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mishbahr/djangocms-forms | djangocms_forms/admin.py | FormSubmissionAdmin.get_urls | def get_urls(self):
"""
Add the export view to urls.
"""
urls = super(FormSubmissionAdmin, self).get_urls()
from django.conf.urls import url
def wrap(view):
def wrapper(*args, **kwargs):
return self.admin_site.admin_view(view)(*args, **kwargs)... | python | def get_urls(self):
"""
Add the export view to urls.
"""
urls = super(FormSubmissionAdmin, self).get_urls()
from django.conf.urls import url
def wrap(view):
def wrapper(*args, **kwargs):
return self.admin_site.admin_view(view)(*args, **kwargs)... | [
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mishbahr/djangocms-forms | djangocms_forms/admin.py | FormSubmissionAdmin.export_view | def export_view(self, request, form_url=''):
"""The 'export' admin view for this model."""
info = self.opts.app_label, self.opts.model_name
if not self.has_export_permission(request):
raise PermissionDenied
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"""The 'export' admin view for this model."""
info = self.opts.app_label, self.opts.model_name
if not self.has_export_permission(request):
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mishbahr/djangocms-forms | djangocms_forms/admin.py | FormSubmissionAdmin.render_export_form | def render_export_form(self, request, context, form_url=''):
"""
Render the from submission export form.
"""
context.update({
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"""
Render the from submission export form.
"""
context.update({
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mishbahr/djangocms-forms | djangocms_forms/forms.py | FormDefinitionAdminForm.clean_form_template | def clean_form_template(self):
""" Check if template exists """
form_template = self.cleaned_data.get('form_template', '')
if form_template:
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get_template(form_template)
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""" Check if template exists """
form_template = self.cleaned_data.get('form_template', '')
if form_template:
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get_template(form_template)
except TemplateDoesNotExist:
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nikdon/pyEntropy | pyentrp/entropy.py | _embed | def _embed(x, order=3, delay=1):
"""Time-delay embedding.
Parameters
----------
x : 1d-array, shape (n_times)
Time series
order : int
Embedding dimension (order)
delay : int
Delay.
Returns
-------
embedded : ndarray, shape (n_times - (order - 1) * delay, ord... | python | def _embed(x, order=3, delay=1):
"""Time-delay embedding.
Parameters
----------
x : 1d-array, shape (n_times)
Time series
order : int
Embedding dimension (order)
delay : int
Delay.
Returns
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nikdon/pyEntropy | pyentrp/entropy.py | util_pattern_space | def util_pattern_space(time_series, lag, dim):
"""Create a set of sequences with given lag and dimension
Args:
time_series: Vector or string of the sample data
lag: Lag between beginning of sequences
dim: Dimension (number of patterns)
Returns:
2D array of vectors
"""
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"""Create a set of sequences with given lag and dimension
Args:
time_series: Vector or string of the sample data
lag: Lag between beginning of sequences
dim: Dimension (number of patterns)
Returns:
2D array of vectors
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nikdon/pyEntropy | pyentrp/entropy.py | util_granulate_time_series | def util_granulate_time_series(time_series, scale):
"""Extract coarse-grained time series
Args:
time_series: Time series
scale: Scale factor
Returns:
Vector of coarse-grained time series with given scale factor
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n = len(time_series)
b = int(np.fix(n / scale))
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"""Extract coarse-grained time series
Args:
time_series: Time series
scale: Scale factor
Returns:
Vector of coarse-grained time series with given scale factor
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n = len(time_series)
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nikdon/pyEntropy | pyentrp/entropy.py | shannon_entropy | def shannon_entropy(time_series):
"""Return the Shannon Entropy of the sample data.
Args:
time_series: Vector or string of the sample data
Returns:
The Shannon Entropy as float value
"""
# Check if string
if not isinstance(time_series, str):
time_series = list(time_ser... | python | def shannon_entropy(time_series):
"""Return the Shannon Entropy of the sample data.
Args:
time_series: Vector or string of the sample data
Returns:
The Shannon Entropy as float value
"""
# Check if string
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nikdon/pyEntropy | pyentrp/entropy.py | sample_entropy | def sample_entropy(time_series, sample_length, tolerance = None):
"""Calculates the sample entropy of degree m of a time_series.
This method uses chebychev norm.
It is quite fast for random data, but can be slower is there is
structure in the input time series.
Args:
time_series: numpy arr... | python | def sample_entropy(time_series, sample_length, tolerance = None):
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This method uses chebychev norm.
It is quite fast for random data, but can be slower is there is
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nikdon/pyEntropy | pyentrp/entropy.py | multiscale_entropy | def multiscale_entropy(time_series, sample_length, tolerance = None, maxscale = None):
"""Calculate the Multiscale Entropy of the given time series considering
different time-scales of the time series.
Args:
time_series: Time series for analysis
sample_length: Bandwidth or group of points
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different time-scales of the time series.
Args:
time_series: Time series for analysis
sample_length: Bandwidth or group of points
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nikdon/pyEntropy | pyentrp/entropy.py | permutation_entropy | def permutation_entropy(time_series, order=3, delay=1, normalize=False):
"""Permutation Entropy.
Parameters
----------
time_series : list or np.array
Time series
order : int
Order of permutation entropy
delay : int
Time delay
normalize : bool
If True, divide ... | python | def permutation_entropy(time_series, order=3, delay=1, normalize=False):
"""Permutation Entropy.
Parameters
----------
time_series : list or np.array
Time series
order : int
Order of permutation entropy
delay : int
Time delay
normalize : bool
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nikdon/pyEntropy | pyentrp/entropy.py | multiscale_permutation_entropy | def multiscale_permutation_entropy(time_series, m, delay, scale):
"""Calculate the Multiscale Permutation Entropy
Args:
time_series: Time series for analysis
m: Order of permutation entropy
delay: Time delay
scale: Scale factor
Returns:
Vector containing Multiscale ... | python | def multiscale_permutation_entropy(time_series, m, delay, scale):
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Args:
time_series: Time series for analysis
m: Order of permutation entropy
delay: Time delay
scale: Scale factor
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nikdon/pyEntropy | pyentrp/entropy.py | composite_multiscale_entropy | def composite_multiscale_entropy(time_series, sample_length, scale, tolerance=None):
"""Calculate the Composite Multiscale Entropy of the given time series.
Args:
time_series: Time series for analysis
sample_length: Number of sequential points of the time series
scale: Scale factor
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Args:
time_series: Time series for analysis
sample_length: Number of sequential points of the time series
scale: Scale factor
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kyan001/ping3 | ping3.py | ones_comp_sum16 | def ones_comp_sum16(num1: int, num2: int) -> int:
"""Calculates the 1's complement sum for 16-bit numbers.
Args:
num1: 16-bit number.
num2: 16-bit number.
Returns:
The calculated result.
"""
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result = num1 + num2
return result if result < carry else ... | python | def ones_comp_sum16(num1: int, num2: int) -> int:
"""Calculates the 1's complement sum for 16-bit numbers.
Args:
num1: 16-bit number.
num2: 16-bit number.
Returns:
The calculated result.
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kyan001/ping3 | ping3.py | checksum | def checksum(source: bytes) -> int:
"""Calculates the checksum of the input bytes.
RFC1071: https://tools.ietf.org/html/rfc1071
RFC792: https://tools.ietf.org/html/rfc792
Args:
source: The input to be calculated.
Returns:
Calculated checksum.
"""
if len(source) % 2: # if ... | python | def checksum(source: bytes) -> int:
"""Calculates the checksum of the input bytes.
RFC1071: https://tools.ietf.org/html/rfc1071
RFC792: https://tools.ietf.org/html/rfc792
Args:
source: The input to be calculated.
Returns:
Calculated checksum.
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kyan001/ping3 | ping3.py | send_one_ping | def send_one_ping(sock: socket, dest_addr: str, icmp_id: int, seq: int, size: int):
"""Sends one ping to the given destination.
ICMP Header (bits): type (8), code (8), checksum (16), id (16), sequence (16)
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ICMP Wikipedia: https://en.wikipedia.org/wiki/Internet_Control_... | python | def send_one_ping(sock: socket, dest_addr: str, icmp_id: int, seq: int, size: int):
"""Sends one ping to the given destination.
ICMP Header (bits): type (8), code (8), checksum (16), id (16), sequence (16)
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kyan001/ping3 | ping3.py | receive_one_ping | def receive_one_ping(sock: socket, icmp_id: int, seq: int, timeout: int) -> float or None:
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kyan001/ping3 | ping3.py | ping | def ping(dest_addr: str, timeout: int = 4, unit: str = "s", src_addr: str = None, ttl: int = 64, seq: int = 0, size: int = 56) -> float or None:
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kyan001/ping3 | ping3.py | verbose_ping | def verbose_ping(dest_addr: str, count: int = 4, *args, **kwargs):
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barrust/pyspellchecker | spellchecker/spellchecker.py | SpellChecker.distance | def distance(self, val):
""" set the distance parameter """
tmp = 2
try:
int(val)
if val > 0 and val <= 2:
tmp = val
except (ValueError, TypeError):
pass
self._distance = tmp | python | def distance(self, val):
""" set the distance parameter """
tmp = 2
try:
int(val)
if val > 0 and val <= 2:
tmp = val
except (ValueError, TypeError):
pass
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Args:
filepath (str): The filepath to the exported dictionary
encoding (str): The encoding of the resulting output
gzipped (bool):... | python | def export(self, filepath, encoding="utf-8", gzipped=True):
""" Export the word frequency list for import in the future
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filepath (str): The filepath to the exported dictionary
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word (str): The word for which the word probability is \
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barrust/pyspellchecker | spellchecker/spellchecker.py | SpellChecker.correction | def correction(self, word):
""" The most probable correct spelling for the word
Args:
word (str): The word to correct
Returns:
str: The most likely candidate """
return max(self.candidates(word), key=self.word_probability) | python | def correction(self, word):
""" The most probable correct spelling for the word
Args:
word (str): The word to correct
Returns:
str: The most likely candidate """
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Args:
word (str): The word for which to calculate candidate spellings
Returns:
set: The set of ... | python | def candidates(self, word):
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Args:
words (list): List of words to determine which are in the \
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Returns:
set: The set of those words from the input that are in the \
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barrust/pyspellchecker | spellchecker/spellchecker.py | SpellChecker.edit_distance_1 | def edit_distance_1(self, word):
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word (str): The word for which to calculate the edit distance
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word (str): The word for which to calculate the edit distance
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words (list): The words for which to calculate the edit distance
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.pop | def pop(self, key, default=None):
""" Remove the key and return the associated value or default if not
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Args:
key (str): The key to remove
default (obj): The value to return if key is not present """
return self._dictionary.pop(key.lower(), d... | python | def pop(self, key, default=None):
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key (str): The key to remove
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.items | def items(self):
""" Iterator over the words in the dictionary
Yields:
str: The next word in the dictionary
int: The number of instances in the dictionary
Note:
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for word in self._dictionary.ke... | python | def items(self):
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str: The next word in the dictionary
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.load_dictionary | def load_dictionary(self, filename, encoding="utf-8"):
""" Load in a pre-built word frequency list
Args:
filename (str): The filepath to the json (optionally gzipped) \
file to be loaded
encoding (str): The encoding of the dictionary """
with ... | python | def load_dictionary(self, filename, encoding="utf-8"):
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filename (str): The filepath to the json (optionally gzipped) \
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encoding (str): The encoding of the dictionary """
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.load_text_file | def load_text_file(self, filename, encoding="utf-8", tokenizer=None):
""" Load in a text file from which to generate a word frequency list
Args:
filename (str): The filepath to the text file to be loaded
encoding (str): The encoding of the text file
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filename (str): The filepath to the text file to be loaded
encoding (str): The encoding of the text file
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.load_text | def load_text(self, text, tokenizer=None):
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Args:
text (str): The text to be loaded
tokenizer (function): The function to use to tokenize a string
"""
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""" Load text from which to generate a word frequency list
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.load_words | def load_words(self, words):
""" Load a list of words from which to generate a word frequency list
Args:
words (list): The list of words to be loaded """
self._dictionary.update([word.lower() for word in words])
self._update_dictionary() | python | def load_words(self, words):
""" Load a list of words from which to generate a word frequency list
Args:
words (list): The list of words to be loaded """
self._dictionary.update([word.lower() for word in words])
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.remove_words | def remove_words(self, words):
""" Remove a list of words from the word frequency list
Args:
words (list): The list of words to remove """
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self._dictionary.pop(word.lower())
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Args:
words (list): The list of words to remove """
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.remove | def remove(self, word):
""" Remove a word from the word frequency list
Args:
word (str): The word to remove """
self._dictionary.pop(word.lower())
self._update_dictionary() | python | def remove(self, word):
""" Remove a word from the word frequency list
Args:
word (str): The word to remove """
self._dictionary.pop(word.lower())
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency.remove_by_threshold | def remove_by_threshold(self, threshold=5):
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Args:
threshold (int): The threshold at which a word is to be \
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keys = [x for x in self._dictionary.keys()]
for key in keys:
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""" Remove all words at, or below, the provided threshold
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threshold (int): The threshold at which a word is to be \
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keys = [x for x in self._dictionary.keys()]
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barrust/pyspellchecker | spellchecker/spellchecker.py | WordFrequency._update_dictionary | def _update_dictionary(self):
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self._total_words = sum(self._dictionary.values())
self._unique_words = len(self._dictionary.keys())
self._letters = set()
for key in self._dictionary:
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""" Update the word frequency object """
self._total_words = sum(self._dictionary.values())
self._unique_words = len(self._dictionary.keys())
self._letters = set()
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Args:
filename (str): The filename to open
encoding (str): The file encoding to use
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barrust/pyspellchecker | spellchecker/utils.py | write_file | def write_file(filepath, encoding, gzipped, data):
""" Write the data to file either as a gzip file or text based on the
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Args:
filepath (str): The filename to open
encoding (str): The file encoding to use
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merantix/picasso | picasso/examples/keras/model.py | KerasMNISTModel.preprocess | def preprocess(self, raw_inputs):
"""Convert images into the format required by our model.
Our model requires that inputs be grayscale (mode 'L'), be resized to
`MNIST_DIM`, and be represented as float32 numpy arrays in range
[0, 1].
Args:
raw_inputs (list of Images... | python | def preprocess(self, raw_inputs):
"""Convert images into the format required by our model.
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merantix/picasso | picasso/interfaces/rest.py | initialize_new_session | def initialize_new_session():
"""Check session and initialize if necessary
Before every request, check the user session. If no session exists, add
one and provide temporary locations for images
"""
if 'image_uid_counter' in session and 'image_list' in session:
logger.debug('images are alr... | python | def initialize_new_session():
"""Check session and initialize if necessary
Before every request, check the user session. If no session exists, add
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merantix/picasso | picasso/interfaces/rest.py | images | def images():
"""Upload images via REST interface
Check if file upload was successful and sanatize user input.
TODO: return file URL instead of filename
"""
if request.method == 'POST':
file_upload = request.files['file']
if file_upload:
image = dict()
imag... | python | def images():
"""Upload images via REST interface
Check if file upload was successful and sanatize user input.
TODO: return file URL instead of filename
"""
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merantix/picasso | picasso/interfaces/rest.py | visualizers | def visualizers():
"""Get a list of available visualizers
Responses with a JSON list of available visualizers
"""
list_of_visualizers = []
for visualizer in get_visualizations():
list_of_visualizers.append({'name': visualizer})
return jsonify(visualizers=list_of_visualizers) | python | def visualizers():
"""Get a list of available visualizers
Responses with a JSON list of available visualizers
"""
list_of_visualizers = []
for visualizer in get_visualizations():
list_of_visualizers.append({'name': visualizer})
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merantix/picasso | picasso/interfaces/rest.py | visualize | def visualize():
"""Trigger a visualization via the REST API
Takes a single image and generates the visualization data, returning the
output exactly as given by the target visualization.
"""
session['settings'] = {}
image_uid = request.args.get('image')
vis_name = request.args.get('visual... | python | def visualize():
"""Trigger a visualization via the REST API
Takes a single image and generates the visualization data, returning the
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session['settings'] = {}
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merantix/picasso | picasso/interfaces/rest.py | reset | def reset():
"""Delete the session and clear temporary directories
"""
shutil.rmtree(session['img_input_dir'])
shutil.rmtree(session['img_output_dir'])
session.clear()
return jsonify(ok='true') | python | def reset():
"""Delete the session and clear temporary directories
"""
shutil.rmtree(session['img_input_dir'])
shutil.rmtree(session['img_output_dir'])
session.clear()
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merantix/picasso | picasso/visualizations/base.py | BaseVisualization.update_settings | def update_settings(self, settings):
"""Update the settings
If a derived class has an ALLOWED_SETTINGS dict, we check here that
incoming settings from the web app are allowed, and set the child
properties as appropriate.
"""
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"""Update the settings
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merantix/picasso | picasso/examples/keras-vgg16/model.py | KerasVGG16Model.preprocess | def preprocess(self, raw_inputs):
"""
Args:
raw_inputs (list of Images): a list of PIL Image objects
Returns:
array (float32): num images * height * width * num channels
"""
image_arrays = []
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"""
Args:
raw_inputs (list of Images): a list of PIL Image objects
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array (float32): num images * height * width * num channels
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merantix/picasso | picasso/models/keras.py | KerasModel.load | def load(self, data_dir):
"""Load graph and weight data.
Args:
data_dir (:obj:`str`): location of Keras checkpoint (`.hdf5`) files
and model (in `.json`) structure. The default behavior
is to take the latest of each, by OS timestamp.
"""
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"""Load graph and weight data.
Args:
data_dir (:obj:`str`): location of Keras checkpoint (`.hdf5`) files
and model (in `.json`) structure. The default behavior
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merantix/picasso | picasso/models/tensorflow.py | TFModel.load | def load(self, data_dir, tf_input_var=None, tf_predict_var=None):
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merantix/picasso | picasso/models/base.py | load_model | def load_model(model_cls_path, model_cls_name, model_load_args):
"""Get an instance of the described model.
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model_cls_path: Path to the module in which the model class
is defined.
model_cls_name: Name of the model class.
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"""Get an instance of the described model.
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merantix/picasso | picasso/models/base.py | BaseModel.decode_prob | def decode_prob(self, class_probabilities):
"""Given predicted class probabilites for a set of examples, annotate
each logit with a class name.
By default, we name each class using its index in the logits array.
Args:
class_probabilities (array): Class probabilities as outp... | python | def decode_prob(self, class_probabilities):
"""Given predicted class probabilites for a set of examples, annotate
each logit with a class name.
By default, we name each class using its index in the logits array.
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merantix/picasso | picasso/utils.py | _get_visualization_classes | def _get_visualization_classes():
"""Import visualizations classes dynamically
"""
visualization_attr = vars(import_module('picasso.visualizations'))
visualization_submodules = [
visualization_attr[x]
for x in visualization_attr
if isinstance(visualization_attr[x], ModuleType)]
... | python | def _get_visualization_classes():
"""Import visualizations classes dynamically
"""
visualization_attr = vars(import_module('picasso.visualizations'))
visualization_submodules = [
visualization_attr[x]
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merantix/picasso | picasso/utils.py | get_model | def get_model():
"""Get the NN model that's being analyzed from the request context. Put
the model in the request context if it is not yet there.
Returns:
instance of :class:`.models.model.Model` or derived
class
"""
if not hasattr(g, 'model'):
g.model = load_model(current_... | python | def get_model():
"""Get the NN model that's being analyzed from the request context. Put
the model in the request context if it is not yet there.
Returns:
instance of :class:`.models.model.Model` or derived
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"""
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merantix/picasso | picasso/utils.py | get_visualizations | def get_visualizations():
"""Get the available visualizations from the request context. Put the
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Returns:
:obj:`list` of instances of :class:`.BaseVisualization` or
derived class
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"""Get the available visualizations from the request context. Put the
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merantix/picasso | picasso/utils.py | get_app_state | def get_app_state():
"""Get current status of application in context
Returns:
:obj:`dict` of application status
"""
if not hasattr(g, 'app_state'):
model = get_model()
g.app_state = {
'app_title': APP_TITLE,
'model_name': type(model).__name__,
... | python | def get_app_state():
"""Get current status of application in context
Returns:
:obj:`dict` of application status
"""
if not hasattr(g, 'app_state'):
model = get_model()
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arraylabs/pymyq | pymyq/api.py | login | async def login(
username: str, password: str, brand: str,
websession: ClientSession = None) -> API:
"""Log in to the API."""
api = API(brand, websession)
await api.authenticate(username, password)
return api | python | async def login(
username: str, password: str, brand: str,
websession: ClientSession = None) -> API:
"""Log in to the API."""
api = API(brand, websession)
await api.authenticate(username, password)
return api | [
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arraylabs/pymyq | pymyq/api.py | API._create_websession | def _create_websession(self):
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arraylabs/pymyq | pymyq/api.py | API.close_websession | async def close_websession(self):
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# We do not close the web session if it was provided.
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# Need to se... | python | async def close_websession(self):
"""Close web session if not already closed and created by us."""
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arraylabs/pymyq | pymyq/api.py | API.authenticate | async def authenticate(self, username: str, password: str) -> None:
"""Authenticate against the API."""
self._credentials = {
'username': username,
'password': password,
}
await self._get_security_token() | python | async def authenticate(self, username: str, password: str) -> None:
"""Authenticate against the API."""
self._credentials = {
'username': username,
'password': password,
}
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arraylabs/pymyq | pymyq/api.py | API._get_security_token | async def _get_security_token(self) -> None:
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arraylabs/pymyq | pymyq/api.py | API.get_devices | async def get_devices(self, covers_only: bool = True) -> list:
"""Get a list of all devices associated with the account."""
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# print(json.dump... | python | async def get_devices(self, covers_only: bool = True) -> list:
"""Get a list of all devices associated with the account."""
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arraylabs/pymyq | example.py | main | async def main() -> None:
"""Create the aiohttp session and run the example."""
loglevels = dict((logging.getLevelName(level), level)
for level in [10, 20, 30, 40, 50])
logging.basicConfig(
level=loglevels[LOGLEVEL],
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"""Create the aiohttp session and run the example."""
loglevels = dict((logging.getLevelName(level), level)
for level in [10, 20, 30, 40, 50])
logging.basicConfig(
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arraylabs/pymyq | pymyq/device.py | MyQDevice.name | def name(self) -> str:
"""Return the device name."""
return next(
attr['Value'] for attr in self._device_json.get('Attributes', [])
if attr.get('AttributeDisplayName') == 'desc') | python | def name(self) -> str:
"""Return the device name."""
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arraylabs/pymyq | pymyq/device.py | MyQDevice.available | def available(self) -> bool:
"""Return if device is online or not."""
# Both ability to retrieve state from MyQ cloud AND device itself has
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is_available = self.api.online and \
next(
attr['Value'] for attr in
self._device_json.g... | python | def available(self) -> bool:
"""Return if device is online or not."""
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arraylabs/pymyq | pymyq/device.py | MyQDevice.open_allowed | def open_allowed(self) -> bool:
"""Door can be opened unattended."""
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arraylabs/pymyq | pymyq/device.py | MyQDevice.close_allowed | def close_allowed(self) -> bool:
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arraylabs/pymyq | pymyq/device.py | MyQDevice.state | def state(self) -> str:
"""Return the current state of the device (if it exists)."""
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next(
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arraylabs/pymyq | pymyq/device.py | MyQDevice._update_state | def _update_state(self, value: str) -> None:
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if attribute is not None:
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arraylabs/pymyq | pymyq/device.py | MyQDevice._coerce_state_from_string | def _coerce_state_from_string(value: Union[int, str]) -> str:
"""Return a proper state from a string input."""
try:
return STATE_MAP[int(value)]
except KeyError:
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arraylabs/pymyq | pymyq/device.py | MyQDevice._set_state | async def _set_state(self, state: int) -> bool:
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arraylabs/pymyq | pymyq/device.py | MyQDevice.close | async def close(self) -> bool:
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return False
# Do not allow update of this device's state for 10 seconds.
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arraylabs/pymyq | pymyq/device.py | MyQDevice.open | async def open(self) -> bool:
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sporestack/bitcash | bitcash/network/services.py | NetworkAPI.get_transaction | def get_transaction(cls, txid):
"""Gets the full transaction details.
:param txid: The transaction id in question.
:type txid: ``str``
:raises ConnectionError: If all API services fail.
:rtype: ``Transaction``
"""
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try... | python | def get_transaction(cls, txid):
"""Gets the full transaction details.
:param txid: The transaction id in question.
:type txid: ``str``
:raises ConnectionError: If all API services fail.
:rtype: ``Transaction``
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sporestack/bitcash | bitcash/network/services.py | NetworkAPI.get_tx_amount | def get_tx_amount(cls, txid, txindex):
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:type txid: ``str``
:param txindex: The transaction index in question.
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sporestack/bitcash | bitcash/network/fees.py | get_fee | def get_fee(speed=FEE_SPEED_MEDIUM):
"""Gets the recommended satoshi per byte fee.
:param speed: One of: 'fast', 'medium', 'slow'.
:type speed: ``string``
:rtype: ``int``
"""
if speed == FEE_SPEED_FAST:
return DEFAULT_FEE_FAST
elif speed == FEE_SPEED_MEDIUM:
return DEFAULT_F... | python | def get_fee(speed=FEE_SPEED_MEDIUM):
"""Gets the recommended satoshi per byte fee.
:param speed: One of: 'fast', 'medium', 'slow'.
:type speed: ``string``
:rtype: ``int``
"""
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sporestack/bitcash | bitcash/wallet.py | PrivateKey.get_unspents | def get_unspents(self):
"""Fetches all available unspent transaction outputs.
:rtype: ``list`` of :class:`~bitcash.network.meta.Unspent`
"""
self.unspents[:] = NetworkAPI.get_unspent(self.address)
self.balance = sum(unspent.amount for unspent in self.unspents)
return sel... | python | def get_unspents(self):
"""Fetches all available unspent transaction outputs.
:rtype: ``list`` of :class:`~bitcash.network.meta.Unspent`
"""
self.unspents[:] = NetworkAPI.get_unspent(self.address)
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sporestack/bitcash | bitcash/wallet.py | PrivateKey.create_transaction | def create_transaction(self, outputs, fee=None, leftover=None, combine=True,
message=None, unspents=None, custom_pushdata=False): # pragma: no cover
"""Creates a signed P2PKH transaction.
:param outputs: A sequence of outputs you wish to send in the form
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sporestack/bitcash | bitcash/wallet.py | PrivateKey.sign_transaction | def sign_transaction(self, tx_data): # pragma: no cover
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:param tx_data: Output of :func:`~bitcash.PrivateKey.prepare_transaction`.
:type tx_data: ``str``
:returns: The signed transaction as hex.
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sporestack/bitcash | bitcash/transaction.py | sanitize_tx_data | def sanitize_tx_data(unspents, outputs, fee, leftover, combine=True, message=None, compressed=True, custom_pushdata=False):
"""
sanitize_tx_data()
fee is in satoshis per byte.
"""
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libs = {}
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return platform.mac_ver()[2] # Both Darwin and Python are 64bits.
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Groundworkstech/pybfd | pybfd/opcodes.py | main | def main():
"""Test case for simple opcode disassembly."""
test_targets = (
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[ARCH_I386, MACH_X86_64_INTEL_SYNTAX, ENDIAN_MONO, "\x55\x48\x89\xe5\xE8\xA3\xFF\xFF\xFF", 0x1000],
[ARCH_ARM... | python | def main():
"""Test case for simple opcode disassembly."""
test_targets = (
[ARCH_I386, MACH_I386_I386_INTEL_SYNTAX, ENDIAN_MONO, "\x55\x89\xe5\xE8\xB8\xFF\xFF\xFF", 0x1000],
[ARCH_I386, MACH_X86_64_INTEL_SYNTAX, ENDIAN_MONO, "\x55\x48\x89\xe5\xE8\xA3\xFF\xFF\xFF", 0x1000],
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Groundworkstech/pybfd | pybfd/opcodes.py | Opcodes.initialize_bfd | def initialize_bfd(self, abfd):
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self._ptr = _opcodes.initialize_bfd(abfd._ptr)
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self._ptr = _opcodes.initialize_bfd(abfd._ptr)
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Groundworkstech/pybfd | pybfd/opcodes.py | Opcodes.initialize_non_bfd | def initialize_non_bfd(self, architecture=None, machine=None,
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Groundworkstech/pybfd | pybfd/opcodes.py | Opcodes.initialize_smart_disassemble | def initialize_smart_disassemble(self, data, start_address=0):
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Groundworkstech/pybfd | pybfd/opcodes.py | Opcodes.print_single_instruction_callback | def print_single_instruction_callback(self, address, size, branch_delay_insn,
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"""
Callack on each disassembled instruction to print its information.
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Groundworkstech/pybfd | pybfd/opcodes.py | Opcodes.disassemble | def disassemble(self, data, start_address=0):
"""
Return a list containing the virtual memory address, instruction length
and disassembly code for the given binary buffer.
"""
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Groundworkstech/pybfd | pybfd/gen_supported_disasm.py | generate_supported_disassembler_header | def generate_supported_disassembler_header(supported_archs):
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generate a current header for PyBFD.
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arch_entries = []
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] | train | https://github.com/Groundworkstech/pybfd/blob/9e722435929b4ad52212043a6f1e9e9ce60b5d72/pybfd/gen_supported_disasm.py#L215-L225 |
Groundworkstech/pybfd | pybfd/gen_supported_disasm.py | generate_supported_architectures_source | def generate_supported_architectures_source(supported_archs, supported_machines):
"""Extract export symbols using binutils's nm utility from Binutils and
generate a current header for PyBFD.
"""
arch_entries = []
mach_entries = []
for arch, little, big, comment in supported_archs:
arch... | python | def generate_supported_architectures_source(supported_archs, supported_machines):
"""Extract export symbols using binutils's nm utility from Binutils and
generate a current header for PyBFD.
"""
arch_entries = []
mach_entries = []
for arch, little, big, comment in supported_archs:
arch... | [
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Groundworkstech/pybfd | pybfd/bfd.py | Bfd.open | def open(self, _file, target=DEFAULT_TARGET):
"""
Open the existing file for reading.
@param _file : A filename of file descriptor.
@param target: A user-specific BFD target name.
@return : None
"""
# Close any existing BFD structure instance.
self.clos... | python | def open(self, _file, target=DEFAULT_TARGET):
"""
Open the existing file for reading.
@param _file : A filename of file descriptor.
@param target: A user-specific BFD target name.
@return : None
"""
# Close any existing BFD structure instance.
self.clos... | [
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Groundworkstech/pybfd | pybfd/bfd.py | Bfd.__populate_archive_files | def __populate_archive_files(self):
"""Store the list of files inside an archive file."""
self.archive_files = []
for _ptr in _bfd.archive_list_files(self._ptr):
try:
self.archive_files.append(Bfd(_ptr))
except BfdException, err:
#print "Er... | python | def __populate_archive_files(self):
"""Store the list of files inside an archive file."""
self.archive_files = []
for _ptr in _bfd.archive_list_files(self._ptr):
try:
self.archive_files.append(Bfd(_ptr))
except BfdException, err:
#print "Er... | [
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