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jwass/directions.py
directions/base.py
Router.rate_limit_wait
def rate_limit_wait(self): """ Sleep if rate limiting is required based on current time and last query. """ if self._rate_limit_dt and self._last_query is not None: dt = time.time() - self._last_query wait = self._rate_limit_dt - dt if wait > 0: time.sleep(wait)
python
def rate_limit_wait(self): """ Sleep if rate limiting is required based on current time and last query. """ if self._rate_limit_dt and self._last_query is not None: dt = time.time() - self._last_query wait = self._rate_limit_dt - dt if wait > 0: time.sleep(wait)
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Sleep if rate limiting is required based on current time and last query.
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c3734e4cb499fe80e27b2a26575a91ac4e834e95
https://github.com/jwass/directions.py/blob/c3734e4cb499fe80e27b2a26575a91ac4e834e95/directions/base.py#L22-L32
train
jwass/directions.py
directions/base.py
Router.route
def route(self, arg, destination=None, waypoints=None, raw=False, **kwargs): """ Query a route. route(locations): points can be - a sequence of locations - a Shapely LineString route(origin, destination, waypoints=None) - origin and destination are a single destination - waypoints are the points to be inserted between the origin and destination If waypoints is specified, destination must also be specified Each location can be: - string (will be geocoded by the routing provider. Not all providers accept this as input) - (longitude, latitude) sequence (tuple, list, numpy array, etc.) - Shapely Point with x as longitude, y as latitude Additional parameters --------------------- raw : bool, default False Return the raw json dict response from the service Returns ------- list of Route objects If raw is True, returns the json dict instead of converting to Route objects Examples -------- mq = directions.Mapquest(key) routes = mq.route('1 magazine st. cambridge, ma', 'south station boston, ma') routes = mq.route('1 magazine st. cambridge, ma', 'south station boston, ma', waypoints=['700 commonwealth ave. boston, ma']) # Uses each point in the line as a waypoint. There is a limit to the # number of waypoints for each service. Consult the docs. line = LineString(...) routes = mq.route(line) # Feel free to mix different location types routes = mq.route(line.coords[0], 'south station boston, ma', waypoints=[(-71.103972, 42.349324)]) """ points = _parse_points(arg, destination, waypoints) if len(points) < 2: raise ValueError('You must specify at least 2 points') self.rate_limit_wait() data = self.raw_query(points, **kwargs) self._last_query = time.time() if raw: return data return self.format_output(data)
python
def route(self, arg, destination=None, waypoints=None, raw=False, **kwargs): """ Query a route. route(locations): points can be - a sequence of locations - a Shapely LineString route(origin, destination, waypoints=None) - origin and destination are a single destination - waypoints are the points to be inserted between the origin and destination If waypoints is specified, destination must also be specified Each location can be: - string (will be geocoded by the routing provider. Not all providers accept this as input) - (longitude, latitude) sequence (tuple, list, numpy array, etc.) - Shapely Point with x as longitude, y as latitude Additional parameters --------------------- raw : bool, default False Return the raw json dict response from the service Returns ------- list of Route objects If raw is True, returns the json dict instead of converting to Route objects Examples -------- mq = directions.Mapquest(key) routes = mq.route('1 magazine st. cambridge, ma', 'south station boston, ma') routes = mq.route('1 magazine st. cambridge, ma', 'south station boston, ma', waypoints=['700 commonwealth ave. boston, ma']) # Uses each point in the line as a waypoint. There is a limit to the # number of waypoints for each service. Consult the docs. line = LineString(...) routes = mq.route(line) # Feel free to mix different location types routes = mq.route(line.coords[0], 'south station boston, ma', waypoints=[(-71.103972, 42.349324)]) """ points = _parse_points(arg, destination, waypoints) if len(points) < 2: raise ValueError('You must specify at least 2 points') self.rate_limit_wait() data = self.raw_query(points, **kwargs) self._last_query = time.time() if raw: return data return self.format_output(data)
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c3734e4cb499fe80e27b2a26575a91ac4e834e95
https://github.com/jwass/directions.py/blob/c3734e4cb499fe80e27b2a26575a91ac4e834e95/directions/base.py#L38-L99
train
jwass/directions.py
directions/base.py
Route.from_geojson
def from_geojson(cls, data): """ Return a Route from a GeoJSON dictionary, as returned by Route.geojson() """ properties = data['properties'] distance = properties.pop('distance') duration = properties.pop('duration') maneuvers = [] for feature in data['features']: geom = feature['geometry'] if geom['type'] == 'LineString': coords = geom['coordinates'] else: maneuvers.append(Maneuver.from_geojson(feature)) return Route(coords, distance, duration, maneuvers, **properties)
python
def from_geojson(cls, data): """ Return a Route from a GeoJSON dictionary, as returned by Route.geojson() """ properties = data['properties'] distance = properties.pop('distance') duration = properties.pop('duration') maneuvers = [] for feature in data['features']: geom = feature['geometry'] if geom['type'] == 'LineString': coords = geom['coordinates'] else: maneuvers.append(Maneuver.from_geojson(feature)) return Route(coords, distance, duration, maneuvers, **properties)
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Return a Route from a GeoJSON dictionary, as returned by Route.geojson()
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c3734e4cb499fe80e27b2a26575a91ac4e834e95
https://github.com/jwass/directions.py/blob/c3734e4cb499fe80e27b2a26575a91ac4e834e95/directions/base.py#L193-L210
train
comtihon/catcher
catcher/utils/module_utils.py
prepare_modules
def prepare_modules(module_paths: list, available: dict) -> dict: """ Scan all paths for external modules and form key-value dict. :param module_paths: list of external modules (either python packages or third-party scripts) :param available: dict of all registered python modules (can contain python modules from module_paths) :return: dict of external modules, where keys are filenames (same as stepnames) and values are the paths """ indexed = {} for path in module_paths: if not os.path.exists(path) and path not in available: err = 'No such path: ' + path error(err) else: for f in os.listdir(path): mod_path = join(path, f) if f in indexed: warning('Override ' + indexed[f] + ' with ' + mod_path) indexed[f] = mod_path return indexed
python
def prepare_modules(module_paths: list, available: dict) -> dict: """ Scan all paths for external modules and form key-value dict. :param module_paths: list of external modules (either python packages or third-party scripts) :param available: dict of all registered python modules (can contain python modules from module_paths) :return: dict of external modules, where keys are filenames (same as stepnames) and values are the paths """ indexed = {} for path in module_paths: if not os.path.exists(path) and path not in available: err = 'No such path: ' + path error(err) else: for f in os.listdir(path): mod_path = join(path, f) if f in indexed: warning('Override ' + indexed[f] + ' with ' + mod_path) indexed[f] = mod_path return indexed
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5124e69d11cb6987daca595a61a4062d2b5f5ecc
https://github.com/comtihon/catcher/blob/5124e69d11cb6987daca595a61a4062d2b5f5ecc/catcher/utils/module_utils.py#L14-L32
train
keans/lmnotify
lmnotify/ssdp.py
SSDPManager.discover_upnp_devices
def discover_upnp_devices( self, st="upnp:rootdevice", timeout=2, mx=1, retries=1 ): """ sends an SSDP discovery packet to the network and collects the devices that replies to it. A dictionary is returned using the devices unique usn as key """ # prepare UDP socket to transfer the SSDP packets s = socket.socket( socket.AF_INET, socket.SOCK_DGRAM, socket.IPPROTO_UDP ) s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) s.setsockopt(socket.IPPROTO_IP, socket.IP_MULTICAST_TTL, 2) s.settimeout(timeout) # prepare SSDP discover message msg = SSDPDiscoveryMessage(mx=mx, st=st) # try to get devices with multiple retries in case of failure devices = {} for _ in range(retries): # send SSDP discovery message s.sendto(msg.bytes, SSDP_MULTICAST_ADDR) devices = {} try: while True: # parse response and store it in dict r = SSDPResponse(s.recvfrom(65507)) devices[r.usn] = r except socket.timeout: break return devices
python
def discover_upnp_devices( self, st="upnp:rootdevice", timeout=2, mx=1, retries=1 ): """ sends an SSDP discovery packet to the network and collects the devices that replies to it. A dictionary is returned using the devices unique usn as key """ # prepare UDP socket to transfer the SSDP packets s = socket.socket( socket.AF_INET, socket.SOCK_DGRAM, socket.IPPROTO_UDP ) s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) s.setsockopt(socket.IPPROTO_IP, socket.IP_MULTICAST_TTL, 2) s.settimeout(timeout) # prepare SSDP discover message msg = SSDPDiscoveryMessage(mx=mx, st=st) # try to get devices with multiple retries in case of failure devices = {} for _ in range(retries): # send SSDP discovery message s.sendto(msg.bytes, SSDP_MULTICAST_ADDR) devices = {} try: while True: # parse response and store it in dict r = SSDPResponse(s.recvfrom(65507)) devices[r.usn] = r except socket.timeout: break return devices
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sends an SSDP discovery packet to the network and collects the devices that replies to it. A dictionary is returned using the devices unique usn as key
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b0a5282a582e5090852dc20fea8a135ca258d0d3
https://github.com/keans/lmnotify/blob/b0a5282a582e5090852dc20fea8a135ca258d0d3/lmnotify/ssdp.py#L80-L115
train
keans/lmnotify
lmnotify/ssdp.py
SSDPManager.get_filtered_devices
def get_filtered_devices( self, model_name, device_types="upnp:rootdevice", timeout=2 ): """ returns a dict of devices that contain the given model name """ # get list of all UPNP devices in the network upnp_devices = self.discover_upnp_devices(st=device_types) # go through all UPNP devices and filter wanted devices filtered_devices = collections.defaultdict(dict) for dev in upnp_devices.values(): try: # download XML file with information about the device # from the device's location r = requests.get(dev.location, timeout=timeout) if r.status_code == requests.codes.ok: # parse returned XML root = ET.fromstring(r.text) # add shortcut for XML namespace to access sub nodes ns = {"upnp": "urn:schemas-upnp-org:device-1-0"} # get device element device = root.find("upnp:device", ns) if model_name in device.find( "upnp:modelName", ns ).text: # model name is wanted => add to list # get unique UDN of the device that is used as key udn = device.find("upnp:UDN", ns).text # add url base url_base = root.find("upnp:URLBase", ns) if url_base is not None: filtered_devices[udn][ "URLBase" ] = url_base.text # add interesting device attributes and # use unique UDN as key for attr in ( "deviceType", "friendlyName", "manufacturer", "manufacturerURL", "modelDescription", "modelName", "modelNumber" ): el = device.find("upnp:%s" % attr, ns) if el is not None: filtered_devices[udn][ attr ] = el.text.strip() except ET.ParseError: # just skip devices that are invalid xml pass except requests.exceptions.ConnectTimeout: # just skip devices that are not replying in time print("Timeout for '%s'. Skipping." % dev.location) return filtered_devices
python
def get_filtered_devices( self, model_name, device_types="upnp:rootdevice", timeout=2 ): """ returns a dict of devices that contain the given model name """ # get list of all UPNP devices in the network upnp_devices = self.discover_upnp_devices(st=device_types) # go through all UPNP devices and filter wanted devices filtered_devices = collections.defaultdict(dict) for dev in upnp_devices.values(): try: # download XML file with information about the device # from the device's location r = requests.get(dev.location, timeout=timeout) if r.status_code == requests.codes.ok: # parse returned XML root = ET.fromstring(r.text) # add shortcut for XML namespace to access sub nodes ns = {"upnp": "urn:schemas-upnp-org:device-1-0"} # get device element device = root.find("upnp:device", ns) if model_name in device.find( "upnp:modelName", ns ).text: # model name is wanted => add to list # get unique UDN of the device that is used as key udn = device.find("upnp:UDN", ns).text # add url base url_base = root.find("upnp:URLBase", ns) if url_base is not None: filtered_devices[udn][ "URLBase" ] = url_base.text # add interesting device attributes and # use unique UDN as key for attr in ( "deviceType", "friendlyName", "manufacturer", "manufacturerURL", "modelDescription", "modelName", "modelNumber" ): el = device.find("upnp:%s" % attr, ns) if el is not None: filtered_devices[udn][ attr ] = el.text.strip() except ET.ParseError: # just skip devices that are invalid xml pass except requests.exceptions.ConnectTimeout: # just skip devices that are not replying in time print("Timeout for '%s'. Skipping." % dev.location) return filtered_devices
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b0a5282a582e5090852dc20fea8a135ca258d0d3
https://github.com/keans/lmnotify/blob/b0a5282a582e5090852dc20fea8a135ca258d0d3/lmnotify/ssdp.py#L117-L180
train
rasbt/mputil
mputil/map.py
lazy_map
def lazy_map(data_processor, data_generator, n_cpus=1, stepsize=None): """A variant of multiprocessing.Pool.map that supports lazy evaluation As with the regular multiprocessing.Pool.map, the processes are spawned off asynchronously while the results are returned in order. In contrast to multiprocessing.Pool.map, the iterator (here: data_generator) is not consumed at once but evaluated lazily which is useful if the iterator (for example, a generator) contains objects with a large memory footprint. Parameters ========== data_processor : func A processing function that is applied to objects in `data_generator` data_generator : iterator or generator A python iterator or generator that yields objects to be fed into the `data_processor` function for processing. n_cpus=1 : int (default: 1) Number of processes to run in parallel. - If `n_cpus` > 0, the specified number of CPUs will be used. - If `n_cpus=0`, all available CPUs will be used. - If `n_cpus` < 0, all available CPUs - `n_cpus` will be used. stepsize : int or None (default: None) The number of items to fetch from the iterator to pass on to the workers at a time. If `stepsize=None` (default), the stepsize size will be set equal to `n_cpus`. Returns ========= list : A Python list containing the results returned by the `data_processor` function when called on all elements in yielded by the `data_generator` in sorted order. Note that the last list may contain fewer items if the number of elements in `data_generator` is not evenly divisible by `stepsize`. """ if not n_cpus: n_cpus = mp.cpu_count() elif n_cpus < 0: n_cpus = mp.cpu_count() - n_cpus if stepsize is None: stepsize = n_cpus results = [] with mp.Pool(processes=n_cpus) as p: while True: r = p.map(data_processor, islice(data_generator, stepsize)) if r: results.extend(r) else: break return results
python
def lazy_map(data_processor, data_generator, n_cpus=1, stepsize=None): """A variant of multiprocessing.Pool.map that supports lazy evaluation As with the regular multiprocessing.Pool.map, the processes are spawned off asynchronously while the results are returned in order. In contrast to multiprocessing.Pool.map, the iterator (here: data_generator) is not consumed at once but evaluated lazily which is useful if the iterator (for example, a generator) contains objects with a large memory footprint. Parameters ========== data_processor : func A processing function that is applied to objects in `data_generator` data_generator : iterator or generator A python iterator or generator that yields objects to be fed into the `data_processor` function for processing. n_cpus=1 : int (default: 1) Number of processes to run in parallel. - If `n_cpus` > 0, the specified number of CPUs will be used. - If `n_cpus=0`, all available CPUs will be used. - If `n_cpus` < 0, all available CPUs - `n_cpus` will be used. stepsize : int or None (default: None) The number of items to fetch from the iterator to pass on to the workers at a time. If `stepsize=None` (default), the stepsize size will be set equal to `n_cpus`. Returns ========= list : A Python list containing the results returned by the `data_processor` function when called on all elements in yielded by the `data_generator` in sorted order. Note that the last list may contain fewer items if the number of elements in `data_generator` is not evenly divisible by `stepsize`. """ if not n_cpus: n_cpus = mp.cpu_count() elif n_cpus < 0: n_cpus = mp.cpu_count() - n_cpus if stepsize is None: stepsize = n_cpus results = [] with mp.Pool(processes=n_cpus) as p: while True: r = p.map(data_processor, islice(data_generator, stepsize)) if r: results.extend(r) else: break return results
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952844980d4083eabe7b387de69c3d50b04abb9a
https://github.com/rasbt/mputil/blob/952844980d4083eabe7b387de69c3d50b04abb9a/mputil/map.py#L12-L68
train
rasbt/mputil
mputil/map.py
lazy_imap
def lazy_imap(data_processor, data_generator, n_cpus=1, stepsize=None): """A variant of multiprocessing.Pool.imap that supports lazy evaluation As with the regular multiprocessing.Pool.imap, the processes are spawned off asynchronously while the results are returned in order. In contrast to multiprocessing.Pool.imap, the iterator (here: data_generator) is not consumed at once but evaluated lazily which is useful if the iterator (for example, a generator) contains objects with a large memory footprint. Parameters ========== data_processor : func A processing function that is applied to objects in `data_generator` data_generator : iterator or generator A python iterator or generator that yields objects to be fed into the `data_processor` function for processing. n_cpus=1 : int (default: 1) Number of processes to run in parallel. - If `n_cpus` > 0, the specified number of CPUs will be used. - If `n_cpus=0`, all available CPUs will be used. - If `n_cpus` < 0, all available CPUs - `n_cpus` will be used. stepsize : int or None (default: None) The number of items to fetch from the iterator to pass on to the workers at a time. If `stepsize=None` (default), the stepsize size will be set equal to `n_cpus`. Returns ========= list : A Python list containing the *n* results returned by the `data_processor` function when called on elements by the `data_generator` in sorted order; *n* is equal to the size of `stepsize`. If `stepsize` is None, *n* is equal to `n_cpus`. """ if not n_cpus: n_cpus = mp.cpu_count() elif n_cpus < 0: n_cpus = mp.cpu_count() - n_cpus if stepsize is None: stepsize = n_cpus with mp.Pool(processes=n_cpus) as p: while True: r = p.map(data_processor, islice(data_generator, stepsize)) if r: yield r else: break
python
def lazy_imap(data_processor, data_generator, n_cpus=1, stepsize=None): """A variant of multiprocessing.Pool.imap that supports lazy evaluation As with the regular multiprocessing.Pool.imap, the processes are spawned off asynchronously while the results are returned in order. In contrast to multiprocessing.Pool.imap, the iterator (here: data_generator) is not consumed at once but evaluated lazily which is useful if the iterator (for example, a generator) contains objects with a large memory footprint. Parameters ========== data_processor : func A processing function that is applied to objects in `data_generator` data_generator : iterator or generator A python iterator or generator that yields objects to be fed into the `data_processor` function for processing. n_cpus=1 : int (default: 1) Number of processes to run in parallel. - If `n_cpus` > 0, the specified number of CPUs will be used. - If `n_cpus=0`, all available CPUs will be used. - If `n_cpus` < 0, all available CPUs - `n_cpus` will be used. stepsize : int or None (default: None) The number of items to fetch from the iterator to pass on to the workers at a time. If `stepsize=None` (default), the stepsize size will be set equal to `n_cpus`. Returns ========= list : A Python list containing the *n* results returned by the `data_processor` function when called on elements by the `data_generator` in sorted order; *n* is equal to the size of `stepsize`. If `stepsize` is None, *n* is equal to `n_cpus`. """ if not n_cpus: n_cpus = mp.cpu_count() elif n_cpus < 0: n_cpus = mp.cpu_count() - n_cpus if stepsize is None: stepsize = n_cpus with mp.Pool(processes=n_cpus) as p: while True: r = p.map(data_processor, islice(data_generator, stepsize)) if r: yield r else: break
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952844980d4083eabe7b387de69c3d50b04abb9a
https://github.com/rasbt/mputil/blob/952844980d4083eabe7b387de69c3d50b04abb9a/mputil/map.py#L71-L123
train
comtihon/catcher
catcher/steps/step.py
update_variables
def update_variables(func): """ Use this decorator on Step.action implementation. Your action method should always return variables, or both variables and output. This decorator will update variables with output. """ @wraps(func) def wrapper(self, *args, **kwargs): result = func(self, *args, **kwargs) if isinstance(result, tuple): return self.process_register(result[0], result[1]) else: return self.process_register(result) return wrapper
python
def update_variables(func): """ Use this decorator on Step.action implementation. Your action method should always return variables, or both variables and output. This decorator will update variables with output. """ @wraps(func) def wrapper(self, *args, **kwargs): result = func(self, *args, **kwargs) if isinstance(result, tuple): return self.process_register(result[0], result[1]) else: return self.process_register(result) return wrapper
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Use this decorator on Step.action implementation. Your action method should always return variables, or both variables and output. This decorator will update variables with output.
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5124e69d11cb6987daca595a61a4062d2b5f5ecc
https://github.com/comtihon/catcher/blob/5124e69d11cb6987daca595a61a4062d2b5f5ecc/catcher/steps/step.py#L156-L175
train
keans/lmnotify
lmnotify/models.py
AppModel._set_properties
def _set_properties(self, data): """ set the properties of the app model by the given data dict """ for property in data.keys(): if property in vars(self): setattr(self, property, data[property])
python
def _set_properties(self, data): """ set the properties of the app model by the given data dict """ for property in data.keys(): if property in vars(self): setattr(self, property, data[property])
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set the properties of the app model by the given data dict
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b0a5282a582e5090852dc20fea8a135ca258d0d3
https://github.com/keans/lmnotify/blob/b0a5282a582e5090852dc20fea8a135ca258d0d3/lmnotify/models.py#L18-L24
train
keans/lmnotify
setup.py
get_long_description
def get_long_description(): """ get long description from README.rst file """ with codecs.open(os.path.join(here, "README.rst"), "r", "utf-8") as f: return f.read()
python
def get_long_description(): """ get long description from README.rst file """ with codecs.open(os.path.join(here, "README.rst"), "r", "utf-8") as f: return f.read()
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get long description from README.rst file
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b0a5282a582e5090852dc20fea8a135ca258d0d3
https://github.com/keans/lmnotify/blob/b0a5282a582e5090852dc20fea8a135ca258d0d3/setup.py#L9-L14
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/actionHandlers/rollCallHandler.py
roll_call_handler
async def roll_call_handler(service, action_type, payload, props, **kwds): """ This action handler responds to the "roll call" emitted by the api gateway when it is brought up with the normal summary produced by the service. """ # if the action type corresponds to a roll call if action_type == roll_call_type(): # then announce the service await service.announce()
python
async def roll_call_handler(service, action_type, payload, props, **kwds): """ This action handler responds to the "roll call" emitted by the api gateway when it is brought up with the normal summary produced by the service. """ # if the action type corresponds to a roll call if action_type == roll_call_type(): # then announce the service await service.announce()
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This action handler responds to the "roll call" emitted by the api gateway when it is brought up with the normal summary produced by the service.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/actionHandlers/rollCallHandler.py#L3-L12
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/actionHandlers/flexibleAPIHandler.py
flexible_api_handler
async def flexible_api_handler(service, action_type, payload, props, **kwds): """ This query handler builds the dynamic picture of availible services. """ # if the action represents a new service if action_type == intialize_service_action(): # the treat the payload like json if its a string model = json.loads(payload) if isinstance(payload, str) else payload # the list of known models models = service._external_service_data['models'] # the list of known connections connections = service._external_service_data['connections'] # the list of known mutations mutations = service._external_service_data['mutations'] # if the model is a connection if 'connection' in model: # if we haven't seen the connection before if not [conn for conn in connections if conn['name'] == model['name']]: # add it to the list connections.append(model) # or if there are registered fields elif 'fields' in model and not [mod for mod in models if mod['name'] == model['name']]: # add it to the model list models.append(model) # the service could provide mutations as well as affect the topology if 'mutations' in model: # go over each mutation announce for mutation in model['mutations']: # if there isn't a mutation by the same name in the local cache if not [mut for mut in mutations if mut['name'] == mutation['name']]: # add it to the local cache mutations.append(mutation) # if there are models if models: # create a new schema corresponding to the models and connections service.schema = generate_api_schema( models=models, connections=connections, mutations=mutations, )
python
async def flexible_api_handler(service, action_type, payload, props, **kwds): """ This query handler builds the dynamic picture of availible services. """ # if the action represents a new service if action_type == intialize_service_action(): # the treat the payload like json if its a string model = json.loads(payload) if isinstance(payload, str) else payload # the list of known models models = service._external_service_data['models'] # the list of known connections connections = service._external_service_data['connections'] # the list of known mutations mutations = service._external_service_data['mutations'] # if the model is a connection if 'connection' in model: # if we haven't seen the connection before if not [conn for conn in connections if conn['name'] == model['name']]: # add it to the list connections.append(model) # or if there are registered fields elif 'fields' in model and not [mod for mod in models if mod['name'] == model['name']]: # add it to the model list models.append(model) # the service could provide mutations as well as affect the topology if 'mutations' in model: # go over each mutation announce for mutation in model['mutations']: # if there isn't a mutation by the same name in the local cache if not [mut for mut in mutations if mut['name'] == mutation['name']]: # add it to the local cache mutations.append(mutation) # if there are models if models: # create a new schema corresponding to the models and connections service.schema = generate_api_schema( models=models, connections=connections, mutations=mutations, )
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This query handler builds the dynamic picture of availible services.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/actionHandlers/flexibleAPIHandler.py#L7-L51
train
AlecAivazis/graphql-over-kafka
nautilus/api/filter.py
_parse_order_by
def _parse_order_by(model, order_by): """ This function figures out the list of orderings for the given model and argument. Args: model (nautilus.BaseModel): The model to compute ordering against order_by (list of str): the list of fields to order_by. If the field starts with a `+` then the order is acending, if `-` descending, if no character proceeds the field, the ordering is assumed to be ascending. Returns: (list of filters): the model filters to apply to the query """ # the list of filters for the models out = [] # for each attribute we have to order by for key in order_by: # remove any whitespace key = key.strip() # if the key starts with a plus if key.startswith("+"): # add the ascending filter to the list out.append(getattr(model, key[1:])) # otherwise if the key starts with a minus elif key.startswith("-"): # add the descending filter to the list out.append(getattr(model, key[1:]).desc()) # otherwise the key needs the default filter else: # add the default filter to the list out.append(getattr(model, key)) # returnt the list of filters return out
python
def _parse_order_by(model, order_by): """ This function figures out the list of orderings for the given model and argument. Args: model (nautilus.BaseModel): The model to compute ordering against order_by (list of str): the list of fields to order_by. If the field starts with a `+` then the order is acending, if `-` descending, if no character proceeds the field, the ordering is assumed to be ascending. Returns: (list of filters): the model filters to apply to the query """ # the list of filters for the models out = [] # for each attribute we have to order by for key in order_by: # remove any whitespace key = key.strip() # if the key starts with a plus if key.startswith("+"): # add the ascending filter to the list out.append(getattr(model, key[1:])) # otherwise if the key starts with a minus elif key.startswith("-"): # add the descending filter to the list out.append(getattr(model, key[1:]).desc()) # otherwise the key needs the default filter else: # add the default filter to the list out.append(getattr(model, key)) # returnt the list of filters return out
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/filter.py#L112-L147
train
AlecAivazis/graphql-over-kafka
nautilus/management/scripts/create.py
model
def model(model_names): """ Creates the example directory structure necessary for a model service. """ # for each model name we need to create for model_name in model_names: # the template context context = { 'name': model_name, } # render the model template render_template(template='common', context=context) render_template(template='model', context=context)
python
def model(model_names): """ Creates the example directory structure necessary for a model service. """ # for each model name we need to create for model_name in model_names: # the template context context = { 'name': model_name, } # render the model template render_template(template='common', context=context) render_template(template='model', context=context)
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Creates the example directory structure necessary for a model service.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/management/scripts/create.py#L19-L32
train
AlecAivazis/graphql-over-kafka
nautilus/management/scripts/create.py
api
def api(): """ Create the folder/directories for an ApiGateway service. """ # the template context context = { 'name': 'api', 'secret_key': random_string(32) } render_template(template='common', context=context) render_template(template='api', context=context)
python
def api(): """ Create the folder/directories for an ApiGateway service. """ # the template context context = { 'name': 'api', 'secret_key': random_string(32) } render_template(template='common', context=context) render_template(template='api', context=context)
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Create the folder/directories for an ApiGateway service.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/management/scripts/create.py#L36-L47
train
AlecAivazis/graphql-over-kafka
nautilus/management/scripts/create.py
auth
def auth(): """ Create the folder/directories for an Auth service. """ # the template context context = { 'name': 'auth', } render_template(template='common', context=context) render_template(template='auth', context=context)
python
def auth(): """ Create the folder/directories for an Auth service. """ # the template context context = { 'name': 'auth', } render_template(template='common', context=context) render_template(template='auth', context=context)
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Create the folder/directories for an Auth service.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/management/scripts/create.py#L51-L61
train
AlecAivazis/graphql-over-kafka
nautilus/management/scripts/create.py
connection
def connection(model_connections): """ Creates the example directory structure necessary for a connection service. """ # for each connection group for connection_str in model_connections: # the services to connect services = connection_str.split(':') services.sort() service_name = ''.join([service.title() for service in services]) # the template context context = { # make sure the first letter is lowercase 'name': service_name[0].lower() + service_name[1:], 'services': services, } render_template(template='common', context=context) render_template(template='connection', context=context)
python
def connection(model_connections): """ Creates the example directory structure necessary for a connection service. """ # for each connection group for connection_str in model_connections: # the services to connect services = connection_str.split(':') services.sort() service_name = ''.join([service.title() for service in services]) # the template context context = { # make sure the first letter is lowercase 'name': service_name[0].lower() + service_name[1:], 'services': services, } render_template(template='common', context=context) render_template(template='connection', context=context)
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Creates the example directory structure necessary for a connection service.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/management/scripts/create.py#L66-L89
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/models.py
get_model_string
def get_model_string(model): """ This function returns the conventional action designator for a given model. """ name = model if isinstance(model, str) else model.__name__ return normalize_string(name)
python
def get_model_string(model): """ This function returns the conventional action designator for a given model. """ name = model if isinstance(model, str) else model.__name__ return normalize_string(name)
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This function returns the conventional action designator for a given model.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/models.py#L8-L13
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/build_native_type_dictionary.py
build_native_type_dictionary
def build_native_type_dictionary(fields, respect_required=False, wrap_field=True, name=''): """ This function takes a list of type summaries and builds a dictionary with native representations of each entry. Useful for dynamically building native class records from summaries. """ # a place to start when building the input field attributes input_fields = {} # go over every input in the summary for field in fields: field_name = name + field['name'] field_type = field['type'] # if the type field is a string if isinstance(field_type, str): # compute the native api type for the field field_type = convert_typestring_to_api_native(field_type)( # required=respect_required and field['required'] ) # add an entry in the attributes input_fields[field['name']] = field_type # we could also be looking at a dictionary elif isinstance(field_type, dict): object_fields = field_type['fields'] # add the dictionary to the parent as a graphql object type input_fields[field['name']] = graphql_type_from_summary( summary={ 'name': field_name+"ArgType", 'fields': object_fields } ) # if we are supposed to wrap the object in a field if wrap_field: # then wrap the value we just added input_fields[field['name']] = graphene.Field(input_fields[field['name']]) # we're done return input_fields
python
def build_native_type_dictionary(fields, respect_required=False, wrap_field=True, name=''): """ This function takes a list of type summaries and builds a dictionary with native representations of each entry. Useful for dynamically building native class records from summaries. """ # a place to start when building the input field attributes input_fields = {} # go over every input in the summary for field in fields: field_name = name + field['name'] field_type = field['type'] # if the type field is a string if isinstance(field_type, str): # compute the native api type for the field field_type = convert_typestring_to_api_native(field_type)( # required=respect_required and field['required'] ) # add an entry in the attributes input_fields[field['name']] = field_type # we could also be looking at a dictionary elif isinstance(field_type, dict): object_fields = field_type['fields'] # add the dictionary to the parent as a graphql object type input_fields[field['name']] = graphql_type_from_summary( summary={ 'name': field_name+"ArgType", 'fields': object_fields } ) # if we are supposed to wrap the object in a field if wrap_field: # then wrap the value we just added input_fields[field['name']] = graphene.Field(input_fields[field['name']]) # we're done return input_fields
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/build_native_type_dictionary.py#L7-L49
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/summarize_crud_mutation.py
summarize_crud_mutation
def summarize_crud_mutation(method, model, isAsync=False): """ This function provides the standard form for crud mutations. """ # create the approrpriate action type action_type = get_crud_action(method=method, model=model) # the name of the mutation name = crud_mutation_name(model=model, action=method) # a mapping of methods to input factories input_map = { 'create': create_mutation_inputs, 'update': update_mutation_inputs, 'delete': delete_mutation_inputs, } # a mappting of methods to output factories output_map = { 'create': create_mutation_outputs, 'update': update_mutation_outputs, 'delete': delete_mutation_outputs, } # the inputs for the mutation inputs = input_map[method](model) # the mutation outputs outputs = output_map[method](model) # return the appropriate summary return summarize_mutation( mutation_name=name, event=action_type, isAsync=isAsync, inputs=inputs, outputs=outputs )
python
def summarize_crud_mutation(method, model, isAsync=False): """ This function provides the standard form for crud mutations. """ # create the approrpriate action type action_type = get_crud_action(method=method, model=model) # the name of the mutation name = crud_mutation_name(model=model, action=method) # a mapping of methods to input factories input_map = { 'create': create_mutation_inputs, 'update': update_mutation_inputs, 'delete': delete_mutation_inputs, } # a mappting of methods to output factories output_map = { 'create': create_mutation_outputs, 'update': update_mutation_outputs, 'delete': delete_mutation_outputs, } # the inputs for the mutation inputs = input_map[method](model) # the mutation outputs outputs = output_map[method](model) # return the appropriate summary return summarize_mutation( mutation_name=name, event=action_type, isAsync=isAsync, inputs=inputs, outputs=outputs )
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/summarize_crud_mutation.py#L15-L48
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/consumers/kafka.py
KafkaBroker.start
def start(self): """ This function starts the brokers interaction with the kafka stream """ self.loop.run_until_complete(self._consumer.start()) self.loop.run_until_complete(self._producer.start()) self._consumer_task = self.loop.create_task(self._consume_event_callback())
python
def start(self): """ This function starts the brokers interaction with the kafka stream """ self.loop.run_until_complete(self._consumer.start()) self.loop.run_until_complete(self._producer.start()) self._consumer_task = self.loop.create_task(self._consume_event_callback())
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/consumers/kafka.py#L88-L94
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/consumers/kafka.py
KafkaBroker.stop
def stop(self): """ This method stops the brokers interaction with the kafka stream """ self.loop.run_until_complete(self._consumer.stop()) self.loop.run_until_complete(self._producer.stop()) # attempt try: # to cancel the service self._consumer_task.cancel() # if there was no service except AttributeError: # keep going pass
python
def stop(self): """ This method stops the brokers interaction with the kafka stream """ self.loop.run_until_complete(self._consumer.stop()) self.loop.run_until_complete(self._producer.stop()) # attempt try: # to cancel the service self._consumer_task.cancel() # if there was no service except AttributeError: # keep going pass
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/consumers/kafka.py#L97-L111
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/consumers/kafka.py
KafkaBroker.send
async def send(self, payload='', action_type='', channel=None, **kwds): """ This method sends a message over the kafka stream. """ # use a custom channel if one was provided channel = channel or self.producer_channel # serialize the action type for the message = serialize_action(action_type=action_type, payload=payload, **kwds) # send the message return await self._producer.send(channel, message.encode())
python
async def send(self, payload='', action_type='', channel=None, **kwds): """ This method sends a message over the kafka stream. """ # use a custom channel if one was provided channel = channel or self.producer_channel # serialize the action type for the message = serialize_action(action_type=action_type, payload=payload, **kwds) # send the message return await self._producer.send(channel, message.encode())
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This method sends a message over the kafka stream.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/consumers/kafka.py#L114-L124
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/actions.py
serialize_action
def serialize_action(action_type, payload, **extra_fields): """ This function returns the conventional form of the actions. """ action_dict = dict( action_type=action_type, payload=payload, **extra_fields ) # return a serializable version return json.dumps(action_dict)
python
def serialize_action(action_type, payload, **extra_fields): """ This function returns the conventional form of the actions. """ action_dict = dict( action_type=action_type, payload=payload, **extra_fields ) # return a serializable version return json.dumps(action_dict)
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/actions.py#L27-L37
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/fields_for_model.py
fields_for_model
def fields_for_model(model): """ This function returns the fields for a schema that matches the provided nautilus model. Args: model (nautilus.model.BaseModel): The model to base the field list on Returns: (dict<field_name: str, graphqlType>): A mapping of field names to graphql types """ # the attribute arguments (no filters) args = {field.name.lower() : convert_peewee_field(field) \ for field in model.fields()} # use the field arguments, without the segments return args
python
def fields_for_model(model): """ This function returns the fields for a schema that matches the provided nautilus model. Args: model (nautilus.model.BaseModel): The model to base the field list on Returns: (dict<field_name: str, graphqlType>): A mapping of field names to graphql types """ # the attribute arguments (no filters) args = {field.name.lower() : convert_peewee_field(field) \ for field in model.fields()} # use the field arguments, without the segments return args
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/fields_for_model.py#L4-L21
train
AlecAivazis/graphql-over-kafka
nautilus/models/util.py
create_connection_model
def create_connection_model(service): """ Create an SQL Alchemy table that connects the provides services """ # the services connected services = service._services # the mixins / base for the model bases = (BaseModel,) # the fields of the derived attributes = {model_service_name(service): fields.CharField() for service in services} # create an instance of base model with the right attributes return type(BaseModel)(connection_service_name(service), bases, attributes)
python
def create_connection_model(service): """ Create an SQL Alchemy table that connects the provides services """ # the services connected services = service._services # the mixins / base for the model bases = (BaseModel,) # the fields of the derived attributes = {model_service_name(service): fields.CharField() for service in services} # create an instance of base model with the right attributes return type(BaseModel)(connection_service_name(service), bases, attributes)
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/models/util.py#L5-L16
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/actionHandlers/createHandler.py
create_handler
def create_handler(Model, name=None, **kwds): """ This factory returns an action handler that creates a new instance of the specified model when a create action is recieved, assuming the action follows nautilus convetions. Args: Model (nautilus.BaseModel): The model to create when the action received. Returns: function(action_type, payload): The action handler for this model """ async def action_handler(service, action_type, payload, props, notify=True, **kwds): # if the payload represents a new instance of `Model` if action_type == get_crud_action('create', name or Model): # print('handling create for ' + name or Model) try: # the props of the message message_props = {} # if there was a correlation id in the request if 'correlation_id' in props: # make sure it ends up in the reply message_props['correlation_id'] = props['correlation_id'] # for each required field for requirement in Model.required_fields(): # save the name of the field field_name = requirement.name # ensure the value is in the payload # TODO: check all required fields rather than failing on the first if not field_name in payload and field_name != 'id': # yell loudly raise ValueError( "Required field not found in payload: %s" %field_name ) # create a new model new_model = Model(**payload) # save the new model instance new_model.save() # if we need to tell someone about what happened if notify: # publish the scucess event await service.event_broker.send( payload=ModelSerializer().serialize(new_model), action_type=change_action_status(action_type, success_status()), **message_props ) # if something goes wrong except Exception as err: # if we need to tell someone about what happened if notify: # publish the error as an event await service.event_broker.send( payload=str(err), action_type=change_action_status(action_type, error_status()), **message_props ) # otherwise we aren't supposed to notify else: # raise the exception normally raise err # return the handler return action_handler
python
def create_handler(Model, name=None, **kwds): """ This factory returns an action handler that creates a new instance of the specified model when a create action is recieved, assuming the action follows nautilus convetions. Args: Model (nautilus.BaseModel): The model to create when the action received. Returns: function(action_type, payload): The action handler for this model """ async def action_handler(service, action_type, payload, props, notify=True, **kwds): # if the payload represents a new instance of `Model` if action_type == get_crud_action('create', name or Model): # print('handling create for ' + name or Model) try: # the props of the message message_props = {} # if there was a correlation id in the request if 'correlation_id' in props: # make sure it ends up in the reply message_props['correlation_id'] = props['correlation_id'] # for each required field for requirement in Model.required_fields(): # save the name of the field field_name = requirement.name # ensure the value is in the payload # TODO: check all required fields rather than failing on the first if not field_name in payload and field_name != 'id': # yell loudly raise ValueError( "Required field not found in payload: %s" %field_name ) # create a new model new_model = Model(**payload) # save the new model instance new_model.save() # if we need to tell someone about what happened if notify: # publish the scucess event await service.event_broker.send( payload=ModelSerializer().serialize(new_model), action_type=change_action_status(action_type, success_status()), **message_props ) # if something goes wrong except Exception as err: # if we need to tell someone about what happened if notify: # publish the error as an event await service.event_broker.send( payload=str(err), action_type=change_action_status(action_type, error_status()), **message_props ) # otherwise we aren't supposed to notify else: # raise the exception normally raise err # return the handler return action_handler
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/actionHandlers/createHandler.py#L12-L83
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/graph_entity.py
GraphEntity._has_id
async def _has_id(self, *args, **kwds): """ Equality checks are overwitten to perform the actual check in a semantic way. """ # if there is only one positional argument if len(args) == 1: # parse the appropriate query result = await parse_string( self._query, self.service.object_resolver, self.service.connection_resolver, self.service.mutation_resolver, obey_auth=False ) # go to the bottom of the result for the list of matching ids return self._find_id(result['data'], args[0]) # otherwise else: # treat the attribute like a normal filter return self._has_id(**kwds)
python
async def _has_id(self, *args, **kwds): """ Equality checks are overwitten to perform the actual check in a semantic way. """ # if there is only one positional argument if len(args) == 1: # parse the appropriate query result = await parse_string( self._query, self.service.object_resolver, self.service.connection_resolver, self.service.mutation_resolver, obey_auth=False ) # go to the bottom of the result for the list of matching ids return self._find_id(result['data'], args[0]) # otherwise else: # treat the attribute like a normal filter return self._has_id(**kwds)
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/graph_entity.py#L102-L122
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/graph_entity.py
GraphEntity._find_id
def _find_id(self, result, uid): """ This method performs a depth-first search for the given uid in the dictionary of results. """ # if the result is a list if isinstance(result, list): # if the list has a valid entry if any([self._find_id(value, uid) for value in result]): # then we're done return True # otherwise results could be dictionaries if isinstance(result, dict): # the children of the result that are lists list_children = [value for value in result.values() if isinstance(value, list)] # go to every value that is a list for value in list_children: # if the value is a match if self._find_id(value, uid): # we're done return True # the children of the result that are dicts dict_children = [value for value in result.values() if isinstance(value, dict)] # perform the check on every child that is a dict for value in dict_children: # if the child is a match if self._find_id(value, uid): # we're done return True # if there are no values that are lists and there is an id key if not list_children and not dict_children and 'id' in result: # the value of the remote id field result_id = result['id'] # we've found a match if the id field matches (cast to match type) return result_id == type(result_id)(uid) # we didn't find the result return False
python
def _find_id(self, result, uid): """ This method performs a depth-first search for the given uid in the dictionary of results. """ # if the result is a list if isinstance(result, list): # if the list has a valid entry if any([self._find_id(value, uid) for value in result]): # then we're done return True # otherwise results could be dictionaries if isinstance(result, dict): # the children of the result that are lists list_children = [value for value in result.values() if isinstance(value, list)] # go to every value that is a list for value in list_children: # if the value is a match if self._find_id(value, uid): # we're done return True # the children of the result that are dicts dict_children = [value for value in result.values() if isinstance(value, dict)] # perform the check on every child that is a dict for value in dict_children: # if the child is a match if self._find_id(value, uid): # we're done return True # if there are no values that are lists and there is an id key if not list_children and not dict_children and 'id' in result: # the value of the remote id field result_id = result['id'] # we've found a match if the id field matches (cast to match type) return result_id == type(result_id)(uid) # we didn't find the result return False
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/graph_entity.py#L126-L167
train
pyscaffold/configupdater
src/configupdater/configupdater.py
Block.add_before
def add_before(self): """Returns a builder inserting a new block before the current block""" idx = self._container.structure.index(self) return BlockBuilder(self._container, idx)
python
def add_before(self): """Returns a builder inserting a new block before the current block""" idx = self._container.structure.index(self) return BlockBuilder(self._container, idx)
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L115-L118
train
pyscaffold/configupdater
src/configupdater/configupdater.py
Block.add_after
def add_after(self): """Returns a builder inserting a new block after the current block""" idx = self._container.structure.index(self) return BlockBuilder(self._container, idx+1)
python
def add_after(self): """Returns a builder inserting a new block after the current block""" idx = self._container.structure.index(self) return BlockBuilder(self._container, idx+1)
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L121-L124
train
pyscaffold/configupdater
src/configupdater/configupdater.py
BlockBuilder.comment
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python
def comment(self, text, comment_prefix='#'): """Creates a comment block Args: text (str): content of comment without # comment_prefix (str): character indicating start of comment Returns: self for chaining """ comment = Comment(self._container) if not text.startswith(comment_prefix): text = "{} {}".format(comment_prefix, text) if not text.endswith('\n'): text = "{}{}".format(text, '\n') comment.add_line(text) self._container.structure.insert(self._idx, comment) self._idx += 1 return self
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L133-L151
train
pyscaffold/configupdater
src/configupdater/configupdater.py
BlockBuilder.section
def section(self, section): """Creates a section block Args: section (str or :class:`Section`): name of section or object Returns: self for chaining """ if not isinstance(self._container, ConfigUpdater): raise ValueError("Sections can only be added at section level!") if isinstance(section, str): # create a new section section = Section(section, container=self._container) elif not isinstance(section, Section): raise ValueError("Parameter must be a string or Section type!") if section.name in [block.name for block in self._container if isinstance(block, Section)]: raise DuplicateSectionError(section.name) self._container.structure.insert(self._idx, section) self._idx += 1 return self
python
def section(self, section): """Creates a section block Args: section (str or :class:`Section`): name of section or object Returns: self for chaining """ if not isinstance(self._container, ConfigUpdater): raise ValueError("Sections can only be added at section level!") if isinstance(section, str): # create a new section section = Section(section, container=self._container) elif not isinstance(section, Section): raise ValueError("Parameter must be a string or Section type!") if section.name in [block.name for block in self._container if isinstance(block, Section)]: raise DuplicateSectionError(section.name) self._container.structure.insert(self._idx, section) self._idx += 1 return self
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L153-L174
train
pyscaffold/configupdater
src/configupdater/configupdater.py
BlockBuilder.space
def space(self, newlines=1): """Creates a vertical space of newlines Args: newlines (int): number of empty lines Returns: self for chaining """ space = Space() for line in range(newlines): space.add_line('\n') self._container.structure.insert(self._idx, space) self._idx += 1 return self
python
def space(self, newlines=1): """Creates a vertical space of newlines Args: newlines (int): number of empty lines Returns: self for chaining """ space = Space() for line in range(newlines): space.add_line('\n') self._container.structure.insert(self._idx, space) self._idx += 1 return self
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Creates a vertical space of newlines Args: newlines (int): number of empty lines Returns: self for chaining
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L176-L190
train
pyscaffold/configupdater
src/configupdater/configupdater.py
BlockBuilder.option
def option(self, key, value=None, **kwargs): """Creates a new option inside a section Args: key (str): key of the option value (str or None): value of the option **kwargs: are passed to the constructor of :class:`Option` Returns: self for chaining """ if not isinstance(self._container, Section): raise ValueError("Options can only be added inside a section!") option = Option(key, value, container=self._container, **kwargs) option.value = value self._container.structure.insert(self._idx, option) self._idx += 1 return self
python
def option(self, key, value=None, **kwargs): """Creates a new option inside a section Args: key (str): key of the option value (str or None): value of the option **kwargs: are passed to the constructor of :class:`Option` Returns: self for chaining """ if not isinstance(self._container, Section): raise ValueError("Options can only be added inside a section!") option = Option(key, value, container=self._container, **kwargs) option.value = value self._container.structure.insert(self._idx, option) self._idx += 1 return self
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L192-L209
train
pyscaffold/configupdater
src/configupdater/configupdater.py
Section.add_comment
def add_comment(self, line): """Add a Comment object to the section Used during initial parsing mainly Args: line (str): one line in the comment """ if not isinstance(self.last_item, Comment): comment = Comment(self._structure) self._structure.append(comment) self.last_item.add_line(line) return self
python
def add_comment(self, line): """Add a Comment object to the section Used during initial parsing mainly Args: line (str): one line in the comment """ if not isinstance(self.last_item, Comment): comment = Comment(self._structure) self._structure.append(comment) self.last_item.add_line(line) return self
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Add a Comment object to the section Used during initial parsing mainly Args: line (str): one line in the comment
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L254-L266
train
pyscaffold/configupdater
src/configupdater/configupdater.py
Section.add_space
def add_space(self, line): """Add a Space object to the section Used during initial parsing mainly Args: line (str): one line that defines the space, maybe whitespaces """ if not isinstance(self.last_item, Space): space = Space(self._structure) self._structure.append(space) self.last_item.add_line(line) return self
python
def add_space(self, line): """Add a Space object to the section Used during initial parsing mainly Args: line (str): one line that defines the space, maybe whitespaces """ if not isinstance(self.last_item, Space): space = Space(self._structure) self._structure.append(space) self.last_item.add_line(line) return self
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L268-L280
train
pyscaffold/configupdater
src/configupdater/configupdater.py
Section.to_dict
def to_dict(self): """Transform to dictionary Returns: dict: dictionary with same content """ return {key: self.__getitem__(key).value for key in self.options()}
python
def to_dict(self): """Transform to dictionary Returns: dict: dictionary with same content """ return {key: self.__getitem__(key).value for key in self.options()}
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Transform to dictionary Returns: dict: dictionary with same content
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L356-L362
train
pyscaffold/configupdater
src/configupdater/configupdater.py
Section.set
def set(self, option, value=None): """Set an option for chaining. Args: option (str): option name value (str): value, default None """ option = self._container.optionxform(option) if option in self.options(): self.__getitem__(option).value = value else: self.__setitem__(option, value) return self
python
def set(self, option, value=None): """Set an option for chaining. Args: option (str): option name value (str): value, default None """ option = self._container.optionxform(option) if option in self.options(): self.__getitem__(option).value = value else: self.__setitem__(option, value) return self
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L379-L391
train
pyscaffold/configupdater
src/configupdater/configupdater.py
Option.set_values
def set_values(self, values, separator='\n', indent=4*' '): """Sets the value to a given list of options, e.g. multi-line values Args: values (list): list of values separator (str): separator for values, default: line separator indent (str): indentation depth in case of line separator """ self._updated = True self._multiline_value_joined = True self._values = values if separator == '\n': values.insert(0, '') separator = separator + indent self._value = separator.join(values)
python
def set_values(self, values, separator='\n', indent=4*' '): """Sets the value to a given list of options, e.g. multi-line values Args: values (list): list of values separator (str): separator for values, default: line separator indent (str): indentation depth in case of line separator """ self._updated = True self._multiline_value_joined = True self._values = values if separator == '\n': values.insert(0, '') separator = separator + indent self._value = separator.join(values)
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L478-L492
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.read
def read(self, filename, encoding=None): """Read and parse a filename. Args: filename (str): path to file encoding (str): encoding of file, default None """ with open(filename, encoding=encoding) as fp: self._read(fp, filename) self._filename = os.path.abspath(filename)
python
def read(self, filename, encoding=None): """Read and parse a filename. Args: filename (str): path to file encoding (str): encoding of file, default None """ with open(filename, encoding=encoding) as fp: self._read(fp, filename) self._filename = os.path.abspath(filename)
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Read and parse a filename. Args: filename (str): path to file encoding (str): encoding of file, default None
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L597-L606
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.update_file
def update_file(self): """Update the read-in configuration file. """ if self._filename is None: raise NoConfigFileReadError() with open(self._filename, 'w') as fb: self.write(fb)
python
def update_file(self): """Update the read-in configuration file. """ if self._filename is None: raise NoConfigFileReadError() with open(self._filename, 'w') as fb: self.write(fb)
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Update the read-in configuration file.
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L825-L831
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.validate_format
def validate_format(self, **kwargs): """Call ConfigParser to validate config Args: kwargs: are passed to :class:`configparser.ConfigParser` """ args = dict( dict_type=self._dict, allow_no_value=self._allow_no_value, inline_comment_prefixes=self._inline_comment_prefixes, strict=self._strict, empty_lines_in_values=self._empty_lines_in_values ) args.update(kwargs) parser = ConfigParser(**args) updated_cfg = str(self) parser.read_string(updated_cfg)
python
def validate_format(self, **kwargs): """Call ConfigParser to validate config Args: kwargs: are passed to :class:`configparser.ConfigParser` """ args = dict( dict_type=self._dict, allow_no_value=self._allow_no_value, inline_comment_prefixes=self._inline_comment_prefixes, strict=self._strict, empty_lines_in_values=self._empty_lines_in_values ) args.update(kwargs) parser = ConfigParser(**args) updated_cfg = str(self) parser.read_string(updated_cfg)
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Call ConfigParser to validate config Args: kwargs: are passed to :class:`configparser.ConfigParser`
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L833-L849
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.add_section
def add_section(self, section): """Create a new section in the configuration. Raise DuplicateSectionError if a section by the specified name already exists. Raise ValueError if name is DEFAULT. Args: section (str or :class:`Section`): name or Section type """ if section in self.sections(): raise DuplicateSectionError(section) if isinstance(section, str): # create a new section section = Section(section, container=self) elif not isinstance(section, Section): raise ValueError("Parameter must be a string or Section type!") self._structure.append(section)
python
def add_section(self, section): """Create a new section in the configuration. Raise DuplicateSectionError if a section by the specified name already exists. Raise ValueError if name is DEFAULT. Args: section (str or :class:`Section`): name or Section type """ if section in self.sections(): raise DuplicateSectionError(section) if isinstance(section, str): # create a new section section = Section(section, container=self) elif not isinstance(section, Section): raise ValueError("Parameter must be a string or Section type!") self._structure.append(section)
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L912-L928
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.options
def options(self, section): """Returns list of configuration options for the named section. Args: section (str): name of section Returns: list: list of option names """ if not self.has_section(section): raise NoSectionError(section) from None return self.__getitem__(section).options()
python
def options(self, section): """Returns list of configuration options for the named section. Args: section (str): name of section Returns: list: list of option names """ if not self.has_section(section): raise NoSectionError(section) from None return self.__getitem__(section).options()
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L941-L952
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.get
def get(self, section, option): """Gets an option value for a given section. Args: section (str): section name option (str): option name Returns: :class:`Option`: Option object holding key/value pair """ if not self.has_section(section): raise NoSectionError(section) from None section = self.__getitem__(section) option = self.optionxform(option) try: value = section[option] except KeyError: raise NoOptionError(option, section) return value
python
def get(self, section, option): """Gets an option value for a given section. Args: section (str): section name option (str): option name Returns: :class:`Option`: Option object holding key/value pair """ if not self.has_section(section): raise NoSectionError(section) from None section = self.__getitem__(section) option = self.optionxform(option) try: value = section[option] except KeyError: raise NoOptionError(option, section) return value
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L954-L974
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.items
def items(self, section=_UNSET): """Return a list of (name, value) tuples for options or sections. If section is given, return a list of tuples with (name, value) for each option in the section. Otherwise, return a list of tuples with (section_name, section_type) for each section. Args: section (str): optional section name, default UNSET Returns: list: list of :class:`Section` or :class:`Option` objects """ if section is _UNSET: return [(sect.name, sect) for sect in self.sections_blocks()] section = self.__getitem__(section) return [(opt.key, opt) for opt in section.option_blocks()]
python
def items(self, section=_UNSET): """Return a list of (name, value) tuples for options or sections. If section is given, return a list of tuples with (name, value) for each option in the section. Otherwise, return a list of tuples with (section_name, section_type) for each section. Args: section (str): optional section name, default UNSET Returns: list: list of :class:`Section` or :class:`Option` objects """ if section is _UNSET: return [(sect.name, sect) for sect in self.sections_blocks()] section = self.__getitem__(section) return [(opt.key, opt) for opt in section.option_blocks()]
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Return a list of (name, value) tuples for options or sections. If section is given, return a list of tuples with (name, value) for each option in the section. Otherwise, return a list of tuples with (section_name, section_type) for each section. Args: section (str): optional section name, default UNSET Returns: list: list of :class:`Section` or :class:`Option` objects
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L976-L993
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.has_option
def has_option(self, section, option): """Checks for the existence of a given option in a given section. Args: section (str): name of section option (str): name of option Returns: bool: whether the option exists in the given section """ if section not in self.sections(): return False else: option = self.optionxform(option) return option in self[section]
python
def has_option(self, section, option): """Checks for the existence of a given option in a given section. Args: section (str): name of section option (str): name of option Returns: bool: whether the option exists in the given section """ if section not in self.sections(): return False else: option = self.optionxform(option) return option in self[section]
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L995-L1009
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.set
def set(self, section, option, value=None): """Set an option. Args: section (str): section name option (str): option name value (str): value, default None """ try: section = self.__getitem__(section) except KeyError: raise NoSectionError(section) from None option = self.optionxform(option) if option in section: section[option].value = value else: section[option] = value return self
python
def set(self, section, option, value=None): """Set an option. Args: section (str): section name option (str): option name value (str): value, default None """ try: section = self.__getitem__(section) except KeyError: raise NoSectionError(section) from None option = self.optionxform(option) if option in section: section[option].value = value else: section[option] = value return self
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L1011-L1028
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.remove_option
def remove_option(self, section, option): """Remove an option. Args: section (str): section name option (str): option name Returns: bool: whether the option was actually removed """ try: section = self.__getitem__(section) except KeyError: raise NoSectionError(section) from None option = self.optionxform(option) existed = option in section.options() if existed: del section[option] return existed
python
def remove_option(self, section, option): """Remove an option. Args: section (str): section name option (str): option name Returns: bool: whether the option was actually removed """ try: section = self.__getitem__(section) except KeyError: raise NoSectionError(section) from None option = self.optionxform(option) existed = option in section.options() if existed: del section[option] return existed
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L1030-L1048
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.remove_section
def remove_section(self, name): """Remove a file section. Args: name: name of the section Returns: bool: whether the section was actually removed """ existed = self.has_section(name) if existed: idx = self._get_section_idx(name) del self._structure[idx] return existed
python
def remove_section(self, name): """Remove a file section. Args: name: name of the section Returns: bool: whether the section was actually removed """ existed = self.has_section(name) if existed: idx = self._get_section_idx(name) del self._structure[idx] return existed
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L1050-L1063
train
pyscaffold/configupdater
src/configupdater/configupdater.py
ConfigUpdater.to_dict
def to_dict(self): """Transform to dictionary Returns: dict: dictionary with same content """ return {sect: self.__getitem__(sect).to_dict() for sect in self.sections()}
python
def to_dict(self): """Transform to dictionary Returns: dict: dictionary with same content """ return {sect: self.__getitem__(sect).to_dict() for sect in self.sections()}
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6ebac0b1fa7b8222baacdd4991d18cfc61659f84
https://github.com/pyscaffold/configupdater/blob/6ebac0b1fa7b8222baacdd4991d18cfc61659f84/src/configupdater/configupdater.py#L1065-L1072
train
AlecAivazis/graphql-over-kafka
nautilus/management/util/render_template.py
render_template
def render_template(template, out_dir='.', context=None): ''' This function renders the template desginated by the argument to the designated directory using the given context. Args: template (string) : the source template to use (relative to ./templates) out_dir (string) : the name of the output directory context (dict) : the template rendering context ''' # the directory containing templates template_directory = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', 'templates', template ) # the files and empty directories to copy files = [] empty_dirs = [] for (dirpath, _, filenames) in os.walk(template_directory): # if there are no files in the directory if len(filenames) == 0: # add the directory to the list empty_dirs.append(os.path.relpath(dirpath, template_directory)) # otherwise there are files in this directory else: # add the files to the list files.extend([os.path.join(dirpath, filepath) for filepath in filenames]) # for each template file for source_file in files: # open a new file that we are going to write to with open(source_file, 'r') as file: # create a template out of the source file contents template = Template(file.read()) # render the template with the given contents template_rendered = template.render(**(context or {})) # the location of the source relative to the template directory source_relpath = os.path.relpath(source_file, template_directory) # the target filename filename = os.path.join(out_dir, source_relpath) # create a jinja template out of the file path filename_rendered = Template(filename).render(**context) # the directory of the target file source_dir = os.path.dirname(filename_rendered) # if the directory doesn't exist if not os.path.exists(source_dir): # create the directories os.makedirs(source_dir) # create the target file with open(filename_rendered, 'w') as target_file: # write the rendered template to the target file target_file.write(template_rendered) # for each empty directory for dirpath in empty_dirs: try: # dirname dirname = os.path.join(out_dir, dirpath) # treat the dirname as a jinja template dirname_rendered = Template(dirname).render(**context) # if the directory doesn't exist if not os.path.exists(dirname_rendered): # create the directory in the target, replacing the name os.makedirs(dirname_rendered) except OSError as exc: # if the directory already exists if exc.errno == errno.EEXIST and os.path.isdir(dirpath): # keep going (noop) pass # otherwise its an error we don't handle else: # pass it along raise
python
def render_template(template, out_dir='.', context=None): ''' This function renders the template desginated by the argument to the designated directory using the given context. Args: template (string) : the source template to use (relative to ./templates) out_dir (string) : the name of the output directory context (dict) : the template rendering context ''' # the directory containing templates template_directory = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', 'templates', template ) # the files and empty directories to copy files = [] empty_dirs = [] for (dirpath, _, filenames) in os.walk(template_directory): # if there are no files in the directory if len(filenames) == 0: # add the directory to the list empty_dirs.append(os.path.relpath(dirpath, template_directory)) # otherwise there are files in this directory else: # add the files to the list files.extend([os.path.join(dirpath, filepath) for filepath in filenames]) # for each template file for source_file in files: # open a new file that we are going to write to with open(source_file, 'r') as file: # create a template out of the source file contents template = Template(file.read()) # render the template with the given contents template_rendered = template.render(**(context or {})) # the location of the source relative to the template directory source_relpath = os.path.relpath(source_file, template_directory) # the target filename filename = os.path.join(out_dir, source_relpath) # create a jinja template out of the file path filename_rendered = Template(filename).render(**context) # the directory of the target file source_dir = os.path.dirname(filename_rendered) # if the directory doesn't exist if not os.path.exists(source_dir): # create the directories os.makedirs(source_dir) # create the target file with open(filename_rendered, 'w') as target_file: # write the rendered template to the target file target_file.write(template_rendered) # for each empty directory for dirpath in empty_dirs: try: # dirname dirname = os.path.join(out_dir, dirpath) # treat the dirname as a jinja template dirname_rendered = Template(dirname).render(**context) # if the directory doesn't exist if not os.path.exists(dirname_rendered): # create the directory in the target, replacing the name os.makedirs(dirname_rendered) except OSError as exc: # if the directory already exists if exc.errno == errno.EEXIST and os.path.isdir(dirpath): # keep going (noop) pass # otherwise its an error we don't handle else: # pass it along raise
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/management/util/render_template.py#L6-L86
train
AlecAivazis/graphql-over-kafka
nautilus/management/scripts/events/publish.py
publish
def publish(type, payload): """ Publish a message with the specified action_type and payload over the event system. Useful for debugging. """ async def _produce(): # fire an action with the given values await producer.send(action_type=type, payload=payload) # notify the user that we were successful print("Successfully dispatched action with type {}.".format(type)) # create a producer producer = ActionHandler() # start the producer producer.start() # get the current event loop loop = asyncio.get_event_loop() # run the production sequence loop.run_until_complete(_produce()) # start the producer producer.stop()
python
def publish(type, payload): """ Publish a message with the specified action_type and payload over the event system. Useful for debugging. """ async def _produce(): # fire an action with the given values await producer.send(action_type=type, payload=payload) # notify the user that we were successful print("Successfully dispatched action with type {}.".format(type)) # create a producer producer = ActionHandler() # start the producer producer.start() # get the current event loop loop = asyncio.get_event_loop() # run the production sequence loop.run_until_complete(_produce()) # start the producer producer.stop()
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/management/scripts/events/publish.py#L15-L38
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/actionHandlers/deleteHandler.py
delete_handler
def delete_handler(Model, name=None, **kwds): """ This factory returns an action handler that deletes a new instance of the specified model when a delete action is recieved, assuming the action follows nautilus convetions. Args: Model (nautilus.BaseModel): The model to delete when the action received. Returns: function(type, payload): The action handler for this model """ # necessary imports from nautilus.database import db async def action_handler(service, action_type, payload, props, notify=True, **kwds): # if the payload represents a new instance of `model` if action_type == get_crud_action('delete', name or Model): try: # the props of the message message_props = {} # if there was a correlation id in the request if 'correlation_id' in props: # make sure it ends up in the reply message_props['correlation_id'] = props['correlation_id'] # the id in the payload representing the record to delete record_id = payload['id'] if 'id' in payload else payload['pk'] # get the model matching the payload try: model_query = Model.select().where(Model.primary_key() == record_id) except KeyError: raise RuntimeError("Could not find appropriate id to remove service record.") # remove the model instance model_query.get().delete_instance() # if we need to tell someone about what happened if notify: # publish the success event await service.event_broker.send( payload='{"status":"ok"}', action_type=change_action_status(action_type, success_status()), **message_props ) # if something goes wrong except Exception as err: # if we need to tell someone about what happened if notify: # publish the error as an event await service.event_broker.send( payload=str(err), action_type=change_action_status(action_type, error_status()), **message_props ) # otherwise we aren't supposed to notify else: # raise the exception normally raise err # return the handler return action_handler
python
def delete_handler(Model, name=None, **kwds): """ This factory returns an action handler that deletes a new instance of the specified model when a delete action is recieved, assuming the action follows nautilus convetions. Args: Model (nautilus.BaseModel): The model to delete when the action received. Returns: function(type, payload): The action handler for this model """ # necessary imports from nautilus.database import db async def action_handler(service, action_type, payload, props, notify=True, **kwds): # if the payload represents a new instance of `model` if action_type == get_crud_action('delete', name or Model): try: # the props of the message message_props = {} # if there was a correlation id in the request if 'correlation_id' in props: # make sure it ends up in the reply message_props['correlation_id'] = props['correlation_id'] # the id in the payload representing the record to delete record_id = payload['id'] if 'id' in payload else payload['pk'] # get the model matching the payload try: model_query = Model.select().where(Model.primary_key() == record_id) except KeyError: raise RuntimeError("Could not find appropriate id to remove service record.") # remove the model instance model_query.get().delete_instance() # if we need to tell someone about what happened if notify: # publish the success event await service.event_broker.send( payload='{"status":"ok"}', action_type=change_action_status(action_type, success_status()), **message_props ) # if something goes wrong except Exception as err: # if we need to tell someone about what happened if notify: # publish the error as an event await service.event_broker.send( payload=str(err), action_type=change_action_status(action_type, error_status()), **message_props ) # otherwise we aren't supposed to notify else: # raise the exception normally raise err # return the handler return action_handler
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/actionHandlers/deleteHandler.py#L10-L71
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/actionHandlers/readHandler.py
read_handler
def read_handler(Model, name=None, **kwds): """ This factory returns an action handler that responds to read requests by resolving the payload as a graphql query against the internal schema. Args: Model (nautilus.BaseModel): The model to delete when the action received. Returns: function(type, payload): The action handler for this model """ async def action_handler(service, action_type, payload, props, **kwds): # if the payload represents a new instance of `model` if action_type == get_crud_action('read', name or Model): # the props of the message message_props = {} # if there was a correlation id in the request if 'correlation_id' in props: # make sure it ends up in the reply message_props['correlation_id'] = props['correlation_id'] try: # resolve the query using the service schema resolved = service.schema.execute(payload) # create the string response response = json.dumps({ 'data': {key:value for key,value in resolved.data.items()}, 'errors': resolved.errors }) # publish the success event await service.event_broker.send( payload=response, action_type=change_action_status(action_type, success_status()), **message_props ) # if something goes wrong except Exception as err: # publish the error as an event await service.event_broker.send( payload=str(err), action_type=change_action_status(action_type, error_status()), **message_props ) # return the handler return action_handler
python
def read_handler(Model, name=None, **kwds): """ This factory returns an action handler that responds to read requests by resolving the payload as a graphql query against the internal schema. Args: Model (nautilus.BaseModel): The model to delete when the action received. Returns: function(type, payload): The action handler for this model """ async def action_handler(service, action_type, payload, props, **kwds): # if the payload represents a new instance of `model` if action_type == get_crud_action('read', name or Model): # the props of the message message_props = {} # if there was a correlation id in the request if 'correlation_id' in props: # make sure it ends up in the reply message_props['correlation_id'] = props['correlation_id'] try: # resolve the query using the service schema resolved = service.schema.execute(payload) # create the string response response = json.dumps({ 'data': {key:value for key,value in resolved.data.items()}, 'errors': resolved.errors }) # publish the success event await service.event_broker.send( payload=response, action_type=change_action_status(action_type, success_status()), **message_props ) # if something goes wrong except Exception as err: # publish the error as an event await service.event_broker.send( payload=str(err), action_type=change_action_status(action_type, error_status()), **message_props ) # return the handler return action_handler
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/actionHandlers/readHandler.py#L6-L56
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/actionHandlers/crudHandler.py
crud_handler
def crud_handler(Model, name=None, **kwds): """ This action handler factory reaturns an action handler that responds to actions with CRUD types (following nautilus conventions) and performs the necessary mutation on the model's database. Args: Model (nautilus.BaseModel): The model to delete when the action received. Returns: function(type, payload): The action handler for this model """ # import the necessary modules from nautilus.network.events import combine_action_handlers from . import update_handler, create_handler, delete_handler, read_handler # combine them into one handler return combine_action_handlers( create_handler(Model, name=name), read_handler(Model, name=name), update_handler(Model, name=name), delete_handler(Model, name=name), )
python
def crud_handler(Model, name=None, **kwds): """ This action handler factory reaturns an action handler that responds to actions with CRUD types (following nautilus conventions) and performs the necessary mutation on the model's database. Args: Model (nautilus.BaseModel): The model to delete when the action received. Returns: function(type, payload): The action handler for this model """ # import the necessary modules from nautilus.network.events import combine_action_handlers from . import update_handler, create_handler, delete_handler, read_handler # combine them into one handler return combine_action_handlers( create_handler(Model, name=name), read_handler(Model, name=name), update_handler(Model, name=name), delete_handler(Model, name=name), )
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/actionHandlers/crudHandler.py#L1-L25
train
AlecAivazis/graphql-over-kafka
nautilus/management/scripts/events/ask.py
ask
def ask(type, payload): """ Publish a message with the specified action_type and payload over the event system. Useful for debugging. """ async def _produce(): # notify the user that we were successful print("Dispatching action with type {}...".format(type)) # fire an action with the given values response = await producer.ask(action_type=type, payload=payload) # show the user the reply print(response) # create a producer producer = ActionHandler() # start the producer producer.start() # get the current event loop loop = asyncio.get_event_loop() # run the production sequence loop.run_until_complete(_produce()) # start the producer producer.stop()
python
def ask(type, payload): """ Publish a message with the specified action_type and payload over the event system. Useful for debugging. """ async def _produce(): # notify the user that we were successful print("Dispatching action with type {}...".format(type)) # fire an action with the given values response = await producer.ask(action_type=type, payload=payload) # show the user the reply print(response) # create a producer producer = ActionHandler() # start the producer producer.start() # get the current event loop loop = asyncio.get_event_loop() # run the production sequence loop.run_until_complete(_produce()) # start the producer producer.stop()
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/management/scripts/events/ask.py#L15-L40
train
AlecAivazis/graphql-over-kafka
nautilus/config/config.py
Config._from_type
def _from_type(self, config): """ This method converts a type into a dict. """ def is_user_attribute(attr): return ( not attr.startswith('__') and not isinstance(getattr(config, attr), collections.abc.Callable) ) return {attr: getattr(config, attr) for attr in dir(config) \ if is_user_attribute(attr)}
python
def _from_type(self, config): """ This method converts a type into a dict. """ def is_user_attribute(attr): return ( not attr.startswith('__') and not isinstance(getattr(config, attr), collections.abc.Callable) ) return {attr: getattr(config, attr) for attr in dir(config) \ if is_user_attribute(attr)}
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/config/config.py#L41-L52
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/walk_query.py
walk_query
async def walk_query(obj, object_resolver, connection_resolver, errors, current_user=None, __naut_name=None, obey_auth=True, **filters): """ This function traverses a query and collects the corresponding information in a dictionary. """ # if the object has no selection set if not hasattr(obj, 'selection_set'): # yell loudly raise ValueError("Can only resolve objects, not primitive types") # the name of the node node_name = __naut_name or obj.name.value if obj.name else obj.operation # the selected fields selection_set = obj.selection_set.selections def _build_arg_tree(arg): """ This function recursively builds the arguments for lists and single values """ # TODO: what about object arguments?? # if there is a single value if hasattr(arg, 'value'): # assign the value to the filter return arg.value # otherwise if there are multiple values for the argument elif hasattr(arg, 'values'): return [_build_arg_tree(node) for node in arg.values] # for each argument on this node for arg in obj.arguments: # add it to the query filters filters[arg.name.value] = _build_arg_tree(arg.value) # the fields we have to ask for fields = [field for field in selection_set if not field.selection_set] # the links between objects connections = [field for field in selection_set if field.selection_set] try: # resolve the model with the given fields models = await object_resolver(node_name, [field.name.value for field in fields], current_user=current_user, obey_auth=obey_auth, **filters) # if something went wrong resolving the object except Exception as e: # add the error as a string errors.append(e.__str__()) # stop here return None # add connections to each matching model for model in models: # if is an id for the model if 'pk' in model: # for each connection for connection in connections: # the name of the connection connection_name = connection.name.value # the target of the connection node = { 'name': node_name, 'pk': model['pk'] } try: # go through the connection connected_ids, next_target = await connection_resolver( connection_name, node, ) # if there are connections if connected_ids: # add the id filter to the list filters['pk_in'] = connected_ids # add the connection field value = await walk_query( connection, object_resolver, connection_resolver, errors, current_user=current_user, obey_auth=obey_auth, __naut_name=next_target, **filters ) # there were no connections else: value = [] # if something went wrong except Exception as e: # add the error as a string errors.append(e.__str__()) # stop here value = None # set the connection to the appropriate value model[connection_name] = value # return the list of matching models return models
python
async def walk_query(obj, object_resolver, connection_resolver, errors, current_user=None, __naut_name=None, obey_auth=True, **filters): """ This function traverses a query and collects the corresponding information in a dictionary. """ # if the object has no selection set if not hasattr(obj, 'selection_set'): # yell loudly raise ValueError("Can only resolve objects, not primitive types") # the name of the node node_name = __naut_name or obj.name.value if obj.name else obj.operation # the selected fields selection_set = obj.selection_set.selections def _build_arg_tree(arg): """ This function recursively builds the arguments for lists and single values """ # TODO: what about object arguments?? # if there is a single value if hasattr(arg, 'value'): # assign the value to the filter return arg.value # otherwise if there are multiple values for the argument elif hasattr(arg, 'values'): return [_build_arg_tree(node) for node in arg.values] # for each argument on this node for arg in obj.arguments: # add it to the query filters filters[arg.name.value] = _build_arg_tree(arg.value) # the fields we have to ask for fields = [field for field in selection_set if not field.selection_set] # the links between objects connections = [field for field in selection_set if field.selection_set] try: # resolve the model with the given fields models = await object_resolver(node_name, [field.name.value for field in fields], current_user=current_user, obey_auth=obey_auth, **filters) # if something went wrong resolving the object except Exception as e: # add the error as a string errors.append(e.__str__()) # stop here return None # add connections to each matching model for model in models: # if is an id for the model if 'pk' in model: # for each connection for connection in connections: # the name of the connection connection_name = connection.name.value # the target of the connection node = { 'name': node_name, 'pk': model['pk'] } try: # go through the connection connected_ids, next_target = await connection_resolver( connection_name, node, ) # if there are connections if connected_ids: # add the id filter to the list filters['pk_in'] = connected_ids # add the connection field value = await walk_query( connection, object_resolver, connection_resolver, errors, current_user=current_user, obey_auth=obey_auth, __naut_name=next_target, **filters ) # there were no connections else: value = [] # if something went wrong except Exception as e: # add the error as a string errors.append(e.__str__()) # stop here value = None # set the connection to the appropriate value model[connection_name] = value # return the list of matching models return models
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/walk_query.py#L1-L102
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/actionHandlers/queryHandler.py
query_handler
async def query_handler(service, action_type, payload, props, **kwds): """ This action handler interprets the payload as a query to be executed by the api gateway service. """ # check that the action type indicates a query if action_type == query_action_type(): print('encountered query event {!r} '.format(payload)) # perform the query result = await parse_string(payload, service.object_resolver, service.connection_resolver, service.mutation_resolver, obey_auth=False ) # the props for the reply message reply_props = {'correlation_id': props['correlation_id']} if 'correlation_id' in props else {} # publish the success event await service.event_broker.send( payload=result, action_type=change_action_status(action_type, success_status()), **reply_props )
python
async def query_handler(service, action_type, payload, props, **kwds): """ This action handler interprets the payload as a query to be executed by the api gateway service. """ # check that the action type indicates a query if action_type == query_action_type(): print('encountered query event {!r} '.format(payload)) # perform the query result = await parse_string(payload, service.object_resolver, service.connection_resolver, service.mutation_resolver, obey_auth=False ) # the props for the reply message reply_props = {'correlation_id': props['correlation_id']} if 'correlation_id' in props else {} # publish the success event await service.event_broker.send( payload=result, action_type=change_action_status(action_type, success_status()), **reply_props )
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/actionHandlers/queryHandler.py#L5-L29
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/summarize_mutation_io.py
summarize_mutation_io
def summarize_mutation_io(name, type, required=False): """ This function returns the standard summary for mutations inputs and outputs """ return dict( name=name, type=type, required=required )
python
def summarize_mutation_io(name, type, required=False): """ This function returns the standard summary for mutations inputs and outputs """ return dict( name=name, type=type, required=required )
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/summarize_mutation_io.py#L1-L10
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/api.py
crud_mutation_name
def crud_mutation_name(action, model): """ This function returns the name of a mutation that performs the specified crud action on the given model service """ model_string = get_model_string(model) # make sure the mutation name is correctly camelcases model_string = model_string[0].upper() + model_string[1:] # return the mutation name return "{}{}".format(action, model_string)
python
def crud_mutation_name(action, model): """ This function returns the name of a mutation that performs the specified crud action on the given model service """ model_string = get_model_string(model) # make sure the mutation name is correctly camelcases model_string = model_string[0].upper() + model_string[1:] # return the mutation name return "{}{}".format(action, model_string)
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/api.py#L15-L25
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/api.py
create_mutation_inputs
def create_mutation_inputs(service): """ Args: service : The service being created by the mutation Returns: (list) : a list of all of the fields availible for the service, with the required ones respected. """ # grab the default list of field summaries inputs = _service_mutation_summaries(service) # make sure the pk isn't in the list inputs.remove([field for field in inputs if field['name'] == 'id'][0]) # return the final list return inputs
python
def create_mutation_inputs(service): """ Args: service : The service being created by the mutation Returns: (list) : a list of all of the fields availible for the service, with the required ones respected. """ # grab the default list of field summaries inputs = _service_mutation_summaries(service) # make sure the pk isn't in the list inputs.remove([field for field in inputs if field['name'] == 'id'][0]) # return the final list return inputs
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/api.py#L28-L42
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/api.py
update_mutation_inputs
def update_mutation_inputs(service): """ Args: service : The service being updated by the mutation Returns: (list) : a list of all of the fields availible for the service. Pk is a required field in order to filter the results """ # grab the default list of field summaries inputs = _service_mutation_summaries(service) # visit each field for field in inputs: # if we're looking at the id field if field['name'] == 'id': # make sure its required field['required'] = True # but no other field else: # is required field['required'] = False # return the final list return inputs
python
def update_mutation_inputs(service): """ Args: service : The service being updated by the mutation Returns: (list) : a list of all of the fields availible for the service. Pk is a required field in order to filter the results """ # grab the default list of field summaries inputs = _service_mutation_summaries(service) # visit each field for field in inputs: # if we're looking at the id field if field['name'] == 'id': # make sure its required field['required'] = True # but no other field else: # is required field['required'] = False # return the final list return inputs
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/api.py#L57-L80
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/api.py
delete_mutation_inputs
def delete_mutation_inputs(service): """ Args: service : The service being deleted by the mutation Returns: ([str]): the only input for delete is the pk of the service. """ from nautilus.api.util import summarize_mutation_io # the only input for delete events is the pk of the service record return [summarize_mutation_io(name='pk', type='ID', required=True)]
python
def delete_mutation_inputs(service): """ Args: service : The service being deleted by the mutation Returns: ([str]): the only input for delete is the pk of the service. """ from nautilus.api.util import summarize_mutation_io # the only input for delete events is the pk of the service record return [summarize_mutation_io(name='pk', type='ID', required=True)]
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/api.py#L96-L106
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/api.py
_summarize_o_mutation_type
def _summarize_o_mutation_type(model): """ This function create the actual mutation io summary corresponding to the model """ from nautilus.api.util import summarize_mutation_io # compute the appropriate name for the object object_type_name = get_model_string(model) # return a mutation io object return summarize_mutation_io( name=object_type_name, type=_summarize_object_type(model), required=False )
python
def _summarize_o_mutation_type(model): """ This function create the actual mutation io summary corresponding to the model """ from nautilus.api.util import summarize_mutation_io # compute the appropriate name for the object object_type_name = get_model_string(model) # return a mutation io object return summarize_mutation_io( name=object_type_name, type=_summarize_object_type(model), required=False )
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/api.py#L134-L147
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/api.py
_summarize_object_type
def _summarize_object_type(model): """ This function returns the summary for a given model """ # the fields for the service's model model_fields = {field.name: field for field in list(model.fields())} # summarize the model return { 'fields': [{ 'name': key, 'type': type(convert_peewee_field(value)).__name__ } for key, value in model_fields.items() ] }
python
def _summarize_object_type(model): """ This function returns the summary for a given model """ # the fields for the service's model model_fields = {field.name: field for field in list(model.fields())} # summarize the model return { 'fields': [{ 'name': key, 'type': type(convert_peewee_field(value)).__name__ } for key, value in model_fields.items() ] }
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/api.py#L149-L162
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/util.py
combine_action_handlers
def combine_action_handlers(*handlers): """ This function combines the given action handlers into a single function which will call all of them. """ # make sure each of the given handlers is callable for handler in handlers: # if the handler is not a function if not (iscoroutinefunction(handler) or iscoroutine(handler)): # yell loudly raise ValueError("Provided handler is not a coroutine: %s" % handler) # the combined action handler async def combined_handler(*args, **kwds): # goes over every given handler for handler in handlers: # call the handler await handler(*args, **kwds) # return the combined action handler return combined_handler
python
def combine_action_handlers(*handlers): """ This function combines the given action handlers into a single function which will call all of them. """ # make sure each of the given handlers is callable for handler in handlers: # if the handler is not a function if not (iscoroutinefunction(handler) or iscoroutine(handler)): # yell loudly raise ValueError("Provided handler is not a coroutine: %s" % handler) # the combined action handler async def combined_handler(*args, **kwds): # goes over every given handler for handler in handlers: # call the handler await handler(*args, **kwds) # return the combined action handler return combined_handler
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/util.py#L6-L26
train
AlecAivazis/graphql-over-kafka
nautilus/network/events/actionHandlers/updateHandler.py
update_handler
def update_handler(Model, name=None, **kwds): """ This factory returns an action handler that updates a new instance of the specified model when a update action is recieved, assuming the action follows nautilus convetions. Args: Model (nautilus.BaseModel): The model to update when the action received. Returns: function(type, payload): The action handler for this model """ async def action_handler(service, action_type, payload, props, notify=True, **kwds): # if the payload represents a new instance of `Model` if action_type == get_crud_action('update', name or Model): try: # the props of the message message_props = {} # if there was a correlation id in the request if 'correlation_id' in props: # make sure it ends up in the reply message_props['correlation_id'] = props['correlation_id'] # grab the nam eof the primary key for the model pk_field = Model.primary_key() # make sure there is a primary key to id the model if not pk_field.name in payload: # yell loudly raise ValueError("Must specify the pk of the model when updating") # grab the matching model model = Model.select().where(pk_field == payload[pk_field.name]).get() # remove the key from the payload payload.pop(pk_field.name, None) # for every key,value pair for key, value in payload.items(): # TODO: add protection for certain fields from being # changed by the api setattr(model, key, value) # save the updates model.save() # if we need to tell someone about what happened if notify: # publish the scucess event await service.event_broker.send( payload=ModelSerializer().serialize(model), action_type=change_action_status(action_type, success_status()), **message_props ) # if something goes wrong except Exception as err: # if we need to tell someone about what happened if notify: # publish the error as an event await service.event_broker.send( payload=str(err), action_type=change_action_status(action_type, error_status()), **message_props ) # otherwise we aren't supposed to notify else: # raise the exception normally raise err # return the handler return action_handler
python
def update_handler(Model, name=None, **kwds): """ This factory returns an action handler that updates a new instance of the specified model when a update action is recieved, assuming the action follows nautilus convetions. Args: Model (nautilus.BaseModel): The model to update when the action received. Returns: function(type, payload): The action handler for this model """ async def action_handler(service, action_type, payload, props, notify=True, **kwds): # if the payload represents a new instance of `Model` if action_type == get_crud_action('update', name or Model): try: # the props of the message message_props = {} # if there was a correlation id in the request if 'correlation_id' in props: # make sure it ends up in the reply message_props['correlation_id'] = props['correlation_id'] # grab the nam eof the primary key for the model pk_field = Model.primary_key() # make sure there is a primary key to id the model if not pk_field.name in payload: # yell loudly raise ValueError("Must specify the pk of the model when updating") # grab the matching model model = Model.select().where(pk_field == payload[pk_field.name]).get() # remove the key from the payload payload.pop(pk_field.name, None) # for every key,value pair for key, value in payload.items(): # TODO: add protection for certain fields from being # changed by the api setattr(model, key, value) # save the updates model.save() # if we need to tell someone about what happened if notify: # publish the scucess event await service.event_broker.send( payload=ModelSerializer().serialize(model), action_type=change_action_status(action_type, success_status()), **message_props ) # if something goes wrong except Exception as err: # if we need to tell someone about what happened if notify: # publish the error as an event await service.event_broker.send( payload=str(err), action_type=change_action_status(action_type, error_status()), **message_props ) # otherwise we aren't supposed to notify else: # raise the exception normally raise err # return the handler return action_handler
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/network/events/actionHandlers/updateHandler.py#L10-L83
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/graphql_mutation_from_summary.py
graphql_mutation_from_summary
def graphql_mutation_from_summary(summary): """ This function returns a graphql mutation corresponding to the provided summary. """ # get the name of the mutation from the summary mutation_name = summary['name'] # print(summary) # the treat the "type" string as a gra input_name = mutation_name + "Input" input_fields = build_native_type_dictionary(summary['inputs'], name=input_name, respect_required=True) # the inputs for the mutation are defined by a class record inputs = type('Input', (object,), input_fields) # the outputs for the mutation are attributes to the class record output_name = mutation_name + "Output" outputs = build_native_type_dictionary(summary['outputs'], name=output_name) # a no-op in order to satisfy the introspection query mutate = classmethod(lambda *_, **__ : 'hello') # create the appropriate mutation class record mutation = type(mutation_name, (graphene.Mutation,), { 'Input': inputs, 'mutate': mutate, **outputs }) # return the newly created mutation record return mutation
python
def graphql_mutation_from_summary(summary): """ This function returns a graphql mutation corresponding to the provided summary. """ # get the name of the mutation from the summary mutation_name = summary['name'] # print(summary) # the treat the "type" string as a gra input_name = mutation_name + "Input" input_fields = build_native_type_dictionary(summary['inputs'], name=input_name, respect_required=True) # the inputs for the mutation are defined by a class record inputs = type('Input', (object,), input_fields) # the outputs for the mutation are attributes to the class record output_name = mutation_name + "Output" outputs = build_native_type_dictionary(summary['outputs'], name=output_name) # a no-op in order to satisfy the introspection query mutate = classmethod(lambda *_, **__ : 'hello') # create the appropriate mutation class record mutation = type(mutation_name, (graphene.Mutation,), { 'Input': inputs, 'mutate': mutate, **outputs }) # return the newly created mutation record return mutation
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/graphql_mutation_from_summary.py#L6-L38
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/arg_string_from_dict.py
arg_string_from_dict
def arg_string_from_dict(arg_dict, **kwds): """ This function takes a series of ditionaries and creates an argument string for a graphql query """ # the filters dictionary filters = { **arg_dict, **kwds, } # return the correctly formed string return ", ".join("{}: {}".format(key, json.dumps(value)) for key,value in filters.items())
python
def arg_string_from_dict(arg_dict, **kwds): """ This function takes a series of ditionaries and creates an argument string for a graphql query """ # the filters dictionary filters = { **arg_dict, **kwds, } # return the correctly formed string return ", ".join("{}: {}".format(key, json.dumps(value)) for key,value in filters.items())
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/arg_string_from_dict.py#L3-L14
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/create_model_schema.py
create_model_schema
def create_model_schema(target_model): """ This function creates a graphql schema that provides a single model """ from nautilus.database import db # create the schema instance schema = graphene.Schema(auto_camelcase=False) # grab the primary key from the model primary_key = target_model.primary_key() primary_key_type = convert_peewee_field(primary_key) # create a graphene object class ModelObjectType(PeeweeObjectType): class Meta: model = target_model pk = Field(primary_key_type, description="The primary key for this object.") @graphene.resolve_only_args def resolve_pk(self): return getattr(self, self.primary_key().name) class Query(graphene.ObjectType): """ the root level query """ all_models = List(ModelObjectType, args=args_for_model(target_model)) @graphene.resolve_only_args def resolve_all_models(self, **args): # filter the model query according to the arguments # print(filter_model(target_model, args)[0].__dict__) return filter_model(target_model, args) # add the query to the schema schema.query = Query return schema
python
def create_model_schema(target_model): """ This function creates a graphql schema that provides a single model """ from nautilus.database import db # create the schema instance schema = graphene.Schema(auto_camelcase=False) # grab the primary key from the model primary_key = target_model.primary_key() primary_key_type = convert_peewee_field(primary_key) # create a graphene object class ModelObjectType(PeeweeObjectType): class Meta: model = target_model pk = Field(primary_key_type, description="The primary key for this object.") @graphene.resolve_only_args def resolve_pk(self): return getattr(self, self.primary_key().name) class Query(graphene.ObjectType): """ the root level query """ all_models = List(ModelObjectType, args=args_for_model(target_model)) @graphene.resolve_only_args def resolve_all_models(self, **args): # filter the model query according to the arguments # print(filter_model(target_model, args)[0].__dict__) return filter_model(target_model, args) # add the query to the schema schema.query = Query return schema
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This function creates a graphql schema that provides a single model
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/create_model_schema.py#L9-L48
train
AlecAivazis/graphql-over-kafka
nautilus/conventions/services.py
connection_service_name
def connection_service_name(service, *args): ''' the name of a service that manages the connection between services ''' # if the service is a string if isinstance(service, str): return service return normalize_string(type(service).__name__)
python
def connection_service_name(service, *args): ''' the name of a service that manages the connection between services ''' # if the service is a string if isinstance(service, str): return service return normalize_string(type(service).__name__)
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/conventions/services.py#L22-L28
train
AlecAivazis/graphql-over-kafka
nautilus/auth/util/read_session_token.py
read_session_token
def read_session_token(secret_key, token): """ This function verifies the token using the secret key and returns its contents. """ return jwt.decode(token.encode('utf-8'), secret_key, algorithms=[token_encryption_algorithm()] )
python
def read_session_token(secret_key, token): """ This function verifies the token using the secret key and returns its contents. """ return jwt.decode(token.encode('utf-8'), secret_key, algorithms=[token_encryption_algorithm()] )
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This function verifies the token using the secret key and returns its contents.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/auth/util/read_session_token.py#L6-L13
train
AlecAivazis/graphql-over-kafka
nautilus/services/service.py
ServiceActionHandler.handle_action
async def handle_action(self, action_type, payload, **kwds): """ The default action Handler has no action. """ # if there is a service attached to the action handler if hasattr(self, 'service'): # handle roll calls await roll_call_handler(self.service, action_type, payload, **kwds)
python
async def handle_action(self, action_type, payload, **kwds): """ The default action Handler has no action. """ # if there is a service attached to the action handler if hasattr(self, 'service'): # handle roll calls await roll_call_handler(self.service, action_type, payload, **kwds)
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The default action Handler has no action.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/service.py#L47-L54
train
AlecAivazis/graphql-over-kafka
nautilus/services/service.py
Service.announce
async def announce(self): """ This method is used to announce the existence of the service """ # send a serialized event await self.event_broker.send( action_type=intialize_service_action(), payload=json.dumps(self.summarize()) )
python
async def announce(self): """ This method is used to announce the existence of the service """ # send a serialized event await self.event_broker.send( action_type=intialize_service_action(), payload=json.dumps(self.summarize()) )
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/service.py#L166-L174
train
AlecAivazis/graphql-over-kafka
nautilus/services/service.py
Service.run
def run(self, host="localhost", port=8000, shutdown_timeout=60.0, **kwargs): """ This function starts the service's network intefaces. Args: port (int): The port for the http server. """ print("Running service on http://localhost:%i. " % port + \ "Press Ctrl+C to terminate.") # apply the configuration to the service config self.config.port = port self.config.host = host # start the loop try: # if an event broker has been created for this service if self.event_broker: # start the broker self.event_broker.start() # announce the service self.loop.run_until_complete(self.announce()) # the handler for the http server http_handler = self.app.make_handler() # create an asyncio server self._http_server = self.loop.create_server(http_handler, host, port) # grab the handler for the server callback self._server_handler = self.loop.run_until_complete(self._http_server) # start the event loop self.loop.run_forever() # if the user interrupted the server except KeyboardInterrupt: # keep going pass # when we're done finally: try: # clean up the service self.cleanup() # if we end up closing before any variables get assigned except UnboundLocalError: # just ignore it (there was nothing to close) pass # close the event loop self.loop.close()
python
def run(self, host="localhost", port=8000, shutdown_timeout=60.0, **kwargs): """ This function starts the service's network intefaces. Args: port (int): The port for the http server. """ print("Running service on http://localhost:%i. " % port + \ "Press Ctrl+C to terminate.") # apply the configuration to the service config self.config.port = port self.config.host = host # start the loop try: # if an event broker has been created for this service if self.event_broker: # start the broker self.event_broker.start() # announce the service self.loop.run_until_complete(self.announce()) # the handler for the http server http_handler = self.app.make_handler() # create an asyncio server self._http_server = self.loop.create_server(http_handler, host, port) # grab the handler for the server callback self._server_handler = self.loop.run_until_complete(self._http_server) # start the event loop self.loop.run_forever() # if the user interrupted the server except KeyboardInterrupt: # keep going pass # when we're done finally: try: # clean up the service self.cleanup() # if we end up closing before any variables get assigned except UnboundLocalError: # just ignore it (there was nothing to close) pass # close the event loop self.loop.close()
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This function starts the service's network intefaces. Args: port (int): The port for the http server.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/service.py#L208-L257
train
AlecAivazis/graphql-over-kafka
nautilus/services/service.py
Service.cleanup
def cleanup(self): """ This function is called when the service has finished running regardless of intentionally or not. """ # if an event broker has been created for this service if self.event_broker: # stop the event broker self.event_broker.stop() # attempt try: # close the http server self._server_handler.close() self.loop.run_until_complete(self._server_handler.wait_closed()) self.loop.run_until_complete(self._http_handler.finish_connections(shutdown_timeout)) # if there was no handler except AttributeError: # keep going pass # more cleanup self.loop.run_until_complete(self.app.shutdown()) self.loop.run_until_complete(self.app.cleanup())
python
def cleanup(self): """ This function is called when the service has finished running regardless of intentionally or not. """ # if an event broker has been created for this service if self.event_broker: # stop the event broker self.event_broker.stop() # attempt try: # close the http server self._server_handler.close() self.loop.run_until_complete(self._server_handler.wait_closed()) self.loop.run_until_complete(self._http_handler.finish_connections(shutdown_timeout)) # if there was no handler except AttributeError: # keep going pass # more cleanup self.loop.run_until_complete(self.app.shutdown()) self.loop.run_until_complete(self.app.cleanup())
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This function is called when the service has finished running regardless of intentionally or not.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/service.py#L260-L284
train
AlecAivazis/graphql-over-kafka
nautilus/services/service.py
Service.add_http_endpoint
def add_http_endpoint(self, url, request_handler): """ This method provides a programatic way of added invidual routes to the http server. Args: url (str): the url to be handled by the request_handler request_handler (nautilus.network.RequestHandler): The request handler """ self.app.router.add_route('*', url, request_handler)
python
def add_http_endpoint(self, url, request_handler): """ This method provides a programatic way of added invidual routes to the http server. Args: url (str): the url to be handled by the request_handler request_handler (nautilus.network.RequestHandler): The request handler """ self.app.router.add_route('*', url, request_handler)
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This method provides a programatic way of added invidual routes to the http server. Args: url (str): the url to be handled by the request_handler request_handler (nautilus.network.RequestHandler): The request handler
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/service.py#L287-L296
train
AlecAivazis/graphql-over-kafka
nautilus/services/service.py
Service.route
def route(cls, route, config=None): """ This method provides a decorator for adding endpoints to the http server. Args: route (str): The url to be handled by the RequestHandled config (dict): Configuration for the request handler Example: .. code-block:: python import nautilus from nauilus.network.http import RequestHandler class MyService(nautilus.Service): # ... @MyService.route('/') class HelloWorld(RequestHandler): def get(self): return self.finish('hello world') """ def decorator(wrapped_class, **kwds): # add the endpoint at the given route cls._routes.append( dict(url=route, request_handler=wrapped_class) ) # return the class undecorated return wrapped_class # return the decorator return decorator
python
def route(cls, route, config=None): """ This method provides a decorator for adding endpoints to the http server. Args: route (str): The url to be handled by the RequestHandled config (dict): Configuration for the request handler Example: .. code-block:: python import nautilus from nauilus.network.http import RequestHandler class MyService(nautilus.Service): # ... @MyService.route('/') class HelloWorld(RequestHandler): def get(self): return self.finish('hello world') """ def decorator(wrapped_class, **kwds): # add the endpoint at the given route cls._routes.append( dict(url=route, request_handler=wrapped_class) ) # return the class undecorated return wrapped_class # return the decorator return decorator
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/service.py#L300-L334
train
AlecAivazis/graphql-over-kafka
nautilus/auth/util/generate_session_token.py
generate_session_token
def generate_session_token(secret_key, **payload): """ This function generates a session token signed by the secret key which can be used to extract the user credentials in a verifiable way. """ return jwt.encode(payload, secret_key, algorithm=token_encryption_algorithm()).decode('utf-8')
python
def generate_session_token(secret_key, **payload): """ This function generates a session token signed by the secret key which can be used to extract the user credentials in a verifiable way. """ return jwt.encode(payload, secret_key, algorithm=token_encryption_algorithm()).decode('utf-8')
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This function generates a session token signed by the secret key which can be used to extract the user credentials in a verifiable way.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/auth/util/generate_session_token.py#L6-L11
train
AlecAivazis/graphql-over-kafka
nautilus/api/util/summarize_mutation.py
summarize_mutation
def summarize_mutation(mutation_name, event, inputs, outputs, isAsync=False): """ This function provides a standard representation of mutations to be used when services announce themselves """ return dict( name=mutation_name, event=event, isAsync=isAsync, inputs=inputs, outputs=outputs, )
python
def summarize_mutation(mutation_name, event, inputs, outputs, isAsync=False): """ This function provides a standard representation of mutations to be used when services announce themselves """ return dict( name=mutation_name, event=event, isAsync=isAsync, inputs=inputs, outputs=outputs, )
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This function provides a standard representation of mutations to be used when services announce themselves
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/api/util/summarize_mutation.py#L1-L12
train
AlecAivazis/graphql-over-kafka
nautilus/auth/primitives/passwordHash.py
PasswordHash.new
def new(cls, password, rounds): """Creates a PasswordHash from the given password.""" if isinstance(password, str): password = password.encode('utf-8') return cls(cls._new(password, rounds))
python
def new(cls, password, rounds): """Creates a PasswordHash from the given password.""" if isinstance(password, str): password = password.encode('utf-8') return cls(cls._new(password, rounds))
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Creates a PasswordHash from the given password.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/auth/primitives/passwordHash.py#L51-L55
train
AlecAivazis/graphql-over-kafka
nautilus/auth/primitives/passwordHash.py
PasswordHash.coerce
def coerce(cls, key, value): """Ensure that loaded values are PasswordHashes.""" if isinstance(value, PasswordHash): return value return super(PasswordHash, cls).coerce(key, value)
python
def coerce(cls, key, value): """Ensure that loaded values are PasswordHashes.""" if isinstance(value, PasswordHash): return value return super(PasswordHash, cls).coerce(key, value)
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/auth/primitives/passwordHash.py#L59-L63
train
AlecAivazis/graphql-over-kafka
nautilus/auth/primitives/passwordHash.py
PasswordHash.rehash
def rehash(self, password): """Recreates the internal hash.""" self.hash = self._new(password, self.desired_rounds) self.rounds = self.desired_rounds
python
def rehash(self, password): """Recreates the internal hash.""" self.hash = self._new(password, self.desired_rounds) self.rounds = self.desired_rounds
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Recreates the internal hash.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/auth/primitives/passwordHash.py#L75-L78
train
AlecAivazis/graphql-over-kafka
nautilus/services/modelService.py
ModelService.init_db
def init_db(self): """ This function configures the database used for models to make the configuration parameters. """ # get the database url from the configuration db_url = self.config.get('database_url', 'sqlite:///nautilus.db') # configure the nautilus database to the url nautilus.database.init_db(db_url)
python
def init_db(self): """ This function configures the database used for models to make the configuration parameters. """ # get the database url from the configuration db_url = self.config.get('database_url', 'sqlite:///nautilus.db') # configure the nautilus database to the url nautilus.database.init_db(db_url)
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This function configures the database used for models to make the configuration parameters.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/modelService.py#L101-L109
train
AlecAivazis/graphql-over-kafka
nautilus/services/apiGateway.py
APIGateway.auth_criteria
def auth_criteria(self): """ This attribute provides the mapping of services to their auth requirement Returns: (dict) : the mapping from services to their auth requirements. """ # the dictionary we will return auth = {} # go over each attribute of the service for attr in dir(self): # make sure we could hit an infinite loop if attr != 'auth_criteria': # get the actual attribute attribute = getattr(self, attr) # if the service represents an auth criteria if isinstance(attribute, Callable) and hasattr(attribute, '_service_auth'): # add the criteria to the final results auth[getattr(self, attr)._service_auth] = attribute # return the auth mapping return auth
python
def auth_criteria(self): """ This attribute provides the mapping of services to their auth requirement Returns: (dict) : the mapping from services to their auth requirements. """ # the dictionary we will return auth = {} # go over each attribute of the service for attr in dir(self): # make sure we could hit an infinite loop if attr != 'auth_criteria': # get the actual attribute attribute = getattr(self, attr) # if the service represents an auth criteria if isinstance(attribute, Callable) and hasattr(attribute, '_service_auth'): # add the criteria to the final results auth[getattr(self, attr)._service_auth] = attribute # return the auth mapping return auth
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This attribute provides the mapping of services to their auth requirement Returns: (dict) : the mapping from services to their auth requirements.
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/apiGateway.py#L87-L109
train
AlecAivazis/graphql-over-kafka
nautilus/services/apiGateway.py
APIGateway.login_user
async def login_user(self, password, **kwds): """ This function handles the registration of the given user credentials in the database """ # find the matching user with the given email user_data = (await self._get_matching_user(fields=list(kwds.keys()), **kwds))['data'] try: # look for a matching entry in the local database passwordEntry = self.model.select().where( self.model.user == user_data[root_query()][0]['pk'] )[0] # if we couldn't acess the id of the result except (KeyError, IndexError) as e: # yell loudly raise RuntimeError('Could not find matching registered user') # if the given password matches the stored hash if passwordEntry and passwordEntry.password == password: # the remote entry for the user user = user_data[root_query()][0] # then return a dictionary with the user and sessionToken return { 'user': user, 'sessionToken': self._user_session_token(user) } # otherwise the passwords don't match raise RuntimeError("Incorrect credentials")
python
async def login_user(self, password, **kwds): """ This function handles the registration of the given user credentials in the database """ # find the matching user with the given email user_data = (await self._get_matching_user(fields=list(kwds.keys()), **kwds))['data'] try: # look for a matching entry in the local database passwordEntry = self.model.select().where( self.model.user == user_data[root_query()][0]['pk'] )[0] # if we couldn't acess the id of the result except (KeyError, IndexError) as e: # yell loudly raise RuntimeError('Could not find matching registered user') # if the given password matches the stored hash if passwordEntry and passwordEntry.password == password: # the remote entry for the user user = user_data[root_query()][0] # then return a dictionary with the user and sessionToken return { 'user': user, 'sessionToken': self._user_session_token(user) } # otherwise the passwords don't match raise RuntimeError("Incorrect credentials")
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This function handles the registration of the given user credentials in the database
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/apiGateway.py#L144-L172
train
AlecAivazis/graphql-over-kafka
nautilus/services/apiGateway.py
APIGateway.register_user
async def register_user(self, password, **kwds): """ This function is used to provide a sessionToken for later requests. Args: uid (str): The """ # so make one user = await self._create_remote_user(password=password, **kwds) # if there is no pk field if not 'pk' in user: # make sure the user has a pk field user['pk'] = user['id'] # the query to find a matching query match_query = self.model.user == user['id'] # if the user has already been registered if self.model.select().where(match_query).count() > 0: # yell loudly raise RuntimeError('The user is already registered.') # create an entry in the user password table password = self.model(user=user['id'], password=password) # save it to the database password.save() # return a dictionary with the user we created and a session token for later use return { 'user': user, 'sessionToken': self._user_session_token(user) }
python
async def register_user(self, password, **kwds): """ This function is used to provide a sessionToken for later requests. Args: uid (str): The """ # so make one user = await self._create_remote_user(password=password, **kwds) # if there is no pk field if not 'pk' in user: # make sure the user has a pk field user['pk'] = user['id'] # the query to find a matching query match_query = self.model.user == user['id'] # if the user has already been registered if self.model.select().where(match_query).count() > 0: # yell loudly raise RuntimeError('The user is already registered.') # create an entry in the user password table password = self.model(user=user['id'], password=password) # save it to the database password.save() # return a dictionary with the user we created and a session token for later use return { 'user': user, 'sessionToken': self._user_session_token(user) }
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This function is used to provide a sessionToken for later requests. Args: uid (str): The
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/apiGateway.py#L175-L207
train
AlecAivazis/graphql-over-kafka
nautilus/services/apiGateway.py
APIGateway.object_resolver
async def object_resolver(self, object_name, fields, obey_auth=False, current_user=None, **filters): """ This function resolves a given object in the remote backend services """ try: # check if an object with that name has been registered registered = [model for model in self._external_service_data['models'] \ if model['name']==object_name][0] # if there is no connection data yet except AttributeError: raise ValueError("No objects are registered with this schema yet.") # if we dont recognize the model that was requested except IndexError: raise ValueError("Cannot query for object {} on this service.".format(object_name)) # the valid fields for this object valid_fields = [field['name'] for field in registered['fields']] # figure out if any invalid fields were requested invalid_fields = [field for field in fields if field not in valid_fields] try: # make sure we never treat pk as invalid invalid_fields.remove('pk') # if they weren't asking for pk as a field except ValueError: pass # if there were if invalid_fields: # yell loudly raise ValueError("Cannot query for fields {!r} on {}".format( invalid_fields, registered['name'] )) # make sure we include the id in the request fields.append('pk') # the query for model records query = query_for_model(fields, **filters) # the action type for the question action_type = get_crud_action('read', object_name) # query the appropriate stream for the information response = await self.event_broker.ask( action_type=action_type, payload=query ) # treat the reply like a json object response_data = json.loads(response) # if something went wrong if 'errors' in response_data and response_data['errors']: # return an empty response raise ValueError(','.join(response_data['errors'])) # grab the valid list of matches result = response_data['data'][root_query()] # grab the auth handler for the object auth_criteria = self.auth_criteria.get(object_name) # if we care about auth requirements and there is one for this object if obey_auth and auth_criteria: # build a second list of authorized entries authorized_results = [] # for each query result for query_result in result: # create a graph entity for the model graph_entity = GraphEntity(self, model_type=object_name, id=query_result['pk']) # if the auth handler passes if await auth_criteria(model=graph_entity, user_id=current_user): # add the result to the final list authorized_results.append(query_result) # overwrite the query result result = authorized_results # apply the auth handler to the result return result
python
async def object_resolver(self, object_name, fields, obey_auth=False, current_user=None, **filters): """ This function resolves a given object in the remote backend services """ try: # check if an object with that name has been registered registered = [model for model in self._external_service_data['models'] \ if model['name']==object_name][0] # if there is no connection data yet except AttributeError: raise ValueError("No objects are registered with this schema yet.") # if we dont recognize the model that was requested except IndexError: raise ValueError("Cannot query for object {} on this service.".format(object_name)) # the valid fields for this object valid_fields = [field['name'] for field in registered['fields']] # figure out if any invalid fields were requested invalid_fields = [field for field in fields if field not in valid_fields] try: # make sure we never treat pk as invalid invalid_fields.remove('pk') # if they weren't asking for pk as a field except ValueError: pass # if there were if invalid_fields: # yell loudly raise ValueError("Cannot query for fields {!r} on {}".format( invalid_fields, registered['name'] )) # make sure we include the id in the request fields.append('pk') # the query for model records query = query_for_model(fields, **filters) # the action type for the question action_type = get_crud_action('read', object_name) # query the appropriate stream for the information response = await self.event_broker.ask( action_type=action_type, payload=query ) # treat the reply like a json object response_data = json.loads(response) # if something went wrong if 'errors' in response_data and response_data['errors']: # return an empty response raise ValueError(','.join(response_data['errors'])) # grab the valid list of matches result = response_data['data'][root_query()] # grab the auth handler for the object auth_criteria = self.auth_criteria.get(object_name) # if we care about auth requirements and there is one for this object if obey_auth and auth_criteria: # build a second list of authorized entries authorized_results = [] # for each query result for query_result in result: # create a graph entity for the model graph_entity = GraphEntity(self, model_type=object_name, id=query_result['pk']) # if the auth handler passes if await auth_criteria(model=graph_entity, user_id=current_user): # add the result to the final list authorized_results.append(query_result) # overwrite the query result result = authorized_results # apply the auth handler to the result return result
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/apiGateway.py#L210-L293
train
AlecAivazis/graphql-over-kafka
nautilus/services/apiGateway.py
APIGateway.mutation_resolver
async def mutation_resolver(self, mutation_name, args, fields): """ the default behavior for mutations is to look up the event, publish the correct event type with the args as the body, and return the fields contained in the result """ try: # make sure we can identify the mutation mutation_summary = [mutation for mutation in \ self._external_service_data['mutations'] \ if mutation['name'] == mutation_name][0] # if we couldn't get the first entry in the list except KeyError as e: # make sure the error is reported raise ValueError("Could not execute mutation named: " + mutation_name) # the function to use for running the mutation depends on its schronicity # event_function = self.event_broker.ask \ # if mutation_summary['isAsync'] else self.event_broker.send event_function = self.event_broker.ask # send the event and wait for a response value = await event_function( action_type=mutation_summary['event'], payload=args ) try: # return a dictionary with the values we asked for return json.loads(value) # if the result was not valid json except json.decoder.JSONDecodeError: # just throw the value raise RuntimeError(value)
python
async def mutation_resolver(self, mutation_name, args, fields): """ the default behavior for mutations is to look up the event, publish the correct event type with the args as the body, and return the fields contained in the result """ try: # make sure we can identify the mutation mutation_summary = [mutation for mutation in \ self._external_service_data['mutations'] \ if mutation['name'] == mutation_name][0] # if we couldn't get the first entry in the list except KeyError as e: # make sure the error is reported raise ValueError("Could not execute mutation named: " + mutation_name) # the function to use for running the mutation depends on its schronicity # event_function = self.event_broker.ask \ # if mutation_summary['isAsync'] else self.event_broker.send event_function = self.event_broker.ask # send the event and wait for a response value = await event_function( action_type=mutation_summary['event'], payload=args ) try: # return a dictionary with the values we asked for return json.loads(value) # if the result was not valid json except json.decoder.JSONDecodeError: # just throw the value raise RuntimeError(value)
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the default behavior for mutations is to look up the event, publish the correct event type with the args as the body, and return the fields contained in the result
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/apiGateway.py#L350-L385
train
AlecAivazis/graphql-over-kafka
nautilus/services/apiGateway.py
APIGateway._check_for_matching_user
async def _check_for_matching_user(self, **user_filters): """ This function checks if there is a user with the same uid in the remote user service Args: **kwds : the filters of the user to check for Returns: (bool): wether or not there is a matching user """ # there is a matching user if there are no errors and no results from user_data = self._get_matching_user(user_filters) # return true if there were no errors and at lease one result return not user_data['errors'] and len(user_data['data'][root_query()])
python
async def _check_for_matching_user(self, **user_filters): """ This function checks if there is a user with the same uid in the remote user service Args: **kwds : the filters of the user to check for Returns: (bool): wether or not there is a matching user """ # there is a matching user if there are no errors and no results from user_data = self._get_matching_user(user_filters) # return true if there were no errors and at lease one result return not user_data['errors'] and len(user_data['data'][root_query()])
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/apiGateway.py#L434-L447
train
AlecAivazis/graphql-over-kafka
nautilus/services/apiGateway.py
APIGateway._create_remote_user
async def _create_remote_user(self, **payload): """ This method creates a service record in the remote user service with the given email. Args: uid (str): the user identifier to create Returns: (dict): a summary of the user that was created """ # the action for reading user entries read_action = get_crud_action(method='create', model='user') # see if there is a matching user user_data = await self.event_broker.ask( action_type=read_action, payload=payload ) # treat the reply like a json object return json.loads(user_data)
python
async def _create_remote_user(self, **payload): """ This method creates a service record in the remote user service with the given email. Args: uid (str): the user identifier to create Returns: (dict): a summary of the user that was created """ # the action for reading user entries read_action = get_crud_action(method='create', model='user') # see if there is a matching user user_data = await self.event_broker.ask( action_type=read_action, payload=payload ) # treat the reply like a json object return json.loads(user_data)
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This method creates a service record in the remote user service with the given email. Args: uid (str): the user identifier to create Returns: (dict): a summary of the user that was created
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70e2acef27a2f87355590be1a6ca60ce3ab4d09c
https://github.com/AlecAivazis/graphql-over-kafka/blob/70e2acef27a2f87355590be1a6ca60ce3ab4d09c/nautilus/services/apiGateway.py#L450-L468
train
MartinThoma/asr
asr/align.py
calculate_wer
def calculate_wer(reference, hypothesis): """ Calculation of WER with Levenshtein distance. Works only for iterables up to 254 elements (uint8). O(nm) time and space complexity. >>> calculate_wer("who is there".split(), "is there".split()) 1 >>> calculate_wer("who is there".split(), "".split()) 3 >>> calculate_wer("".split(), "who is there".split()) 3 """ # initialisation import numpy d = numpy.zeros((len(reference)+1)*(len(hypothesis)+1), dtype=numpy.uint8) d = d.reshape((len(reference)+1, len(hypothesis)+1)) for i in range(len(reference)+1): for j in range(len(hypothesis)+1): if i == 0: d[0][j] = j elif j == 0: d[i][0] = i # computation for i in range(1, len(reference)+1): for j in range(1, len(hypothesis)+1): if reference[i-1] == hypothesis[j-1]: d[i][j] = d[i-1][j-1] else: substitution = d[i-1][j-1] + 1 insertion = d[i][j-1] + 1 deletion = d[i-1][j] + 1 d[i][j] = min(substitution, insertion, deletion) return d[len(reference)][len(hypothesis)]/float(len(reference))
python
def calculate_wer(reference, hypothesis): """ Calculation of WER with Levenshtein distance. Works only for iterables up to 254 elements (uint8). O(nm) time and space complexity. >>> calculate_wer("who is there".split(), "is there".split()) 1 >>> calculate_wer("who is there".split(), "".split()) 3 >>> calculate_wer("".split(), "who is there".split()) 3 """ # initialisation import numpy d = numpy.zeros((len(reference)+1)*(len(hypothesis)+1), dtype=numpy.uint8) d = d.reshape((len(reference)+1, len(hypothesis)+1)) for i in range(len(reference)+1): for j in range(len(hypothesis)+1): if i == 0: d[0][j] = j elif j == 0: d[i][0] = i # computation for i in range(1, len(reference)+1): for j in range(1, len(hypothesis)+1): if reference[i-1] == hypothesis[j-1]: d[i][j] = d[i-1][j-1] else: substitution = d[i-1][j-1] + 1 insertion = d[i][j-1] + 1 deletion = d[i-1][j] + 1 d[i][j] = min(substitution, insertion, deletion) return d[len(reference)][len(hypothesis)]/float(len(reference))
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Calculation of WER with Levenshtein distance. Works only for iterables up to 254 elements (uint8). O(nm) time and space complexity. >>> calculate_wer("who is there".split(), "is there".split()) 1 >>> calculate_wer("who is there".split(), "".split()) 3 >>> calculate_wer("".split(), "who is there".split()) 3
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b453074761a4a2f1ee40cd5315b2e000c3b72142
https://github.com/MartinThoma/asr/blob/b453074761a4a2f1ee40cd5315b2e000c3b72142/asr/align.py#L7-L42
train
MartinThoma/asr
asr/align.py
get_parser
def get_parser(): """Get a parser object""" from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter parser = ArgumentParser(description=__doc__, formatter_class=ArgumentDefaultsHelpFormatter) parser.add_argument("-s1", dest="s1", help="sequence 1") parser.add_argument("-s2", dest="s2", help="sequence 2") return parser
python
def get_parser(): """Get a parser object""" from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter parser = ArgumentParser(description=__doc__, formatter_class=ArgumentDefaultsHelpFormatter) parser.add_argument("-s1", dest="s1", help="sequence 1") parser.add_argument("-s2", dest="s2", help="sequence 2") return parser
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Get a parser object
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b453074761a4a2f1ee40cd5315b2e000c3b72142
https://github.com/MartinThoma/asr/blob/b453074761a4a2f1ee40cd5315b2e000c3b72142/asr/align.py#L45-L52
train
pschmitt/pyteleloisirs
pyteleloisirs/pyteleloisirs.py
_async_request_soup
async def _async_request_soup(url): ''' Perform a GET web request and return a bs4 parser ''' from bs4 import BeautifulSoup import aiohttp _LOGGER.debug('GET %s', url) async with aiohttp.ClientSession() as session: resp = await session.get(url) text = await resp.text() return BeautifulSoup(text, 'html.parser')
python
async def _async_request_soup(url): ''' Perform a GET web request and return a bs4 parser ''' from bs4 import BeautifulSoup import aiohttp _LOGGER.debug('GET %s', url) async with aiohttp.ClientSession() as session: resp = await session.get(url) text = await resp.text() return BeautifulSoup(text, 'html.parser')
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Perform a GET web request and return a bs4 parser
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d63610fd3729862455ac42afca440469f8063fba
https://github.com/pschmitt/pyteleloisirs/blob/d63610fd3729862455ac42afca440469f8063fba/pyteleloisirs/pyteleloisirs.py#L15-L25
train
pschmitt/pyteleloisirs
pyteleloisirs/pyteleloisirs.py
async_determine_channel
async def async_determine_channel(channel): ''' Check whether the current channel is correct. If not try to determine it using fuzzywuzzy ''' from fuzzywuzzy import process channel_data = await async_get_channels() if not channel_data: _LOGGER.error('No channel data. Cannot determine requested channel.') return channels = [c for c in channel_data.get('data', {}).keys()] if channel in channels: return channel else: res = process.extractOne(channel, channels)[0] _LOGGER.debug('No direct match found for %s. Resort to guesswork.' 'Guessed %s', channel, res) return res
python
async def async_determine_channel(channel): ''' Check whether the current channel is correct. If not try to determine it using fuzzywuzzy ''' from fuzzywuzzy import process channel_data = await async_get_channels() if not channel_data: _LOGGER.error('No channel data. Cannot determine requested channel.') return channels = [c for c in channel_data.get('data', {}).keys()] if channel in channels: return channel else: res = process.extractOne(channel, channels)[0] _LOGGER.debug('No direct match found for %s. Resort to guesswork.' 'Guessed %s', channel, res) return res
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Check whether the current channel is correct. If not try to determine it using fuzzywuzzy
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d63610fd3729862455ac42afca440469f8063fba
https://github.com/pschmitt/pyteleloisirs/blob/d63610fd3729862455ac42afca440469f8063fba/pyteleloisirs/pyteleloisirs.py#L28-L45
train
pschmitt/pyteleloisirs
pyteleloisirs/pyteleloisirs.py
async_get_channels
async def async_get_channels(no_cache=False, refresh_interval=4): ''' Get channel list and corresponding urls ''' # Check cache now = datetime.datetime.now() max_cache_age = datetime.timedelta(hours=refresh_interval) if not no_cache and 'channels' in _CACHE: cache = _CACHE.get('channels') cache_age = cache.get('last_updated') if now - cache_age < max_cache_age: _LOGGER.debug('Found channel list in cache.') return cache else: _LOGGER.debug('Found outdated channel list in cache. Update it.') _CACHE.pop('channels') soup = await _async_request_soup(BASE_URL + '/plan.html') channels = {} for li_item in soup.find_all('li'): try: child = li_item.findChild() if not child or child.name != 'a': continue href = child.get('href') if not href or not href.startswith('/programme/chaine'): continue channels[child.get('title')] = BASE_URL + href except Exception as exc: _LOGGER.error('Exception occured while fetching the channel ' 'list: %s', exc) if channels: _CACHE['channels'] = {'last_updated': now, 'data': channels} return _CACHE['channels']
python
async def async_get_channels(no_cache=False, refresh_interval=4): ''' Get channel list and corresponding urls ''' # Check cache now = datetime.datetime.now() max_cache_age = datetime.timedelta(hours=refresh_interval) if not no_cache and 'channels' in _CACHE: cache = _CACHE.get('channels') cache_age = cache.get('last_updated') if now - cache_age < max_cache_age: _LOGGER.debug('Found channel list in cache.') return cache else: _LOGGER.debug('Found outdated channel list in cache. Update it.') _CACHE.pop('channels') soup = await _async_request_soup(BASE_URL + '/plan.html') channels = {} for li_item in soup.find_all('li'): try: child = li_item.findChild() if not child or child.name != 'a': continue href = child.get('href') if not href or not href.startswith('/programme/chaine'): continue channels[child.get('title')] = BASE_URL + href except Exception as exc: _LOGGER.error('Exception occured while fetching the channel ' 'list: %s', exc) if channels: _CACHE['channels'] = {'last_updated': now, 'data': channels} return _CACHE['channels']
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Get channel list and corresponding urls
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d63610fd3729862455ac42afca440469f8063fba
https://github.com/pschmitt/pyteleloisirs/blob/d63610fd3729862455ac42afca440469f8063fba/pyteleloisirs/pyteleloisirs.py#L48-L80
train