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ask/redish
redish/types.py
SortedSet.remove
def remove(self, member): """Remove member.""" if not self.client.zrem(self.name, member): raise KeyError(member)
python
def remove(self, member): """Remove member.""" if not self.client.zrem(self.name, member): raise KeyError(member)
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Remove member.
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train
https://github.com/ask/redish/blob/4845f8d5e12fd953ecad624b4e1e89f79a082a3e/redish/types.py#L293-L296
ask/redish
redish/types.py
SortedSet.increment
def increment(self, member, amount=1): """Increment the score of ``member`` by ``amount``.""" return self.client.zincrby(self.name, member, amount)
python
def increment(self, member, amount=1): """Increment the score of ``member`` by ``amount``.""" return self.client.zincrby(self.name, member, amount)
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Increment the score of ``member`` by ``amount``.
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train
https://github.com/ask/redish/blob/4845f8d5e12fd953ecad624b4e1e89f79a082a3e/redish/types.py#L306-L308
ask/redish
redish/types.py
SortedSet.range_by_score
def range_by_score(self, min, max, num=None, withscores=False): """Return all the elements with score >= min and score <= max (a range query) from the sorted set.""" return self.client.zrangebyscore(self.name, min, max, num=num, withscores=withscores)
python
def range_by_score(self, min, max, num=None, withscores=False): """Return all the elements with score >= min and score <= max (a range query) from the sorted set.""" return self.client.zrangebyscore(self.name, min, max, num=num, withscores=withscores)
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Return all the elements with score >= min and score <= max (a range query) from the sorted set.
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train
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ask/redish
redish/types.py
Dict.pop
def pop(self, key, *args, **kwargs): """Remove specified key and return the corresponding value. :keyword default: If key is not found, ``default`` is returned if given, otherwise :exc:`KeyError` is raised. """ try: val = self[key] except KeyError: if len(args): return args[0] if "default" in kwargs: return kwargs["default"] raise try: del(self[key]) except KeyError: pass return val
python
def pop(self, key, *args, **kwargs): """Remove specified key and return the corresponding value. :keyword default: If key is not found, ``default`` is returned if given, otherwise :exc:`KeyError` is raised. """ try: val = self[key] except KeyError: if len(args): return args[0] if "default" in kwargs: return kwargs["default"] raise try: del(self[key]) except KeyError: pass return val
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Remove specified key and return the corresponding value. :keyword default: If key is not found, ``default`` is returned if given, otherwise :exc:`KeyError` is raised.
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train
https://github.com/ask/redish/blob/4845f8d5e12fd953ecad624b4e1e89f79a082a3e/redish/types.py#L439-L460
ask/redish
redish/types.py
Queue.full
def full(self): """Return ``True`` if the queue is full, ``False`` otherwise (not reliable!). Only applicable if :attr:`maxsize` is set. """ return self.maxsize and len(self.list) >= self.maxsize or False
python
def full(self): """Return ``True`` if the queue is full, ``False`` otherwise (not reliable!). Only applicable if :attr:`maxsize` is set. """ return self.maxsize and len(self.list) >= self.maxsize or False
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train
https://github.com/ask/redish/blob/4845f8d5e12fd953ecad624b4e1e89f79a082a3e/redish/types.py#L491-L498
ask/redish
redish/types.py
Queue.get
def get(self, block=True, timeout=None): """Remove and return an item from the queue. If optional args ``block`` is ``True`` and ``timeout`` is ``None`` (the default), block if necessary until an item is available. If ``timeout`` is a positive number, it blocks at most ``timeout`` seconds and raises the :exc:`Queue.Empty` exception if no item was available within that time. Otherwise (``block`` is ``False``), return an item if one is immediately available, else raise the :exc:`Queue.Empty` exception (``timeout`` is ignored in that case). """ if not block: return self.get_nowait() item = self._bpop([self.name], timeout=timeout) if item is not None: return item raise Empty
python
def get(self, block=True, timeout=None): """Remove and return an item from the queue. If optional args ``block`` is ``True`` and ``timeout`` is ``None`` (the default), block if necessary until an item is available. If ``timeout`` is a positive number, it blocks at most ``timeout`` seconds and raises the :exc:`Queue.Empty` exception if no item was available within that time. Otherwise (``block`` is ``False``), return an item if one is immediately available, else raise the :exc:`Queue.Empty` exception (``timeout`` is ignored in that case). """ if not block: return self.get_nowait() item = self._bpop([self.name], timeout=timeout) if item is not None: return item raise Empty
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Remove and return an item from the queue. If optional args ``block`` is ``True`` and ``timeout`` is ``None`` (the default), block if necessary until an item is available. If ``timeout`` is a positive number, it blocks at most ``timeout`` seconds and raises the :exc:`Queue.Empty` exception if no item was available within that time. Otherwise (``block`` is ``False``), return an item if one is immediately available, else raise the :exc:`Queue.Empty` exception (``timeout`` is ignored in that case).
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train
https://github.com/ask/redish/blob/4845f8d5e12fd953ecad624b4e1e89f79a082a3e/redish/types.py#L500-L518
ask/redish
redish/types.py
Queue.put
def put(self, item, **kwargs): """Put an item into the queue.""" if self.full(): raise Full() self._append(item)
python
def put(self, item, **kwargs): """Put an item into the queue.""" if self.full(): raise Full() self._append(item)
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train
https://github.com/ask/redish/blob/4845f8d5e12fd953ecad624b4e1e89f79a082a3e/redish/types.py#L531-L535
ask/redish
redish/types.py
ZSet.increment
def increment(self, member, amount=1): """Increment the score of ``member`` by ``amount``.""" self._dict[member] += amount return self._dict[member]
python
def increment(self, member, amount=1): """Increment the score of ``member`` by ``amount``.""" self._dict[member] += amount return self._dict[member]
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train
https://github.com/ask/redish/blob/4845f8d5e12fd953ecad624b4e1e89f79a082a3e/redish/types.py#L771-L774
ask/redish
redish/types.py
ZSet.range_by_score
def range_by_score(self, min, max): """Return all the elements with score >= min and score <= max (a range query) from the sorted set.""" data = self.items() keys = [r[1] for r in data] start = bisect.bisect_left(keys, min) end = bisect.bisect_right(keys, max, start) return self._as_set()[start:end]
python
def range_by_score(self, min, max): """Return all the elements with score >= min and score <= max (a range query) from the sorted set.""" data = self.items() keys = [r[1] for r in data] start = bisect.bisect_left(keys, min) end = bisect.bisect_right(keys, max, start) return self._as_set()[start:end]
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Return all the elements with score >= min and score <= max (a range query) from the sorted set.
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noahgoldman/adbpy
adbpy/socket.py
Socket.connect
def connect(self): """Connect to the given socket""" if not self.connected: self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.socket.connect(self.address) self.connected = True
python
def connect(self): """Connect to the given socket""" if not self.connected: self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.socket.connect(self.address) self.connected = True
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Connect to the given socket
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train
https://github.com/noahgoldman/adbpy/blob/ecbff8a8f151852b5c36847dc812582a8674a503/adbpy/socket.py#L30-L35
noahgoldman/adbpy
adbpy/socket.py
Socket.send
def send(self, data): """Send a formatted message to the ADB server""" self._send_data(int_to_hex(len(data))) self._send_data(data)
python
def send(self, data): """Send a formatted message to the ADB server""" self._send_data(int_to_hex(len(data))) self._send_data(data)
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Send a formatted message to the ADB server
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train
https://github.com/noahgoldman/adbpy/blob/ecbff8a8f151852b5c36847dc812582a8674a503/adbpy/socket.py#L42-L46
noahgoldman/adbpy
adbpy/socket.py
Socket._send_data
def _send_data(self, data): """Send data to the ADB server""" total_sent = 0 while total_sent < len(data): # Send only the bytes that haven't been # sent yet sent = self.socket.send(data[total_sent:].encode("ascii")) if sent == 0: self.close() raise RuntimeError("Socket connection dropped, " "send failed") total_sent += sent
python
def _send_data(self, data): """Send data to the ADB server""" total_sent = 0 while total_sent < len(data): # Send only the bytes that haven't been # sent yet sent = self.socket.send(data[total_sent:].encode("ascii")) if sent == 0: self.close() raise RuntimeError("Socket connection dropped, " "send failed") total_sent += sent
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Send data to the ADB server
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train
https://github.com/noahgoldman/adbpy/blob/ecbff8a8f151852b5c36847dc812582a8674a503/adbpy/socket.py#L48-L61
noahgoldman/adbpy
adbpy/socket.py
Socket.receive_until_end
def receive_until_end(self, timeout=None): """ Reads and blocks until the socket closes Used for the "shell" command, where STDOUT and STDERR are just redirected to the terminal with no length """ if self.receive_fixed_length(4) != "OKAY": raise SocketError("Socket communication failed: " "the server did not return a valid response") # The time at which the receive starts start_time = time.clock() output = "" while True: if timeout is not None: self.socket.settimeout(timeout - (time.clock() - start_time)) chunk = '' try: chunk = self.socket.recv(4096).decode("ascii") except socket.timeout: return output if not chunk: return output output += chunk
python
def receive_until_end(self, timeout=None): """ Reads and blocks until the socket closes Used for the "shell" command, where STDOUT and STDERR are just redirected to the terminal with no length """ if self.receive_fixed_length(4) != "OKAY": raise SocketError("Socket communication failed: " "the server did not return a valid response") # The time at which the receive starts start_time = time.clock() output = "" while True: if timeout is not None: self.socket.settimeout(timeout - (time.clock() - start_time)) chunk = '' try: chunk = self.socket.recv(4096).decode("ascii") except socket.timeout: return output if not chunk: return output output += chunk
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train
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bitprophet/botox
botox/aws.py
defaults
def defaults(f, self, *args, **kwargs): """ For ``PARAMETERS`` keys, replace None ``kwargs`` with ``self`` attr values. Should be applied on the top of any decorator stack so other decorators see the "right" kwargs. Will also apply transformations found in ``TRANSFORMS``. """ for name, data in PARAMETERS.iteritems(): kwargs[name] = kwargs.get(name) or getattr(self, name) if 'transform' in data: kwargs[name] = data['transform'](kwargs[name]) return f(self, *args, **kwargs)
python
def defaults(f, self, *args, **kwargs): """ For ``PARAMETERS`` keys, replace None ``kwargs`` with ``self`` attr values. Should be applied on the top of any decorator stack so other decorators see the "right" kwargs. Will also apply transformations found in ``TRANSFORMS``. """ for name, data in PARAMETERS.iteritems(): kwargs[name] = kwargs.get(name) or getattr(self, name) if 'transform' in data: kwargs[name] = data['transform'](kwargs[name]) return f(self, *args, **kwargs)
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train
https://github.com/bitprophet/botox/blob/02c887a28bd2638273548cc7d1e6d6f1d4d38bf9/botox/aws.py#L81-L94
bitprophet/botox
botox/aws.py
requires
def requires(*params): """ Raise ValueError if any ``params`` are omitted from the decorated kwargs. None values are considered omissions. Example usage on an AWS() method: @requires('zone', 'security_groups') def my_aws_method(self, custom_args, **kwargs): # We'll only get here if 'kwargs' contained non-None values for # both 'zone' and 'security_groups'. """ def requires(f, self, *args, **kwargs): missing = filter(lambda x: kwargs.get(x) is None, params) if missing: msgs = ", ".join([PARAMETERS[x]['msg'] for x in missing]) raise ValueError("Missing the following parameters: %s" % msgs) return f(self, *args, **kwargs) return decorator(requires)
python
def requires(*params): """ Raise ValueError if any ``params`` are omitted from the decorated kwargs. None values are considered omissions. Example usage on an AWS() method: @requires('zone', 'security_groups') def my_aws_method(self, custom_args, **kwargs): # We'll only get here if 'kwargs' contained non-None values for # both 'zone' and 'security_groups'. """ def requires(f, self, *args, **kwargs): missing = filter(lambda x: kwargs.get(x) is None, params) if missing: msgs = ", ".join([PARAMETERS[x]['msg'] for x in missing]) raise ValueError("Missing the following parameters: %s" % msgs) return f(self, *args, **kwargs) return decorator(requires)
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bitprophet/botox
botox/aws.py
AWS.get_security_group_id
def get_security_group_id(self, name): """ Take name string, give back security group ID. To get around VPC's API being stupid. """ # Memoize entire list of groups if not hasattr(self, '_security_groups'): self._security_groups = {} for group in self.get_all_security_groups(): self._security_groups[group.name] = group.id return self._security_groups[name]
python
def get_security_group_id(self, name): """ Take name string, give back security group ID. To get around VPC's API being stupid. """ # Memoize entire list of groups if not hasattr(self, '_security_groups'): self._security_groups = {} for group in self.get_all_security_groups(): self._security_groups[group.name] = group.id return self._security_groups[name]
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train
https://github.com/bitprophet/botox/blob/02c887a28bd2638273548cc7d1e6d6f1d4d38bf9/botox/aws.py#L188-L199
bitprophet/botox
botox/aws.py
AWS.get_instance_subnet_name
def get_instance_subnet_name(self, instance): """ Return a human readable name for given instance's subnet, or None. Uses stored config mapping of subnet IDs to names. """ # TODO: we have to do this here since we are monkeypatching Instance. # If we switch to custom Instance (sub)class then we could do it in the # object, provided it has access to the configuration data. if instance.subnet_id: # Account for omitted 'subnet-' subnet = self.config['subnets'][instance.subnet_id[7:]] else: subnet = BLANK return subnet
python
def get_instance_subnet_name(self, instance): """ Return a human readable name for given instance's subnet, or None. Uses stored config mapping of subnet IDs to names. """ # TODO: we have to do this here since we are monkeypatching Instance. # If we switch to custom Instance (sub)class then we could do it in the # object, provided it has access to the configuration data. if instance.subnet_id: # Account for omitted 'subnet-' subnet = self.config['subnets'][instance.subnet_id[7:]] else: subnet = BLANK return subnet
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train
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bitprophet/botox
botox/aws.py
AWS.get_subnet_id
def get_subnet_id(self, name): """ Return subnet ID for given ``name``, if it exists. E.g. with a subnet mapping of ``{'abc123': 'ops', '67fd56': 'prod'}``, ``get_subnet_id('ops')`` would return ``'abc123'``. If the map has non-unique values, the first matching key will be returned. If no match is found, the given ``name`` is returned as-is. This works well for e.g. normalizing names-or-IDs to just IDs. """ for subnet_id, subnet_name in self.config['subnets'].iteritems(): if subnet_name == name: return subnet_id return name
python
def get_subnet_id(self, name): """ Return subnet ID for given ``name``, if it exists. E.g. with a subnet mapping of ``{'abc123': 'ops', '67fd56': 'prod'}``, ``get_subnet_id('ops')`` would return ``'abc123'``. If the map has non-unique values, the first matching key will be returned. If no match is found, the given ``name`` is returned as-is. This works well for e.g. normalizing names-or-IDs to just IDs. """ for subnet_id, subnet_name in self.config['subnets'].iteritems(): if subnet_name == name: return subnet_id return name
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https://github.com/bitprophet/botox/blob/02c887a28bd2638273548cc7d1e6d6f1d4d38bf9/botox/aws.py#L217-L231
bitprophet/botox
botox/aws.py
AWS.create
def create(self, hostname, **kwargs): """ Create new EC2 instance named ``hostname``. You may specify keyword arguments matching those of ``__init__`` (e.g. ``size``, ``ami``) to override any defaults given when the object was created, or to fill in parameters not given at initialization time. Additional parameters that are instance-specific: * ``ip``: The static private IP address for the new host. This method returns a ``boto.EC2.instance.Instance`` object. """ # Create creating = "Creating '%s' (a %s instance of %s)" % ( hostname, kwargs['size'], kwargs['ami'] ) with self.msg(creating): instance = self._create(hostname, kwargs) # Name with self.msg("Tagging as '%s'" % hostname): try: instance.rename(hostname) # One-time retry for API errors when setting tags except _ResponseError: time.sleep(1) instance.rename(hostname) # Wait for it to finish booting with self.msg("Waiting for boot: "): tick = 5 while instance.state != 'running': self.log(".", end='') time.sleep(tick) instance.update() return instance
python
def create(self, hostname, **kwargs): """ Create new EC2 instance named ``hostname``. You may specify keyword arguments matching those of ``__init__`` (e.g. ``size``, ``ami``) to override any defaults given when the object was created, or to fill in parameters not given at initialization time. Additional parameters that are instance-specific: * ``ip``: The static private IP address for the new host. This method returns a ``boto.EC2.instance.Instance`` object. """ # Create creating = "Creating '%s' (a %s instance of %s)" % ( hostname, kwargs['size'], kwargs['ami'] ) with self.msg(creating): instance = self._create(hostname, kwargs) # Name with self.msg("Tagging as '%s'" % hostname): try: instance.rename(hostname) # One-time retry for API errors when setting tags except _ResponseError: time.sleep(1) instance.rename(hostname) # Wait for it to finish booting with self.msg("Waiting for boot: "): tick = 5 while instance.state != 'running': self.log(".", end='') time.sleep(tick) instance.update() return instance
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Create new EC2 instance named ``hostname``. You may specify keyword arguments matching those of ``__init__`` (e.g. ``size``, ``ami``) to override any defaults given when the object was created, or to fill in parameters not given at initialization time. Additional parameters that are instance-specific: * ``ip``: The static private IP address for the new host. This method returns a ``boto.EC2.instance.Instance`` object.
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train
https://github.com/bitprophet/botox/blob/02c887a28bd2638273548cc7d1e6d6f1d4d38bf9/botox/aws.py#L257-L295
bitprophet/botox
botox/aws.py
AWS.get
def get(self, arg): """ Return instance object with given EC2 ID or nametag. """ try: reservations = self.get_all_instances(filters={'tag:Name': [arg]}) instance = reservations[0].instances[0] except IndexError: try: instance = self.get_all_instances([arg])[0].instances[0] except (_ResponseError, IndexError): # TODO: encapsulate actual exception for debugging err = "Can't find any instance with name or ID '%s'" % arg raise ValueError(err) return instance
python
def get(self, arg): """ Return instance object with given EC2 ID or nametag. """ try: reservations = self.get_all_instances(filters={'tag:Name': [arg]}) instance = reservations[0].instances[0] except IndexError: try: instance = self.get_all_instances([arg])[0].instances[0] except (_ResponseError, IndexError): # TODO: encapsulate actual exception for debugging err = "Can't find any instance with name or ID '%s'" % arg raise ValueError(err) return instance
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train
https://github.com/bitprophet/botox/blob/02c887a28bd2638273548cc7d1e6d6f1d4d38bf9/botox/aws.py#L324-L338
bitprophet/botox
botox/aws.py
AWS.get_volumes_for_instance
def get_volumes_for_instance(self, arg, device=None): """ Return all EC2 Volume objects attached to ``arg`` instance name or ID. May specify ``device`` to limit to the (single) volume attached as that device. """ instance = self.get(arg) filters = {'attachment.instance-id': instance.id} if device is not None: filters['attachment.device'] = device return self.get_all_volumes(filters=filters)
python
def get_volumes_for_instance(self, arg, device=None): """ Return all EC2 Volume objects attached to ``arg`` instance name or ID. May specify ``device`` to limit to the (single) volume attached as that device. """ instance = self.get(arg) filters = {'attachment.instance-id': instance.id} if device is not None: filters['attachment.device'] = device return self.get_all_volumes(filters=filters)
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Return all EC2 Volume objects attached to ``arg`` instance name or ID. May specify ``device`` to limit to the (single) volume attached as that device.
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train
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bitprophet/botox
botox/aws.py
AWS.terminate
def terminate(self, arg): """ Terminate instance with given EC2 ID or nametag. """ instance = self.get(arg) with self.msg("Terminating %s (%s): " % (instance.name, instance.id)): instance.rename("old-%s" % instance.name) instance.terminate() while instance.state != 'terminated': time.sleep(5) self.log(".", end='') instance.update()
python
def terminate(self, arg): """ Terminate instance with given EC2 ID or nametag. """ instance = self.get(arg) with self.msg("Terminating %s (%s): " % (instance.name, instance.id)): instance.rename("old-%s" % instance.name) instance.terminate() while instance.state != 'terminated': time.sleep(5) self.log(".", end='') instance.update()
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Terminate instance with given EC2 ID or nametag.
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train
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mwhooker/jones
jones/jones.py
ZNodeMap._get
def _get(self): """get and parse data stored in self.path.""" data, stat = self.zk.get(self.path) if not len(data): return {}, stat.version if self.OLD_SEPARATOR in data: return self._get_old() return json.loads(data), stat.version
python
def _get(self): """get and parse data stored in self.path.""" data, stat = self.zk.get(self.path) if not len(data): return {}, stat.version if self.OLD_SEPARATOR in data: return self._get_old() return json.loads(data), stat.version
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get and parse data stored in self.path.
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https://github.com/mwhooker/jones/blob/121e89572ca063f456b8e94cbb8cbee26c307a8f/jones/jones.py#L55-L63
mwhooker/jones
jones/jones.py
ZNodeMap._set
def _set(self, data, version): """serialize and set data to self.path.""" self.zk.set(self.path, json.dumps(data), version)
python
def _set(self, data, version): """serialize and set data to self.path.""" self.zk.set(self.path, json.dumps(data), version)
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serialize and set data to self.path.
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mwhooker/jones
jones/jones.py
ZNodeMap._get_old
def _get_old(self): """get and parse data stored in self.path.""" def _deserialize(d): if not len(d): return {} return dict(l.split(self.OLD_SEPARATOR) for l in d.split('\n')) data, stat = self.zk.get(self.path) return _deserialize(data.decode('utf8')), stat.version
python
def _get_old(self): """get and parse data stored in self.path.""" def _deserialize(d): if not len(d): return {} return dict(l.split(self.OLD_SEPARATOR) for l in d.split('\n')) data, stat = self.zk.get(self.path) return _deserialize(data.decode('utf8')), stat.version
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get and parse data stored in self.path.
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https://github.com/mwhooker/jones/blob/121e89572ca063f456b8e94cbb8cbee26c307a8f/jones/jones.py#L70-L79
mwhooker/jones
jones/jones.py
Jones.create_config
def create_config(self, env, conf): """ Set conf to env under service. pass None to env for root. """ if not isinstance(conf, collections.Mapping): raise ValueError("conf must be a collections.Mapping") self.zk.ensure_path(self.view_path) self._create( self._get_env_path(env), conf ) self._update_view(env)
python
def create_config(self, env, conf): """ Set conf to env under service. pass None to env for root. """ if not isinstance(conf, collections.Mapping): raise ValueError("conf must be a collections.Mapping") self.zk.ensure_path(self.view_path) self._create( self._get_env_path(env), conf ) self._update_view(env)
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Set conf to env under service. pass None to env for root.
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train
https://github.com/mwhooker/jones/blob/121e89572ca063f456b8e94cbb8cbee26c307a8f/jones/jones.py#L134-L151
mwhooker/jones
jones/jones.py
Jones.set_config
def set_config(self, env, conf, version): """ Set conf to env under service. pass None to env for root. """ if not isinstance(conf, collections.Mapping): raise ValueError("conf must be a collections.Mapping") self._set( self._get_env_path(env), conf, version ) path = self._get_env_path(env) """Update env's children with new config.""" for child in zkutil.walk(self.zk, path): self._update_view(Env(child[len(self.conf_path)+1:]))
python
def set_config(self, env, conf, version): """ Set conf to env under service. pass None to env for root. """ if not isinstance(conf, collections.Mapping): raise ValueError("conf must be a collections.Mapping") self._set( self._get_env_path(env), conf, version ) path = self._get_env_path(env) """Update env's children with new config.""" for child in zkutil.walk(self.zk, path): self._update_view(Env(child[len(self.conf_path)+1:]))
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train
https://github.com/mwhooker/jones/blob/121e89572ca063f456b8e94cbb8cbee26c307a8f/jones/jones.py#L153-L171
mwhooker/jones
jones/jones.py
Jones.get_config
def get_config(self, hostname): """ Returns a configuration for hostname. """ version, config = self._get( self.associations.get(hostname) ) return config
python
def get_config(self, hostname): """ Returns a configuration for hostname. """ version, config = self._get( self.associations.get(hostname) ) return config
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https://github.com/mwhooker/jones/blob/121e89572ca063f456b8e94cbb8cbee26c307a8f/jones/jones.py#L183-L191
mwhooker/jones
jones/jones.py
Jones.get_view_by_env
def get_view_by_env(self, env): """ Returns the view of `env`. """ version, data = self._get(self._get_view_path(env)) return data
python
def get_view_by_env(self, env): """ Returns the view of `env`. """ version, data = self._get(self._get_view_path(env)) return data
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Returns the view of `env`.
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https://github.com/mwhooker/jones/blob/121e89572ca063f456b8e94cbb8cbee26c307a8f/jones/jones.py#L204-L210
mwhooker/jones
jones/jones.py
Jones.assoc_host
def assoc_host(self, hostname, env): """ Associate a host with an environment. hostname is opaque to Jones. Any string which uniquely identifies a host is acceptable. """ dest = self._get_view_path(env) self.associations.set(hostname, dest)
python
def assoc_host(self, hostname, env): """ Associate a host with an environment. hostname is opaque to Jones. Any string which uniquely identifies a host is acceptable. """ dest = self._get_view_path(env) self.associations.set(hostname, dest)
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train
https://github.com/mwhooker/jones/blob/121e89572ca063f456b8e94cbb8cbee26c307a8f/jones/jones.py#L212-L221
mwhooker/jones
jones/jones.py
Jones.get_associations
def get_associations(self, env): """ Get all the associations for this env. Root cannot have associations, so return None for root. returns a map of hostnames to environments. """ if env.is_root: return None associations = self.associations.get_all() return [assoc for assoc in associations if associations[assoc] == self._get_view_path(env)]
python
def get_associations(self, env): """ Get all the associations for this env. Root cannot have associations, so return None for root. returns a map of hostnames to environments. """ if env.is_root: return None associations = self.associations.get_all() return [assoc for assoc in associations if associations[assoc] == self._get_view_path(env)]
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Get all the associations for this env. Root cannot have associations, so return None for root. returns a map of hostnames to environments.
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mwhooker/jones
jones/jones.py
Jones._flatten_from_root
def _flatten_from_root(self, env): """ Flatten values from root down in to new view. """ nodes = env.components # Path through the znode graph from root ('') to env path = [nodes[:n] for n in xrange(len(nodes) + 1)] # Expand path and map it to the root path = map( self._get_env_path, [Env('/'.join(p)) for p in path] ) data = {} for n in path: _, config = self._get(n) data.update(config) return data
python
def _flatten_from_root(self, env): """ Flatten values from root down in to new view. """ nodes = env.components # Path through the znode graph from root ('') to env path = [nodes[:n] for n in xrange(len(nodes) + 1)] # Expand path and map it to the root path = map( self._get_env_path, [Env('/'.join(p)) for p in path] ) data = {} for n in path: _, config = self._get(n) data.update(config) return data
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ask/redish
redish/serialization.py
Serializer.encode
def encode(self, value): """Encode value.""" value = self.serialize(value) if self.encoding: value = value.encode(self.encoding) return value
python
def encode(self, value): """Encode value.""" value = self.serialize(value) if self.encoding: value = value.encode(self.encoding) return value
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ask/redish
redish/serialization.py
Serializer.decode
def decode(self, value): """Decode value.""" if self.encoding: value = value.decode(self.encoding) return self.deserialize(value)
python
def decode(self, value): """Decode value.""" if self.encoding: value = value.decode(self.encoding) return self.deserialize(value)
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rmad17/pyreqs
pyreqs.py
install
def install(packagename, save, save_dev, save_test, filename): """ Install the package via pip, pin the package only to requirements file. Use option to decide which file the package will be pinned to. """ print('Installing ', packagename) print(sh_pip.install(packagename)) if not filename: filename = get_filename(save, save_dev, save_test) try: add_requirements(packagename, filename) except AssertionError: print('Package already pinned in ', filename)
python
def install(packagename, save, save_dev, save_test, filename): """ Install the package via pip, pin the package only to requirements file. Use option to decide which file the package will be pinned to. """ print('Installing ', packagename) print(sh_pip.install(packagename)) if not filename: filename = get_filename(save, save_dev, save_test) try: add_requirements(packagename, filename) except AssertionError: print('Package already pinned in ', filename)
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Install the package via pip, pin the package only to requirements file. Use option to decide which file the package will be pinned to.
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rmad17/pyreqs
pyreqs.py
remove
def remove(packagename, save, save_dev, save_test, filename): """ Uninstall the package and remove it from requirements file. """ print(sh_pip.uninstall(packagename, "-y")) if not filename: filename = get_filename(save, save_dev, save_test) remove_requirements(packagename, filename)
python
def remove(packagename, save, save_dev, save_test, filename): """ Uninstall the package and remove it from requirements file. """ print(sh_pip.uninstall(packagename, "-y")) if not filename: filename = get_filename(save, save_dev, save_test) remove_requirements(packagename, filename)
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Uninstall the package and remove it from requirements file.
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DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.os_path_split_asunder
def os_path_split_asunder(path, debug=False): """ http://stackoverflow.com/a/4580931/171094 """ parts = [] while True: newpath, tail = os.path.split(path) if debug: print repr(path), (newpath, tail) if newpath == path: assert not tail if path: parts.append(path) break parts.append(tail) path = newpath parts.reverse() return parts
python
def os_path_split_asunder(path, debug=False): """ http://stackoverflow.com/a/4580931/171094 """ parts = [] while True: newpath, tail = os.path.split(path) if debug: print repr(path), (newpath, tail) if newpath == path: assert not tail if path: parts.append(path) break parts.append(tail) path = newpath parts.reverse() return parts
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http://stackoverflow.com/a/4580931/171094
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DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.is_subdirectory
def is_subdirectory(potential_subdirectory, expected_parent_directory): """ Is the first argument a sub-directory of the second argument? :param potential_subdirectory: :param expected_parent_directory: :return: True if the potential_subdirectory is a child of the expected parent directory """ def _get_normalized_parts(path): return DKCloudCommandRunner.os_path_split_asunder(os.path.realpath(os.path.abspath(os.path.normpath(path)))) # make absolute and handle symbolic links, split into components sub_parts = _get_normalized_parts(potential_subdirectory) parent_parts = _get_normalized_parts(expected_parent_directory) if len(parent_parts) > len(sub_parts): # a parent directory never has more path segments than its child return False # we expect the zip to end with the short path, which we know to be the parent return all(part1 == part2 for part1, part2 in zip(sub_parts, parent_parts))
python
def is_subdirectory(potential_subdirectory, expected_parent_directory): """ Is the first argument a sub-directory of the second argument? :param potential_subdirectory: :param expected_parent_directory: :return: True if the potential_subdirectory is a child of the expected parent directory """ def _get_normalized_parts(path): return DKCloudCommandRunner.os_path_split_asunder(os.path.realpath(os.path.abspath(os.path.normpath(path)))) # make absolute and handle symbolic links, split into components sub_parts = _get_normalized_parts(potential_subdirectory) parent_parts = _get_normalized_parts(expected_parent_directory) if len(parent_parts) > len(sub_parts): # a parent directory never has more path segments than its child return False # we expect the zip to end with the short path, which we know to be the parent return all(part1 == part2 for part1, part2 in zip(sub_parts, parent_parts))
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Is the first argument a sub-directory of the second argument? :param potential_subdirectory: :param expected_parent_directory: :return: True if the potential_subdirectory is a child of the expected parent directory
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train
https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L566-L588
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.update_all_files
def update_all_files(dk_api, kitchen, recipe_name, recipe_dir, message, dryrun=False): """ reutrns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param recipe_dir: string - path to the root of the directory :param message: string message -- commit message, string :rtype: DKReturnCode """ rc = DKReturnCode() if kitchen is None or recipe_name is None or message is None: s = 'ERROR: DKCloudCommandRunner bad input parameters' rc.set(rc.DK_FAIL, s) return rc rc = dk_api.recipe_status(kitchen, recipe_name, recipe_dir) if not rc.ok(): rs = 'DKCloudCommand.update_all_files failed\nmessage: %s' % rc.get_message() rc.set_message(rs) return rc rl = rc.get_payload() if (len(rl['different']) + len(rl['only_local']) + len(rl['only_remote'])) == 0: rs = 'DKCloudCommand.update_all_files no files changed.' rc.set_message(rs) return rc rc = DKCloudCommandRunner._update_changed_files(dk_api, rl['different'], kitchen, recipe_name, message, dryrun) if not rc.ok(): return rc msg_differences = rc.get_message() rc = DKCloudCommandRunner._add_new_files(dk_api, rl['only_local'], kitchen, recipe_name, message, dryrun) if not rc.ok(): return rc msg_additions = rc.get_message() rc = DKCloudCommandRunner._remove_deleted_files(dk_api, rl['only_remote'], kitchen, recipe_name, message, dryrun) if not rc.ok(): return rc msg_deletions = rc.get_message() msg = '' if len(msg_differences) > 0: if len(msg) > 0: msg += '\n' msg += msg_differences + '\n' if len(msg_additions) > 0: if len(msg) > 0: msg += '\n' msg += msg_additions + '\n' if len(msg_deletions) > 0: if len(msg) > 0: msg += '\n' msg += msg_deletions + '\n' rc.set_message(msg) return rc
python
def update_all_files(dk_api, kitchen, recipe_name, recipe_dir, message, dryrun=False): """ reutrns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param recipe_dir: string - path to the root of the directory :param message: string message -- commit message, string :rtype: DKReturnCode """ rc = DKReturnCode() if kitchen is None or recipe_name is None or message is None: s = 'ERROR: DKCloudCommandRunner bad input parameters' rc.set(rc.DK_FAIL, s) return rc rc = dk_api.recipe_status(kitchen, recipe_name, recipe_dir) if not rc.ok(): rs = 'DKCloudCommand.update_all_files failed\nmessage: %s' % rc.get_message() rc.set_message(rs) return rc rl = rc.get_payload() if (len(rl['different']) + len(rl['only_local']) + len(rl['only_remote'])) == 0: rs = 'DKCloudCommand.update_all_files no files changed.' rc.set_message(rs) return rc rc = DKCloudCommandRunner._update_changed_files(dk_api, rl['different'], kitchen, recipe_name, message, dryrun) if not rc.ok(): return rc msg_differences = rc.get_message() rc = DKCloudCommandRunner._add_new_files(dk_api, rl['only_local'], kitchen, recipe_name, message, dryrun) if not rc.ok(): return rc msg_additions = rc.get_message() rc = DKCloudCommandRunner._remove_deleted_files(dk_api, rl['only_remote'], kitchen, recipe_name, message, dryrun) if not rc.ok(): return rc msg_deletions = rc.get_message() msg = '' if len(msg_differences) > 0: if len(msg) > 0: msg += '\n' msg += msg_differences + '\n' if len(msg_additions) > 0: if len(msg) > 0: msg += '\n' msg += msg_additions + '\n' if len(msg_deletions) > 0: if len(msg) > 0: msg += '\n' msg += msg_deletions + '\n' rc.set_message(msg) return rc
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train
https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L753-L811
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.update_file
def update_file(dk_api, kitchen, recipe_name, message, files_to_update_param): """ reutrns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param message: string message -- commit message, string :param files_to_update_param: string -- file system directory where the recipe file lives :rtype: string """ rc = DKReturnCode() if kitchen is None or recipe_name is None or message is None or files_to_update_param is None: s = 'ERROR: DKCloudCommandRunner bad input parameters' rc.set(rc.DK_FAIL, s) return rc # Take a simple string or an array if isinstance(files_to_update_param, basestring): files_to_update = [files_to_update_param] else: files_to_update = files_to_update_param msg = '' for file_to_update in files_to_update: try: with open(file_to_update, 'r') as f: file_contents = f.read() except IOError as e: if len(msg) != 0: msg += '\n' msg += '%s' % (str(e)) rc.set(rc.DK_FAIL, msg) return rc except ValueError as e: if len(msg) != 0: msg += '\n' msg += 'ERROR: %s' % e.message rc.set(rc.DK_FAIL, msg) return rc rc = dk_api.update_file(kitchen, recipe_name, message, file_to_update, file_contents) if not rc.ok(): if len(msg) != 0: msg += '\n' msg += 'DKCloudCommand.update_file for %s failed\n\tmessage: %s' % (file_to_update, rc.get_message()) rc.set_message(msg) return rc else: if len(msg) != 0: msg += '\n' msg += 'DKCloudCommand.update_file for %s succeeded' % file_to_update rc.set_message(msg) return rc
python
def update_file(dk_api, kitchen, recipe_name, message, files_to_update_param): """ reutrns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param message: string message -- commit message, string :param files_to_update_param: string -- file system directory where the recipe file lives :rtype: string """ rc = DKReturnCode() if kitchen is None or recipe_name is None or message is None or files_to_update_param is None: s = 'ERROR: DKCloudCommandRunner bad input parameters' rc.set(rc.DK_FAIL, s) return rc # Take a simple string or an array if isinstance(files_to_update_param, basestring): files_to_update = [files_to_update_param] else: files_to_update = files_to_update_param msg = '' for file_to_update in files_to_update: try: with open(file_to_update, 'r') as f: file_contents = f.read() except IOError as e: if len(msg) != 0: msg += '\n' msg += '%s' % (str(e)) rc.set(rc.DK_FAIL, msg) return rc except ValueError as e: if len(msg) != 0: msg += '\n' msg += 'ERROR: %s' % e.message rc.set(rc.DK_FAIL, msg) return rc rc = dk_api.update_file(kitchen, recipe_name, message, file_to_update, file_contents) if not rc.ok(): if len(msg) != 0: msg += '\n' msg += 'DKCloudCommand.update_file for %s failed\n\tmessage: %s' % (file_to_update, rc.get_message()) rc.set_message(msg) return rc else: if len(msg) != 0: msg += '\n' msg += 'DKCloudCommand.update_file for %s succeeded' % file_to_update rc.set_message(msg) return rc
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train
https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L968-L1020
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.add_file
def add_file(dk_api, kitchen, recipe_name, message, api_file_key): """ returns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string :param message: string -- commit message, string :param api_file_key: string -- directory where the recipe file lives :rtype: DKReturnCode """ rc = DKReturnCode() if kitchen is None or recipe_name is None or message is None or api_file_key is None: s = 'ERROR: DKCloudCommandRunner bad input parameters' rc.set(rc.DK_FAIL, s) return rc ig = DKIgnore() if ig.ignore(api_file_key): rs = 'DKCloudCommand.add_file ignoring %s' % api_file_key rc.set_message(rs) return rc if not os.path.exists(api_file_key): s = "'%s' does not exist" % api_file_key rc.set(rc.DK_FAIL, s) return rc try: with open(api_file_key, 'r') as f: file_contents = f.read() except ValueError as e: s = 'ERROR: %s' % e.message rc.set(rc.DK_FAIL, s) return rc rc = dk_api.add_file(kitchen, recipe_name, message, api_file_key, file_contents) if rc.ok(): rs = 'DKCloudCommand.add_file for %s succeed' % api_file_key else: rs = 'DKCloudCommand.add_file for %s failed\nmessage: %s' % (api_file_key, rc.get_message()) rc.set_message(rs) return rc
python
def add_file(dk_api, kitchen, recipe_name, message, api_file_key): """ returns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string :param message: string -- commit message, string :param api_file_key: string -- directory where the recipe file lives :rtype: DKReturnCode """ rc = DKReturnCode() if kitchen is None or recipe_name is None or message is None or api_file_key is None: s = 'ERROR: DKCloudCommandRunner bad input parameters' rc.set(rc.DK_FAIL, s) return rc ig = DKIgnore() if ig.ignore(api_file_key): rs = 'DKCloudCommand.add_file ignoring %s' % api_file_key rc.set_message(rs) return rc if not os.path.exists(api_file_key): s = "'%s' does not exist" % api_file_key rc.set(rc.DK_FAIL, s) return rc try: with open(api_file_key, 'r') as f: file_contents = f.read() except ValueError as e: s = 'ERROR: %s' % e.message rc.set(rc.DK_FAIL, s) return rc rc = dk_api.add_file(kitchen, recipe_name, message, api_file_key, file_contents) if rc.ok(): rs = 'DKCloudCommand.add_file for %s succeed' % api_file_key else: rs = 'DKCloudCommand.add_file for %s failed\nmessage: %s' % (api_file_key, rc.get_message()) rc.set_message(rs) return rc
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train
https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L1024-L1064
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.delete_file
def delete_file(dk_api, kitchen, recipe_name, message, files_to_delete_param): """ returns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param message: string message -- commit message, string :param files_to_delete_param: path to the files to delete :rtype: DKReturnCode """ rc = DKReturnCode() if kitchen is None or recipe_name is None or message is None or files_to_delete_param is None: s = 'ERROR: DKCloudCommandRunner bad input parameters' rc.set(rc.DK_FAIL, s) return rc # Take a simple string or an array if isinstance(files_to_delete_param, basestring): files_to_delete = [files_to_delete_param] else: files_to_delete = files_to_delete_param msg = '' for file_to_delete in files_to_delete: basename = os.path.basename(file_to_delete) rc = dk_api.delete_file(kitchen, recipe_name, message, file_to_delete, basename) if not rc.ok(): msg += '\nDKCloudCommand.delete_file for %s failed\nmessage: %s' % (file_to_delete, rc.get_message()) rc.set_message(msg) return rc else: msg += 'DKCloudCommand.delete_file for %s succeed' % file_to_delete rc.set_message(msg) return rc
python
def delete_file(dk_api, kitchen, recipe_name, message, files_to_delete_param): """ returns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param message: string message -- commit message, string :param files_to_delete_param: path to the files to delete :rtype: DKReturnCode """ rc = DKReturnCode() if kitchen is None or recipe_name is None or message is None or files_to_delete_param is None: s = 'ERROR: DKCloudCommandRunner bad input parameters' rc.set(rc.DK_FAIL, s) return rc # Take a simple string or an array if isinstance(files_to_delete_param, basestring): files_to_delete = [files_to_delete_param] else: files_to_delete = files_to_delete_param msg = '' for file_to_delete in files_to_delete: basename = os.path.basename(file_to_delete) rc = dk_api.delete_file(kitchen, recipe_name, message, file_to_delete, basename) if not rc.ok(): msg += '\nDKCloudCommand.delete_file for %s failed\nmessage: %s' % (file_to_delete, rc.get_message()) rc.set_message(msg) return rc else: msg += 'DKCloudCommand.delete_file for %s succeed' % file_to_delete rc.set_message(msg) return rc
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train
https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L1068-L1100
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.watch_active_servings
def watch_active_servings(dk_api, kitchen, period): """ returns a string. :param dk_api: -- api object :param kitchen: string :param period: integer :rtype: string """ print 'period', period # try: # p = int(period) # except ValueError: # return 'DKCloudCommand.watch_active_servings requires an integer for the period' if period <= 0: return 'DKCloudCommand.watch_active_servings requires a positive period' DKActiveServingWatcherSingleton().set_sleep_time(period) DKActiveServingWatcherSingleton().set_api(dk_api) DKActiveServingWatcherSingleton().set_kitchen(kitchen) DKActiveServingWatcherSingleton().start_watcher() return ""
python
def watch_active_servings(dk_api, kitchen, period): """ returns a string. :param dk_api: -- api object :param kitchen: string :param period: integer :rtype: string """ print 'period', period # try: # p = int(period) # except ValueError: # return 'DKCloudCommand.watch_active_servings requires an integer for the period' if period <= 0: return 'DKCloudCommand.watch_active_servings requires a positive period' DKActiveServingWatcherSingleton().set_sleep_time(period) DKActiveServingWatcherSingleton().set_api(dk_api) DKActiveServingWatcherSingleton().set_kitchen(kitchen) DKActiveServingWatcherSingleton().start_watcher() return ""
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returns a string. :param dk_api: -- api object :param kitchen: string :param period: integer :rtype: string
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train
https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L1104-L1125
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.get_compiled_serving
def get_compiled_serving(dk_api, kitchen, recipe_name, variation_name): """ returns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param variation_name: string -- name of the recipe variation_name to be used :rtype: DKReturnCode """ rc = dk_api.get_compiled_serving(kitchen, recipe_name, variation_name) if rc.ok(): rs = 'DKCloudCommand.get_compiled_serving succeeded %s\n' % json.dumps(rc.get_payload(), indent=4) else: m = rc.get_message() e = m.split('the logfile errors are:nn') if len(e) > 1: e2 = DKCloudCommandRunner._decompress(e[len(e) - 1]) errors = e2.split('|') re = e[0] + " " + 'the logfile errors are: ' for e in errors: re += '\n%s' % e else: re = m rs = 'DKCloudCommand.get_compiled_serving failed\nmessage: %s\n' % re rc.set_message(rs) return rc
python
def get_compiled_serving(dk_api, kitchen, recipe_name, variation_name): """ returns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param variation_name: string -- name of the recipe variation_name to be used :rtype: DKReturnCode """ rc = dk_api.get_compiled_serving(kitchen, recipe_name, variation_name) if rc.ok(): rs = 'DKCloudCommand.get_compiled_serving succeeded %s\n' % json.dumps(rc.get_payload(), indent=4) else: m = rc.get_message() e = m.split('the logfile errors are:nn') if len(e) > 1: e2 = DKCloudCommandRunner._decompress(e[len(e) - 1]) errors = e2.split('|') re = e[0] + " " + 'the logfile errors are: ' for e in errors: re += '\n%s' % e else: re = m rs = 'DKCloudCommand.get_compiled_serving failed\nmessage: %s\n' % re rc.set_message(rs) return rc
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train
https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L1147-L1172
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.merge_kitchens_improved
def merge_kitchens_improved(dk_api, from_kitchen, to_kitchen): """ returns a string. :param dk_api: -- api object :param from_kitchen: string :param to_kitchen: string -- kitchen name, string :rtype: DKReturnCode """ unresolved_conflicts = DKKitchenDisk.get_unresolved_conflicts(from_kitchen, to_kitchen) if unresolved_conflicts is not None and len(unresolved_conflicts) != 0: msg = DKCloudCommandRunner._print_unresolved_conflicts(unresolved_conflicts) rc = DKReturnCode() rc.set(DKReturnCode.DK_FAIL, msg) return rc resolved_conflicts = DKKitchenDisk.get_resolved_conflicts(from_kitchen, to_kitchen) # if resolved_conflicts is not None and len(resolved_conflicts) != 0: md = dk_api.merge_kitchens_improved(from_kitchen, to_kitchen, resolved_conflicts) if not md.ok(): md.set_message('merge_kitchens_improved error from %s to Kitchen %s\nmessage: %s' % (from_kitchen, to_kitchen, md.get_message())) return md merge_no_conflicts = DKCloudCommandRunner._check_no_merge_conflicts(md.get_payload()) if merge_no_conflicts: msg = DKCloudCommandRunner._print_merge_success(md.get_payload()) current_kitchen = DKKitchenDisk.find_kitchen_name() md.set_message(msg) else: # Found conflicts recipe_name = DKRecipeDisk.find_recipe_name() kitchen_name = DKKitchenDisk.find_kitchen_name() if recipe_name is None and kitchen_name is None: # We are not in a kitchen or recipe folder, so just report the findings rs = DKCloudCommandRunner.print_merge_conflicts(md.get_payload()) md.set_message(rs) else: # We are in a recipe folder, so let's write out the conflicted files. rc = DKCloudCommandRunner.write_merge_conflicts(md.get_payload()) if rc.ok(): md.set_message(rc.get_message()) else: md = rc return md
python
def merge_kitchens_improved(dk_api, from_kitchen, to_kitchen): """ returns a string. :param dk_api: -- api object :param from_kitchen: string :param to_kitchen: string -- kitchen name, string :rtype: DKReturnCode """ unresolved_conflicts = DKKitchenDisk.get_unresolved_conflicts(from_kitchen, to_kitchen) if unresolved_conflicts is not None and len(unresolved_conflicts) != 0: msg = DKCloudCommandRunner._print_unresolved_conflicts(unresolved_conflicts) rc = DKReturnCode() rc.set(DKReturnCode.DK_FAIL, msg) return rc resolved_conflicts = DKKitchenDisk.get_resolved_conflicts(from_kitchen, to_kitchen) # if resolved_conflicts is not None and len(resolved_conflicts) != 0: md = dk_api.merge_kitchens_improved(from_kitchen, to_kitchen, resolved_conflicts) if not md.ok(): md.set_message('merge_kitchens_improved error from %s to Kitchen %s\nmessage: %s' % (from_kitchen, to_kitchen, md.get_message())) return md merge_no_conflicts = DKCloudCommandRunner._check_no_merge_conflicts(md.get_payload()) if merge_no_conflicts: msg = DKCloudCommandRunner._print_merge_success(md.get_payload()) current_kitchen = DKKitchenDisk.find_kitchen_name() md.set_message(msg) else: # Found conflicts recipe_name = DKRecipeDisk.find_recipe_name() kitchen_name = DKKitchenDisk.find_kitchen_name() if recipe_name is None and kitchen_name is None: # We are not in a kitchen or recipe folder, so just report the findings rs = DKCloudCommandRunner.print_merge_conflicts(md.get_payload()) md.set_message(rs) else: # We are in a recipe folder, so let's write out the conflicted files. rc = DKCloudCommandRunner.write_merge_conflicts(md.get_payload()) if rc.ok(): md.set_message(rc.get_message()) else: md = rc return md
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https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L1214-L1257
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.create_order
def create_order(dk_api, kitchen, recipe_name, variation_name, node_name=None): """ returns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param variation_name: string -- name of the recipe variation_name to be run :param node_name: string -- name of the single node to run :rtype: DKReturnCode """ rc = dk_api.create_order(kitchen, recipe_name, variation_name, node_name) if rc.ok(): s = 'Order ID is: %s' % rc.get_payload() else: m = rc.get_message().replace('\\n','\n') e = m.split('the logfile errors are:') if len(e) > 1: e2 = DKCloudCommandRunner._decompress(e[-1]) errors = e2.split('|') re = e[0] + " " + 'the logfile errors are: ' for e in errors: re += '\n%s' % e else: re = m s = 'DKCloudCommand.create_order failed\nmessage: %s\n' % re rc.set_message(s) return rc
python
def create_order(dk_api, kitchen, recipe_name, variation_name, node_name=None): """ returns a string. :param dk_api: -- api object :param kitchen: string :param recipe_name: string -- kitchen name, string :param variation_name: string -- name of the recipe variation_name to be run :param node_name: string -- name of the single node to run :rtype: DKReturnCode """ rc = dk_api.create_order(kitchen, recipe_name, variation_name, node_name) if rc.ok(): s = 'Order ID is: %s' % rc.get_payload() else: m = rc.get_message().replace('\\n','\n') e = m.split('the logfile errors are:') if len(e) > 1: e2 = DKCloudCommandRunner._decompress(e[-1]) errors = e2.split('|') re = e[0] + " " + 'the logfile errors are: ' for e in errors: re += '\n%s' % e else: re = m s = 'DKCloudCommand.create_order failed\nmessage: %s\n' % re rc.set_message(s) return rc
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train
https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L1385-L1411
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner.orderrun_detail
def orderrun_detail(dk_api, kitchen, pd): """ returns a string. :param dk_api: -- api object :param kitchen: string :param pd: dict :rtype: DKReturnCode """ if DKCloudCommandRunner.SUMMARY in pd: display_summary = True else: display_summary = False # always get summary information pd[DKCloudCommandRunner.SUMMARY] = True rc = dk_api.orderrun_detail(kitchen, pd) s = '' if not rc.ok() or not isinstance(rc.get_payload(), list): s = 'Issue with getting order run details\nmessage: %s' % rc.get_message() rc.set_message(s) return rc # we have a list of servings, find the right dict serving_list = rc.get_payload() serving = None if DKCloudCommandRunner.ORDER_RUN_ID in pd: order_run_id = pd[DKCloudCommandRunner.ORDER_RUN_ID] for serv in serving_list: if serv[DKCloudCommandRunner.ORDER_RUN_ID] == order_run_id: serving = serv break elif DKCloudCommandRunner.ORDER_ID in pd: order_id = pd[DKCloudCommandRunner.ORDER_ID] for serv in serving_list: if serv[DKCloudCommandRunner.ORDER_ID] == order_id: serving = serv break else: # find the newest serving dex = -1 latest = None for i, serving in enumerate(serving_list): if DKCloudCommandRunner.ORDER_ID in serving and serving[DKCloudCommandRunner.ORDER_ID] > latest: latest = serving[DKCloudCommandRunner.ORDER_ID] dex = i if dex != -1: serving = serving_list[dex] if serving is None: rc.set(rc.DK_FAIL, "No OrderRun information. Try using 'dk order-list -k %s' to see what is available." % kitchen) return rc # serving now contains the dictionary of the serving to display # pull out the information and put it in the message string of the rc if serving and display_summary: s += '\nORDER RUN SUMMARY\n\n' summary = None if DKCloudCommandRunner.SUMMARY in serving: summary = serving[DKCloudCommandRunner.SUMMARY] pass s += 'Order ID:\t%s\n' % serving[DKCloudCommandRunner.ORDER_ID] orid_from_serving = serving[DKCloudCommandRunner.ORDER_RUN_ID] s += 'Order Run ID:\t%s\n' % orid_from_serving s += 'Status:\t\t%s\n' % serving['status'] s += 'Kitchen:\t%s\n' % kitchen if summary and 'name' in summary: s += 'Recipe:\t\t%s\n' % summary['name'] else: s += 'Recipe:\t\t%s\n' % 'Not available' # variation name is inside the order id, pull it out s += 'Variation:\t%s\n' % orid_from_serving.split('#')[3] if summary and 'start-time' in summary: start_time = summary['start-time'] if isinstance(start_time, basestring): s += 'Start time:\t%s\n' % summary['start-time'].split('.')[0] else: s += 'Start time:\t%s\n' % 'Not available 1' else: s += 'Start time:\t%s\n' % 'Not available 2' run_time = None if summary and 'total-recipe-time' in summary: run_time = summary['total-recipe-time'] if isinstance(run_time, basestring): # Active recipes don't have a run-duration s += 'Run duration:\t%s (H:M:S)\n' % run_time.split('.')[0] else: s += 'Run duration:\t%s\n' % 'Not available' if serving and DKCloudCommandRunner.TESTRESULTS in serving and \ isinstance(serving[DKCloudCommandRunner.TESTRESULTS], basestring): s += '\nTEST RESULTS' s += serving[DKCloudCommandRunner.TESTRESULTS] if serving and DKCloudCommandRunner.TIMINGRESULTS in serving and \ isinstance(serving[DKCloudCommandRunner.TIMINGRESULTS], basestring): s += '\n\nTIMING RESULTS\n\n' s += serving[DKCloudCommandRunner.TIMINGRESULTS] if serving and DKCloudCommandRunner.LOGS in serving and \ isinstance(serving[DKCloudCommandRunner.LOGS], basestring): s += '\n\nLOG\n\n' s += DKCloudCommandRunner._decompress(serving[DKCloudCommandRunner.LOGS]) if 'status' in pd and serving and DKCloudCommandRunner.SUMMARY in serving and \ isinstance(serving[DKCloudCommandRunner.SUMMARY], dict): s += '\nSTEP STATUS\n\n' summary = serving[DKCloudCommandRunner.SUMMARY] # loop through the sorted keys for key in sorted(summary): value = summary[key] if isinstance(value, dict): # node/step info is stored as a dictionary, print the node name (key) and status if 'status' in value: status = value['status'] else: status = 'unknown' s += '%s\t%s\n' % (key, status) if serving and 'runstatus' in pd: s += serving['status'] if serving and 'disp_order_id' in pd and DKCloudCommandRunner.ORDER_ID in serving: s += serving[DKCloudCommandRunner.ORDER_ID] if serving and 'disp_order_run_id' in pd and DKCloudCommandRunner.ORDER_RUN_ID in serving: s += serving[DKCloudCommandRunner.ORDER_RUN_ID] rc.set_message(s) return rc
python
def orderrun_detail(dk_api, kitchen, pd): """ returns a string. :param dk_api: -- api object :param kitchen: string :param pd: dict :rtype: DKReturnCode """ if DKCloudCommandRunner.SUMMARY in pd: display_summary = True else: display_summary = False # always get summary information pd[DKCloudCommandRunner.SUMMARY] = True rc = dk_api.orderrun_detail(kitchen, pd) s = '' if not rc.ok() or not isinstance(rc.get_payload(), list): s = 'Issue with getting order run details\nmessage: %s' % rc.get_message() rc.set_message(s) return rc # we have a list of servings, find the right dict serving_list = rc.get_payload() serving = None if DKCloudCommandRunner.ORDER_RUN_ID in pd: order_run_id = pd[DKCloudCommandRunner.ORDER_RUN_ID] for serv in serving_list: if serv[DKCloudCommandRunner.ORDER_RUN_ID] == order_run_id: serving = serv break elif DKCloudCommandRunner.ORDER_ID in pd: order_id = pd[DKCloudCommandRunner.ORDER_ID] for serv in serving_list: if serv[DKCloudCommandRunner.ORDER_ID] == order_id: serving = serv break else: # find the newest serving dex = -1 latest = None for i, serving in enumerate(serving_list): if DKCloudCommandRunner.ORDER_ID in serving and serving[DKCloudCommandRunner.ORDER_ID] > latest: latest = serving[DKCloudCommandRunner.ORDER_ID] dex = i if dex != -1: serving = serving_list[dex] if serving is None: rc.set(rc.DK_FAIL, "No OrderRun information. Try using 'dk order-list -k %s' to see what is available." % kitchen) return rc # serving now contains the dictionary of the serving to display # pull out the information and put it in the message string of the rc if serving and display_summary: s += '\nORDER RUN SUMMARY\n\n' summary = None if DKCloudCommandRunner.SUMMARY in serving: summary = serving[DKCloudCommandRunner.SUMMARY] pass s += 'Order ID:\t%s\n' % serving[DKCloudCommandRunner.ORDER_ID] orid_from_serving = serving[DKCloudCommandRunner.ORDER_RUN_ID] s += 'Order Run ID:\t%s\n' % orid_from_serving s += 'Status:\t\t%s\n' % serving['status'] s += 'Kitchen:\t%s\n' % kitchen if summary and 'name' in summary: s += 'Recipe:\t\t%s\n' % summary['name'] else: s += 'Recipe:\t\t%s\n' % 'Not available' # variation name is inside the order id, pull it out s += 'Variation:\t%s\n' % orid_from_serving.split('#')[3] if summary and 'start-time' in summary: start_time = summary['start-time'] if isinstance(start_time, basestring): s += 'Start time:\t%s\n' % summary['start-time'].split('.')[0] else: s += 'Start time:\t%s\n' % 'Not available 1' else: s += 'Start time:\t%s\n' % 'Not available 2' run_time = None if summary and 'total-recipe-time' in summary: run_time = summary['total-recipe-time'] if isinstance(run_time, basestring): # Active recipes don't have a run-duration s += 'Run duration:\t%s (H:M:S)\n' % run_time.split('.')[0] else: s += 'Run duration:\t%s\n' % 'Not available' if serving and DKCloudCommandRunner.TESTRESULTS in serving and \ isinstance(serving[DKCloudCommandRunner.TESTRESULTS], basestring): s += '\nTEST RESULTS' s += serving[DKCloudCommandRunner.TESTRESULTS] if serving and DKCloudCommandRunner.TIMINGRESULTS in serving and \ isinstance(serving[DKCloudCommandRunner.TIMINGRESULTS], basestring): s += '\n\nTIMING RESULTS\n\n' s += serving[DKCloudCommandRunner.TIMINGRESULTS] if serving and DKCloudCommandRunner.LOGS in serving and \ isinstance(serving[DKCloudCommandRunner.LOGS], basestring): s += '\n\nLOG\n\n' s += DKCloudCommandRunner._decompress(serving[DKCloudCommandRunner.LOGS]) if 'status' in pd and serving and DKCloudCommandRunner.SUMMARY in serving and \ isinstance(serving[DKCloudCommandRunner.SUMMARY], dict): s += '\nSTEP STATUS\n\n' summary = serving[DKCloudCommandRunner.SUMMARY] # loop through the sorted keys for key in sorted(summary): value = summary[key] if isinstance(value, dict): # node/step info is stored as a dictionary, print the node name (key) and status if 'status' in value: status = value['status'] else: status = 'unknown' s += '%s\t%s\n' % (key, status) if serving and 'runstatus' in pd: s += serving['status'] if serving and 'disp_order_id' in pd and DKCloudCommandRunner.ORDER_ID in serving: s += serving[DKCloudCommandRunner.ORDER_ID] if serving and 'disp_order_run_id' in pd and DKCloudCommandRunner.ORDER_RUN_ID in serving: s += serving[DKCloudCommandRunner.ORDER_RUN_ID] rc.set_message(s) return rc
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returns a string. :param dk_api: -- api object :param kitchen: string :param pd: dict :rtype: DKReturnCode
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https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L1472-L1601
DataKitchen/DKCloudCommand
DKCloudCommand/modules/DKCloudCommandRunner.py
DKCloudCommandRunner._split_one_end
def _split_one_end(path): """ Utility function for splitting off the very end part of a path. """ s = path.rsplit('/', 1) if len(s) == 1: return s[0], '' else: return tuple(s)
python
def _split_one_end(path): """ Utility function for splitting off the very end part of a path. """ s = path.rsplit('/', 1) if len(s) == 1: return s[0], '' else: return tuple(s)
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https://github.com/DataKitchen/DKCloudCommand/blob/1cf9cb08ab02f063eef6b5c4b327af142991daa3/DKCloudCommand/modules/DKCloudCommandRunner.py#L1820-L1828
arubertoson/maya-launcher
mayalauncher.py
get_system_config_directory
def get_system_config_directory(): """ Return platform specific config directory. """ if platform.system().lower() == 'windows': _cfg_directory = Path(os.getenv('APPDATA') or '~') elif platform.system().lower() == 'darwin': _cfg_directory = Path('~', 'Library', 'Preferences') else: _cfg_directory = Path(os.getenv('XDG_CONFIG_HOME') or '~/.config') logger.debug('Fetching configt directory for {}.' .format(platform.system())) return _cfg_directory.joinpath(Path('mayalauncher/.config'))
python
def get_system_config_directory(): """ Return platform specific config directory. """ if platform.system().lower() == 'windows': _cfg_directory = Path(os.getenv('APPDATA') or '~') elif platform.system().lower() == 'darwin': _cfg_directory = Path('~', 'Library', 'Preferences') else: _cfg_directory = Path(os.getenv('XDG_CONFIG_HOME') or '~/.config') logger.debug('Fetching configt directory for {}.' .format(platform.system())) return _cfg_directory.joinpath(Path('mayalauncher/.config'))
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https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L36-L49
arubertoson/maya-launcher
mayalauncher.py
get_version_exec_mapping_from_path
def get_version_exec_mapping_from_path(path): """ Find valid application version from given path object and return a mapping of version, executable. """ version_executable = {} logger.debug('Getting exes from path: {}'.format(path)) for sub_dir in path.iterdir(): if not sub_dir.name.startswith(APPLICATION_NAME): continue release = sub_dir.name.split(APPLICATION_NAME)[-1] executable = Path(sub_dir, 'bin').glob('maya.exe').next() version_executable[release] = str(executable) logger.debug('Found exes for: {}'.format(version_executable.keys())) return version_executable
python
def get_version_exec_mapping_from_path(path): """ Find valid application version from given path object and return a mapping of version, executable. """ version_executable = {} logger.debug('Getting exes from path: {}'.format(path)) for sub_dir in path.iterdir(): if not sub_dir.name.startswith(APPLICATION_NAME): continue release = sub_dir.name.split(APPLICATION_NAME)[-1] executable = Path(sub_dir, 'bin').glob('maya.exe').next() version_executable[release] = str(executable) logger.debug('Found exes for: {}'.format(version_executable.keys())) return version_executable
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L52-L68
arubertoson/maya-launcher
mayalauncher.py
find_applications_on_system
def find_applications_on_system(): """ Collect maya version from Autodesk PATH if exists, else try looking for custom executable paths from config file. """ # First we collect maya versions from the Autodesk folder we presume # is addeed to the system environment "PATH" path_env = os.getenv('PATH').split(os.pathsep) versions = {} for each in path_env: path = Path(os.path.expandvars(each)) if not path.exists(): continue if path.name.endswith(DEVELOPER_NAME): if not path.exists(): continue versions.update(get_version_exec_mapping_from_path(path)) return versions
python
def find_applications_on_system(): """ Collect maya version from Autodesk PATH if exists, else try looking for custom executable paths from config file. """ # First we collect maya versions from the Autodesk folder we presume # is addeed to the system environment "PATH" path_env = os.getenv('PATH').split(os.pathsep) versions = {} for each in path_env: path = Path(os.path.expandvars(each)) if not path.exists(): continue if path.name.endswith(DEVELOPER_NAME): if not path.exists(): continue versions.update(get_version_exec_mapping_from_path(path)) return versions
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https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L71-L88
arubertoson/maya-launcher
mayalauncher.py
build_config
def build_config(config_file=get_system_config_directory()): """ Construct the config object from necessary elements. """ config = Config(config_file, allow_no_value=True) application_versions = find_applications_on_system() # Add found versions to config if they don't exist. Versions found # in the config file takes precedence over versions found in PATH. for item in application_versions.iteritems(): if not config.has_option(Config.EXECUTABLES, item[0]): config.set(Config.EXECUTABLES, item[0], item[1]) return config
python
def build_config(config_file=get_system_config_directory()): """ Construct the config object from necessary elements. """ config = Config(config_file, allow_no_value=True) application_versions = find_applications_on_system() # Add found versions to config if they don't exist. Versions found # in the config file takes precedence over versions found in PATH. for item in application_versions.iteritems(): if not config.has_option(Config.EXECUTABLES, item[0]): config.set(Config.EXECUTABLES, item[0], item[1]) return config
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L167-L179
arubertoson/maya-launcher
mayalauncher.py
get_environment_paths
def get_environment_paths(config, env): """ Get environment paths from given environment variable. """ if env is None: return config.get(Config.DEFAULTS, 'environment') # Config option takes precedence over environment key. if config.has_option(Config.ENVIRONMENTS, env): env = config.get(Config.ENVIRONMENTS, env).replace(' ', '').split(';') else: env = os.getenv(env) if env: env = env.split(os.pathsep) return [i for i in env if i]
python
def get_environment_paths(config, env): """ Get environment paths from given environment variable. """ if env is None: return config.get(Config.DEFAULTS, 'environment') # Config option takes precedence over environment key. if config.has_option(Config.ENVIRONMENTS, env): env = config.get(Config.ENVIRONMENTS, env).replace(' ', '').split(';') else: env = os.getenv(env) if env: env = env.split(os.pathsep) return [i for i in env if i]
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Get environment paths from given environment variable.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L350-L364
arubertoson/maya-launcher
mayalauncher.py
build_maya_environment
def build_maya_environment(config, env=None, arg_paths=None): """ Construct maya environment. """ maya_env = MayaEnvironment() maya_env.exclude_pattern = config.get_list(Config.PATTERNS, 'exclude') maya_env.icon_extensions = config.get_list(Config.PATTERNS, 'icon_ext') env = get_environment_paths(config, env) if not env and arg_paths is None: return logger.info('Using maya factory environment setup.') logger.debug('Launching with addon paths: {}'.format(arg_paths)) logger.debug('Launching with environment paths: {}'.format(env)) if arg_paths: arg_paths = arg_paths.split(' ') for directory in flatten_combine_lists(env, arg_paths or ''): maya_env.traverse_path_for_valid_application_paths(directory) return maya_env
python
def build_maya_environment(config, env=None, arg_paths=None): """ Construct maya environment. """ maya_env = MayaEnvironment() maya_env.exclude_pattern = config.get_list(Config.PATTERNS, 'exclude') maya_env.icon_extensions = config.get_list(Config.PATTERNS, 'icon_ext') env = get_environment_paths(config, env) if not env and arg_paths is None: return logger.info('Using maya factory environment setup.') logger.debug('Launching with addon paths: {}'.format(arg_paths)) logger.debug('Launching with environment paths: {}'.format(env)) if arg_paths: arg_paths = arg_paths.split(' ') for directory in flatten_combine_lists(env, arg_paths or ''): maya_env.traverse_path_for_valid_application_paths(directory) return maya_env
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Construct maya environment.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L367-L386
arubertoson/maya-launcher
mayalauncher.py
launch
def launch(exec_, args): """ Launches application. """ if not exec_: raise RuntimeError( 'Mayalauncher could not find a maya executable, please specify' 'a path in the config file (-e) or add the {} directory location' 'to your PATH system environment.'.format(DEVELOPER_NAME) ) # Launch Maya if args.debug: return watched = WatchFile() cmd = [exec_] if args.file is None else [exec_, args.file] cmd.extend(['-hideConsole', '-log', watched.path]) if args.debug: cmd.append('-noAutoloadPlugins') maya = subprocess.Popen(cmd) # Maya 2016 stupid clic ipm # os.environ['MAYA_DISABLE_CLIC_IPM'] = '1' # os.environ['MAYA_DISABLE_CIP'] = '1' # os.environ['MAYA_OPENCL_IGNORE_DRIVER_VERSION'] = '1' while True: time.sleep(1) maya.poll() watched.check() if maya.returncode is not None: if not maya.returncode == 0: maya = subprocess.Popen(cmd) else: watched.stop() break
python
def launch(exec_, args): """ Launches application. """ if not exec_: raise RuntimeError( 'Mayalauncher could not find a maya executable, please specify' 'a path in the config file (-e) or add the {} directory location' 'to your PATH system environment.'.format(DEVELOPER_NAME) ) # Launch Maya if args.debug: return watched = WatchFile() cmd = [exec_] if args.file is None else [exec_, args.file] cmd.extend(['-hideConsole', '-log', watched.path]) if args.debug: cmd.append('-noAutoloadPlugins') maya = subprocess.Popen(cmd) # Maya 2016 stupid clic ipm # os.environ['MAYA_DISABLE_CLIC_IPM'] = '1' # os.environ['MAYA_DISABLE_CIP'] = '1' # os.environ['MAYA_OPENCL_IGNORE_DRIVER_VERSION'] = '1' while True: time.sleep(1) maya.poll() watched.check() if maya.returncode is not None: if not maya.returncode == 0: maya = subprocess.Popen(cmd) else: watched.stop() break
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Launches application.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L443-L481
arubertoson/maya-launcher
mayalauncher.py
main
def main(): """ Main function of maya launcher. Parses the arguments and tries to launch maya with given them. """ config = build_config() parser = argparse.ArgumentParser( description=""" Maya Launcher is a useful script that tries to deal with all important system environments maya uses when starting up. It aims to streamline the setup process of maya to a simple string instead of constantly having to make sure paths are setup correctly. """ ) parser.add_argument( 'file', nargs='?', default=None, help=""" file is an optional argument telling maya what file to open with the launcher. """) parser.add_argument( '-v', '--version', type=str, choices=get_executable_choices(dict(config.items( Config.EXECUTABLES))), help=""" Launch Maya with given version. """) parser.add_argument( '-env', '--environment', metavar='env', type=str, default=config.get(Config.DEFAULTS, 'environment'), help=""" Launch maya with given environemnt, if no environment is specified will try to use default value. If not default value is specified Maya will behave with factory environment setup. """) parser.add_argument( '-p', '--path', metavar='path', type=str, nargs='+', help=""" Path is an optional argument that takes an unlimited number of paths to use for environment creation. Useful if you don't want to create a environment variable. Just pass the path you want to use. """) parser.add_argument( '-e', '--edit', action='store_true', help=""" Edit config file. """) parser.add_argument( '-d', '--debug', action='store_true', help=""" Start maya in dev mode, autoload on plugins are turned off. """) # Parse the arguments args = parser.parse_args() if args.edit: return config.edit() if args.debug: logger.setLevel(logging.DEBUG) # Get executable from either default value in config or given value. # If neither exists exit launcher. if args.version is None: exec_default = config.get(Config.DEFAULTS, 'executable') if not exec_default and config.items(Config.EXECUTABLES): items = dict(config.items(Config.EXECUTABLES)) exec_ = items[sorted(items.keys(), reverse=True)[0]] else: exec_ = exec_default else: exec_ = config.get(Config.EXECUTABLES, args.version) build_maya_environment(config, args.environment, args.path) logger.info('\nDone building maya environment, launching: \n{}\n'.format(exec_)) launch(exec_, args)
python
def main(): """ Main function of maya launcher. Parses the arguments and tries to launch maya with given them. """ config = build_config() parser = argparse.ArgumentParser( description=""" Maya Launcher is a useful script that tries to deal with all important system environments maya uses when starting up. It aims to streamline the setup process of maya to a simple string instead of constantly having to make sure paths are setup correctly. """ ) parser.add_argument( 'file', nargs='?', default=None, help=""" file is an optional argument telling maya what file to open with the launcher. """) parser.add_argument( '-v', '--version', type=str, choices=get_executable_choices(dict(config.items( Config.EXECUTABLES))), help=""" Launch Maya with given version. """) parser.add_argument( '-env', '--environment', metavar='env', type=str, default=config.get(Config.DEFAULTS, 'environment'), help=""" Launch maya with given environemnt, if no environment is specified will try to use default value. If not default value is specified Maya will behave with factory environment setup. """) parser.add_argument( '-p', '--path', metavar='path', type=str, nargs='+', help=""" Path is an optional argument that takes an unlimited number of paths to use for environment creation. Useful if you don't want to create a environment variable. Just pass the path you want to use. """) parser.add_argument( '-e', '--edit', action='store_true', help=""" Edit config file. """) parser.add_argument( '-d', '--debug', action='store_true', help=""" Start maya in dev mode, autoload on plugins are turned off. """) # Parse the arguments args = parser.parse_args() if args.edit: return config.edit() if args.debug: logger.setLevel(logging.DEBUG) # Get executable from either default value in config or given value. # If neither exists exit launcher. if args.version is None: exec_default = config.get(Config.DEFAULTS, 'executable') if not exec_default and config.items(Config.EXECUTABLES): items = dict(config.items(Config.EXECUTABLES)) exec_ = items[sorted(items.keys(), reverse=True)[0]] else: exec_ = exec_default else: exec_ = config.get(Config.EXECUTABLES, args.version) build_maya_environment(config, args.environment, args.path) logger.info('\nDone building maya environment, launching: \n{}\n'.format(exec_)) launch(exec_, args)
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Main function of maya launcher. Parses the arguments and tries to launch maya with given them.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L484-L579
arubertoson/maya-launcher
mayalauncher.py
Config._create_default_config_file
def _create_default_config_file(self): """ If config file does not exists create and set default values. """ logger.info('Initialize Maya launcher, creating config file...\n') self.add_section(self.DEFAULTS) self.add_section(self.PATTERNS) self.add_section(self.ENVIRONMENTS) self.add_section(self.EXECUTABLES) self.set(self.DEFAULTS, 'executable', None) self.set(self.DEFAULTS, 'environment', None) self.set(self.PATTERNS, 'exclude', ', '.join(self.EXLUDE_PATTERNS)) self.set(self.PATTERNS, 'icon_ext', ', '.join(self.ICON_EXTENSIONS)) self.config_file.parent.mkdir(exist_ok=True) self.config_file.touch() with self.config_file.open('wb') as f: self.write(f) # If this function is run inform the user that a new file has been # created. sys.exit('Maya launcher has successfully created config file at:\n' ' "{}"'.format(str(self.config_file)))
python
def _create_default_config_file(self): """ If config file does not exists create and set default values. """ logger.info('Initialize Maya launcher, creating config file...\n') self.add_section(self.DEFAULTS) self.add_section(self.PATTERNS) self.add_section(self.ENVIRONMENTS) self.add_section(self.EXECUTABLES) self.set(self.DEFAULTS, 'executable', None) self.set(self.DEFAULTS, 'environment', None) self.set(self.PATTERNS, 'exclude', ', '.join(self.EXLUDE_PATTERNS)) self.set(self.PATTERNS, 'icon_ext', ', '.join(self.ICON_EXTENSIONS)) self.config_file.parent.mkdir(exist_ok=True) self.config_file.touch() with self.config_file.open('wb') as f: self.write(f) # If this function is run inform the user that a new file has been # created. sys.exit('Maya launcher has successfully created config file at:\n' ' "{}"'.format(str(self.config_file)))
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If config file does not exists create and set default values.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L113-L135
arubertoson/maya-launcher
mayalauncher.py
Config.get_list
def get_list(self, section, option): """ Convert string value to list object. """ if self.has_option(section, option): return self.get(section, option).replace(' ', '').split(',') else: raise KeyError('{} with {} does not exist.'.format(section, option))
python
def get_list(self, section, option): """ Convert string value to list object. """ if self.has_option(section, option): return self.get(section, option).replace(' ', '').split(',') else: raise KeyError('{} with {} does not exist.'.format(section, option))
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Convert string value to list object.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L137-L145
arubertoson/maya-launcher
mayalauncher.py
Config.edit
def edit(self): """ Edit file with default os application. """ if platform.system().lower() == 'windows': os.startfile(str(self.config_file)) else: if platform.system().lower() == 'darwin': call = 'open' else: call = 'xdg-open' subprocess.call([call, self.config_file])
python
def edit(self): """ Edit file with default os application. """ if platform.system().lower() == 'windows': os.startfile(str(self.config_file)) else: if platform.system().lower() == 'darwin': call = 'open' else: call = 'xdg-open' subprocess.call([call, self.config_file])
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Edit file with default os application.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L153-L164
arubertoson/maya-launcher
mayalauncher.py
MayaEnvironment.is_excluded
def is_excluded(self, path, exclude=None): """ Return if path is in exclude pattern. """ for pattern in (exclude or self.exclude_pattern): if path.match(pattern): return True else: return False
python
def is_excluded(self, path, exclude=None): """ Return if path is in exclude pattern. """ for pattern in (exclude or self.exclude_pattern): if path.match(pattern): return True else: return False
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Return if path is in exclude pattern.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L258-L266
arubertoson/maya-launcher
mayalauncher.py
MayaEnvironment.get_directories_with_extensions
def get_directories_with_extensions(self, start, extensions=None): """ Look for directories with image extensions in given directory and return a list with found dirs. .. note:: In deep file structures this might get pretty slow. """ return set([p.parent for ext in extensions for p in start.rglob(ext)])
python
def get_directories_with_extensions(self, start, extensions=None): """ Look for directories with image extensions in given directory and return a list with found dirs. .. note:: In deep file structures this might get pretty slow. """ return set([p.parent for ext in extensions for p in start.rglob(ext)])
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Look for directories with image extensions in given directory and return a list with found dirs. .. note:: In deep file structures this might get pretty slow.
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L288-L295
arubertoson/maya-launcher
mayalauncher.py
MayaEnvironment.put_path
def put_path(self, path): """ Given path identify in which environment the path belong to and append it. """ if self.is_package(path): logger.debug('PYTHON PACKAGE: {}'.format(path)) self.python_paths.append(path.parent) site.addsitedir(str(path.parent)) xbmdirs = self.get_directories_with_extensions( path, self.icon_extensions, ) self.xbmlang_paths.extend(xbmdirs) return if self.has_next(path.glob('*.' + self.MEL)): logger.debug('MEL: {}'.format(str(path))) self.script_paths.append(path) if self.has_next(path.glob('*.' + self.PYTHON)): logger.debug('PYTHONPATH: {}'.format(str(path))) self.python_paths.append(path) site.addsitedir(str(path)) if self.PLUGIN in list(path.iterdir()): logger.debug('PLUG-IN: {}'.format(str(path))) self.plug_in_paths.append(path) for ext in self.icon_extensions: if self.has_next(path.glob('*.' + ext)): logger.debug('XBM: {}.'.format(str(path))) self.xbmlang_paths.append(path) break
python
def put_path(self, path): """ Given path identify in which environment the path belong to and append it. """ if self.is_package(path): logger.debug('PYTHON PACKAGE: {}'.format(path)) self.python_paths.append(path.parent) site.addsitedir(str(path.parent)) xbmdirs = self.get_directories_with_extensions( path, self.icon_extensions, ) self.xbmlang_paths.extend(xbmdirs) return if self.has_next(path.glob('*.' + self.MEL)): logger.debug('MEL: {}'.format(str(path))) self.script_paths.append(path) if self.has_next(path.glob('*.' + self.PYTHON)): logger.debug('PYTHONPATH: {}'.format(str(path))) self.python_paths.append(path) site.addsitedir(str(path)) if self.PLUGIN in list(path.iterdir()): logger.debug('PLUG-IN: {}'.format(str(path))) self.plug_in_paths.append(path) for ext in self.icon_extensions: if self.has_next(path.glob('*.' + ext)): logger.debug('XBM: {}.'.format(str(path))) self.xbmlang_paths.append(path) break
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L297-L330
arubertoson/maya-launcher
mayalauncher.py
MayaEnvironment.traverse_path_for_valid_application_paths
def traverse_path_for_valid_application_paths(self, top_path): """ For every path beneath top path that does not contain the exclude pattern look for python, mel and images and place them in their corresponding system environments. """ self.put_path(Path(top_path)) for p in self._walk(top_path): self.put_path(p)
python
def traverse_path_for_valid_application_paths(self, top_path): """ For every path beneath top path that does not contain the exclude pattern look for python, mel and images and place them in their corresponding system environments. """ self.put_path(Path(top_path)) for p in self._walk(top_path): self.put_path(p)
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train
https://github.com/arubertoson/maya-launcher/blob/9bd82cce7edf4afb803dd8044107a324e93f197f/mayalauncher.py#L332-L340
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.check_correct_host
def check_correct_host(self): """The method checks whether the host is correctly set and whether it can configure the connection to this host. Does not check the base host knoema.com """ if self._host == 'knoema.com': return url = self._get_url('/api/1.0/frontend/tags') req = urllib.request.Request(url) try: resp = urllib.request.urlopen(req) except: raise ValueError('The specified host {} does not exist'.format(self._host))
python
def check_correct_host(self): """The method checks whether the host is correctly set and whether it can configure the connection to this host. Does not check the base host knoema.com """ if self._host == 'knoema.com': return url = self._get_url('/api/1.0/frontend/tags') req = urllib.request.Request(url) try: resp = urllib.request.urlopen(req) except: raise ValueError('The specified host {} does not exist'.format(self._host))
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The method checks whether the host is correctly set and whether it can configure the connection to this host. Does not check the base host knoema.com
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L87-L96
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.get_dataset
def get_dataset(self, datasetid): """The method is getting information about dataset byt it's id""" path = '/api/1.0/meta/dataset/{}' return self._api_get(definition.Dataset, path.format(datasetid))
python
def get_dataset(self, datasetid): """The method is getting information about dataset byt it's id""" path = '/api/1.0/meta/dataset/{}' return self._api_get(definition.Dataset, path.format(datasetid))
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L98-L102
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.get_dimension
def get_dimension(self, dataset, dimension): """The method is getting information about dimension with items""" path = '/api/1.0/meta/dataset/{}/dimension/{}' return self._api_get(definition.Dimension, path.format(dataset, dimension))
python
def get_dimension(self, dataset, dimension): """The method is getting information about dimension with items""" path = '/api/1.0/meta/dataset/{}/dimension/{}' return self._api_get(definition.Dimension, path.format(dataset, dimension))
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L104-L108
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.get_daterange
def get_daterange(self, dataset): """The method is getting information about date range of dataset""" path = '/api/1.0/meta/dataset/{}/daterange' return self._api_get(definition.DateRange, path.format(dataset))
python
def get_daterange(self, dataset): """The method is getting information about date range of dataset""" path = '/api/1.0/meta/dataset/{}/daterange' return self._api_get(definition.DateRange, path.format(dataset))
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The method is getting information about date range of dataset
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L110-L114
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.get_data
def get_data(self, pivotrequest): """The method is getting data by pivot request""" path = '/api/1.0/data/pivot/' return self._api_post(definition.PivotResponse, path, pivotrequest)
python
def get_data(self, pivotrequest): """The method is getting data by pivot request""" path = '/api/1.0/data/pivot/' return self._api_post(definition.PivotResponse, path, pivotrequest)
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The method is getting data by pivot request
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L116-L120
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.get_data_raw
def get_data_raw(self, request): """The method is getting data by raw request""" path = '/api/1.0/data/raw/' res = self._api_post(definition.RawDataResponse, path, request) token = res.continuation_token while token is not None: res2 = self.get_data_raw_with_token(token) res.series += res2.series token = res2.continuation_token return res
python
def get_data_raw(self, request): """The method is getting data by raw request""" path = '/api/1.0/data/raw/' res = self._api_post(definition.RawDataResponse, path, request) token = res.continuation_token while token is not None: res2 = self.get_data_raw_with_token(token) res.series += res2.series token = res2.continuation_token return res
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The method is getting data by raw request
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L122-L131
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.get_mnemonics
def get_mnemonics (self, mnemonics): """The method get series by mnemonics""" path = '/api/1.0/data/mnemonics?mnemonics={0}' return self._api_get(definition.MnemonicsResponseList, path.format(mnemonics))
python
def get_mnemonics (self, mnemonics): """The method get series by mnemonics""" path = '/api/1.0/data/mnemonics?mnemonics={0}' return self._api_get(definition.MnemonicsResponseList, path.format(mnemonics))
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The method get series by mnemonics
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L137-L140
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.upload_file
def upload_file(self, file): """The method is posting file to the remote server""" url = self._get_url('/api/1.0/upload/post') fcontent = FileContent(file) binary_data = fcontent.get_binary() headers = self._get_request_headers() req = urllib.request.Request(url, binary_data, headers) req.add_header('Content-type', fcontent.get_content_type()) req.add_header('Content-length', len(binary_data)) resp = urllib.request.urlopen(req) return definition.UploadPostResponse(_response_to_json(resp))
python
def upload_file(self, file): """The method is posting file to the remote server""" url = self._get_url('/api/1.0/upload/post') fcontent = FileContent(file) binary_data = fcontent.get_binary() headers = self._get_request_headers() req = urllib.request.Request(url, binary_data, headers) req.add_header('Content-type', fcontent.get_content_type()) req.add_header('Content-length', len(binary_data)) resp = urllib.request.urlopen(req) return definition.UploadPostResponse(_response_to_json(resp))
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The method is posting file to the remote server
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L142-L156
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.upload_verify
def upload_verify(self, file_location, dataset=None): """This method is verifiing posted file on server""" path = '/api/1.0/upload/verify' query = 'doNotGenerateAdvanceReport=true&filePath={}'.format(file_location) if dataset: query = 'doNotGenerateAdvanceReport=true&filePath={}&datasetId={}'.format(file_location, dataset) return self._api_get(definition.UploadVerifyResponse, path, query)
python
def upload_verify(self, file_location, dataset=None): """This method is verifiing posted file on server""" path = '/api/1.0/upload/verify' query = 'doNotGenerateAdvanceReport=true&filePath={}'.format(file_location) if dataset: query = 'doNotGenerateAdvanceReport=true&filePath={}&datasetId={}'.format(file_location, dataset) return self._api_get(definition.UploadVerifyResponse, path, query)
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This method is verifiing posted file on server
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L158-L166
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.upload_submit
def upload_submit(self, upload_request): """The method is submitting dataset upload""" path = '/api/1.0/upload/save' return self._api_post(definition.DatasetUploadResponse, path, upload_request)
python
def upload_submit(self, upload_request): """The method is submitting dataset upload""" path = '/api/1.0/upload/save' return self._api_post(definition.DatasetUploadResponse, path, upload_request)
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The method is submitting dataset upload
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L168-L172
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.upload_status
def upload_status(self, upload_id): """The method is checking status of uploaded dataset""" path = '/api/1.0/upload/status' query = 'id={}'.format(upload_id) return self._api_get(definition.DatasetUploadStatusResponse, path, query)
python
def upload_status(self, upload_id): """The method is checking status of uploaded dataset""" path = '/api/1.0/upload/status' query = 'id={}'.format(upload_id) return self._api_get(definition.DatasetUploadStatusResponse, path, query)
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The method is checking status of uploaded dataset
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L174-L179
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.upload
def upload(self, file_path, dataset=None, public=False): """Use this function to upload data to Knoema dataset.""" upload_status = self.upload_file(file_path) err_msg = 'Dataset has not been uploaded to the remote host' if not upload_status.successful: msg = '{}, because of the following error: {}'.format(err_msg, upload_status.error) raise ValueError(msg) err_msg = 'File has not been verified' upload_ver_status = self.upload_verify(upload_status.properties.location, dataset) if not upload_ver_status.successful: ver_err = '\r\n'.join(upload_ver_status.errors) msg = '{}, because of the following error(s): {}'.format(err_msg, ver_err) raise ValueError(msg) ds_upload = definition.DatasetUpload(upload_ver_status, upload_status, dataset, public) ds_upload_submit_result = self.upload_submit(ds_upload) err_msg = 'Dataset has not been saved to the database' if ds_upload_submit_result.status == 'failed': ver_err = '\r\n'.join(ds_upload_submit_result.errors) msg = '{}, because of the following error(s): {}'.format(err_msg, ver_err) raise ValueError(msg) ds_upload_result = None while True: ds_upload_result = self.upload_status(ds_upload_submit_result.submit_id) if ds_upload_result.status == 'pending' or ds_upload_result.status == 'processing': time.sleep(5) else: break if ds_upload_result.status != 'successful': ver_err = '\r\n'.join(ds_upload_result.errors) msg = '{}, because of the following error(s): {}'.format(err_msg, ver_err) raise ValueError(msg) return ds_upload_result.dataset
python
def upload(self, file_path, dataset=None, public=False): """Use this function to upload data to Knoema dataset.""" upload_status = self.upload_file(file_path) err_msg = 'Dataset has not been uploaded to the remote host' if not upload_status.successful: msg = '{}, because of the following error: {}'.format(err_msg, upload_status.error) raise ValueError(msg) err_msg = 'File has not been verified' upload_ver_status = self.upload_verify(upload_status.properties.location, dataset) if not upload_ver_status.successful: ver_err = '\r\n'.join(upload_ver_status.errors) msg = '{}, because of the following error(s): {}'.format(err_msg, ver_err) raise ValueError(msg) ds_upload = definition.DatasetUpload(upload_ver_status, upload_status, dataset, public) ds_upload_submit_result = self.upload_submit(ds_upload) err_msg = 'Dataset has not been saved to the database' if ds_upload_submit_result.status == 'failed': ver_err = '\r\n'.join(ds_upload_submit_result.errors) msg = '{}, because of the following error(s): {}'.format(err_msg, ver_err) raise ValueError(msg) ds_upload_result = None while True: ds_upload_result = self.upload_status(ds_upload_submit_result.submit_id) if ds_upload_result.status == 'pending' or ds_upload_result.status == 'processing': time.sleep(5) else: break if ds_upload_result.status != 'successful': ver_err = '\r\n'.join(ds_upload_result.errors) msg = '{}, because of the following error(s): {}'.format(err_msg, ver_err) raise ValueError(msg) return ds_upload_result.dataset
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L181-L218
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.delete
def delete(self, dataset): """The method is deleting dataset by it's id""" url = self._get_url('/api/1.0/meta/dataset/{}/delete'.format(dataset)) json_data = '' binary_data = json_data.encode() headers = self._get_request_headers() req = urllib.request.Request(url, binary_data, headers) resp = urllib.request.urlopen(req) str_response = resp.read().decode('utf-8') if str_response != '"successful"' or resp.status < 200 or resp.status >= 300: msg = 'Dataset has not been deleted, because of the following error(s): {}'.format(str_response) raise ValueError(msg)
python
def delete(self, dataset): """The method is deleting dataset by it's id""" url = self._get_url('/api/1.0/meta/dataset/{}/delete'.format(dataset)) json_data = '' binary_data = json_data.encode() headers = self._get_request_headers() req = urllib.request.Request(url, binary_data, headers) resp = urllib.request.urlopen(req) str_response = resp.read().decode('utf-8') if str_response != '"successful"' or resp.status < 200 or resp.status >= 300: msg = 'Dataset has not been deleted, because of the following error(s): {}'.format(str_response) raise ValueError(msg)
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The method is deleting dataset by it's id
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L220-L234
Knoema/knoema-python-driver
knoema/api_client.py
ApiClient.verify
def verify(self, dataset, publication_date, source, refernce_url): """The method is verifying dataset by it's id""" path = '/api/1.0/meta/verifydataset' req = definition.DatasetVerifyRequest(dataset, publication_date, source, refernce_url) result = self._api_post(definition.DatasetVerifyResponse, path, req) if result.status == 'failed': ver_err = '\r\n'.join(result.errors) msg = 'Dataset has not been verified, because of the following error(s): {}'.format(ver_err) raise ValueError(msg)
python
def verify(self, dataset, publication_date, source, refernce_url): """The method is verifying dataset by it's id""" path = '/api/1.0/meta/verifydataset' req = definition.DatasetVerifyRequest(dataset, publication_date, source, refernce_url) result = self._api_post(definition.DatasetVerifyResponse, path, req) if result.status == 'failed': ver_err = '\r\n'.join(result.errors) msg = 'Dataset has not been verified, because of the following error(s): {}'.format(ver_err) raise ValueError(msg)
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The method is verifying dataset by it's id
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L236-L245
Knoema/knoema-python-driver
knoema/api_client.py
FileContent.get_binary
def get_binary(self): """Return a binary buffer containing the file content""" content_disp = 'Content-Disposition: form-data; name="file"; filename="{}"' stream = io.BytesIO() stream.write(_string_to_binary('--{}'.format(self.boundary))) stream.write(_crlf()) stream.write(_string_to_binary(content_disp.format(self.file_name))) stream.write(_crlf()) stream.write(_crlf()) stream.write(self.body) stream.write(_crlf()) stream.write(_string_to_binary('--{}--'.format(self.boundary))) stream.write(_crlf()) return stream.getvalue()
python
def get_binary(self): """Return a binary buffer containing the file content""" content_disp = 'Content-Disposition: form-data; name="file"; filename="{}"' stream = io.BytesIO() stream.write(_string_to_binary('--{}'.format(self.boundary))) stream.write(_crlf()) stream.write(_string_to_binary(content_disp.format(self.file_name))) stream.write(_crlf()) stream.write(_crlf()) stream.write(self.body) stream.write(_crlf()) stream.write(_string_to_binary('--{}--'.format(self.boundary))) stream.write(_crlf()) return stream.getvalue()
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train
https://github.com/Knoema/knoema-python-driver/blob/e98b13db3e4df51c208c272e2977bfbe4c6e5532/knoema/api_client.py#L260-L276
Locu/chronology
pykronos/pykronos/utils/cache.py
QueryCache._scratch_stream_name
def _scratch_stream_name(self): """ A unique cache stream name for this QueryCache. Hashes the necessary facts about this QueryCache to generate a unique cache stream name. Different `query_function` implementations at different `bucket_width` values will be cached to different streams. TODO(marcua): This approach won't work for dynamically-generated functions. We will want to either: 1) Hash the function closure/containing scope. 2) Ditch this approach and rely on the caller to tell us all the information that makes this function unique. """ query_details = [ str(QueryCache.QUERY_CACHE_VERSION), str(self._bucket_width), binascii.b2a_hex(marshal.dumps(self._query_function.func_code)), str(self._query_function_args), str(self._query_function_kwargs), ] return hashlib.sha512('$'.join(query_details)).hexdigest()[:20]
python
def _scratch_stream_name(self): """ A unique cache stream name for this QueryCache. Hashes the necessary facts about this QueryCache to generate a unique cache stream name. Different `query_function` implementations at different `bucket_width` values will be cached to different streams. TODO(marcua): This approach won't work for dynamically-generated functions. We will want to either: 1) Hash the function closure/containing scope. 2) Ditch this approach and rely on the caller to tell us all the information that makes this function unique. """ query_details = [ str(QueryCache.QUERY_CACHE_VERSION), str(self._bucket_width), binascii.b2a_hex(marshal.dumps(self._query_function.func_code)), str(self._query_function_args), str(self._query_function_kwargs), ] return hashlib.sha512('$'.join(query_details)).hexdigest()[:20]
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train
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Locu/chronology
pykronos/pykronos/utils/cache.py
QueryCache._bucket_time
def _bucket_time(self, event_time): """ The seconds since epoch that represent a computed bucket. An event bucket is the time of the earliest possible event for that `bucket_width`. Example: if `bucket_width = timedelta(minutes=10)`, bucket times will be the number of seconds since epoch at 12:00, 12:10, ... on each day. """ event_time = kronos_time_to_epoch_time(event_time) return event_time - (event_time % self._bucket_width)
python
def _bucket_time(self, event_time): """ The seconds since epoch that represent a computed bucket. An event bucket is the time of the earliest possible event for that `bucket_width`. Example: if `bucket_width = timedelta(minutes=10)`, bucket times will be the number of seconds since epoch at 12:00, 12:10, ... on each day. """ event_time = kronos_time_to_epoch_time(event_time) return event_time - (event_time % self._bucket_width)
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The seconds since epoch that represent a computed bucket. An event bucket is the time of the earliest possible event for that `bucket_width`. Example: if `bucket_width = timedelta(minutes=10)`, bucket times will be the number of seconds since epoch at 12:00, 12:10, ... on each day.
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train
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Locu/chronology
pykronos/pykronos/utils/cache.py
QueryCache._bucket_events
def _bucket_events(self, event_iterable): """ Convert an iterable of events into an iterable of lists of events per bucket. """ current_bucket_time = None current_bucket_events = None for event in event_iterable: event_bucket_time = self._bucket_time(event[TIMESTAMP_FIELD]) if current_bucket_time is None or current_bucket_time < event_bucket_time: if current_bucket_events is not None: yield current_bucket_events current_bucket_time = event_bucket_time current_bucket_events = [] current_bucket_events.append(event) if current_bucket_events is not None and current_bucket_events != []: yield current_bucket_events
python
def _bucket_events(self, event_iterable): """ Convert an iterable of events into an iterable of lists of events per bucket. """ current_bucket_time = None current_bucket_events = None for event in event_iterable: event_bucket_time = self._bucket_time(event[TIMESTAMP_FIELD]) if current_bucket_time is None or current_bucket_time < event_bucket_time: if current_bucket_events is not None: yield current_bucket_events current_bucket_time = event_bucket_time current_bucket_events = [] current_bucket_events.append(event) if current_bucket_events is not None and current_bucket_events != []: yield current_bucket_events
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train
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Locu/chronology
pykronos/pykronos/utils/cache.py
QueryCache._cached_results
def _cached_results(self, start_time, end_time): """ Retrieves cached results for any bucket that has a single cache entry. If a bucket has two cache entries, there is a chance that two different writers previously computed and cached a result since Kronos has no transaction semantics. While it might be safe to return one of the cached results if there are multiple, we currently do the safe thing and pretend we have no previously computed data for this bucket. """ cached_buckets = self._bucket_events( self._client.get(self._scratch_stream, start_time, end_time, namespace=self._scratch_namespace)) for bucket_events in cached_buckets: # If we have multiple cache entries for the same bucket, pretend # we have no results for that bucket. if len(bucket_events) == 1: first_result = bucket_events[0] yield (kronos_time_to_epoch_time(first_result[TIMESTAMP_FIELD]), first_result[QueryCache.CACHE_KEY])
python
def _cached_results(self, start_time, end_time): """ Retrieves cached results for any bucket that has a single cache entry. If a bucket has two cache entries, there is a chance that two different writers previously computed and cached a result since Kronos has no transaction semantics. While it might be safe to return one of the cached results if there are multiple, we currently do the safe thing and pretend we have no previously computed data for this bucket. """ cached_buckets = self._bucket_events( self._client.get(self._scratch_stream, start_time, end_time, namespace=self._scratch_namespace)) for bucket_events in cached_buckets: # If we have multiple cache entries for the same bucket, pretend # we have no results for that bucket. if len(bucket_events) == 1: first_result = bucket_events[0] yield (kronos_time_to_epoch_time(first_result[TIMESTAMP_FIELD]), first_result[QueryCache.CACHE_KEY])
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train
https://github.com/Locu/chronology/blob/0edf3ee3286c76e242cbf92436ffa9c836b428e2/pykronos/pykronos/utils/cache.py#L151-L171
Locu/chronology
pykronos/pykronos/utils/cache.py
QueryCache.compute_and_cache_missing_buckets
def compute_and_cache_missing_buckets(self, start_time, end_time, untrusted_time, force_recompute=False): """ Return the results for `query_function` on every `bucket_width` time period between `start_time` and `end_time`. Look for previously cached results to avoid recomputation. For any buckets where all events would have occurred before `untrusted_time`, cache the results. :param start_time: A datetime for the beginning of the range, aligned with `bucket_width`. :param end_time: A datetime for the end of the range, aligned with `bucket_width`. :param untrusted_time: A datetime after which to not trust that computed data is stable. Any buckets that overlap with or follow this untrusted_time will not be cached. :param force_recompute: A boolean that, if True, will force recompute and recaching of even previously cached data. """ if untrusted_time and not untrusted_time.tzinfo: untrusted_time = untrusted_time.replace(tzinfo=tzutc()) events = self._compute_buckets(start_time, end_time, compute_missing=True, cache=True, untrusted_time=untrusted_time, force_recompute=force_recompute) for event in events: yield event
python
def compute_and_cache_missing_buckets(self, start_time, end_time, untrusted_time, force_recompute=False): """ Return the results for `query_function` on every `bucket_width` time period between `start_time` and `end_time`. Look for previously cached results to avoid recomputation. For any buckets where all events would have occurred before `untrusted_time`, cache the results. :param start_time: A datetime for the beginning of the range, aligned with `bucket_width`. :param end_time: A datetime for the end of the range, aligned with `bucket_width`. :param untrusted_time: A datetime after which to not trust that computed data is stable. Any buckets that overlap with or follow this untrusted_time will not be cached. :param force_recompute: A boolean that, if True, will force recompute and recaching of even previously cached data. """ if untrusted_time and not untrusted_time.tzinfo: untrusted_time = untrusted_time.replace(tzinfo=tzutc()) events = self._compute_buckets(start_time, end_time, compute_missing=True, cache=True, untrusted_time=untrusted_time, force_recompute=force_recompute) for event in events: yield event
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train
https://github.com/Locu/chronology/blob/0edf3ee3286c76e242cbf92436ffa9c836b428e2/pykronos/pykronos/utils/cache.py#L237-L264
Locu/chronology
pykronos/pykronos/utils/cache.py
QueryCache.retrieve_interval
def retrieve_interval(self, start_time, end_time, compute_missing=False): """ Return the results for `query_function` on every `bucket_width` time period between `start_time` and `end_time`. Look for previously cached results to avoid recomputation. :param start_time: A datetime for the beginning of the range, aligned with `bucket_width`. :param end_time: A datetime for the end of the range, aligned with `bucket_width`. :param compute_missing: A boolean that, if True, will compute any non-cached results. """ events = self._compute_buckets(start_time, end_time, compute_missing=compute_missing) for event in events: yield event
python
def retrieve_interval(self, start_time, end_time, compute_missing=False): """ Return the results for `query_function` on every `bucket_width` time period between `start_time` and `end_time`. Look for previously cached results to avoid recomputation. :param start_time: A datetime for the beginning of the range, aligned with `bucket_width`. :param end_time: A datetime for the end of the range, aligned with `bucket_width`. :param compute_missing: A boolean that, if True, will compute any non-cached results. """ events = self._compute_buckets(start_time, end_time, compute_missing=compute_missing) for event in events: yield event
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https://github.com/Locu/chronology/blob/0edf3ee3286c76e242cbf92436ffa9c836b428e2/pykronos/pykronos/utils/cache.py#L266-L283
Locu/chronology
jia/scheduler/scheduler.py
_execute
def _execute(task): """A wrapper around exec This exists outside the Scheduler class because it is pickled after it is sent to the executor. """ print "[%s] -- %s -- START" % (datetime.datetime.now(), task['id']) try: with get_app().app_context(): exec task['code'] in {}, {} print "[%s] -- %s -- COMPLETE" % (datetime.datetime.now(), task['id']) except Exception as e: if isinstance(e, PyCodeError): err_msg = "%s: %s\n%s" % (e.data['name'], e.data['message'], ''.join(e.data['traceback'])) else: err_msg = traceback.format_exc() sys.stderr.write(err_msg) sys.stderr.write("[%s] -- %s -- FAIL\n" % (datetime.datetime.now(), task['id'])) email_msg = 'Task %s failed at %s\n\n%s' % (task['id'], datetime.datetime.now(), err_msg) send_mail(get_app().config['SCHEDULER_FAILURE_EMAILS'], 'Scheduler Failure', email_msg) finally: return task
python
def _execute(task): """A wrapper around exec This exists outside the Scheduler class because it is pickled after it is sent to the executor. """ print "[%s] -- %s -- START" % (datetime.datetime.now(), task['id']) try: with get_app().app_context(): exec task['code'] in {}, {} print "[%s] -- %s -- COMPLETE" % (datetime.datetime.now(), task['id']) except Exception as e: if isinstance(e, PyCodeError): err_msg = "%s: %s\n%s" % (e.data['name'], e.data['message'], ''.join(e.data['traceback'])) else: err_msg = traceback.format_exc() sys.stderr.write(err_msg) sys.stderr.write("[%s] -- %s -- FAIL\n" % (datetime.datetime.now(), task['id'])) email_msg = 'Task %s failed at %s\n\n%s' % (task['id'], datetime.datetime.now(), err_msg) send_mail(get_app().config['SCHEDULER_FAILURE_EMAILS'], 'Scheduler Failure', email_msg) finally: return task
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https://github.com/Locu/chronology/blob/0edf3ee3286c76e242cbf92436ffa9c836b428e2/jia/scheduler/scheduler.py#L149-L175
Locu/chronology
jia/scheduler/scheduler.py
Scheduler._loop
def _loop(self, reader): """Main execution loop of the scheduler. The loop runs every second. Between iterations, the loop listens for schedule or cancel requests coming from Flask via over the gipc pipe (reader) and modifies the queue accordingly. When a task completes, it is rescheduled """ results = set() while True: now = datetime.datetime.now() if self._task_queue and self._task_queue[0][0] <= now: task = heappop(self._task_queue)[1] if task['id'] not in self._pending_cancels: result = self._executor.submit(_execute, task) results.add(result) else: self._pending_cancels.remove(task['id']) else: # Check for new tasks coming from HTTP with gevent.Timeout(0.5, False) as t: message = reader.get(timeout=t) if message[0] == 'schedule': self._schedule(message[1], next_run=now) elif message[0] == 'cancel': self._cancel(message[1]) # Reschedule completed tasks if not results: gevent.sleep(0.5) continue ready = self._executor.wait(results, num=1, timeout=0.5) for result in ready: results.remove(result) if result.value: task = result.value interval = int(task['interval']) if interval: run_at = now + datetime.timedelta(seconds=int(task['interval'])) self._schedule(task, next_run=run_at) else: err_msg = result.exception sys.stderr.write("ERROR: %s" % err_msg) email_msg = 'Task %s failed at %s\n\n%s' % ( task['id'], datetime.datetime.now(), err_msg ) send_mail(get_app().config['SCHEDULER_FAILURE_EMAILS'], 'Scheduler Failure', email_msg)
python
def _loop(self, reader): """Main execution loop of the scheduler. The loop runs every second. Between iterations, the loop listens for schedule or cancel requests coming from Flask via over the gipc pipe (reader) and modifies the queue accordingly. When a task completes, it is rescheduled """ results = set() while True: now = datetime.datetime.now() if self._task_queue and self._task_queue[0][0] <= now: task = heappop(self._task_queue)[1] if task['id'] not in self._pending_cancels: result = self._executor.submit(_execute, task) results.add(result) else: self._pending_cancels.remove(task['id']) else: # Check for new tasks coming from HTTP with gevent.Timeout(0.5, False) as t: message = reader.get(timeout=t) if message[0] == 'schedule': self._schedule(message[1], next_run=now) elif message[0] == 'cancel': self._cancel(message[1]) # Reschedule completed tasks if not results: gevent.sleep(0.5) continue ready = self._executor.wait(results, num=1, timeout=0.5) for result in ready: results.remove(result) if result.value: task = result.value interval = int(task['interval']) if interval: run_at = now + datetime.timedelta(seconds=int(task['interval'])) self._schedule(task, next_run=run_at) else: err_msg = result.exception sys.stderr.write("ERROR: %s" % err_msg) email_msg = 'Task %s failed at %s\n\n%s' % ( task['id'], datetime.datetime.now(), err_msg ) send_mail(get_app().config['SCHEDULER_FAILURE_EMAILS'], 'Scheduler Failure', email_msg)
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https://github.com/Locu/chronology/blob/0edf3ee3286c76e242cbf92436ffa9c836b428e2/jia/scheduler/scheduler.py#L95-L146
Locu/chronology
jia/scheduler/decorators.py
token_protected_endpoint
def token_protected_endpoint(function): """Requires valid auth_token in POST to access An auth_token is built by sending a dictionary built from a Werkzeug.Request.form to the scheduler.auth.create_token function. """ @wraps(function) def decorated(*args, **kwargs): auth_token = request.form.get('auth_token') if not auth_token: return json.dumps({ 'status': 'fail', 'reason': 'You must provide an auth_token', }) data = dict(request.form) del data['auth_token'] correct_token = create_token(current_app.config['SECRET_KEY'], data) if _compare_digest(auth_token, correct_token): return function(*args, **kwargs) else: return json.dumps({ 'status': 'fail', 'reason': 'Incorrect auth_token', }) return decorated
python
def token_protected_endpoint(function): """Requires valid auth_token in POST to access An auth_token is built by sending a dictionary built from a Werkzeug.Request.form to the scheduler.auth.create_token function. """ @wraps(function) def decorated(*args, **kwargs): auth_token = request.form.get('auth_token') if not auth_token: return json.dumps({ 'status': 'fail', 'reason': 'You must provide an auth_token', }) data = dict(request.form) del data['auth_token'] correct_token = create_token(current_app.config['SECRET_KEY'], data) if _compare_digest(auth_token, correct_token): return function(*args, **kwargs) else: return json.dumps({ 'status': 'fail', 'reason': 'Incorrect auth_token', }) return decorated
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https://github.com/Locu/chronology/blob/0edf3ee3286c76e242cbf92436ffa9c836b428e2/jia/scheduler/decorators.py#L33-L61
bovee/Aston
aston/trace/math_chromatograms.py
molmz
def molmz(df, noise=10000): """ The mz of the molecular ion. """ d = ((df.values > noise) * df.columns).max(axis=1) return Trace(d, df.index, name='molmz')
python
def molmz(df, noise=10000): """ The mz of the molecular ion. """ d = ((df.values > noise) * df.columns).max(axis=1) return Trace(d, df.index, name='molmz')
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train
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bovee/Aston
aston/trace/math_chromatograms.py
mzminus
def mzminus(df, minus=0, noise=10000): """ The abundances of ions which are minus below the molecular ion. """ mol_ions = ((df.values > noise) * df.columns).max(axis=1) - minus mol_ions[np.abs(mol_ions) < 0] = 0 d = np.abs(np.ones(df.shape) * df.columns - (mol_ions[np.newaxis].T * np.ones(df.shape))) < 1 d = (df.values * d).sum(axis=1) return Trace(d, df.index, name='m-' + str(minus))
python
def mzminus(df, minus=0, noise=10000): """ The abundances of ions which are minus below the molecular ion. """ mol_ions = ((df.values > noise) * df.columns).max(axis=1) - minus mol_ions[np.abs(mol_ions) < 0] = 0 d = np.abs(np.ones(df.shape) * df.columns - (mol_ions[np.newaxis].T * np.ones(df.shape))) < 1 d = (df.values * d).sum(axis=1) return Trace(d, df.index, name='m-' + str(minus))
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The abundances of ions which are minus below the molecular ion.
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train
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bovee/Aston
aston/trace/math_chromatograms.py
basemz
def basemz(df): """ The mz of the most abundant ion. """ # returns the d = np.array(df.columns)[df.values.argmax(axis=1)] return Trace(d, df.index, name='basemz')
python
def basemz(df): """ The mz of the most abundant ion. """ # returns the d = np.array(df.columns)[df.values.argmax(axis=1)] return Trace(d, df.index, name='basemz')
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train
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bovee/Aston
aston/trace/math_chromatograms.py
coda
def coda(df, window, level): """ CODA processing from Windig, Phalp, & Payne 1996 Anal Chem """ # pull out the data d = df.values # smooth the data and standardize it smooth_data = movingaverage(d, df.index, window)[0] stand_data = (smooth_data - smooth_data.mean()) / smooth_data.std() # scale the data to have unit length scale_data = d / np.sqrt(np.sum(d ** 2, axis=0)) # calculate the "mass chromatographic quality" (MCQ) index mcq = np.sum(stand_data * scale_data, axis=0) / np.sqrt(d.shape[0] - 1) # filter out ions with an mcq below level good_ions = [i for i, q in zip(df.columns, mcq) if q >= level] return good_ions
python
def coda(df, window, level): """ CODA processing from Windig, Phalp, & Payne 1996 Anal Chem """ # pull out the data d = df.values # smooth the data and standardize it smooth_data = movingaverage(d, df.index, window)[0] stand_data = (smooth_data - smooth_data.mean()) / smooth_data.std() # scale the data to have unit length scale_data = d / np.sqrt(np.sum(d ** 2, axis=0)) # calculate the "mass chromatographic quality" (MCQ) index mcq = np.sum(stand_data * scale_data, axis=0) / np.sqrt(d.shape[0] - 1) # filter out ions with an mcq below level good_ions = [i for i, q in zip(df.columns, mcq) if q >= level] return good_ions
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bovee/Aston
aston/tracefile/mime.py
tfclasses
def tfclasses(): """ A mapping of mimetypes to every class for reading data files. """ # automatically find any subclasses of TraceFile in the same # directory as me classes = {} mydir = op.dirname(op.abspath(inspect.getfile(get_mimetype))) tfcls = {"<class 'aston.tracefile.TraceFile'>", "<class 'aston.tracefile.ScanListFile'>"} for filename in glob(op.join(mydir, '*.py')): name = op.splitext(op.basename(filename))[0] module = import_module('aston.tracefile.' + name) for clsname in dir(module): cls = getattr(module, clsname) if hasattr(cls, '__base__'): if str(cls.__base__) in tfcls: classes[cls.mime] = cls return classes
python
def tfclasses(): """ A mapping of mimetypes to every class for reading data files. """ # automatically find any subclasses of TraceFile in the same # directory as me classes = {} mydir = op.dirname(op.abspath(inspect.getfile(get_mimetype))) tfcls = {"<class 'aston.tracefile.TraceFile'>", "<class 'aston.tracefile.ScanListFile'>"} for filename in glob(op.join(mydir, '*.py')): name = op.splitext(op.basename(filename))[0] module = import_module('aston.tracefile.' + name) for clsname in dir(module): cls = getattr(module, clsname) if hasattr(cls, '__base__'): if str(cls.__base__) in tfcls: classes[cls.mime] = cls return classes
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bovee/Aston
aston/peak/peak_fitting.py
guess_initc
def guess_initc(ts, f, rts=[]): """ ts - An AstonSeries that's being fitted with peaks f - The functional form of the peaks (e.g. gaussian) rts - peak maxima to fit; each number corresponds to one peak """ def find_side(y, loc=None): if loc is None: loc = y.argmax() ddy = np.diff(np.diff(y)) lft_loc, rgt_loc = loc - 2, loc + 1 while rgt_loc >= 0 and rgt_loc < len(ddy): if ddy[rgt_loc] < ddy[rgt_loc - 1]: break rgt_loc += 1 while lft_loc >= 0 and lft_loc < len(ddy): if ddy[lft_loc] < ddy[lft_loc + 1]: break lft_loc -= 1 return lft_loc + 1, rgt_loc + 1 # weight_mom = lambda m, a, w: \ # np.sum(w * (a - np.sum(w * a) / np.sum(w)) ** m) / np.sum(w) # sig = np.sqrt(weight_mom(2, ts.index, ts.values)) # sigma # peak_params['s'] = weight_mom(3, ts.index, ts.values) / sig ** 3 # peak_params['e'] = weight_mom(4, ts.index, ts.values) / sig ** 4 - 3 # TODO: better method of calculation of these? all_params = [] for rt in rts: peak_params = {'x': rt} # ts.index[ts.values.argmax()] top_idx = np.abs(ts.index - rt).argmin() side_idx = find_side(ts.values, top_idx) peak_params['h'] = ts.values[top_idx] # - min(ts.y[side_idx[0]], ts.y[side_idx[1]]) peak_params['w'] = ts.index[side_idx[1]] - ts.index[side_idx[0]] peak_params['s'] = 1.1 peak_params['e'] = 1. peak_params['a'] = 1. all_params.append(peak_params) return all_params
python
def guess_initc(ts, f, rts=[]): """ ts - An AstonSeries that's being fitted with peaks f - The functional form of the peaks (e.g. gaussian) rts - peak maxima to fit; each number corresponds to one peak """ def find_side(y, loc=None): if loc is None: loc = y.argmax() ddy = np.diff(np.diff(y)) lft_loc, rgt_loc = loc - 2, loc + 1 while rgt_loc >= 0 and rgt_loc < len(ddy): if ddy[rgt_loc] < ddy[rgt_loc - 1]: break rgt_loc += 1 while lft_loc >= 0 and lft_loc < len(ddy): if ddy[lft_loc] < ddy[lft_loc + 1]: break lft_loc -= 1 return lft_loc + 1, rgt_loc + 1 # weight_mom = lambda m, a, w: \ # np.sum(w * (a - np.sum(w * a) / np.sum(w)) ** m) / np.sum(w) # sig = np.sqrt(weight_mom(2, ts.index, ts.values)) # sigma # peak_params['s'] = weight_mom(3, ts.index, ts.values) / sig ** 3 # peak_params['e'] = weight_mom(4, ts.index, ts.values) / sig ** 4 - 3 # TODO: better method of calculation of these? all_params = [] for rt in rts: peak_params = {'x': rt} # ts.index[ts.values.argmax()] top_idx = np.abs(ts.index - rt).argmin() side_idx = find_side(ts.values, top_idx) peak_params['h'] = ts.values[top_idx] # - min(ts.y[side_idx[0]], ts.y[side_idx[1]]) peak_params['w'] = ts.index[side_idx[1]] - ts.index[side_idx[0]] peak_params['s'] = 1.1 peak_params['e'] = 1. peak_params['a'] = 1. all_params.append(peak_params) return all_params
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https://github.com/bovee/Aston/blob/007630fdf074690373d03398fe818260d3d3cf5a/aston/peak/peak_fitting.py#L46-L85
bovee/Aston
aston/peak/peak_fitting.py
fit
def fit(ts, fs=[], all_params=[], fit_vars=None, alg='leastsq', make_bounded=True): """ Use a minimization algorithm to fit a AstonSeries with analytical functions. """ if fit_vars is None: fit_vars = [f._peakargs for f in fs] initc = [min(ts.values)] for f, peak_params, to_fit in zip(fs, all_params, fit_vars): if 'v' in to_fit: to_fit.remove('v') if make_bounded and hasattr(f, '_pbounds'): new_v = _to_unbnd_p({i: peak_params[i] for i in to_fit}, f._pbounds) initc += [new_v[i] for i in to_fit] else: initc += [peak_params[i] for i in to_fit] def errfunc_lsq(fit_params, t, y, all_params): # first value in fit_params is baseline # fit_y = np.ones(len(t)) * fit_params[0] fit_y = np.zeros(len(t)) param_i = 1 for f, peak_params, to_fit in zip(fs, all_params, fit_vars): for k in to_fit: peak_params[k] = fit_params[param_i] param_i += 1 if make_bounded and hasattr(f, '_pbounds'): fit_y += f(t, **_to_bound_p(peak_params, f._pbounds)) else: fit_y += f(t, **peak_params) return fit_y - y def errfunc(p, t, y, all_params): return np.sum(errfunc_lsq(p, t, y, all_params) ** 2) if alg == 'simplex': fit_p, _ = fmin(errfunc, initc, args=(ts.index, ts.values, peak_params)) # elif alg == 'anneal': # fit_p, _ = anneal(errfunc, initc, args=(ts.index, ts.values, # peak_params)) elif alg == 'lbfgsb': # TODO: use bounds param fitp, _ = fmin_l_bfgs_b(errfunc, fit_p, args=(ts.index, ts.values, peak_params), approx_grad=True) elif alg == 'leastsq': fit_p, _ = leastsq(errfunc_lsq, initc, args=(ts.index, ts.values, all_params)) # else: # r = minimize(errfunc, initc, \ # args=(ts.index, ts.values, all_params), \ # jac=False, gtol=1e-2) # #if not r['success']: # # print('Fail:' + str(f)) # # print(r) # #if np.nan in r['x']: # not r['success']? # # fit_p = initc # #else: # # fit_p = r['x'] fit_pl = fit_p.tolist() v = fit_pl.pop(0) # noqa fitted_params = [] for f, to_fit in zip(fs, fit_vars): fit_p_dict = {v: fit_pl.pop(0) for v in to_fit} # fit_p_dict['v'] = v if make_bounded and hasattr(f, '_pbounds'): fitted_params.append(_to_bound_p(fit_p_dict, f._pbounds)) else: fitted_params.append(fit_p_dict) # calculate r^2 of the fit ss_err = errfunc(fit_p, ts.index, ts.values, fitted_params) ss_tot = np.sum((ts.values - np.mean(ts.values)) ** 2) r2 = 1 - ss_err / ss_tot res = {'r^2': r2} return fitted_params, res
python
def fit(ts, fs=[], all_params=[], fit_vars=None, alg='leastsq', make_bounded=True): """ Use a minimization algorithm to fit a AstonSeries with analytical functions. """ if fit_vars is None: fit_vars = [f._peakargs for f in fs] initc = [min(ts.values)] for f, peak_params, to_fit in zip(fs, all_params, fit_vars): if 'v' in to_fit: to_fit.remove('v') if make_bounded and hasattr(f, '_pbounds'): new_v = _to_unbnd_p({i: peak_params[i] for i in to_fit}, f._pbounds) initc += [new_v[i] for i in to_fit] else: initc += [peak_params[i] for i in to_fit] def errfunc_lsq(fit_params, t, y, all_params): # first value in fit_params is baseline # fit_y = np.ones(len(t)) * fit_params[0] fit_y = np.zeros(len(t)) param_i = 1 for f, peak_params, to_fit in zip(fs, all_params, fit_vars): for k in to_fit: peak_params[k] = fit_params[param_i] param_i += 1 if make_bounded and hasattr(f, '_pbounds'): fit_y += f(t, **_to_bound_p(peak_params, f._pbounds)) else: fit_y += f(t, **peak_params) return fit_y - y def errfunc(p, t, y, all_params): return np.sum(errfunc_lsq(p, t, y, all_params) ** 2) if alg == 'simplex': fit_p, _ = fmin(errfunc, initc, args=(ts.index, ts.values, peak_params)) # elif alg == 'anneal': # fit_p, _ = anneal(errfunc, initc, args=(ts.index, ts.values, # peak_params)) elif alg == 'lbfgsb': # TODO: use bounds param fitp, _ = fmin_l_bfgs_b(errfunc, fit_p, args=(ts.index, ts.values, peak_params), approx_grad=True) elif alg == 'leastsq': fit_p, _ = leastsq(errfunc_lsq, initc, args=(ts.index, ts.values, all_params)) # else: # r = minimize(errfunc, initc, \ # args=(ts.index, ts.values, all_params), \ # jac=False, gtol=1e-2) # #if not r['success']: # # print('Fail:' + str(f)) # # print(r) # #if np.nan in r['x']: # not r['success']? # # fit_p = initc # #else: # # fit_p = r['x'] fit_pl = fit_p.tolist() v = fit_pl.pop(0) # noqa fitted_params = [] for f, to_fit in zip(fs, fit_vars): fit_p_dict = {v: fit_pl.pop(0) for v in to_fit} # fit_p_dict['v'] = v if make_bounded and hasattr(f, '_pbounds'): fitted_params.append(_to_bound_p(fit_p_dict, f._pbounds)) else: fitted_params.append(fit_p_dict) # calculate r^2 of the fit ss_err = errfunc(fit_p, ts.index, ts.values, fitted_params) ss_tot = np.sum((ts.values - np.mean(ts.values)) ** 2) r2 = 1 - ss_err / ss_tot res = {'r^2': r2} return fitted_params, res
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Locu/chronology
kronos/kronos/core/executor.py
execute_greenlet_async
def execute_greenlet_async(func, *args, **kwargs): """ Executes `func` in a separate greenlet in the same process. Memory and other resources are available (e.g. TCP connections etc.) `args` and `kwargs` are passed to `func`. """ global _GREENLET_EXECUTOR if _GREENLET_EXECUTOR is None: _GREENLET_EXECUTOR = GreenletExecutor( num_greenlets=settings.node.greenlet_pool_size) return _GREENLET_EXECUTOR.submit(func, *args, **kwargs)
python
def execute_greenlet_async(func, *args, **kwargs): """ Executes `func` in a separate greenlet in the same process. Memory and other resources are available (e.g. TCP connections etc.) `args` and `kwargs` are passed to `func`. """ global _GREENLET_EXECUTOR if _GREENLET_EXECUTOR is None: _GREENLET_EXECUTOR = GreenletExecutor( num_greenlets=settings.node.greenlet_pool_size) return _GREENLET_EXECUTOR.submit(func, *args, **kwargs)
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Locu/chronology
kronos/kronos/core/executor.py
execute_process_async
def execute_process_async(func, *args, **kwargs): """ Executes `func` in a separate process. Memory and other resources are not available. This gives true concurrency at the cost of losing access to these resources. `args` and `kwargs` are """ global _GIPC_EXECUTOR if _GIPC_EXECUTOR is None: _GIPC_EXECUTOR = GIPCExecutor( num_procs=settings.node.gipc_pool_size, num_greenlets=settings.node.greenlet_pool_size) return _GIPC_EXECUTOR.submit(func, *args, **kwargs)
python
def execute_process_async(func, *args, **kwargs): """ Executes `func` in a separate process. Memory and other resources are not available. This gives true concurrency at the cost of losing access to these resources. `args` and `kwargs` are """ global _GIPC_EXECUTOR if _GIPC_EXECUTOR is None: _GIPC_EXECUTOR = GIPCExecutor( num_procs=settings.node.gipc_pool_size, num_greenlets=settings.node.greenlet_pool_size) return _GIPC_EXECUTOR.submit(func, *args, **kwargs)
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Locu/chronology
kronos/kronos/core/executor.py
wait
def wait(results, num=None, timeout=None): """ Wait for results of async executions to become available/ready. `results`: List of AsyncResult instances returned by one of `execute_greenlet_async` or `execute_process_async`. `num`: Number of results to wait for. None implies wait for all results. `timeout`: Number of seconds to wait for `num` of the `results` to become ready. """ return AbstractExecutor.wait(results, num=num, timeout=timeout)
python
def wait(results, num=None, timeout=None): """ Wait for results of async executions to become available/ready. `results`: List of AsyncResult instances returned by one of `execute_greenlet_async` or `execute_process_async`. `num`: Number of results to wait for. None implies wait for all results. `timeout`: Number of seconds to wait for `num` of the `results` to become ready. """ return AbstractExecutor.wait(results, num=num, timeout=timeout)
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jessamynsmith/twitterbot
twitter_bot/messages/markov_chain.py
MarkovChainMessageProvider.create
def create(self, mention, max_message_length): """ Create a message :param mention: JSON object containing mention details from Twitter (or an empty dict {}) :param max_message_length: Maximum allowable length for created message :return: A random message created using a Markov chain generator """ message = [] def message_len(): return sum([len(w) + 1 for w in message]) while message_len() < max_message_length: message.append(self.a_random_word(message[-1] if message else None)) return ' '.join(message[:-1])
python
def create(self, mention, max_message_length): """ Create a message :param mention: JSON object containing mention details from Twitter (or an empty dict {}) :param max_message_length: Maximum allowable length for created message :return: A random message created using a Markov chain generator """ message = [] def message_len(): return sum([len(w) + 1 for w in message]) while message_len() < max_message_length: message.append(self.a_random_word(message[-1] if message else None)) return ' '.join(message[:-1])
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LasLabs/python-helpscout
helpscout/web_hook/__init__.py
HelpScoutWebHook.receive
def receive(self, event_type, signature, data_str): """Receive a web hook for the event and signature. Args: event_type (str): Name of the event that was received (from the request ``X-HelpScout-Event`` header). signature (str): The signature that was received, which serves as authentication (from the request ``X-HelpScout-Signature`` header). data_str (str): The raw data that was posted by HelpScout to the web hook. This must be the raw string, because if it is parsed with JSON it will lose its ordering and not pass signature validation. Raises: helpscout.exceptions.HelpScoutSecurityException: If an invalid signature is provided, and ``raise_if_invalid`` is ``True``. Returns: helpscout.web_hook.WebHookEvent: The authenticated web hook request. """ if not self.validate_signature(signature, data_str): raise HelpScoutSecurityException( 'The signature provided by this request was invalid.', ) return HelpScoutWebHookEvent( event_type=event_type, record=json.loads(data_str), )
python
def receive(self, event_type, signature, data_str): """Receive a web hook for the event and signature. Args: event_type (str): Name of the event that was received (from the request ``X-HelpScout-Event`` header). signature (str): The signature that was received, which serves as authentication (from the request ``X-HelpScout-Signature`` header). data_str (str): The raw data that was posted by HelpScout to the web hook. This must be the raw string, because if it is parsed with JSON it will lose its ordering and not pass signature validation. Raises: helpscout.exceptions.HelpScoutSecurityException: If an invalid signature is provided, and ``raise_if_invalid`` is ``True``. Returns: helpscout.web_hook.WebHookEvent: The authenticated web hook request. """ if not self.validate_signature(signature, data_str): raise HelpScoutSecurityException( 'The signature provided by this request was invalid.', ) return HelpScoutWebHookEvent( event_type=event_type, record=json.loads(data_str), )
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https://github.com/LasLabs/python-helpscout/blob/84bf669417d72ca19641a02c9a660e1ae4271de4/helpscout/web_hook/__init__.py#L39-L70
LasLabs/python-helpscout
helpscout/web_hook/__init__.py
HelpScoutWebHook.validate_signature
def validate_signature(self, signature, data, encoding='utf8'): """Validate the signature for the provided data. Args: signature (str or bytes or bytearray): Signature that was provided for the request. data (str or bytes or bytearray): Data string to validate against the signature. encoding (str, optional): If a string was provided for ``data`` or ``signature``, this is the character encoding. Returns: bool: Whether the signature is valid for the provided data. """ if isinstance(data, string_types): data = bytearray(data, encoding) if isinstance(signature, string_types): signature = bytearray(signature, encoding) secret_key = bytearray(self.secret_key, 'utf8') hashed = hmac.new(secret_key, data, sha1) encoded = b64encode(hashed.digest()) return encoded.strip() == signature.strip()
python
def validate_signature(self, signature, data, encoding='utf8'): """Validate the signature for the provided data. Args: signature (str or bytes or bytearray): Signature that was provided for the request. data (str or bytes or bytearray): Data string to validate against the signature. encoding (str, optional): If a string was provided for ``data`` or ``signature``, this is the character encoding. Returns: bool: Whether the signature is valid for the provided data. """ if isinstance(data, string_types): data = bytearray(data, encoding) if isinstance(signature, string_types): signature = bytearray(signature, encoding) secret_key = bytearray(self.secret_key, 'utf8') hashed = hmac.new(secret_key, data, sha1) encoded = b64encode(hashed.digest()) return encoded.strip() == signature.strip()
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