def __init__(self,
ignore=[regexp(r'.*\.git.*'),
regexp(r'.*\.DS_Store$')],
mapping=[],
host=None,
user=None,
password=None,
rootdir=None):
self.ignore = ignore
self.PATH_MAPPING = mapping
self.host = host
self.user = user
self.password = password
self.root = rootdir
self.observer = None
self.stream = None
self.sf = None
self.connected = False
self.exit = False
try:
self.connect()
except Exception as e:
logging.critical("SSH Could not connect!")
logging.critical(str(e))
exit(1)
def doador_2008(cnpj_ou_cpf):
u'''
Consulta o CNPJ ou CPF informado na página de doadores da campanha de 2008
e retorna uma lista contendo os campos em "doador_2008.campos".
Exemplo:
>>> campos = doador_2008('00000000000191')
>>> campos is not None
True
>>> len(campos) == len(doador_2008.campos)
True
'''
pessoa = pessoa_or_valueerror(cnpj_ou_cpf)
scraper = Scraper()
# primeiro verifica se a pessoa foi doadora
url = 'http://www.tse.jus.br/spce2008ConsultaFinanciamento/lovPesquisaDoador.jsp'
scraper.open(url)
scraper.browser.form['cdCpfCnpjDoador'] = pessoa.plain()
scraper.browser.form.find_control(name='acao').readonly = False
scraper.browser.form['acao'] = 'pesquisar'
scraper.submit()
if scraper.html.find('font', text=regexp('A pesquisa n.o retornou resultado.')):
return None
# e pega a lista de quem recebeu
url = 'http://www.tse.jus.br/spce2008ConsultaFinanciamento/inicioServlet.do?acao=candidato'
scraper.open(url)
scraper.browser.form.find_control(name='cdCpfCnpjDoador').readonly = False
scraper.browser.form['cdCpfCnpjDoador'] = pessoa.plain()
scraper.browser.form.find_control(name='acao').readonly = False
scraper.browser.form['acao'] = 'resumo'
scraper.submit()
url = 'http://www.tse.jus.br/spce2008ConsultaFinanciamento/listaReceitaCand.jsp'
scraper.open(url)
td = scraper.html.find('td', attrs={'class':'Left'})
fields = []
while True:
try:
# vai percorrendo os campos <td> e pegando o conteúdo
items = [c for c in td.contents if isinstance(c, basestring)]
s = ''.join(items)
s = s.strip()
fields.append(s.encode('utf8'))
td = td.nextSibling.nextSibling
except AttributeError:
break
return fields
def doador_2004(cnpj_ou_cpf):
u'''
Retorna uma tabela com as doações desta pessoa (cnpj_ou_cpf). A tabela
é uma lista de listas, cada uma contendo os campos em "doador_2004.campos".
>>> tabela = doador_2004('85.907.012/0001-57')
>>> tabela is not None
True
>>> len(tabela)
16
>>> len(tabela[0]) == len(doador_2004.campos)
True
URL: http://www.tse.gov.br/internet/eleicoes/2004/prest_blank.htm
'''
pessoa = pessoa_or_valueerror(cnpj_ou_cpf)
scraper = Scraper()
url = 'http://www.tse.gov.br/sadEleicao2004Prestacao/spce/index.jsp'
scraper.open(url)
scraper.browser.select_form(name='formDoador')
scraper.browser.form.find_control(name='nome').readonly = False
scraper.browser.form.find_control(name='numero').readonly = False
scraper.browser.form['numero'] = pessoa.plain()
scraper.browser.form['nome'] = '%'
try:
scraper.submit()
except:
return None
if not scraper.html.find(text=regexp('Valor Total de Fornecimento')):
return None
table = scraper.html.findAll('table')[-1]
lines = []
for tr in table.findAll('tr')[1:-1]:
columns = []
for td in tr.findAll('td'):
try:
contents = td.b.contents
except:
contents = td.contents
content = ' '.join(contents).strip()
text = html2unicode(content)
columns.append(text)
lines.append(columns)
return lines
def doador_2006(cnpj_ou_cpf):
u'''
Retorna uma tabela com as doações desta pessoa (cnpj_ou_cpf). A tabela é
uma lista de listas, cada uma contendo os campos em "doador_2006.campos".
>>> tabela = doador_2006('181.929.206-15')
>>> tabela is not None
True
>>> len(tabela)
1
>>> len(tabela[0]) == len(doador_2006.campos)
True
URL: http://www.tse.gov.br/internet/eleicoes/2006/prest_contas_blank.htm
'''
pessoa = pessoa_or_valueerror(cnpj_ou_cpf)
scraper = Scraper()
url = 'http://www.tse.gov.br/sadSPCE06F3/faces/careceitaByDoador.jsp'
scraper.open(url)
scraper.browser.form['frmByDoador:cdCpfCgc'] = pessoa.plain()
scraper.submit(name='frmByDoador:_id4')
strong = scraper.html.find('strong', text=regexp('.*prestadas pelo doador.*'))
if strong is None:
return None
table = strong.parent.parent.parent.parent
table = table.nextSibling.nextSibling.nextSibling.nextSibling
lines = []
for tr in table.tbody.findAll('tr'):
columns = []
for td in tr.findAll('td'):
content = td.contents[0].strip()
text = html2unicode(content)
columns.append(text)
lines.append(columns)
return lines
"""Task that analyzes dependencies."""
import datetime
from re import compile as regexp
from selinon import FatalTaskError
import urllib.parse
from f8a_worker.base import BaseTask
from f8a_worker.errors import TaskError
from f8a_worker.schemas import SchemaRef
from f8a_worker.solver import get_ecosystem_solver
from f8a_worker.utils import json_serial
gh_dep = regexp('@?[\w-]+/[\w-]+')
class DependencySnapshotTask(BaseTask):
"""Task that analyzes dependencies."""
_analysis_name = 'dependency_snapshot'
schema_ref = SchemaRef(_analysis_name, '1-0-0')
def _collect_dependencies(self):
"""Return all dependencies for current analysis flow (operates on parent mercator result).
:return: List[str], list of dependencies
"""
wr = self.parent_task_result('metadata')
if not isinstance(wr, dict):
raise TaskError(
'metadata task result has unexpected type: {}; expected dict'.
def FeedShow (macro, Date, Tail, NameDb=DATABASE):
from re import match as regexp
from datetime import datetime
import sqlite3 as db
from news2.utils import date2rus, DATE_FMT
FeedsCon = None
FeedPage = []
f = macro.formatter
BaseQuery = "SELECT Title,Link,Published FROM News WHERE Publish=1"
DateLimit = " AND Published GLOB '%s*'" % Date
DataQuery = BaseQuery
if Date:
if regexp(r"^[0-9]{4}-[0-1][0-9]-[0-3][0-9]$", Date):
DataQuery = DataQuery + DateLimit
else:
if regexp(r"^@.*$", Date):
Tail = NORM_LIMIT
Date = None
if 1 > Tail > MAX_LIMIT:
Tail = MAX_LIMIT
RowLimit = " ORDER BY Published DESC LIMIT %d" % Tail
DataQuery = DataQuery + RowLimit
try:
FeedsCon = db.connect(NameDb)
FeedsCon.row_factory = db.Row
FeedsCur = FeedsCon.cursor()
FeedsCur.execute(DataQuery)
Feeds = FeedsCur.fetchall()
FFeed = True
for feed in Feeds:
if not FFeed:
FeedPage.append(f.rule())
else:
FFeed = False
if Date == None:
Date = feed["Published"][:10]
FeedPage.append(f.big(True)+f.strong(True)+f.pagelink(True,pagename=PAGE_LINK+'/'+Date) +
f.text(date2rus(datetime.strptime(Date,DATE_FMT).date())) +
f.url(False)+f.strong(False)+f.big(False))
FeedPage.append(f.heading(True,4))
FeedPage.append(f.heading(False,4))
FeedPage.append(f.paragraph(True))
FeedPage.append(f.url(True,href=feed["Link"])+f.icon("www")+f.text(feed["Title"])+f.url(False))
if not FFeed:
FeedPage.append(f.paragraph(False))
except:
FeedPage = ""
finally:
if FeedsCon:
FeedsCon.close()
return "".join(FeedPage)
def construct_velocity_tree_py(X1, X2):
n = X1.shape[1]
# merge two data with a given time
t = 0.5
X_all = np.hstack((X1, X1 + t * X2))
# parameter settings
maxIter = 20
eps = 1e-3
sigma = 0.001
gamma = 10
# run DDRTree algorithm
W, Z, stree, Y, R, history = DDRTree_py(
X_all, maxIter=maxIter, eps=eps, sigma=sigma, gamma=gamma
)
# draw velocity figure
# quiver(Z(1, 1: 100), Z(2, 1: 100), Z(1, 101: 200)-Z(1, 1: 100), Z(2, 101: 200)-Z(2, 1: 100));
# plot(Z(1, 1: 100), Z(2, 1: 100), 'ob');
# plot(Z(1, 101: 200), Z(2, 101: 200), 'sr');
G = stree
sG = remove_velocity_points(G, n)
tree = sG
row = []
col = []
val = []
for i in range(sG.shape[0]):
for j in range(sG.shape[1]):
if sG[i][j] != 0:
row = row + [i]
col = col + [j]
val = val + [sG[1][j]]
tree_fname = "tree.csv"
# write sG data to tree.csv
#######
branch_fname = "branch.txt"
cmd = "python extract_branches.py" + tree_fname + branch_fname
branch_cell = []
fid = open(branch_fname, "r")
tline = next(fid)
while isinstance(tline, str):
path = re.regexp(tline, "\d*", "Match") ############
branch_cell = branch_cell + [path] #################
tline = next(fid)
fid.close()
dG = np.zeros((n, n))
for p in range(len(branch_cell)):
path = branch_cell[p]
pos_direct = 0
for bp in range(len(path)):
u = path(bp)
v = u + n
# find the shorest path on graph G(works for trees)
nodeid = u
ve_nodeid = v
shortest_mat = shortest_path(
csgraph=G, directed=False, indices=nodeid, return_predecessors=True
)
velocity_path = []
while ve_nodeid != nodeid:
velocity_path = [shortest_mat[nodeid][ve_nodeid]] + velocity_path
ve_nodeid = shortest_mat[nodeid][ve_nodeid]
velocity_path = [shortest_mat[nodeid][ve_nodeid]] + velocity_path
###v_path = G.Nodes.Name(velocity_path)
# check direction consistency between path and v_path
valid_idx = []
for i in velocity_path:
if i <= n:
valid_idx = valid_idx + [i]
if len(valid_idx) == 1:
# compute direction matching
if bp < len(path):
tree_next_point = Z[:, path(bp)]
v_point = Z[:, v]
u_point = Z[:, u]
angle = calculate_angle(u_point, tree_next_point, v_point)
angle = angle / 3.14 * 180
if angle < 90:
pos_direct = pos_direct + 1
else:
tree_pre_point = Z[:, path(bp - 1)]
v_point = Z[:, v]
u_point = Z[:, u]
angle = calculate_angle(u_point, tree_pre_point, v_point)
angle = angle / 3.14 * 180
if angle > 90:
pos_direct = pos_direct + 1
else:
if bp < len(path):
if path[bp + 1] == valid_idx[2]:
pos_direct = pos_direct + 1
else:
if path[bp - 1] != valid_idx[2]:
pos_direct = pos_direct + 1
neg_direct = len(path) - pos_direct
print(
"branch="
+ str(p)
+ ", ("
+ path[0]
+ "->"
+ path[-1]
+ "), pos="
+ pos_direct
+ ", neg="
+ neg_direct
+ "\n"
)
print(path)
print("\n")
if pos_direct > neg_direct:
for bp in range(len(path) - 1):
dG[path[bp], path[bp + 1]] = 1
else:
for bp in range(len(path) - 1):
dG[path(bp + 1), path(bp)] = 1
# figure;
# plot(digraph(dG));
# title('directed graph') figure; hold on;
row = []
col = []
for i in range(dG.shape[0]):
for j in range(dG.shape[1]):
if dG[i][j] != 0:
row = row + [i]
col = col + [j]
for tn in range(len(row)):
p1 = Y[:, row[tn]]
p2 = Y[:, col[tn]]
dp = p2 - p1
h = plt.quiver(
p1(1), p1(2), dp(1), dp(2), "LineWidth", 5
) ###############need to plot it
set(h, "MaxHeadSize", 1e3, "AutoScaleFactor", 1) #############
for i in range(n):
plt.text(Y(1, i), Y(2, i), str(i)) ##############
plt.savefig("./results/t01_figure3.fig") ##################
def add_regexps(self, regexps):
for re in regexps:
if isinstance(re, str):
self.url_regexps.append(regexp(re))
else:
self.url_regexps.append(re)
from re import compile as regexp
import os
from leapp.libraries.stdlib import run
_current_boot_matcher = regexp(r'BootCurrent: (?P<boot_current>([0-9A-F]*))')
_next_boot_matcher = regexp(r'BootNext: (?P<boot_next>([0-9A-F]*))')
def get_current_boot_match(string):
match = _current_boot_matcher.match(string)
if not match:
return None
captured_groups = match.groupdict()
return captured_groups['boot_current']
def get_next_boot_match(string):
match = _next_boot_matcher.match(string)
if not match:
return None
captured_groups = match.groupdict()
return captured_groups['boot_next']
def maybe_emit_updated_boot_entry():
if not os.path.exists('/sbin/efibootmgr'):
return
efi_info = run(['/sbin/efibootmgr'], checked=False, split=True)
if efi_info['exit_code'] != 0:
from requests import get
from json import loads
from re import compile as regexp
from xml.etree import ElementTree as ET # ... call home!
# Bunch of tokens that we're going to handle specially, the last
# rule matches all letters, in such case lexicographic comparison is
# used. In other cases the definition order of the token is used.
__tokens = (r'rc', r'pre', r'beta', r'alpha', '[a-zA-Z]*',)
# Select number from a string
__number = regexp(r'(\d*)')
# Split by dots (.), dashes (-) and whatever we define in `__tokens`
__splitter = regexp(r'\.|-|({})'.format('|'.join(__tokens))).split
def __split(data):
""" Split the data using `__splitter` and filter out empties """
return list(filter(None, __splitter(data)))
def __parse_vc(n):
""" Parse version component """
# Already an int, return
if isinstance(n, int):
return n
# This part is one of our named `__tokens` so sort them
# from left-right (hence the -1.0)
if n in __tokens:
return -1.0 * (__tokens.index(n) + 1)
def check_encode_format(string):
"""Checks using regexp whether a string fits the encoding format"""
return regexp(ENCODE_RE).match(string) is not None
"Convert a Turtle test type into an LD Patch test type."
# exceptions
entry_name = unicode(entry_name)
if entry_name == "turtle-eval-bad-04":
return NS.NegativeSyntaxTest
# because bad IRIs are forbidden by the LD Patch syntax
# else
return {
RDFT.TestTurtleEval: NS.PositiveEvaluationTest,
RDFT.TestTurtleNegativeEval: NS.NegativeEvaluationTest,
RDFT.TestTurtlePositiveSyntax: NS.PositiveSyntaxTest,
RDFT.TestTurtleNegativeSyntax: NS.NegativeSyntaxTest,
}[etype]
STRIP_COMMENT = regexp(r'(?<!\\)#[^">]*$|^#.*$')
def ttl2patch(iri, revext="", command="Add"):
"Convert a ttl file into an ldpatch file."
ret = URIRef(iri.replace(".ttl", "{}.ldpatch".format(revext)))
ipath = i2p(iri)
opath = i2p(ret)
with open(opath, "w") as ofile:
with open(ipath) as ifile:
for line in ifile:
if line.startswith("@prefix"):
ofile.write(line)
ofile.write("{} {{\n".format(command))
with open(ipath) as ifile:
for line in ifile:
if not line.startswith("@prefix"):
from inspect import getargspec, stack
from re import compile as regexp
from struct import unpack
from uuid import uuid4
from django.conf import settings
ValidEmail = regexp(
r"(?i)(^[-!#$%&'*+/=?^_`{}|~0-9A-Z]+(\.[-!#$%&'*+/=?^_`{}|~0-9A-Z]+)*"
r'|^"([\001-\010\013\014\016-\037!#-\[\]-\177]|\\[\001-\011\013\014\016-\177])*"'
r')@(?:[A-Z0-9-]+\.)+[A-Z]{2,6}$'
)
def choices( choices ):
"""Constructs a tuple of choices tuples for the specified choices."""
return tuple( [ ( str( choice ), str( choice ).capitalize() ) for choice in choices ] )
def identify_remote_ip( request ):
"""Identifies the remote ip of the specified request."""
return request.META.get( 'REMOTE_ADDR' )
def trace_stack( indent = '' ):
"""Traces the stack at the current source line."""
lines = []
for frame, filename, lineno, context, source, pos in reversed( stack()[ 1: ] ):
lines.append( '%sfile "%s", line %d, in %s' % ( indent, filename, lineno, context ) )
if source: