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def unix_timestamp_to_datetime(unix_timestamp):
"""
<Purpose>
Convert 'unix_timestamp' (i.e., POSIX time, in UNIX_TIMESTAMP_SCHEMA format)
to a datetime.datetime() object. 'unix_timestamp' is the number of seconds
since the epoch (January 1, 1970.)
>>> datetime_object = unix_timestamp_to_datetime(1445455680)
>>> datetime_object
datetime.datetime(2015, 10, 21, 19, 28)
<Arguments>
unix_timestamp:
An integer representing the time (e.g., 1445455680). Conformant to
'securesystemslib.formats.UNIX_TIMESTAMP_SCHEMA'.
<Exceptions>
securesystemslib.exceptions.FormatError, if 'unix_timestamp' is improperly
formatted.
<Side Effects>
None.
<Returns>
A datetime.datetime() object corresponding to 'unix_timestamp'.
"""
# Is 'unix_timestamp' properly formatted?
# Raise 'securesystemslib.exceptions.FormatError' if there is a mismatch.
securesystemslib.formats.UNIX_TIMESTAMP_SCHEMA.check_match(unix_timestamp)
# Convert 'unix_timestamp' to a 'time.struct_time', in UTC. The Daylight
# Savings Time (DST) flag is set to zero. datetime.fromtimestamp() is not
# used because it returns a local datetime.
struct_time = time.gmtime(unix_timestamp)
# Extract the (year, month, day, hour, minutes, seconds) arguments for the
# datetime object to be returned.
datetime_object = datetime.datetime(*struct_time[:6])
return datetime_object
|
<Purpose>
Convert 'unix_timestamp' (i.e., POSIX time, in UNIX_TIMESTAMP_SCHEMA format)
to a datetime.datetime() object. 'unix_timestamp' is the number of seconds
since the epoch (January 1, 1970.)
>>> datetime_object = unix_timestamp_to_datetime(1445455680)
>>> datetime_object
datetime.datetime(2015, 10, 21, 19, 28)
<Arguments>
unix_timestamp:
An integer representing the time (e.g., 1445455680). Conformant to
'securesystemslib.formats.UNIX_TIMESTAMP_SCHEMA'.
<Exceptions>
securesystemslib.exceptions.FormatError, if 'unix_timestamp' is improperly
formatted.
<Side Effects>
None.
<Returns>
A datetime.datetime() object corresponding to 'unix_timestamp'.
|
entailment
|
def format_base64(data):
"""
<Purpose>
Return the base64 encoding of 'data' with whitespace and '=' signs omitted.
<Arguments>
data:
Binary or buffer of data to convert.
<Exceptions>
securesystemslib.exceptions.FormatError, if the base64 encoding fails or the
argument is invalid.
<Side Effects>
None.
<Returns>
A base64-encoded string.
"""
try:
return binascii.b2a_base64(data).decode('utf-8').rstrip('=\n ')
except (TypeError, binascii.Error) as e:
raise securesystemslib.exceptions.FormatError('Invalid base64'
' encoding: ' + str(e))
|
<Purpose>
Return the base64 encoding of 'data' with whitespace and '=' signs omitted.
<Arguments>
data:
Binary or buffer of data to convert.
<Exceptions>
securesystemslib.exceptions.FormatError, if the base64 encoding fails or the
argument is invalid.
<Side Effects>
None.
<Returns>
A base64-encoded string.
|
entailment
|
def parse_base64(base64_string):
"""
<Purpose>
Parse a base64 encoding with whitespace and '=' signs omitted.
<Arguments>
base64_string:
A string holding a base64 value.
<Exceptions>
securesystemslib.exceptions.FormatError, if 'base64_string' cannot be parsed
due to an invalid base64 encoding.
<Side Effects>
None.
<Returns>
A byte string representing the parsed based64 encoding of
'base64_string'.
"""
if not isinstance(base64_string, six.string_types):
message = 'Invalid argument: '+repr(base64_string)
raise securesystemslib.exceptions.FormatError(message)
extra = len(base64_string) % 4
if extra:
padding = '=' * (4 - extra)
base64_string = base64_string + padding
try:
return binascii.a2b_base64(base64_string.encode('utf-8'))
except (TypeError, binascii.Error) as e:
raise securesystemslib.exceptions.FormatError('Invalid base64'
' encoding: ' + str(e))
|
<Purpose>
Parse a base64 encoding with whitespace and '=' signs omitted.
<Arguments>
base64_string:
A string holding a base64 value.
<Exceptions>
securesystemslib.exceptions.FormatError, if 'base64_string' cannot be parsed
due to an invalid base64 encoding.
<Side Effects>
None.
<Returns>
A byte string representing the parsed based64 encoding of
'base64_string'.
|
entailment
|
def encode_canonical(object, output_function=None):
"""
<Purpose>
Encode 'object' in canonical JSON form, as specified at
http://wiki.laptop.org/go/Canonical_JSON . It's a restricted
dialect of JSON in which keys are always lexically sorted,
there is no whitespace, floats aren't allowed, and only quote
and backslash get escaped. The result is encoded in UTF-8,
and the resulting bits are passed to output_function (if provided),
or joined into a string and returned.
Note: This function should be called prior to computing the hash or
signature of a JSON object in TUF. For example, generating a signature
of a signing role object such as 'ROOT_SCHEMA' is required to ensure
repeatable hashes are generated across different json module versions
and platforms. Code elsewhere is free to dump JSON objects in any format
they wish (e.g., utilizing indentation and single quotes around object
keys). These objects are only required to be in "canonical JSON" format
when their hashes or signatures are needed.
>>> encode_canonical("")
'""'
>>> encode_canonical([1, 2, 3])
'[1,2,3]'
>>> encode_canonical([])
'[]'
>>> encode_canonical({"A": [99]})
'{"A":[99]}'
>>> encode_canonical({"x" : 3, "y" : 2})
'{"x":3,"y":2}'
<Arguments>
object:
The object to be encoded.
output_function:
The result will be passed as arguments to 'output_function'
(e.g., output_function('result')).
<Exceptions>
securesystemslib.exceptions.FormatError, if 'object' cannot be encoded or
'output_function' is not callable.
<Side Effects>
The results are fed to 'output_function()' if 'output_function' is set.
<Returns>
A string representing the 'object' encoded in canonical JSON form.
"""
result = None
# If 'output_function' is unset, treat it as
# appending to a list.
if output_function is None:
result = []
output_function = result.append
try:
_encode_canonical(object, output_function)
except (TypeError, securesystemslib.exceptions.FormatError) as e:
message = 'Could not encode ' + repr(object) + ': ' + str(e)
raise securesystemslib.exceptions.FormatError(message)
# Return the encoded 'object' as a string.
# Note: Implies 'output_function' is None,
# otherwise results are sent to 'output_function'.
if result is not None:
return ''.join(result)
|
<Purpose>
Encode 'object' in canonical JSON form, as specified at
http://wiki.laptop.org/go/Canonical_JSON . It's a restricted
dialect of JSON in which keys are always lexically sorted,
there is no whitespace, floats aren't allowed, and only quote
and backslash get escaped. The result is encoded in UTF-8,
and the resulting bits are passed to output_function (if provided),
or joined into a string and returned.
Note: This function should be called prior to computing the hash or
signature of a JSON object in TUF. For example, generating a signature
of a signing role object such as 'ROOT_SCHEMA' is required to ensure
repeatable hashes are generated across different json module versions
and platforms. Code elsewhere is free to dump JSON objects in any format
they wish (e.g., utilizing indentation and single quotes around object
keys). These objects are only required to be in "canonical JSON" format
when their hashes or signatures are needed.
>>> encode_canonical("")
'""'
>>> encode_canonical([1, 2, 3])
'[1,2,3]'
>>> encode_canonical([])
'[]'
>>> encode_canonical({"A": [99]})
'{"A":[99]}'
>>> encode_canonical({"x" : 3, "y" : 2})
'{"x":3,"y":2}'
<Arguments>
object:
The object to be encoded.
output_function:
The result will be passed as arguments to 'output_function'
(e.g., output_function('result')).
<Exceptions>
securesystemslib.exceptions.FormatError, if 'object' cannot be encoded or
'output_function' is not callable.
<Side Effects>
The results are fed to 'output_function()' if 'output_function' is set.
<Returns>
A string representing the 'object' encoded in canonical JSON form.
|
entailment
|
def process_error_labels(value):
""" Process the error labels of a dependent variable 'value' to ensure uniqueness. """
observed_error_labels = {}
for error in value.get('errors', []):
label = error.get('label', 'error')
if label not in observed_error_labels:
observed_error_labels[label] = 0
observed_error_labels[label] += 1
if observed_error_labels[label] > 1:
error['label'] = label + '_' + str(observed_error_labels[label])
# append "_1" to first error label that has a duplicate
if observed_error_labels[label] == 2:
for error1 in value.get('errors', []):
error1_label = error1.get('label', 'error')
if error1_label == label:
error1['label'] = label + "_1"
break
|
Process the error labels of a dependent variable 'value' to ensure uniqueness.
|
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|
def raw(text):
"""Returns a raw string representation of text"""
new_string = ''
for char in text:
try:
new_string += escape_dict[char]
except KeyError:
new_string += char
return new_string
|
Returns a raw string representation of text
|
entailment
|
def get_winfunc(libname, funcname, restype=None, argtypes=(), _libcache={}):
"""Retrieve a function from a library/DLL, and set the data types."""
if libname not in _libcache:
_libcache[libname] = windll.LoadLibrary(libname)
func = getattr(_libcache[libname], funcname)
func.argtypes = argtypes
func.restype = restype
return func
|
Retrieve a function from a library/DLL, and set the data types.
|
entailment
|
def WinMSGLoop():
"""Run the main windows message loop."""
LPMSG = POINTER(MSG)
LRESULT = c_ulong
GetMessage = get_winfunc("user32", "GetMessageW", BOOL, (LPMSG, HWND, UINT, UINT))
TranslateMessage = get_winfunc("user32", "TranslateMessage", BOOL, (LPMSG,))
# restype = LRESULT
DispatchMessage = get_winfunc("user32", "DispatchMessageW", LRESULT, (LPMSG,))
msg = MSG()
lpmsg = byref(msg)
while GetMessage(lpmsg, HWND(), 0, 0) > 0:
TranslateMessage(lpmsg)
DispatchMessage(lpmsg)
|
Run the main windows message loop.
|
entailment
|
def ConnectTo(self, appName, data=None):
"""Exceptional error is handled in zdde Init() method, so the exception
must be re-raised"""
global number_of_apps_communicating
self.ddeServerName = appName
try:
self.ddec = DDEClient(self.ddeServerName, self.ddeClientName) # establish conversation
except DDEError:
raise
else:
number_of_apps_communicating +=1
|
Exceptional error is handled in zdde Init() method, so the exception
must be re-raised
|
entailment
|
def Request(self, item, timeout=None):
"""Request DDE client
timeout in seconds
Note ... handle the exception within this function.
"""
if not timeout:
timeout = self.ddetimeout
try:
reply = self.ddec.request(item, int(timeout*1000)) # convert timeout into milliseconds
except DDEError:
err_str = str(sys.exc_info()[1])
error = err_str[err_str.find('err=')+4:err_str.find('err=')+10]
if error == hex(DMLERR_DATAACKTIMEOUT):
print("TIMEOUT REACHED. Please use a higher timeout.\n")
if (sys.version_info > (3, 0)): #this is only evaluated in case of an error
reply = b'-998' #Timeout error value
else:
reply = '-998' #Timeout error value
return reply
|
Request DDE client
timeout in seconds
Note ... handle the exception within this function.
|
entailment
|
def advise(self, item, stop=False):
"""Request updates when DDE data changes."""
hszItem = DDE.CreateStringHandle(self._idInst, item, CP_WINUNICODE)
hDdeData = DDE.ClientTransaction(LPBYTE(), 0, self._hConv, hszItem, CF_TEXT, XTYP_ADVSTOP if stop else XTYP_ADVSTART, TIMEOUT_ASYNC, LPDWORD())
DDE.FreeStringHandle(self._idInst, hszItem)
if not hDdeData:
raise DDEError("Unable to %s advise" % ("stop" if stop else "start"), self._idInst)
DDE.FreeDataHandle(hDdeData)
|
Request updates when DDE data changes.
|
entailment
|
def execute(self, command):
"""Execute a DDE command."""
pData = c_char_p(command)
cbData = DWORD(len(command) + 1)
hDdeData = DDE.ClientTransaction(pData, cbData, self._hConv, HSZ(), CF_TEXT, XTYP_EXECUTE, TIMEOUT_ASYNC, LPDWORD())
if not hDdeData:
raise DDEError("Unable to send command", self._idInst)
DDE.FreeDataHandle(hDdeData)
|
Execute a DDE command.
|
entailment
|
def request(self, item, timeout=5000):
"""Request data from DDE service."""
hszItem = DDE.CreateStringHandle(self._idInst, item, CP_WINUNICODE)
#hDdeData = DDE.ClientTransaction(LPBYTE(), 0, self._hConv, hszItem, CF_TEXT, XTYP_REQUEST, timeout, LPDWORD())
pdwResult = DWORD(0)
hDdeData = DDE.ClientTransaction(LPBYTE(), 0, self._hConv, hszItem, CF_TEXT, XTYP_REQUEST, timeout, byref(pdwResult))
DDE.FreeStringHandle(self._idInst, hszItem)
if not hDdeData:
raise DDEError("Unable to request item", self._idInst)
if timeout != TIMEOUT_ASYNC:
pdwSize = DWORD(0)
pData = DDE.AccessData(hDdeData, byref(pdwSize))
if not pData:
DDE.FreeDataHandle(hDdeData)
raise DDEError("Unable to access data in request function", self._idInst)
DDE.UnaccessData(hDdeData)
else:
pData = None
DDE.FreeDataHandle(hDdeData)
return pData
|
Request data from DDE service.
|
entailment
|
def _callback(self, wType, uFmt, hConv, hsz1, hsz2, hDdeData, dwData1, dwData2):
"""DdeCallback callback function for processing Dynamic Data Exchange (DDE)
transactions sent by DDEML in response to DDE events
Parameters
----------
wType : transaction type (UINT)
uFmt : clipboard data format (UINT)
hConv : handle to conversation (HCONV)
hsz1 : handle to string (HSZ)
hsz2 : handle to string (HSZ)
hDDedata : handle to global memory object (HDDEDATA)
dwData1 : transaction-specific data (DWORD)
dwData2 : transaction-specific data (DWORD)
Returns
-------
ret : specific to the type of transaction (HDDEDATA)
"""
if wType == XTYP_ADVDATA: # value of the data item has changed [hsz1 = topic; hsz2 = item; hDdeData = data]
dwSize = DWORD(0)
pData = DDE.AccessData(hDdeData, byref(dwSize))
if pData:
item = create_string_buffer('\000' * 128)
DDE.QueryString(self._idInst, hsz2, item, 128, CP_WINANSI)
self.callback(pData, item.value)
DDE.UnaccessData(hDdeData)
return DDE_FACK
else:
print("Error: AccessData returned NULL! (err = %s)"% (hex(DDE.GetLastError(self._idInst))))
if wType == XTYP_DISCONNECT:
print("Disconnect notification received from server")
return 0
|
DdeCallback callback function for processing Dynamic Data Exchange (DDE)
transactions sent by DDEML in response to DDE events
Parameters
----------
wType : transaction type (UINT)
uFmt : clipboard data format (UINT)
hConv : handle to conversation (HCONV)
hsz1 : handle to string (HSZ)
hsz2 : handle to string (HSZ)
hDDedata : handle to global memory object (HDDEDATA)
dwData1 : transaction-specific data (DWORD)
dwData2 : transaction-specific data (DWORD)
Returns
-------
ret : specific to the type of transaction (HDDEDATA)
|
entailment
|
def parse(self, data_in, *args, **kwargs):
"""
:param data_in: path to submission.yaml
:param args:
:param kwargs:
:raise ValueError:
"""
if not os.path.exists(data_in):
raise ValueError("File / Directory does not exist: %s" % data_in)
if os.path.isdir(data_in):
submission_filepath = os.path.join(data_in, 'submission.yaml')
if not os.path.exists(submission_filepath):
submission_filepath = os.path.join(data_in, 'submission.yml')
if not os.path.exists(submission_filepath):
raise ValueError("No submission file in %s" % data_in)
data_in = submission_filepath
# first validate submission file:
with open(data_in, 'r') as submission_file:
submission_data = list(yaml.load_all(submission_file, Loader=Loader))
if len(submission_data) == 0:
raise RuntimeError("Submission file (%s) is empty" % data_in)
submission_file_validator = SubmissionFileValidator()
if not submission_file_validator.validate(file_path=data_in,
data=submission_data):
raise RuntimeError(
"Submission file (%s) did not pass validation: %s" %
(data_in, self._pretty_print_errors(
submission_file_validator.get_messages())))
metadata = {}
tables = []
# validator for table data
data_file_validator = DataFileValidator()
index = 0
for i in range(0, len(submission_data)):
if not submission_data[i]: # empty YAML document
continue
if 'data_file' not in submission_data[i]:
metadata = submission_data[i] # information about whole submission
continue
table_filepath = os.path.join(os.path.dirname(data_in),
submission_data[i]['data_file'])
with open(table_filepath, 'r') as table_file:
if not os.path.exists(table_filepath):
raise ValueError(
"table file: %s does not exist" % table.data_file)
table_data = yaml.load(table_file, Loader=Loader)
if not data_file_validator.validate(data=table_data,
file_path=table_filepath):
raise RuntimeError(
"Data file (%s) did not pass validation: %s" %
(table_filepath, self._pretty_print_errors(
data_file_validator.get_messages())))
index = index + 1
table = Table(index=index, metadata=submission_data[i],
data=table_data)
tables.append(table)
return ParsedData(metadata, tables)
|
:param data_in: path to submission.yaml
:param args:
:param kwargs:
:raise ValueError:
|
entailment
|
def generate_ai_request(
predict_rows,
req_dict=None,
req_file=ANTINEX_PUBLISH_REQUEST_FILE,
features=ANTINEX_FEATURES_TO_PROCESS,
ignore_features=ANTINEX_IGNORE_FEATURES,
sort_values=ANTINEX_SORT_VALUES,
ml_type=ANTINEX_ML_TYPE,
use_model_name=ANTINEX_USE_MODEL_NAME,
predict_feature=ANTINEX_PREDICT_FEATURE,
seed=ANTINEX_SEED,
test_size=ANTINEX_TEST_SIZE,
batch_size=ANTINEX_BATCH_SIZE,
epochs=ANTINEX_EPOCHS,
num_splits=ANTINEX_NUM_SPLITS,
loss=ANTINEX_LOSS,
optimizer=ANTINEX_OPTIMIZER,
metrics=ANTINEX_METRICS,
histories=ANTINEX_HISTORIES,
filter_features_dict=FILTER_FEATURES_DICT,
filter_features=FILTER_FEATURES,
convert_enabled=ANTINEX_CONVERT_DATA,
convert_to_type=ANTINEX_CONVERT_DATA_TYPE,
include_failed_conversions=ANTINEX_INCLUDE_FAILED_CONVERSIONS,
value_for_missing=ANTINEX_MISSING_VALUE,
version=ANTINEX_VERSION,
publish_to_core=ANTINEX_PUBLISH_TO_CORE,
check_missing_predict_feature=ANTINEX_CHECK_MISSING_PREDICT,
debug=ANTINEX_CLIENT_DEBUG):
"""generate_ai_request
:param predict_rows: list of predict rows to build into the request
:param req_dict: request dictionary to update - for long-running clients
:param req_file: file holding a request dict to update - one-off tests
:param features: features to process in the data
:param ignore_features: features to ignore in the data (non-numerics)
:param sort_values: optional - order rows for scaler normalization
:param ml_type: machine learning type - classification/regression
:param use_model_name: use a pre-trained model by name
:param predict_feature: predict the values of this feature
:param seed: seed for randomness reproducability
:param test_size: split train/test data
:param batch_size: batch size for processing
:param epochs: test epochs
:param num_splits: test splits for cross validation
:param loss: loss function
:param optimizer: optimizer
:param metrics: metrics to apply
:param histories: historical values to test
:param filter_features_dict: dictionary of features to use
:param filter_features: list of features to use
:param convert_to_type: convert predict_row values to scaler-ready values
:param include_failed_conversions: should the predict rows include fails
:param value_for_missing: set this value to any columns that are missing
:param version: version of the API request
:param publish_to_core: want to publish it to the core or the worker
:param debug: log debug messages
"""
status = NOT_SET
err = "not-set"
data = None
if not ANTINEX_PUBLISH_ENABLED:
log.info(("publish disabled ANTINEX_PUBLISH_ENABLED={}")
.format(
ANTINEX_PUBLISH_ENABLED))
status = DISABLED
err = "disabled"
return {
"status": status,
"error": err,
"data": None}
# stop if not enabled
try:
err = "checking number of predict rows"
if len(predict_rows) == 0:
err = "please provide a list of predict_rows"
log.error(err)
status = FAILED
res = {
"status": status,
"error": err,
"data": None}
return res
# stop if there's no new rows
body = None
if not req_dict:
if os.path.exists(req_file):
with open(req_file, "r") as f:
body = json.loads(f.read())
else:
body = copy.deepcopy(
req_dict)
# end of loading body from requested
if not body:
err = ("failed to load request body "
"req_dict={} req_file={}").format(
req_dict,
req_file)
log.error(err)
status = FAILED
res = {
"status": status,
"error": err,
"data": None}
return res
# if body is empty
err = ("setting values rows={} body={} features={}").format(
len(predict_rows),
body,
filter_features)
if debug:
log.info(err)
use_predict_rows = []
for r in predict_rows:
new_row = {}
for col in r:
cur_value = r[col]
if col in filter_features_dict:
if not cur_value:
cur_value = value_for_missing
if ANTINEX_CONVERT_DATA:
try:
if convert_to_type == "float":
new_row[col] = float(cur_value)
elif convert_to_type == "int":
new_row[col] = int(cur_value)
except Exception as e:
if include_failed_conversions:
new_row[col] = cur_value
else:
log.error(("failed converting {}={} type={}")
.format(
col,
cur_value,
convert_to_type))
# if conversion failed
else:
new_row[col] = cur_value
# if not converting data
# if the column is in the filtered features
# for all columns in the row dictionary
for col in filter_features:
if col not in new_row:
new_row[col] = value_for_missing
# make sure to fill in missing columns with a default
if check_missing_predict_feature:
if predict_feature not in new_row:
new_row[predict_feature] = value_for_missing
use_predict_rows.append(new_row)
# for all predict rows to convert and fileter
err = ("converted rows={} to use_rows={}").format(
len(predict_rows),
len(use_predict_rows))
log.info(err)
body["label"] = use_model_name
body["predict_feature"] = predict_feature
body["predict_rows"] = use_predict_rows
body["publish_to_core"] = publish_to_core
body["seed"] = seed
body["test_size"] = test_size
body["batch_size"] = batch_size
body["epochs"] = epochs
body["num_splits"] = num_splits
body["loss"] = loss
body["optimizer"] = optimizer
body["metrics"] = metrics
body["histories"] = histories
body["ml_type"] = ml_type
if sort_values:
body["sort_values"] = sort_values
if filter_features:
body["features_to_process"] = filter_features
if ignore_features:
body["ignore_features"] = ignore_features
data = body
if debug:
log.info(("req={}")
.format(
ppj(data)))
status = SUCCESS
err = ""
except Exception as e:
log.error(("failed last_step='{}' with ex={}")
.format(
err,
e))
status = ERROR
# end of try/ex
res = {
"status": status,
"error": err,
"data": data}
return res
|
generate_ai_request
:param predict_rows: list of predict rows to build into the request
:param req_dict: request dictionary to update - for long-running clients
:param req_file: file holding a request dict to update - one-off tests
:param features: features to process in the data
:param ignore_features: features to ignore in the data (non-numerics)
:param sort_values: optional - order rows for scaler normalization
:param ml_type: machine learning type - classification/regression
:param use_model_name: use a pre-trained model by name
:param predict_feature: predict the values of this feature
:param seed: seed for randomness reproducability
:param test_size: split train/test data
:param batch_size: batch size for processing
:param epochs: test epochs
:param num_splits: test splits for cross validation
:param loss: loss function
:param optimizer: optimizer
:param metrics: metrics to apply
:param histories: historical values to test
:param filter_features_dict: dictionary of features to use
:param filter_features: list of features to use
:param convert_to_type: convert predict_row values to scaler-ready values
:param include_failed_conversions: should the predict rows include fails
:param value_for_missing: set this value to any columns that are missing
:param version: version of the API request
:param publish_to_core: want to publish it to the core or the worker
:param debug: log debug messages
|
entailment
|
def get_ml_job():
"""get_ml_job
Get an ``MLJob`` by database id.
"""
parser = argparse.ArgumentParser(
description=("Python client get AI Job by ID"))
parser.add_argument(
"-u",
help="username",
required=False,
dest="user")
parser.add_argument(
"-p",
help="user password",
required=False,
dest="password")
parser.add_argument(
"-e",
help="user email",
required=False,
dest="email")
parser.add_argument(
"-a",
help="url endpoint with default http://localhost:8010",
required=False,
dest="url")
parser.add_argument(
"-i",
help="User's MLJob.id to look up",
required=False,
dest="job_id")
parser.add_argument(
"-b",
help=(
"optional - path to CA bundle directory for "
"client encryption over HTTP"),
required=False,
dest="ca_dir")
parser.add_argument(
"-c",
help=(
"optional - path to x509 certificate for "
"client encryption over HTTP"),
required=False,
dest="cert_file")
parser.add_argument(
"-k",
help=(
"optional - path to x509 key file for "
"client encryption over HTTP"),
required=False,
dest="key_file")
parser.add_argument(
"-s",
help="silent",
required=False,
dest="silent",
action="store_true")
parser.add_argument(
"-d",
help="debug",
required=False,
dest="debug",
action="store_true")
args = parser.parse_args()
user = ev(
"API_USER",
"user-not-set")
password = ev(
"API_PASSWORD",
"password-not-set")
email = ev(
"API_EMAIL",
"email-not-set")
url = ev(
"API_URL",
"http://localhost:8010")
job_id = ev(
"JOB_ID",
"job_id-not-set")
ca_dir = os.getenv(
"API_CA_BUNDLE_DIR",
None)
cert_file = os.getenv(
"API_CERT_FILE",
None)
key_file = os.getenv(
"API_KEY_FILE",
None)
verbose = bool(str(ev(
"API_VERBOSE",
"true")).lower() == "true")
debug = bool(str(ev(
"API_DEBUG",
"false")).lower() == "true")
if args.user:
user = args.user
if args.password:
password = args.password
if args.email:
email = args.email
if args.url:
url = args.url
if args.job_id:
job_id = args.job_id
if args.ca_dir:
ca_dir = args.ca_dir
if args.cert_file:
cert_file = args.cert_file
if args.key_file:
key_file = args.key_file
if args.silent:
verbose = False
if args.debug:
debug = True
usage = (
"Please run with "
"-u <username> "
"-p <password> "
"-a <AntiNex URL http://localhost:8010> "
"-i <job_id> "
"-b <optional - path to CA bundle directory> "
"-c <optional - path to x509 ssl certificate file> "
"-k <optional - path to x509 ssl key file>")
valid = True
if not user or user == "user-not-set":
log.error("missing user")
valid = False
if not password or password == "password-not-set":
log.error("missing password")
valid = False
if not job_id or job_id == "job_id-not-set":
log.error("missing job_id")
valid = False
else:
try:
job_id = int(job_id)
except Exception as e:
log.error("please use -i <job_id with an integer>")
valid = False
if not valid:
log.error(usage)
sys.exit(1)
if verbose:
log.info((
"creating client user={} url={} job_id={} "
"ca_dir={} cert_file={} key_file={}").format(
user,
url,
job_id,
ca_dir,
cert_file,
key_file))
client = AIClient(
user=user,
email=email,
password=password,
url=url,
ca_dir=ca_dir,
cert_file=cert_file,
key_file=key_file,
verbose=verbose,
debug=debug)
if verbose:
log.info(("loading request in job_id={}")
.format(
job_id))
response = client.get_job_by_id(
job_id=job_id)
if response["status"] == SUCCESS:
if debug:
log.info(("got a job response={}")
.format(
response["data"]))
elif response["status"] == FAILED:
log.error(("job failed with error='{}' with response={}")
.format(
response["error"],
response["data"]))
sys.exit(1)
elif response["status"] == ERROR:
if "missing " in response["error"]:
log.error(("Did not find a job with id={} for user={}")
.format(
job_id,
user))
else:
log.error(("job had an error='{}' with response={}")
.format(
response["error"],
response["data"]))
sys.exit(1)
elif response["status"] == LOGIN_FAILED:
log.error(("job reported user was not able to log in "
"with an error='{}' with response={}")
.format(
response["error"],
response["data"]))
sys.exit(1)
job_data = response["data"]
if len(job_data) == 0:
log.error(("Did not find a job with id={} for user={}")
.format(
job_id,
user))
sys.exit(1)
job_id = job_data.get("id", None)
job_status = job_data.get("status", None)
log.info(("job={}")
.format(
ppj(job_data)))
log.info(("done getting job.id={} status={}")
.format(
job_id,
job_status))
|
get_ml_job
Get an ``MLJob`` by database id.
|
entailment
|
def get_molo_comments(parser, token):
"""
Get a limited set of comments for a given object.
Defaults to a limit of 5. Setting the limit to -1 disables limiting.
Set the amount of comments to
usage:
{% get_molo_comments for object as variable_name %}
{% get_molo_comments for object as variable_name limit amount %}
{% get_molo_comments for object as variable_name limit amount child_limit amount %} # noqa
"""
keywords = token.contents.split()
if len(keywords) != 5 and len(keywords) != 7 and len(keywords) != 9:
raise template.TemplateSyntaxError(
"'%s' tag takes exactly 2,4 or 6 arguments" % (keywords[0],))
if keywords[1] != 'for':
raise template.TemplateSyntaxError(
"first argument to '%s' tag must be 'for'" % (keywords[0],))
if keywords[3] != 'as':
raise template.TemplateSyntaxError(
"first argument to '%s' tag must be 'as'" % (keywords[0],))
if len(keywords) > 5 and keywords[5] != 'limit':
raise template.TemplateSyntaxError(
"third argument to '%s' tag must be 'limit'" % (keywords[0],))
if len(keywords) == 7:
return GetMoloCommentsNode(keywords[2], keywords[4], keywords[6])
if len(keywords) > 7 and keywords[7] != 'child_limit':
raise template.TemplateSyntaxError(
"third argument to '%s' tag must be 'child_limit'"
% (keywords[0],))
if len(keywords) > 7:
return GetMoloCommentsNode(keywords[2], keywords[4],
keywords[6], keywords[8])
return GetMoloCommentsNode(keywords[2], keywords[4])
|
Get a limited set of comments for a given object.
Defaults to a limit of 5. Setting the limit to -1 disables limiting.
Set the amount of comments to
usage:
{% get_molo_comments for object as variable_name %}
{% get_molo_comments for object as variable_name limit amount %}
{% get_molo_comments for object as variable_name limit amount child_limit amount %} # noqa
|
entailment
|
def get_comments_content_object(parser, token):
"""
Get a limited set of comments for a given object.
Defaults to a limit of 5. Setting the limit to -1 disables limiting.
usage:
{% get_comments_content_object for form_object as variable_name %}
"""
keywords = token.contents.split()
if len(keywords) != 5:
raise template.TemplateSyntaxError(
"'%s' tag takes exactly 2 arguments" % (keywords[0],))
if keywords[1] != 'for':
raise template.TemplateSyntaxError(
"first argument to '%s' tag must be 'for'" % (keywords[0],))
if keywords[3] != 'as':
raise template.TemplateSyntaxError(
"first argument to '%s' tag must be 'as'" % (keywords[0],))
return GetCommentsContentObject(keywords[2], keywords[4])
|
Get a limited set of comments for a given object.
Defaults to a limit of 5. Setting the limit to -1 disables limiting.
usage:
{% get_comments_content_object for form_object as variable_name %}
|
entailment
|
def report(request, comment_id):
"""
Flags a comment on GET.
Redirects to whatever is provided in request.REQUEST['next'].
"""
comment = get_object_or_404(
django_comments.get_model(), pk=comment_id, site__pk=settings.SITE_ID)
if comment.parent is not None:
messages.info(request, _('Reporting comment replies is not allowed.'))
else:
perform_flag(request, comment)
messages.info(request, _('The comment has been reported.'))
next = request.GET.get('next') or comment.get_absolute_url()
return HttpResponseRedirect(next)
|
Flags a comment on GET.
Redirects to whatever is provided in request.REQUEST['next'].
|
entailment
|
def post_molo_comment(request, next=None, using=None):
"""
Allows for posting of a Molo Comment, this allows comments to
be set with the "user_name" as "Anonymous"
"""
data = request.POST.copy()
if 'submit_anonymously' in data:
data['name'] = 'Anonymous'
# replace with our changed POST data
# ensure we always set an email
data['email'] = request.user.email or 'blank@email.com'
request.POST = data
return post_comment(request, next=next, using=next)
|
Allows for posting of a Molo Comment, this allows comments to
be set with the "user_name" as "Anonymous"
|
entailment
|
def build_ai_client_from_env(
verbose=ANTINEX_CLIENT_VERBOSE,
debug=ANTINEX_CLIENT_DEBUG,
ca_dir=None,
cert_file=None,
key_file=None):
"""build_ai_client_from_env
Use environment variables to build a client
:param verbose: verbose logging
:param debug: debug internal client calls
:param ca_dir: optional path to CA bundle dir
:param cert_file: optional path to x509 ssl cert file
:param key_file: optional path to x509 ssl key file
"""
if not ANTINEX_PUBLISH_ENABLED:
log.info((
"publish disabled ANTINEX_PUBLISH_ENABLED={}").format(
ANTINEX_PUBLISH_ENABLED))
return None
use_ca_dir = ca_dir
use_cert_file = cert_file
use_key_file = key_file
if ANTINEX_CA_FILE or ANTINEX_KEY_FILE or ANTINEX_CERT_FILE:
use_ca_dir = ANTINEX_CA_FILE
use_cert_file = ANTINEX_CERT_FILE
use_key_file = ANTINEX_KEY_FILE
log.info((
"creating env client user={} url={} "
"ca={} cert={} key={}").format(
ANTINEX_USER,
ANTINEX_URL,
ANTINEX_CA_FILE,
ANTINEX_CERT_FILE,
ANTINEX_KEY_FILE))
else:
log.info((
"creating client user={} url={} "
"ca={} cert={} key={}").format(
ANTINEX_USER,
ANTINEX_URL,
use_ca_dir,
use_cert_file,
use_key_file))
# if secure or dev
return AIClient(
user=ANTINEX_USER,
email=ANTINEX_EMAIL,
password=ANTINEX_PASSWORD,
url=ANTINEX_URL,
ca_dir=use_ca_dir,
cert_file=use_cert_file,
key_file=use_key_file,
verbose=verbose,
debug=debug)
|
build_ai_client_from_env
Use environment variables to build a client
:param verbose: verbose logging
:param debug: debug internal client calls
:param ca_dir: optional path to CA bundle dir
:param cert_file: optional path to x509 ssl cert file
:param key_file: optional path to x509 ssl key file
|
entailment
|
def train_new_deep_neural_network():
"""train_new_deep_neural_network
Train a new deep neural network and store the results as a new:
``MLJob`` and ``MLJobResult`` database records.
"""
parser = argparse.ArgumentParser(
description=(
"Python client to Train a Deep Neural Network "
"with AntiNex Django Rest Framework"))
parser.add_argument(
"-u",
help="username",
required=False,
dest="user")
parser.add_argument(
"-p",
help="user password",
required=False,
dest="password")
parser.add_argument(
"-e",
help="user email",
required=False,
dest="email")
parser.add_argument(
"-a",
help="url endpoint with default http://localhost:8010",
required=False,
dest="url")
parser.add_argument(
"-f",
help="file to use default ./examples/test-keras-dnn.json",
required=False,
dest="datafile")
parser.add_argument(
"-b",
help=(
"optional - path to CA bundle directory for "
"client encryption over HTTP"),
required=False,
dest="ca_dir")
parser.add_argument(
"-c",
help=(
"optional - path to x509 certificate for "
"client encryption over HTTP"),
required=False,
dest="cert_file")
parser.add_argument(
"-k",
help=(
"optional - path to x509 key file for "
"client encryption over HTTP"),
required=False,
dest="key_file")
parser.add_argument(
"-s",
help="silent",
required=False,
dest="silent",
action="store_true")
parser.add_argument(
"-d",
help="debug",
required=False,
dest="debug",
action="store_true")
args = parser.parse_args()
user = ev(
"API_USER",
"user-not-set")
password = ev(
"API_PASSWORD",
"password-not-set")
email = ev(
"API_EMAIL",
"email-not-set")
url = ev(
"API_URL",
"http://localhost:8010")
datafile = ev(
"DATAFILE",
"datafile-not-set")
ca_dir = os.getenv(
"API_CA_BUNDLE_DIR",
None)
cert_file = os.getenv(
"API_CERT_FILE",
None)
key_file = os.getenv(
"API_KEY_FILE",
None)
verbose = bool(str(ev(
"API_VERBOSE",
"true")).lower() == "true")
debug = bool(str(ev(
"API_DEBUG",
"false")).lower() == "true")
if args.user:
user = args.user
if args.password:
password = args.password
if args.email:
email = args.email
if args.url:
url = args.url
if args.datafile:
datafile = args.datafile
if args.ca_dir:
ca_dir = args.ca_dir
if args.cert_file:
cert_file = args.cert_file
if args.key_file:
key_file = args.key_file
if args.silent:
verbose = False
if args.debug:
debug = True
usage = (
"Please run with "
"-u <username> "
"-p <password> "
"-a <AntiNex URL http://localhost:8010> "
"-f <path to json file> "
"-b <optional - path to CA bundle directory> "
"-c <optional - path to x509 ssl certificate file> "
"-k <optional - path to x509 ssl key file>")
valid = True
if not user or user == "user-not-set":
log.error("missing user")
valid = False
if not password or password == "password-not-set":
log.error("missing password")
valid = False
if not datafile or datafile == "datafile-not-set":
log.error("missing datafile")
valid = False
else:
if not os.path.exists(datafile):
log.error(("did not find datafile={} on disk")
.format(
datafile))
valid = False
if not valid:
log.error(usage)
sys.exit(1)
if verbose:
log.info((
"creating client user={} url={} file={} "
"ca_dir={} cert_file={} key_file={}").format(
user,
url,
datafile,
ca_dir,
cert_file,
key_file))
client = AIClient(
user=user,
email=email,
password=password,
url=url,
ca_dir=ca_dir,
cert_file=cert_file,
key_file=key_file,
verbose=verbose,
debug=debug)
if verbose:
log.info(("loading request in datafile={}")
.format(
datafile))
req_body = None
with open(datafile, "r") as f:
req_body = json.loads(f.read())
if verbose:
log.info("running job")
job_was_started = False
response = client.run_job(
body=req_body)
if response["status"] == SUCCESS:
log.info(("job started with response={}")
.format(
response["data"]))
job_was_started = True
elif response["status"] == FAILED:
log.error(("job failed with error='{}' with response={}")
.format(
response["error"],
response["data"]))
elif response["status"] == ERROR:
log.error(("job had an error='{}' with response={}")
.format(
response["error"],
response["data"]))
elif response["status"] == LOGIN_FAILED:
log.error(("job reported user was not able to log in "
"with an error='{}' with response={}")
.format(
response["error"],
response["data"]))
if not job_was_started:
sys.exit(1)
if debug:
log.info(("parsing response data={}")
.format(
response["data"]))
else:
if verbose:
log.info("parsing data")
res_data = response["data"]
job_data = res_data.get(
"job",
None)
result_data = res_data.get(
"results",
None)
if not job_data:
log.error(("missing job dictionary in response data={}")
.format(
response["data"]))
sys.exit(1)
if not result_data:
log.error(("missing results dictionary in response data={}")
.format(
response["data"]))
sys.exit(1)
job_id = job_data.get("id", None)
job_status = job_data.get("status", None)
result_id = result_data.get("id", None)
result_status = result_data.get("status", None)
log.info(("started job.id={} job.status={} with "
"result.id={} result.status={}")
.format(
job_id,
job_status,
result_id,
result_status))
job_results = client.wait_for_job_to_finish(
job_id=job_id)
if job_results["status"] != SUCCESS:
log.error(("failed waiting for job.id={} to finish error={} data={}")
.format(
job_id,
job_results["error"],
job_results["data"]))
sys.exit(1)
final_job = job_results["data"]["job"]
final_result = job_results["data"]["result"]
if verbose:
log.info(("job={}")
.format(
ppj(final_job)))
else:
log.info(("job={}")
.format(
str(final_job)[0:10]))
if verbose:
log.info(("result={}")
.format(
ppj(final_result)))
else:
log.info(("result={}")
.format(
str(final_result)[0:10]))
log.info(("job.id={} is done")
.format(
job_id))
predictions = final_result["predictions_json"].get(
"predictions",
[])
log.info(("loading predictions={} into pandas dataframe")
.format(
len(predictions)))
df = pd.DataFrame(predictions)
if verbose:
log.info(("dataframe={}")
.format(
df))
|
train_new_deep_neural_network
Train a new deep neural network and store the results as a new:
``MLJob`` and ``MLJobResult`` database records.
|
entailment
|
def prepare_new_dataset():
"""prepare_new_dataset
Prepare a new ``MLPrepare`` record and dataset files on disk.
"""
parser = argparse.ArgumentParser(
description=(
"Python client to Prepare a dataset"))
parser.add_argument(
"-u",
help="username",
required=False,
dest="user")
parser.add_argument(
"-p",
help="user password",
required=False,
dest="password")
parser.add_argument(
"-e",
help="user email",
required=False,
dest="email")
parser.add_argument(
"-a",
help="url endpoint with default http://localhost:8010",
required=False,
dest="url")
parser.add_argument(
"-f",
help="file to use default ./examples/test-keras-dnn.json",
required=False,
dest="prepare_file")
parser.add_argument(
"-b",
help=(
"optional - path to CA bundle directory for "
"client encryption over HTTP"),
required=False,
dest="ca_dir")
parser.add_argument(
"-c",
help=(
"optional - path to x509 certificate for "
"client encryption over HTTP"),
required=False,
dest="cert_file")
parser.add_argument(
"-k",
help=(
"optional - path to x509 key file for "
"client encryption over HTTP"),
required=False,
dest="key_file")
parser.add_argument(
"-s",
help="silent",
required=False,
dest="silent",
action="store_true")
parser.add_argument(
"-d",
help="debug",
required=False,
dest="debug",
action="store_true")
args = parser.parse_args()
user = ev(
"API_USER",
"user-not-set")
password = ev(
"API_PASSWORD",
"password-not-set")
email = ev(
"API_EMAIL",
"email-not-set")
url = ev(
"API_URL",
"http://localhost:8010")
prepare_file = ev(
"DATAFILE",
"prepare_file-not-set")
ca_dir = os.getenv(
"API_CA_BUNDLE_DIR",
None)
cert_file = os.getenv(
"API_CERT_FILE",
None)
key_file = os.getenv(
"API_KEY_FILE",
None)
verbose = bool(str(ev(
"API_VERBOSE",
"true")).lower() == "true")
debug = bool(str(ev(
"API_DEBUG",
"false")).lower() == "true")
if args.user:
user = args.user
if args.password:
password = args.password
if args.email:
email = args.email
if args.url:
url = args.url
if args.prepare_file:
prepare_file = args.prepare_file
if args.ca_dir:
ca_dir = args.ca_dir
if args.cert_file:
cert_file = args.cert_file
if args.key_file:
key_file = args.key_file
if args.silent:
verbose = False
if args.debug:
debug = True
usage = (
"Please run with "
"-u <username> "
"-p <password> "
"-a <AntiNex URL http://localhost:8010> "
"-f <path to prepare file> "
"-b <optional - path to CA bundle directory> "
"-c <optional - path to x509 ssl certificate file> "
"-k <optional - path to x509 ssl key file>")
valid = True
if not user or user == "user-not-set":
log.error("missing user")
valid = False
if not password or password == "password-not-set":
log.error("missing password")
valid = False
if not prepare_file or prepare_file == "prepare_file-not-set":
log.error("missing prepare_file")
valid = False
else:
if not os.path.exists(prepare_file):
log.error(("did not find prepare_file={} on disk")
.format(
prepare_file))
valid = False
if not valid:
log.error(usage)
sys.exit(1)
if verbose:
log.info(("creating client user={} url={} file={}")
.format(
user,
url,
prepare_file))
client = AIClient(
user=user,
email=email,
password=password,
url=url,
ca_dir=ca_dir,
cert_file=cert_file,
key_file=key_file,
verbose=verbose,
debug=debug)
if verbose:
log.info(("loading request in prepare_file={}")
.format(
prepare_file))
req_body = None
with open(prepare_file, "r") as f:
req_body = json.loads(f.read())
if verbose:
log.info("running prepare")
prepare_was_started = False
response = client.run_prepare(
body=req_body)
if response["status"] == SUCCESS:
log.info(("prepare started with response={}")
.format(
response["data"]))
prepare_was_started = True
elif response["status"] == FAILED:
log.error(("prepare failed with error='{}' with response={}")
.format(
response["error"],
response["data"]))
elif response["status"] == ERROR:
log.error(("prepare had an error='{}' with response={}")
.format(
response["error"],
response["data"]))
elif response["status"] == LOGIN_FAILED:
log.error(("prepare reported user was not able to log in "
"with an error='{}' with response={}")
.format(
response["error"],
response["data"]))
if not prepare_was_started:
sys.exit(1)
if debug:
log.info(("parsing response data={}")
.format(
response["data"]))
else:
if verbose:
log.info("parsing data")
prepare_data = response["data"]
if not prepare_data:
log.error(("missing prepare dictionary in response data={}")
.format(
response["data"]))
sys.exit(1)
prepare_id = prepare_data.get("id", None)
prepare_status = prepare_data.get("status", None)
log.info(("started prepare.id={} prepare.status={}")
.format(
prepare_id,
prepare_status))
prepare_results = client.wait_for_prepare_to_finish(
prepare_id=prepare_id)
if prepare_results["status"] != SUCCESS:
log.error(("failed waiting for prepare.id={} to finish "
"error={} data={}")
.format(
prepare_id,
prepare_results["error"],
prepare_results["data"]))
sys.exit(1)
final_prepare = prepare_results["data"]
log.info(("prepare={}")
.format(
ppj(final_prepare)))
log.info(("prepare.id={} is done")
.format(
prepare_id))
|
prepare_new_dataset
Prepare a new ``MLPrepare`` record and dataset files on disk.
|
entailment
|
def drape(raster, feature):
"""Convert a 2D feature to a 3D feature by sampling a raster
Parameters:
raster (rasterio): raster to provide the z coordinate
feature (dict): fiona feature record to convert
Returns:
result (Point or Linestring): shapely Point or LineString of xyz coordinate triples
"""
coords = feature['geometry']['coordinates']
geom_type = feature['geometry']['type']
if geom_type == 'Point':
xyz = sample(raster, [coords])
result = Point(xyz[0])
elif geom_type == 'LineString':
xyz = sample(raster, coords)
points = [Point(x, y, z) for x, y, z in xyz]
result = LineString(points)
else:
logging.error('drape not implemented for {}'.format(geom_type))
return result
|
Convert a 2D feature to a 3D feature by sampling a raster
Parameters:
raster (rasterio): raster to provide the z coordinate
feature (dict): fiona feature record to convert
Returns:
result (Point or Linestring): shapely Point or LineString of xyz coordinate triples
|
entailment
|
def sample(raster, coords):
"""Sample a raster at given coordinates
Given a list of coordinates, return a list of x,y,z triples with z coordinates sampled from an input raster
Parameters:
raster (rasterio): raster dataset to sample
coords: array of tuples containing coordinate pairs (x,y) or triples (x,y,z)
Returns:
result: array of tuples containing coordinate triples (x,y,z)
"""
if len(coords[0]) == 3:
logging.info('Input is a 3D geometry, z coordinate will be updated.')
z = raster.sample([(x, y) for x, y, z in coords], indexes=raster.indexes)
else:
z = raster.sample(coords, indexes=raster.indexes)
result = [(vert[0], vert[1], vert_z) for vert, vert_z in zip(coords, z)]
return result
|
Sample a raster at given coordinates
Given a list of coordinates, return a list of x,y,z triples with z coordinates sampled from an input raster
Parameters:
raster (rasterio): raster dataset to sample
coords: array of tuples containing coordinate pairs (x,y) or triples (x,y,z)
Returns:
result: array of tuples containing coordinate triples (x,y,z)
|
entailment
|
def setup_logging(
default_level=logging.INFO,
default_path="{}/logging.json".format(
os.getenv(
"LOG_DIR",
os.path.dirname(os.path.realpath(__file__)))),
env_key="LOG_CFG",
config_name=None):
"""setup_logging
Setup logging configuration
:param default_level: level to log
:param default_path: path to config (optional)
:param env_key: path to config in this env var
:param config_name: filename for config
"""
path = default_path
file_name = default_path.split("/")[-1]
if config_name:
file_name = config_name
path = "{}/{}".format(
"/".join(default_path.split("/")[:-1]),
file_name)
value = os.getenv(env_key, None)
if value:
path = value
if os.path.exists(path):
with open(path, "rt") as f:
config = json.load(f)
logging.config.dictConfig(config)
return
else:
cwd_path = os.getcwd() + "/antinex_client/log/{}".format(
file_name)
if os.path.exists(cwd_path):
with open(cwd_path, "rt") as f:
config = json.load(f)
logging.config.dictConfig(config)
return
rels_path = os.getcwd() + "/../log/{}".format(
file_name)
if os.path.exists(rels_path):
with open(rels_path, "rt") as f:
config = json.load(f)
logging.config.dictConfig(config)
return
else:
logging.basicConfig(level=default_level)
return
|
setup_logging
Setup logging configuration
:param default_level: level to log
:param default_path: path to config (optional)
:param env_key: path to config in this env var
:param config_name: filename for config
|
entailment
|
def build_logger(
name=os.getenv(
"LOG_NAME",
"client"),
config="logging.json",
log_level=logging.INFO,
log_config_path="{}/logging.json".format(
os.getenv(
"LOG_CFG",
os.path.dirname(os.path.realpath(__file__))))):
"""build_logger
:param name: name that shows in the logger
:param config: name of the config file
:param log_level: level to log
:param log_config_path: path to log config file
"""
use_config = ("./log/{}").format(
"{}".format(
config))
if not os.path.exists(use_config):
use_config = log_config_path
if not os.path.exists(use_config):
use_config = ("./antinex_client/log/{}").format(
"logging.json")
# find the log processing
setup_logging(
default_level=log_level,
default_path=use_config)
return logging.getLogger(name)
|
build_logger
:param name: name that shows in the logger
:param config: name of the config file
:param log_level: level to log
:param log_config_path: path to log config file
|
entailment
|
def build_colorized_logger(
name=os.getenv(
"LOG_NAME",
"client"),
config="colors-logging.json",
log_level=logging.INFO,
log_config_path="{}/logging.json".format(
os.getenv(
"LOG_CFG",
os.path.dirname(os.path.realpath(__file__))))):
"""build_colorized_logger
:param name: name that shows in the logger
:param config: name of the config file
:param log_level: level to log
:param log_config_path: path to log config file
"""
override_config = os.getenv(
"SHARED_LOG_CFG",
None)
debug_log_config = bool(os.getenv(
"DEBUG_SHARED_LOG_CFG",
"0") == "1")
if override_config:
if debug_log_config:
print((
"creating logger config env var: "
"SHARED_LOG_CFG={}".format(
override_config)))
if os.path.exists(override_config):
setup_logging(
default_level=log_level,
default_path=override_config)
return logging.getLogger(name)
if debug_log_config:
print((
"Failed to find log config using env var: "
"SHARED_LOG_CFG={}".format(
override_config)))
else:
if debug_log_config:
print((
"Not using shared logging env var: "
"SHARED_LOG_CFG={}".format(
override_config)))
# allow a shared log config across all components
use_config = ("{}").format(
config)
if not os.path.exists(use_config):
use_config = ("./antinex_client/log/{}").format(
config)
if not os.path.exists(use_config):
use_config = log_config_path
if not os.path.exists(use_config):
use_config = ("./log/{}").format(
config)
if not os.path.exists(use_config):
use_config = ("./antinex_client/log/{}").format(
"logging.json")
# find the last log config backup from the base of the repo
# find the log config from the defaults with the env LOG_CFG
# find the log config from the base of the repo
# find the log config by the given path
setup_logging(
default_level=log_level,
default_path=use_config)
return logging.getLogger(name)
|
build_colorized_logger
:param name: name that shows in the logger
:param config: name of the config file
:param log_level: level to log
:param log_config_path: path to log config file
|
entailment
|
def authenticate(self, request: HttpRequest, auth_route: str, actual_params: dict) -> bool:
"""
Your AuhtService should override this method for request authentication, otherwise means no authentication.
:param request: HttpRequest Django's HttpRequest object
:param auth_route: str User's resqueted route
:param actual_params: User's url parameters
:return: bool
"""
if auth_route and actual_params:
self.auth_data = {}
return True
|
Your AuhtService should override this method for request authentication, otherwise means no authentication.
:param request: HttpRequest Django's HttpRequest object
:param auth_route: str User's resqueted route
:param actual_params: User's url parameters
:return: bool
|
entailment
|
def cli(source_f, raster_f, output, verbose):
"""
Converts 2D geometries to 3D using GEOS sample through fiona.
\b
Example:
drape point.shp elevation.tif -o point_z.shp
"""
with fiona.open(source_f, 'r') as source:
source_driver = source.driver
source_crs = source.crs
sink_schema = source.schema.copy()
source_geom = source.schema['geometry']
if source_geom == 'Point':
sink_schema['geometry'] = '3D Point'
elif source_geom == 'LineString':
sink_schema['geometry'] = '3D LineString'
elif source_geom == '3D Point' or source_geom == '3D LineString':
pass
else:
click.BadParameter("Source geometry type {} not implemented".format(source_geom))
with rasterio.open(raster_f) as raster:
if source_crs != raster.crs:
click.BadParameter("Features and raster have different CRS.")
if raster.count > 1:
warnings.warn("Found {0} bands in {1}, expected a single band raster".format(raster.bands, raster_f))
supported = ['int16', 'int32', 'float32', 'float64']
if raster.dtypes[0] not in supported:
warnings.warn("Found {0} type in {1}, expected one of {2}".format(raster.dtypes[0]), raster_f, supported)
with fiona.open(
output, 'w',
driver=source_driver,
crs=source_crs,
schema=sink_schema) as sink:
for feature in source:
try:
feature_z = drapery.drape(raster, feature)
sink.write({
'geometry': mapping(feature_z),
'properties': feature['properties'],
})
except Exception:
logging.exception("Error processing feature %s:", feature['id'])
|
Converts 2D geometries to 3D using GEOS sample through fiona.
\b
Example:
drape point.shp elevation.tif -o point_z.shp
|
entailment
|
def for_model(self, model):
"""
QuerySet for all comments for a particular model (either an instance or
a class).
"""
ct = ContentType.objects.get_for_model(model)
qs = self.get_queryset().filter(content_type=ct)
if isinstance(model, models.Model):
qs = qs.filter(object_pk=force_text(model._get_pk_val()))
return qs
|
QuerySet for all comments for a particular model (either an instance or
a class).
|
entailment
|
def eval(self, command):
'Blocking call, returns the value of the execution in JS'
event = threading.Event()
# TODO: Add event to server
#job_id = str(id(command))
import random
job_id = str(random.random())
server.EVALUATIONS[job_id] = event
message = '?' + job_id + '=' + command
logging.info(('message:', [message]))
for listener in server.LISTENERS.get(self.path, []):
logging.debug(('listener:', listener))
listener.write_message(message)
success = event.wait(timeout=30)
if success:
value_parser = server.RESULTS[job_id]
del server.EVALUATIONS[job_id]
del server.RESULTS[job_id]
return value_parser()
else:
del server.EVALUATIONS[job_id]
if job_id in server.RESULTS:
del server.RESULTS[job_id]
raise IOError('Evaluation failed.')
|
Blocking call, returns the value of the execution in JS
|
entailment
|
def register(self, callback, name):
'Register a callback on server and on connected clients.'
server.CALLBACKS[name] = callback
self.run('''
window.skink.%s = function(args=[]) {
window.skink.call("%s", args);
}''' % (name, name))
|
Register a callback on server and on connected clients.
|
entailment
|
def launch_exception(message):
"""
Launch a Python exception from an error that took place in the browser.
messsage format:
- name: str
- description: str
"""
error_name = message['name']
error_descr = message['description']
mapping = {
'ReferenceError': NameError,
}
if message['name'] in mapping:
raise mapping[error_name](error_descr)
else:
raise Exception('{}: {}'.format(error_name, error_descr))
|
Launch a Python exception from an error that took place in the browser.
messsage format:
- name: str
- description: str
|
entailment
|
def start_predictions():
"""start_predictions
Using environment variables, create an AntiNex AI Client.
You can also use command line args if you want.
This can train a new deep neural network if it does not
exist or it can use an existing pre-trained deep neural
network within the AntiNex Core to make new predictions.
"""
parser = argparse.ArgumentParser(
description=(
"Python client to make Predictions "
"using a Pre-trained Deep Neural Network "
"with AntiNex Django Rest Framework"))
parser.add_argument(
"-f",
help=(
"file to use default ./examples/"
"predict-rows-scaler-full-django.json"),
required=False,
dest="datafile")
parser.add_argument(
"-m",
help="send mock data",
required=False,
dest="use_fake_rows",
action="store_true")
parser.add_argument(
"-b",
help=(
"optional - path to CA bundle directory for "
"client encryption over HTTP"),
required=False,
dest="ca_dir")
parser.add_argument(
"-c",
help=(
"optional - path to x509 certificate for "
"client encryption over HTTP"),
required=False,
dest="cert_file")
parser.add_argument(
"-k",
help=(
"optional - path to x509 key file for "
"client encryption over HTTP"),
required=False,
dest="key_file")
parser.add_argument(
"-s",
help="silent",
required=False,
dest="silent",
action="store_true")
parser.add_argument(
"-d",
help="debug",
required=False,
dest="debug",
action="store_true")
args = parser.parse_args()
datafile = ev(
"DATAFILE",
"./examples/predict-rows-scaler-full-django.json")
ca_dir = os.getenv(
"API_CA_BUNDLE_DIR",
None)
cert_file = os.getenv(
"API_CERT_FILE",
None)
key_file = os.getenv(
"API_KEY_FILE",
None)
verbose = bool(str(ev(
"API_CLIENT_VERBOSE",
"1")).lower() == "1")
debug = bool(str(ev(
"API_CLIENT_DEBUG",
"0")).lower() == "1")
use_fake_rows = False
if args.use_fake_rows:
use_fake_rows = True
if args.datafile:
datafile = args.datafile
if args.ca_dir:
ca_dir = args.ca_dir
if args.cert_file:
cert_file = args.cert_file
if args.key_file:
key_file = args.key_file
if args.silent:
verbose = False
if args.debug:
debug = True
if verbose:
log.info("creating client")
client = build_ai_client_from_env(
ca_dir=ca_dir,
cert_file=cert_file,
key_file=key_file,
verbose=verbose,
debug=debug)
if verbose:
log.info(("loading request in datafile={}")
.format(
datafile))
# pass in full or partial prediction record dictionaries
# the generate_ai_request will fill in gaps with defaults
fake_rows_for_predicting = [
{
"tcp_seq": 1
},
{
"tcp_seq": 2
},
{
"tcp_seq": 3
},
{
"tcp_seq": 4
}
]
res_gen = None
if use_fake_rows:
res_gen = generate_ai_request(
predict_rows=fake_rows_for_predicting)
else:
req_with_org_rows = None
with open(datafile, "r") as f:
req_with_org_rows = json.loads(f.read())
res_gen = generate_ai_request(
predict_rows=req_with_org_rows["predict_rows"])
# end of sending mock data from this file or a file on disk
if res_gen["status"] != SUCCESS:
log.error(("failed generate_ai_request with error={}")
.format(
res_gen["error"]))
sys.exit(1)
req_body = res_gen["data"]
if verbose:
log.info("running job")
job_was_started = False
response = client.run_job(
body=req_body)
if response["status"] == SUCCESS:
log.info(("job started with response={}")
.format(
response["data"]))
job_was_started = True
elif response["status"] == FAILED:
log.error(("job failed with error='{}' with response={}")
.format(
response["error"],
response["data"]))
elif response["status"] == ERROR:
log.error(("job had an error='{}' with response={}")
.format(
response["error"],
response["data"]))
elif response["status"] == LOGIN_FAILED:
log.error(("job reported user was not able to log in "
"with an error='{}' with response={}")
.format(
response["error"],
response["data"]))
if not job_was_started:
sys.exit(1)
if debug:
log.info(("parsing response data={}")
.format(
response["data"]))
else:
if verbose:
log.info("parsing data")
res_data = response["data"]
job_data = res_data.get(
"job",
None)
result_data = res_data.get(
"results",
None)
if not job_data:
log.error(("missing job dictionary in response data={}")
.format(
response["data"]))
sys.exit(1)
if not result_data:
log.error(("missing results dictionary in response data={}")
.format(
response["data"]))
sys.exit(1)
job_id = job_data.get("id", None)
job_status = job_data.get("status", None)
result_id = result_data.get("id", None)
result_status = result_data.get("status", None)
log.info(("started job.id={} job.status={} with "
"result.id={} result.status={}")
.format(
job_id,
job_status,
result_id,
result_status))
job_results = client.wait_for_job_to_finish(
job_id=job_id)
if job_results["status"] != SUCCESS:
log.error(("failed waiting for job.id={} to finish error={} data={}")
.format(
job_id,
job_results["error"],
job_results["data"]))
sys.exit(1)
final_job = job_results["data"]["job"]
final_result = job_results["data"]["result"]
log.info(("job={}")
.format(
ppj(final_job)))
log.info(("result={}")
.format(
ppj(final_result)))
log.info(("job.id={} is done")
.format(
job_id))
predictions = final_result["predictions_json"].get(
"predictions",
[])
log.info(("loading predictions={} into pandas dataframe")
.format(
len(predictions)))
df = pd.DataFrame(predictions)
log.info(("dataframe={}")
.format(
df))
|
start_predictions
Using environment variables, create an AntiNex AI Client.
You can also use command line args if you want.
This can train a new deep neural network if it does not
exist or it can use an existing pre-trained deep neural
network within the AntiNex Core to make new predictions.
|
entailment
|
def login(
self):
"""login"""
auth_url = self.api_urls["login"]
if self.verbose:
log.info(("log in user={} url={} ca_dir={} cert={}")
.format(
self.user,
auth_url,
self.ca_dir,
self.cert))
use_headers = {
"Content-type": "application/json"
}
login_data = {
"username": self.user,
"password": self.password
}
if self.debug:
log.info((
"LOGIN with body={} headers={} url={} "
"verify={} cert={}").format(
login_data,
use_headers,
auth_url,
self.use_verify,
self.cert))
response = requests.post(
auth_url,
verify=self.use_verify,
cert=self.cert,
data=json.dumps(login_data),
headers=use_headers)
if self.debug:
log.info(("LOGIN response status_code={} text={} reason={}")
.format(
response.status_code,
response.text,
response.reason))
user_token = ""
if response.status_code == 200:
user_token = json.loads(response.text)["token"]
if user_token != "":
self.token = user_token
self.login_status = LOGIN_SUCCESS
if self.verbose:
log.debug("login success")
else:
log.error(("failed to login user={} to url={} text={}")
.format(
self.user,
auth_url,
response.text))
self.login_status = LOGIN_FAILED
# if the user token exists
return self.login_status
|
login
|
entailment
|
def build_response(
self,
status=NOT_SET,
error="",
data=None):
"""build_response
:param status: status code
:param error: error message
:param data: dictionary to send back
"""
res_node = {
"status": status,
"error": error,
"data": data
}
return res_node
|
build_response
:param status: status code
:param error: error message
:param data: dictionary to send back
|
entailment
|
def retry_login(
self):
"""retry_login"""
if not self.user or not self.password:
return self.build_response(
status=ERROR,
error="please set the user and password")
retry = 0
not_done = True
while not_done:
if self.is_logged_in():
return self.build_response(
status=SUCCESS)
else:
if self.verbose:
log.debug(("login attempt={} max={}")
.format(
retry,
self.max_retries))
if self.login() == LOGIN_SUCCESS:
return self.build_response(
status=SUCCESS)
else:
time.sleep(
self.login_retry_wait_time)
# if able to login or not
retry += 1
if retry > self.max_retries:
return self.build_response(
status=ERROR,
error="failed logging in user={} retries={}".format(
self.user,
self.max_retries))
# if login worked or not
return self.build_response(
status=FAILED,
error="user={} not able to login attempts={}".format(
self.user,
retry))
|
retry_login
|
entailment
|
def get_prepare_by_id(
self,
prepare_id=None):
"""get_prepare_by_id
:param prepare_id: MLJob.id in the database
"""
if not prepare_id:
log.error("missing prepare_id for get_prepare_by_id")
return self.build_response(
status=ERROR,
error="missing prepare_id for get_prepare_by_id")
if self.debug:
log.info(("user={} getting prepare={}")
.format(
self.user,
prepare_id))
url = "{}{}".format(
self.api_urls["prepare"],
prepare_id)
not_done = True
while not_done:
if self.debug:
log.info((
"JOB attempting to get={} to url={} "
"verify={} cert={}").format(
prepare_id,
url,
self.use_verify,
self.cert))
response = requests.get(
url,
verify=self.use_verify,
cert=self.cert,
headers=self.get_auth_header())
if self.debug:
log.info(("JOB response status_code={} text={} reason={}")
.format(
response.status_code,
response.text,
response.reason))
if response.status_code == 401:
login_res = self.retry_login()
if login_res["status"] != SUCCESS:
if self.verbose:
log.error(
"retry login attempts failed")
return self.build_response(
status=login_res["status"],
error=login_res["error"])
# if able to log back in just retry the call
elif response.status_code == 200:
if self.verbose:
log.debug("deserializing")
prepare_data = json.loads(
response.text)
prepare_id = prepare_data.get(
"id",
None)
if not prepare_id:
return self.build_response(
status=ERROR,
error="missing prepare.id",
data="text={} reason={}".format(
response.reason,
response.text))
self.all_prepares[str(prepare_id)] = prepare_data
if self.debug:
log.info(("added prepare={} all_prepares={}")
.format(
prepare_id,
len(self.all_prepares)))
return self.build_response(
status=SUCCESS,
error="",
data=prepare_data)
else:
err_msg = ("failed with "
"status_code={} text={} reason={}").format(
response.status_code,
response.text,
response.reason)
if self.verbose:
log.error(err_msg)
return self.build_response(
status=ERROR,
error=err_msg)
|
get_prepare_by_id
:param prepare_id: MLJob.id in the database
|
entailment
|
def wait_for_job_to_finish(
self,
job_id,
sec_to_sleep=5.0,
max_retries=100000):
"""wait_for_job_to_finish
:param job_id: MLJob.id to wait on
:param sec_to_sleep: seconds to sleep during polling
:param max_retries: max retires until stopping
"""
not_done = True
retry_attempt = 1
while not_done:
if self.debug:
log.info(("JOBSTATUS getting job.id={} details")
.format(
job_id))
response = self.get_job_by_id(job_id)
if self.debug:
log.info(("JOBSTATUS got job.id={} response={}")
.format(
job_id,
response))
if response["status"] != SUCCESS:
log.error(("JOBSTATUS failed to get job.id={} with error={}")
.format(
job_id,
response["error"]))
return self.build_response(
status=ERROR,
error=response["error"],
data=response["data"])
# stop if this failed getting the job details
job_data = response.get(
"data",
None)
if not job_data:
return self.build_response(
status=ERROR,
error="failed to find job dictionary in response",
data=response["data"])
job_status = job_data["status"]
if job_status == "finished" \
or job_status == "completed" \
or job_status == "launched":
if self.debug:
log.info(("job.id={} is done with status={}")
.format(
job_id,
job_status))
result_id = job_data["predict_manifest"]["result_id"]
if self.debug:
log.info(("JOBRESULT getting result.id={} details")
.format(
result_id))
response = self.get_result_by_id(result_id)
if self.debug:
log.info(("JOBRESULT got result.id={} response={}")
.format(
result_id,
response))
if response["status"] != SUCCESS:
log.error(("JOBRESULT failed to get "
"result.id={} with error={}")
.format(
result_id,
response["error"]))
return self.build_response(
status=ERROR,
error=response["error"],
data=response["data"])
# stop if this failed getting the result details
result_data = response.get(
"data",
None)
if result_data["status"] == "finished":
full_response = {
"job": job_data,
"result": result_data
}
not_done = False
return self.build_response(
status=SUCCESS,
error="",
data=full_response)
else:
if retry_attempt % 100 == 0:
if self.verbose:
log.info(("result_id={} are not done retry={}")
.format(
result_id,
retry_attempt))
retry_attempt += 1
if retry_attempt > max_retries:
err_msg = ("failed waiting "
"for job.id={} result.id={} "
"to finish").format(
job_id,
result_id)
log.error(err_msg)
return self.build_response(
status=ERROR,
error=err_msg)
else:
time.sleep(sec_to_sleep)
# wait while results are written to the db
else:
retry_attempt += 1
if retry_attempt > max_retries:
err_msg = ("failed waiting "
"for job.id={} to finish").format(
job_id)
log.error(err_msg)
return self.build_response(
status=ERROR,
error=err_msg)
else:
if self.verbose:
if retry_attempt % 100 == 0:
log.info(("waiting on job.id={} retry={}")
.format(
job_id,
retry_attempt))
# if logging just to show this is running
time.sleep(sec_to_sleep)
|
wait_for_job_to_finish
:param job_id: MLJob.id to wait on
:param sec_to_sleep: seconds to sleep during polling
:param max_retries: max retires until stopping
|
entailment
|
def wait_for_prepare_to_finish(
self,
prepare_id,
sec_to_sleep=5.0,
max_retries=100000):
"""wait_for_prepare_to_finish
:param prepare_id: MLPrepare.id to wait on
:param sec_to_sleep: seconds to sleep during polling
:param max_retries: max retires until stopping
"""
not_done = True
retry_attempt = 1
while not_done:
if self.debug:
log.info(("PREPSTATUS getting prepare.id={} details")
.format(
prepare_id))
response = self.get_prepare_by_id(prepare_id)
if self.debug:
log.info(("PREPSTATUS got prepare.id={} response={}")
.format(
prepare_id,
response))
if response["status"] != SUCCESS:
log.error(("PREPSTATUS failed to get prepare.id={} "
"with error={}")
.format(
prepare_id,
response["error"]))
return self.build_response(
status=ERROR,
error=response["error"],
data=response["data"])
# stop if this failed getting the prepare details
prepare_data = response.get(
"data",
None)
if not prepare_data:
return self.build_response(
status=ERROR,
error="failed to find prepare dictionary in response",
data=response["data"])
prepare_status = prepare_data["status"]
if prepare_status == "finished" \
or prepare_status == "completed":
not_done = False
return self.build_response(
status=SUCCESS,
error="",
data=prepare_data)
else:
retry_attempt += 1
if retry_attempt > max_retries:
err_msg = ("failed waiting "
"for prepare.id={} to finish").format(
prepare_id)
log.error(err_msg)
return self.build_response(
status=ERROR,
error=err_msg)
else:
if self.verbose:
if retry_attempt % 100 == 0:
log.info(("waiting on prepare.id={} retry={}")
.format(
prepare_id,
retry_attempt))
# if logging just to show this is running
time.sleep(sec_to_sleep)
|
wait_for_prepare_to_finish
:param prepare_id: MLPrepare.id to wait on
:param sec_to_sleep: seconds to sleep during polling
:param max_retries: max retires until stopping
|
entailment
|
def get_comment_object(self):
"""
NB: Overridden to remove dupe comment check for admins (necessary for
canned responses)
Return a new (unsaved) comment object based on the information in this
form. Assumes that the form is already validated and will throw a
ValueError if not.
Does not set any of the fields that would come from a Request object
(i.e. ``user`` or ``ip_address``).
"""
if not self.is_valid():
raise ValueError(
"get_comment_object may only be called on valid forms")
CommentModel = self.get_comment_model()
new = CommentModel(**self.get_comment_create_data())
user_model = get_user_model()
try:
user = user_model.objects.get(username=new.user_name)
if not user.is_staff:
new = self.check_for_duplicate_comment(new)
except user_model.DoesNotExist:
# post_molo_comment may have set the username to 'Anonymous'
new = self.check_for_duplicate_comment(new)
return new
|
NB: Overridden to remove dupe comment check for admins (necessary for
canned responses)
Return a new (unsaved) comment object based on the information in this
form. Assumes that the form is already validated and will throw a
ValueError if not.
Does not set any of the fields that would come from a Request object
(i.e. ``user`` or ``ip_address``).
|
entailment
|
def boot(app_name) -> Rinzler:
"""
Start Rinzler App
:param app_name: str Application's identifier
:return: dict
"""
app = Rinzler(app_name)
app.log.info("App booted =)")
return app
|
Start Rinzler App
:param app_name: str Application's identifier
:return: dict
|
entailment
|
def mount(self, route: str, controller: callable) -> url:
"""
Maps a route namespace with the given params and point it's requests to the especified controller.
:param route: str Namespace route to be mapped
:param controller: callback Controller callable to map end-points
:rtype: url
"""
if issubclass(controller, TemplateView):
return url(
r"%s" % route,
Router(self, route, controller).handle
)
else:
raise TypeError("The controller %s must be a subclass of %s" % (
controller, TemplateView
)
)
|
Maps a route namespace with the given params and point it's requests to the especified controller.
:param route: str Namespace route to be mapped
:param controller: callback Controller callable to map end-points
:rtype: url
|
entailment
|
def set_auth_service(self, auth_service: BaseAuthService):
"""
Sets the authentication service
:param auth_service: BaseAuthService Authentication service
:raises: TypeError If the auth_service object is not a subclass of rinzler.auth.BaseAuthService
:rtype: Rinzler
"""
if issubclass(auth_service.__class__, BaseAuthService):
self.auth_service = auth_service
return self
else:
raise TypeError("Your auth service object must be a subclass of rinzler.auth.BaseAuthService.")
|
Sets the authentication service
:param auth_service: BaseAuthService Authentication service
:raises: TypeError If the auth_service object is not a subclass of rinzler.auth.BaseAuthService
:rtype: Rinzler
|
entailment
|
def handle(self, request: HttpRequest) -> HttpResponse:
"""
Prepares for the CallBackResolver and handles the response and exceptions
:param request HttpRequest
:rtype: HttpResponse
"""
self.__request_start = datetime.now()
self.__request = request
self.__uri = request.path[1:]
self.__method = request.method
# Initializes the callable controller and call it's connect method to get the mapped end-points.
controller: RouteMapping = self.__controller().connect(self.app)
self.__end_points = controller.get_routes()
indent = self.get_json_ident(request.META)
if self.set_end_point_uri() is False:
return self.set_response_headers(self.no_route_found(self.__request).render(indent))
response = HttpResponse(None)
try:
response = self.exec_route_callback()
except RinzlerHttpException as e:
client.captureException()
self.app.log.error(f"< {e.status_code}", exc_info=True)
response = Response(None, status=e.status_code)
except RequestDataTooBig:
client.captureException()
self.app.log.error("< 413", exc_info=True)
response = Response(None, status=413)
except BaseException:
client.captureException()
self.app.log.error("< 500", exc_info=True)
response = Response(None, status=500)
finally:
if type(response) == Response:
return self.set_response_headers(response.render(indent))
else:
return self.set_response_headers(response)
|
Prepares for the CallBackResolver and handles the response and exceptions
:param request HttpRequest
:rtype: HttpResponse
|
entailment
|
def exec_route_callback(self) -> Response or object:
"""
Executes the resolved end-point callback, or its fallback
:rtype: Response or object
"""
if self.__method.lower() in self.__end_points:
for bound in self.__end_points[self.__method.lower()]:
route = list(bound)[0]
expected_params = self.get_url_params(route)
actual_params = self.get_url_params(self.get_end_point_uri())
if self.request_matches_route(self.get_end_point_uri(), route):
self.app.log.info("> {0} {1}".format(self.__method, self.__uri))
if self.authenticate(route, actual_params):
self.app.log.debug(
"%s(%d) %s" % ("body ", len(self.__request.body), self.__request.body.decode('utf-8'))
)
pattern_params = self.get_callback_pattern(expected_params, actual_params)
self.app.request_handle_time = (
lambda d: int((d.days * 24 * 60 * 60 * 1000) + (d.seconds * 1000) + (d.microseconds / 1000))
)(datetime.now() - self.__request_start)
return bound[route](self.__request, self.app, **pattern_params)
else:
raise AuthException("Authentication failed.")
if self.__method == "OPTIONS":
self.app.log.info("Route matched: {0} {1}".format(self.__method, self.__uri))
return self.default_route_options()
if self.__route == '' and self.__uri == '':
return self.welcome_page()
else:
return self.no_route_found(self.__request)
|
Executes the resolved end-point callback, or its fallback
:rtype: Response or object
|
entailment
|
def request_matches_route(self, actual_route: str, expected_route: str):
"""
Determines whether a route matches the actual requested route or not
:param actual_route str
:param expected_route
:rtype: Boolean
"""
expected_params = self.get_url_params(expected_route)
actual_params = self.get_url_params(actual_route)
i = 0
if len(expected_params) == len(actual_params):
for param in actual_params:
if expected_params[i][0] != "{":
if param != expected_params[i]:
return False
i += 1
else:
return False
return True
|
Determines whether a route matches the actual requested route or not
:param actual_route str
:param expected_route
:rtype: Boolean
|
entailment
|
def authenticate(self, bound_route, actual_params) -> bool:
"""
Runs the pre-defined authenticaton service
:param bound_route str route matched
:param actual_params dict actual url parameters
:rtype: bool
"""
if self.__auth_service is not None:
auth_route = "{0}_{1}{2}".format(self.__method, self.__route, bound_route)
auth_data = self.__auth_service.authenticate(self.__request, auth_route, actual_params)
if auth_data is True:
self.app.auth_data = self.__auth_service.auth_data
else:
return False
return True
|
Runs the pre-defined authenticaton service
:param bound_route str route matched
:param actual_params dict actual url parameters
:rtype: bool
|
entailment
|
def get_callback_pattern(expected_params, actual_params):
"""
Assembles a dictionary whith the parameters schema defined for this route
:param expected_params dict parameters schema defined for this route
:param actual_params dict actual url parameters
:rtype: dict
"""
pattern = dict()
key = 0
for exp_param in expected_params:
if exp_param[0] == '{' and exp_param[-1:] == '}':
pattern[exp_param[1:-1]] = actual_params[key]
key = key + 1
return pattern
|
Assembles a dictionary whith the parameters schema defined for this route
:param expected_params dict parameters schema defined for this route
:param actual_params dict actual url parameters
:rtype: dict
|
entailment
|
def get_url_params(end_point: str) -> list:
"""
Gets route parameters as dictionary
:param end_point str target route
:rtype: list
"""
var_params = end_point.split('/')
if len(var_params) == 1 and var_params[0] == '':
return []
elif len(var_params) == 1 and var_params[0] != '':
return [var_params[0]]
else:
params = list()
for param in var_params:
if len(param) > 0:
params.append(param)
return params
|
Gets route parameters as dictionary
:param end_point str target route
:rtype: list
|
entailment
|
def set_end_point_uri(self) -> bool:
"""
Extracts the route from the accessed URL and sets it to __end_point_uri
:rtype: bool
"""
expected_parts = self.__route.split("/")
actual_parts = self.__uri.split("/")
i = 0
for part in expected_parts:
if part != actual_parts[i]:
return False
i = i + 1
uri_prefix = len(self.__route)
self.__end_point_uri = self.__uri[uri_prefix:]
return True
|
Extracts the route from the accessed URL and sets it to __end_point_uri
:rtype: bool
|
entailment
|
def no_route_found(self, request):
"""
Default callback for route not found
:param request HttpRequest
:rtype: Response
"""
response_obj = OrderedDict()
response_obj["status"] = False
response_obj["exceptions"] = {
"message": "No route found for {0} {1}".format(self.__method, self.__uri),
}
response_obj["request"] = {
"method": self.__method,
"path_info": self.__uri,
"content": request.body.decode("utf-8")
}
response_obj["message"] = "We are sorry, but something went terribly wrong."
return Response(response_obj, content_type="application/json", status=404, charset="utf-8")
|
Default callback for route not found
:param request HttpRequest
:rtype: Response
|
entailment
|
def welcome_page(self):
"""
Defaulf welcome page when the route / is note mapped yet
:rtype: HttpResponse
"""
message = "HTTP/1.1 200 OK RINZLER FRAMEWORK"
return HttpResponse(
"<center><h1>{0}({1})</h1></center>".format(message, self.app.app_name),
content_type="text/html", charset="utf-8"
)
|
Defaulf welcome page when the route / is note mapped yet
:rtype: HttpResponse
|
entailment
|
def default_route_options():
"""
Default callback for OPTIONS request
:rtype: Response
"""
response_obj = OrderedDict()
response_obj["status"] = True
response_obj["data"] = "Ok"
return Response(response_obj, content_type="application/json", charset="utf-8")
|
Default callback for OPTIONS request
:rtype: Response
|
entailment
|
def set_response_headers(self, response: HttpResponse) -> HttpResponse:
"""
Appends default headers to every response returned by the API
:param response HttpResponse
:rtype: HttpResponse
"""
public_name = os.environ.get('SERVER_PUBLIC_NAME')
response_headers = {
'access-control-allow-headers': self.app.allowed_headers,
'access-control-allow-methods': self.app.allowed_methods,
'access-control-allow-origin': self.app.allowed_origins,
'access-control-allow-credentials': True,
'www-authenticate': "Bearer",
'server-public-name': public_name if public_name else "No one",
'user-info': "Rinzler Framework rulez!"
}
response_headers.update(self.app.default_headers)
for key in response_headers:
response[key] = response_headers[key]
status = response.status_code
if status != 404:
self.app.log.info("< {0}".format(status))
return response
|
Appends default headers to every response returned by the API
:param response HttpResponse
:rtype: HttpResponse
|
entailment
|
def get_json_ident(request_headers: dict) -> int:
"""
Defines whether the JSON response will be indented or not
:param request_headers: dict
:return: self
"""
if 'HTTP_USER_AGENT' in request_headers:
indent = 2 if re.match("[Mozilla]{7}", request_headers['HTTP_USER_AGENT']) else 0
else:
indent = 0
return indent
|
Defines whether the JSON response will be indented or not
:param request_headers: dict
:return: self
|
entailment
|
def prop(key, dct_or_obj):
"""
Implementation of prop (get_item) that also supports object attributes
:param key:
:param dct_or_obj:
:return:
"""
# Note that hasattr is a builtin and getattr is a ramda function, hence the different arg position
if isinstance(dict, dct_or_obj):
if has(key, dct_or_obj):
return dct_or_obj[key]
else:
raise Exception("No key %s found for dict %s" % (key, dct_or_obj))
elif isinstance(list, dct_or_obj):
if isint(key):
return dct_or_obj[key]
else:
raise Exception("Key %s not expected for list type: %s" % (key, dct_or_obj))
elif isinstance(object, dct_or_obj):
if hasattr(dct_or_obj, key):
return getattr(key, dct_or_obj)
else:
raise Exception("No key %s found for objects %s" % (key, dct_or_obj))
else:
raise Exception("%s is neither a dict nor objects" % dct_or_obj)
|
Implementation of prop (get_item) that also supports object attributes
:param key:
:param dct_or_obj:
:return:
|
entailment
|
def all_pass_dict(f, dct):
"""
Returns true if all dct values pass f
:param f: binary lambda predicate
:param dct:
:return: True or false
"""
return all(map_with_obj_to_values(
lambda key, value: f(key, value),
dct
))
|
Returns true if all dct values pass f
:param f: binary lambda predicate
:param dct:
:return: True or false
|
entailment
|
def prop_or(default, key, dct_or_obj):
"""
Ramda propOr implementation. This also resolves object attributes, so key
can be a dict prop or an attribute of dct_or_obj
:param default: Value if dct_or_obj doesn't have key_or_prop or the resolved value is null
:param key:
:param dct_or_obj:
:return:
"""
# Note that hasattr is a builtin and getattr is a ramda function, hence the different arg position
if isinstance(dict, dct_or_obj):
value = dct_or_obj[key] if has(key, dct_or_obj) else default
elif isinstance(object, dct_or_obj):
value = getattr(key, dct_or_obj) if hasattr(dct_or_obj, key) else default
else:
value = default
# 0 and False are ok, None defaults
if value == None:
return default
return value
|
Ramda propOr implementation. This also resolves object attributes, so key
can be a dict prop or an attribute of dct_or_obj
:param default: Value if dct_or_obj doesn't have key_or_prop or the resolved value is null
:param key:
:param dct_or_obj:
:return:
|
entailment
|
def prop_eq_or(default, key, value, dct):
"""
Ramda propEq plus propOr implementation
:param default:
:param key:
:param value:
:param dct:
:return:
"""
return dct[key] and dct[key] == value if key in dct else default
|
Ramda propEq plus propOr implementation
:param default:
:param key:
:param value:
:param dct:
:return:
|
entailment
|
def prop_eq_or_in_or(default, key, value, dct):
"""
Ramda propEq/propIn plus propOr
:param default:
:param key:
:param value:
:param dct:
:return:
"""
return has(key, dct) and \
(dct[key] == value if key in dct else (
dct[key] in value if isinstance((list, tuple), value) and not isinstance(str, value)
else default
))
|
Ramda propEq/propIn plus propOr
:param default:
:param key:
:param value:
:param dct:
:return:
|
entailment
|
def item_path_or(default, keys, dict_or_obj):
"""
Optional version of item_path with a default value. keys can be dict keys or object attributes, or a combination
:param default:
:param keys: List of keys or dot-separated string
:param dict_or_obj: A dict or obj
:return:
"""
if not keys:
raise ValueError("Expected at least one key, got {0}".format(keys))
resolved_keys = keys.split('.') if isinstance(str, keys) else keys
current_value = dict_or_obj
for key in resolved_keys:
current_value = prop_or(default, key, default_to({}, current_value))
return current_value
|
Optional version of item_path with a default value. keys can be dict keys or object attributes, or a combination
:param default:
:param keys: List of keys or dot-separated string
:param dict_or_obj: A dict or obj
:return:
|
entailment
|
def item_str_path(keys, dct):
"""
Given a string of path segments separated by ., splits them into an array. Int strings are converted
to numbers to serve as an array index
:param keys: e.g. 'foo.bar.1.goo'
:param dct: e.g. dict(foo=dict(bar=[dict(goo='a'), dict(goo='b')])
:return: The resolved value or an error. E.g. for above the result would be b
"""
return item_path(map(lambda segment: int(segment) if isint(segment) else segment, keys.split('.')), dct)
|
Given a string of path segments separated by ., splits them into an array. Int strings are converted
to numbers to serve as an array index
:param keys: e.g. 'foo.bar.1.goo'
:param dct: e.g. dict(foo=dict(bar=[dict(goo='a'), dict(goo='b')])
:return: The resolved value or an error. E.g. for above the result would be b
|
entailment
|
def item_str_path_or(default, keys, dct):
"""
Given a string of path segments separated by ., splits them into an array. Int strings are converted
to numbers to serve as an array index
:param default: Value if any part yields None or undefined
:param keys: e.g. 'foo.bar.1.goo'
:param dct: e.g. dict(foo=dict(bar=[dict(goo='a'), dict(goo='b')])
:return: The resolved value or an error. E.g. for above the result would be b
"""
return item_path_or(default, map(lambda segment: int(segment) if isint(segment) else segment, keys.split('.')), dct)
|
Given a string of path segments separated by ., splits them into an array. Int strings are converted
to numbers to serve as an array index
:param default: Value if any part yields None or undefined
:param keys: e.g. 'foo.bar.1.goo'
:param dct: e.g. dict(foo=dict(bar=[dict(goo='a'), dict(goo='b')])
:return: The resolved value or an error. E.g. for above the result would be b
|
entailment
|
def has(prop, object_or_dct):
"""
Implementation of ramda has
:param prop:
:param object_or_dct:
:return:
"""
return prop in object_or_dct if isinstance(dict, object_or_dct) else hasattr(object_or_dct, prop)
|
Implementation of ramda has
:param prop:
:param object_or_dct:
:return:
|
entailment
|
def omit_deep(omit_props, dct):
"""
Implementation of omit that recurses. This tests the same keys at every level of dict and in lists
:param omit_props:
:param dct:
:return:
"""
omit_partial = omit_deep(omit_props)
if isinstance(dict, dct):
# Filter out keys and then recurse on each value that wasn't filtered out
return map_dict(omit_partial, compact_dict(omit(omit_props, dct)))
if isinstance((list, tuple), dct):
# run omit_deep on each value
return map(omit_partial, dct)
# scalar
return dct
|
Implementation of omit that recurses. This tests the same keys at every level of dict and in lists
:param omit_props:
:param dct:
:return:
|
entailment
|
def pick_deep(pick_dct, dct):
"""
Implementation of pick that recurses. This tests the same keys at every level of dict and in lists
:param pick_dct: Deep dict matching some portion of dct.
:param dct: Dct to filter. Any key matching pick_dct pass through. It doesn't matter what the pick_dct value
is as long as the key exists. Arrays also pass through if the have matching values in pick_dct
:return:
"""
if isinstance(dict, dct):
# Filter out keys and then recurse on each value that wasn't filtered out
return map_with_obj(
lambda k, v: pick_deep(prop(k, pick_dct), v),
pick(keys(pick_dct), dct)
)
if isinstance((list, tuple), dct):
# run pick_deep on each value
return map(
lambda tup: pick_deep(*tup),
list(zip(pick_dct or [], dct))
)
# scalar
return dct
|
Implementation of pick that recurses. This tests the same keys at every level of dict and in lists
:param pick_dct: Deep dict matching some portion of dct.
:param dct: Dct to filter. Any key matching pick_dct pass through. It doesn't matter what the pick_dct value
is as long as the key exists. Arrays also pass through if the have matching values in pick_dct
:return:
|
entailment
|
def map_with_obj_deep(f, dct):
"""
Implementation of map that recurses. This tests the same keys at every level of dict and in lists
:param f: 2-ary function expecting a key and value and returns a modified value
:param dct: Dict for deep processing
:return: Modified dct with matching props mapped
"""
return _map_deep(lambda k, v: [k, f(k, v)], dct)
|
Implementation of map that recurses. This tests the same keys at every level of dict and in lists
:param f: 2-ary function expecting a key and value and returns a modified value
:param dct: Dict for deep processing
:return: Modified dct with matching props mapped
|
entailment
|
def map_keys_deep(f, dct):
"""
Implementation of map that recurses. This tests the same keys at every level of dict and in lists
:param f: 2-ary function expecting a key and value and returns a modified key
:param dct: Dict for deep processing
:return: Modified dct with matching props mapped
"""
return _map_deep(lambda k, v: [f(k, v), v], dct)
|
Implementation of map that recurses. This tests the same keys at every level of dict and in lists
:param f: 2-ary function expecting a key and value and returns a modified key
:param dct: Dict for deep processing
:return: Modified dct with matching props mapped
|
entailment
|
def _map_deep(f, dct):
"""
Used by map_deep and map_keys_deep
:param map_props:
:param f: Expects a key and value and returns a pair
:param dct:
:return:
"""
if isinstance(dict, dct):
return map_key_values(lambda k, v: f(k, _map_deep(f, v)), dct)
elif isinstance((list, tuple), dct):
# Call each value with the index as the key. Since f returns a key value discard the key that it returns
# Even if this is called with map_keys_deep we can't manipulate index values here
return map(lambda iv: f(iv[0], _map_deep(f, iv[1]))[1], enumerate(dct))
# scalar
return dct
|
Used by map_deep and map_keys_deep
:param map_props:
:param f: Expects a key and value and returns a pair
:param dct:
:return:
|
entailment
|
def dict_matches_params_deep(params_dct, dct):
"""
Filters deeply by comparing dct to filter_dct's value at each depth. Whenever a mismatch occurs the whole
thing returns false
:param params_dct: dict matching any portion of dct. E.g. filter_dct = {foo: {bar: 1}} would allow
{foo: {bar: 1, car: 2}} to pass, {foo: {bar: 2}} would fail, {goo: ...} would fail
:param dct: Dict for deep processing
:return: True if all pass else false
"""
def recurse_if_param_exists(params, key, value):
"""
If a param[key] exists, recurse. Otherwise return True since there is no param to contest value
:param params:
:param key:
:param value:
:return:
"""
return dict_matches_params_deep(
prop(key, params),
value
) if has(key, params) else True
def recurse_if_array_param_exists(params, index, value):
"""
If a param[key] exists, recurse. Otherwise return True since there is no param to contest value
:param params:
:param index:
:param value:
:return:
"""
return dict_matches_params_deep(
params[index],
value
) if isinstance((list, tuple), params_dct) and index < length(params_dct) else True
if isinstance(dict, dct):
# Filter out keys and then recurse on each value
return all_pass_dict(
# Recurse on each value if there is a corresponding filter_dct[key]. If not we pass
lambda key, value: recurse_if_param_exists(params_dct, key, value),
# We shallow merge, giving dct priority with (hopefully) unmatchable values
merge(map_with_obj(lambda k, v: 1 / (-e * pi), params_dct), dct)
)
if isinstance((list, tuple), dct):
if isinstance((list, tuple), params_dct) and length(dct) < length(params_dct):
# if there are more param items then dct items fail
return False
# run map_deep on each value
return all(map(
lambda ivalue: recurse_if_array_param_exists(params_dct, *ivalue),
enumerate(dct)
))
# scalar. Not that anything not truthy, False, None, 0, are considered equal
return params_dct == dct
|
Filters deeply by comparing dct to filter_dct's value at each depth. Whenever a mismatch occurs the whole
thing returns false
:param params_dct: dict matching any portion of dct. E.g. filter_dct = {foo: {bar: 1}} would allow
{foo: {bar: 1, car: 2}} to pass, {foo: {bar: 2}} would fail, {goo: ...} would fail
:param dct: Dict for deep processing
:return: True if all pass else false
|
entailment
|
def join(strin, items):
"""
Ramda implementation of join
:param strin:
:param items:
:return:
"""
return strin.join(map(lambda item: str(item), items))
|
Ramda implementation of join
:param strin:
:param items:
:return:
|
entailment
|
def map_with_obj(f, dct):
"""
Implementation of Ramda's mapObjIndexed without the final argument.
This returns the original key with the mapped value. Use map_key_values to modify the keys too
:param f: Called with a key and value
:param dct:
:return {dict}: Keyed by the original key, valued by the mapped value
"""
f_dict = {}
for k, v in dct.items():
f_dict[k] = f(k, v)
return f_dict
|
Implementation of Ramda's mapObjIndexed without the final argument.
This returns the original key with the mapped value. Use map_key_values to modify the keys too
:param f: Called with a key and value
:param dct:
:return {dict}: Keyed by the original key, valued by the mapped value
|
entailment
|
def map_keys(f, dct):
"""
Calls f with each key of dct, possibly returning a modified key. Values are unchanged
:param f: Called with each key and returns the same key or a modified key
:param dct:
:return: A dct with keys possibly modifed but values unchanged
"""
f_dict = {}
for k, v in dct.items():
f_dict[f(k)] = v
return f_dict
|
Calls f with each key of dct, possibly returning a modified key. Values are unchanged
:param f: Called with each key and returns the same key or a modified key
:param dct:
:return: A dct with keys possibly modifed but values unchanged
|
entailment
|
def map_keys_with_obj(f, dct):
"""
Calls f with each key and value of dct, possibly returning a modified key. Values are unchanged
:param f: Called with each key and value and returns the same key or a modified key
:param dct:
:return: A dct with keys possibly modifed but values unchanged
"""
f_dict = {}
for k, v in dct.items():
f_dict[f(k, v)] = v
return f_dict
|
Calls f with each key and value of dct, possibly returning a modified key. Values are unchanged
:param f: Called with each key and value and returns the same key or a modified key
:param dct:
:return: A dct with keys possibly modifed but values unchanged
|
entailment
|
def merge_deep(dct1, dct2, merger=None):
"""
Deep merge by this spec below
:param dct1:
:param dct2:
:param merger Optional merger
:return:
"""
my_merger = merger or Merger(
# pass in a list of tuples,with the
# strategies you are looking to apply
# to each type.
[
(list, ["append"]),
(dict, ["merge"])
],
# next, choose the fallback strategies,
# applied to all other types:
["override"],
# finally, choose the strategies in
# the case where the types conflict:
["override"]
)
return my_merger.merge(dct1, dct2)
|
Deep merge by this spec below
:param dct1:
:param dct2:
:param merger Optional merger
:return:
|
entailment
|
def merge_all(dcts):
"""
Shallow merge all the dcts
:param dcts:
:return:
"""
return reduce(
lambda accum, dct: merge(accum, dct),
dict(),
dcts
)
|
Shallow merge all the dcts
:param dcts:
:return:
|
entailment
|
def from_pairs_to_array_values(pairs):
"""
Like from pairs but combines duplicate key values into arrays
:param pairs:
:return:
"""
result = {}
for pair in pairs:
result[pair[0]] = concat(prop_or([], pair[0], result), [pair[1]])
return result
|
Like from pairs but combines duplicate key values into arrays
:param pairs:
:return:
|
entailment
|
def map_prop_value_as_index(prp, lst):
"""
Returns the given prop of each item in the list
:param prp:
:param lst:
:return:
"""
return from_pairs(map(lambda item: (prop(prp, item), item), lst))
|
Returns the given prop of each item in the list
:param prp:
:param lst:
:return:
|
entailment
|
def key_string_to_lens_path(key_string):
"""
Converts a key string like 'foo.bar.0.wopper' to ['foo', 'bar', 0, 'wopper']
:param {String} keyString The dot-separated key string
:return {[String]} The lens array containing string or integers
"""
return map(
if_else(
isinstance(int),
# convert to int
lambda s: int(s),
# Leave the string alone
identity
),
key_string.split('.')
)
|
Converts a key string like 'foo.bar.0.wopper' to ['foo', 'bar', 0, 'wopper']
:param {String} keyString The dot-separated key string
:return {[String]} The lens array containing string or integers
|
entailment
|
def fake_lens_path_view(lens_path, obj):
"""
Simulates R.view with a lens_path since we don't have lens functions
:param lens_path: Array of string paths
:param obj: Object containing the given path
:return: The value at the path or None
"""
segment = head(lens_path)
return if_else(
both(lambda _: identity(segment), has(segment)),
# Recurse on the rest of the path
compose(fake_lens_path_view(tail(lens_path)), getitem(segment)),
# Give up
lambda _: None
)(obj)
|
Simulates R.view with a lens_path since we don't have lens functions
:param lens_path: Array of string paths
:param obj: Object containing the given path
:return: The value at the path or None
|
entailment
|
def fake_lens_path_set(lens_path, value, obj):
"""
Simulates R.set with a lens_path since we don't have lens functions
:param lens_path: Array of string paths
:param value: The value to set at the lens path
:param obj: Object containing the given path
:return: The value at the path or None
"""
segment = head(lens_path)
obj_copy = copy.copy(obj)
def set_array_index(i, v, l):
# Fill the array with None up to the given index and set the index to v
try:
l[i] = v
except IndexError:
for _ in range(i - len(l) + 1):
l.append(None)
l[i] = v
if not (length(lens_path) - 1):
# Done
new_value = value
else:
# Find the value at the path or create a {} or [] at obj[segment]
found_or_created = item_path_or(
if_else(
lambda segment: segment.isnumeric(),
always([]),
always({})
)(head(tail(lens_path))),
segment,
obj
)
# Recurse on the rest of the path
new_value = fake_lens_path_set(tail(lens_path), value, found_or_created)
# Set or replace
if segment.isnumeric():
set_array_index(int(segment), new_value, obj_copy)
else:
obj_copy[segment] = new_value
return obj_copy
|
Simulates R.set with a lens_path since we don't have lens functions
:param lens_path: Array of string paths
:param value: The value to set at the lens path
:param obj: Object containing the given path
:return: The value at the path or None
|
entailment
|
def unflatten_dct(obj):
"""
Undoes the work of flatten_dict
@param {Object} obj 1-D object in the form returned by flattenObj
@returns {Object} The original
:param obj:
:return:
"""
def reduce_func(accum, key_string_and_value):
key_string = key_string_and_value[0]
value = key_string_and_value[1]
item_key_path = key_string_to_lens_path(key_string)
# All but the last segment gives us the item container len
container_key_path = init(item_key_path)
container = unless(
# If the path has any length (not []) and the value is set, don't do anything
both(always(length(container_key_path)), fake_lens_path_view(container_key_path)),
# Else we are at the top level, so use the existing accum or create a [] or {}
# depending on if our item key is a number or not
lambda x: default_to(
if_else(
lambda segment: segment.isnumeric(),
always([]),
always({})
)(head(item_key_path))
)(x)
)(accum)
# Finally set the container at the itemLensPath
return fake_lens_path_set(
item_key_path,
value,
container
)
return compose(
reduce(
reduce_func,
# null initial value
None
),
to_pairs
)(obj)
|
Undoes the work of flatten_dict
@param {Object} obj 1-D object in the form returned by flattenObj
@returns {Object} The original
:param obj:
:return:
|
entailment
|
def ppj(json_data):
"""ppj
:param json_data: dictionary to print
"""
return str(json.dumps(
json_data,
sort_keys=True,
indent=4,
separators=(',', ': ')))
|
ppj
:param json_data: dictionary to print
|
entailment
|
def change_view(self, request, object_id, form_url='', extra_context=None):
"""
Override change view to add extra context enabling moderate tool.
"""
context = {
'has_moderate_tool': True
}
if extra_context:
context.update(extra_context)
return super(AdminModeratorMixin, self).change_view(
request=request,
object_id=object_id,
form_url=form_url,
extra_context=context
)
|
Override change view to add extra context enabling moderate tool.
|
entailment
|
def get_urls(self):
"""
Add aditional moderate url.
"""
from django.conf.urls import url
urls = super(AdminModeratorMixin, self).get_urls()
info = self.model._meta.app_label, self.model._meta.model_name
return [
url(r'^(.+)/moderate/$',
self.admin_site.admin_view(self.moderate_view),
name='%s_%s_moderate' % info),
] + urls
|
Add aditional moderate url.
|
entailment
|
def render(self, indent=0):
"""
Renders a HttpResponse for the ongoing request
:param indent int
:rtype: HttpResponse
"""
self.__indent = indent
return HttpResponse(
str(self), content_type=self.__content_type, charset=self.__charset, **self.__kwargs
)
|
Renders a HttpResponse for the ongoing request
:param indent int
:rtype: HttpResponse
|
entailment
|
def setup_logging(default_path='logging.yaml', env_key='LOG_CFG'):
"""
Setup logging configuration
"""
path = default_path
value = os.getenv(env_key, None)
if value:
path = value
if os.path.exists(path):
with open(path, 'rt') as f:
configs = yaml.safe_load(f.read())
logging.config.dictConfig(configs)
else:
logging.config.dictConfig(config)
|
Setup logging configuration
|
entailment
|
def get(self, route: str(), callback: object()):
"""
Binds a GET route with the given callback
:rtype: object
"""
self.__set_route('get', {route: callback})
return RouteMapping
|
Binds a GET route with the given callback
:rtype: object
|
entailment
|
def post(self, route: str(), callback: object()):
"""
Binds a POST route with the given callback
:rtype: object
"""
self.__set_route('post', {route: callback})
return RouteMapping
|
Binds a POST route with the given callback
:rtype: object
|
entailment
|
def put(self, route: str(), callback: object()):
"""
Binds a PUT route with the given callback
:rtype: object
"""
self.__set_route('put', {route: callback})
return RouteMapping
|
Binds a PUT route with the given callback
:rtype: object
|
entailment
|
def patch(self, route: str(), callback: object()):
"""
Binds a PATCH route with the given callback
:rtype: object
"""
self.__set_route('patch', {route: callback})
return RouteMapping
|
Binds a PATCH route with the given callback
:rtype: object
|
entailment
|
def delete(self, route: str(), callback: object()):
"""
Binds a PUT route with the given callback
:rtype: object
"""
self.__set_route('delete', {route: callback})
return RouteMapping
|
Binds a PUT route with the given callback
:rtype: object
|
entailment
|
def head(self, route: str(), callback: object()):
"""
Binds a HEAD route with the given callback
:rtype: object
"""
self.__set_route('head', {route: callback})
return RouteMapping
|
Binds a HEAD route with the given callback
:rtype: object
|
entailment
|
def options(self, route: str(), callback: object()):
"""
Binds a OPTIONS route with the given callback
:rtype: object
"""
self.__set_route('options', {route: callback})
return RouteMapping
|
Binds a OPTIONS route with the given callback
:rtype: object
|
entailment
|
def __set_route(self, type_route, route):
"""
Sets the given type_route and route to the route mapping
:rtype: object
"""
if type_route in self.__routes:
if not self.verify_route_already_bound(type_route, route):
self.__routes[type_route].append(route)
else:
self.__routes[type_route] = [route]
return RouteMapping
|
Sets the given type_route and route to the route mapping
:rtype: object
|
entailment
|
def operating_system():
"""Return a string identifying the operating system the application
is running on.
:rtype: str
"""
if platform.system() == 'Darwin':
return 'OS X Version %s' % platform.mac_ver()[0]
distribution = ' '.join(platform.linux_distribution()).strip()
os_platform = platform.platform(True, True)
if distribution:
os_platform += ' (%s)' % distribution
return os_platform
|
Return a string identifying the operating system the application
is running on.
:rtype: str
|
entailment
|
def start(self):
"""Daemonize if the process is not already running."""
if self._is_already_running():
LOGGER.error('Is already running')
sys.exit(1)
try:
self._daemonize()
self.controller.start()
except Exception as error:
sys.stderr.write('\nERROR: Startup of %s Failed\n.' %
sys.argv[0].split('/')[-1])
exception_log = self._get_exception_log_path()
if exception_log:
with open(exception_log, 'a') as handle:
timestamp = datetime.datetime.now().isoformat()
handle.write('{:->80}\n'.format(' [START]'))
handle.write('%s Exception [%s]\n' % (sys.argv[0],
timestamp))
handle.write('{:->80}\n'.format(' [INFO]'))
handle.write('Interpreter: %s\n' % sys.executable)
handle.write('CLI arguments: %s\n' % ' '.join(sys.argv))
handle.write('Exception: %s\n' % error)
handle.write('Traceback:\n')
output = traceback.format_exception(*sys.exc_info())
_dev_null = [(handle.write(line),
sys.stdout.write(line)) for line in output]
handle.write('{:->80}\n'.format(' [END]'))
handle.flush()
sys.stderr.write('\nException log: %s\n\n' % exception_log)
sys.exit(1)
|
Daemonize if the process is not already running.
|
entailment
|
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