id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
|---|---|---|---|---|---|---|---|---|---|---|---|
220,000 | lorien/grab | grab/script/crawl.py | save_list | def save_list(lst, path):
"""
Save items from list to the file.
"""
with open(path, 'wb') as out:
lines = []
for item in lst:
if isinstance(item, (six.text_type, six.binary_type)):
lines.append(make_str(item))
else:
lines.append(ma... | python | def save_list(lst, path):
"""
Save items from list to the file.
"""
with open(path, 'wb') as out:
lines = []
for item in lst:
if isinstance(item, (six.text_type, six.binary_type)):
lines.append(make_str(item))
else:
lines.append(ma... | [
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220,001 | lorien/grab | grab/proxylist.py | parse_proxy_line | def parse_proxy_line(line):
"""
Parse proxy details from the raw text line.
The text line could be in one of the following formats:
* host:port
* host:port:username:password
"""
line = line.strip()
match = RE_SIMPLE_PROXY.search(line)
if match:
return match.group(1), match.... | python | def parse_proxy_line(line):
"""
Parse proxy details from the raw text line.
The text line could be in one of the following formats:
* host:port
* host:port:username:password
"""
line = line.strip()
match = RE_SIMPLE_PROXY.search(line)
if match:
return match.group(1), match.... | [
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220,002 | lorien/grab | grab/proxylist.py | parse_raw_list_data | def parse_raw_list_data(data, proxy_type='http', proxy_userpwd=None):
"""Iterate over proxy servers found in the raw data"""
if not isinstance(data, six.text_type):
data = data.decode('utf-8')
for orig_line in data.splitlines():
line = orig_line.strip().replace(' ', '')
if line and n... | python | def parse_raw_list_data(data, proxy_type='http', proxy_userpwd=None):
"""Iterate over proxy servers found in the raw data"""
if not isinstance(data, six.text_type):
data = data.decode('utf-8')
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line = orig_line.strip().replace(' ', '')
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220,003 | lorien/grab | grab/proxylist.py | ProxyList.load | def load(self):
"""Load proxy list from configured proxy source"""
self._list = self._source.load()
self._list_iter = itertools.cycle(self._list) | python | def load(self):
"""Load proxy list from configured proxy source"""
self._list = self._source.load()
self._list_iter = itertools.cycle(self._list) | [
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220,004 | lorien/grab | grab/proxylist.py | ProxyList.get_random_proxy | def get_random_proxy(self):
"""Return random proxy"""
idx = randint(0, len(self._list) - 1)
return self._list[idx] | python | def get_random_proxy(self):
"""Return random proxy"""
idx = randint(0, len(self._list) - 1)
return self._list[idx] | [
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220,005 | lorien/grab | grab/spider/task.py | Task.clone | def clone(self, **kwargs):
"""
Clone Task instance.
Reset network_try_count, increase task_try_count.
Reset priority attribute if it was not set explicitly.
"""
# First, create exact copy of the current Task object
attr_copy = self.__dict__.copy()
if att... | python | def clone(self, **kwargs):
"""
Clone Task instance.
Reset network_try_count, increase task_try_count.
Reset priority attribute if it was not set explicitly.
"""
# First, create exact copy of the current Task object
attr_copy = self.__dict__.copy()
if att... | [
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220,006 | lorien/grab | grab/base.py | copy_config | def copy_config(config, mutable_config_keys=MUTABLE_CONFIG_KEYS):
"""
Copy grab config with correct handling of mutable config values.
"""
cloned_config = copy(config)
# Apply ``copy`` function to mutable config values
for key in mutable_config_keys:
cloned_config[key] = copy(config[key... | python | def copy_config(config, mutable_config_keys=MUTABLE_CONFIG_KEYS):
"""
Copy grab config with correct handling of mutable config values.
"""
cloned_config = copy(config)
# Apply ``copy`` function to mutable config values
for key in mutable_config_keys:
cloned_config[key] = copy(config[key... | [
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220,007 | lorien/grab | grab/base.py | Grab.reset | def reset(self):
"""
Reset all attributes which could be modified during previous request
or which is not initialized yet if this is the new Grab instance.
This methods is automatically called before each network request.
"""
self.request_head = None
#self.reque... | python | def reset(self):
"""
Reset all attributes which could be modified during previous request
or which is not initialized yet if this is the new Grab instance.
This methods is automatically called before each network request.
"""
self.request_head = None
#self.reque... | [
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220,008 | lorien/grab | grab/base.py | Grab.clone | def clone(self, **kwargs):
"""
Create clone of Grab instance.
Cloned instance will have the same state: cookies, referrer, response
document data
:param **kwargs: overrides settings of cloned grab instance
"""
grab = Grab(transport=self.transport_param)
... | python | def clone(self, **kwargs):
"""
Create clone of Grab instance.
Cloned instance will have the same state: cookies, referrer, response
document data
:param **kwargs: overrides settings of cloned grab instance
"""
grab = Grab(transport=self.transport_param)
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220,009 | lorien/grab | grab/base.py | Grab.adopt | def adopt(self, grab):
"""
Copy the state of another `Grab` instance.
Use case: create backup of current state to the cloned instance and
then restore the state from it.
"""
self.load_config(grab.config)
self.doc = grab.doc.copy(new_grab=self)
for key ... | python | def adopt(self, grab):
"""
Copy the state of another `Grab` instance.
Use case: create backup of current state to the cloned instance and
then restore the state from it.
"""
self.load_config(grab.config)
self.doc = grab.doc.copy(new_grab=self)
for key ... | [
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220,010 | lorien/grab | grab/base.py | Grab.dump_config | def dump_config(self):
"""
Make clone of current config.
"""
conf = copy_config(self.config, self.mutable_config_keys)
conf['state'] = {
'cookiejar_cookies': list(self.cookies.cookiejar),
}
return conf | python | def dump_config(self):
"""
Make clone of current config.
"""
conf = copy_config(self.config, self.mutable_config_keys)
conf['state'] = {
'cookiejar_cookies': list(self.cookies.cookiejar),
}
return conf | [
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220,011 | lorien/grab | grab/base.py | Grab.load_config | def load_config(self, config):
"""
Configure grab instance with external config object.
"""
self.config = copy_config(config, self.mutable_config_keys)
if 'cookiejar_cookies' in config['state']:
self.cookies = CookieManager.from_cookie_list(
config['s... | python | def load_config(self, config):
"""
Configure grab instance with external config object.
"""
self.config = copy_config(config, self.mutable_config_keys)
if 'cookiejar_cookies' in config['state']:
self.cookies = CookieManager.from_cookie_list(
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220,012 | lorien/grab | grab/base.py | Grab.setup | def setup(self, **kwargs):
"""
Setting up Grab instance configuration.
"""
for key in kwargs:
if key not in self.config.keys():
raise error.GrabMisuseError('Unknown option: %s' % key)
if 'url' in kwargs:
if self.config.get('url'):
... | python | def setup(self, **kwargs):
"""
Setting up Grab instance configuration.
"""
for key in kwargs:
if key not in self.config.keys():
raise error.GrabMisuseError('Unknown option: %s' % key)
if 'url' in kwargs:
if self.config.get('url'):
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220,013 | lorien/grab | grab/base.py | Grab.download | def download(self, url, location, **kwargs):
"""
Fetch document located at ``url`` and save to to ``location``.
"""
doc = self.go(url, **kwargs)
with open(location, 'wb') as out:
out.write(doc.body)
return len(doc.body) | python | def download(self, url, location, **kwargs):
"""
Fetch document located at ``url`` and save to to ``location``.
"""
doc = self.go(url, **kwargs)
with open(location, 'wb') as out:
out.write(doc.body)
return len(doc.body) | [
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220,014 | lorien/grab | grab/base.py | Grab.prepare_request | def prepare_request(self, **kwargs):
"""
Configure all things to make real network request.
This method is called before doing real request via
transport extension.
"""
if self.transport is None:
self.setup_transport(self.transport_param)
self.reset()... | python | def prepare_request(self, **kwargs):
"""
Configure all things to make real network request.
This method is called before doing real request via
transport extension.
"""
if self.transport is None:
self.setup_transport(self.transport_param)
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220,015 | lorien/grab | grab/base.py | Grab.log_request | def log_request(self, extra=''):
"""
Send request details to logging system.
"""
# pylint: disable=no-member
thread_name = threading.currentThread().getName().lower()
# pylint: enable=no-member
if thread_name == 'mainthread':
thread_name = ''
... | python | def log_request(self, extra=''):
"""
Send request details to logging system.
"""
# pylint: disable=no-member
thread_name = threading.currentThread().getName().lower()
# pylint: enable=no-member
if thread_name == 'mainthread':
thread_name = ''
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220,016 | lorien/grab | grab/base.py | Grab.request | def request(self, **kwargs):
"""
Perform network request.
You can specify grab settings in ``**kwargs``.
Any keyword argument will be passed to ``self.config``.
Returns: ``Document`` objects.
"""
self.prepare_request(**kwargs)
refresh_count = 0
... | python | def request(self, **kwargs):
"""
Perform network request.
You can specify grab settings in ``**kwargs``.
Any keyword argument will be passed to ``self.config``.
Returns: ``Document`` objects.
"""
self.prepare_request(**kwargs)
refresh_count = 0
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220,017 | lorien/grab | grab/base.py | Grab.submit | def submit(self, make_request=True, **kwargs):
"""
Submit current form.
:param make_request: if `False` then grab instance will be
configured with form post data but request will not be
performed
For details see `Document.submit()` method
Example::
... | python | def submit(self, make_request=True, **kwargs):
"""
Submit current form.
:param make_request: if `False` then grab instance will be
configured with form post data but request will not be
performed
For details see `Document.submit()` method
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220,018 | lorien/grab | grab/base.py | Grab.process_request_result | def process_request_result(self, prepare_response_func=None):
"""
Process result of real request performed via transport extension.
"""
now = datetime.utcnow()
# TODO: move into separate method
if self.config['debug_post']:
post = self.config['post'] or self.... | python | def process_request_result(self, prepare_response_func=None):
"""
Process result of real request performed via transport extension.
"""
now = datetime.utcnow()
# TODO: move into separate method
if self.config['debug_post']:
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220,019 | lorien/grab | grab/base.py | Grab.save_failed_dump | def save_failed_dump(self):
"""
Save dump of failed request for debugging.
This method is called then fatal network exception is raised.
The saved dump could be used for debugging the reason of the failure.
"""
# try/except for safety, to not break live spiders
... | python | def save_failed_dump(self):
"""
Save dump of failed request for debugging.
This method is called then fatal network exception is raised.
The saved dump could be used for debugging the reason of the failure.
"""
# try/except for safety, to not break live spiders
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220,020 | lorien/grab | grab/base.py | Grab.setup_document | def setup_document(self, content, **kwargs):
"""
Setup `response` object without real network requests.
Useful for testing and debuging.
All ``**kwargs`` will be passed to `Document` constructor.
"""
self.reset()
if isinstance(content, six.text_type):
... | python | def setup_document(self, content, **kwargs):
"""
Setup `response` object without real network requests.
Useful for testing and debuging.
All ``**kwargs`` will be passed to `Document` constructor.
"""
self.reset()
if isinstance(content, six.text_type):
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220,021 | lorien/grab | grab/base.py | Grab.change_proxy | def change_proxy(self, random=True):
"""
Set random proxy from proxylist.
"""
if self.proxylist.size():
if random:
proxy = self.proxylist.get_random_proxy()
else:
proxy = self.proxylist.get_next_proxy()
self.setup(proxy... | python | def change_proxy(self, random=True):
"""
Set random proxy from proxylist.
"""
if self.proxylist.size():
if random:
proxy = self.proxylist.get_random_proxy()
else:
proxy = self.proxylist.get_next_proxy()
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220,022 | lorien/grab | grab/base.py | Grab.make_url_absolute | def make_url_absolute(self, url, resolve_base=False):
"""
Make url absolute using previous request url as base url.
"""
if self.config['url']:
if resolve_base:
ubody = self.doc.unicode_body()
base_url = find_base_url(ubody)
if ... | python | def make_url_absolute(self, url, resolve_base=False):
"""
Make url absolute using previous request url as base url.
"""
if self.config['url']:
if resolve_base:
ubody = self.doc.unicode_body()
base_url = find_base_url(ubody)
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220,023 | lorien/grab | grab/base.py | Grab.detect_request_method | def detect_request_method(self):
"""
Analyze request config and find which
request method will be used.
Returns request method in upper case
This method needs simetime when `process_config` method
was not called yet.
"""
method = self.config['method']
... | python | def detect_request_method(self):
"""
Analyze request config and find which
request method will be used.
Returns request method in upper case
This method needs simetime when `process_config` method
was not called yet.
"""
method = self.config['method']
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220,024 | lorien/grab | grab/cookie.py | create_cookie | def create_cookie(name, value, domain, httponly=None, **kwargs):
"""Creates `cookielib.Cookie` instance"""
if domain == 'localhost':
domain = ''
config = dict(
name=name,
value=value,
version=0,
port=None,
domain=domain,
path='/',
secure=False... | python | def create_cookie(name, value, domain, httponly=None, **kwargs):
"""Creates `cookielib.Cookie` instance"""
if domain == 'localhost':
domain = ''
config = dict(
name=name,
value=value,
version=0,
port=None,
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secure=False... | [
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220,025 | lorien/grab | grab/cookie.py | CookieManager.set | def set(self, name, value, domain, **kwargs):
"""Add new cookie or replace existing cookie with same parameters.
:param name: name of cookie
:param value: value of cookie
:param kwargs: extra attributes of cookie
"""
if domain == 'localhost':
domain = ''
... | python | def set(self, name, value, domain, **kwargs):
"""Add new cookie or replace existing cookie with same parameters.
:param name: name of cookie
:param value: value of cookie
:param kwargs: extra attributes of cookie
"""
if domain == 'localhost':
domain = ''
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220,026 | lorien/grab | grab/cookie.py | CookieManager.load_from_file | def load_from_file(self, path):
"""
Load cookies from the file.
Content of file should be a JSON-serialized list of dicts.
"""
with open(path) as inf:
data = inf.read()
if data:
items = json.loads(data)
else:
i... | python | def load_from_file(self, path):
"""
Load cookies from the file.
Content of file should be a JSON-serialized list of dicts.
"""
with open(path) as inf:
data = inf.read()
if data:
items = json.loads(data)
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220,027 | lorien/grab | grab/cookie.py | CookieManager.save_to_file | def save_to_file(self, path):
"""
Dump all cookies to file.
Cookies are dumped as JSON-serialized dict of keys and values.
"""
with open(path, 'w') as out:
out.write(json.dumps(self.get_dict())) | python | def save_to_file(self, path):
"""
Dump all cookies to file.
Cookies are dumped as JSON-serialized dict of keys and values.
"""
with open(path, 'w') as out:
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220,028 | lorien/grab | grab/spider/task_dispatcher_service.py | TaskDispatcherService.process_service_result | def process_service_result(self, result, task, meta=None):
"""
Process result submitted from any service to task dispatcher service.
Result could be:
* Task
* None
* Task instance
* ResponseNotValid-based exception
* Arbitrary exception
* Network ... | python | def process_service_result(self, result, task, meta=None):
"""
Process result submitted from any service to task dispatcher service.
Result could be:
* Task
* None
* Task instance
* ResponseNotValid-based exception
* Arbitrary exception
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220,029 | lorien/grab | grab/deprecated.py | DeprecatedThings.find_link | def find_link(self, href_pattern, make_absolute=True):
"""
Find link in response body which href value matches ``href_pattern``.
Returns found url or None.
"""
if make_absolute:
self.tree.make_links_absolute(self.doc.url)
if isinstance(href_pattern, six.tex... | python | def find_link(self, href_pattern, make_absolute=True):
"""
Find link in response body which href value matches ``href_pattern``.
Returns found url or None.
"""
if make_absolute:
self.tree.make_links_absolute(self.doc.url)
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220,030 | lorien/grab | grab/deprecated.py | DeprecatedThings.find_link_rex | def find_link_rex(self, rex, make_absolute=True):
"""
Find link matched the given regular expression in response body.
Returns found url or None.
"""
if make_absolute:
self.tree.make_links_absolute(self.doc.url)
for elem, _, link, _ in self.tree.iterlinks()... | python | def find_link_rex(self, rex, make_absolute=True):
"""
Find link matched the given regular expression in response body.
Returns found url or None.
"""
if make_absolute:
self.tree.make_links_absolute(self.doc.url)
for elem, _, link, _ in self.tree.iterlinks()... | [
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220,031 | lorien/grab | grab/deprecated.py | DeprecatedThings.css_one | def css_one(self, path, default=NULL):
"""
Get first element which matches the given css path
or raise DataNotFound.
"""
try:
return self.css_list(path)[0]
except IndexError:
if default is NULL:
raise DataNotFound('CSS path not... | python | def css_one(self, path, default=NULL):
"""
Get first element which matches the given css path
or raise DataNotFound.
"""
try:
return self.css_list(path)[0]
except IndexError:
if default is NULL:
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220,032 | lorien/grab | grab/deprecated.py | DeprecatedThings.css_text | def css_text(self, path, default=NULL, smart=False, normalize_space=True):
"""
Get normalized text of node which matches the css path.
"""
try:
return get_node_text(self.css_one(path), smart=smart,
normalize_space=normalize_space)
exc... | python | def css_text(self, path, default=NULL, smart=False, normalize_space=True):
"""
Get normalized text of node which matches the css path.
"""
try:
return get_node_text(self.css_one(path), smart=smart,
normalize_space=normalize_space)
exc... | [
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220,033 | lorien/grab | grab/deprecated.py | DeprecatedThings.css_number | def css_number(self, path, default=NULL, ignore_spaces=False, smart=False,
make_int=True):
"""
Find number in normalized text of node which
matches the given css path.
"""
try:
text = self.css_text(path, smart=smart)
return find_num... | python | def css_number(self, path, default=NULL, ignore_spaces=False, smart=False,
make_int=True):
"""
Find number in normalized text of node which
matches the given css path.
"""
try:
text = self.css_text(path, smart=smart)
return find_num... | [
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220,034 | lorien/grab | grab/deprecated.py | DeprecatedThings.strip_tags | def strip_tags(self, content, smart=False):
"""
Strip tags from the HTML content.
"""
from lxml.html import fromstring
return get_node_text(fromstring(content), smart=smart) | python | def strip_tags(self, content, smart=False):
"""
Strip tags from the HTML content.
"""
from lxml.html import fromstring
return get_node_text(fromstring(content), smart=smart) | [
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220,035 | lorien/grab | grab/util/misc.py | camel_case_to_underscore | def camel_case_to_underscore(name):
"""Converts camel_case into CamelCase"""
res = RE_TOKEN1.sub(r'\1_\2', name)
res = RE_TOKEN2.sub(r'\1_\2', res)
return res.lower() | python | def camel_case_to_underscore(name):
"""Converts camel_case into CamelCase"""
res = RE_TOKEN1.sub(r'\1_\2', name)
res = RE_TOKEN2.sub(r'\1_\2', res)
return res.lower() | [
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220,036 | lorien/grab | grab/document.py | read_bom | def read_bom(data):
"""Read the byte order mark in the text, if present, and
return the encoding represented by the BOM and the BOM.
If no BOM can be detected, (None, None) is returned.
"""
# common case is no BOM, so this is fast
if data and data[0] in _FIRST_CHARS:
for bom, encoding i... | python | def read_bom(data):
"""Read the byte order mark in the text, if present, and
return the encoding represented by the BOM and the BOM.
If no BOM can be detected, (None, None) is returned.
"""
# common case is no BOM, so this is fast
if data and data[0] in _FIRST_CHARS:
for bom, encoding i... | [
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220,037 | lorien/grab | grab/document.py | Document.parse | def parse(self, charset=None, headers=None):
"""
Parse headers.
This method is called after Grab instance performs network request.
"""
if headers:
self.headers = headers
else:
# Parse headers only from last response
# There could be ... | python | def parse(self, charset=None, headers=None):
"""
Parse headers.
This method is called after Grab instance performs network request.
"""
if headers:
self.headers = headers
else:
# Parse headers only from last response
# There could be ... | [
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220,038 | lorien/grab | grab/document.py | Document.detect_charset | def detect_charset(self):
"""
Detect charset of the response.
Try following methods:
* meta[name="Http-Equiv"]
* XML declaration
* HTTP Content-Type header
Ignore unknown charsets.
Use utf-8 as fallback charset.
"""
charset = None
... | python | def detect_charset(self):
"""
Detect charset of the response.
Try following methods:
* meta[name="Http-Equiv"]
* XML declaration
* HTTP Content-Type header
Ignore unknown charsets.
Use utf-8 as fallback charset.
"""
charset = None
... | [
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220,039 | lorien/grab | grab/document.py | Document.copy | def copy(self, new_grab=None):
"""
Clone the Response object.
"""
obj = self.__class__()
obj.process_grab(new_grab if new_grab else self.grab)
copy_keys = ('status', 'code', 'head', 'body', 'total_time',
'connect_time', 'name_lookup_time',
... | python | def copy(self, new_grab=None):
"""
Clone the Response object.
"""
obj = self.__class__()
obj.process_grab(new_grab if new_grab else self.grab)
copy_keys = ('status', 'code', 'head', 'body', 'total_time',
'connect_time', 'name_lookup_time',
... | [
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220,040 | lorien/grab | grab/document.py | Document.save | def save(self, path):
"""
Save response body to file.
"""
path_dir = os.path.split(path)[0]
if not os.path.exists(path_dir):
try:
os.makedirs(path_dir)
except OSError:
pass
with open(path, 'wb') as out:
... | python | def save(self, path):
"""
Save response body to file.
"""
path_dir = os.path.split(path)[0]
if not os.path.exists(path_dir):
try:
os.makedirs(path_dir)
except OSError:
pass
with open(path, 'wb') as out:
... | [
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220,041 | lorien/grab | grab/document.py | Document.save_hash | def save_hash(self, location, basedir, ext=None):
"""
Save response body into file with special path
builded from hash. That allows to lower number of files
per directory.
:param location: URL of file or something else. It is
used to build the SHA1 hash.
:par... | python | def save_hash(self, location, basedir, ext=None):
"""
Save response body into file with special path
builded from hash. That allows to lower number of files
per directory.
:param location: URL of file or something else. It is
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220,042 | lorien/grab | grab/document.py | Document.json | def json(self):
"""
Return response body deserialized into JSON object.
"""
if six.PY3:
return json.loads(self.body.decode(self.charset))
else:
return json.loads(self.body) | python | def json(self):
"""
Return response body deserialized into JSON object.
"""
if six.PY3:
return json.loads(self.body.decode(self.charset))
else:
return json.loads(self.body) | [
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220,043 | lorien/grab | grab/document.py | Document.browse | def browse(self):
"""
Save response in temporary file and open it in GUI browser.
"""
_, path = tempfile.mkstemp()
self.save(path)
webbrowser.open('file://' + path) | python | def browse(self):
"""
Save response in temporary file and open it in GUI browser.
"""
_, path = tempfile.mkstemp()
self.save(path)
webbrowser.open('file://' + path) | [
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220,044 | lorien/grab | grab/document.py | Document.text_search | def text_search(self, anchor, byte=False):
"""
Search the substring in response body.
:param anchor: string to search
:param byte: if False then `anchor` should be the
unicode string, and search will be performed in
`response.unicode_body()` else `anchor` should ... | python | def text_search(self, anchor, byte=False):
"""
Search the substring in response body.
:param anchor: string to search
:param byte: if False then `anchor` should be the
unicode string, and search will be performed in
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220,045 | lorien/grab | grab/document.py | Document.text_assert | def text_assert(self, anchor, byte=False):
"""
If `anchor` is not found then raise `DataNotFound` exception.
"""
if not self.text_search(anchor, byte=byte):
raise DataNotFound(u'Substring not found: %s' % anchor) | python | def text_assert(self, anchor, byte=False):
"""
If `anchor` is not found then raise `DataNotFound` exception.
"""
if not self.text_search(anchor, byte=byte):
raise DataNotFound(u'Substring not found: %s' % anchor) | [
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220,046 | lorien/grab | grab/document.py | Document.text_assert_any | def text_assert_any(self, anchors, byte=False):
"""
If no `anchors` were found then raise `DataNotFound` exception.
"""
found = False
for anchor in anchors:
if self.text_search(anchor, byte=byte):
found = True
break
if not foun... | python | def text_assert_any(self, anchors, byte=False):
"""
If no `anchors` were found then raise `DataNotFound` exception.
"""
found = False
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220,047 | lorien/grab | grab/document.py | Document.rex_text | def rex_text(self, regexp, flags=0, byte=False, default=NULL):
"""
Search regular expression in response body and return content of first
matching group.
:param byte: if False then search is performed in
`response.unicode_body()` else the rex is searched in `response.body`.
... | python | def rex_text(self, regexp, flags=0, byte=False, default=NULL):
"""
Search regular expression in response body and return content of first
matching group.
:param byte: if False then search is performed in
`response.unicode_body()` else the rex is searched in `response.body`.
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220,048 | lorien/grab | grab/document.py | Document.rex_search | def rex_search(self, regexp, flags=0, byte=False, default=NULL):
"""
Search the regular expression in response body.
:param byte: if False then search is performed in
`response.unicode_body()` else the rex is searched in `response.body`.
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"""
Search the regular expression in response body.
:param byte: if False then search is performed in
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220,049 | lorien/grab | grab/document.py | Document.rex_assert | def rex_assert(self, rex, byte=False):
"""
If `rex` expression is not found then raise `DataNotFound` exception.
"""
self.rex_search(rex, byte=byte) | python | def rex_assert(self, rex, byte=False):
"""
If `rex` expression is not found then raise `DataNotFound` exception.
"""
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220,050 | lorien/grab | grab/document.py | Document.pyquery | def pyquery(self):
"""
Returns pyquery handler.
"""
if not self._pyquery:
from pyquery import PyQuery
self._pyquery = PyQuery(self.tree)
return self._pyquery | python | def pyquery(self):
"""
Returns pyquery handler.
"""
if not self._pyquery:
from pyquery import PyQuery
self._pyquery = PyQuery(self.tree)
return self._pyquery | [
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220,051 | lorien/grab | grab/document.py | Document.unicode_body | def unicode_body(self, ignore_errors=True, fix_special_entities=True):
"""
Return response body as unicode string.
"""
if not self._unicode_body:
self._unicode_body = self.convert_body_to_unicode(
body=self.body,
bom=self.bom,
... | python | def unicode_body(self, ignore_errors=True, fix_special_entities=True):
"""
Return response body as unicode string.
"""
if not self._unicode_body:
self._unicode_body = self.convert_body_to_unicode(
body=self.body,
bom=self.bom,
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220,052 | lorien/grab | grab/document.py | Document.choose_form | def choose_form(self, number=None, xpath=None, name=None, **kwargs):
"""
Set the default form.
:param number: number of form (starting from zero)
:param id: value of "id" attribute
:param name: value of "name" attribute
:param xpath: XPath query
:raises: :class:`... | python | def choose_form(self, number=None, xpath=None, name=None, **kwargs):
"""
Set the default form.
:param number: number of form (starting from zero)
:param id: value of "id" attribute
:param name: value of "name" attribute
:param xpath: XPath query
:raises: :class:`... | [
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:param xpath: XPath query
:raises: :class:`DataNotFound` if form not found
:raises: :class:`GrabMisuseError`
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220,053 | lorien/grab | grab/document.py | Document.form | def form(self):
"""
This attribute points to default form.
If form was not selected manually then select the form
which has the biggest number of input elements.
The form value is just an `lxml.html` form element.
Example::
g.go('some URL')
# C... | python | def form(self):
"""
This attribute points to default form.
If form was not selected manually then select the form
which has the biggest number of input elements.
The form value is just an `lxml.html` form element.
Example::
g.go('some URL')
# C... | [
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If form was not selected manually then select the form
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The form value is just an `lxml.html` form element.
Example::
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220,054 | lorien/grab | grab/document.py | Document.set_input | def set_input(self, name, value):
"""
Set the value of form element by its `name` attribute.
:param name: name of element
:param value: value which should be set to element
To check/uncheck the checkbox pass boolean value.
Example::
g.set_input('sex', 'mal... | python | def set_input(self, name, value):
"""
Set the value of form element by its `name` attribute.
:param name: name of element
:param value: value which should be set to element
To check/uncheck the checkbox pass boolean value.
Example::
g.set_input('sex', 'mal... | [
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:param name: name of element
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Example::
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220,055 | lorien/grab | grab/document.py | Document.set_input_by_id | def set_input_by_id(self, _id, value):
"""
Set the value of form element by its `id` attribute.
:param _id: id of element
:param value: value which should be set to element
"""
xpath = './/*[@id="%s"]' % _id
if self._lxml_form is None:
self.choose_fo... | python | def set_input_by_id(self, _id, value):
"""
Set the value of form element by its `id` attribute.
:param _id: id of element
:param value: value which should be set to element
"""
xpath = './/*[@id="%s"]' % _id
if self._lxml_form is None:
self.choose_fo... | [
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220,056 | lorien/grab | grab/document.py | Document.set_input_by_number | def set_input_by_number(self, number, value):
"""
Set the value of form element by its number in the form
:param number: number of element
:param value: value which should be set to element
"""
sel = XpathSelector(self.form)
elem = sel.select('.//input[@type="te... | python | def set_input_by_number(self, number, value):
"""
Set the value of form element by its number in the form
:param number: number of element
:param value: value which should be set to element
"""
sel = XpathSelector(self.form)
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220,057 | lorien/grab | grab/document.py | Document.set_input_by_xpath | def set_input_by_xpath(self, xpath, value):
"""
Set the value of form element by xpath
:param xpath: xpath path
:param value: value which should be set to element
"""
elem = self.select(xpath).node()
if self._lxml_form is None:
# Explicitly set the ... | python | def set_input_by_xpath(self, xpath, value):
"""
Set the value of form element by xpath
:param xpath: xpath path
:param value: value which should be set to element
"""
elem = self.select(xpath).node()
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220,058 | lorien/grab | grab/document.py | Document.get_form_request | def get_form_request(
self, submit_name=None,
url=None, extra_post=None, remove_from_post=None):
"""
Submit default form.
:param submit_name: name of button which should be "clicked" to
submit form
:param url: explicitly specify form action url
... | python | def get_form_request(
self, submit_name=None,
url=None, extra_post=None, remove_from_post=None):
"""
Submit default form.
:param submit_name: name of button which should be "clicked" to
submit form
:param url: explicitly specify form action url
... | [
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:param submit_name: name of button which should be "clicked" to
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:param url: explicitly specify form action url
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220,059 | lorien/grab | grab/document.py | Document.form_fields | def form_fields(self):
"""
Return fields of default form.
Fill some fields with reasonable values.
"""
fields = dict(self.form.fields) # pylint: disable=no-member
fields_to_remove = set()
for key, val in list(fields.items()):
if isinstance(val, Che... | python | def form_fields(self):
"""
Return fields of default form.
Fill some fields with reasonable values.
"""
fields = dict(self.form.fields) # pylint: disable=no-member
fields_to_remove = set()
for key, val in list(fields.items()):
if isinstance(val, Che... | [
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220,060 | maxpumperla/elephas | elephas/utils/functional_utils.py | add_params | def add_params(param_list_left, param_list_right):
"""Add two lists of parameters one by one
:param param_list_left: list of numpy arrays
:param param_list_right: list of numpy arrays
:return: list of numpy arrays
"""
res = []
for x, y in zip(param_list_left, param_list_right):
res.... | python | def add_params(param_list_left, param_list_right):
"""Add two lists of parameters one by one
:param param_list_left: list of numpy arrays
:param param_list_right: list of numpy arrays
:return: list of numpy arrays
"""
res = []
for x, y in zip(param_list_left, param_list_right):
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220,061 | maxpumperla/elephas | elephas/utils/functional_utils.py | subtract_params | def subtract_params(param_list_left, param_list_right):
"""Subtract two lists of parameters
:param param_list_left: list of numpy arrays
:param param_list_right: list of numpy arrays
:return: list of numpy arrays
"""
res = []
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res.a... | python | def subtract_params(param_list_left, param_list_right):
"""Subtract two lists of parameters
:param param_list_left: list of numpy arrays
:param param_list_right: list of numpy arrays
:return: list of numpy arrays
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220,062 | maxpumperla/elephas | elephas/utils/functional_utils.py | get_neutral | def get_neutral(array_list):
"""Get list of zero-valued numpy arrays for
specified list of numpy arrays
:param array_list: list of numpy arrays
:return: list of zeros of same shape as input
"""
res = []
for x in array_list:
res.append(np.zeros_like(x))
return res | python | def get_neutral(array_list):
"""Get list of zero-valued numpy arrays for
specified list of numpy arrays
:param array_list: list of numpy arrays
:return: list of zeros of same shape as input
"""
res = []
for x in array_list:
res.append(np.zeros_like(x))
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220,063 | maxpumperla/elephas | elephas/utils/functional_utils.py | divide_by | def divide_by(array_list, num_workers):
"""Divide a list of parameters by an integer num_workers.
:param array_list:
:param num_workers:
:return:
"""
for i, x in enumerate(array_list):
array_list[i] /= num_workers
return array_list | python | def divide_by(array_list, num_workers):
"""Divide a list of parameters by an integer num_workers.
:param array_list:
:param num_workers:
:return:
"""
for i, x in enumerate(array_list):
array_list[i] /= num_workers
return array_list | [
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220,064 | maxpumperla/elephas | elephas/parameter/server.py | HttpServer.start_flask_service | def start_flask_service(self):
"""Define Flask parameter server service.
This HTTP server can do two things: get the current model
parameters and update model parameters. After registering
the `parameters` and `update` routes, the service will
get started.
"""
a... | python | def start_flask_service(self):
"""Define Flask parameter server service.
This HTTP server can do two things: get the current model
parameters and update model parameters. After registering
the `parameters` and `update` routes, the service will
get started.
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220,065 | maxpumperla/elephas | elephas/mllib/adapter.py | to_matrix | def to_matrix(np_array):
"""Convert numpy array to MLlib Matrix
"""
if len(np_array.shape) == 2:
return Matrices.dense(np_array.shape[0],
np_array.shape[1],
np_array.ravel())
else:
raise Exception("An MLLib Matrix can only be cr... | python | def to_matrix(np_array):
"""Convert numpy array to MLlib Matrix
"""
if len(np_array.shape) == 2:
return Matrices.dense(np_array.shape[0],
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220,066 | maxpumperla/elephas | elephas/mllib/adapter.py | to_vector | def to_vector(np_array):
"""Convert numpy array to MLlib Vector
"""
if len(np_array.shape) == 1:
return Vectors.dense(np_array)
else:
raise Exception("An MLLib Vector can only be created from a one-dimensional " +
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"""Convert numpy array to MLlib Vector
"""
if len(np_array.shape) == 1:
return Vectors.dense(np_array)
else:
raise Exception("An MLLib Vector can only be created from a one-dimensional " +
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220,067 | maxpumperla/elephas | elephas/java/adapter.py | retrieve_keras_weights | def retrieve_keras_weights(java_model):
"""For a previously imported Keras model, after training it with DL4J Spark,
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:param java_model: DL4J model (MultiLayerNetwork or ComputationGraph
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"""For a previously imported Keras model, after training it with DL4J Spark,
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220,068 | maxpumperla/elephas | elephas/ml_model.py | ElephasEstimator._fit | def _fit(self, df):
"""Private fit method of the Estimator, which trains the model.
"""
simple_rdd = df_to_simple_rdd(df, categorical=self.get_categorical_labels(), nb_classes=self.get_nb_classes(),
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"""Private fit method of the Estimator, which trains the model.
"""
simple_rdd = df_to_simple_rdd(df, categorical=self.get_categorical_labels(), nb_classes=self.get_nb_classes(),
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220,069 | maxpumperla/elephas | elephas/ml_model.py | ElephasTransformer._transform | def _transform(self, df):
"""Private transform method of a Transformer. This serves as batch-prediction method for our purposes.
"""
output_col = self.getOutputCol()
label_col = self.getLabelCol()
new_schema = copy.deepcopy(df.schema)
new_schema.add(StructField(output_col... | python | def _transform(self, df):
"""Private transform method of a Transformer. This serves as batch-prediction method for our purposes.
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label_col = self.getLabelCol()
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220,070 | maxpumperla/elephas | elephas/java/ndarray.py | _from_numpy | def _from_numpy(np_array):
"""
Convert numpy array to nd4j array
"""
# Convert the numpy array to nd4j context dtype
required_dtype = get_np_dtype(get_context_dtype())
if np_array.dtype != required_dtype:
raise Exception("{} is required, got {}".format(
repr(required_dtype),... | python | def _from_numpy(np_array):
"""
Convert numpy array to nd4j array
"""
# Convert the numpy array to nd4j context dtype
required_dtype = get_np_dtype(get_context_dtype())
if np_array.dtype != required_dtype:
raise Exception("{} is required, got {}".format(
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220,071 | maxpumperla/elephas | elephas/java/ndarray.py | _to_numpy | def _to_numpy(nd4j_array):
"""
Convert nd4j array to numpy array
"""
buff = nd4j_array.data()
address = buff.pointer().address()
dtype = get_context_dtype()
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p... | python | def _to_numpy(nd4j_array):
"""
Convert nd4j array to numpy array
"""
buff = nd4j_array.data()
address = buff.pointer().address()
dtype = get_context_dtype()
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220,072 | maxpumperla/elephas | elephas/utils/rwlock.py | RWLock.acquire_read | def acquire_read(self):
"""
Acquire a read lock. Several threads can hold this typeof lock.
It is exclusive with write locks.
"""
self.monitor.acquire()
while self.rwlock < 0 or self.writers_waiting:
self.readers_ok.wait()
self.rwlock += 1
self... | python | def acquire_read(self):
"""
Acquire a read lock. Several threads can hold this typeof lock.
It is exclusive with write locks.
"""
self.monitor.acquire()
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self.rwlock += 1
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220,073 | maxpumperla/elephas | elephas/utils/rwlock.py | RWLock.acquire_write | def acquire_write(self):
"""
Acquire a write lock. Only one thread can hold this lock, and
only when no read locks are also held.
"""
self.monitor.acquire()
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self.writers_waiting += 1
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"""
Acquire a write lock. Only one thread can hold this lock, and
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"""
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self.writers_waiting += 1
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220,074 | maxpumperla/elephas | elephas/utils/rwlock.py | RWLock.release | def release(self):
"""
Release a lock, whether read or write.
"""
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if self.rwlock < 0:
self.rwlock = 0
else:
self.rwlock -= 1
wake_writers = self.writers_waiting and self.rwlock == 0
wake_readers = self.writers... | python | def release(self):
"""
Release a lock, whether read or write.
"""
self.monitor.acquire()
if self.rwlock < 0:
self.rwlock = 0
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self.rwlock -= 1
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220,075 | maxpumperla/elephas | elephas/ml/adapter.py | to_data_frame | def to_data_frame(sc, features, labels, categorical=False):
"""Convert numpy arrays of features and labels into Spark DataFrame
"""
lp_rdd = to_labeled_point(sc, features, labels, categorical)
sql_context = SQLContext(sc)
df = sql_context.createDataFrame(lp_rdd)
return df | python | def to_data_frame(sc, features, labels, categorical=False):
"""Convert numpy arrays of features and labels into Spark DataFrame
"""
lp_rdd = to_labeled_point(sc, features, labels, categorical)
sql_context = SQLContext(sc)
df = sql_context.createDataFrame(lp_rdd)
return df | [
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220,076 | maxpumperla/elephas | elephas/ml/adapter.py | from_data_frame | def from_data_frame(df, categorical=False, nb_classes=None):
"""Convert DataFrame back to pair of numpy arrays
"""
lp_rdd = df.rdd.map(lambda row: LabeledPoint(row.label, row.features))
features, labels = from_labeled_point(lp_rdd, categorical, nb_classes)
return features, labels | python | def from_data_frame(df, categorical=False, nb_classes=None):
"""Convert DataFrame back to pair of numpy arrays
"""
lp_rdd = df.rdd.map(lambda row: LabeledPoint(row.label, row.features))
features, labels = from_labeled_point(lp_rdd, categorical, nb_classes)
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220,077 | maxpumperla/elephas | elephas/ml/adapter.py | df_to_simple_rdd | def df_to_simple_rdd(df, categorical=False, nb_classes=None, features_col='features', label_col='label'):
"""Convert DataFrame into RDD of pairs
"""
sql_context = df.sql_ctx
sql_context.registerDataFrameAsTable(df, "temp_table")
selected_df = sql_context.sql(
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"""Convert DataFrame into RDD of pairs
"""
sql_context = df.sql_ctx
sql_context.registerDataFrameAsTable(df, "temp_table")
selected_df = sql_context.sql(
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220,078 | maxpumperla/elephas | elephas/spark_model.py | SparkModel.fit | def fit(self, rdd, epochs=10, batch_size=32,
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"""
Train an elephas model on an RDD. The Keras model configuration as specified
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220,079 | maxpumperla/elephas | elephas/spark_model.py | SparkModel._fit | def _fit(self, rdd, epochs, batch_size, verbose, validation_split):
"""Protected train method to make wrapping of modes easier
"""
self._master_network.compile(optimizer=self.master_optimizer,
loss=self.master_loss,
metric... | python | def _fit(self, rdd, epochs, batch_size, verbose, validation_split):
"""Protected train method to make wrapping of modes easier
"""
self._master_network.compile(optimizer=self.master_optimizer,
loss=self.master_loss,
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220,080 | maxpumperla/elephas | elephas/spark_model.py | SparkMLlibModel.fit | def fit(self, labeled_points, epochs=10, batch_size=32, verbose=0, validation_split=0.1,
categorical=False, nb_classes=None):
"""Train an elephas model on an RDD of LabeledPoints
"""
rdd = lp_to_simple_rdd(labeled_points, categorical, nb_classes)
rdd = rdd.repartition(self.nu... | python | def fit(self, labeled_points, epochs=10, batch_size=32, verbose=0, validation_split=0.1,
categorical=False, nb_classes=None):
"""Train an elephas model on an RDD of LabeledPoints
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rdd = lp_to_simple_rdd(labeled_points, categorical, nb_classes)
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220,081 | maxpumperla/elephas | elephas/spark_model.py | SparkMLlibModel.predict | def predict(self, mllib_data):
"""Predict probabilities for an RDD of features
"""
if isinstance(mllib_data, pyspark.mllib.linalg.Matrix):
return to_matrix(self._master_network.predict(from_matrix(mllib_data)))
elif isinstance(mllib_data, pyspark.mllib.linalg.Vector):
... | python | def predict(self, mllib_data):
"""Predict probabilities for an RDD of features
"""
if isinstance(mllib_data, pyspark.mllib.linalg.Matrix):
return to_matrix(self._master_network.predict(from_matrix(mllib_data)))
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220,082 | maxpumperla/elephas | elephas/worker.py | SparkWorker.train | def train(self, data_iterator):
"""Train a keras model on a worker
"""
optimizer = get_optimizer(self.master_optimizer)
self.model = model_from_yaml(self.yaml, self.custom_objects)
self.model.compile(optimizer=optimizer,
loss=self.master_loss, metrics=s... | python | def train(self, data_iterator):
"""Train a keras model on a worker
"""
optimizer = get_optimizer(self.master_optimizer)
self.model = model_from_yaml(self.yaml, self.custom_objects)
self.model.compile(optimizer=optimizer,
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220,083 | maxpumperla/elephas | elephas/worker.py | AsynchronousSparkWorker.train | def train(self, data_iterator):
"""Train a keras model on a worker and send asynchronous updates
to parameter server
"""
feature_iterator, label_iterator = tee(data_iterator, 2)
x_train = np.asarray([x for x, y in feature_iterator])
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"""Train a keras model on a worker and send asynchronous updates
to parameter server
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feature_iterator, label_iterator = tee(data_iterator, 2)
x_train = np.asarray([x for x, y in feature_iterator])
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220,084 | maxpumperla/elephas | elephas/utils/sockets.py | determine_master | def determine_master(port=4000):
"""Determine address of master so that workers
can connect to it. If the environment variable
SPARK_LOCAL_IP is set, that address will be used.
:param port: port on which the application runs
:return: Master address
Example usage:
SPARK_LOCAL_IP=127.0.0... | python | def determine_master(port=4000):
"""Determine address of master so that workers
can connect to it. If the environment variable
SPARK_LOCAL_IP is set, that address will be used.
:param port: port on which the application runs
:return: Master address
Example usage:
SPARK_LOCAL_IP=127.0.0... | [
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220,085 | maxpumperla/elephas | elephas/utils/sockets.py | _receive_all | def _receive_all(socket, num_bytes):
"""Reads `num_bytes` bytes from the specified socket.
:param socket: open socket instance
:param num_bytes: number of bytes to read
:return: received data
"""
buffer = ''
buffer_size = 0
bytes_left = num_bytes
while buffer_size < num_bytes:
... | python | def _receive_all(socket, num_bytes):
"""Reads `num_bytes` bytes from the specified socket.
:param socket: open socket instance
:param num_bytes: number of bytes to read
:return: received data
"""
buffer = ''
buffer_size = 0
bytes_left = num_bytes
while buffer_size < num_bytes:
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220,086 | maxpumperla/elephas | elephas/utils/sockets.py | receive | def receive(socket, num_bytes=20):
"""Receive data frame from open socket.
:param socket: open socket instance
:param num_bytes: number of bytes to read
:return: received data
"""
length = int(_receive_all(socket, num_bytes).decode())
serialized_data = _receive_all(socket, length)
retu... | python | def receive(socket, num_bytes=20):
"""Receive data frame from open socket.
:param socket: open socket instance
:param num_bytes: number of bytes to read
:return: received data
"""
length = int(_receive_all(socket, num_bytes).decode())
serialized_data = _receive_all(socket, length)
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220,087 | maxpumperla/elephas | elephas/utils/sockets.py | send | def send(socket, data, num_bytes=20):
"""Send data to specified socket.
:param socket: open socket instance
:param data: data to send
:param num_bytes: number of bytes to read
:return: received data
"""
pickled_data = pickle.dumps(data, -1)
length = str(len(pickled_data)).zfill(num_by... | python | def send(socket, data, num_bytes=20):
"""Send data to specified socket.
:param socket: open socket instance
:param data: data to send
:param num_bytes: number of bytes to read
:return: received data
"""
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220,088 | maxpumperla/elephas | elephas/utils/rdd_utils.py | to_java_rdd | def to_java_rdd(jsc, features, labels, batch_size):
"""Convert numpy features and labels into a JavaRDD of
DL4J DataSet type.
:param jsc: JavaSparkContext from pyjnius
:param features: numpy array with features
:param labels: numpy array with labels:
:return: JavaRDD<DataSet>
"""
data_s... | python | def to_java_rdd(jsc, features, labels, batch_size):
"""Convert numpy features and labels into a JavaRDD of
DL4J DataSet type.
:param jsc: JavaSparkContext from pyjnius
:param features: numpy array with features
:param labels: numpy array with labels:
:return: JavaRDD<DataSet>
"""
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220,089 | maxpumperla/elephas | elephas/utils/rdd_utils.py | to_simple_rdd | def to_simple_rdd(sc, features, labels):
"""Convert numpy arrays of features and labels into
an RDD of pairs.
:param sc: Spark context
:param features: numpy array with features
:param labels: numpy array with labels
:return: Spark RDD with feature-label pairs
"""
pairs = [(x, y) for x,... | python | def to_simple_rdd(sc, features, labels):
"""Convert numpy arrays of features and labels into
an RDD of pairs.
:param sc: Spark context
:param features: numpy array with features
:param labels: numpy array with labels
:return: Spark RDD with feature-label pairs
"""
pairs = [(x, y) for x,... | [
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220,090 | maxpumperla/elephas | elephas/utils/rdd_utils.py | to_labeled_point | def to_labeled_point(sc, features, labels, categorical=False):
"""Convert numpy arrays of features and labels into
a LabeledPoint RDD for MLlib and ML integration.
:param sc: Spark context
:param features: numpy array with features
:param labels: numpy array with labels
:param categorical: bool... | python | def to_labeled_point(sc, features, labels, categorical=False):
"""Convert numpy arrays of features and labels into
a LabeledPoint RDD for MLlib and ML integration.
:param sc: Spark context
:param features: numpy array with features
:param labels: numpy array with labels
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220,091 | maxpumperla/elephas | elephas/utils/rdd_utils.py | from_labeled_point | def from_labeled_point(rdd, categorical=False, nb_classes=None):
"""Convert a LabeledPoint RDD back to a pair of numpy arrays
:param rdd: LabeledPoint RDD
:param categorical: boolean, if labels should be one-hot encode when returned
:param nb_classes: optional int, indicating the number of class labels... | python | def from_labeled_point(rdd, categorical=False, nb_classes=None):
"""Convert a LabeledPoint RDD back to a pair of numpy arrays
:param rdd: LabeledPoint RDD
:param categorical: boolean, if labels should be one-hot encode when returned
:param nb_classes: optional int, indicating the number of class labels... | [
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220,092 | maxpumperla/elephas | elephas/utils/rdd_utils.py | encode_label | def encode_label(label, nb_classes):
"""One-hot encoding of a single label
:param label: class label (int or double without floating point digits)
:param nb_classes: int, number of total classes
:return: one-hot encoded vector
"""
encoded = np.zeros(nb_classes)
encoded[int(label)] = 1.
... | python | def encode_label(label, nb_classes):
"""One-hot encoding of a single label
:param label: class label (int or double without floating point digits)
:param nb_classes: int, number of total classes
:return: one-hot encoded vector
"""
encoded = np.zeros(nb_classes)
encoded[int(label)] = 1.
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] | 84605acdc9564673c487637dcb27f5def128bcc7 | https://github.com/maxpumperla/elephas/blob/84605acdc9564673c487637dcb27f5def128bcc7/elephas/utils/rdd_utils.py#L92-L101 |
220,093 | maxpumperla/elephas | elephas/utils/rdd_utils.py | lp_to_simple_rdd | def lp_to_simple_rdd(lp_rdd, categorical=False, nb_classes=None):
"""Convert a LabeledPoint RDD into an RDD of feature-label pairs
:param lp_rdd: LabeledPoint RDD of features and labels
:param categorical: boolean, if labels should be one-hot encode when returned
:param nb_classes: int, number of total... | python | def lp_to_simple_rdd(lp_rdd, categorical=False, nb_classes=None):
"""Convert a LabeledPoint RDD into an RDD of feature-label pairs
:param lp_rdd: LabeledPoint RDD of features and labels
:param categorical: boolean, if labels should be one-hot encode when returned
:param nb_classes: int, number of total... | [
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:param nb_classes: int, number of total classes
:return: Spark RDD with feature-label pairs | [
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220,094 | lebinh/ngxtop | ngxtop/ngxtop.py | follow | def follow(the_file):
"""
Follow a given file and yield new lines when they are available, like `tail -f`.
"""
with open(the_file) as f:
f.seek(0, 2) # seek to eof
while True:
line = f.readline()
if not line:
time.sleep(0.1) # sleep briefly befor... | python | def follow(the_file):
"""
Follow a given file and yield new lines when they are available, like `tail -f`.
"""
with open(the_file) as f:
f.seek(0, 2) # seek to eof
while True:
line = f.readline()
if not line:
time.sleep(0.1) # sleep briefly befor... | [
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220,095 | lebinh/ngxtop | ngxtop/ngxtop.py | map_field | def map_field(field, func, dict_sequence):
"""
Apply given function to value of given key in every dictionary in sequence and
set the result as new value for that key.
"""
for item in dict_sequence:
try:
item[field] = func(item.get(field, None))
yield item
exc... | python | def map_field(field, func, dict_sequence):
"""
Apply given function to value of given key in every dictionary in sequence and
set the result as new value for that key.
"""
for item in dict_sequence:
try:
item[field] = func(item.get(field, None))
yield item
exc... | [
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220,096 | lebinh/ngxtop | ngxtop/ngxtop.py | add_field | def add_field(field, func, dict_sequence):
"""
Apply given function to the record and store result in given field of current record.
Do nothing if record already contains given field.
"""
for item in dict_sequence:
if field not in item:
item[field] = func(item)
yield item | python | def add_field(field, func, dict_sequence):
"""
Apply given function to the record and store result in given field of current record.
Do nothing if record already contains given field.
"""
for item in dict_sequence:
if field not in item:
item[field] = func(item)
yield item | [
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220,097 | dedupeio/dedupe | dedupe/canonical.py | getCanonicalRep | def getCanonicalRep(record_cluster):
"""
Given a list of records within a duplicate cluster, constructs a
canonical representation of the cluster by finding canonical
values for each field
"""
canonical_rep = {}
keys = record_cluster[0].keys()
for key in keys:
key_values = []
... | python | def getCanonicalRep(record_cluster):
"""
Given a list of records within a duplicate cluster, constructs a
canonical representation of the cluster by finding canonical
values for each field
"""
canonical_rep = {}
keys = record_cluster[0].keys()
for key in keys:
key_values = []
... | [
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220,098 | dedupeio/dedupe | dedupe/predicates.py | nearIntegersPredicate | def nearIntegersPredicate(field):
"""return any integers N, N+1, and N-1"""
ints = integers(field)
near_ints = set()
for char in ints:
num = int(char)
near_ints.add(str(num - 1))
near_ints.add(str(num))
near_ints.add(str(num + 1))
return near_ints | python | def nearIntegersPredicate(field):
"""return any integers N, N+1, and N-1"""
ints = integers(field)
near_ints = set()
for char in ints:
num = int(char)
near_ints.add(str(num - 1))
near_ints.add(str(num))
near_ints.add(str(num + 1))
return near_ints | [
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220,099 | dedupeio/dedupe | dedupe/core.py | randomPairsMatch | def randomPairsMatch(n_records_A, n_records_B, sample_size):
"""
Return random combinations of indices for record list A and B
"""
n = int(n_records_A * n_records_B)
if sample_size >= n:
random_pairs = numpy.arange(n)
else:
random_pairs = numpy.array(random.sample(range(n), samp... | python | def randomPairsMatch(n_records_A, n_records_B, sample_size):
"""
Return random combinations of indices for record list A and B
"""
n = int(n_records_A * n_records_B)
if sample_size >= n:
random_pairs = numpy.arange(n)
else:
random_pairs = numpy.array(random.sample(range(n), samp... | [
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