record_modified = T("Contact Updated"),
msg_record_deleted = T("Contact Deleted"),
msg_list_empty = T("No Contacts Found"))
activity_contact_search = S3Search(
advanced=(S3SearchSimpleWidget(
name = "activity_contact_search_simple",
label = T("Name"),
comment = T("You can search by person name - enter any of the first, middle or last names, separated by spaces. You may use % as wildcard. Press 'Search' without input to list all persons."),
field = ["person_id$first_name",
"person_id$middle_name",
"person_id$last_name"
]
),
S3SearchLocationHierarchyWidget(
name="activity_contact_search_L1",
field="person_id$L1",
cols = 3,
),
S3SearchLocationHierarchyWidget(
name="activity_contact_search_L2",
field="person_id$L2",
cols = 3,
),
))
# Resource configuration
hierarchy = current.gis.get_location_hierarchy()
configure(tablename,
search_method=activity_contact_search,
list_fields=["activity_id",
(T("Project"), "activity_id$project_id"),
"person_id",
(hierarchy["L0"], "person_id$L0"),
(hierarchy["L1"], "person_id$L1"),
(hierarchy["L2"], "person_id$L2"),
(hierarchy["L3"], "person_id$L3"),
(T("Email"), "email"),
(T("Mobile Phone"), "sms")])
# ---------------------------------------------------------------------
# Pass variables back to global scope (response.s3.*)
#
return dict(
project_project_id = project_id,
project_activity_id = activity_id,
project_hfa_opts = project_hfa_opts,
project_project_represent = self.project_represent,
)
# -------------------------------------------------------------------------
def defaults(self):
""" Safe defaults for model-global names if module is disabled """
dummy = S3ReusableField("dummy_id", "integer",
readable=False,
writable=False)
return Storage(
project_project_id = lambda: dummy("project_id"),
project_activity_id = lambda: dummy("activity_id"),
project_project_represent = lambda v, r: current.messages.NONE
)
# -------------------------------------------------------------------------
@staticmethod
def multiref_represent(opts, tablename, represent_string = "%(name)s"):
"""
Represent a list of references
@param opt: the current value or list of values
@param tablename: the referenced table
@param represent_string: format string to represent the records
"""
DEFAULT = ""
db = current.db
s3db = current.s3db
UNKNOWN_OPT = current.messages.UNKNOWN_OPT
table = s3db.table(tablename, None)
if table is None:
return DEFAULT
if not isinstance(opts, (list, tuple)):
opts = [opts]
rows = db(table.id.belongs(opts)).select()
rstr = Storage([(str(row.id), row) for row in rows])
keys = rstr.keys()
represent = lambda o: str(o) in keys and \
represent_string % rstr[str(o)] or UNKNOWN_OPT
vals = [represent(o) for o in opts]
if len(opts) > 1:
vals = ", ".join(vals)
else:
vals = len(vals) and vals[0] or DEFAULT
return vals
# ---------------------------------------------------------------------
@staticmethod
def project_represent(id, row=None, show_link=True):
""" FK representation """
db = current.db
NONE = current.messages.NONE
if id:
val = (id and [db.project_project[id].name] or [NONE])[0]
if not show_link:
return val
return A(val, _href = URL(c="project",
f="project",
args=[id]))
else:
return NONE
# ---------------------------------------------------------------------
@staticmethod
def project_project_onvalidation(form):
""" Form validation """
if not form.vars.code and "name" in form.vars:
# Populate code from name
form.vars.code = form.vars.name
return
# ---------------------------------------------------------------------
@staticmethod
def project_project_onaccept(form):
""" Set the project to be owned by the customer """
db = current.db
s3db = current.s3db
if "organisation_id" in form.vars:
# Set Project to be owned by this Customer
organisation_id = form.vars.organisation_id
otable = s3db.org_organisation
query = (otable.id == organisation_id)
role = db(query).select(otable.owned_by_organisation,
limitby=(0, 1)).first()
if role:
table = s3db.project_project
query = (table.id == form.vars.id)
db(query).update(owned_by_organisation=role.owned_by_organisation)
return
# ---------------------------------------------------------------------
@staticmethod
def project_project_deduplicate(item):
""" Import item de-duplication """
if item.id:
return
if item.tablename == "project_project" and \
"name" in item.data:
# Match project by name (all-lowercase)
table = item.table
name = item.data.name
try:
query = (table.name.lower() == name.lower())
except AttributeError, exception:
s3_debug("project_deduplicate", exception.message)
else:
duplicate = current.db(query).select(table.id,
table.name,
limitby=(0, 1)).first()
if duplicate:
item.id = duplicate.id
item.data.name = duplicate.name
item.method = item.METHOD.UPDATE
return
# -------------------------------------------------------------------------
@staticmethod
def project_timeline(r, **attr):
"""
Display the project on a Simile Timeline
http://www.simile-widgets.org/wiki/Reference_Documentation_for_Timeline
Currently this just displays a Google Calendar
@ToDo: Add Milestones
@ToDo: Filters for different 'layers'
@ToDo: export milestones/tasks as .ics
"""
if r.representation == "html" and r.name == "project":
T = current.T
request = current.request
response = current.response
session = current.session
s3 = response.s3
calendar = r.record.calendar
# Add core Simile Code
s3.scripts.append("/%s/static/scripts/simile/timeline/timeline-api.js" % request.application)
# Pass vars to our JS code
s3.js_global.append("S3.timeline.calendar = '%s';" % calendar)
# Add our control script
if session.s3.debug:
s3.scripts.append("/%s/static/scripts/S3/s3.timeline.js" % request.application)
else:
s3.scripts.append("/%s/static/scripts/S3/s3.timeline.min.js" % request.application)
# Create the DIV
item = DIV(_id="s3timeline", _style="height: 400px; border: 1px solid #aaa; font-family: Trebuchet MS, sans-serif; font-size: 85%;")
output = dict(item=item)
output["title"] = T("Project Calendar")
# Maintain RHeader for consistency
if "rheader" in attr:
rheader = attr["rheader"](r)
if rheader:
output["rheader"] = rheader
response.view = "timeline.html"
return output
else:
raise HTTP(501, BADMETHOD)
# ---------------------------------------------------------------------
@staticmethod
def hfa_opts_represent(opt, row=None):
""" Option representation """
s3 = current.response.s3
NONE = current.messages.NONE
project_hfa_opts = s3.project_hfa_opts
opts = opt
if isinstance(opt, int):
opts = [opt]
elif not isinstance(opt, (list, tuple)):
return NONE
vals = [project_hfa_opts.get(o, NONE) for o in opts]
return ", ".join(vals)
# ---------------------------------------------------------------------
@staticmethod
def project_activity_onvalidation(form):
""" """
pca = current.deployment_settings.get_project_community_activity()
if pca:
location_id = form.vars.location_id
if location_id:
db = current.db
s3db = current.s3db
table = s3db.gis_location
query = (table.id == form.vars.location_id)
row = db(query).select(table.parent,
limitby=(0, 1)).first()
if row and row.parent:
query = (table.id == row.parent)
parent = db(query).select(table.name,
limitby=(0, 1)).first()
if parent:
form.vars.name = parent.name
return
# ---------------------------------------------------------------------
@staticmethod
def project_activity_deduplicate(item):
""" Import item de-duplication """
db = current.db
settings = current.deployment_settings
pca = settings.get_project_community_activity()
if item.id:
return
if item.tablename != "project_activity":
return
table = item.table
duplicate = None
if pca:
if "project_id" in item.data and \
"location_id" in item.data:
# Match activity by project_id and location_id
project_id = item.data.project_id
location_id = item.data.location_id
query = (table.project_id == project_id) & \
(table.location_id == location_id)
duplicate = db(query).select(table.id,
limitby=(0, 1)).first()
else:
if "project_id" in item.data and "name" in item.data:
# Match activity by project_id and name
project_id = item.data.project_id
name = item.data.name
query = (table.project_id == project_id) & \
(table.name == name)
duplicate = db(query).select(table.id,
limitby=(0, 1)).first()
if duplicate:
item.id = duplicate.id
item.method = item.METHOD.UPDATE
return
# =============================================================================
class S3ProjectDRRModel(S3Model):
"""
Project DRR Model
This class contains the tabels suitable for use by multinational
organisations tracking projects at a high level
"""
names = ["project_organisation",
#"project_site",
"project_beneficiary_type",
"project_beneficiary",
"project_organisation_roles",
"project_organisation_lead_role"
]
def model(self):
T = current.T
db = current.db
s3 = current.response.s3
currency_type = s3.currency_type
#location_id = self.gis_location_id
organisation_id = self.org_organisation_id
project_id = self.project_project_id
activity_id = self.project_activity_id
#multi_activity_type_id = self.project_multi_activity_type_id
pca = current.deployment_settings.get_project_community_activity()
messages = current.messages
NONE = messages.NONE
# ---------------------------------------------------------------------
# Project Organisation
#
project_organisation_roles = {
1: T("Lead Implementer"), # T("Host National Society")
2: T("Partner"), # T("Partner National Society")
3: T("Donor"),
4: T("Customer"), # T("Beneficiary")?
}
project_organisation_lead_role = 1
organisation_help = T("Add all organizations which are involved in different roles in this project")
tablename = "project_organisation"
table = self.define_table(tablename,
project_id(),
organisation_id(comment = DIV(A(T("Add Organization"),
_class="colorbox",
_href=URL(c="org", f="organisation",
args="create",
vars=dict(format="popup")),
_target="top",
_title=T("Add Organization")),
DIV(_class="tooltip",
_title="%s|%s" % (T("Organization"),
organisation_help))
)
),
Field("role", "integer",
requires = IS_NULL_OR(IS_IN_SET(project_organisation_roles)),
represent = lambda opt, row=None: \
project_organisation_roles.get(opt, NONE)),
Field("amount", "double",
requires = IS_FLOAT_AMOUNT(),
represent = lambda v, row=None: \
IS_FLOAT_AMOUNT.represent(v, precision=2),
widget = IS_FLOAT_AMOUNT.widget,
label = T("Funds Contributed by this Organization")),
currency_type(),
s3.comments(),
*s3.meta_fields())
# Field configuration?
# CRUD Strings
ADD_PROJECT_ORG = T("Add Organization to Project")
LIST_PROJECT_ORG = T("List Project Organizations")
s3.crud_strings[tablename] = Storage(
title_create = ADD_PROJECT_ORG,
title_display = T("Project Organization Details"),
title_list = LIST_PROJECT_ORG,
title_update = T("Edit Project Organization"),
title_search = T("Search Project Organizations"),
title_upload = T("Import Project Organizations"),
title_report = T("Funding Report"),
subtitle_create = T("Add Organization to Project"),
subtitle_list = T("Project Organizations"),
subtitle_report = T("Funding"),
label_list_button = LIST_PROJECT_ORG,
label_create_button = ADD_PROJECT_ORG,
label_delete_button = T("Remove Organization from Project"),
msg_record_created = T("Organization added to Project"),
msg_record_modified = T("Project Organization updated"),
msg_record_deleted = T("Organization removed from Project"),
msg_list_empty = T("No Organizations for this Project"))
# Search Method?
# Resource Configuration
self.configure(tablename,
deduplicate=self.project_organisation_deduplicate,
onvalidation=self.project_organisation_onvalidation)
# Reusable Field
# Components
# ---------------------------------------------------------------------
# Project Site
# @ToDo: Deprecated?
#
# tablename = "project_site"
# table = self.define_table(tablename,
# self.super_link("site_id", "org_site"),
# project_id(),
# Field("name", notnull=True,
# length=64, # Mayon Compatibility
# label = T("Name")),
# location_id(),
# multi_activity_type_id(),
# *(s3.address_fields() + s3.meta_fields()))
# Field configuration
# CRUD Strings
# Search Method
# Resource Configuration
# Reusable Field
# CRUD strings
# ADD_PROJECT_SITE = T("Add Project Site")
# LIST_PROJECT_SITE = T("List Project Sites")
# s3.crud_strings[tablename] = Storage(
# title_create = ADD_PROJECT_SITE,
# title_display = T("Project Site Details"),
# title_list = LIST_PROJECT_SITE,
# title_update = T("Edit Project Site"),
# title_search = T("Search Project Sites"),
# title_upload = T("Import Project Sites"),
# subtitle_create = T("Add New Project Site"),
# subtitle_list = T("Sites"),
# label_list_button = LIST_PROJECT_SITE,
# label_create_button = ADD_PROJECT_SITE,
# label_delete_button = T("Delete Project Site"),
# msg_record_created = T("Project Site added"),
# msg_record_modified = T("Project Site updated"),
# msg_record_deleted = T("Project Site deleted"),
# msg_list_empty = T("No Project Sites currently registered"))
# project_site_id = S3ReusableField("project_site_id", db.project_site,
# #sortby="default/indexname",
# requires = IS_NULL_OR(IS_ONE_OF(db, "project_site.id", "%(name)s")),
# represent = lambda id, row=None: \
# (id and [db(db.project_site.id == id).select(db.project_site.name,
# limitby=(0, 1)).first().name] or [NONE])[0],
# label = T("Project Site"),
# comment = s3_popup_comment(c="project",
# f="site",
# title=ADD_PROJECT_SITE,
# tooltip=T("If you don't see the site in the list, you can add a new one by clicking link 'Add Project Site'.")),,
# ondelete = "CASCADE")
# self.configure(tablename,
# super_entity="org_site",
# onvalidation=s3.address_onvalidation)
# ---------------------------------------------------------------------
# Project Beneficiary Type
#
tablename = "project_beneficiary_type"
table = self.define_table(tablename,
Field("name",
length=128,
unique=True,
requires = IS_NOT_IN_DB(db,
"project_beneficiary_type.name")),
*s3.meta_fields())
# Field configuration?
# CRUD Strings
ADD_BNF_TYPE = T("Add Beneficiary Type")
LIST_BNF_TYPE = T("List Beneficiary Types")
s3.crud_strings[tablename] = Storage(
title_create = ADD_BNF_TYPE,
title_display = T("Beneficiary Type"),
title_list = LIST_BNF_TYPE,
title_update = T("Edit Beneficiary Type"),
title_search = T("Search Beneficiary Types"),
subtitle_create = T("Add New Beneficiary Type"),
subtitle_list = T("Beneficiary Types"),
label_list_button = LIST_BNF_TYPE,
label_create_button = ADD_BNF_TYPE,
msg_record_created = T("Beneficiary Type Added"),
msg_record_modified = T("Beneficiary Type Updated"),
msg_record_deleted = T("Beneficiary Type Deleted"),
msg_list_empty = T("No Beneficiary Types Found")
)
# Search Method?
# Resource Configuration?
# Reusable Field
beneficiary_type_id = S3ReusableField("beneficiary_type_id", db.project_beneficiary_type,
requires = IS_NULL_OR(IS_ONE_OF(db,
"project_beneficiary_type.id",
self.beneficiary_type_represent)),
represent = self.beneficiary_type_represent,
label = T("Beneficiary Type"),
comment = s3_popup_comment(c="project",
f="beneficiary_type",
title=ADD_BNF_TYPE,
tooltip=T("Please record Beneficiary according to the reporting needs of your project")),
ondelete = "CASCADE")
# ---------------------------------------------------------------------
# Project Beneficiary
#
tablename = "project_beneficiary"
table = self.define_table(tablename,
# populated automatically
project_id(readable=False,
writable=False),
activity_id(comment=None),
beneficiary_type_id(empty=False),
Field("number", "integer",
label = T("Quantity"),
requires = IS_INT_IN_RANGE(0, 99999999)),
s3.comments(),
*s3.meta_fields())
# Field configuration
if pca:
table.activity_id.label = T("Community")
# CRUD Strings
ADD_BNF = T("Add Beneficiaries")
LIST_BNF = T("List Beneficiaries")
s3.crud_strings[tablename] = Storage(
title_create = ADD_BNF,
title_display = T("Beneficiaries Details"),
title_list = LIST_BNF,
title_update = T("Edit Beneficiaries"),
title_search = T("Search Beneficiaries"),
title_report = T("Beneficiary Report"),
subtitle_create = T("Add New Beneficiaries"),
subtitle_list = T("Beneficiaries"),
label_list_button = LIST_BNF,
label_create_button = ADD_BNF,
msg_record_created = T("Beneficiaries Added"),
msg_record_modified = T("Beneficiaries Updated"),
msg_record_deleted = T("Beneficiaries Deleted"),
msg_list_empty = T("No Beneficiaries Found")
)
table.virtualfields.append(S3ProjectBeneficiaryVirtualfields())
# Search Method?
# Resource Configuration
report_fields=[
"activity_id",
(T("Beneficiary Type"), "beneficiary_type_id"),
"project_id",
"project_id$multi_hazard_id",
"project_id$multi_theme_id",
"activity_id$multi_activity_type_id"
]
lh = current.gis.get_location_hierarchy()
lh = [(lh[opt], opt) for opt in lh]
report_fields.extend(lh)
self.configure(tablename,
onaccept=self.project_beneficiary_onaccept,
deduplicate=self.project_beneficiary_deduplicate,
report_filter=[
S3SearchOptionsWidget(
field=["project_id"],
name="project",
label=T("Project")
),
S3SearchOptionsWidget(
field=["beneficiary_type_id"],
name="beneficiary_type_id",
label=T("Beneficiary Type")
),
# Can't search be VirtualFields currently
# S3SearchLocationHierarchyWidget(
# name="beneficiary_search_L1",
# field="activity_id$L1",
# cols = 3,
# ),
],
report_rows=report_fields,
report_cols=report_fields,
report_fact=["number"],
report_method=["sum"])
# Reusable Field
beneficiary_id = S3ReusableField("beneficiary_id", db.project_beneficiary,
sortby="name",
requires = IS_NULL_OR(IS_ONE_OF(db,
"project_beneficiary.id",
"%(type)s",
sort=True)),
represent = lambda id, row=None: \
s3_get_db_field_value(tablename = "project_beneficiary",
fieldname = "type",
look_up_value = id),
label = T("Beneficiaries"),
comment = s3_popup_comment(c="project",
f="beneficiary",
title=ADD_BNF,
tooltip=T("If you don't see the beneficiary in the list, you can add a new one by clicking link 'Add Beneficiary'.")),
ondelete = "SET NULL")
# ---------------------------------------------------------------------
# Pass variables back to global scope (response.s3.*)
#
return dict(
project_organisation_roles = project_organisation_roles,
project_organisation_lead_role = project_organisation_lead_role,
)
# -------------------------------------------------------------------------
def defaults(self):
""" Safe defaults for model-global names if module is disabled """
dummy = S3ReusableField("dummy_id", "integer",
readable=False,
writable=False)
return Storage(
)
# ---------------------------------------------------------------------
@staticmethod
def project_organisation_onvalidation(form, lead_role=None):
""" Form validation """
db = current.db
s3db = current.s3db
s3 = current.response.s3
otable = s3db.project_organisation
if lead_role is None:
lead_role = s3.project_organisation_lead_role
project_id = form.vars.project_id
organisation_id = form.vars.organisation_id
if str(form.vars.role) == str(lead_role) and project_id:
query = (otable.deleted != True) & \
(otable.project_id == project_id) & \
(otable.role == lead_role) & \
(otable.organisation_id != organisation_id)
row = db(query).select(otable.id, limitby=(0, 1)).first()
if row:
form.errors.role = T("Lead Implementer for this project is already set, please choose another role.")
return
# ---------------------------------------------------------------------
@staticmethod
def project_organisation_deduplicate(item):
""" Import item de-duplication """
db = current.db
if item.id:
return
if item.tablename == "project_organisation" and \
"project_id" in item.data and \
"organisation_id" in item.data:
# Match project by org_id and project_id
table = item.table
project_id = item.data.project_id
organisation_id = item.data.organisation_id
query = (table.project_id == project_id) & \
(table.organisation_id == organisation_id)
duplicate = db(query).select(table.id,
limitby=(0, 1)).first()
if duplicate:
item.id = duplicate.id
item.method = item.METHOD.UPDATE
return
# ---------------------------------------------------------------------
@staticmethod
def beneficiary_type_represent(type_id, row=None):
""" FK representation """
db = current.db
s3db = current.s3db
UNKNOWN_OPT = current.messages.UNKNOWN_OPT
if isinstance(type_id, Row):
if "name" in type_id:
return type_id.name
elif "id" in type_id:
type_id = type_id.id
else:
return UNKNOWN_OPT
bnf_type = s3db.project_beneficiary_type
query = bnf_type.id == type_id
row = db(query).select(bnf_type.name, limitby=(0, 1)).first()
if row:
return row.name
else:
return UNKNOWN_OPT
# ---------------------------------------------------------------------
@staticmethod
def project_beneficiary_onaccept(form):
""" Record creation post-processing """
db = current.db
s3db = current.s3db
btable = s3db.project_beneficiary
atable = s3db.project_activity
record_id = form.vars.id
query = (btable.id == record_id) & \
(atable.id == btable.activity_id)
activity = db(query).select(atable.project_id,
limitby=(0, 1)).first()
if activity:
db(btable.id == record_id).update(project_id=activity.project_id)
return
# ---------------------------------------------------------------------
@staticmethod
def project_beneficiary_deduplicate(item):
""" Import item de-duplication """
db = current.db
if item.id:
return
if item.tablename == "project_beneficiary" and \
"beneficiary_type_id" in item.data and \
"activity_id" in item.data:
# Match beneficiary by type and activity_id
table = item.table
beneficiary_type_id = item.data.beneficiary_type_id
activity_id = item.data.activity_id
query = (table.beneficiary_type_id == beneficiary_type_id) & \
(table.activity_id == activity_id)
duplicate = db(query).select(table.id,
limitby=(0, 1)).first()
if duplicate:
item.id = duplicate.id
item.method = item.METHOD.UPDATE
return
# =============================================================================
class S3ProjectTaskModel(S3Model):
"""
Project Task Model
This class holds the tables used for a smaller Organisation to manage
their Tasks in detail.
"""
names = ["project_milestone",
"project_task",
"project_time",
"project_comment",
"project_task_project",
"project_task_activity",
"project_task_id",
]
def model(self):
db = current.db
T = current.T
auth = current.auth
request = current.request
s3 = current.response.s3
settings = current.deployment_settings
person_id = self.pr_person_id
location_id = self.gis_location_id
site_id = self.org_site_id
project_id = self.project_project_id
activity_id = self.project_activity_id
s3_date_format = settings.get_L10n_date_format()
s3_utc_represent = lambda dt: S3DateTime.datetime_represent(dt, utc=True)
s3_date_represent = lambda dt: S3DateTime.date_represent(dt, utc=True)
messages = current.messages
NONE = messages.NONE
UNKNOWN_OPT = messages.UNKNOWN_OPT
# Shortcuts
add_component = self.add_component
comments = s3.comments
configure = self.configure
crud_strings = s3.crud_strings
define_table = self.define_table
super_link = self.super_link
meta_fields = s3.meta_fields
# ---------------------------------------------------------------------
# Project Milestone
#
tablename = "project_milestone"
table = define_table(tablename,
# Stage Report
super_link("doc_id", "doc_entity"),
project_id(),
Field("name",
label = T("Short Description"),
requires=IS_NOT_EMPTY()),
Field("date", "date",
label = T("Date"),
represent = s3_date_represent,
requires = IS_NULL_OR(IS_DATE(format = s3_date_format))),
comments(),
format="%(name)s",
*meta_fields())
# CRUD Strings
ADD_MILESTONE = T("Add Milestone")
crud_strings[tablename] = Storage(
title_create = ADD_MILESTONE,
title_display = T("Milestone Details"),
title_list = T("List Milestones"),
title_update = T("Edit Milestone"),
title_search = T("Search Milestones"),
title_upload = T("Import Milestone Data"),
subtitle_create = T("Add New Milestone"),
subtitle_list = T("Milestones"),
subtitle_report = T("Milestones"),
label_list_button = T("List Milestones"),
label_create_button = ADD_MILESTONE,
msg_record_created = T("Milestone Added"),
msg_record_modified = T("Milestone Updated"),
msg_record_deleted = T("Milestone Deleted"),
msg_list_empty = T("No Milestones Found")
)
# Reusable Field
milestone_id = S3ReusableField("milestone_id", db.project_milestone,
sortby="name",
requires = IS_NULL_OR(IS_ONE_OF(db, "project_milestone.id",
"%(name)s")),
represent = self.milestone_represent,
comment = s3_popup_comment(c="project",
f="milestone",
title=ADD_MILESTONE,
tooltip=T("A project milestone marks a significant date in the calendar which shows that progress towards the overall objective is being made.")),
label = T("Milestone"),
ondelete = "RESTRICT")
# ---------------------------------------------------------------------
# Tasks
#
# Tasks can be linked to Activities or directly to Projects
# - they can also be used by the Event/Scenario modules
#
# @ToDo: Recurring tasks
#
# These Statuses can be customised, although doing so limits the ability to do synchronization
# - best bet is simply to comment statuses that you don't wish to use
#
project_task_status_opts = {
1: T("Draft"),
2: T("New"),
3: T("Assigned"),
4: T("Feedback"),
5: T("Blocked"),
6: T("On Hold"),
7: T("Cancelled"),
8: T("Duplicate"),
9: T("Ready"),
10: T("Verified"),
11: T("Reopened"),
12: T("Completed"),
#99: T("unspecified")
}
project_task_active_statuses = [2, 3, 4, 11]
project_task_priority_opts = {
1:T("Urgent"),
2:T("High"),
3:T("Normal"),
4:T("Low")
}
#staff = auth.s3_has_role("STAFF")
staff = True
milestones = settings.get_project_milestones()
tablename = "project_task"
table = define_table(tablename,
super_link("doc_id", "doc_entity"),
Field("template", "boolean",
default=False,
readable=False,
writable=False),
Field("name",
label = T("Short Description"),
length=100,
notnull=True,
requires = IS_LENGTH(maxsize=100, minsize=1)),
Field("description", "text",
label = T("Detailed Description/URL"),
comment = DIV(_class="tooltip",
_title="%s|%s" % (T("Detailed Description/URL"),
T("Please provide as much detail as you can, including the URL(s) where the bug occurs or you'd like the new feature to go.")))),
site_id,
location_id(label=T("Deployment Location"),
readable=False,
writable=False
),
Field("source",
label = T("Source")),
Field("priority", "integer",
requires = IS_IN_SET(project_task_priority_opts,
zero=None),
default = 3,
label = T("Priority"),
represent = lambda opt, row=None: \
project_task_priority_opts.get(opt,
UNKNOWN_OPT)),
# Could be a Person, Team or Organisation
super_link("pe_id", "pr_pentity",
readable = staff,
writable = staff,
label = T("Assigned to"),
filterby = "instance_type",
filter_opts = ["pr_person", "pr_group", "org_organisation"],
represent = lambda id, row=None: \
project_assignee_represent(id),
# @ToDo: Widget
#widget = S3PentityWidget(),
#comment = DIV(_class="tooltip",
# _title="%s|%s" % (T("Assigned to"),
# T("Enter some characters to bring up a list of possible matches")))
),
Field("date_due", "datetime",
label = T("Date Due"),
readable = staff,
writable = staff,
requires = [IS_EMPTY_OR(
IS_UTC_DATETIME_IN_RANGE(
minimum=request.utcnow - datetime.timedelta(days=1),
error_message="%s %%(min)s!" %
T("Enter a valid future date")))],
widget = S3DateTimeWidget(past=0,
future=8760), # Hours, so 1 year
represent = s3_date_represent),
milestone_id(
readable = milestones and staff,
writable = milestones and staff,
),
Field("time_estimated", "double",
readable = staff,
writable = staff,
represent = lambda v: v or "",
label = "%s (%s)" % (T("Time Estimate"),
T("hours"))),
Field("time_actual", "double",
readable = staff,
# This comes from the Time component
writable=False,
label = "%s (%s)" % (T("Time Taken"),
T("hours"))),
Field("status", "integer",
requires = IS_IN_SET(project_task_status_opts,
zero=None),
default = 2,
readable = staff,
writable = staff,
label = T("Status"),
represent = lambda opt, row=None: \
project_task_status_opts.get(opt,
UNKNOWN_OPT)),
*meta_fields())
# Field configurations
# Comment these if you don't need a Site associated with Tasks
#table.site_id.readable = table.site_id.writable = True
#table.site_id.label = T("Check-in at Facility") # T("Managing Office")
table.created_on.represent = s3_date_represent
# CRUD Strings
ADD_TASK = T("Add Task")
LIST_TASKS = T("List Tasks")
crud_strings[tablename] = Storage(
title_create = ADD_TASK,
title_display = T("Task Details"),
title_list = LIST_TASKS,
title_update = T("Edit Task"),
title_search = T("Search Tasks"),
title_upload = T("Import Tasks"),
subtitle_create = T("Add New Task"),
subtitle_list = T("Tasks"),
label_list_button = LIST_TASKS,
label_create_button = ADD_TASK,
msg_record_created = T("Task added"),
msg_record_modified = T("Task updated"),
msg_record_deleted = T("Task deleted"),
msg_list_empty = T("No tasks currently registered"))
# Virtual Fields
# Do just for the common report
table.virtualfields.append(S3ProjectTaskVirtualfields())
# Search Method
task_search = S3Search(
advanced = (
# Virtual fields not supported by Search Widgets yet
#S3SearchOptionsWidget(
#name = "task_search_project",
#label = T("Project"),
#field = ["project"],
#cols = 3
#),
# This Syntax not supported by Search Widgets yet
#S3SearchOptionsWidget(
# name = "task_search_project",
# label = T("Project"),
# field = ["task.task_id:project_task:project_id$name"],
# cols = 3
#),
# Virtual fields not supported by Search Widgets yet
#S3SearchOptionsWidget(
#name = "task_search_activity",
#label = T("Activity"),
#field = ["activity"],
#cols = 3
#),
S3SearchOptionsWidget(
name = "task_search_priority",
label = T("Priority"),
field = ["priority"],
cols = 4
),
S3SearchSimpleWidget(
name = "task_search_text_advanced",
label = T("Description"),
comment = T("Search for a Task by description."),
field = [ "name",
"description",
]
),
S3SearchOptionsWidget(
name = "task_search_created_by",
label = T("Created By"),
field = ["created_by"],
cols = 4
),
S3SearchOptionsWidget(
name = "task_search_assignee",
label = T("Assigned To"),
field = ["pe_id"],
cols = 4
),
S3SearchMinMaxWidget(
name="task_search_date_created",
method="range",
label=T("Date Created"),
field=["created_on"]
),
S3SearchMinMaxWidget(
name="task_search_date_due",
method="range",
label=T("Date Due"),
field=["date_due"]
),
S3SearchOptionsWidget(
name = "task_search_status",
label = T("Status"),
field = ["status"],
cols = 4
),
)
)
list_fields=["id",
"priority",
(T("ID"), "task_id"),
"name",
"pe_id",
"date_due",
"time_estimated",
"created_on",
"status",
#"site_id"
]
if settings.get_project_milestones():
list_fields.insert(5, "milestone_id")
# Resource Configuration
configure(tablename,
super_entity="doc_entity",
copyable=True,
orderby="project_task.priority",
onvalidation=self.task_onvalidation,
create_next=URL(f="task", args=["[id]"]),
create_onaccept=self.task_create_onaccept,
update_onaccept=self.task_update_onaccept,
search_method=task_search,
list_fields=list_fields,
extra="description")
# Reusable field
task_id = S3ReusableField("task_id", db.project_task,
label = T("Task"),
sortby="name",
requires = IS_NULL_OR(IS_ONE_OF(db, "project_task.id", "%(name)s")),
represent = lambda id, row=None: \
(id and [db.project_task[id].name] or [NONE])[0],
comment = s3_popup_comment(c="project",
f="task",
title=ADD_TASK,
tooltip=T("A task is a piece of work that an individual or team can do in 1-2 days.")),
ondelete = "CASCADE")
# ---------------------------------------------------------------------
# Custom Methods
self.set_method("project_task",
method="dispatch",
action=self.task_dispatch)
# Components
# Projects (for imports)
add_component("project_project",
project_task=Storage(
link="project_task_project",
joinby="task_id",
key="project_id",
actuate="embed",
autocomplete="name",
autodelete=False))
# Activities (for imports)
add_component("project_activity",
project_task=Storage(
link="project_task_activity",
joinby="task_id",
key="activity_id",
actuate="embed",
autocomplete="name",
autodelete=False))
# Job roles
add_component("hrm_job_role",
project_task=Storage(
link="project_task_job_role",
joinby="task_id",
key="job_role_id",
actuate="embed",
autocomplete="name",
autodelete=False))
# Human Resources (assigned)
add_component("hrm_human_resource",
project_task=Storage(
link="project_task_human_resource",
joinby="task_id",
key="human_resource_id",
actuate="embed",
autocomplete="name",
autodelete=False))
# Requests
add_component("req_req",
project_task=Storage(
link="project_task_req",
joinby="task_id",
key="req_id",
actuate="embed",
autocomplete="request_number",
autodelete=False))
# Time
add_component("project_time", project_task="task_id")
# Comments (for imports))
add_component("project_comment", project_task="task_id")
# ---------------------------------------------------------------------
# Link Tasks <-> Projects
#
tablename = "project_task_project"
table = define_table(tablename,
task_id(),
project_id(),
*meta_fields())
# Field configuration
# CRUD Strings
# Search Method
# Resource Configuration
# Reusable Field
# ---------------------------------------------------------------------
# Link task <-> activity
#
# Tasks <> Activities
tablename = "project_task_activity"
table = define_table(tablename,
task_id(),
activity_id(),
*meta_fields())
# Field configuration
# CRUD Strings
# Search Method
# Resource Configuration
# Reusable Field
# ---------------------------------------------------------------------
# Project comment
#
# @ToDo: Attachments?
#
# Parent field allows us to:
# * easily filter for top-level threads
# * easily filter for next level of threading
# * hook a new reply into the correct location in the hierarchy
#
tablename = "project_comment"
table = define_table(tablename,
Field("parent", "reference project_comment",
requires = IS_EMPTY_OR(IS_ONE_OF(db,
"project_comment.id")),
readable=False),
#project_id(),
#activity_id(),
task_id(),
Field("body", "text",
notnull=True,
label = T("Comment")),
*meta_fields())
# Field configuration?
# CRUD Strings?
# Search Method?
# Resource Configuration
configure(tablename,
list_fields=["id",
"task_id",
"created_by",
"modified_on"
])
# Reusable Field?
# ---------------------------------------------------------------------
# Project Time
# - used to Log hours spent on a Task
#
tablename = "project_time"
table = define_table(tablename,
task_id(),
person_id(default=auth.s3_logged_in_person()),
Field("date", "datetime",
label = T("Date"),
requires = IS_EMPTY_OR(IS_UTC_DATETIME()),
represent = s3_utc_represent,
widget = S3DateTimeWidget(past=8760, # Hours, so 1 year
future=0),
default = request.utcnow),
Field("hours", "double",
label = "%s (%s)" % (T("Time"),
T("hours"))),
comments(),
format="%(comments)s",
*meta_fields())
# CRUD Strings
ADD_TIME = T("Log Time Spent")
crud_strings[tablename] = Storage(
title_create = ADD_TIME,
title_display = T("Logged Time Details"),
title_list = T("List Logged Time"),
title_update = T("Edit Logged Time"),
title_search = T("Search Logged Time"),
title_upload = T("Import Logged Time data"),
title_report = T("Last Week's Work"),
subtitle_create = T("Log New Time"),
subtitle_list = T("Logged Time"),
subtitle_report = T("Logged Time"),
label_list_button = T("List Logged Time"),
label_create_button = ADD_TIME,
msg_record_created = T("Time Logged"),
msg_record_modified = T("Time Log Updated"),
msg_record_deleted = T("Time Log Deleted"),
msg_list_empty = T("No Time Logged")
)
if "rows" in request.get_vars and request.get_vars.rows == "project":
s3.crud_strings[tablename].title_report = T("Project Time Report")
# Virtual Fields
table.virtualfields.append(S3ProjectTimeVirtualfields())
configure(tablename,
onaccept=self.time_onaccept,
list_fields=["id",
(T("Project"), "project"),
"task_id",
"person_id",
"date",
"hours",
"comments",
])
# ---------------------------------------------------------------------
# Pass variables back to global scope (response.s3.*)
#
return dict(
project_task_id = task_id,
project_task_active_statuses = project_task_active_statuses,
)
# -------------------------------------------------------------------------
def defaults(self):
""" Safe defaults for model-global names if module is disabled """
dummy = S3ReusableField("dummy_id", "integer",
readable=False,
writable=False)
return Storage(
project_task_id = lambda: dummy("task_id")
)
# ---------------------------------------------------------------------
@staticmethod
def milestone_represent(id, row=None):
""" FK representation """
db = current.db
NONE = current.messages.NONE
if id:
val = (id and [db.project_milestone[id].name] or [NONE])[0]
return val
else:
return NONE
# -------------------------------------------------------------------------
@staticmethod
def task_onvalidation(form):
""" Task form validation """
T = current.T
vars = form.vars
if str(vars.status) == "3" and not vars.pe_id:
form.errors.pe_id = \
T("Status 'assigned' requires the %(fieldname)s to not be blank") % \
dict(fieldname=current.db.project_task.pe_id.label)
elif vars.pe_id and str(vars.status) == "2":
# Set the Status to 'Assigned' if left at default 'New'
vars.status = 3
return
# -------------------------------------------------------------------------
@staticmethod
def task_update_onaccept(form):
"""
* Process the additional fields: Project/Activity
* Log changes as comments
* If the task is assigned to someone then notify them
"""
db = current.db
s3db = current.s3db
s3mgr = current.manager
vars = form.vars
id = vars.id
record = form.record
table = s3db.project_task
changed = {}
for var in vars:
vvar = vars[var]
rvar = record[var]
if vvar != rvar:
if table[var].type == "integer":
vvar = int(vvar)
if vvar == rvar:
continue
represent = table[var].represent
if not represent:
represent = lambda o: o
if rvar:
changed[var] = "%s changed from %s to %s" % \
(table[var].label, represent(rvar), represent(vvar))
else:
changed[var] = "%s changed to %s" % \
(table[var].label, represent(vvar))
if changed:
table = s3db.project_comment
text = s3_user_represent(current.auth.user.id)
for var in changed:
text = "%s\n%s" % (text, changed[var])
table.insert(task_id=id,
body=text)
vars = current.request.post_vars
if "project_id" in vars:
ptable = s3db.project_project
ltable = s3db.project_task_project
filter = (ltable.task_id == id)
if vars.project_id:
# Create the link to the Project
#master = s3mgr.define_resource("project", "task", id=id)
#record = db(ptable.id == vars.project_id).select(ptable.id,
# limitby=(0, 1)).first()
#link = s3mgr.define_resource("project", "task_project")
#link_id = link.update_link(master, record)
query = (ltable.task_id == id) & \
(ltable.project_id == vars.project_id)
record = db(query).select(ltable.id, limitby=(0, 1)).first()
if record:
link_id = record.id
else:
link_id = ltable.insert(task_id = id,
project_id = vars.project_id)
filter = filter & (ltable.id != link_id)
# Remove any other links
links = s3mgr.define_resource("project", "task_project",
filter=filter)
ondelete = s3mgr.model.get_config("project_task_project",
"ondelete")
links.delete(ondelete=ondelete)
if "activity_id" in vars:
atable = s3db.project_activity
ltable = s3db.project_task_activity
filter = (ltable.task_id == id)
if vars.activity_id:
# Create the link to the Activity
#master = s3mgr.define_resource("project", "task", id=id)
#record = db(atable.id == vars.activity_id).select(atable.id,
# limitby=(0, 1)).first()
#link = s3mgr.define_resource("project", "task_activity")
#link_id = link.update_link(master, record)
query = (ltable.task_id == id) & \
(ltable.activity_id == vars.activity_id)
record = db(query).select(ltable.id, limitby=(0, 1)).first()
if record:
link_id = record.id
else:
link_id = ltable.insert(task_id = id,
activity_id = vars.activity_id)
filter = filter & (ltable.id != link_id)
# Remove any other links
links = s3mgr.define_resource("project", "task_activity",
filter=filter)
ondelete = s3mgr.model.get_config("project_task_activity",
"ondelete")
links.delete(ondelete=ondelete)
# Notify Assignee
task_notify(form)
return
# -------------------------------------------------------------------------
@staticmethod
def task_create_onaccept(form):
"""
When a Task is created:
* Process the additional fields: Project/Activity
* create associated Link Tables
* ensure that it is owned by the Project Customer
* notify assignee
"""
db = current.db
s3db = current.s3db
session = current.session
vars = form.vars
id = vars.id
_vars = current.request.post_vars
if session.s3.event:
# Create a link between this Task & the active Event
etable = s3db.event_task
etable.insert(event_id=session.s3.event,
task_id=id)
vars = current.request.post_vars
table = s3db.project_task
if "project_id" in vars:
# Create Link to Project
ltable = s3db.project_task_project
if vars.project_id:
link_id = ltable.insert(task_id = id,
project_id = _vars.project_id)
if "activity_id" in vars:
# Create Link to Activity
ltable = s3db.project_task_activity
if vars.activity_id:
link_id = ltable.insert(task_id = id,
activity_id = _vars.activity_id)
# Find the associated Project
ptable = db.project_project
ltable = db.project_task_project
query = (ltable.task_id == id) & \
(ltable.project_id == ptable.id)
project = db(query).select(ptable.organisation_id,
limitby=(0, 1)).first()
if project:
# Set Task to be owned by this Customer
organisation_id = project.organisation_id
otable = s3db.org_organisation
query = (otable.id == organisation_id)
role = db(query).select(otable.owned_by_organisation,
limitby=(0, 1)).first()
if role:
table = s3db.project_task
query = (table.id == vars.id)
db(query).update(owned_by_organisation=role.owned_by_organisation)
# Make sure the task is also linked to the project
# when created under an activity
if id:
lta = s3db.project_task_activity
ltp = s3db.project_task_project
ta = s3db.project_activity
query = (ltp.task_id == id)
row = db(query).select(ltp.project_id,
limitby=(0, 1)).first()
if not row:
query = (lta.task_id == id) & \
(lta.activity_id == ta.id)
row = db(query).select(ta.project_id,
limitby=(0, 1)).first()
if row and row.project_id:
ltp.insert(task_id=id,
project_id=row.project_id)
# Notify Assignee
task_notify(form)
return
# -------------------------------------------------------------------------
@staticmethod
def task_dispatch(r, **attr):
"""
Send a Task Dispatch notice from a Task
- if a location is supplied, this will be formatted as an OpenGeoSMS
"""
T = current.T
msg = current.msg
response = current.response
if r.representation == "html" and \
r.name == "task" and r.id and not r.component:
record = r.record
text = "%s: %s" % (record.name,
record.description)
# Encode the message as an OpenGeoSMS
message = msg.prepare_opengeosms(record.location_id,
code="ST",
map="google",
text=text)
# URL to redirect to after message sent
url = URL(c="project",
f="task",
args=r.id)
# Create the form
if record.pe_id:
opts = dict(recipient=record.pe_id)
else:
opts = dict(recipient_type="pr_person")
output = msg.compose(type="SMS",
message = message,
url = url,
**opts)
# Maintain RHeader for consistency
if "rheader" in attr:
rheader = attr["rheader"](r)
if rheader:
output["rheader"] = rheader
output["title"] = T("Send Task Notification")
response.view = "msg/compose.html"
return output
else:
raise HTTP(501, BADMETHOD)
# -------------------------------------------------------------------------
@staticmethod
def time_onaccept(form):
""" When Time is logged, update the Task & Activity """
db = current.db
titable = db.project_time
ttable = db.project_task
atable = db.project_activity
tatable = db.project_task_activity
# Find the Task
task_id = form.vars.task_id
if not task_id:
# Component Form
query = (titable.id == form.vars.id)
record = db(query).select(titable.task_id,
limitby=(0, 1)).first()
if record:
task_id = record.task_id
# Total the Hours Logged
query = (titable.deleted == False) & \
(titable.task_id == task_id)
rows = db(query).select(titable.hours)
hours = 0
for row in rows:
hours += row.hours
# Update the Task
query = (ttable.id == task_id)
db(query).update(time_actual=hours)
# Find the Activity
query = (tatable.deleted == False) & \
(tatable.task_id == task_id)
activity = db(query).select(tatable.activity_id,
limitby=(0, 1)).first()
if activity:
activity_id = activity.activity_id
# Find all Tasks in this Activity
query = (ttable.deleted == False) & \
(tatable.deleted == False) & \
(tatable.task_id == ttable.id) & \
(tatable.activity_id == activity_id)
tasks = db(query).select(ttable.time_actual)
# Total the Hours Logged
hours = 0
for task in tasks:
hours += task.time_actual
# Update the Activity
query = (atable.id == activity_id)
db(query).update(time_actual=hours)
return
# =============================================================================
class S3ProjectTaskHRMModel(S3Model):
"""
Project Task HRM Model
This class holds the tables used to link Tasks to Human Resources
- either individuals or Job Roles
"""
names = ["project_task_job_role",
"project_task_human_resource",
]
def model(self):
s3 = current.response.s3
task_id = self.project_task_id
human_resource_id = self.hrm_human_resource_id
job_role_id = self.hrm_job_role_id
# Shortcuts
define_table = self.define_table
# ---------------------------------------------------------------------
# Link Tasks <> Human Resources
tablename = "project_task_human_resource"
table = define_table(tablename,
task_id(),
human_resource_id(),
*s3.meta_fields())
# ---------------------------------------------------------------------
# Link Tasks <> Job Roles
tablename = "project_task_job_role"
table = define_table(tablename,
task_id(),
job_role_id(),
*s3.meta_fields())
# ---------------------------------------------------------------------
# Pass variables back to global scope (response.s3.*)
#
return dict(
)
# =============================================================================
class S3ProjectTaskIReportModel(S3Model):
"""
Project Task IReport Model
This class holds the table used to link Tasks with Incident Reports.
"""
names = ["project_task_ireport",
]
def model(self):
s3 = current.response.s3
task_id = self.project_task_id
ireport_id = self.irs_ireport_id
# ---------------------------------------------------------------------
# Link Tasks <-> Incident Reports
#
tablename = "project_task_ireport"
table = self.define_table(tablename,
task_id(),
ireport_id(),
*s3.meta_fields())
self.configure(tablename,
onaccept=self.task_ireport_onaccept)
# ---------------------------------------------------------------------
# Pass variables back to global scope (response.s3.*)
#
return dict(
)
# -------------------------------------------------------------------------
@staticmethod
def task_ireport_onaccept(form):
"""
When a Task is linked to an IReport, then populate the location_id
"""
vars = form.vars
ireport_id = vars.ireport_id
task_id = vars.task_id
db = current.db
s3db = current.s3db
# Check if we already have a Location for the Task
table = s3db.project_task
query = (table.id == task_id)
record = db(query).select(table.location_id,
limitby=(0, 1)).first()
if not record or record.location_id:
return
# Find the Incident Location
itable = s3db.irs_ireport
query = (itable.id == ireport_id)
record = db(query).select(itable.location_id,
limitby=(0, 1)).first()
if not record or not record.location_id:
return
location_id = record.location_id
# Update the Task
query = (table.id == task_id)
db(query).update(location_id=location_id)
return
# -----------------------------------------------------------------------------
def project_assignee_represent(id):
""" Represent the Person a Task is assigned-to or list views """
db = current.db
s3db = current.s3db
cache = s3db.cache
output = current.messages.NONE
if not id:
return output
if isinstance(id, Row):
instance_type = id.instance_type
id = id.pe_id
else:
etable = s3db.pr_pentity
query = (etable.id == id)
record = db(query).select(etable.instance_type,
cache=cache,
limitby=(0, 1)).first()
if not record:
return output
instance_type = record.instance_type
table = s3db[instance_type]
query = (table.pe_id == id)
if instance_type == "pr_person":
record = db(query).select(table.first_name,
table.middle_name,
table.last_name,
table.initials,
cache=cache,
limitby=(0, 1)).first()
if record:
output = record.initials or s3_fullname(record)
elif instance_type in ("pr_group", "org_organisation"):
# Team or Organisation
record = db(query).select(table.name,
cache=cache,
limitby=(0, 1)).first()
if record:
output = record.name
else:
# Should not happen of correctly filtered, return default
pass
return output
# =============================================================================
def project_rheader(r, tabs=[]):
""" Project Resource Headers - used in Project & Budget modules """
if r.representation != "html":
# RHeaders only used in interactive views
return None
record = r.record
if record is None:
# List or Create form: rheader makes no sense here
return None
table = r.table
resourcename = r.name
T = current.T
auth = current.auth
settings = current.deployment_settings
drr = settings.get_project_drr()
pca = settings.get_project_community_activity()
milestones = settings.get_project_milestones()
if resourcename == "project":
# Tabs
tabs = [(T("Basic Details"), None)]
append = tabs.append
if drr:
append((T("Organizations"), "organisation"))
ADMIN = current.session.s3.system_roles.ADMIN
admin = auth.s3_has_role(ADMIN)
#staff = auth.s3_has_role("STAFF")
staff = True
if staff or drr:
append((T("Communities") if pca else T("Activities"), "activity"))
if staff and milestones:
append((T("Milestones"), "milestone"))
if not drr:
append((T("Tasks"), "task"))
if drr:
append((T("Documents"), "document"))
elif staff:
append((T("Attachments"), "document"))
if record.calendar:
append((T("Calendar"), "timeline"))
rheader_tabs = s3_rheader_tabs(r, tabs)
row3 = ""
if drr:
row2 = TR(
TH("%s: " % table.countries_id.label),
table.countries_id.represent(record.countries_id),
)
else:
row2 = TR(
TH("%s: " % table.organisation_id.label),
table.organisation_id.represent(record.organisation_id)
)
if record.end_date:
row3 = TR(
TH("%s: " % table.end_date.label),
table.end_date.represent(record.end_date)
)
rheader = DIV(TABLE(
TR(
TH("%s: " % table.name.label),
record.name
),
row2,
row3,
), rheader_tabs)
elif resourcename == "activity":
# @ToDo: integrate tabs?
rheader_tabs = s3_rheader_tabs(r, tabs)
tbl = TABLE()
if record.project_id is not None:
tbl.append(
TR(
TH("%s: " % table.project_id.label),
table.project_id.represent(record.project_id))
)
if pca:
tbl.append(
TR(
TH("%s: " % table.location_id.label),
table.location_id.represent(record.location_id)
)
)
else:
tbl.append(
TR(
TH("%s: " % table.name.label),
record.name
)
)
rheader = DIV(tbl, rheader_tabs)
elif resourcename == "task":
db = current.db
s3db = current.s3db
# Tabs
tabs = [(T("Details"), None)]
append = tabs.append
staff = auth.s3_has_role("STAFF")
if staff:
append((T("Time"), "time")),
#append((T("Comments"), "discuss"))
append((T("Attachments"), "document"))
if settings.has_module("msg"):
append((T("Notify"), "dispatch"))
#(T("Roles"), "job_role"),
#(T("Assignments"), "human_resource"),
#(T("Requests"), "req")
rheader_tabs = s3_rheader_tabs(r, tabs)
# RHeader
ptable = s3db.project_project
ltable = s3db.project_task_project
query = (ltable.deleted == False) & \
(ltable.task_id == r.id) & \
(ltable.project_id == ptable.id)
project = db(query).select(ptable.id,
limitby=(0, 1)).first()
if project:
project = TR(
TH("%s: " % T("Project")),
s3db.project_project_represent(project.id)
)
else:
project = ""
atable = s3db.project_activity
ltable = s3db.project_task_activity
query = (ltable.deleted == False) & \
(ltable.task_id == r.id) & \
(ltable.activity_id == atable.id)
activity = db(query).select(atable.name,
limitby=(0, 1)).first()
if activity:
activity = TR(
TH("%s: " % T("Activity")),
activity.name
)
else:
activity = ""
if record.description:
description = TR(
TH("%s: " % table.description.label),
record.description
)
else:
description = ""
if record.site_id:
facility = TR(
TH("%s: " % table.site_id.label),
table.site_id.represent(record.site_id),
)
else:
facility = ""
if record.location_id:
location = TR(
TH("%s: " % table.location_id.label),
table.location_id.represent(record.location_id),
)
else:
location = ""
if record.pe_id:
assignee = TR(
TH("%s: " % table.pe_id.label),
s3db.pr_pentity_represent(record.pe_id,
show_label=False),
)
else:
assignee = ""
if record.time_estimated:
time_estimated = TR(
TH("%s: " % table.time_estimated.label),
record.time_estimated
)
else:
time_estimated = ""
if record.time_actual:
time_actual = TR(
TH("%s: " % table.time_actual.label),
record.time_actual
)
else:
time_actual = ""
# Comments
# if r.method == "discuss":
# comments = ""
# else:
# ctable = s3db.project_comment
# query = (ctable.deleted == False) & \
# (ctable.task_id == r.id)
# comments = db(query).select(ctable.body).last()
# if comments:
# try:
# markup = etree.XML(comments.body)
# text = markup.xpath(".//text()")
# if text:
# text = " ".join(text)
# else:
# text = ""
# except etree.XMLSyntaxError:
# t = html.fromstring(comments.body)
# text = t.text_content()
# comments = TR(
# TH("%s: " % T("Latest Comment")),
# A(text,
# _href=URL(args=[r.id, "discuss"]))
# )
# else:
# comments = ""
rheader = DIV(TABLE(
project,
activity,
TR(
TH("%s: " % table.name.label),
record.name,
),
description,
facility,
location,
assignee,
time_estimated,
time_actual,
#comments,
), rheader_tabs)
return rheader
# -------------------------------------------------------------------------
def task_notify(form):
"""
If the task is assigned to someone then notify them
"""
vars = form.vars
try:
pe_id = int(vars.pe_id)
except TypeError, ValueError:
return
if form.record is None or (pe_id != form.record.pe_id):
# Assignee has changed
settings = current.deployment_settings
if settings.has_module("msg"):
# Notify assignee
subject = "%s: Task assigned to you" % settings.get_system_name_short()
url = "%s%s" % (settings.get_base_public_url(),
URL(c="project", f="task", args=vars.id))
message = "You have been assigned a Task:\n\n%s\n\n%s\n\n%s" % \
(url,
vars.name,
vars.description or "")
current.msg.send_by_pe_id(pe_id, subject, message)
return
# =============================================================================
class S3ProjectVirtualfields:
""" Virtual fields for the project_project table """
def organisation(self):
""" Name of the lead organisation of the project """
db = current.db
s3db = current.s3db
s3 = current.response.s3
otable = s3db.org_organisation
ltable = s3db.project_organisation
LEAD_ROLE = s3.project_organisation_lead_role
query = (ltable.deleted != True) & \
(ltable.project_id == self.project_project.id) & \
(ltable.role == LEAD_ROLE) & \
(ltable.organisation_id == otable.id)
org = db(query).select(otable.name,
limitby=(0, 1)).first()
if org:
return org.name
else:
return None
# =============================================================================
class S3ProjectActivityVirtualfields:
""" Virtual fields for the project_activity table """
extra_fields = ["project_id", "location_id"]
def organisation(self):
""" Name of the lead organisation of the project """
db = current.db
s3db = current.s3db
s3 = current.response.s3
otable = s3db.org_organisation
ltable = s3db.project_organisation
LEAD_ROLE = s3.project_organisation_lead_role
query = (ltable.deleted != True) & \
(ltable.project_id == self.project_activity.project_id) & \
(ltable.role == LEAD_ROLE) & \
(ltable.organisation_id == otable.id)
org = db(query).select(otable.name,
limitby=(0, 1)).first()
if org:
return org.name
else:
return None
def L0(self):
parents = Storage()
parents = current.gis.get_parent_per_level(parents,
self.project_activity.location_id,
ids=False,
names=True)
if "L0" in parents:
return parents["L0"]
else:
return None
def L1(self):
parents = Storage()
parents = current.gis.get_parent_per_level(parents,
self.project_activity.location_id,
ids=False,
names=True)
if "L1" in parents:
return parents["L1"]
else:
return None
def L2(self):
parents = Storage()
parents = current.gis.get_parent_per_level(parents,
self.project_activity.location_id,
ids=False,
names=True)
if "L2" in parents:
return parents["L2"]
else:
return None
def L3(self):
parents = Storage()
parents = current.gis.get_parent_per_level(parents,
self.project_activity.location_id,
ids=False,
names=True)
if "L3" in parents:
return parents["L3"]
else:
return None
# =============================================================================
class S3ProjectBeneficiaryVirtualfields:
""" Virtual fields for the project_beneficiary table """
extra_fields = ["activity_id"]
def L0(self):
db = current.db
s3db = current.s3db
s3 = current.response.s3
atable = s3db.project_activity
query = (atable.id == self.project_beneficiary.activity_id)
activity = db(query).select(atable.location_id,
limitby=(0, 1)).first()
if activity:
parents = Storage()
parents = current.gis.get_parent_per_level(parents,
activity.location_id,
ids=False,
names=True)
if "L0" in parents:
return parents["L0"]
else:
return current.messages.NONE
else:
return current.messages.NONE
def L1(self):
db = current.db
s3db = current.s3db
s3 = current.response.s3
atable = s3db.project_activity
query = (atable.id == self.project_beneficiary.activity_id)
activity = db(query).select(atable.location_id,
limitby=(0, 1)).first()
if activity:
parents = Storage()
parents = current.gis.get_parent_per_level(parents,
activity.location_id,
ids=False,
names=True)
if "L1" in parents:
return parents["L1"]
else:
return current.messages.NONE
else:
return current.messages.NONE
def L2(self):
db = current.db
s3db = current.s3db
s3 = current.response.s3
atable = s3db.project_activity
query = (atable.id == self.project_beneficiary.activity_id)
activity = db(query).select(atable.location_id,
limitby=(0, 1)).first()
if activity:
parents = Storage()
parents = current.gis.get_parent_per_level(parents,
activity.location_id,
ids=False,
names=True)
if "L2" in parents:
return parents["L2"]
else:
return current.messages.NONE
else:
return current.messages.NONE
def L3(self):
db = current.db
s3db = current.s3db
s3 = current.response.s3
atable = s3db.project_activity
query = (atable.id == self.project_beneficiary.activity_id)
activity = db(query).select(atable.location_id,
limitby=(0, 1)).first()
if activity:
parents = Storage()
parents = current.gis.get_parent_per_level(parents,
activity.location_id,
ids=False,
names=True)
if "L3" in parents:
return parents["L3"]
else:
return current.messages.NONE
else:
return current.messages.NONE
# =============================================================================
class S3ProjectActivityContactVirtualFields:
""" Virtual fields for the project_activity_contact table """
extra_fields = ["person_id"]
def email(self):
db = current.db
s3db = current.s3db
ptable = s3db.pr_person
ctable = s3db.pr_contact
person_id = self.project_activity_contact.person_id
query = (ctable.deleted != True) & \
(ptable.id == person_id) & \
(ctable.pe_id == ptable.pe_id) & \
(ctable.contact_method == "EMAIL")
items = db(query).select(ctable.value)
return ", ".join([item.value for item in items])
def sms(self):
db = current.db
s3db = current.s3db
ptable = s3db.pr_person
ctable = s3db.pr_contact
person_id = self.project_activity_contact.person_id
query = (ctable.deleted != True) & \
(ptable.id == person_id) & \
(ctable.pe_id == ptable.pe_id) & \
(ctable.contact_method == "SMS")
items = db(query).select(ctable.value)
return ", ".join([item.value for item in items])
# =============================================================================
class S3ProjectTaskVirtualfields:
""" Virtual fields for the project_task table """
extra_fields = ["id",
"project_task_project:project_id$name",
"project_task_activity:activity_id$name"]
def project(self):
"""
Project associated with this task
"""
try:
return self.project_project.name
except AttributeError:
return None
def activity(self):
"""
Activity associated with this task
"""
try:
return self.project_activity.name
except AttributeError:
return None
def task_id(self):
try:
return self.project_task.id
except AttributeError:
return None
# =============================================================================
class S3ProjectTimeVirtualfields:
""" Virtual fields for the project_time table """
extra_fields = ["task_id", "person_id", "date"]
def project(self):
"""
Project associated with this time entry
- used by the 'Project Time' report
"""
db = current.db
s3db = current.s3db
ptable = s3db.project_project
ltable = s3db.project_task_project
query = (ltable.deleted != True) & \
(ltable.task_id == self.project_time.task_id) & \
(ltable.project_id == ptable.id)
project = db(query).select(ptable.name,
limitby=(0, 1)).first()
if project:
return project.name
else:
return None
def day(self):
"""
Day of the last Week this time entry relates to
- used by the 'Last Week's Work' report
"""
T = current.T
now = current.request.utcnow
thisdate = self.project_time.date
if not thisdate:
return "-"
week = datetime.timedelta(days=7)
if thisdate < (now - week):
# Ignore data older than the last week
# - should already be filtered in controller anyway
return "-"
return thisdate.date().strftime("%d %B")
# END =========================================================================
| mit |
zenlambda/pip | tests/conftest.py | 36 | 6986 | import os
import shutil
import py
import pytest
from pip.utils import appdirs
from tests.lib import SRC_DIR, TestData
from tests.lib.path import Path
from tests.lib.scripttest import PipTestEnvironment
from tests.lib.venv import VirtualEnvironment
def pytest_collection_modifyitems(items):
for item in items:
if not hasattr(item, 'module'): # e.g.: DoctestTextfile
continue
module_path = os.path.relpath(
item.module.__file__,
os.path.commonprefix([__file__, item.module.__file__]),
)
module_root_dir = module_path.split(os.pathsep)[0]
if (module_root_dir.startswith("functional") or
module_root_dir.startswith("integration") or
module_root_dir.startswith("lib")):
item.add_marker(pytest.mark.integration)
elif module_root_dir.startswith("unit"):
item.add_marker(pytest.mark.unit)
# We don't want to allow using the script resource if this is a
# unit test, as unit tests should not need all that heavy lifting
if set(getattr(item, "funcargnames", [])) & set(["script"]):
raise RuntimeError(
"Cannot use the ``script`` funcarg in a unit test: "
"(filename = {0}, item = {1})".format(module_path, item)
)
else:
raise RuntimeError(
"Unknown test type (filename = {0})".format(module_path)
)
@pytest.fixture
def tmpdir(request):
"""
Return a temporary directory path object which is unique to each test
function invocation, created as a sub directory of the base temporary
directory. The returned object is a ``tests.lib.path.Path`` object.
This is taken from pytest itself but modified to return our typical
path object instead of py.path.local as well as deleting the temporary
directories at the end of each test case.
"""
name = request.node.name
name = py.std.re.sub("[\W]", "_", name)
tmp = request.config._tmpdirhandler.mktemp(name, numbered=True)
# Clear out the temporary directory after the test has finished using it.
# This should prevent us from needing a multiple gigabyte temporary
# directory while running the tests.
request.addfinalizer(lambda: shutil.rmtree(str(tmp), ignore_errors=True))
return Path(str(tmp))
@pytest.fixture(autouse=True)
def isolate(tmpdir):
"""
Isolate our tests so that things like global configuration files and the
like do not affect our test results.
We use an autouse function scoped fixture because we want to ensure that
every test has it's own isolated home directory.
"""
# TODO: Ensure Windows will respect $HOME, including for the cache
# directory
# TODO: Figure out how to isolate from *system* level configuration files
# as well as user level configuration files.
# Create a directory to use as our home location.
home_dir = os.path.join(str(tmpdir), "home")
os.makedirs(home_dir)
# Create a directory to use as a fake root
fake_root = os.path.join(str(tmpdir), "fake-root")
os.makedirs(fake_root)
# Set our home directory to our temporary directory, this should force all
# of our relative configuration files to be read from here instead of the
# user's actual $HOME directory.
os.environ["HOME"] = home_dir
# Isolate ourselves from XDG directories
os.environ["XDG_DATA_HOME"] = os.path.join(home_dir, ".local", "share")
os.environ["XDG_CONFIG_HOME"] = os.path.join(home_dir, ".config")
os.environ["XDG_CACHE_HOME"] = os.path.join(home_dir, ".cache")
os.environ["XDG_RUNTIME_DIR"] = os.path.join(home_dir, ".runtime")
os.environ["XDG_DATA_DIRS"] = ":".join([
os.path.join(fake_root, "usr", "local", "share"),
os.path.join(fake_root, "usr", "share"),
])
os.environ["XDG_CONFIG_DIRS"] = os.path.join(fake_root, "etc", "xdg")
# Configure git, because without an author name/email git will complain
# and cause test failures.
os.environ["GIT_CONFIG_NOSYSTEM"] = "1"
os.environ["GIT_AUTHOR_NAME"] = "pip"
os.environ["GIT_AUTHOR_EMAIL"] = "pypa-dev@googlegroups.com"
# We want to disable the version check from running in the tests
os.environ["PIP_DISABLE_PIP_VERSION_CHECK"] = "true"
os.makedirs(os.path.join(home_dir, ".config", "git"))
with open(os.path.join(home_dir, ".config", "git", "config"), "wb") as fp:
fp.write(
b"[user]\n\tname = pip\n\temail = pypa-dev@googlegroups.com\n"
)
@pytest.fixture
def virtualenv(tmpdir, monkeypatch, isolate):
"""
Return a virtual environment which is unique to each test function
invocation created inside of a sub directory of the test function's
temporary directory. The returned object is a
``tests.lib.venv.VirtualEnvironment`` object.
"""
# Force shutil to use the older method of rmtree that didn't use the fd
# functions. These seem to fail on Travis (and only on Travis).
monkeypatch.setattr(shutil, "_use_fd_functions", False, raising=False)
# Copy over our source tree so that each virtual environment is self
# contained
pip_src = tmpdir.join("pip_src").abspath
shutil.copytree(
SRC_DIR,
pip_src,
ignore=shutil.ignore_patterns(
"*.pyc", "__pycache__", "contrib", "docs", "tasks", "*.txt",
"tests", "pip.egg-info", "build", "dist", ".tox", ".git",
),
)
# Create the virtual environment
venv = VirtualEnvironment.create(
tmpdir.join("workspace", "venv"),
pip_source_dir=pip_src,
)
# Clean out our cache: creating the venv injects wheels into it.
if os.path.exists(appdirs.user_cache_dir("pip")):
shutil.rmtree(appdirs.user_cache_dir("pip"))
# Undo our monkeypatching of shutil
monkeypatch.undo()
return venv
@pytest.fixture
def script(tmpdir, virtualenv):
"""
Return a PipTestEnvironment which is unique to each test function and
will execute all commands inside of the unique virtual environment for this
test function. The returned object is a
``tests.lib.scripttest.PipTestEnvironment``.
"""
return PipTestEnvironment(
# The base location for our test environment
tmpdir.join("workspace"),
# Tell the Test Environment where our virtualenv is located
virtualenv=virtualenv.location,
# Do not ignore hidden files, they need to be checked as well
ignore_hidden=False,
# We are starting with an already empty directory
start_clear=False,
# We want to ensure no temporary files are left behind, so the
# PipTestEnvironment needs to capture and assert against temp
capture_temp=True,
assert_no_temp=True,
)
@pytest.fixture
def data(tmpdir):
return TestData.copy(tmpdir.join("data"))
| mit |
anandology/pyjamas | pygtkweb/demos/010-radiobuttons.py | 7 | 2093 | #!/usr/bin/env python
# example radiobuttons.py
import pygtk
pygtk.require('2.0')
import gtk
class RadioButtons:
def callback(self, widget, data=None):
print "%s was toggled %s" % (data, ("OFF", "ON")[widget.get_active()])
def close_application(self, widget, event, data=None):
gtk.main_quit()
return False
def __init__(self):
self.window = gtk.Window(gtk.WINDOW_TOPLEVEL)
self.window.connect("delete_event", self.close_application)
self.window.set_title("radio buttons")
self.window.set_border_width(0)
box1 = gtk.VBox(False, 0)
self.window.add(box1)
box1.show()
box2 = gtk.VBox(False, 10)
box2.set_border_width(10)
box1.pack_start(box2, True, True, 0)
box2.show()
button = gtk.RadioButton(None, "radio button1")
button.connect("toggled", self.callback, "radio button 1")
box2.pack_start(button, True, True, 0)
button.show()
button = gtk.RadioButton(button, "radio button2")
button.connect("toggled", self.callback, "radio button 2")
button.set_active(True)
box2.pack_start(button, True, True, 0)
button.show()
button = gtk.RadioButton(button, "radio button3")
button.connect("toggled", self.callback, "radio button 3")
box2.pack_start(button, True, True, 0)
button.show()
separator = gtk.HSeparator()
box1.pack_start(separator, False, True, 0)
separator.show()
box2 = gtk.VBox(False, 10)
box2.set_border_width(10)
box1.pack_start(box2, False, True, 0)
box2.show()
button = gtk.Button("close")
button.connect_object("clicked", self.close_application, self.window,
None)
box2.pack_start(button, True, True, 0)
button.set_flags(gtk.CAN_DEFAULT)
button.grab_default()
button.show()
self.window.show()
def main():
gtk.main()
return 0
if __name__ == "__main__":
RadioButtons()
main()
| apache-2.0 |
appsembler/edx-platform | common/test/acceptance/tests/lms/test_lms_course_discovery.py | 24 | 2206 | """
Test course discovery.
"""
import datetime
import json
import uuid
from common.test.acceptance.fixtures.course import CourseFixture
from common.test.acceptance.pages.common.auto_auth import AutoAuthPage
from common.test.acceptance.pages.common.logout import LogoutPage
from common.test.acceptance.pages.lms.discovery import CourseDiscoveryPage
from common.test.acceptance.tests.helpers import AcceptanceTest, remove_file
class CourseDiscoveryTest(AcceptanceTest):
"""
Test searching for courses.
"""
STAFF_USERNAME = "STAFF_TESTER"
STAFF_EMAIL = "staff101@example.com"
TEST_INDEX_FILENAME = "test_root/index_file.dat"
def setUp(self):
"""
Create course page and courses to find
"""
# create index file
with open(self.TEST_INDEX_FILENAME, "w+") as index_file:
json.dump({}, index_file)
self.addCleanup(remove_file, self.TEST_INDEX_FILENAME)
super(CourseDiscoveryTest, self).setUp()
self.page = CourseDiscoveryPage(self.browser)
for i in range(12):
org = 'test_org'
number = "{}{}".format(str(i), str(uuid.uuid4().get_hex().upper()[0:6]))
run = "test_run"
name = "test course" if i < 10 else "grass is always greener"
settings = {'enrollment_start': datetime.datetime(1970, 1, 1).isoformat()}
CourseFixture(org, number, run, name, settings=settings).install()
def _auto_auth(self, username, email, staff):
"""
Logout and login with given credentials.
"""
LogoutPage(self.browser).visit()
AutoAuthPage(self.browser, username=username, email=email, staff=staff).visit()
def test_page_existence(self):
"""
Make sure that the page is accessible.
"""
self.page.visit()
def test_search(self):
"""
Make sure you can search for courses.
"""
self.page.visit()
self.assertEqual(len(self.page.result_items), 12)
self.page.search("grass")
self.assertEqual(len(self.page.result_items), 2)
self.page.clear_search()
self.assertEqual(len(self.page.result_items), 12)
| agpl-3.0 |
Yen-Chung-En/2015cdb_g1 | static/Brython3.1.1-20150328-091302/Lib/_abcoll.py | 688 | 5155 | # Copyright 2007 Google, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
"""Abstract Base Classes (ABCs) for collections, according to PEP 3119.
DON'T USE THIS MODULE DIRECTLY! The classes here should be imported
via collections; they are defined here only to alleviate certain
bootstrapping issues. Unit tests are in test_collections.
"""
from abc import ABCMeta, abstractmethod
import sys
__all__ = ["Hashable", "Iterable", "Iterator",
"Sized", "Container", "Callable",
"Set", "MutableSet",
"Mapping", "MutableMapping",
"MappingView", "KeysView", "ItemsView", "ValuesView",
"Sequence", "MutableSequence",
"ByteString",
]
"""
### collection related types which are not exposed through builtin ###
## iterators ##
#fixme brython
#bytes_iterator = type(iter(b''))
bytes_iterator = type(iter(''))
#fixme brython
#bytearray_iterator = type(iter(bytearray()))
#callable_iterator = ???
dict_keyiterator = type(iter({}.keys()))
dict_valueiterator = type(iter({}.values()))
dict_itemiterator = type(iter({}.items()))
list_iterator = type(iter([]))
list_reverseiterator = type(iter(reversed([])))
range_iterator = type(iter(range(0)))
set_iterator = type(iter(set()))
str_iterator = type(iter(""))
tuple_iterator = type(iter(()))
zip_iterator = type(iter(zip()))
## views ##
dict_keys = type({}.keys())
dict_values = type({}.values())
dict_items = type({}.items())
## misc ##
dict_proxy = type(type.__dict__)
"""
def abstractmethod(self):
return self
### ONE-TRICK PONIES ###
#class Iterable(metaclass=ABCMeta):
class Iterable:
@abstractmethod
def __iter__(self):
while False:
yield None
@classmethod
def __subclasshook__(cls, C):
if cls is Iterable:
if any("__iter__" in B.__dict__ for B in C.__mro__):
return True
return NotImplemented
#class Sized(metaclass=ABCMeta):
class Sized:
@abstractmethod
def __len__(self):
return 0
@classmethod
def __subclasshook__(cls, C):
if cls is Sized:
if any("__len__" in B.__dict__ for B in C.__mro__):
return True
return NotImplemented
#class Container(metaclass=ABCMeta):
class Container:
@abstractmethod
def __contains__(self, x):
return False
@classmethod
def __subclasshook__(cls, C):
if cls is Container:
if any("__contains__" in B.__dict__ for B in C.__mro__):
return True
return NotImplemented
### MAPPINGS ###
class Mapping(Sized, Iterable, Container):
@abstractmethod
def __getitem__(self, key):
raise KeyError
def get(self, key, default=None):
try:
return self[key]
except KeyError:
return default
def __contains__(self, key):
try:
self[key]
except KeyError:
return False
else:
return True
def keys(self):
return KeysView(self)
def items(self):
return ItemsView(self)
def values(self):
return ValuesView(self)
def __eq__(self, other):
if not isinstance(other, Mapping):
return NotImplemented
return dict(self.items()) == dict(other.items())
def __ne__(self, other):
return not (self == other)
class MutableMapping(Mapping):
@abstractmethod
def __setitem__(self, key, value):
raise KeyError
@abstractmethod
def __delitem__(self, key):
raise KeyError
__marker = object()
def pop(self, key, default=__marker):
try:
value = self[key]
except KeyError:
if default is self.__marker:
raise
return default
else:
del self[key]
return value
def popitem(self):
try:
key = next(iter(self))
except StopIteration:
raise KeyError
value = self[key]
del self[key]
return key, value
def clear(self):
try:
while True:
self.popitem()
except KeyError:
pass
def update(*args, **kwds):
if len(args) > 2:
raise TypeError("update() takes at most 2 positional "
"arguments ({} given)".format(len(args)))
elif not args:
raise TypeError("update() takes at least 1 argument (0 given)")
self = args[0]
other = args[1] if len(args) >= 2 else ()
if isinstance(other, Mapping):
for key in other:
self[key] = other[key]
elif hasattr(other, "keys"):
for key in other.keys():
self[key] = other[key]
else:
for key, value in other:
self[key] = value
for key, value in kwds.items():
self[key] = value
def setdefault(self, key, default=None):
try:
return self[key]
except KeyError:
self[key] = default
return default
#MutableMapping.register(dict)
| agpl-3.0 |
jangler/vcii | vcii/test/test_sheet.py | 1 | 2485 | import random
import unittest
from vcii.sheet import *
class TestSheet(unittest.TestCase):
def test_key_to_indices(self):
with self.assertRaises(ValueError):
indices_from_label('1A')
self.assertEqual(indices_from_label('A1'), (0, 0))
self.assertEqual(indices_from_label('zz99'), (26**2 + 25, 98))
def test_append(self):
sheet = Sheet()
sheet.cursor = [(lambda: random.randint(0, 10))()] * 2
sheet.append('rain')
self.assertEqual(sheet.active_cell.content, 'rain')
self.assertTrue(sheet.modified)
sheet.modified = False
sheet.append('bow')
self.assertEqual(sheet.active_cell.content, 'rainbow')
self.assertTrue(sheet.modified)
def test_expand(self):
sheet = Sheet()
self.assertEqual(sheet.size, (0, 0))
max_size = 0, 0
for i in range(10):
coords = [(lambda: random.randint(0, 10))()] * 2
sheet.expand(*coords)
max_size = tuple(max(max_size[j], coords[j] + 1) for j in range(2))
self.assertEqual(sheet.size, max_size)
self.assertTrue(sheet.modified)
def test_setitem(self):
sheet = Sheet()
sheet['C2'] = 'testing'
self.assertEqual(sheet.cells[2][1].content, 'testing')
self.assertEqual(sheet.size, (3, 2))
self.assertTrue(sheet.modified)
def test_move_cursor(self):
sheet = Sheet()
sheet.move_cursor(0, 0)
self.assertEqual(sheet.cursor, [0, 0])
sheet.move_cursor(-1, 1)
self.assertEqual(sheet.cursor, [0, 1])
sheet.move_cursor(1, -2)
self.assertEqual(sheet.cursor, [1, 0])
self.assertFalse(sheet.modified)
sheet.expand(0, 0)
sheet.modified = False
sheet.move_cursor(-1, 0)
self.assertEqual(sheet.cursor, [0, 0])
self.assertFalse(sheet.modified)
def test_column_width(self):
sheet = Sheet()
sheet.expand(1, 0)
self.assertEqual(sheet.column_width(1), DEFAULT_COLUMN_WIDTH)
self.assertEqual(sheet.column_width(2), DEFAULT_COLUMN_WIDTH)
sheet.column_widths[1] = 5
self.assertEqual(sheet.column_width(0), DEFAULT_COLUMN_WIDTH)
self.assertEqual(sheet.column_width(1), 5)
def test_resize_column(self):
sheet = Sheet()
sheet.resize_column(0, 0)
self.assertEqual(sheet.size, (1, 1))
self.assertEqual(sheet.column_widths, [2])
| mit |
eightyfourcoin/84 | share/qt/make_spinner.py | 4415 | 1035 | #!/usr/bin/env python
# W.J. van der Laan, 2011
# Make spinning .mng animation from a .png
# Requires imagemagick 6.7+
from __future__ import division
from os import path
from PIL import Image
from subprocess import Popen
SRC='img/reload_scaled.png'
DST='../../src/qt/res/movies/update_spinner.mng'
TMPDIR='/tmp'
TMPNAME='tmp-%03i.png'
NUMFRAMES=35
FRAMERATE=10.0
CONVERT='convert'
CLOCKWISE=True
DSIZE=(16,16)
im_src = Image.open(SRC)
if CLOCKWISE:
im_src = im_src.transpose(Image.FLIP_LEFT_RIGHT)
def frame_to_filename(frame):
return path.join(TMPDIR, TMPNAME % frame)
frame_files = []
for frame in xrange(NUMFRAMES):
rotation = (frame + 0.5) / NUMFRAMES * 360.0
if CLOCKWISE:
rotation = -rotation
im_new = im_src.rotate(rotation, Image.BICUBIC)
im_new.thumbnail(DSIZE, Image.ANTIALIAS)
outfile = frame_to_filename(frame)
im_new.save(outfile, 'png')
frame_files.append(outfile)
p = Popen([CONVERT, "-delay", str(FRAMERATE), "-dispose", "2"] + frame_files + [DST])
p.communicate()
| mit |
sg00dwin/origin | vendor/github.com/google/certificate-transparency/python/ct/client/db/sqlite_temp_db.py | 35 | 6021 | import logging
import sqlite3
from ct.client.db import temp_db
from ct.client.db import database
from ct.client.db import sqlite_connection as sqlitecon
from ct.proto import client_pb2
class SQLiteTempDBFactory(object):
"""A database factory that manages mappings from public identifiers
(log names) to SQLite databases."""
def __init__(self, connection_manager, database_dir):
"""Initialize the database factory.
Args:
connection_manager: an SQLiteConnectionManager object
database_dir: the directory where the database files reside.
"""
self.__mgr = connection_manager
self.__database_dir = database_dir
# This is the meta-table mapping database IDs to server names.
with self.__mgr.get_connection() as conn:
conn.execute("CREATE TABLE IF NOT EXISTS database_mapping("
"id INTEGER PRIMARY KEY, server_name TEXT UNIQUE)")
self.__tables = ["database_mapping"]
def __repr__(self):
return "%r(%r)" % (self.__class__.__name__, self.__mgr)
def __str__(self):
return "%s(%s, tables: %s): " % (self.__class__.__name__,
self.__mgr, self.__tables)
@staticmethod
def __database_id_to_name(database_id):
return "db%d" % database_id
def __get_db_name(self, cursor, log_server):
cursor.execute("SELECT id from database_mapping WHERE server_name = ?",
(log_server,))
row = cursor.fetchone()
if row is None:
raise database.KeyError("No database for log server %s" %
log_server)
return self.__database_id_to_name(row["id"])
# TODO(ekasper): add a remove_storage() for removing obsolete data.
def create_storage(self, log_server):
"""Create a SQLiteTempDB object pointing to the temporary storage of a
given log server. If the temporary storage does not exist, creates one.
Args:
log_server: the server name.
"""
with self.__mgr.get_connection() as conn:
cursor = conn.cursor()
try:
database_name = self.__get_db_name(cursor, log_server)
except database.KeyError:
try:
cursor.execute("INSERT INTO database_mapping(server_name) "
"VALUES (?)", (log_server,))
database_name = self.__database_id_to_name(cursor.lastrowid)
except sqlite3.IntegrityError as e:
raise database.KeyError("Failed to create a table mapping "
"for server %s: is a concurrent "
"factory running?\n%s" %
(log_server, e))
return SQLiteTempDB(sqlitecon.SQLiteConnectionManager(
self.__database_dir + "/" + database_name))
class SQLiteTempDB(temp_db.TempDB):
"""SQLite implementation of TempDB."""
def __init__(self, connection_manager):
"""Create an SQLiteTempDB object.
Args:
connection_manager: and SQLiteConnectionManager object
"""
self.__mgr = connection_manager
with self.__mgr.get_connection() as conn:
conn.execute("CREATE TABLE IF NOT EXISTS entries("
"id INTEGER PRIMARY KEY, entry BLOB)")
self.__tables = ["entries"]
def __repr__(self):
return "%r(%r)" % (self.__class__.__name__, self.__mgr)
def __str__(self):
return "%s(%s, tables: %s): " % (self.__class__.__name__,
self.__mgr, self.__tables)
# Not part of the abstract interface: used to identify the database file
# we're writing to.
def db_name(self):
return self.__mgr.db_name
def drop_entries(self):
"""Drop all entries."""
with self.__mgr.get_connection() as conn:
conn.execute("DELETE FROM entries")
def store_entries(self, entries):
"""Batch store log entries.
Args:
entries: an iterable of (entry_number, client_pb2.EntryResponse)
tuples
"""
with self.__mgr.get_connection() as conn:
cursor = conn.cursor()
serialized_entries = map(lambda x: (
x[0], sqlite3.Binary(x[1].SerializeToString())), entries)
try:
cursor.executemany("INSERT OR REPLACE INTO entries(id, entry) VALUES "
"(?, ?)", serialized_entries)
except sqlite3.IntegrityError as e:
raise database.KeyError("Failed to insert entries: an entry "
"with the given sequence number "
"already exists\n%s" % e)
def scan_entries(self, start, end):
"""Retrieve log entries.
Args:
start: index of the first entry to retrieve.
end: index of the last entry to retrieve.
Yields:
client_pb2.EntryResponse protos
Raises:
KeyError: an entry with a sequence number in the range does not
exist.
"""
with self.__mgr.get_connection() as conn:
cursor = conn.cursor()
next_id = start
for row in cursor.execute("SELECT id, entry FROM entries WHERE id "
"BETWEEN ? and ? ORDER BY id ASC",
(start, end)):
if row["id"] != next_id:
raise database.KeyError("No such entry: %d" % next_id)
entry = client_pb2.EntryResponse()
entry.ParseFromString(str(row["entry"]))
yield entry
next_id += 1
if next_id != end + 1:
raise database.KeyError("No such entry: %d" % next_id)
| apache-2.0 |
kikocorreoso/brython | www/src/Lib/encodings/cp864.py | 37 | 34353 | """ Python Character Mapping Codec generated from 'VENDORS/MICSFT/PC/CP864.TXT' with gencodec.py.
"""#"
import codecs
### Codec APIs
class Codec(codecs.Codec):
def encode(self,input,errors='strict'):
return codecs.charmap_encode(input,errors,encoding_map)
def decode(self,input,errors='strict'):
return codecs.charmap_decode(input,errors,decoding_table)
class IncrementalEncoder(codecs.IncrementalEncoder):
def encode(self, input, final=False):
return codecs.charmap_encode(input,self.errors,encoding_map)[0]
class IncrementalDecoder(codecs.IncrementalDecoder):
def decode(self, input, final=False):
return codecs.charmap_decode(input,self.errors,decoding_table)[0]
class StreamWriter(Codec,codecs.StreamWriter):
pass
class StreamReader(Codec,codecs.StreamReader):
pass
### encodings module API
def getregentry():
return codecs.CodecInfo(
name='cp864',
encode=Codec().encode,
decode=Codec().decode,
incrementalencoder=IncrementalEncoder,
incrementaldecoder=IncrementalDecoder,
streamreader=StreamReader,
streamwriter=StreamWriter,
)
### Decoding Map
decoding_map = codecs.make_identity_dict(range(256))
decoding_map.update({
0x0025: 0x066a, # ARABIC PERCENT SIGN
0x0080: 0x00b0, # DEGREE SIGN
0x0081: 0x00b7, # MIDDLE DOT
0x0082: 0x2219, # BULLET OPERATOR
0x0083: 0x221a, # SQUARE ROOT
0x0084: 0x2592, # MEDIUM SHADE
0x0085: 0x2500, # FORMS LIGHT HORIZONTAL
0x0086: 0x2502, # FORMS LIGHT VERTICAL
0x0087: 0x253c, # FORMS LIGHT VERTICAL AND HORIZONTAL
0x0088: 0x2524, # FORMS LIGHT VERTICAL AND LEFT
0x0089: 0x252c, # FORMS LIGHT DOWN AND HORIZONTAL
0x008a: 0x251c, # FORMS LIGHT VERTICAL AND RIGHT
0x008b: 0x2534, # FORMS LIGHT UP AND HORIZONTAL
0x008c: 0x2510, # FORMS LIGHT DOWN AND LEFT
0x008d: 0x250c, # FORMS LIGHT DOWN AND RIGHT
0x008e: 0x2514, # FORMS LIGHT UP AND RIGHT
0x008f: 0x2518, # FORMS LIGHT UP AND LEFT
0x0090: 0x03b2, # GREEK SMALL BETA
0x0091: 0x221e, # INFINITY
0x0092: 0x03c6, # GREEK SMALL PHI
0x0093: 0x00b1, # PLUS-OR-MINUS SIGN
0x0094: 0x00bd, # FRACTION 1/2
0x0095: 0x00bc, # FRACTION 1/4
0x0096: 0x2248, # ALMOST EQUAL TO
0x0097: 0x00ab, # LEFT POINTING GUILLEMET
0x0098: 0x00bb, # RIGHT POINTING GUILLEMET
0x0099: 0xfef7, # ARABIC LIGATURE LAM WITH ALEF WITH HAMZA ABOVE ISOLATED FORM
0x009a: 0xfef8, # ARABIC LIGATURE LAM WITH ALEF WITH HAMZA ABOVE FINAL FORM
0x009b: None, # UNDEFINED
0x009c: None, # UNDEFINED
0x009d: 0xfefb, # ARABIC LIGATURE LAM WITH ALEF ISOLATED FORM
0x009e: 0xfefc, # ARABIC LIGATURE LAM WITH ALEF FINAL FORM
0x009f: None, # UNDEFINED
0x00a1: 0x00ad, # SOFT HYPHEN
0x00a2: 0xfe82, # ARABIC LETTER ALEF WITH MADDA ABOVE FINAL FORM
0x00a5: 0xfe84, # ARABIC LETTER ALEF WITH HAMZA ABOVE FINAL FORM
0x00a6: None, # UNDEFINED
0x00a7: None, # UNDEFINED
0x00a8: 0xfe8e, # ARABIC LETTER ALEF FINAL FORM
0x00a9: 0xfe8f, # ARABIC LETTER BEH ISOLATED FORM
0x00aa: 0xfe95, # ARABIC LETTER TEH ISOLATED FORM
0x00ab: 0xfe99, # ARABIC LETTER THEH ISOLATED FORM
0x00ac: 0x060c, # ARABIC COMMA
0x00ad: 0xfe9d, # ARABIC LETTER JEEM ISOLATED FORM
0x00ae: 0xfea1, # ARABIC LETTER HAH ISOLATED FORM
0x00af: 0xfea5, # ARABIC LETTER KHAH ISOLATED FORM
0x00b0: 0x0660, # ARABIC-INDIC DIGIT ZERO
0x00b1: 0x0661, # ARABIC-INDIC DIGIT ONE
0x00b2: 0x0662, # ARABIC-INDIC DIGIT TWO
0x00b3: 0x0663, # ARABIC-INDIC DIGIT THREE
0x00b4: 0x0664, # ARABIC-INDIC DIGIT FOUR
0x00b5: 0x0665, # ARABIC-INDIC DIGIT FIVE
0x00b6: 0x0666, # ARABIC-INDIC DIGIT SIX
0x00b7: 0x0667, # ARABIC-INDIC DIGIT SEVEN
0x00b8: 0x0668, # ARABIC-INDIC DIGIT EIGHT
0x00b9: 0x0669, # ARABIC-INDIC DIGIT NINE
0x00ba: 0xfed1, # ARABIC LETTER FEH ISOLATED FORM
0x00bb: 0x061b, # ARABIC SEMICOLON
0x00bc: 0xfeb1, # ARABIC LETTER SEEN ISOLATED FORM
0x00bd: 0xfeb5, # ARABIC LETTER SHEEN ISOLATED FORM
0x00be: 0xfeb9, # ARABIC LETTER SAD ISOLATED FORM
0x00bf: 0x061f, # ARABIC QUESTION MARK
0x00c0: 0x00a2, # CENT SIGN
0x00c1: 0xfe80, # ARABIC LETTER HAMZA ISOLATED FORM
0x00c2: 0xfe81, # ARABIC LETTER ALEF WITH MADDA ABOVE ISOLATED FORM
0x00c3: 0xfe83, # ARABIC LETTER ALEF WITH HAMZA ABOVE ISOLATED FORM
0x00c4: 0xfe85, # ARABIC LETTER WAW WITH HAMZA ABOVE ISOLATED FORM
0x00c5: 0xfeca, # ARABIC LETTER AIN FINAL FORM
0x00c6: 0xfe8b, # ARABIC LETTER YEH WITH HAMZA ABOVE INITIAL FORM
0x00c7: 0xfe8d, # ARABIC LETTER ALEF ISOLATED FORM
0x00c8: 0xfe91, # ARABIC LETTER BEH INITIAL FORM
0x00c9: 0xfe93, # ARABIC LETTER TEH MARBUTA ISOLATED FORM
0x00ca: 0xfe97, # ARABIC LETTER TEH INITIAL FORM
0x00cb: 0xfe9b, # ARABIC LETTER THEH INITIAL FORM
0x00cc: 0xfe9f, # ARABIC LETTER JEEM INITIAL FORM
0x00cd: 0xfea3, # ARABIC LETTER HAH INITIAL FORM
0x00ce: 0xfea7, # ARABIC LETTER KHAH INITIAL FORM
0x00cf: 0xfea9, # ARABIC LETTER DAL ISOLATED FORM
0x00d0: 0xfeab, # ARABIC LETTER THAL ISOLATED FORM
0x00d1: 0xfead, # ARABIC LETTER REH ISOLATED FORM
0x00d2: 0xfeaf, # ARABIC LETTER ZAIN ISOLATED FORM
0x00d3: 0xfeb3, # ARABIC LETTER SEEN INITIAL FORM
0x00d4: 0xfeb7, # ARABIC LETTER SHEEN INITIAL FORM
0x00d5: 0xfebb, # ARABIC LETTER SAD INITIAL FORM
0x00d6: 0xfebf, # ARABIC LETTER DAD INITIAL FORM
0x00d7: 0xfec1, # ARABIC LETTER TAH ISOLATED FORM
0x00d8: 0xfec5, # ARABIC LETTER ZAH ISOLATED FORM
0x00d9: 0xfecb, # ARABIC LETTER AIN INITIAL FORM
0x00da: 0xfecf, # ARABIC LETTER GHAIN INITIAL FORM
0x00db: 0x00a6, # BROKEN VERTICAL BAR
0x00dc: 0x00ac, # NOT SIGN
0x00dd: 0x00f7, # DIVISION SIGN
0x00de: 0x00d7, # MULTIPLICATION SIGN
0x00df: 0xfec9, # ARABIC LETTER AIN ISOLATED FORM
0x00e0: 0x0640, # ARABIC TATWEEL
0x00e1: 0xfed3, # ARABIC LETTER FEH INITIAL FORM
0x00e2: 0xfed7, # ARABIC LETTER QAF INITIAL FORM
0x00e3: 0xfedb, # ARABIC LETTER KAF INITIAL FORM
0x00e4: 0xfedf, # ARABIC LETTER LAM INITIAL FORM
0x00e5: 0xfee3, # ARABIC LETTER MEEM INITIAL FORM
0x00e6: 0xfee7, # ARABIC LETTER NOON INITIAL FORM
0x00e7: 0xfeeb, # ARABIC LETTER HEH INITIAL FORM
0x00e8: 0xfeed, # ARABIC LETTER WAW ISOLATED FORM
0x00e9: 0xfeef, # ARABIC LETTER ALEF MAKSURA ISOLATED FORM
0x00ea: 0xfef3, # ARABIC LETTER YEH INITIAL FORM
0x00eb: 0xfebd, # ARABIC LETTER DAD ISOLATED FORM
0x00ec: 0xfecc, # ARABIC LETTER AIN MEDIAL FORM
0x00ed: 0xfece, # ARABIC LETTER GHAIN FINAL FORM
0x00ee: 0xfecd, # ARABIC LETTER GHAIN ISOLATED FORM
0x00ef: 0xfee1, # ARABIC LETTER MEEM ISOLATED FORM
0x00f0: 0xfe7d, # ARABIC SHADDA MEDIAL FORM
0x00f1: 0x0651, # ARABIC SHADDAH
0x00f2: 0xfee5, # ARABIC LETTER NOON ISOLATED FORM
0x00f3: 0xfee9, # ARABIC LETTER HEH ISOLATED FORM
0x00f4: 0xfeec, # ARABIC LETTER HEH MEDIAL FORM
0x00f5: 0xfef0, # ARABIC LETTER ALEF MAKSURA FINAL FORM
0x00f6: 0xfef2, # ARABIC LETTER YEH FINAL FORM
0x00f7: 0xfed0, # ARABIC LETTER GHAIN MEDIAL FORM
0x00f8: 0xfed5, # ARABIC LETTER QAF ISOLATED FORM
0x00f9: 0xfef5, # ARABIC LIGATURE LAM WITH ALEF WITH MADDA ABOVE ISOLATED FORM
0x00fa: 0xfef6, # ARABIC LIGATURE LAM WITH ALEF WITH MADDA ABOVE FINAL FORM
0x00fb: 0xfedd, # ARABIC LETTER LAM ISOLATED FORM
0x00fc: 0xfed9, # ARABIC LETTER KAF ISOLATED FORM
0x00fd: 0xfef1, # ARABIC LETTER YEH ISOLATED FORM
0x00fe: 0x25a0, # BLACK SQUARE
0x00ff: None, # UNDEFINED
})
### Decoding Table
decoding_table = (
'\x00' # 0x0000 -> NULL
'\x01' # 0x0001 -> START OF HEADING
'\x02' # 0x0002 -> START OF TEXT
'\x03' # 0x0003 -> END OF TEXT
'\x04' # 0x0004 -> END OF TRANSMISSION
'\x05' # 0x0005 -> ENQUIRY
'\x06' # 0x0006 -> ACKNOWLEDGE
'\x07' # 0x0007 -> BELL
'\x08' # 0x0008 -> BACKSPACE
'\t' # 0x0009 -> HORIZONTAL TABULATION
'\n' # 0x000a -> LINE FEED
'\x0b' # 0x000b -> VERTICAL TABULATION
'\x0c' # 0x000c -> FORM FEED
'\r' # 0x000d -> CARRIAGE RETURN
'\x0e' # 0x000e -> SHIFT OUT
'\x0f' # 0x000f -> SHIFT IN
'\x10' # 0x0010 -> DATA LINK ESCAPE
'\x11' # 0x0011 -> DEVICE CONTROL ONE
'\x12' # 0x0012 -> DEVICE CONTROL TWO
'\x13' # 0x0013 -> DEVICE CONTROL THREE
'\x14' # 0x0014 -> DEVICE CONTROL FOUR
'\x15' # 0x0015 -> NEGATIVE ACKNOWLEDGE
'\x16' # 0x0016 -> SYNCHRONOUS IDLE
'\x17' # 0x0017 -> END OF TRANSMISSION BLOCK
'\x18' # 0x0018 -> CANCEL
'\x19' # 0x0019 -> END OF MEDIUM
'\x1a' # 0x001a -> SUBSTITUTE
'\x1b' # 0x001b -> ESCAPE
'\x1c' # 0x001c -> FILE SEPARATOR
'\x1d' # 0x001d -> GROUP SEPARATOR
'\x1e' # 0x001e -> RECORD SEPARATOR
'\x1f' # 0x001f -> UNIT SEPARATOR
' ' # 0x0020 -> SPACE
'!' # 0x0021 -> EXCLAMATION MARK
'"' # 0x0022 -> QUOTATION MARK
'#' # 0x0023 -> NUMBER SIGN
'$' # 0x0024 -> DOLLAR SIGN
'\u066a' # 0x0025 -> ARABIC PERCENT SIGN
'&' # 0x0026 -> AMPERSAND
"'" # 0x0027 -> APOSTROPHE
'(' # 0x0028 -> LEFT PARENTHESIS
')' # 0x0029 -> RIGHT PARENTHESIS
'*' # 0x002a -> ASTERISK
'+' # 0x002b -> PLUS SIGN
',' # 0x002c -> COMMA
'-' # 0x002d -> HYPHEN-MINUS
'.' # 0x002e -> FULL STOP
'/' # 0x002f -> SOLIDUS
'0' # 0x0030 -> DIGIT ZERO
'1' # 0x0031 -> DIGIT ONE
'2' # 0x0032 -> DIGIT TWO
'3' # 0x0033 -> DIGIT THREE
'4' # 0x0034 -> DIGIT FOUR
'5' # 0x0035 -> DIGIT FIVE
'6' # 0x0036 -> DIGIT SIX
'7' # 0x0037 -> DIGIT SEVEN
'8' # 0x0038 -> DIGIT EIGHT
'9' # 0x0039 -> DIGIT NINE
':' # 0x003a -> COLON
';' # 0x003b -> SEMICOLON
'<' # 0x003c -> LESS-THAN SIGN
'=' # 0x003d -> EQUALS SIGN
'>' # 0x003e -> GREATER-THAN SIGN
'?' # 0x003f -> QUESTION MARK
'@' # 0x0040 -> COMMERCIAL AT
'A' # 0x0041 -> LATIN CAPITAL LETTER A
'B' # 0x0042 -> LATIN CAPITAL LETTER B
'C' # 0x0043 -> LATIN CAPITAL LETTER C
'D' # 0x0044 -> LATIN CAPITAL LETTER D
'E' # 0x0045 -> LATIN CAPITAL LETTER E
'F' # 0x0046 -> LATIN CAPITAL LETTER F
'G' # 0x0047 -> LATIN CAPITAL LETTER G
'H' # 0x0048 -> LATIN CAPITAL LETTER H
'I' # 0x0049 -> LATIN CAPITAL LETTER I
'J' # 0x004a -> LATIN CAPITAL LETTER J
'K' # 0x004b -> LATIN CAPITAL LETTER K
'L' # 0x004c -> LATIN CAPITAL LETTER L
'M' # 0x004d -> LATIN CAPITAL LETTER M
'N' # 0x004e -> LATIN CAPITAL LETTER N
'O' # 0x004f -> LATIN CAPITAL LETTER O
'P' # 0x0050 -> LATIN CAPITAL LETTER P
'Q' # 0x0051 -> LATIN CAPITAL LETTER Q
'R' # 0x0052 -> LATIN CAPITAL LETTER R
'S' # 0x0053 -> LATIN CAPITAL LETTER S
'T' # 0x0054 -> LATIN CAPITAL LETTER T
'U' # 0x0055 -> LATIN CAPITAL LETTER U
'V' # 0x0056 -> LATIN CAPITAL LETTER V
'W' # 0x0057 -> LATIN CAPITAL LETTER W
'X' # 0x0058 -> LATIN CAPITAL LETTER X
'Y' # 0x0059 -> LATIN CAPITAL LETTER Y
'Z' # 0x005a -> LATIN CAPITAL LETTER Z
'[' # 0x005b -> LEFT SQUARE BRACKET
'\\' # 0x005c -> REVERSE SOLIDUS
']' # 0x005d -> RIGHT SQUARE BRACKET
'^' # 0x005e -> CIRCUMFLEX ACCENT
'_' # 0x005f -> LOW LINE
'`' # 0x0060 -> GRAVE ACCENT
'a' # 0x0061 -> LATIN SMALL LETTER A
'b' # 0x0062 -> LATIN SMALL LETTER B
'c' # 0x0063 -> LATIN SMALL LETTER C
'd' # 0x0064 -> LATIN SMALL LETTER D
'e' # 0x0065 -> LATIN SMALL LETTER E
'f' # 0x0066 -> LATIN SMALL LETTER F
'g' # 0x0067 -> LATIN SMALL LETTER G
'h' # 0x0068 -> LATIN SMALL LETTER H
'i' # 0x0069 -> LATIN SMALL LETTER I
'j' # 0x006a -> LATIN SMALL LETTER J
'k' # 0x006b -> LATIN SMALL LETTER K
'l' # 0x006c -> LATIN SMALL LETTER L
'm' # 0x006d -> LATIN SMALL LETTER M
'n' # 0x006e -> LATIN SMALL LETTER N
'o' # 0x006f -> LATIN SMALL LETTER O
'p' # 0x0070 -> LATIN SMALL LETTER P
'q' # 0x0071 -> LATIN SMALL LETTER Q
'r' # 0x0072 -> LATIN SMALL LETTER R
's' # 0x0073 -> LATIN SMALL LETTER S
't' # 0x0074 -> LATIN SMALL LETTER T
'u' # 0x0075 -> LATIN SMALL LETTER U
'v' # 0x0076 -> LATIN SMALL LETTER V
'w' # 0x0077 -> LATIN SMALL LETTER W
'x' # 0x0078 -> LATIN SMALL LETTER X
'y' # 0x0079 -> LATIN SMALL LETTER Y
'z' # 0x007a -> LATIN SMALL LETTER Z
'{' # 0x007b -> LEFT CURLY BRACKET
'|' # 0x007c -> VERTICAL LINE
'}' # 0x007d -> RIGHT CURLY BRACKET
'~' # 0x007e -> TILDE
'\x7f' # 0x007f -> DELETE
'\xb0' # 0x0080 -> DEGREE SIGN
'\xb7' # 0x0081 -> MIDDLE DOT
'\u2219' # 0x0082 -> BULLET OPERATOR
'\u221a' # 0x0083 -> SQUARE ROOT
'\u2592' # 0x0084 -> MEDIUM SHADE
'\u2500' # 0x0085 -> FORMS LIGHT HORIZONTAL
'\u2502' # 0x0086 -> FORMS LIGHT VERTICAL
'\u253c' # 0x0087 -> FORMS LIGHT VERTICAL AND HORIZONTAL
'\u2524' # 0x0088 -> FORMS LIGHT VERTICAL AND LEFT
'\u252c' # 0x0089 -> FORMS LIGHT DOWN AND HORIZONTAL
'\u251c' # 0x008a -> FORMS LIGHT VERTICAL AND RIGHT
'\u2534' # 0x008b -> FORMS LIGHT UP AND HORIZONTAL
'\u2510' # 0x008c -> FORMS LIGHT DOWN AND LEFT
'\u250c' # 0x008d -> FORMS LIGHT DOWN AND RIGHT
'\u2514' # 0x008e -> FORMS LIGHT UP AND RIGHT
'\u2518' # 0x008f -> FORMS LIGHT UP AND LEFT
'\u03b2' # 0x0090 -> GREEK SMALL BETA
'\u221e' # 0x0091 -> INFINITY
'\u03c6' # 0x0092 -> GREEK SMALL PHI
'\xb1' # 0x0093 -> PLUS-OR-MINUS SIGN
'\xbd' # 0x0094 -> FRACTION 1/2
'\xbc' # 0x0095 -> FRACTION 1/4
'\u2248' # 0x0096 -> ALMOST EQUAL TO
'\xab' # 0x0097 -> LEFT POINTING GUILLEMET
'\xbb' # 0x0098 -> RIGHT POINTING GUILLEMET
'\ufef7' # 0x0099 -> ARABIC LIGATURE LAM WITH ALEF WITH HAMZA ABOVE ISOLATED FORM
'\ufef8' # 0x009a -> ARABIC LIGATURE LAM WITH ALEF WITH HAMZA ABOVE FINAL FORM
'\ufffe' # 0x009b -> UNDEFINED
'\ufffe' # 0x009c -> UNDEFINED
'\ufefb' # 0x009d -> ARABIC LIGATURE LAM WITH ALEF ISOLATED FORM
'\ufefc' # 0x009e -> ARABIC LIGATURE LAM WITH ALEF FINAL FORM
'\ufffe' # 0x009f -> UNDEFINED
'\xa0' # 0x00a0 -> NON-BREAKING SPACE
'\xad' # 0x00a1 -> SOFT HYPHEN
'\ufe82' # 0x00a2 -> ARABIC LETTER ALEF WITH MADDA ABOVE FINAL FORM
'\xa3' # 0x00a3 -> POUND SIGN
'\xa4' # 0x00a4 -> CURRENCY SIGN
'\ufe84' # 0x00a5 -> ARABIC LETTER ALEF WITH HAMZA ABOVE FINAL FORM
'\ufffe' # 0x00a6 -> UNDEFINED
'\ufffe' # 0x00a7 -> UNDEFINED
'\ufe8e' # 0x00a8 -> ARABIC LETTER ALEF FINAL FORM
'\ufe8f' # 0x00a9 -> ARABIC LETTER BEH ISOLATED FORM
'\ufe95' # 0x00aa -> ARABIC LETTER TEH ISOLATED FORM
'\ufe99' # 0x00ab -> ARABIC LETTER THEH ISOLATED FORM
'\u060c' # 0x00ac -> ARABIC COMMA
'\ufe9d' # 0x00ad -> ARABIC LETTER JEEM ISOLATED FORM
'\ufea1' # 0x00ae -> ARABIC LETTER HAH ISOLATED FORM
'\ufea5' # 0x00af -> ARABIC LETTER KHAH ISOLATED FORM
'\u0660' # 0x00b0 -> ARABIC-INDIC DIGIT ZERO
'\u0661' # 0x00b1 -> ARABIC-INDIC DIGIT ONE
'\u0662' # 0x00b2 -> ARABIC-INDIC DIGIT TWO
'\u0663' # 0x00b3 -> ARABIC-INDIC DIGIT THREE
'\u0664' # 0x00b4 -> ARABIC-INDIC DIGIT FOUR
'\u0665' # 0x00b5 -> ARABIC-INDIC DIGIT FIVE
'\u0666' # 0x00b6 -> ARABIC-INDIC DIGIT SIX
'\u0667' # 0x00b7 -> ARABIC-INDIC DIGIT SEVEN
'\u0668' # 0x00b8 -> ARABIC-INDIC DIGIT EIGHT
'\u0669' # 0x00b9 -> ARABIC-INDIC DIGIT NINE
'\ufed1' # 0x00ba -> ARABIC LETTER FEH ISOLATED FORM
'\u061b' # 0x00bb -> ARABIC SEMICOLON
'\ufeb1' # 0x00bc -> ARABIC LETTER SEEN ISOLATED FORM
'\ufeb5' # 0x00bd -> ARABIC LETTER SHEEN ISOLATED FORM
'\ufeb9' # 0x00be -> ARABIC LETTER SAD ISOLATED FORM
'\u061f' # 0x00bf -> ARABIC QUESTION MARK
'\xa2' # 0x00c0 -> CENT SIGN
'\ufe80' # 0x00c1 -> ARABIC LETTER HAMZA ISOLATED FORM
'\ufe81' # 0x00c2 -> ARABIC LETTER ALEF WITH MADDA ABOVE ISOLATED FORM
'\ufe83' # 0x00c3 -> ARABIC LETTER ALEF WITH HAMZA ABOVE ISOLATED FORM
'\ufe85' # 0x00c4 -> ARABIC LETTER WAW WITH HAMZA ABOVE ISOLATED FORM
'\ufeca' # 0x00c5 -> ARABIC LETTER AIN FINAL FORM
'\ufe8b' # 0x00c6 -> ARABIC LETTER YEH WITH HAMZA ABOVE INITIAL FORM
'\ufe8d' # 0x00c7 -> ARABIC LETTER ALEF ISOLATED FORM
'\ufe91' # 0x00c8 -> ARABIC LETTER BEH INITIAL FORM
'\ufe93' # 0x00c9 -> ARABIC LETTER TEH MARBUTA ISOLATED FORM
'\ufe97' # 0x00ca -> ARABIC LETTER TEH INITIAL FORM
'\ufe9b' # 0x00cb -> ARABIC LETTER THEH INITIAL FORM
'\ufe9f' # 0x00cc -> ARABIC LETTER JEEM INITIAL FORM
'\ufea3' # 0x00cd -> ARABIC LETTER HAH INITIAL FORM
'\ufea7' # 0x00ce -> ARABIC LETTER KHAH INITIAL FORM
'\ufea9' # 0x00cf -> ARABIC LETTER DAL ISOLATED FORM
'\ufeab' # 0x00d0 -> ARABIC LETTER THAL ISOLATED FORM
'\ufead' # 0x00d1 -> ARABIC LETTER REH ISOLATED FORM
'\ufeaf' # 0x00d2 -> ARABIC LETTER ZAIN ISOLATED FORM
'\ufeb3' # 0x00d3 -> ARABIC LETTER SEEN INITIAL FORM
'\ufeb7' # 0x00d4 -> ARABIC LETTER SHEEN INITIAL FORM
'\ufebb' # 0x00d5 -> ARABIC LETTER SAD INITIAL FORM
'\ufebf' # 0x00d6 -> ARABIC LETTER DAD INITIAL FORM
'\ufec1' # 0x00d7 -> ARABIC LETTER TAH ISOLATED FORM
'\ufec5' # 0x00d8 -> ARABIC LETTER ZAH ISOLATED FORM
'\ufecb' # 0x00d9 -> ARABIC LETTER AIN INITIAL FORM
'\ufecf' # 0x00da -> ARABIC LETTER GHAIN INITIAL FORM
'\xa6' # 0x00db -> BROKEN VERTICAL BAR
'\xac' # 0x00dc -> NOT SIGN
'\xf7' # 0x00dd -> DIVISION SIGN
'\xd7' # 0x00de -> MULTIPLICATION SIGN
'\ufec9' # 0x00df -> ARABIC LETTER AIN ISOLATED FORM
'\u0640' # 0x00e0 -> ARABIC TATWEEL
'\ufed3' # 0x00e1 -> ARABIC LETTER FEH INITIAL FORM
'\ufed7' # 0x00e2 -> ARABIC LETTER QAF INITIAL FORM
'\ufedb' # 0x00e3 -> ARABIC LETTER KAF INITIAL FORM
'\ufedf' # 0x00e4 -> ARABIC LETTER LAM INITIAL FORM
'\ufee3' # 0x00e5 -> ARABIC LETTER MEEM INITIAL FORM
'\ufee7' # 0x00e6 -> ARABIC LETTER NOON INITIAL FORM
'\ufeeb' # 0x00e7 -> ARABIC LETTER HEH INITIAL FORM
'\ufeed' # 0x00e8 -> ARABIC LETTER WAW ISOLATED FORM
'\ufeef' # 0x00e9 -> ARABIC LETTER ALEF MAKSURA ISOLATED FORM
'\ufef3' # 0x00ea -> ARABIC LETTER YEH INITIAL FORM
'\ufebd' # 0x00eb -> ARABIC LETTER DAD ISOLATED FORM
'\ufecc' # 0x00ec -> ARABIC LETTER AIN MEDIAL FORM
'\ufece' # 0x00ed -> ARABIC LETTER GHAIN FINAL FORM
'\ufecd' # 0x00ee -> ARABIC LETTER GHAIN ISOLATED FORM
'\ufee1' # 0x00ef -> ARABIC LETTER MEEM ISOLATED FORM
'\ufe7d' # 0x00f0 -> ARABIC SHADDA MEDIAL FORM
'\u0651' # 0x00f1 -> ARABIC SHADDAH
'\ufee5' # 0x00f2 -> ARABIC LETTER NOON ISOLATED FORM
'\ufee9' # 0x00f3 -> ARABIC LETTER HEH ISOLATED FORM
'\ufeec' # 0x00f4 -> ARABIC LETTER HEH MEDIAL FORM
'\ufef0' # 0x00f5 -> ARABIC LETTER ALEF MAKSURA FINAL FORM
'\ufef2' # 0x00f6 -> ARABIC LETTER YEH FINAL FORM
'\ufed0' # 0x00f7 -> ARABIC LETTER GHAIN MEDIAL FORM
'\ufed5' # 0x00f8 -> ARABIC LETTER QAF ISOLATED FORM
'\ufef5' # 0x00f9 -> ARABIC LIGATURE LAM WITH ALEF WITH MADDA ABOVE ISOLATED FORM
'\ufef6' # 0x00fa -> ARABIC LIGATURE LAM WITH ALEF WITH MADDA ABOVE FINAL FORM
'\ufedd' # 0x00fb -> ARABIC LETTER LAM ISOLATED FORM
'\ufed9' # 0x00fc -> ARABIC LETTER KAF ISOLATED FORM
'\ufef1' # 0x00fd -> ARABIC LETTER YEH ISOLATED FORM
'\u25a0' # 0x00fe -> BLACK SQUARE
'\ufffe' # 0x00ff -> UNDEFINED
)
### Encoding Map
encoding_map = {
0x0000: 0x0000, # NULL
0x0001: 0x0001, # START OF HEADING
0x0002: 0x0002, # START OF TEXT
0x0003: 0x0003, # END OF TEXT
0x0004: 0x0004, # END OF TRANSMISSION
0x0005: 0x0005, # ENQUIRY
0x0006: 0x0006, # ACKNOWLEDGE
0x0007: 0x0007, # BELL
0x0008: 0x0008, # BACKSPACE
0x0009: 0x0009, # HORIZONTAL TABULATION
0x000a: 0x000a, # LINE FEED
0x000b: 0x000b, # VERTICAL TABULATION
0x000c: 0x000c, # FORM FEED
0x000d: 0x000d, # CARRIAGE RETURN
0x000e: 0x000e, # SHIFT OUT
0x000f: 0x000f, # SHIFT IN
0x0010: 0x0010, # DATA LINK ESCAPE
0x0011: 0x0011, # DEVICE CONTROL ONE
0x0012: 0x0012, # DEVICE CONTROL TWO
0x0013: 0x0013, # DEVICE CONTROL THREE
0x0014: 0x0014, # DEVICE CONTROL FOUR
0x0015: 0x0015, # NEGATIVE ACKNOWLEDGE
0x0016: 0x0016, # SYNCHRONOUS IDLE
0x0017: 0x0017, # END OF TRANSMISSION BLOCK
0x0018: 0x0018, # CANCEL
0x0019: 0x0019, # END OF MEDIUM
0x001a: 0x001a, # SUBSTITUTE
0x001b: 0x001b, # ESCAPE
0x001c: 0x001c, # FILE SEPARATOR
0x001d: 0x001d, # GROUP SEPARATOR
0x001e: 0x001e, # RECORD SEPARATOR
0x001f: 0x001f, # UNIT SEPARATOR
0x0020: 0x0020, # SPACE
0x0021: 0x0021, # EXCLAMATION MARK
0x0022: 0x0022, # QUOTATION MARK
0x0023: 0x0023, # NUMBER SIGN
0x0024: 0x0024, # DOLLAR SIGN
0x0026: 0x0026, # AMPERSAND
0x0027: 0x0027, # APOSTROPHE
0x0028: 0x0028, # LEFT PARENTHESIS
0x0029: 0x0029, # RIGHT PARENTHESIS
0x002a: 0x002a, # ASTERISK
0x002b: 0x002b, # PLUS SIGN
0x002c: 0x002c, # COMMA
0x002d: 0x002d, # HYPHEN-MINUS
0x002e: 0x002e, # FULL STOP
0x002f: 0x002f, # SOLIDUS
0x0030: 0x0030, # DIGIT ZERO
0x0031: 0x0031, # DIGIT ONE
0x0032: 0x0032, # DIGIT TWO
0x0033: 0x0033, # DIGIT THREE
0x0034: 0x0034, # DIGIT FOUR
0x0035: 0x0035, # DIGIT FIVE
0x0036: 0x0036, # DIGIT SIX
0x0037: 0x0037, # DIGIT SEVEN
0x0038: 0x0038, # DIGIT EIGHT
0x0039: 0x0039, # DIGIT NINE
0x003a: 0x003a, # COLON
0x003b: 0x003b, # SEMICOLON
0x003c: 0x003c, # LESS-THAN SIGN
0x003d: 0x003d, # EQUALS SIGN
0x003e: 0x003e, # GREATER-THAN SIGN
0x003f: 0x003f, # QUESTION MARK
0x0040: 0x0040, # COMMERCIAL AT
0x0041: 0x0041, # LATIN CAPITAL LETTER A
0x0042: 0x0042, # LATIN CAPITAL LETTER B
0x0043: 0x0043, # LATIN CAPITAL LETTER C
0x0044: 0x0044, # LATIN CAPITAL LETTER D
0x0045: 0x0045, # LATIN CAPITAL LETTER E
0x0046: 0x0046, # LATIN CAPITAL LETTER F
0x0047: 0x0047, # LATIN CAPITAL LETTER G
0x0048: 0x0048, # LATIN CAPITAL LETTER H
0x0049: 0x0049, # LATIN CAPITAL LETTER I
0x004a: 0x004a, # LATIN CAPITAL LETTER J
0x004b: 0x004b, # LATIN CAPITAL LETTER K
0x004c: 0x004c, # LATIN CAPITAL LETTER L
0x004d: 0x004d, # LATIN CAPITAL LETTER M
0x004e: 0x004e, # LATIN CAPITAL LETTER N
0x004f: 0x004f, # LATIN CAPITAL LETTER O
0x0050: 0x0050, # LATIN CAPITAL LETTER P
0x0051: 0x0051, # LATIN CAPITAL LETTER Q
0x0052: 0x0052, # LATIN CAPITAL LETTER R
0x0053: 0x0053, # LATIN CAPITAL LETTER S
0x0054: 0x0054, # LATIN CAPITAL LETTER T
0x0055: 0x0055, # LATIN CAPITAL LETTER U
0x0056: 0x0056, # LATIN CAPITAL LETTER V
0x0057: 0x0057, # LATIN CAPITAL LETTER W
0x0058: 0x0058, # LATIN CAPITAL LETTER X
0x0059: 0x0059, # LATIN CAPITAL LETTER Y
0x005a: 0x005a, # LATIN CAPITAL LETTER Z
0x005b: 0x005b, # LEFT SQUARE BRACKET
0x005c: 0x005c, # REVERSE SOLIDUS
0x005d: 0x005d, # RIGHT SQUARE BRACKET
0x005e: 0x005e, # CIRCUMFLEX ACCENT
0x005f: 0x005f, # LOW LINE
0x0060: 0x0060, # GRAVE ACCENT
0x0061: 0x0061, # LATIN SMALL LETTER A
0x0062: 0x0062, # LATIN SMALL LETTER B
0x0063: 0x0063, # LATIN SMALL LETTER C
0x0064: 0x0064, # LATIN SMALL LETTER D
0x0065: 0x0065, # LATIN SMALL LETTER E
0x0066: 0x0066, # LATIN SMALL LETTER F
0x0067: 0x0067, # LATIN SMALL LETTER G
0x0068: 0x0068, # LATIN SMALL LETTER H
0x0069: 0x0069, # LATIN SMALL LETTER I
0x006a: 0x006a, # LATIN SMALL LETTER J
0x006b: 0x006b, # LATIN SMALL LETTER K
0x006c: 0x006c, # LATIN SMALL LETTER L
0x006d: 0x006d, # LATIN SMALL LETTER M
0x006e: 0x006e, # LATIN SMALL LETTER N
0x006f: 0x006f, # LATIN SMALL LETTER O
0x0070: 0x0070, # LATIN SMALL LETTER P
0x0071: 0x0071, # LATIN SMALL LETTER Q
0x0072: 0x0072, # LATIN SMALL LETTER R
0x0073: 0x0073, # LATIN SMALL LETTER S
0x0074: 0x0074, # LATIN SMALL LETTER T
0x0075: 0x0075, # LATIN SMALL LETTER U
0x0076: 0x0076, # LATIN SMALL LETTER V
0x0077: 0x0077, # LATIN SMALL LETTER W
0x0078: 0x0078, # LATIN SMALL LETTER X
0x0079: 0x0079, # LATIN SMALL LETTER Y
0x007a: 0x007a, # LATIN SMALL LETTER Z
0x007b: 0x007b, # LEFT CURLY BRACKET
0x007c: 0x007c, # VERTICAL LINE
0x007d: 0x007d, # RIGHT CURLY BRACKET
0x007e: 0x007e, # TILDE
0x007f: 0x007f, # DELETE
0x00a0: 0x00a0, # NON-BREAKING SPACE
0x00a2: 0x00c0, # CENT SIGN
0x00a3: 0x00a3, # POUND SIGN
0x00a4: 0x00a4, # CURRENCY SIGN
0x00a6: 0x00db, # BROKEN VERTICAL BAR
0x00ab: 0x0097, # LEFT POINTING GUILLEMET
0x00ac: 0x00dc, # NOT SIGN
0x00ad: 0x00a1, # SOFT HYPHEN
0x00b0: 0x0080, # DEGREE SIGN
0x00b1: 0x0093, # PLUS-OR-MINUS SIGN
0x00b7: 0x0081, # MIDDLE DOT
0x00bb: 0x0098, # RIGHT POINTING GUILLEMET
0x00bc: 0x0095, # FRACTION 1/4
0x00bd: 0x0094, # FRACTION 1/2
0x00d7: 0x00de, # MULTIPLICATION SIGN
0x00f7: 0x00dd, # DIVISION SIGN
0x03b2: 0x0090, # GREEK SMALL BETA
0x03c6: 0x0092, # GREEK SMALL PHI
0x060c: 0x00ac, # ARABIC COMMA
0x061b: 0x00bb, # ARABIC SEMICOLON
0x061f: 0x00bf, # ARABIC QUESTION MARK
0x0640: 0x00e0, # ARABIC TATWEEL
0x0651: 0x00f1, # ARABIC SHADDAH
0x0660: 0x00b0, # ARABIC-INDIC DIGIT ZERO
0x0661: 0x00b1, # ARABIC-INDIC DIGIT ONE
0x0662: 0x00b2, # ARABIC-INDIC DIGIT TWO
0x0663: 0x00b3, # ARABIC-INDIC DIGIT THREE
0x0664: 0x00b4, # ARABIC-INDIC DIGIT FOUR
0x0665: 0x00b5, # ARABIC-INDIC DIGIT FIVE
0x0666: 0x00b6, # ARABIC-INDIC DIGIT SIX
0x0667: 0x00b7, # ARABIC-INDIC DIGIT SEVEN
0x0668: 0x00b8, # ARABIC-INDIC DIGIT EIGHT
0x0669: 0x00b9, # ARABIC-INDIC DIGIT NINE
0x066a: 0x0025, # ARABIC PERCENT SIGN
0x2219: 0x0082, # BULLET OPERATOR
0x221a: 0x0083, # SQUARE ROOT
0x221e: 0x0091, # INFINITY
0x2248: 0x0096, # ALMOST EQUAL TO
0x2500: 0x0085, # FORMS LIGHT HORIZONTAL
0x2502: 0x0086, # FORMS LIGHT VERTICAL
0x250c: 0x008d, # FORMS LIGHT DOWN AND RIGHT
0x2510: 0x008c, # FORMS LIGHT DOWN AND LEFT
0x2514: 0x008e, # FORMS LIGHT UP AND RIGHT
0x2518: 0x008f, # FORMS LIGHT UP AND LEFT
0x251c: 0x008a, # FORMS LIGHT VERTICAL AND RIGHT
0x2524: 0x0088, # FORMS LIGHT VERTICAL AND LEFT
0x252c: 0x0089, # FORMS LIGHT DOWN AND HORIZONTAL
0x2534: 0x008b, # FORMS LIGHT UP AND HORIZONTAL
0x253c: 0x0087, # FORMS LIGHT VERTICAL AND HORIZONTAL
0x2592: 0x0084, # MEDIUM SHADE
0x25a0: 0x00fe, # BLACK SQUARE
0xfe7d: 0x00f0, # ARABIC SHADDA MEDIAL FORM
0xfe80: 0x00c1, # ARABIC LETTER HAMZA ISOLATED FORM
0xfe81: 0x00c2, # ARABIC LETTER ALEF WITH MADDA ABOVE ISOLATED FORM
0xfe82: 0x00a2, # ARABIC LETTER ALEF WITH MADDA ABOVE FINAL FORM
0xfe83: 0x00c3, # ARABIC LETTER ALEF WITH HAMZA ABOVE ISOLATED FORM
0xfe84: 0x00a5, # ARABIC LETTER ALEF WITH HAMZA ABOVE FINAL FORM
0xfe85: 0x00c4, # ARABIC LETTER WAW WITH HAMZA ABOVE ISOLATED FORM
0xfe8b: 0x00c6, # ARABIC LETTER YEH WITH HAMZA ABOVE INITIAL FORM
0xfe8d: 0x00c7, # ARABIC LETTER ALEF ISOLATED FORM
0xfe8e: 0x00a8, # ARABIC LETTER ALEF FINAL FORM
0xfe8f: 0x00a9, # ARABIC LETTER BEH ISOLATED FORM
0xfe91: 0x00c8, # ARABIC LETTER BEH INITIAL FORM
0xfe93: 0x00c9, # ARABIC LETTER TEH MARBUTA ISOLATED FORM
0xfe95: 0x00aa, # ARABIC LETTER TEH ISOLATED FORM
0xfe97: 0x00ca, # ARABIC LETTER TEH INITIAL FORM
0xfe99: 0x00ab, # ARABIC LETTER THEH ISOLATED FORM
0xfe9b: 0x00cb, # ARABIC LETTER THEH INITIAL FORM
0xfe9d: 0x00ad, # ARABIC LETTER JEEM ISOLATED FORM
0xfe9f: 0x00cc, # ARABIC LETTER JEEM INITIAL FORM
0xfea1: 0x00ae, # ARABIC LETTER HAH ISOLATED FORM
0xfea3: 0x00cd, # ARABIC LETTER HAH INITIAL FORM
0xfea5: 0x00af, # ARABIC LETTER KHAH ISOLATED FORM
0xfea7: 0x00ce, # ARABIC LETTER KHAH INITIAL FORM
0xfea9: 0x00cf, # ARABIC LETTER DAL ISOLATED FORM
0xfeab: 0x00d0, # ARABIC LETTER THAL ISOLATED FORM
0xfead: 0x00d1, # ARABIC LETTER REH ISOLATED FORM
0xfeaf: 0x00d2, # ARABIC LETTER ZAIN ISOLATED FORM
0xfeb1: 0x00bc, # ARABIC LETTER SEEN ISOLATED FORM
0xfeb3: 0x00d3, # ARABIC LETTER SEEN INITIAL FORM
0xfeb5: 0x00bd, # ARABIC LETTER SHEEN ISOLATED FORM
0xfeb7: 0x00d4, # ARABIC LETTER SHEEN INITIAL FORM
0xfeb9: 0x00be, # ARABIC LETTER SAD ISOLATED FORM
0xfebb: 0x00d5, # ARABIC LETTER SAD INITIAL FORM
0xfebd: 0x00eb, # ARABIC LETTER DAD ISOLATED FORM
0xfebf: 0x00d6, # ARABIC LETTER DAD INITIAL FORM
0xfec1: 0x00d7, # ARABIC LETTER TAH ISOLATED FORM
0xfec5: 0x00d8, # ARABIC LETTER ZAH ISOLATED FORM
0xfec9: 0x00df, # ARABIC LETTER AIN ISOLATED FORM
0xfeca: 0x00c5, # ARABIC LETTER AIN FINAL FORM
0xfecb: 0x00d9, # ARABIC LETTER AIN INITIAL FORM
0xfecc: 0x00ec, # ARABIC LETTER AIN MEDIAL FORM
0xfecd: 0x00ee, # ARABIC LETTER GHAIN ISOLATED FORM
0xfece: 0x00ed, # ARABIC LETTER GHAIN FINAL FORM
0xfecf: 0x00da, # ARABIC LETTER GHAIN INITIAL FORM
0xfed0: 0x00f7, # ARABIC LETTER GHAIN MEDIAL FORM
0xfed1: 0x00ba, # ARABIC LETTER FEH ISOLATED FORM
0xfed3: 0x00e1, # ARABIC LETTER FEH INITIAL FORM
0xfed5: 0x00f8, # ARABIC LETTER QAF ISOLATED FORM
0xfed7: 0x00e2, # ARABIC LETTER QAF INITIAL FORM
0xfed9: 0x00fc, # ARABIC LETTER KAF ISOLATED FORM
0xfedb: 0x00e3, # ARABIC LETTER KAF INITIAL FORM
0xfedd: 0x00fb, # ARABIC LETTER LAM ISOLATED FORM
0xfedf: 0x00e4, # ARABIC LETTER LAM INITIAL FORM
0xfee1: 0x00ef, # ARABIC LETTER MEEM ISOLATED FORM
0xfee3: 0x00e5, # ARABIC LETTER MEEM INITIAL FORM
0xfee5: 0x00f2, # ARABIC LETTER NOON ISOLATED FORM
0xfee7: 0x00e6, # ARABIC LETTER NOON INITIAL FORM
0xfee9: 0x00f3, # ARABIC LETTER HEH ISOLATED FORM
0xfeeb: 0x00e7, # ARABIC LETTER HEH INITIAL FORM
0xfeec: 0x00f4, # ARABIC LETTER HEH MEDIAL FORM
0xfeed: 0x00e8, # ARABIC LETTER WAW ISOLATED FORM
0xfeef: 0x00e9, # ARABIC LETTER ALEF MAKSURA ISOLATED FORM
0xfef0: 0x00f5, # ARABIC LETTER ALEF MAKSURA FINAL FORM
0xfef1: 0x00fd, # ARABIC LETTER YEH ISOLATED FORM
0xfef2: 0x00f6, # ARABIC LETTER YEH FINAL FORM
0xfef3: 0x00ea, # ARABIC LETTER YEH INITIAL FORM
0xfef5: 0x00f9, # ARABIC LIGATURE LAM WITH ALEF WITH MADDA ABOVE ISOLATED FORM
0xfef6: 0x00fa, # ARABIC LIGATURE LAM WITH ALEF WITH MADDA ABOVE FINAL FORM
0xfef7: 0x0099, # ARABIC LIGATURE LAM WITH ALEF WITH HAMZA ABOVE ISOLATED FORM
0xfef8: 0x009a, # ARABIC LIGATURE LAM WITH ALEF WITH HAMZA ABOVE FINAL FORM
0xfefb: 0x009d, # ARABIC LIGATURE LAM WITH ALEF ISOLATED FORM
0xfefc: 0x009e, # ARABIC LIGATURE LAM WITH ALEF FINAL FORM
}
| bsd-3-clause |
thorwhalen/ut | ml/stream/sequences.py | 1 | 6137 |
from sklearn.base import BaseEstimator
from collections import Counter
import pandas as pd
from numpy import sum, nan, isnan
from ut.util.uiter import window
class NextElementPredictor(BaseEstimator):
def predict(self, seqs):
preds = self.predict_proba(seqs)
return [max(pred, key=lambda key: pred[key]) for pred in preds]
def predict_proba(self, seqs):
return list(map(self._predict_proba_conditioned_on_recent_subseq, seqs))
def _predict_proba_conditioned_on_recent_subseq(self, recent_subseq):
raise NotImplementedError("Need to implement this method")
class MarkovNextElementPred(NextElementPredictor):
_list_of_attributes_to_display = ['markov_window', 'empty_element', 'keep_stats_in_memory']
def __init__(self, markov_window=2, empty_element=-1, keep_stats_in_memory=True):
self.markov_window = markov_window
self.keep_stats_in_memory = keep_stats_in_memory
self.empty_element = empty_element
self._empty_element_padding = [empty_element] * (self.markov_window - 1)
@property
def total_tuple_count(self):
"""
:return: Number of observed window tuples (sum of values in self.snip_tuples_counter_)
"""
if self.total_tuple_count_ is not None:
return self.total_tuple_count_
else:
total_tuple_count_ = sum(self.snip_tuples_counter_.values())
if self.keep_stats_in_memory:
self.total_tuple_count_ = total_tuple_count_
return total_tuple_count_
@property
def pair_prob(self):
"""
:return: Series of probabilities (unsmoothed count ratios) indexed by snip pairs
"""
if self.pair_prob_ is not None:
return self.pair_prob_
else:
pair_prob_ = pd.Series(self.snip_tuples_counter_) / self.total_tuple_count
if self.keep_stats_in_memory:
self.pair_probs_ = pair_prob_
return pair_prob_
@property
def element_prob(self):
"""
:return: Series of snips probabilities (unsmoothed count ratios)
"""
if self.element_prob_ is not None:
return self.element_prob_
else:
element_prob_ = (self.pair_prob * self.total_tuple_count)
element_prob_ = element_prob_.groupby(level=0).sum()
element_prob_ = element_prob_.drop(labels=self.empty_element)
# element_prob_ = element_prob_.iloc[
# element_prob_.index.get_level_values(level=0) != self.empty_element]
element_prob_ /= element_prob_.sum()
if self.keep_stats_in_memory:
self.element_prob_ = element_prob_
return element_prob_
@property
def conditional_prob(self):
"""
:return: Series of probabilities of last element (level) conditional on previous ones (including empty elements)
"""
if self.conditional_prob_ is not None:
return self.conditional_prob_
else:
conditional_prob_ = self._drop_empty_elements_of_sr(self.pair_prob, levels=[self.markov_window - 1])
conditional_levels = list(range(self.markov_window - 1))
conditional_prob_ = conditional_prob_.div(
conditional_prob_.groupby(level=conditional_levels).sum(), level=0) # TODO: Only works for two levels
if self.keep_stats_in_memory:
self.conditional_prob_ = conditional_prob_
return conditional_prob_
@property
def initial_element_prob(self):
"""
:return: Series of snips probabilities (unsmoothed count ratios)
"""
if self.initial_element_prob_ is not None:
return self.initial_element_prob_
else:
initial_element_prob_ = self.pair_prob.xs(self.empty_element, level=0, drop_level=True)
initial_element_prob_ /= initial_element_prob_.sum()
if self.keep_stats_in_memory:
self.initial_element_prob_ = initial_element_prob_
return initial_element_prob_
def fit(self, snips_list):
# reset anything previously learned
self._initialize_params()
return self.partial_fit(snips_list)
def partial_fit(self, snips_list):
if not set(['snip_tuples_counter_']).issubset(list(self.__dict__.keys())):
self._initialize_params()
for snips in snips_list:
self._partial_fit_of_a_single_snips(snips)
return self
def _initialize_params(self):
"""
Initializes model params (the snip_tuples_counter_, etc.)
:return: None
"""
self.snip_tuples_counter_ = Counter()
self._reset_properties()
def _reset_properties(self):
"""
Resets some properties that depend on snip_tuples_counter_ to be computed (is used when the later changes)
These will be recomputed when requested.
:return: None
"""
self.total_tuple_count_ = None
self.pair_prob_ = None
self.element_prob_ = None
self.initial_element_prob_ = None
self.conditional_prob_ = None
def _partial_fit_of_a_single_snips(self, snips):
self._reset_properties()
self.snip_tuples_counter_.update(window(self._empty_element_padding + list(snips) + self._empty_element_padding,
n=self.markov_window))
def _drop_empty_elements_of_sr(self, sr, levels=None, renormalize=False):
if levels is None:
levels = list(range(self.markov_window))
for level in levels:
sr = sr.drop(labels=self.empty_element, level=level)
if renormalize:
sr /= sr.sum()
return sr
def _predict_proba_conditioned_on_recent_subseq(self, recent_subseq):
pass
def __repr__(self):
d = {attr: getattr(self, attr) for attr in self._list_of_attributes_to_display if attr in self.__dict__}
d['total_tuple_count'] = self.total_tuple_count
return self.__class__.__name__ + '\n' + str(d)
| mit |
ShassAro/ShassAro | Bl_project/blVirtualEnv/lib/python2.7/site-packages/setuptools/tests/test_test.py | 124 | 3712 | # -*- coding: UTF-8 -*-
"""develop tests
"""
import os
import shutil
import site
import sys
import tempfile
import unittest
from distutils.errors import DistutilsError
from setuptools.compat import StringIO
from setuptools.command.test import test
from setuptools.command import easy_install as easy_install_pkg
from setuptools.dist import Distribution
SETUP_PY = """\
from setuptools import setup
setup(name='foo',
packages=['name', 'name.space', 'name.space.tests'],
namespace_packages=['name'],
test_suite='name.space.tests.test_suite',
)
"""
NS_INIT = """# -*- coding: Latin-1 -*-
# Söme Arbiträry Ünicode to test Issüé 310
try:
__import__('pkg_resources').declare_namespace(__name__)
except ImportError:
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)
"""
# Make sure this is Latin-1 binary, before writing:
if sys.version_info < (3,):
NS_INIT = NS_INIT.decode('UTF-8')
NS_INIT = NS_INIT.encode('Latin-1')
TEST_PY = """import unittest
class TestTest(unittest.TestCase):
def test_test(self):
print "Foo" # Should fail under Python 3 unless 2to3 is used
test_suite = unittest.makeSuite(TestTest)
"""
class TestTestTest(unittest.TestCase):
def setUp(self):
if sys.version < "2.6" or hasattr(sys, 'real_prefix'):
return
# Directory structure
self.dir = tempfile.mkdtemp()
os.mkdir(os.path.join(self.dir, 'name'))
os.mkdir(os.path.join(self.dir, 'name', 'space'))
os.mkdir(os.path.join(self.dir, 'name', 'space', 'tests'))
# setup.py
setup = os.path.join(self.dir, 'setup.py')
f = open(setup, 'wt')
f.write(SETUP_PY)
f.close()
self.old_cwd = os.getcwd()
# name/__init__.py
init = os.path.join(self.dir, 'name', '__init__.py')
f = open(init, 'wb')
f.write(NS_INIT)
f.close()
# name/space/__init__.py
init = os.path.join(self.dir, 'name', 'space', '__init__.py')
f = open(init, 'wt')
f.write('#empty\n')
f.close()
# name/space/tests/__init__.py
init = os.path.join(self.dir, 'name', 'space', 'tests', '__init__.py')
f = open(init, 'wt')
f.write(TEST_PY)
f.close()
os.chdir(self.dir)
self.old_base = site.USER_BASE
site.USER_BASE = tempfile.mkdtemp()
self.old_site = site.USER_SITE
site.USER_SITE = tempfile.mkdtemp()
def tearDown(self):
if sys.version < "2.6" or hasattr(sys, 'real_prefix'):
return
os.chdir(self.old_cwd)
shutil.rmtree(self.dir)
shutil.rmtree(site.USER_BASE)
shutil.rmtree(site.USER_SITE)
site.USER_BASE = self.old_base
site.USER_SITE = self.old_site
def test_test(self):
if sys.version < "2.6" or hasattr(sys, 'real_prefix'):
return
dist = Distribution(dict(
name='foo',
packages=['name', 'name.space', 'name.space.tests'],
namespace_packages=['name'],
test_suite='name.space.tests.test_suite',
use_2to3=True,
))
dist.script_name = 'setup.py'
cmd = test(dist)
cmd.user = 1
cmd.ensure_finalized()
cmd.install_dir = site.USER_SITE
cmd.user = 1
old_stdout = sys.stdout
sys.stdout = StringIO()
try:
try: # try/except/finally doesn't work in Python 2.4, so we need nested try-statements.
cmd.run()
except SystemExit: # The test runner calls sys.exit, stop that making an error.
pass
finally:
sys.stdout = old_stdout
| gpl-2.0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.