repo stringlengths 7 54 | path stringlengths 4 223 | func_name stringlengths 1 134 | original_string stringlengths 75 104k | language stringclasses 1
value | code stringlengths 75 104k | code_tokens listlengths 20 28.4k | docstring stringlengths 1 46.3k | docstring_tokens listlengths 1 1.66k | sha stringlengths 40 40 | url stringlengths 87 315 | partition stringclasses 1
value | summary stringlengths 4 350 | obf_code stringlengths 7.85k 764k |
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prometheus/client_python | prometheus_client/exposition.py | make_wsgi_app | def make_wsgi_app(registry=REGISTRY):
"""Create a WSGI app which serves the metrics from a registry."""
def prometheus_app(environ, start_response):
params = parse_qs(environ.get('QUERY_STRING', ''))
r = registry
encoder, content_type = choose_encoder(environ.get('HTTP_ACCEPT'))
... | python | def make_wsgi_app(registry=REGISTRY):
"""Create a WSGI app which serves the metrics from a registry."""
def prometheus_app(environ, start_response):
params = parse_qs(environ.get('QUERY_STRING', ''))
r = registry
encoder, content_type = choose_encoder(environ.get('HTTP_ACCEPT'))
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prometheus/client_python | prometheus_client/exposition.py | start_wsgi_server | def start_wsgi_server(port, addr='', registry=REGISTRY):
"""Starts a WSGI server for prometheus metrics as a daemon thread."""
app = make_wsgi_app(registry)
httpd = make_server(addr, port, app, handler_class=_SilentHandler)
t = threading.Thread(target=httpd.serve_forever)
t.daemon = True
t.start... | python | def start_wsgi_server(port, addr='', registry=REGISTRY):
"""Starts a WSGI server for prometheus metrics as a daemon thread."""
app = make_wsgi_app(registry)
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prometheus/client_python | prometheus_client/exposition.py | start_http_server | def start_http_server(port, addr='', registry=REGISTRY):
"""Starts an HTTP server for prometheus metrics as a daemon thread"""
CustomMetricsHandler = MetricsHandler.factory(registry)
httpd = _ThreadingSimpleServer((addr, port), CustomMetricsHandler)
t = threading.Thread(target=httpd.serve_forever)
t... | python | def start_http_server(port, addr='', registry=REGISTRY):
"""Starts an HTTP server for prometheus metrics as a daemon thread"""
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httpd = _ThreadingSimpleServer((addr, port), CustomMetricsHandler)
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prometheus/client_python | prometheus_client/exposition.py | write_to_textfile | def write_to_textfile(path, registry):
"""Write metrics to the given path.
This is intended for use with the Node exporter textfile collector.
The path must end in .prom for the textfile collector to process it."""
tmppath = '%s.%s.%s' % (path, os.getpid(), threading.current_thread().ident)
with op... | python | def write_to_textfile(path, registry):
"""Write metrics to the given path.
This is intended for use with the Node exporter textfile collector.
The path must end in .prom for the textfile collector to process it."""
tmppath = '%s.%s.%s' % (path, os.getpid(), threading.current_thread().ident)
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prometheus/client_python | prometheus_client/exposition.py | default_handler | def default_handler(url, method, timeout, headers, data):
"""Default handler that implements HTTP/HTTPS connections.
Used by the push_to_gateway functions. Can be re-used by other handlers."""
def handle():
request = Request(url, data=data)
request.get_method = lambda: method
for k... | python | def default_handler(url, method, timeout, headers, data):
"""Default handler that implements HTTP/HTTPS connections.
Used by the push_to_gateway functions. Can be re-used by other handlers."""
def handle():
request = Request(url, data=data)
request.get_method = lambda: method
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prometheus/client_python | prometheus_client/exposition.py | basic_auth_handler | def basic_auth_handler(url, method, timeout, headers, data, username=None, password=None):
"""Handler that implements HTTP/HTTPS connections with Basic Auth.
Sets auth headers using supplied 'username' and 'password', if set.
Used by the push_to_gateway functions. Can be re-used by other handlers."""
... | python | def basic_auth_handler(url, method, timeout, headers, data, username=None, password=None):
"""Handler that implements HTTP/HTTPS connections with Basic Auth.
Sets auth headers using supplied 'username' and 'password', if set.
Used by the push_to_gateway functions. Can be re-used by other handlers."""
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prometheus/client_python | prometheus_client/exposition.py | push_to_gateway | def push_to_gateway(
gateway, job, registry, grouping_key=None, timeout=30,
handler=default_handler):
"""Push metrics to the given pushgateway.
`gateway` the url for your push gateway. Either of the form
'http://pushgateway.local', or 'pushgateway.local'.
Scheme defa... | python | def push_to_gateway(
gateway, job, registry, grouping_key=None, timeout=30,
handler=default_handler):
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`gateway` the url for your push gateway. Either of the form
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prometheus/client_python | prometheus_client/exposition.py | delete_from_gateway | def delete_from_gateway(
gateway, job, grouping_key=None, timeout=30, handler=default_handler):
"""Delete metrics from the given pushgateway.
`gateway` the url for your push gateway. Either of the form
'http://pushgateway.local', or 'pushgateway.local'.
Scheme defaults to 'h... | python | def delete_from_gateway(
gateway, job, grouping_key=None, timeout=30, handler=default_handler):
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prometheus/client_python | prometheus_client/exposition.py | instance_ip_grouping_key | def instance_ip_grouping_key():
"""Grouping key with instance set to the IP Address of this host."""
with closing(socket.socket(socket.AF_INET, socket.SOCK_DGRAM)) as s:
s.connect(('localhost', 0))
return {'instance': s.getsockname()[0]} | python | def instance_ip_grouping_key():
"""Grouping key with instance set to the IP Address of this host."""
with closing(socket.socket(socket.AF_INET, socket.SOCK_DGRAM)) as s:
s.connect(('localhost', 0))
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prometheus/client_python | prometheus_client/exposition.py | MetricsHandler.factory | def factory(cls, registry):
"""Returns a dynamic MetricsHandler class tied
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"""
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# As we have unicode_literals, we need to create a str()
... | python | def factory(cls, registry):
"""Returns a dynamic MetricsHandler class tied
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"""
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prometheus/client_python | prometheus_client/openmetrics/parser.py | text_fd_to_metric_families | def text_fd_to_metric_families(fd):
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Yields Metric's.
"""
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"""Parse Prometheus text format from a file descriptor.
This is a laxer parser than the main Go parser,
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Yields Metric's.
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prometheus/client_python | prometheus_client/registry.py | CollectorRegistry.register | def register(self, collector):
"""Add a collector to the registry."""
with self._lock:
names = self._get_names(collector)
duplicates = set(self._names_to_collectors).intersection(names)
if duplicates:
raise ValueError(
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"""Add a collector to the registry."""
with self._lock:
names = self._get_names(collector)
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prometheus/client_python | prometheus_client/registry.py | CollectorRegistry.unregister | def unregister(self, collector):
"""Remove a collector from the registry."""
with self._lock:
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del self._names_to_collectors[name]
del self._collector_to_names[collector] | python | def unregister(self, collector):
"""Remove a collector from the registry."""
with self._lock:
for name in self._collector_to_names[collector]:
del self._names_to_collectors[name]
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prometheus/client_python | prometheus_client/registry.py | CollectorRegistry._get_names | def _get_names(self, collector):
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desc_func = None
# If there's a describe function, use it.
try:
desc_func = collector.describe
except AttributeError:
pass
# Otherwise, if auto describe is enabl... | python | def _get_names(self, collector):
"""Get names of timeseries the collector produces."""
desc_func = None
# If there's a describe function, use it.
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desc_func = collector.describe
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prometheus/client_python | prometheus_client/registry.py | CollectorRegistry.collect | def collect(self):
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yield metric | python | def collect(self):
"""Yields metrics from the collectors in the registry."""
collectors = None
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prometheus/client_python | prometheus_client/registry.py | CollectorRegistry.restricted_registry | def restricted_registry(self, names):
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Returns an object which upon collect() will return
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generate_latest(REGISTRY.restricted_registry(['a_timeseries']))
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"""Returns object that only collects some metrics.
Returns an object which upon collect() will return
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prometheus/client_python | prometheus_client/registry.py | CollectorRegistry.get_sample_value | def get_sample_value(self, name, labels=None):
"""Returns the sample value, or None if not found.
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if labels is None:
labels = {}
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for s in metric.samples:
... | python | def get_sample_value(self, name, labels=None):
"""Returns the sample value, or None if not found.
This is inefficient, and intended only for use in unittests.
"""
if labels is None:
labels = {}
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prometheus/client_python | prometheus_client/multiprocess.py | mark_process_dead | def mark_process_dead(pid, path=None):
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for f in glob.glob(os.path.join(path, 'gauge_livesum_{0}.db'.format(pid))):
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for f in glob.glob(o... | python | def mark_process_dead(pid, path=None):
"""Do bookkeeping for when one process dies in a multi-process setup."""
if path is None:
path = os.environ.get('prometheus_multiproc_dir')
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prometheus/client_python | prometheus_client/multiprocess.py | MultiProcessCollector.merge | def merge(files, accumulate=True):
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But if writing the merged data back to mmap files, use
accumulate=False to avoid compound accumulation.
"""
metrics = {}
... | python | def merge(files, accumulate=True):
"""Merge metrics from given mmap files.
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metrics = {}
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prometheus/client_python | prometheus_client/decorator.py | getargspec | def getargspec(f):
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spec = getfullargspec(f)
return ArgSpec(spec.args, spec.varargs, spec.varkw, spec.defaults) | python | def getargspec(f):
"""A replacement for inspect.getargspec"""
spec = getfullargspec(f)
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prometheus/client_python | prometheus_client/decorator.py | decorate | def decorate(func, caller):
"""
decorate(func, caller) decorates a function using a caller.
"""
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prometheus/client_python | prometheus_client/parser.py | text_fd_to_metric_families | def text_fd_to_metric_families(fd):
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prometheus/client_python | prometheus_client/mmap_dict.py | mmap_key | def mmap_key(metric_name, name, labelnames, labelvalues):
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prometheus/client_python | prometheus_client/mmap_dict.py | MmapedDict._init_value | def _init_value(self, key):
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prometheus/client_python | prometheus_client/mmap_dict.py | MmapedDict._read_all_values | def _read_all_values(self):
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prometheus/client_python | prometheus_client/metrics.py | MetricWrapperBase.labels | def labels(self, *labelvalues, **labelkwargs):
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prometheus/client_python | prometheus_client/metrics.py | MetricWrapperBase.remove | def remove(self, *labelvalues):
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prometheus/client_python | prometheus_client/metrics.py | Gauge.set_function | def set_function(self, f):
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prometheus/client_python | prometheus_client/metrics.py | Summary.observe | def observe(self, amount):
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prometheus/client_python | prometheus_client/metrics.py | Histogram.observe | def observe(self, amount):
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"""Set info metric."""
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rmax/scrapy-redis | src/scrapy_redis/dupefilter.py | RFPDupeFilter.from_settings | def from_settings(cls, settings):
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rmax/scrapy-redis | src/scrapy_redis/dupefilter.py | RFPDupeFilter.request_seen | def request_seen(self, request):
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Returns
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bool
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"""Returns True if request was already seen.
Parameters
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request : scrapy.http.Request
Returns
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bool
"""
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rmax/scrapy-redis | src/scrapy_redis/dupefilter.py | RFPDupeFilter.log | def log(self, request, spider):
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request : scrapy.http.Request
spider : scrapy.spiders.Spider
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"""Logs given request.
Parameters
----------
request : scrapy.http.Request
spider : scrapy.spiders.Spider
"""
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rmax/scrapy-redis | example-project/process_items.py | process_items | def process_items(r, keys, timeout, limit=0, log_every=1000, wait=.1):
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r : Redis
Redis connection instance.
keys : list
List of keys to read the items from.
timeout: int
Read timeout.
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r : Redis
Redis connection instance.
keys : list
List of keys to read the items from.
timeout: int
Read timeout.
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rmax/scrapy-redis | src/scrapy_redis/connection.py | get_redis_from_settings | def get_redis_from_settings(settings):
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rmax/scrapy-redis | src/scrapy_redis/connection.py | get_redis | def get_redis(**kwargs):
"""Returns a redis client instance.
Parameters
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redis_cls : class, optional
Defaults to ``redis.StrictRedis``.
url : str, optional
If given, ``redis_cls.from_url`` is used to instantiate the class.
**kwargs
Extra parameters to be passed... | python | def get_redis(**kwargs):
"""Returns a redis client instance.
Parameters
----------
redis_cls : class, optional
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url : str, optional
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rmax/scrapy-redis | src/scrapy_redis/utils.py | bytes_to_str | def bytes_to_str(s, encoding='utf-8'):
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if six.PY3 and isinstance(s, bytes):
return s.decode(encoding)
return s | python | def bytes_to_str(s, encoding='utf-8'):
"""Returns a str if a bytes object is given."""
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return s.decode(encoding)
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rmax/scrapy-redis | src/scrapy_redis/spiders.py | RedisMixin.setup_redis | def setup_redis(self, crawler=None):
"""Setup redis connection and idle signal.
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"""
if self.server is not None:
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# We allow optional crawler argument to keep bac... | python | def setup_redis(self, crawler=None):
"""Setup redis connection and idle signal.
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rmax/scrapy-redis | src/scrapy_redis/spiders.py | RedisMixin.next_requests | def next_requests(self):
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fetch_one = self.server.spop if use_set else self.server.lpop
# XXX: Do we need to use a timeout here?
found = 0
... | python | def next_requests(self):
"""Returns a request to be scheduled or none."""
use_set = self.settings.getbool('REDIS_START_URLS_AS_SET', defaults.START_URLS_AS_SET)
fetch_one = self.server.spop if use_set else self.server.lpop
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"""Returns a Request instance from data coming from Redis.
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rmax/scrapy-redis | src/scrapy_redis/spiders.py | RedisMixin.schedule_next_requests | def schedule_next_requests(self):
"""Schedules a request if available"""
# TODO: While there is capacity, schedule a batch of redis requests.
for req in self.next_requests():
self.crawler.engine.crawl(req, spider=self) | python | def schedule_next_requests(self):
"""Schedules a request if available"""
# TODO: While there is capacity, schedule a batch of redis requests.
for req in self.next_requests():
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rmax/scrapy-redis | src/scrapy_redis/queue.py | Base._encode_request | def _encode_request(self, request):
"""Encode a request object"""
obj = request_to_dict(request, self.spider)
return self.serializer.dumps(obj) | python | def _encode_request(self, request):
"""Encode a request object"""
obj = request_to_dict(request, self.spider)
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rmax/scrapy-redis | src/scrapy_redis/queue.py | Base._decode_request | def _decode_request(self, encoded_request):
"""Decode an request previously encoded"""
obj = self.serializer.loads(encoded_request)
return request_from_dict(obj, self.spider) | python | def _decode_request(self, encoded_request):
"""Decode an request previously encoded"""
obj = self.serializer.loads(encoded_request)
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rmax/scrapy-redis | src/scrapy_redis/queue.py | FifoQueue.push | def push(self, request):
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rmax/scrapy-redis | src/scrapy_redis/queue.py | PriorityQueue.push | def push(self, request):
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rmax/scrapy-redis | src/scrapy_redis/queue.py | PriorityQueue.pop | def pop(self, timeout=0):
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Pop a request
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# use atomic range/remove using multi/exec
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pipe.multi()
pipe.zrange(self.key, 0, 0).zremrangebyrank(self.key, 0, 0)
results, count... | python | def pop(self, timeout=0):
"""
Pop a request
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b-ryan/powerline-shell | powerline_shell/colortrans.py | rgb2short | def rgb2short(r, g, b):
""" Find the closest xterm-256 approximation to the given RGB value.
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>>> rgb2short(255, 255, 255)
... | python | def rgb2short(r, g, b):
""" Find the closest xterm-256 approximation to the given RGB value.
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b-ryan/powerline-shell | powerline_shell/segments/cwd.py | maybe_shorten_name | def maybe_shorten_name(powerline, name):
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Brutally simple email address validation. Note unlike most email address validation
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* "John Doe <local_part@domain.com>" style "pretty" email addresses are processed
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"""
Brutally simple email address validation. Note unlike most email address validation
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port: str = None,
name: str = None,
query: Dict[str, Any] = None,
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Create a DSN from from connection settings.
Stolen approximately from sqlalchemy/engine/url.py:URL.
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password: str = None,
host: str = None,
port: str = None,
name: str = None,
query: Dict[str, Any] = None,
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"""
Stolen approximately from django. Import a dotted module path and return the attribute/class designated by the
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"""
try:
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samuelcolvin/pydantic | pydantic/utils.py | truncate | def truncate(v: str, *, max_len: int = 80) -> str:
"""
Truncate a value and add a unicode ellipsis (three dots) to the end if it was too long
"""
if isinstance(v, str) and len(v) > (max_len - 2):
# -3 so quote + string + … + quote has correct length
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Truncate a value and add a unicode ellipsis (three dots) to the end if it was too long
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samuelcolvin/pydantic | pydantic/utils.py | validate_field_name | def validate_field_name(bases: List[Type['BaseModel']], field_name: str) -> None:
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Ensure that the field's name does not shadow an existing attribute of the model.
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Ensure that the field's name does not shadow an existing attribute of the model.
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samuelcolvin/pydantic | pydantic/utils.py | url_regex_generator | def url_regex_generator(*, relative: bool, require_tld: bool) -> Pattern[str]:
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samuelcolvin/pydantic | pydantic/utils.py | resolve_annotations | def resolve_annotations(raw_annotations: Dict[str, AnyType], module_name: Optional[str]) -> Dict[str, AnyType]:
"""
Partially taken from typing.get_type_hints.
Resolve string or ForwardRef annotations into type objects if possible.
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Resolve string or ForwardRef annotations into type objects if possible.
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samuelcolvin/pydantic | pydantic/utils.py | update_field_forward_refs | def update_field_forward_refs(field: 'Field', globalns: Any, localns: Any) -> None:
"""
Try to update ForwardRefs on fields based on this Field, globalns and localns.
"""
if type(field.type_) == ForwardRef:
field.type_ = field.type_._evaluate(globalns, localns or None) # type: ignore
fi... | python | def update_field_forward_refs(field: 'Field', globalns: Any, localns: Any) -> None:
"""
Try to update ForwardRefs on fields based on this Field, globalns and localns.
"""
if type(field.type_) == ForwardRef:
field.type_ = field.type_._evaluate(globalns, localns or None) # type: ignore
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samuelcolvin/pydantic | pydantic/validators.py | ip_v4_network_validator | def ip_v4_network_validator(v: Any) -> IPv4Network:
"""
Assume IPv4Network initialised with a default ``strict`` argument
See more:
https://docs.python.org/library/ipaddress.html#ipaddress.IPv4Network
"""
if isinstance(v, IPv4Network):
return v
with change_exception(errors.IPv4Netw... | python | def ip_v4_network_validator(v: Any) -> IPv4Network:
"""
Assume IPv4Network initialised with a default ``strict`` argument
See more:
https://docs.python.org/library/ipaddress.html#ipaddress.IPv4Network
"""
if isinstance(v, IPv4Network):
return v
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samuelcolvin/pydantic | pydantic/validators.py | ip_v6_network_validator | def ip_v6_network_validator(v: Any) -> IPv6Network:
"""
Assume IPv6Network initialised with a default ``strict`` argument
See more:
https://docs.python.org/library/ipaddress.html#ipaddress.IPv6Network
"""
if isinstance(v, IPv6Network):
return v
with change_exception(errors.IPv6Netw... | python | def ip_v6_network_validator(v: Any) -> IPv6Network:
"""
Assume IPv6Network initialised with a default ``strict`` argument
See more:
https://docs.python.org/library/ipaddress.html#ipaddress.IPv6Network
"""
if isinstance(v, IPv6Network):
return v
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samuelcolvin/pydantic | pydantic/validators.py | callable_validator | def callable_validator(v: Any) -> AnyCallable:
"""
Perform a simple check if the value is callable.
Note: complete matching of argument type hints and return types is not performed
"""
if callable(v):
return v
raise errors.CallableError(value=v) | python | def callable_validator(v: Any) -> AnyCallable:
"""
Perform a simple check if the value is callable.
Note: complete matching of argument type hints and return types is not performed
"""
if callable(v):
return v
raise errors.CallableError(value=v) | [
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samuelcolvin/pydantic | pydantic/env_settings.py | BaseSettings._build_environ | def _build_environ(self) -> Dict[str, Optional[str]]:
"""
Build environment variables suitable for passing to the Model.
"""
d: Dict[str, Optional[str]] = {}
if self.__config__.case_insensitive:
env_vars = {k.lower(): v for k, v in os.environ.items()}
else:
... | python | def _build_environ(self) -> Dict[str, Optional[str]]:
"""
Build environment variables suitable for passing to the Model.
"""
d: Dict[str, Optional[str]] = {}
if self.__config__.case_insensitive:
env_vars = {k.lower(): v for k, v in os.environ.items()}
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samuelcolvin/pydantic | pydantic/class_validators.py | validator | def validator(
*fields: str, pre: bool = False, whole: bool = False, always: bool = False, check_fields: bool = True
) -> Callable[[AnyCallable], classmethod]:
"""
Decorate methods on the class indicating that they should be used to validate fields
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*fields: str, pre: bool = False, whole: bool = False, always: bool = False, check_fields: bool = True
) -> Callable[[AnyCallable], classmethod]:
"""
Decorate methods on the class indicating that they should be used to validate fields
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samuelcolvin/pydantic | pydantic/class_validators.py | make_generic_validator | def make_generic_validator(validator: AnyCallable) -> 'ValidatorCallable':
"""
Make a generic function which calls a validator with the right arguments.
Unfortunately other approaches (eg. return a partial of a function that builds the arguments) is slow,
hence this laborious way of doing things.
... | python | def make_generic_validator(validator: AnyCallable) -> 'ValidatorCallable':
"""
Make a generic function which calls a validator with the right arguments.
Unfortunately other approaches (eg. return a partial of a function that builds the arguments) is slow,
hence this laborious way of doing things.
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samuelcolvin/pydantic | pydantic/fields.py | Field._validate_sequence_like | def _validate_sequence_like(
self, v: Any, values: Dict[str, Any], loc: 'LocType', cls: Optional['ModelOrDc']
) -> 'ValidateReturn':
"""
Validate sequence-like containers: lists, tuples, sets and generators
"""
if not sequence_like(v):
e: errors_.PydanticTypeErro... | python | def _validate_sequence_like(
self, v: Any, values: Dict[str, Any], loc: 'LocType', cls: Optional['ModelOrDc']
) -> 'ValidateReturn':
"""
Validate sequence-like containers: lists, tuples, sets and generators
"""
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samuelcolvin/pydantic | pydantic/fields.py | Field.is_complex | def is_complex(self) -> bool:
"""
Whether the field is "complex" eg. env variables should be parsed as JSON.
"""
from .main import BaseModel # noqa: F811
return (
self.shape != Shape.SINGLETON
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"""
Whether the field is "complex" eg. env variables should be parsed as JSON.
"""
from .main import BaseModel # noqa: F811
return (
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samuelcolvin/pydantic | pydantic/schema.py | schema | def schema(
models: Sequence[Type['main.BaseModel']],
*,
by_alias: bool = True,
title: Optional[str] = None,
description: Optional[str] = None,
ref_prefix: Optional[str] = None,
) -> Dict[str, Any]:
"""
Process a list of models and generate a single JSON Schema with all of them defined i... | python | def schema(
models: Sequence[Type['main.BaseModel']],
*,
by_alias: bool = True,
title: Optional[str] = None,
description: Optional[str] = None,
ref_prefix: Optional[str] = None,
) -> Dict[str, Any]:
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samuelcolvin/pydantic | pydantic/schema.py | model_schema | def model_schema(
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"""
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samuelcolvin/pydantic | pydantic/schema.py | field_schema | def field_schema(
field: Field,
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ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
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samuelcolvin/pydantic | pydantic/schema.py | get_field_schema_validations | def get_field_schema_validations(field: Field) -> Dict[str, Any]:
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"""
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f_schema: Dict[str, Any] = {}
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samuelcolvin/pydantic | pydantic/schema.py | get_model_name_map | def get_model_name_map(unique_models: Set[Type['main.BaseModel']]) -> Dict[Type['main.BaseModel'], str]:
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samuelcolvin/pydantic | pydantic/schema.py | get_flat_models_from_model | def get_flat_models_from_model(model: Type['main.BaseModel']) -> Set[Type['main.BaseModel']]:
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samuelcolvin/pydantic | pydantic/schema.py | get_flat_models_from_fields | def get_flat_models_from_fields(fields: Sequence[Field]) -> Set[Type['main.BaseModel']]:
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samuelcolvin/pydantic | pydantic/schema.py | get_flat_models_from_models | def get_flat_models_from_models(models: Sequence[Type['main.BaseModel']]) -> Set[Type['main.BaseModel']]:
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samuelcolvin/pydantic | pydantic/schema.py | field_type_schema | def field_type_schema(
field: Field,
*,
by_alias: bool,
model_name_map: Dict[Type['main.BaseModel'], str],
schema_overrides: bool = False,
ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
"""
Used by ``field_schema()``, you probably should be using that funct... | python | def field_type_schema(
field: Field,
*,
by_alias: bool,
model_name_map: Dict[Type['main.BaseModel'], str],
schema_overrides: bool = False,
ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
"""
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samuelcolvin/pydantic | pydantic/schema.py | model_process_schema | def model_process_schema(
model: Type['main.BaseModel'],
*,
by_alias: bool = True,
model_name_map: Dict[Type['main.BaseModel'], str],
ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
"""
Used by ``model_schema()``, you probably should be using that function.
... | python | def model_process_schema(
model: Type['main.BaseModel'],
*,
by_alias: bool = True,
model_name_map: Dict[Type['main.BaseModel'], str],
ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
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samuelcolvin/pydantic | pydantic/schema.py | model_type_schema | def model_type_schema(
model: Type['main.BaseModel'],
*,
by_alias: bool,
model_name_map: Dict[Type['main.BaseModel'], str],
ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
"""
You probably should be using ``model_schema()``, this function is indirectly used by t... | python | def model_type_schema(
model: Type['main.BaseModel'],
*,
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ref_prefix: Optional[str] = None,
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samuelcolvin/pydantic | pydantic/schema.py | field_singleton_sub_fields_schema | def field_singleton_sub_fields_schema(
sub_fields: Sequence[Field],
*,
by_alias: bool,
model_name_map: Dict[Type['main.BaseModel'], str],
schema_overrides: bool = False,
ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
"""
This function is indirectly used by ... | python | def field_singleton_sub_fields_schema(
sub_fields: Sequence[Field],
*,
by_alias: bool,
model_name_map: Dict[Type['main.BaseModel'], str],
schema_overrides: bool = False,
ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
"""
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samuelcolvin/pydantic | pydantic/schema.py | field_singleton_schema | def field_singleton_schema( # noqa: C901 (ignore complexity)
field: Field,
*,
by_alias: bool,
model_name_map: Dict[Type['main.BaseModel'], str],
schema_overrides: bool = False,
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"""
This function is indirectly ... | python | def field_singleton_schema( # noqa: C901 (ignore complexity)
field: Field,
*,
by_alias: bool,
model_name_map: Dict[Type['main.BaseModel'], str],
schema_overrides: bool = False,
ref_prefix: Optional[str] = None,
) -> Tuple[Dict[str, Any], Dict[str, Any]]:
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samuelcolvin/pydantic | pydantic/schema.py | get_annotation_from_schema | def get_annotation_from_schema(annotation: Any, schema: Schema) -> Type[Any]:
"""
Get an annotation with validation implemented for numbers and strings based on the schema.
:param annotation: an annotation from a field specification, as ``str``, ``ConstrainedStr``
:param schema: an instance of Schema, ... | python | def get_annotation_from_schema(annotation: Any, schema: Schema) -> Type[Any]:
"""
Get an annotation with validation implemented for numbers and strings based on the schema.
:param annotation: an annotation from a field specification, as ``str``, ``ConstrainedStr``
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samuelcolvin/pydantic | pydantic/main.py | create_model | def create_model( # noqa: C901 (ignore complexity)
model_name: str,
*,
__config__: Type[BaseConfig] = None,
__base__: Type[BaseModel] = None,
__module__: Optional[str] = None,
__validators__: Dict[str, classmethod] = None,
**field_definitions: Any,
) -> BaseModel:
"""
Dynamically cr... | python | def create_model( # noqa: C901 (ignore complexity)
model_name: str,
*,
__config__: Type[BaseConfig] = None,
__base__: Type[BaseModel] = None,
__module__: Optional[str] = None,
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samuelcolvin/pydantic | pydantic/main.py | validate_model | def validate_model( # noqa: C901 (ignore complexity)
model: Union[BaseModel, Type[BaseModel]], input_data: 'DictStrAny', raise_exc: bool = True, cls: 'ModelOrDc' = None
) -> Union['DictStrAny', Tuple['DictStrAny', Optional[ValidationError]]]:
"""
validate data against a model.
"""
values = {}
e... | python | def validate_model( # noqa: C901 (ignore complexity)
model: Union[BaseModel, Type[BaseModel]], input_data: 'DictStrAny', raise_exc: bool = True, cls: 'ModelOrDc' = None
) -> Union['DictStrAny', Tuple['DictStrAny', Optional[ValidationError]]]:
"""
validate data against a model.
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values = {}
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samuelcolvin/pydantic | pydantic/main.py | BaseModel.dict | def dict(
self, *, include: 'SetStr' = None, exclude: 'SetStr' = None, by_alias: bool = False, skip_defaults: bool = False
) -> 'DictStrAny':
"""
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
"""
get_key = self._g... | python | def dict(
self, *, include: 'SetStr' = None, exclude: 'SetStr' = None, by_alias: bool = False, skip_defaults: bool = False
) -> 'DictStrAny':
"""
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
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samuelcolvin/pydantic | pydantic/main.py | BaseModel.json | def json(
self,
*,
include: 'SetStr' = None,
exclude: 'SetStr' = None,
by_alias: bool = False,
skip_defaults: bool = False,
encoder: Optional[Callable[[Any], Any]] = None,
**dumps_kwargs: Any,
) -> str:
"""
Generate a JSON representatio... | python | def json(
self,
*,
include: 'SetStr' = None,
exclude: 'SetStr' = None,
by_alias: bool = False,
skip_defaults: bool = False,
encoder: Optional[Callable[[Any], Any]] = None,
**dumps_kwargs: Any,
) -> str:
"""
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samuelcolvin/pydantic | pydantic/main.py | BaseModel.construct | def construct(cls: Type['Model'], values: 'DictAny', fields_set: 'SetStr') -> 'Model':
"""
Creates a new model and set __values__ without any validation, thus values should already be trusted.
Chances are you don't want to use this method directly.
"""
m = cls.__new__(cls)
... | python | def construct(cls: Type['Model'], values: 'DictAny', fields_set: 'SetStr') -> 'Model':
"""
Creates a new model and set __values__ without any validation, thus values should already be trusted.
Chances are you don't want to use this method directly.
"""
m = cls.__new__(cls)
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samuelcolvin/pydantic | pydantic/main.py | BaseModel.copy | def copy(
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include: 'SetStr' = None,
exclude: 'SetStr' = None,
update: 'DictStrAny' = None,
deep: bool = False,
) -> 'Model':
"""
Duplicate a model, optionally choose which fields to include, exclude and change.
:param include... | python | def copy(
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exclude: 'SetStr' = None,
update: 'DictStrAny' = None,
deep: bool = False,
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samuelcolvin/pydantic | pydantic/main.py | BaseModel.update_forward_refs | def update_forward_refs(cls, **localns: Any) -> None:
"""
Try to update ForwardRefs on fields based on this Model, globalns and localns.
"""
globalns = sys.modules[cls.__module__].__dict__
globalns.setdefault(cls.__name__, cls)
for f in cls.__fields__.values():
... | python | def update_forward_refs(cls, **localns: Any) -> None:
"""
Try to update ForwardRefs on fields based on this Model, globalns and localns.
"""
globalns = sys.modules[cls.__module__].__dict__
globalns.setdefault(cls.__name__, cls)
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samuelcolvin/pydantic | pydantic/datetime_parse.py | parse_date | def parse_date(value: Union[date, StrIntFloat]) -> date:
"""
Parse a date/int/float/string and return a datetime.date.
Raise ValueError if the input is well formatted but not a valid date.
Raise ValueError if the input isn't well formatted.
"""
if isinstance(value, date):
if isinstance(... | python | def parse_date(value: Union[date, StrIntFloat]) -> date:
"""
Parse a date/int/float/string and return a datetime.date.
Raise ValueError if the input is well formatted but not a valid date.
Raise ValueError if the input isn't well formatted.
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samuelcolvin/pydantic | pydantic/datetime_parse.py | parse_time | def parse_time(value: Union[time, str]) -> time:
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samuelcolvin/pydantic | pydantic/datetime_parse.py | parse_datetime | def parse_datetime(value: Union[datetime, StrIntFloat]) -> datetime:
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the output uses a timezone with a fixed offset from UTC.
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samuelcolvin/pydantic | pydantic/datetime_parse.py | parse_duration | def parse_duration(value: StrIntFloat) -> timedelta:
"""
Parse a duration int/float/string and return a datetime.timedelta.
The preferred format for durations in Django is '%d %H:%M:%S.%f'.
Also supports ISO 8601 representation.
"""
if isinstance(value, timedelta):
return value
if... | python | def parse_duration(value: StrIntFloat) -> timedelta:
"""
Parse a duration int/float/string and return a datetime.timedelta.
The preferred format for durations in Django is '%d %H:%M:%S.%f'.
Also supports ISO 8601 representation.
"""
if isinstance(value, timedelta):
return value
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pycontribs/jira | jira/client.py | translate_resource_args | def translate_resource_args(func):
"""Decorator that converts Issue and Project resources to their keys when used as arguments."""
@wraps(func)
def wrapper(*args, **kwargs):
"""
:type args: *Any
:type kwargs: **Any
:return: Any
"""
arg_list = []
for ar... | python | def translate_resource_args(func):
"""Decorator that converts Issue and Project resources to their keys when used as arguments."""
@wraps(func)
def wrapper(*args, **kwargs):
"""
:type args: *Any
:type kwargs: **Any
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pycontribs/jira | jira/client.py | JIRA._check_update_ | def _check_update_(self):
"""Check if the current version of the library is outdated."""
try:
data = requests.get("https://pypi.python.org/pypi/jira/json", timeout=2.001).json()
released_version = data['info']['version']
if parse_version(released_version) > parse_ver... | python | def _check_update_(self):
"""Check if the current version of the library is outdated."""
try:
data = requests.get("https://pypi.python.org/pypi/jira/json", timeout=2.001).json()
released_version = data['info']['version']
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pycontribs/jira | jira/client.py | JIRA._fetch_pages | def _fetch_pages(self,
item_type,
items_key,
request_path,
startAt=0,
maxResults=50,
params=None,
base=JIRA_BASE_URL,
):
"""Fetch pages.
... | python | def _fetch_pages(self,
item_type,
items_key,
request_path,
startAt=0,
maxResults=50,
params=None,
base=JIRA_BASE_URL,
):
"""Fetch pages.
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