xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

a8d74f3cfb963afbf0326e3a3f7e5bfe03135acd

279

py

Python

appmgmt/views/__init__.py

ekivemark/BlueButtonDev

c751a5c52a83df6b97ef2c653a4492d959610c42

[ "Apache-2.0" ]

5

2016-03-02T23:25:39.000Z

2020-10-29T07:28:42.000Z

appmgmt/views/__init__.py

HowardEdidin/BlueButtonFHIR_API

b8433055507bcc334f70bc864eacd379a04f69db

[ "Apache-2.0" ]

13

2020-02-11T22:50:32.000Z

2022-03-11T23:12:48.000Z

appmgmt/views/__init__.py

HowardEdidin/BlueButtonFHIR_API

b8433055507bcc334f70bc864eacd379a04f69db

[ "Apache-2.0" ]

4

2016-02-02T19:17:24.000Z

2020-10-10T16:10:31.000Z

# -*- coding: utf-8 -*- """ bofhirdev FILE: __init__.py Created: 10/29/15 4:11 PM """ __author__ = 'Mark Scrimshire:@ekivemark' from appmgmt.views.application import * from appmgmt.views.main import * from appmgmt.views.organization import * from appmgmt.views.trust import *

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5

7682d4d3aded2670b2fbac760968aaa98452be92

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py

Python

models/pre_reqs.py

andehwong/taylor_stacks

9301c53286cc8c6f8ced1eefd597456702f337f1

[ "MIT" ]

null

models/pre_reqs.py

andehwong/taylor_stacks

9301c53286cc8c6f8ced1eefd597456702f337f1

[ "MIT" ]

null

models/pre_reqs.py

andehwong/taylor_stacks

9301c53286cc8c6f8ced1eefd597456702f337f1

[ "MIT" ]

null

class PreRequisites: def __init__(self, course_list=None): self.course_list = course_list

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4f455cbb4559a570b24a34bef3ea606a40bbb2ab

116

py

Python

MovieRecommend/movieviewer/admin.py

tyanakiev/MovieRecommend

869613bdb5e9b1f869fe89382316f11a7a7c4352

[ "MIT" ]

null

MovieRecommend/movieviewer/admin.py

tyanakiev/MovieRecommend

869613bdb5e9b1f869fe89382316f11a7a7c4352

[ "MIT" ]

null

MovieRecommend/movieviewer/admin.py

tyanakiev/MovieRecommend

869613bdb5e9b1f869fe89382316f11a7a7c4352

[ "MIT" ]

null

from django.contrib import admin # Register your models here. from .models import Movie admin.site.register(Movie)

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5

4f75033b6adbbb71564cf2822fd11416bc1836e0

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py

Python

setup.py

makotookamura/GmoCoin

025d3e68364bf52418dbc3445987ff21528db732

[ "Apache-2.0" ]

5

2020-05-06T13:02:12.000Z

2020-11-06T04:11:45.000Z

setup.py

makotookamura/GmoCoin

025d3e68364bf52418dbc3445987ff21528db732

[ "Apache-2.0" ]

44

2020-11-15T01:17:38.000Z

2021-07-20T13:45:12.000Z

setup.py

makotookamura/GmoCoin

025d3e68364bf52418dbc3445987ff21528db732

[ "Apache-2.0" ]

1

2022-02-20T22:18:38.000Z

from setuptools import setup setup()

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5

4f8ae2ee6cd56d54ef4f2b985fb576cfb1c0b3d7

42

py

Python

DBus.py

whitelynx/karvy

e380a19ace60168b374855ea1ee9c347936b67fe

[ "MIT" ]

3

2020-04-19T19:56:18.000Z

2021-09-30T03:07:42.000Z

DBus.py

whitelynx/karvy

e380a19ace60168b374855ea1ee9c347936b67fe

[ "MIT" ]

null

DBus.py

whitelynx/karvy

e380a19ace60168b374855ea1ee9c347936b67fe

[ "MIT" ]

1

2020-10-27T13:43:38.000Z

import dbus systemBus = dbus.SystemBus()

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4fa39d40604d714fbf43d4c73891cfb2c040641c

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py

Python

src/impscan/conda_meta/__init__.py

lmmx/impscan

fd809f9f32302e3b67bc921164f34fdd837cf92b

[ "MIT" ]

null

src/impscan/conda_meta/__init__.py

lmmx/impscan

fd809f9f32302e3b67bc921164f34fdd837cf92b

[ "MIT" ]

15

2021-06-24T15:30:57.000Z

2021-07-30T14:04:38.000Z

src/impscan/conda_meta/__init__.py

lmmx/impscan

fd809f9f32302e3b67bc921164f34fdd837cf92b

[ "MIT" ]

null

from . import formats, streaming_formats __all__ = ["formats", "streaming_formats"]

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5

4fa4b9281842f5d0bdd26adbde7c63ff91654a2f

119

py

Python

tagger/commander/__init__.py

9bstudios/mecco_tagger

08af7cc0939602ae15e43fa081bbc0825b2ef7a7

[ "MIT" ]

null

tagger/commander/__init__.py

9bstudios/mecco_tagger

08af7cc0939602ae15e43fa081bbc0825b2ef7a7

[ "MIT" ]

null

tagger/commander/__init__.py

9bstudios/mecco_tagger

08af7cc0939602ae15e43fa081bbc0825b2ef7a7

[ "MIT" ]

null

# python __version__ = "0.36" __author__ = "Adam" from Commander import * from MeshEditor import * from Var import *

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5

96ebd0b99171cfdc8c68e9074997111347fb23f9

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py

Python

src/viz/eval.py

Jatin-WIAI/ct-segmentation

e1e90ea376a21f35011399be9e5c66f8e0450241

[ "Apache-2.0" ]

null

src/viz/eval.py

Jatin-WIAI/ct-segmentation

e1e90ea376a21f35011399be9e5c66f8e0450241

[ "Apache-2.0" ]

null

src/viz/eval.py

Jatin-WIAI/ct-segmentation

e1e90ea376a21f35011399be9e5c66f8e0450241

[ "Apache-2.0" ]

null

from copy import deepcopy import matplotlib.pyplot as plt import numpy as np import wandb from src.utils.threshold import * from scipy.stats import norm from sklearn.calibration import calibration_curve from sklearn.metrics import (auc, average_precision_score, det_curve, matthews_corrcoef, precision_recall_curve, precision_score, roc_auc_score, roc_curve) def plot_reliability_curve(y_true_arr, y_pred_proba_arr, labels_arr, n_bins=10, log_wandb=False, **kwargs): """Function for plotting reliability curve (test of extent of calibration) The user provides a list of N GT arrays, N predicted probabilities, N labels, and that results in N reliability curves. Args: y_true_arr (list/np.array): list of all GT arrays y_pred_proba_arr (list/np.array): list of all predicted probabilities labels_arr (list/np.array): list of labels n_bins (int, optional): Number of bins to use. Defaults to 10. log_wandb (bool, optional): If true, figure is logged to W&B. Defaults to False. Returns: plt.Figure, plt.Axes: Tuple of fig, ax """ fig, ax = plt.subplots(figsize=(12, 8)) ax.plot([0, 1], [0, 1], '--', c='black', label='Perfect Calibration') for i, (y_true, y_pred_proba) in enumerate(zip(y_true_arr, y_pred_proba_arr)): frac_pos, pred_prob = calibration_curve( y_true, y_pred_proba[:, 1], n_bins=n_bins) ax.plot(pred_prob, frac_pos, '-o', label=f'{labels_arr[i]}') ax.set_title('Reliability Diagram') ax.set_xlabel('Predicted Probability, Positive Class') ax.set_ylabel('Fraction of Positives') ax.grid() ax.legend() if log_wandb: wandb.log({"reliab_curve": [wandb.Image(fig)]}) plt.close(fig) return fig, ax def plot_pr_curve(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None, plot_prevalance_for_idx=None, log_wandb=False): """Function for plotting PR curve Args: y_true_arr (list/np.array): list of all GT arrays y_pred_proba_arr (list/np.array): list of all predicted probabilities labels_arr (list/np.array): list of labels pos_label (str, optional): What is the label of the positive class. Defaults to 'Yes'. plot_thres_for_idx (int, optional): If true, best threshold (F1) is plotted for the PR curve corresponding to this index. Defaults to None. plot_prevalance_for_idx (int, optional): If true, prevelance of pos class is plotted for the PR curve corresponding to this index. Defaults to None. log_wandb (bool, optional): If true, figure is logged to W&B. Defaults to False. Returns: plt.Figure, plt.Axes: The tuple of figure and axes """ fig, ax = plt.subplots(figsize=(12, 8)) for i, (y_true, y_pred_proba) in enumerate(zip(y_true_arr, y_pred_proba_arr)): p, r, _ = precision_recall_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) ap = average_precision_score(y_true, y_pred_proba[:, 1], pos_label=pos_label) ax.plot(r, p, label=f'{labels_arr[i]} (AP - {round(ap, 2)})') if plot_thres_for_idx is not None: y_true = y_true_arr[plot_thres_for_idx] y_pred_proba = y_pred_proba_arr[plot_thres_for_idx] _, idx = get_best_threshold_f1( y_true, y_pred_proba, pos_label=pos_label) p, r, _ = precision_recall_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) ax.plot([r[idx]], [p[idx]], '-o', c=ax.lines[plot_thres_for_idx].get_color(), label=f'Best {labels_arr[plot_thres_for_idx]} Threshold (F1)') if plot_prevalance_for_idx is not None: y_true = y_true_arr[plot_prevalance_for_idx] ax.plot([0, 1], [sum(y_true == pos_label)/len(y_true)]*2, c='black', ls='--', label=f'{labels_arr[plot_prevalance_for_idx]} Prevelance ' + f'({round(sum(y_true == pos_label)/len(y_true), 2)})') ax.set_xlabel('Recall') ax.set_ylabel('Precision') ax.set_title('PR Curve') ax.grid() ax.legend() if log_wandb: wandb.log({"pr_curve": [wandb.Image(fig)]}) plt.close(fig) return fig, ax def plot_roc_curve(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None, log_wandb=False): """Function for plotting ROC curve Args: y_true_arr (list/np.array): list of all GT arrays y_pred_proba_arr (list/np.array): list of all predicted probabilities labels_arr (list/np.array): list of labels pos_label (str, optional): What is the label of the positive class. Defaults to 'Yes'. plot_thres_for_idx (int, optional): If true, best threshold (F1) is plotted for the ROC curve corresponding to this index. Defaults to None. log_wandb (bool, optional): If true, figure is logged to W&B. Defaults to False. Returns: plt.Figure, plt.Axes: The tuple of figure and axes """ fig, ax = plt.subplots(figsize=(12, 8)) for i, (y_true, y_pred_proba) in enumerate(zip(y_true_arr, y_pred_proba_arr)): fpr, tpr, _ = roc_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) auc = roc_auc_score(y_true, y_pred_proba[:, 1]) ax.plot(fpr, tpr, label=f'{labels_arr[i]} (AUC - {round(auc, 3)})') if plot_thres_for_idx is not None: y_true = y_true_arr[plot_thres_for_idx] y_pred_proba = y_pred_proba_arr[plot_thres_for_idx] _, idx = get_best_threshold_gmean( y_true, y_pred_proba, pos_label=pos_label) fpr, tpr, _ = roc_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) ax.plot([fpr[idx]], [tpr[idx]], '-o', c=ax.lines[plot_thres_for_idx].get_color(), label=f'Best {labels_arr[plot_thres_for_idx]} Threshold (GMean)') ax.set_xlabel('False Positive Rate') ax.set_ylabel('True Positive Rate') ax.set_title('ROC Curve') ax.legend() ax.grid() if log_wandb: wandb.log({"roc_curve": [wandb.Image(fig)]}) plt.close(fig) return fig, ax def plot_det_curve(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None, log_wandb=False): """Function for plotting DET curve Args: y_true_arr (list/np.array): list of all GT arrays y_pred_proba_arr (list/np.array): list of all predicted probabilities labels_arr (list/np.array): list of labels pos_label (str, optional): What is the label of the positive class. Defaults to 'Yes'. plot_thres_for_idx (int, optional): If true, best threshold (F1) is plotted for the DET curve corresponding to this index. Defaults to None. log_wandb (bool, optional): If true, figure is logged to W&B. Defaults to False. Returns: plt.Figure, plt.Axes: The tuple of figure and axes """ fig, ax = plt.subplots(figsize=(12, 8)) for i, (y_true, y_pred_proba) in enumerate(zip(y_true_arr, y_pred_proba_arr)): fpr, fnr, _ = det_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) auc_score = auc(fpr, fnr) ax.plot(norm.ppf(fpr), norm.ppf(fnr), label=f'{labels_arr[i]} (AUC - {round(auc_score, 3)})') if plot_thres_for_idx is not None: y_true = y_true_arr[plot_thres_for_idx] y_pred_proba = y_pred_proba_arr[plot_thres_for_idx] _, idx = get_best_threshold_gmean( y_true, y_pred_proba, pos_label=pos_label) fpr, fnr, _ = det_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) ax.plot([norm.ppf(fpr[idx])], [norm.ppf(fnr[idx])], '-o', c=ax.lines[plot_thres_for_idx].get_color(), label=f'Best {labels_arr[plot_thres_for_idx]} Threshold (GMean)') ax.set_xlabel('False Positive Rate') ax.set_ylabel('False Negative Rate') ax.set_title('DET Curve') ax.legend() ax.grid() ticks = [0.001, 0.01, 0.05, 0.20, 0.5, 0.80, 0.95, 0.99, 0.999] tick_locations = norm.ppf(ticks) tick_labels = [ '{:.0%}'.format(s) if (100*s).is_integer() else '{:.1%}'.format(s) for s in ticks ] ax.set_xticks(tick_locations) ax.set_xticklabels(tick_labels) ax.set_yticks(tick_locations) ax.set_yticklabels(tick_labels) if log_wandb: wandb.log({"det_curve": [wandb.Image(fig)]}) plt.close(fig) return fig, ax def plot_f1(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None, log_wandb=False): """Function for plotting F1 curve (F1 vs threshold) F1 is defined as the harmonic mean between Precision and Recall Args: y_true_arr (list/np.array): list of all GT arrays y_pred_proba_arr (list/np.array): list of all predicted probabilities labels_arr (list/np.array): list of labels pos_label (str, optional): What is the label of the positive class. Defaults to 'Yes'. plot_thres_for_idx (int, optional): If true, best threshold (F1) is plotted for the F1 curve corresponding to this index. Defaults to None. log_wandb (bool, optional): If true, figure is logged to W&B. Defaults to False. Returns: plt.Figure, plt.Axes: The tuple of figure and axes """ fig, ax = plt.subplots(figsize=(12, 8)) for i, (y_true, y_pred_proba) in enumerate(zip(y_true_arr, y_pred_proba_arr)): p, r, pr_thresholds = precision_recall_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) f1 = 2*(p*r/(p + r)) ax.plot(pr_thresholds, f1[:-1], label=f'{labels_arr[i]}') if plot_thres_for_idx is not None: y_true = y_true_arr[plot_thres_for_idx] y_pred_proba = y_pred_proba_arr[plot_thres_for_idx] _, idx = get_best_threshold_f1( y_true, y_pred_proba, pos_label=pos_label) p, r, pr_thresholds = precision_recall_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) f1 = 2*(p*r/(p + r)) ax.plot([pr_thresholds[idx]], [f1[idx]], '-o', c=ax.lines[plot_thres_for_idx].get_color(), label=f'Best {labels_arr[plot_thres_for_idx]} Threshold (F1)') ax.set_title('F1 vs threshold') ax.set_xlabel('Threshold') ax.set_ylabel('F1') ax.grid() ax.legend() if log_wandb: wandb.log({"f1": [wandb.Image(fig)]}) plt.close(fig) return fig, ax def plot_matthews_coeff(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None, log_wandb=False): # ! Todo - MCC is returning error, and it is taking too much time. Need to debug. """Function for plotting MCC curve (MCC vs threshold) Matthews Correlation Coefficient (MCC) is different from F1 and other metrics as it takes into account performance on all 4 elements of the binary confusion matrix. Check out https://en.wikipedia.org/wiki/Matthews_correlation_coefficient for a detailed definition. Args: y_true_arr (list/np.array): list of all GT arrays y_pred_proba_arr (list/np.array): list of all predicted probabilities labels_arr (list/np.array): list of labels pos_label (str, optional): What is the label of the positive class. Defaults to 'Yes'. plot_thres_for_idx (int, optional): If true, best threshold (F1) is plotted for the MCC curve corresponding to this index. Defaults to None. log_wandb (bool, optional): If true, figure is logged to W&B. Defaults to False. Returns: plt.Figure, plt.Axes: The tuple of figure and axes """ fig, ax = plt.subplots(figsize=(12, 8)) for i, (y_true, y_pred_proba) in enumerate(zip(y_true_arr, y_pred_proba_arr)): thresholds = np.sort(y_pred_proba[:, 1]) y_true = deepcopy(y_true) mcc_arr = [] for thres in thresholds: y_pred = (y_pred_proba[:, 1] > thres).astype(int) y_true[y_true == pos_label] = 1 y_true[y_true != pos_label] = 0 mcc = matthews_corrcoef( y_true.to_numpy().astype(int), y_pred) mcc_arr.append(mcc) ax.plot(thresholds, mcc_arr, label=f'{labels_arr[i]}') # if plot_thres_for_idx is not None: # y_true = y_true_arr[plot_thres_for_idx] # y_pred_proba = y_pred_proba_arr[plot_thres_for_idx] # _, idx = get_best_threshold_f1(y_true, y_pred_proba, pos_label=pos_label) # p, r, pr_thresholds = precision_recall_curve( # y_true, y_pred_proba[:, 1], pos_label=pos_label) # f1 = 2*(p*r/(p + r)) # ax.plot([pr_thresholds[idx]], [f1[idx]], '-o', c=ax.lines[plot_thres_for_idx].get_color(), # label=f'Best {labels_arr[plot_thres_for_idx]} Threshold (F1)') ax.set_title('MCC vs threshold') ax.set_xlabel('Threshold') ax.set_ylabel('MCC') ax.grid() ax.legend() if log_wandb: wandb.log({"matthews_coeff": [wandb.Image(fig)]}) plt.close(fig) return fig, ax def plot_fm_index(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None, log_wandb=False): """Function for plotting FM curve (Folkwes-Mallows) - FM vs Threshold. FM is defined as sqrt(Precision*Recall). Just like F1 is the harmonic mean of P and R, FM is the geometric mean. Practically, its values end up being v close to the corresponding F1 values. They can be interchangeably used. Args: y_true_arr (list/np.array): list of all GT arrays y_pred_proba_arr (list/np.array): list of all predicted probabilities labels_arr (list/np.array): list of labels pos_label (str, optional): What is the label of the positive class. Defaults to 'Yes'. plot_thres_for_idx (int, optional): If true, best threshold (F1) is plotted for the FM curve corresponding to this index. Defaults to None. log_wandb (bool, optional): If true, figure is logged to W&B. Defaults to False. Returns: plt.Figure, plt.Axes: The tuple of figure and axes """ fig, ax = plt.subplots(figsize=(12, 8)) for i, (y_true, y_pred_proba) in enumerate(zip(y_true_arr, y_pred_proba_arr)): p, r, pr_thresholds = precision_recall_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) fm = np.sqrt(p*r) ax.plot(pr_thresholds, fm[:-1], label=f'{labels_arr[i]}') if plot_thres_for_idx is not None: y_true = y_true_arr[plot_thres_for_idx] y_pred_proba = y_pred_proba_arr[plot_thres_for_idx] _, idx = get_best_threshold_fowlkes_mallows( y_true, y_pred_proba, pos_label=pos_label) p, r, _ = precision_recall_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) fm = np.sqrt(p*r) ax.plot([pr_thresholds[idx]], [fm[idx]], '-o', c=ax.lines[plot_thres_for_idx].get_color(), label=f'Best {labels_arr[plot_thres_for_idx]} Threshold (FM Index)') ax.set_title('Fowlkes–Mallows index vs threshold') ax.set_xlabel('Threshold') ax.set_ylabel('Fowlkes–Mallows index') ax.grid() ax.legend() if log_wandb: wandb.log({"fm_index": [wandb.Image(fig)]}) plt.close(fig) return fig, ax def plot_gmean(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None, log_wandb=False): """Function for plotting Gmean curve (Gmean vs Threshold) GMean is defined as sqrt(tpr * (1 - fpr)), where tpr, fpr are the true positive, and false positive rates respectively. Args: y_true_arr (list/np.array): list of all GT arrays y_pred_proba_arr (list/np.array): list of all predicted probabilities labels_arr (list/np.array): list of labels pos_label (str, optional): What is the label of the positive class. Defaults to 'Yes'. plot_thres_for_idx (int, optional): If true, best threshold (F1) is plotted for the Gmean curve corresponding to this index. Defaults to None. log_wandb (bool, optional): If true, figure is logged to W&B. Defaults to False. Returns: plt.Figure, plt.Axes: The tuple of figure and axes """ fig, ax = plt.subplots(figsize=(12, 8)) for i, (y_true, y_pred_proba) in enumerate(zip(y_true_arr, y_pred_proba_arr)): fpr, tpr, roc_thresholds = roc_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) gmean = np.sqrt(tpr * (1-fpr)) ax.plot(roc_thresholds[1:], gmean[1:], label=f'{labels_arr[i]}') if plot_thres_for_idx is not None: y_true = y_true_arr[plot_thres_for_idx] y_pred_proba = y_pred_proba_arr[plot_thres_for_idx] _, idx = get_best_threshold_gmean( y_true, y_pred_proba, pos_label=pos_label) fpr, tpr, roc_thresholds = roc_curve( y_true, y_pred_proba[:, 1], pos_label=pos_label) gmean = np.sqrt(tpr * (1-fpr)) ax.plot([roc_thresholds[idx]], [gmean[idx]], '-o', c=ax.lines[plot_thres_for_idx].get_color(), label=f'Best {labels_arr[plot_thres_for_idx]} Threshold (GMean)') ax.set_title('GMean vs threshold') ax.set_xlabel('Threshold') ax.set_ylabel('GMean') ax.grid() ax.legend() if log_wandb: wandb.log({"gmean": [wandb.Image(fig)]}) plt.close(fig) return fig, ax

41.611374

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0.651822

2,761

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3.881565

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null

0

1

0

null

0

5

96ff2457d4db41b9ba7cc34889225f94e9d21a0d

76

py

Python

tests/pyflakes_bears/pep8_naming_test_files/E02/valid.py

MacBox7/coala-pyflakes

637f8a2e77973384be79d30b0dae1f43072e60c8

[ "MIT" ]

null

tests/pyflakes_bears/pep8_naming_test_files/E02/valid.py

MacBox7/coala-pyflakes

637f8a2e77973384be79d30b0dae1f43072e60c8

[ "MIT" ]

12

2018-05-21T06:12:59.000Z

2018-07-30T10:37:16.000Z

tests/pyflakes_bears/pep8_naming_test_files/E02/valid.py

MacBox7/coala-pyflakes

637f8a2e77973384be79d30b0dae1f43072e60c8

[ "MIT" ]

1

2018-06-10T16:16:47.000Z

def foo(): ''' >>> from mod import good as bad ''' pass

12.666667

39

0.421053

9

76

3.555556

1

0

0.421053

76

5

40

15.2

0.727273

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true

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1

0

null

0

1

0

null

0

1

0

5

4fb7abcc8362249508823da8e96c2c68fcad7632

128

py

Python

contenedores/admin.py

tedesco8/dj_restApi

58e54fa5f444a6fdec8f622ceab6480daa8368ea

[ "MIT" ]

1

2020-03-25T14:18:13.000Z

contenedores/admin.py

tedesco8/api-rest-django

58e54fa5f444a6fdec8f622ceab6480daa8368ea

[ "MIT" ]

9

2020-11-19T16:25:31.000Z

2021-09-22T19:38:38.000Z

contenedores/admin.py

tedesco8/api-rest-django

58e54fa5f444a6fdec8f622ceab6480daa8368ea

[ "MIT" ]

1

2020-03-04T03:34:56.000Z

from django.contrib import admin from contenedores.models import * # Register your models here. admin.site.register(Contenedor)

25.6

33

0.820313

17

128

6.176471

0.705882

0

0.109375

128

5

34

25.6

0.921053

0.203125

0

1

0

true

0

0.666667

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0.666667

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null

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1

0

null

0

1

0

1

0

1

0

5

4ffda25dda548615cf215830cb8ab0dcea6e0008

19

py

Python

examples/round/ex2.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/round/ex2.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/round/ex2.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

print(round(-0.5))

9.5

18

0.631579

4

19

3

1

0

0.111111

0.052632

19

1

19

0.555556

0

1

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true

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0

null

0

1

0

null

0

1

0

1

0

5

8ca556817ff8b309f5815088c12f76fcc22932ce

155

py

Python

book/admin.py

YevgeniiKaidashov/book-store

dda5e8b1560699a6d20249d1ef92f65a60f1eadd

[ "MIT" ]

1

2019-04-28T08:30:43.000Z

book/admin.py

YevgeniiKaidashov/book-store

dda5e8b1560699a6d20249d1ef92f65a60f1eadd

[ "MIT" ]

null

book/admin.py

YevgeniiKaidashov/book-store

dda5e8b1560699a6d20249d1ef92f65a60f1eadd

[ "MIT" ]

null

from django.contrib import admin from book.models import Book, Author # Register your models here. admin.site.register(Book) admin.site.register(Author)

19.375

36

0.8

23

155

5.391304

0.521739

0.145161

0.274194

0

0.116129

155

7

37

22.142857

0.905109

0.167742

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

8cb2be5c48441cbe53ca661a886e3648aa65460f

410

py

Python

python/anyascii/_data/_2b4.py

casept/anyascii

d4f426b91751254b68eaa84c6cd23099edd668e6

[ "ISC" ]

null

python/anyascii/_data/_2b4.py

casept/anyascii

d4f426b91751254b68eaa84c6cd23099edd668e6

[ "ISC" ]

null

python/anyascii/_data/_2b4.py

casept/anyascii

d4f426b91751254b68eaa84c6cd23099edd668e6

[ "ISC" ]

null

b=' Yue Shan Kuai Na Ba Ling Fan Zhi Ping Tian Yi Zhou Ni Guan Hong Bu Ke Wei Jiao Bu Kan Lei Lou Zhuan Meng Yan Han Ba Zi Fu Guo Cong Qian Za Yang Liu Ji Xu Qiao Jun Mou Shen Xuan Wan Ji Lu Nie He Zong Yu'

410

0.373171

51

410

3

0.941176

0

0.619512

410

1

410

0.980769

0

1

0.987835

0

1

0

false

0

null

0

1

0

1

0

1

0

1

0

null

0

5

8ce955b13cbf94bfd6f4e7e10ca49601ebb35cec

91

py

Python

models/baseline/__init__.py

Thesharing/lfesm

e956ed76f5a85259000742db093726d4b4c51751

[ "Apache-2.0" ]

6

2020-01-31T13:14:11.000Z

2021-05-16T11:43:17.000Z

models/baseline/__init__.py

Cyprestar/scm-fsim

924fb184451fa4ca0eb419a1dcc0bd6cea2edf3a

[ "Apache-2.0" ]

5

2020-11-16T06:23:31.000Z

2022-01-04T10:17:16.000Z

models/baseline/__init__.py

Cyprestar/scm-fsim

924fb184451fa4ca0eb419a1dcc0bd6cea2edf3a

[ "Apache-2.0" ]

4

2020-11-04T02:42:57.000Z

2022-03-21T06:36:20.000Z

from .bert import BERTBaseline from .cnn import CNNBaseline from .lstm import LSTMBaseline

22.75

30

0.835165

12

91

6.333333

0.666667

0

0.131868

91

3

31

30.333333

0.962025

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

50679659170a4b5587b49ec001688dc775e5914c

194

py

Python

app/urls.py

shikharvaish28/mr-caption

b24107e55ee587ff16275e9428b4dfd8091d31c9

[ "MIT" ]

3

2018-10-10T16:27:40.000Z

2018-10-10T16:27:46.000Z

app/urls.py

shikharvaish28/mr-caption

b24107e55ee587ff16275e9428b4dfd8091d31c9

[ "MIT" ]

null

app/urls.py

shikharvaish28/mr-caption

b24107e55ee587ff16275e9428b4dfd8091d31c9

[ "MIT" ]

1

2018-10-08T13:32:09.000Z

from django.conf.urls import url from . import views from django.conf import settings from django.views.static import serve urlpatterns = [ url(r'^$', views.get_image , name='get_image'), ]

24.25

51

0.742268

29

194

4.896552

0.517241

0.211268

0.197183

0

0.14433

194

8

52

24.25

0.855422

0

0.05641

0

1

0

false

0

0.571429

0

0.571429

0

1

0

null

1

0

1

0

null

0

1

0

5

5080bcd64d7348d9b49c180691bef5a20a1d2798

5,678

py

Python

predict_api_test.py

johnson7788/mt-dnn

26e5c4a5bfdbf1a1dd1c903e606db1c070568237

[ "MIT" ]

null

predict_api_test.py

johnson7788/mt-dnn

26e5c4a5bfdbf1a1dd1c903e606db1c070568237

[ "MIT" ]

null

predict_api_test.py

johnson7788/mt-dnn

26e5c4a5bfdbf1a1dd1c903e606db1c070568237

[ "MIT" ]

1

2021-07-14T08:57:20.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Date : 2021/6/30 2:00 下午 # @File : api_test.py # @Author: johnson # @Contact : github: johnson7788 # @Desc : import requests import json def dopredict_absa(test_data, host="127.0.0.1:3326"): """ 预测结果 :param test_data: :return: """ url = f"http://{host}/api/absa_predict" data = {'data': test_data} headers = {'content-type': 'application/json'} r = requests.post(url, headers=headers, data=json.dumps(data), timeout=360) print(r.json()) return r.json() def dopredict_absa_fullscore(test_data, host="127.0.0.1:3326"): """ 预测结果 :param test_data: :return: """ url = f"http://{host}/api/absa_predict_fullscore" data = {'data': test_data} headers = {'content-type': 'application/json'} r = requests.post(url, headers=headers, data=json.dumps(data), timeout=360) print(r.json()) return r.json() def dopredict_dem8(test_data, host="127.0.0.1:3326"): """ 预测结果 :param test_data: [('持妆不能输雅诗兰黛上妆即定妆雅诗兰黛DW粉底是我的心头好持妆遮瑕磨皮粉底液测评', '遮瑕', '成分'),...] :return: """ url = f"http://{host}/api/dem8_predict" data = {'data': test_data} headers = {'content-type': 'application/json'} r = requests.post(url, headers=headers, data=json.dumps(data), timeout=360) print(r.json()) return r.json() def dopredict_purchase(test_data, host="127.0.0.1:3326"): """ 预测结果 :param test_data: [('持妆不能输雅诗兰黛上妆即定妆雅诗兰黛DW粉底是我的心头好持妆遮瑕磨皮粉底液测评', '遮瑕', '成分'),...] :return: """ url = f"http://{host}/api/purchase_predict" data = {'data': test_data} headers = {'content-type': 'application/json'} r = requests.post(url, headers=headers, data=json.dumps(data), timeout=360) print(r.json()) return r.json() def dem8(test_data, host="127.0.0.1:3326"): """ 预测结果, 多个aspect关键字的情况 :param test_data: [('持妆不能输雅诗兰黛上妆即定妆雅诗兰黛DW粉底是我的心头好持妆遮瑕磨皮粉底液测评', ['遮瑕','粉底'], '成分'),...] :return: """ url = f"http://{host}/api/dem8" data = {'data': test_data} headers = {'content-type': 'application/json'} r = requests.post(url, headers=headers, data=json.dumps(data), timeout=360) print(r.json()) return r.json() def dopredict_absa_dem8(test_data, host="127.0.0.1:3326"): """ 预测属性之后预测情感 :param test_data: [('持妆不能输雅诗兰黛上妆即定妆雅诗兰黛DW粉底是我的心头好持妆遮瑕磨皮粉底液测评', '遮瑕', '成分'),...] :return: """ url = f"http://{host}/api/absa_dem8_predict" data = {'data': test_data} headers = {'content-type': 'application/json'} r = requests.post(url, headers=headers, data=json.dumps(data), timeout=360) print(r.json()) return r.json() def dopredict_absa_sentence(test_data, host="127.0.0.1:3326"): """ 预测属性之后预测情感 :param test_data: [('持妆不能输雅诗兰黛上妆即定妆雅诗兰黛DW粉底是我的心头好持妆遮瑕磨皮粉底液测评', '遮瑕', '成分'),...] :return: """ url = f"http://{host}/api/absa_predict_sentence" data = {'data': test_data} headers = {'content-type': 'application/json'} r = requests.post(url, headers=headers, data=json.dumps(data), timeout=360) print(r.json()) return r.json() if __name__ == '__main__': # host = "127.0.0.1:3326" # host = "192.168.50.139:3326" host = "192.168.50.189:3326" absa_data = [('这个遮瑕效果很差，很不好用', '遮瑕'), ('抗氧化效果一般', '抗氧化'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。', '水润'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。', '质感'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。', '补水')] dem8_data = [('持妆不能输雅诗兰黛上妆即定妆雅诗兰黛DW粉底是我的心头好持妆遮瑕磨皮粉底液测评', '遮瑕', '成分'), ('活动有赠品比较划算，之前买过快用完了，一支可以分两次使用，早上抗氧化必备VC', '抗氧化','成分'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。', '水润', '功效'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。', '质感','功效'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。', '补水','功效')] purchase_data = [['飘了大概两周终于到了\n希望我的头发别再掉了\n但是我又纠结要不要用，\n看到各种各样的评价，还说有疯狂的脱发期，那我要不要用？\n担心越用越脱啊。再加上我头发甚至连头皮都是干巴巴的类型。\n#REGENERATE \n#Grow Gorgeous Grow Gorgeous强效防脱增发精华头发增长生发液密发增发英国进口 \n#Dr.Hauschka 德国世家 \n#Alpecin 咖啡因C1 洗发水 \n#Alpecin 咖啡因防脱免洗发根滋养液 ', '买了alpecin洗发水增发液纠结要不要用？', 'grow gorgeous强效防脱增发精华']] # dem8_dd = [('持妆不能输雅诗兰黛上妆即定妆雅诗兰黛DW粉底是我的心头好持妆遮瑕磨皮粉底液测评', ['遮瑕','粉底'], '成分'), ('活动有赠品比较划算，之前买过快用完了，一支可以分两次使用，早上抗氧化必备VC', ['抗氧化'],'成分'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。',['水润','补水'], '功效'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。', ['质感'],'功效'), ('海洋冰泉水润清透是MG面膜深受顾客喜爱的经典款面膜之一，已经使用了两年多了。该产品外包装精致、里面的面膜质感很好，与面部的贴合度、大小符合度都不错，使面膜的精华液能很好的均匀的敷于脸部各个部位。适用于各种肌肤，补水效果好，用后皮肤水润、光滑，以后还会回购的。', ['补水'],'功效')] # dopredict_absa(host=host,test_data=absa_data) # dopredict_absa_fullscore(host=host,test_data=absa_data) # dopredict_dem8(host=host,test_data=dem8_data) # dopredict_purchase(host=host,test_data=purchase_data) # dem8(host=host,test_data=dem8_dd) # 句子情感 sentence_data = ['持妆不能输雅诗兰黛上妆即定妆雅诗兰黛DW粉底是我的心头好持妆遮瑕磨皮粉底液测评', '活动有赠品比较划算，之前买过快用完了，一支可以分两次使用，早上抗氧化必备VC'] dopredict_absa_sentence(host=host, test_data=sentence_data) # dopredict_absa_dem8(test_data=dem8_data,host=host)

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sdcclient/monitor/dashboard_converters/__init__.py

DaveCanHaz/sysdig-sdk-python

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[ "MIT" ]

null

sdcclient/monitor/dashboard_converters/__init__.py

DaveCanHaz/sysdig-sdk-python

2c8cb5674add8d5e7efcd6f3ff9fe9c1e7a88dac

[ "MIT" ]

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sdcclient/monitor/dashboard_converters/__init__.py

DaveCanHaz/sysdig-sdk-python

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from ._dashboard_versions import convert_dashboard_between_versions from ._dashboard_scope import convert_scope_string_to_expression

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Python

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bspiritxp/jcramda

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[ "MIT" ]

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jcramda/__init__.py

bspiritxp/jcramda

290f41fa8f6e5f729f666e800ffee28c2c9d4b06

[ "MIT" ]

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2022-02-11T03:25:11.000Z

jcramda/__init__.py

bspiritxp/jcramda

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from .core import * from .base import * from .factor import (Just, Nothing, Maybe) _ = HP = EmptyParam Version = '1.0.5'

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Python

Python/Tests/TestData/DebuggerProject/BreakpointTest3.py

nanshuiyu/pytools

9f9271fe8cf564b4f94e9456d400f4306ea77c23

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Python/Tests/TestData/DebuggerProject/BreakpointTest3.py

nanshuiyu/pytools

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Python/Tests/TestData/DebuggerProject/BreakpointTest3.py

nanshuiyu/pytools

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def f(): print('hello') print('calling f') f()

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py

Python

b3cdi/__init__.py

abbudao/b3_cdi_curve

b717c8c84f65e1d65c25726992f987d6f6042e23

[ "MIT" ]

1

2020-11-18T19:18:28.000Z

b3cdi/__init__.py

abbudao/b3_cdi_curve

b717c8c84f65e1d65c25726992f987d6f6042e23

[ "MIT" ]

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b3cdi/__init__.py

abbudao/b3_cdi_curve

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2020-11-18T19:18:42.000Z

from .b3cdi import sync_db, create_time_series

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py/tests/smoketest.py

v-zion/phrase-machine

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py/tests/smoketest.py

v-zion/phrase-machine

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# -*- encoding: utf-8 -*- text = u""" Mr. Speaker, Mr. President, distinguished Members of the Congress, honored guests, and fellow citizens: I come before you to report on the state of our Union, and I'm pleased to report that after 4 years of united effort, the American people have brought forth a nation renewed, stronger, freer, and more secure than before. Four years ago we began to change, forever I hope, our assumptions about government and its place in our lives. Out of that change has come great and robust growth-in our confidence, our economy, and our role in the world. Tonight America is stronger because of the values that we hold dear. We believe faith and freedom must be our guiding stars, for they show us truth, they make us brave, give us hope, and leave us wiser than we were. Our progress began not in Washington, DC, but in the hearts of our families, communities, workplaces, and voluntary groups which, together, are unleashing the invincible spirit of one great nation under God. Four years ago we said we would invigorate our economy by giving people greater freedom and incentives to take risks and letting them keep more of what they earned. We did what we promised, and a great industrial giant is reborn. Tonight we can take pride in 25 straight months of economic growth, the strongest in 34 years; a 3-year inflation average of 3.9 percent, the lowest in 17 years; and 7.3 million new jobs in 2 years, with more of our citizens working than ever before. New freedom in our lives has planted the rich seeds for future success: For an America of wisdom that honors the family, knowing that if the family goes, so goes our civilization; For an America of vision that sees tomorrow's dreams in the learning and hard work we do today; For an America of courage whose service men and women, even as we meet, proudly stand watch on the frontiers of freedom; For an America of compassion that opens its heart to those who cry out for help. We have begun well. But it's only a beginning. We're not here to congratulate ourselves on what we have done but to challenge ourselves to finish what has not yet been done. We're here to speak for millions in our inner cities who long for real jobs, safe neighborhoods, and schools that truly teach. We're here to speak for the American farmer, the entrepreneur, and every worker in industries fighting to modernize and compete. And, yes, we're here to stand, and proudly so, for all who struggle to break free from totalitarianism, for all who know in their hearts that freedom is the one true path to peace and human happiness. Proverbs tell us, without a vision the people perish. When asked what great principle holds our Union together, Abraham Lincoln said: "Something in Declaration giving liberty, not alone to the people of this country, but hope to the world for all future time." We honor the giants of our history not by going back but forward to the dreams their vision foresaw. My fellow citizens, this nation is poised for greatness. The time has come to proceed toward a great new challenge—a second American Revolution of hope and opportunity; a revolution carrying us to new heights of progress by pushing back frontiers of knowledge and space; a revolution of spirit that taps the soul of America, enabling us to summon greater strength than we've ever known; and a revolution that carries beyond our shores the golden promise of human freedom in a world of peace. Let us begin by challenging our conventional wisdom. There are no constraints on the human mind, no walls around the human spirit, no barriers to our progress except those we ourselves erect. Already, pushing down tax rates has freed our economy to vault forward to record growth. In Europe, they're calling it "the American Miracle." Day by day, we're shattering accepted notions of what is possible. When I was growing up, we failed to see how a new thing called radio would transform our marketplace. Well, today, many have not yet seen how advances in technology are transforming our lives. In the late 1950's workers at the AT&T semiconductor plant in Pennsylvania produced five transistors a day for $7.50 apiece. They now produce over a million for less than a penny apiece. New laser techniques could revolutionize heart bypass surgery, cut diagnosis time for viruses linked to cancer from weeks to minutes, reduce hospital costs dramatically, and hold out new promise for saving human lives. Our automobile industry has overhauled assembly lines, increased worker productivity, and is competitive once again. We stand on the threshold of a great ability to produce more, do more, be more. Our economy is not getting older and weaker; it's getting younger and stronger. It doesn't need rest and supervision; it needs new challenge, greater freedom. And that word "freedom" is the key to the second American revolution that we need to bring about. Let us move together with an historic reform of tax simplification for fairness and growth. Last year I asked Treasury Secretary-then-Regan to develop a plan to simplify the tax code, so all taxpayers would be treated more fairly and personal tax rates could come further down. We have cut tax rates by almost 25 percent, yet the tax system remains unfair and limits our potential for growth. Exclusions and exemptions cause similar incomes to be taxed at different levels. Low-income families face steep tax barriers that make hard lives even harder. The Treasury Department has produced an excellent reform plan, whose principles will guide the final proposal that we will ask you to enact. One thing that tax reform will not be is a tax increase in disguise. We will not jeopardize the mortgage interest deduction that families need. We will reduce personal tax rates as low as possible by removing many tax preferences. We will propose a top rate of no more than 35 percent, and possibly lower. And we will propose reducing corporate rates, while maintaining incentives for capital formation. To encourage opportunity and jobs rather than dependency and welfare, we will propose that individuals living at or near the poverty line be totally exempt from Federal income tax. To restore fairness to families, we will propose increasing significantly the personal exemption. And tonight, I am instructing Treasury Secretary James Baker—I have to get used to saying that—to begin working with congressional authors and committees for bipartisan legislation conforming to these principles. We will call upon the American people for support and upon every man and woman in this Chamber. Together, we can pass, this year, a tax bill for fairness, simplicity, and growth, making this economy the engine of our dreams and America the investment capital of the world. So let us begin. Tax simplification will be a giant step toward unleashing the tremendous pent-up power of our economy. But a second American revolution must carry the promise of opportunity for all. It is time to liberate the spirit of enterprise in the most distressed areas of our country. This government will meet its responsibility to help those in need. But policies that increase dependency, break up families, and destroy self-respect are not progressive; they're reactionary. Despite our strides in civil rights, blacks, Hispanics, and all minorities will not have full and equal power until they have full economic power. We have repeatedly sought passage of enterprise zones to help those in the abandoned corners of our land find jobs, learn skills, and build better lives. This legislation is supported by a majority of you. Mr. Speaker, I know we agree that 'there must be no forgotten Americans. Let us place new dreams in a million hearts and create a new generation of entrepreneurs by passing enterprise zones this year. And, Tip, you could make that a birthday present. Nor must we lose the chance to pass our youth employment opportunity wage proposal. We can help teenagers, who have the highest unemployment rate, find summer jobs, so they can know the pride of work and have confidence in their futures. We'll continue to support the Job Training Partnership Act, which has a nearly two-thirds job placement rate. Credits in education and health care vouchers will help working families shop for services that they need. Our administration is already encouraging certain low-income public housing residents to own and manage their own dwellings. It's time that all public housing residents have that opportunity of ownership. The Federal Government can help create a new atmosphere of freedom. But States and localities, many of which enjoy surpluses from the recovery, must not permit their tax and regulatory policies to stand as barriers to growth. Let us resolve that we will stop spreading dependency and start spreading opportunity; that we will stop spreading bondage and start spreading freedom. There are some who say that growth initiatives must await final action on deficit reductions. Well, the best way to reduce deficits is through economic growth. More businesses will be started, more investments made, more jobs created, and more people will be on payrolls paying taxes. The best way to reduce government spending is to reduce the need for spending by increasing prosperity. Each added percentage point per year of real GNP growth will lead to cumulative reduction in deficits of nearly $200 billion over 5 years. To move steadily toward a balanced budget, we must also lighten government's claim on our total economy. We will not do this by raising taxes. We must make sure that our economy grows faster than the growth in spending by the Federal Government. In our fiscal year 1986 budget, overall government program spending will be frozen at the current level. It must not be one dime higher than fiscal year 1985, and three points are key. First, the social safety net for the elderly, the needy, the disabled, and unemployed will be left intact. Growth of our major health care programs, Medicare and Medicaid, will be slowed, but protections for the elderly and needy will be preserved. Second, we must not relax our efforts to restore military strength just as we near our goal of a fully equipped, trained, and ready professional corps. National security is government's first responsibility; so in past years defense spending took about half the Federal budget. Today it takes less than a third. We've already reduced our planned defense expenditures by nearly a hundred billion dollars over the past 4 years and reduced projected spending again this year. You know, we only have a military-industrial complex until a time of danger, and then it becomes the arsenal of democracy. Spending for defense is investing in things that are priceless—peace and freedom. Third, we must reduce or eliminate costly government subsidies. For example, deregulation of the airline industry has led to cheaper airfares, but on Amtrak taxpayers pay about $35 per passenger every time an Amtrak train leaves the station, It's time we ended this huge Federal subsidy. Our farm program costs have quadrupled in recent years. Yet I know from visiting farmers, many in great financial distress, that we need an orderly transition to a market-oriented farm economy. We can help farmers best not by expanding Federal payments but by making fundamental reforms, keeping interest rates heading down, and knocking down foreign trade barriers to American farm exports. We're moving ahead with Grace commission reforms to eliminate waste and improve government's management practices. In the long run, we must protect the taxpayers from government. And I ask again that you pass, as 32 States have now called for, an amendment mandating the Federal Government spend no more than it takes in. And I ask for the authority, used responsibly by 43 Governors, to veto individual items in appropriation bills. Senator Mattingly has introduced a bill permitting a 2-year trial run of the line-item veto. I hope you'll pass and send that legislation to my desk. Nearly 50 years of government living beyond its means has brought us to a time of reckoning. Ours is but a moment in history. But one moment of courage, idealism, and bipartisan unity can change American history forever. Sound monetary policy is key to long-running economic strength and stability. We will continue to cooperate with the Federal Reserve Board, seeking a steady policy that ensures price stability without keeping interest rates artificially high or needlessly holding down growth. Reducing unneeded red tape and regulations, and deregulating the energy, transportation, and financial industries have unleashed new competition, giving consumers more choices, better services, and lower prices. In just one set of grant programs we have reduced 905 pages of regulations to 31. We seek to fully deregulate natural gas to bring on new supplies and bring us closer to energy independence. Consistent with safety standards, we will continue removing restraints on the bus and railroad industries, we will soon end up legislation—or send up legislation, I should say—to return Conrail to the private sector where it belongs, and we will support further deregulation of the trucking industry. Every dollar the Federal Government does not take from us, every decision it does not make for us will make our economy stronger, our lives more abundant, our future more free. Our second American revolution will push on to new possibilities not only on Earth but in the next frontier of space. Despite budget restraints, we will seek record funding for research and development. We've seen the success of the space shuttle. Now we're going to develop a permanently manned space station and new opportunities for free enterprise, because in the next decade Americans and our friends around the world will be living and working together in space. In the zero gravity of space, we could manufacture in 30 days lifesaving medicines it would take 30 years to make on Earth. We can make crystals of exceptional purity to produce super computers, creating jobs, technologies, and medical breakthroughs beyond anything we ever dreamed possible. As we do all this, we'll continue to protect our natural resources. We will seek reauthorization and expanded funding for the Superfund program to continue cleaning up hazardous waste sites which threaten human health and the environment. Now, there's another great heritage to speak of this evening. Of all the changes that have swept America the past 4 years, none brings greater promise than our rediscovery of the values of faith, freedom, family, work, and neighborhood. We see signs of renewal in increased attendance in places of worship; renewed optimism and faith in our future; love of country rediscovered by our young, who are leading the way. We've rediscovered that work is good in and of itself, that it ennobles us to create and contribute no matter how seemingly humble our jobs. We've seen a powerful new current from an old and honorable tradition—American generosity. From thousands answering Peace Corps appeals to help boost food production in Africa, to millions volunteering time, corporations adopting schools, and communities pulling together to help the neediest among us at home, we have refound our values. Private sector initiatives are crucial to our future. I thank the Congress for passing equal access legislation giving religious groups the same right to use classrooms after school that other groups enjoy. But no citizen need tremble, nor the world shudder, if a child stands in a classroom and breathes a prayer. We ask you again, give children back a right they had for a century and a half or more in this country. The question of abortion grips our nation. Abortion is either the taking of a human life or it isn't. And if it is—and medical technology is increasingly showing it is—it must be stopped. It is a terrible irony that while some turn to abortion, so many others who cannot become parents cry out for children to adopt. We have room for these children. We can fill the cradles of those who want a child to love. And tonight I ask you in the Congress to move this year on legislation to protect the unborn. In the area of education, we're returning to excellence, and again, the heroes are our people, not government. We're stressing basics of discipline, rigorous testing, and homework, while helping children become computer-smart as well. For 20 years scholastic aptitude test scores of our high school students went down, but now they have gone up 2 of the last 3 years. We must go forward in our commitment to the new basics, giving parents greater authority and making sure good teachers are rewarded for hard work and achievement through merit pay. Of all the changes in the past 20 years, none has more threatened our sense of national well-being than the explosion of violent crime. One does not have to be attacked to be a victim. The woman who must run to her car after shopping at night is a victim. The couple draping their door with locks and chains are victims; as is the tired, decent cleaning woman who can't ride a subway home without being afraid. We do not seek to violate the rights of defendants. But shouldn't we feel more compassion for the victims of crime than for those who commit crime? For the first time in 20 years, the crime index has fallen 2 years in a row. We've convicted over 7,400 drug offenders and put them, as well as leaders of organized crime, behind bars in record numbers. But we must do more. I urge the House to follow the Senate and enact proposals permitting use of all reliable evidence that police officers acquire in good faith. These proposals would also reform the habeas corpus laws and allow, in keeping with the will of the overwhelming majority of Americans, the use of the death penalty where necessary. There can be no economic revival in ghettos when the most violent among us are allowed to roam free. It's time we restored domestic tranquility. And we mean to do just that. Just as we're positioned as never before to secure justice in our economy, we're poised as never before to create a safer, freer, more peaceful world. Our alliances are stronger than ever. Our economy is stronger than ever. We have resumed our historic role as a leader of the free world. And all of these together are a great force for peace. Since 1981 we've been committed to seeking fair and verifiable arms agreements that would lower the risk of war and reduce the size of nuclear arsenals. Now our determination to maintain a strong defense has influenced the Soviet Union to return to the bargaining table. Our negotiators must be able to go to that table with the united support of the American people. All of us have no greater dream than to see the day when nuclear weapons are banned from this Earth forever. Each Member of the Congress has a role to play in modernizing our defenses, thus supporting our chances for a meaningful arms agreement. Your vote this spring on the Peacekeeper missile will be a critical test of our resolve to maintain the strength we need and move toward mutual and verifiable arms reductions. For the past 20 years we've believed that no war will be launched as long as each side knows it can retaliate with a deadly counterstrike. Well, I believe there's a better way of eliminating the threat of nuclear war. It is a Strategic Defense Initiative aimed ultimately at finding a nonnuclear defense against ballistic missiles. It's the most hopeful possibility of the nuclear age. But it's not very well understood. Some say it will bring war to the heavens, but its purpose is to deter war in the heavens and on Earth. Now, some say the research would be expensive. Perhaps, but it could save millions of lives, indeed humanity itself. And some say if we build such a system, the Soviets will build a defense system of their own. Well, they already have strategic defenses that surpass ours; a civil defense system, where we have almost none; and a research program covering roughly the same areas of technology that we're now exploring. And finally some say the research will take a long time. Well, the answer to that is: Let's get started. Harry Truman once said that, ultimately, our security and the world's hopes for peace and human progress "lie not in measures of defense or in the control of weapons, but in the growth and expansion of freedom and self-government." And tonight, we declare anew to our fellow citizens of the world: Freedom is not the sole prerogative of a chosen few; it is the universal right of all God's children. Look to where peace and prosperity flourish today. It is in homes that freedom built. Victories against poverty are greatest and peace most secure where people live by laws that ensure free press, free speech, and freedom to worship, vote, and create wealth. Our mission is to nourish and defend freedom and democracy, and to communicate these ideals everywhere we can. America's economic success is freedom's success; it can be repeated a hundred times in a hundred different nations. Many countries in east Asia and the Pacific have few resources other than the enterprise of their own people. But through low tax rates and free markets they've soared ahead of centralized economies. And now China is opening up its economy to meet its needs. We need a stronger and simpler approach to the process of making and implementing trade policy, and we'll be studying potential changes in that process in the next few weeks. We've seen the benefits of free trade and lived through the disasters of protectionism. Tonight I ask all our trading partners, developed and developing alike, to join us in a new round of trade negotiations to expand trade and competition and strengthen the global economy—and to begin it in this next year. There are more than 3 billion human beings living in Third World countries with an average per capita income of $650 a year. Many are victims of dictatorships that impoverished them with taxation and corruption. Let us ask our allies to join us in a practical program of trade and assistance that fosters economic development through personal incentives to help these people climb from poverty on their own. We cannot play innocents abroad in a world that's not innocent; nor can we be passive when freedom is under siege. Without resources, diplomacy cannot succeed. Our security assistance programs help friendly governments defend themselves and give them confidence to work for peace. And I hope that you in the Congress will understand that, dollar for dollar, security assistance contributes as much to global security as our own defense budget. We must stand by all our democratic allies. And we must not break faith with those who are risking their lives—on every continent, from Afghanistan to Nicaragua—to defy Soviet-supported aggression and secure rights which have been ours from birth. The Sandinista dictatorship of Nicaragua, with full Cuban-Soviet bloc support, not only persecutes its people, the church, and denies a free press, but arms and provides bases for Communist terrorists attacking neighboring states. Support for freedom fighters is self-defense and totally consistent with the OAS and U.N. Charters. It is essential that the Congress continue all facets of our assistance to Central America. I want to work with you to support the democratic forces whose struggle is tied to our own security. And tonight, I've spoken of great plans and great dreams. They're dreams we can make come true. Two hundred years of American history should have taught us that nothing is impossible. Ten years ago a young girl left Vietnam with her family, part of the exodus that followed the fall of Saigon. They came to the United States with no possessions and not knowing a word of English. Ten years ago—the young girl studied hard, learned English, and finished high school in the top of her class. And this May, May 22d to be exact, is a big date on her calendar. Just 10 years from the time she left Vietnam, she will graduate from the United States Military Academy at West Point. I thought you might like to meet an American hero named Jean Nguyen. Now, there's someone else here tonight, born 79 years ago. She lives in the inner city, where she cares for infants born of mothers who are heroin addicts. The children, born in withdrawal, are sometimes even dropped on her doorstep. She helps them with love. Go to her house some night, and maybe you'll see her silhouette against the window as she walks the floor talking softly, soothing a child in her arms-Mother Hale of Harlem, and she, too, is an American hero. Jean, Mother Hale, your lives tell us that the oldest American saying is new again: Anything is possible in America if we have the faith, the will, and the heart. History is asking us once again to be a force for good in the world. Let us begin in unity, with justice, and love. Thank you, and God bless you. """ import phrasemachine phrases = phrasemachine.get_phrases(text) print "%s phrase types" % len(phrases['counts']) print "%s phrase hits" % sum(phrases['counts'].values()) print "Top phrases:" print phrases['counts'].most_common(10) print "From crappy tokenization:" crappy_tokens = text.split() print phrasemachine.get_phrases(tokens=crappy_tokens)['counts'].most_common(10) print "Phrase spans" phrases = phrasemachine.get_phrases(text, output=['token_spans','tokens']) print "%s phrase hits" % len(phrases['token_spans']) print phrases['token_spans'][:20] print phrases['token_spans'][-20:] print "First several phrase hits" print [(s,e, phrases['tokens'][s:e]) for (s,e) in phrases['token_spans'][:10]] print "From crappy tokenization" xx = phrasemachine.get_phrases(tokens=crappy_tokens, output='token_spans')['token_spans'] print [(s,e, crappy_tokens[s:e]) for (s,e) in xx[:10]]

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py

Python

tests/conftest.py

testdrivenio/django-performance-testing

e41494ebc5a7e698a34e6c383f4055b42a0e16a9

[ "MIT" ]

6

2020-03-30T13:16:24.000Z

2022-02-03T21:26:18.000Z

tests/conftest.py

testdrivenio/django-performance-testing

e41494ebc5a7e698a34e6c383f4055b42a0e16a9

[ "MIT" ]

3

2021-06-09T17:43:48.000Z

2022-02-10T07:48:28.000Z

tests/conftest.py

testdrivenio/django-performance-testing

e41494ebc5a7e698a34e6c383f4055b42a0e16a9

[ "MIT" ]

2

2020-02-26T21:02:22.000Z

2020-11-14T16:55:17.000Z

from django.conf import settings def pytest_configure(config): settings.NPLUSONE_RAISE = True

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py

Python

tests/testdata.py

bousquf/okta-cli

8073ee171bd0ae690f087fa8f3260cbd24cefbda

[ "MIT" ]

28

2019-02-10T00:10:36.000Z

2022-03-02T14:33:36.000Z

tests/testdata.py

bousquf/okta-cli

8073ee171bd0ae690f087fa8f3260cbd24cefbda

[ "MIT" ]

9

2020-03-27T03:39:08.000Z

2021-12-03T21:09:57.000Z

tests/testdata.py

bousquf/okta-cli

8073ee171bd0ae690f087fa8f3260cbd24cefbda

[ "MIT" ]

11

2019-04-30T06:26:41.000Z

2022-02-06T03:41:31.000Z

_perms_self_read_only = [ { "principal": "SELF", "action": "READ_ONLY" } ] _perms_self_read_write = [ { "principal": "SELF", "action": "READ_WRITE" } ] _perms_self_hide = [ { "principal": "SELF", "action": "HIDE" } ] # a dump of an okta user schema with some example # properties (int, bool) okta_user_schema = { "id": "https://paracelsus.okta.com/meta/schemas/user/default", "$schema": "http://json-schema.org/draft-04/schema#", "name": "user", "title": "User", "description": "Okta user profile template with default permission settings", "lastUpdated": "2019-02-04T14:38:16.000Z", "created": "2018-07-23T08:46:45.000Z", "definitions": { "custom": { "id": "#custom", "type": "object", "properties": { "abool": { "title": "A bool", "description": "A boolean variable", "type": "boolean", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "anint": { "title": "An int", "description": "An integer value", "type": "integer", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, }, }, "base": { "id": "#base", "type": "object", "properties": { "login": { "title": "Username", "type": "string", "required": True, "mutability": "READ_WRITE", "scope": "NONE", "minLength": 5, "maxLength": 100, "pattern": ".+", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "firstName": { "title": "First name", "type": "string", "required": True, "mutability": "READ_WRITE", "scope": "NONE", "minLength": 1, "maxLength": 50, "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "lastName": { "title": "Last name", "type": "string", "required": True, "mutability": "READ_WRITE", "scope": "NONE", "minLength": 1, "maxLength": 50, "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "middleName": { "title": "Middle name", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "honorificPrefix": { "title": "Honorific prefix", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "honorificSuffix": { "title": "Honorific suffix", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "email": { "title": "Primary email", "type": "string", "required": True, "format": "email", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "title": { "title": "Title", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "displayName": { "title": "Display name", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "nickName": { "title": "Nickname", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "profileUrl": { "title": "Profile Url", "type": "string", "format": "uri", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "secondEmail": { "title": "Secondary email", "type": "string", "format": "email", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "mobilePhone": { "title": "Mobile phone", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "maxLength": 100, "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "primaryPhone": { "title": "Primary phone", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "maxLength": 100, "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "streetAddress": { "title": "Street address", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_hide, "master": {"type": "PROFILE_MASTER"} }, "city": { "title": "City", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_hide, "master": {"type": "PROFILE_MASTER"} }, "state": { "title": "State", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_hide, "master": {"type": "PROFILE_MASTER"} }, "zipCode": { "title": "Zip code", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_hide, "master": {"type": "PROFILE_MASTER"} }, "countryCode": { "title": "Country code", "type": "string", "format": "country-code", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_hide, "master": {"type": "PROFILE_MASTER"} }, "postalAddress": { "title": "Postal Address", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_hide, "master": {"type": "PROFILE_MASTER"} }, "preferredLanguage": { "title": "Preferred language", "type": "string", "format": "language-code", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "locale": { "title": "Locale", "type": "string", "format": "locale", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "timezone": { "title": "Time zone", "type": "string", "format": "timezone", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "userType": { "title": "User type", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "employeeNumber": { "title": "Employee number", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "costCenter": { "title": "Cost center", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "organization": { "title": "Organization", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "division": { "title": "Division", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "department": { "title": "Department", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_write, "master": {"type": "PROFILE_MASTER"} }, "managerId": { "title": "ManagerId", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} }, "manager": { "title": "Manager", "type": "string", "mutability": "READ_WRITE", "scope": "NONE", "permissions": _perms_self_read_only, "master": {"type": "PROFILE_MASTER"} } }, "required": [ "login", "firstName", "lastName", "email" ] } }, "type": "object", "properties": { "profile": { "allOf": [ { "$ref": "#/definitions/custom" }, { "$ref": "#/definitions/base" } ] } } } okta_groups_list = [ { "id": "group1", "created": "2018-09-13T12:51:16.000Z", "lastUpdated": "2018-10-17T12:00:38.000Z", "lastMembershipUpdated": "2019-01-16T08:48:12.000Z", "objectClass": [ "okta:user_group" ], "type": "OKTA_GROUP", "profile": { "name": "Group One", "description": "" }, "_links": { "logo": [ { "name": "medium", "href": "https://some.logo", "type": "image/png" }, { "name": "large", "href": "https://some_large.logo", "type": "image/png" } ], "users": {"href": "http://okta/api/v1/groups/group1/users"}, "apps": {"href": "http://okta/api/v1/groups/group1/apps"}, } }, { "id": "group2", "created": "2018-09-13T12:51:16.000Z", "lastUpdated": "2018-10-17T12:00:38.000Z", "lastMembershipUpdated": "2019-01-16T08:48:12.000Z", "objectClass": [ "okta:user_group" ], "type": "OKTA_GROUP", "profile": { "name": "Group Two", "description": "" }, "_links": { "logo": [ { "name": "medium", "href": "https://some.logo", "type": "image/png" }, { "name": "large", "href": "https://some_large.logo", "type": "image/png" } ], "users": {"href": "http://okta/api/v1/groups/group2/users"}, "apps": {"href": "http://okta/api/v1/groups/group2/apps"}, } }, { "id": "group3", "created": "2018-09-13T12:51:16.000Z", "lastUpdated": "2018-10-17T12:00:38.000Z", "lastMembershipUpdated": "2019-01-16T08:48:12.000Z", "objectClass": [ "okta:user_group" ], "type": "OKTA_GROUP", "profile": { "name": "Group 3", "description": "" }, "_links": { "logo": [ { "name": "medium", "href": "https://some.logo", "type": "image/png" }, { "name": "large", "href": "https://some_large.logo", "type": "image/png" } ], "users": {"href": "http://okta/api/v1/groups/group3/users"}, "apps": {"href": "http://okta/api/v1/groups/group3/apps"}, } }, ]

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outputformat/__init__.py

JuPeg/outputformat

bfbb659a05edeb57bf3049ed3836b4842e5a8af0

[ "MIT" ]

146

2021-12-30T12:57:22.000Z

2022-03-30T08:14:53.000Z

outputformat/__init__.py

JuPeg/outputformat

bfbb659a05edeb57bf3049ed3836b4842e5a8af0

[ "MIT" ]

1

2022-01-03T19:03:41.000Z

outputformat/__init__.py

JuPeg/outputformat

bfbb659a05edeb57bf3049ed3836b4842e5a8af0

[ "MIT" ]

6

2021-12-30T16:01:47.000Z

2022-02-23T08:31:39.000Z

from outputformat.title import boxtitle from outputformat.title import linetitle from outputformat.title import bigtitle from outputformat.list import showlist from outputformat.plot import bar from outputformat.plot import barlist from outputformat.dict import showdict from outputformat.misc import br from outputformat.misc import b from outputformat.color import c from outputformat.color import rainbow

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e8474ee4171b46a0e1537b469c5c84d93f9697f2

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py

Python

PacManTaro/create_app.py

SomHackathon2020/somhackathon2020-pacmantaro

9fb3fb83ada72fa043e61d2c44b8b02f14cbe60a

[ "MIT" ]

3

2020-02-09T10:56:49.000Z

2020-02-09T12:14:26.000Z

PacManTaro/create_app.py

SomHackathon2020/somhackathon2020-pacmantaro

9fb3fb83ada72fa043e61d2c44b8b02f14cbe60a

[ "MIT" ]

null

PacManTaro/create_app.py

SomHackathon2020/somhackathon2020-pacmantaro

9fb3fb83ada72fa043e61d2c44b8b02f14cbe60a

[ "MIT" ]

null

from __init__ import db, create_app db.create_all(app=create_app())

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null

0

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5

e8572a7e02a2e363db2073ce95c9ebce16c8e8ac

83

py

Python

stf_utils/common/exceptions.py

z00sts/stf-utils

844c38145a82614872b35d9771dde45e7d7d083c

[ "MIT" ]

52

2016-04-01T02:43:26.000Z

2022-02-18T08:36:45.000Z

stf_utils/common/exceptions.py

z00sts/stf-utils

844c38145a82614872b35d9771dde45e7d7d083c

[ "MIT" ]

44

2016-03-22T05:02:17.000Z

2019-09-06T15:43:37.000Z

stf_utils/common/exceptions.py

z00sts/stf-utils

844c38145a82614872b35d9771dde45e7d7d083c

[ "MIT" ]

23

2016-03-21T10:55:45.000Z

2021-05-25T01:17:56.000Z

class APIException(Exception): pass class ADBException(Exception): pass

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1

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null

0

1

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5

e86be447d4493428f150f2a567444f15ac87df09

347

py

Python

tests/test_bboxformat.py

tensorturtle/rebox

8835f4d2482aff7d2d0852930bdbbdf49320a8d3

[ "MIT" ]

13

2021-10-19T01:46:22.000Z

2022-03-23T19:13:30.000Z

tests/test_bboxformat.py

tensorturtle/rebox

8835f4d2482aff7d2d0852930bdbbdf49320a8d3

[ "MIT" ]

3

2021-08-08T13:18:51.000Z

2021-08-10T10:06:25.000Z

tests/test_bboxformat.py

tensorturtle/bboxconvert

8835f4d2482aff7d2d0852930bdbbdf49320a8d3

[ "MIT" ]

2

2021-07-27T03:06:48.000Z

2022-01-24T10:19:46.000Z

import pytest from rebox import BBoxFormat @pytest.fixture def example_format(): return BBoxFormat("XYXY", 10) def test_style(example_format): assert example_format.style == "XYXY" def test_scale(example_format): assert example_format.scale == 10 def test_is_relative(example_format): assert example_format.is_relative == True

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0

1

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1

0

5

e86d7bb7adc6a7573c9402851337b42bd4d3d8ca

248

py

Python

website_project/admin.py

jakubpliszka/website_project

de6925253fe5397b584086f1b9acc86532301d68

[ "MIT" ]

null

website_project/admin.py

jakubpliszka/website_project

de6925253fe5397b584086f1b9acc86532301d68

[ "MIT" ]

null

website_project/admin.py

jakubpliszka/website_project

de6925253fe5397b584086f1b9acc86532301d68

[ "MIT" ]

null

from django.contrib import admin from website_project.models import ArrivalFlight, DepartureFlight, Destination # Register your models here. admin.site.register(DepartureFlight) admin.site.register(ArrivalFlight) admin.site.register(Destination)

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0

5

e86e63a4a80e6a28ae6f42c9ba80c7fe0b2213a8

775

py

Python

ecojunk/core/api/permissions.py

PIN-UPV/EcoJunkWebServer

53a42687c303ffe345f59dc1f11fa41c3526f6d7

[ "MIT" ]

1

2018-10-02T11:54:26.000Z

ecojunk/core/api/permissions.py

PIN-UPV/EcoJunkWebServer

53a42687c303ffe345f59dc1f11fa41c3526f6d7

[ "MIT" ]

8

2018-10-03T08:02:39.000Z

2018-11-21T07:42:26.000Z

ecojunk/core/api/permissions.py

PIN-UPV/EcoJunkWebServer

53a42687c303ffe345f59dc1f11fa41c3526f6d7

[ "MIT" ]

1

2018-10-02T11:54:32.000Z

from rest_framework import permissions class NoDeletes(permissions.BasePermission): """Doesn't allow deletes for the resource.""" def has_permission(self, request, view): if request.method == "DELETE": return False return True def has_object_permission(self, request, view, obj): if request.method == "DELETE": return False return True class NoUpdates(permissions.BasePermission): """Doesn't allow updates for the resource.""" def has_permission(self, request, view): if request.method == "PATCH": return False return True def has_object_permission(self, request, view, obj): if request.method == "PATCH": return False return True

25.833333

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775

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e89a1bbf4a2114a81baaa2b55241d82bf24d2c9d

47

py

Python

pyUSID/__version__.py

sulaymandesai/pyUSID

fa4d152856e4717c92b1fbe34222eb2e1c042707

[ "MIT" ]

null

pyUSID/__version__.py

sulaymandesai/pyUSID

fa4d152856e4717c92b1fbe34222eb2e1c042707

[ "MIT" ]

null

pyUSID/__version__.py

sulaymandesai/pyUSID

fa4d152856e4717c92b1fbe34222eb2e1c042707

[ "MIT" ]

null

version = '0.0.9' time = '2020-09-17 11:20:25'

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1

0

1

0

null

0

5

e8a7c97d7015452b6c76ca3374e54172089b338e

234

py

Python

qulab/db/query.py

liuqichun3809/quantum-lab

05bea707b314ea1687866f56ee439079336cfbbc

[ "MIT" ]

3

2020-08-30T16:11:49.000Z

2021-03-05T12:09:30.000Z

qulab/db/query.py

liuqichun3809/quantum-lab

05bea707b314ea1687866f56ee439079336cfbbc

[ "MIT" ]

null

qulab/db/query.py

liuqichun3809/quantum-lab

05bea707b314ea1687866f56ee439079336cfbbc

[ "MIT" ]

2

2019-07-24T15:12:31.000Z

2019-09-20T02:17:28.000Z

from .schema.app import getApplication, listApplication from .schema.code_mod import getModuleByFullname from .schema.drv_inst import getInstrumentByName from .schema.record import query_records from .schema.user import getUserByName

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null

0

1

0

1

0

5

e8d00bb66182638b8928e3dc7e618036a28233c3

43

py

Python

tests/__init__.py

ziv1234/python-dynalite-devices

870daea2e540973fb913afdfff8425dae546708a

[ "MIT" ]

3

2020-04-23T09:03:19.000Z

2021-12-07T15:33:20.000Z

tests/__init__.py

ziv1234/python-dynalite-devices

870daea2e540973fb913afdfff8425dae546708a

[ "MIT" ]

3

2021-02-23T14:02:18.000Z

2022-03-03T07:22:22.000Z

tests/__init__.py

ziv1234/python-dynalite-devices

870daea2e540973fb913afdfff8425dae546708a

[ "MIT" ]

3

2020-05-05T05:08:22.000Z

2022-01-05T04:31:53.000Z

"""Testing for Dynalite Communications."""

21.5

42

0.744186

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1

43

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1

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1

0

null

0

1

0

5

2cf1e8de55bdfecda5f2b91f609ae0da92575b9d

376

py

Python

create_bumblebee_app.py

Omarzintan/bumblebee-ai

0b8c5cecf032730e23b1b710a88538f5e4ea70c9

[ "MIT" ]

3

2021-05-06T16:29:26.000Z

2022-01-09T03:32:40.000Z

create_bumblebee_app.py

Omarzintan/bumblebee-ai

0b8c5cecf032730e23b1b710a88538f5e4ea70c9

[ "MIT" ]

1

2021-05-20T17:59:12.000Z

create_bumblebee_app.py

Omarzintan/bumblebee-ai

0b8c5cecf032730e23b1b710a88538f5e4ea70c9

[ "MIT" ]

null

from helpers import bumblebee_root, python3_path with open("bumblebee_app", "w") as file: file.write("#!/bin/sh\n") file.write("export BUMBLEBEE_PATH="+bumblebee_root+"\n") file.write("export PYTHON3_PATH="+python3_path+"\n") file.write("export SERVER_URL=http://127.0.0.1:5000\n") file.write("\n") file.write("$PYTHON3_PATH $BUMBLEBEE_PATH/main.py")

37.6

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61

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1

0

null

0

1

0

5

fa0ad380650fa790ff534a87b82e7be4358d7c0f

145

py

Python

general/admin.py

ma1VAR3/Enhanced-Noticeboard

cef224ab4754989923db15bb800e982a0a30c1ae

[ "MIT" ]

null

general/admin.py

ma1VAR3/Enhanced-Noticeboard

cef224ab4754989923db15bb800e982a0a30c1ae

[ "MIT" ]

null

general/admin.py

ma1VAR3/Enhanced-Noticeboard

cef224ab4754989923db15bb800e982a0a30c1ae

[ "MIT" ]

2

2021-02-01T03:05:29.000Z

2021-02-02T04:42:27.000Z

from django.contrib import admin # Register your models here. from .models import Event,FAQ admin.site.register(Event) admin.site.register(FAQ)

20.714286

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null

0

1

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1

0

5

fa2190ac4ee159b0e2ddd16c61b8c63c789a139a

109

py

Python

hubspot/crm/association_type.py

fakepop/hubspot-api-python

f04103a09f93f5c26c99991b25fa76801074f3d3

[ "Apache-2.0" ]

117

2020-04-06T08:22:53.000Z

2022-03-18T03:41:29.000Z

hubspot/crm/association_type.py

fakepop/hubspot-api-python

f04103a09f93f5c26c99991b25fa76801074f3d3

[ "Apache-2.0" ]

62

2020-04-06T16:21:06.000Z

2022-03-17T16:50:44.000Z

hubspot/crm/association_type.py

fakepop/hubspot-api-python

f04103a09f93f5c26c99991b25fa76801074f3d3

[ "Apache-2.0" ]

45

2020-04-06T16:13:52.000Z

2022-03-30T21:33:17.000Z

class AssociationType: COMPANY_TO_CONTACT = "company_to_contact" CONTACT_TO_DEAL = "contact_to_deal"

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fa65e75f27a4ac7b777e06372c0c91e439eb9abc

59

py

Python

malaya_speech/train/model/fastspeechsplit/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

111

2020-08-31T04:58:54.000Z

2022-03-29T15:44:18.000Z

malaya_speech/train/model/fastspeechsplit/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

14

2020-12-16T07:27:22.000Z

2022-03-15T17:39:01.000Z

malaya_speech/train/model/fastspeechsplit/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

29

2021-02-09T08:57:15.000Z

2022-03-12T14:09:19.000Z

from .model import Model, Model_F0 from . import inference

19.666667

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true

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0

5

d7013a02b214517ac16dac7f4d8c27e152c81b58

60

py

Python

nemo/backends/pytorch/torchvision/__init__.py

vsl9/NeMo

4137c2b4e3cba0ec5ca1da7b58b3ff97fdb25e50

[ "Apache-2.0" ]

10

2020-03-17T08:32:06.000Z

2021-04-19T19:03:50.000Z

nemo/backends/pytorch/torchvision/__init__.py

vsl9/NeMo

4137c2b4e3cba0ec5ca1da7b58b3ff97fdb25e50

[ "Apache-2.0" ]

3

2020-11-13T17:45:41.000Z

2022-03-12T00:28:59.000Z

nemo/backends/pytorch/torchvision/__init__.py

vsl9/NeMo

4137c2b4e3cba0ec5ca1da7b58b3ff97fdb25e50

[ "Apache-2.0" ]

3

2020-03-10T05:10:07.000Z

2020-12-08T01:33:35.000Z

20

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0

1

0

1

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5

d7066adff8f44144c2c2ad35f9b1b288b372772f

11,257

py

Python

RankBasedMonteCarlo/Methods.py

tazzben/RankBasedMonteCarlo

1471891668ef545950a966085e8afd0582f6dd9b

[ "MIT" ]

null

RankBasedMonteCarlo/Methods.py

tazzben/RankBasedMonteCarlo

1471891668ef545950a966085e8afd0582f6dd9b

[ "MIT" ]

null

RankBasedMonteCarlo/Methods.py

tazzben/RankBasedMonteCarlo

1471891668ef545950a966085e8afd0582f6dd9b

[ "MIT" ]

null

import numpy import pandas import sys import multiprocessing class _RankBasedMonteCarlo: def _RandomRank(self, ns): objects = numpy.concatenate( [numpy.repeat((i + 1), n) for i, n in enumerate(ns)], axis=None ) numpy.random.shuffle(objects) return pandas.DataFrame({"Group": objects.tolist(),}).assign( Rank=range(1, objects.size + 1) ) def _RandomStatistic(self, sampleSizes): sample = self._RandomRank(sampleSizes) return self._CalculateStatistic(sample) def _PoolMonteCarlo(self, ns, reps): p = multiprocessing.Pool() r = [] for i, result in enumerate( p.imap_unordered(self._RandomStatistic, (ns,) * reps) ): r.append(result) sys.stderr.write("\r{: .2f}% done".format(100 * i / reps)) p.close() p.join() return numpy.array(r) def _CalculateStatistic(self, sample): return sample["Rank"].median() def PrintCriticalValueTable( self, ns, reps=10000, observedValue=None, PrintToScreen=True, cvs=[0.01, 0.025, 0.05, 0.1], reverseDist=False, ): """ Prints the critical values and p-value, if an observed test statistic is supplied. The method returns a dictionary of critical values and p-value as a tuple. Parameters ---------- ns : tuple A tuple listing the number of observations per group. For instance (6,5) reps : int The number of repetitions the process completes before producing critical values. Default is 10,000. observedValue : float Optional value used to determine p-value PrintToScreen : bool Specifies if the critical values are printed to the screen. Defaults to True. cvs : list Specifies a list of critical values. reviseDist : bool Parameter to reverse the direction of the null distribution for the purposes of calculating p-values. Defaults to standard. Returns _______ criticalValues : dictionary A dictionary of critical values corresponding to the specified parameter list. pvalue : float or None The p-value of the observedValue specified in the parameter list (None if unspecified). """ r = self._PoolMonteCarlo(ns, reps) cvresults = [] for i in cvs: qvalue = numpy.quantile(r, i) cvresults.append(qvalue) if PrintToScreen: print( "\n" + pandas.DataFrame( zip(cvs, cvresults), columns=["Quantile", "Critical Value"] ).to_string(index=False) ) try: observedValue = float(observedValue) pvalue = ( len(r[(r > observedValue)]) / reps if reverseDist else len(r[(r < observedValue)]) / reps ) if PrintToScreen: print( "Percent of distribution " + ("above" if reverseDist else "below") + " the observed value:" + "{: .4f}".format(pvalue) ) return (dict(zip(cvs, cvresults)), pvalue) except: return (dict(zip(cvs, cvresults)), None) class MonteCarloKolmogorovSmirnov(_RankBasedMonteCarlo): """ Calculates the null hypothesis distribution of the two sample Kolmogorov-Smirnov test """ def _CalculateStatistic(self, sample): n1len = len(sample[sample["Group"] == 1].index) n2len = len(sample[sample["Group"] == 2].index) return numpy.array( [ numpy.abs( len(sample[((sample["Group"] == 1) & (sample["Rank"] <= x))].index) / n1len - len( sample[((sample["Group"] == 2) & (sample["Rank"] <= x))].index ) / n2len ) for x in sample["Rank"] ] ).max() def PrintCriticalValueTable( self, ns, reps=10000, observedValue=None, PrintToScreen=True, cvs=[0.9, 0.95, 0.975, 0.99], reverseDist=True, ): """ Prints the critical values and p-value, if an observed test statistic is supplied. The method returns a dictionary of critical values and p-value as a tuple. Parameters ---------- ns : tuple A tuple listing the number of observations per group. For instance (6,5) reps : int The number of repetitions the process completes before producing critical values. Default is 10,000. observedValue : float Optional value used to determine p-value PrintToScreen : bool Specifies if the critical values are printed to the screen. Defaults to True. cvs : list Specifies a list of critical values. reviseDist : bool Parameter to reverse the direction of the null distribution for the purposes of calculating p-values. Defaults to standard. Returns _______ criticalValues : dictionary A dictionary of critical values corresponding to the specified parameter list. pvalue : float or None The p-value of the observedValue specified in the parameter list (None if unspecified). """ return super().PrintCriticalValueTable( ns, reps, observedValue, PrintToScreen, cvs, reverseDist ) class MonteCarloKuiper(_RankBasedMonteCarlo): """ Calculates the null hypothesis distribution of the two sample Kuiper test """ def _CalculateStatistic(self, sample): n1len = len(sample[sample["Group"] == 1].index) n2len = len(sample[sample["Group"] == 2].index) dPos = numpy.array( [ len(sample[((sample["Group"] == 1) & (sample["Rank"] <= x))].index) / n1len - len(sample[((sample["Group"] == 2) & (sample["Rank"] <= x))].index) / n2len for x in sample["Rank"] ] ).max() dNeg = numpy.array( [ len(sample[((sample["Group"] == 2) & (sample["Rank"] <= x))].index) / n2len - len(sample[((sample["Group"] == 1) & (sample["Rank"] <= x))].index) / n1len for x in sample["Rank"] ] ).max() return dPos + dNeg def PrintCriticalValueTable( self, ns, reps=10000, observedValue=None, PrintToScreen=True, cvs=[0.9, 0.95, 0.975, 0.99], reverseDist=True, ): """ Prints the critical values and p-value, if an observed test statistic is supplied. The method returns a dictionary of critical values and p-value as a tuple. Parameters ---------- ns : tuple A tuple listing the number of observations per group. For instance (6,5) reps : int The number of repetitions the process completes before producing critical values. Default is 10,000. observedValue : float Optional value used to determine p-value PrintToScreen : bool Specifies if the critical values are printed to the screen. Defaults to True. cvs : list Specifies a list of critical values. reviseDist : bool Parameter to reverse the direction of the null distribution for the purposes of calculating p-values. Defaults to standard. Returns _______ criticalValues : dictionary A dictionary of critical values corresponding to the specified parameter list. pvalue : float or None The p-value of the observedValue specified in the parameter list (None if unspecified). """ return super().PrintCriticalValueTable( ns, reps, observedValue, PrintToScreen, cvs, reverseDist ) class MonteCarloMannWhitney(_RankBasedMonteCarlo): """ Calculates the null hypothesis distribution of the Mann-Whitney test """ def _CalculateStatistic(self, sample): n1len = len(sample[sample["Group"] == 1].index) U1 = sample[sample["Group"] == 1]["Rank"].sum() - (n1len * (n1len + 1)) / 2 return U1 class MonteCarloKruskalWallis(_RankBasedMonteCarlo): """ Calculates the null hypothesis distribution of the Kruskal–Wallis test """ def _CalculateStatistic(self, sample): n = len(sample.index) rbar = 0.5 * (n + 1) divisor = 0 numerator = 0 for group in pandas.unique(sample["Group"]): grouplen = len(sample[sample["Group"] == group].index) groupmean = sample[sample["Group"] == group]["Rank"].mean() divisor += numpy.array( [ numpy.power((x - rbar), 2) for x in sample[sample["Group"] == group]["Rank"] ] ).sum() numerator += grouplen * numpy.power((groupmean - rbar), 2) return ((n - 1) * numerator) / divisor def PrintCriticalValueTable( self, ns, reps=10000, observedValue=None, PrintToScreen=True, cvs=[0.9, 0.95, 0.975, 0.99], reverseDist=True, ): """ Prints the critical values and p-value, if an observed test statistic is supplied. The method returns a dictionary of critical values and p-value as a tuple. Parameters ---------- ns : tuple A tuple listing the number of observations per group. For instance (6,5) reps : int The number of repetitions the process completes before producing critical values. Default is 10,000. observedValue : float Optional value used to determine p-value PrintToScreen : bool Specifies if the critical values are printed to the screen. Defaults to True. cvs : list Specifies a list of critical values. reviseDist : bool Parameter to reverse the direction of the null distribution for the purposes of calculating p-values. Defaults to standard. Returns _______ criticalValues : dictionary A dictionary of critical values corresponding to the specified parameter list. pvalue : float or None The p-value of the observedValue specified in the parameter list (None if unspecified). """ return super().PrintCriticalValueTable( ns, reps, observedValue, PrintToScreen, cvs, reverseDist )

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Python

deepdab/ai/__init__.py

lantunes/deepdab

0e30f102b9d7c37d3691540496b1649f2704d586

[ "Apache-2.0" ]

1

2019-04-04T02:26:51.000Z

deepdab/ai/__init__.py

lantunes/deepdab

0e30f102b9d7c37d3691540496b1649f2704d586

[ "Apache-2.0" ]

null

deepdab/ai/__init__.py

lantunes/deepdab

0e30f102b9d7c37d3691540496b1649f2704d586

[ "Apache-2.0" ]

null

from .tabular_policy import * from .td0_policy import * from .td1_tabular_policy import * from .td1_gradient_policy import * from .td1_gradient_policy_v2 import * from .td1_gradient_policy_cnn import * from .td1_gradient_policy_linear_v2 import * from .td1_gradient_policy_mlp_v2 import * from .td1_gradient_policy_cnn_v2 import * from .td1_gradient_policy_cnn_v2b import * from .td1_gradient_policy_cnn_v2c import * from .td1_gradient_policy_cnn_v2d import * from .td1_gradient_3x3_policy_cnn_v2 import * from .level1_heuristic_policy import * from .level2_heuristic_policy import * from .causal_entropic_policy import * from .pg_policy_cnn import * from .mcts_game import * from .mcts_policy import * from .mcts_policy2 import * from .mcts_root_parallel_policy import * from .pg_policy_cnn2 import * from .pg_policy_mcts_cnn2 import * from .pg_policy_3x3_cnn import * from .mcts_policy_net_policy import * from .mcts_policy_net_policy_cpuct import * from .pg_policy_cnn3 import * from .pg_policy_cnn4 import * from .pg_policy_cnn2_adversarial import * from .pg_policy_cnn2b import * from .sl_value_3x3_cnn import * from .pg_policy_3x3_cnn_5layer import *

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d78d417a9946e184ad415d5e1948b6b670534e75

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py

Python

pyeccodes/defs/grib2/tables/local/ecmf/4/1_2_table.py

ecmwf/pyeccodes

dce2c72d3adcc0cb801731366be53327ce13a00b

[ "Apache-2.0" ]

7

2020-04-14T09:41:17.000Z

2021-08-06T09:38:19.000Z

pyeccodes/defs/grib2/tables/local/ecmf/4/1_2_table.py

ecmwf/pyeccodes

dce2c72d3adcc0cb801731366be53327ce13a00b

[ "Apache-2.0" ]

null

pyeccodes/defs/grib2/tables/local/ecmf/4/1_2_table.py

ecmwf/pyeccodes

dce2c72d3adcc0cb801731366be53327ce13a00b

[ "Apache-2.0" ]

3

2020-04-30T12:44:48.000Z

2020-12-15T08:40:26.000Z

def load(h): return ({'abbr': 191, 'code': 191, 'title': 'funny reference time'},)

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py

Python

src/test/resources/python-code-examples/throw_return.py

florayym/depends

6c437a78268d91d54059b560c0273ae3c9253452

[ "BSD-3-Clause", "MIT" ]

146

2019-03-09T03:02:59.000Z

2022-03-28T11:28:41.000Z

src/test/resources/python-code-examples/throw_return.py

florayym/depends

6c437a78268d91d54059b560c0273ae3c9253452

[ "BSD-3-Clause", "MIT" ]

27

2019-03-11T02:12:54.000Z

2021-12-21T00:24:13.000Z

src/test/resources/python-code-examples/throw_return.py

florayym/depends

6c437a78268d91d54059b560c0273ae3c9253452

[ "BSD-3-Clause", "MIT" ]

41

2019-03-09T03:04:50.000Z

2022-01-14T06:53:14.000Z

class Bar(): pass def t1(): raise Bar() def t2(): return Bar()

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ad26491c3ba25dfdfa993b707c490b7194c94836

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py

Python

test.py

T-Terra/password-manager

87df40dbdb8d9e24b1e20ef40c2db8a55a64890c

[ "MIT" ]

null

test.py

T-Terra/password-manager

87df40dbdb8d9e24b1e20ef40c2db8a55a64890c

[ "MIT" ]

null

test.py

T-Terra/password-manager

87df40dbdb8d9e24b1e20ef40c2db8a55a64890c

[ "MIT" ]

null

from lib.screen import screen_insert screen_insert()

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ad2e3ad0758b96b25bd669d36e9eeb2f333fee03

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py

Python

tests/conftest.py

reinhard-mueller/webargs

907a394762403ab4309bc950c93e19eafb92806e

[ "MIT" ]

601

2015-01-02T20:56:39.000Z

2018-12-27T00:41:15.000Z

tests/conftest.py

reinhard-mueller/webargs

907a394762403ab4309bc950c93e19eafb92806e

[ "MIT" ]

219

2018-12-27T22:21:05.000Z

2022-03-17T16:19:35.000Z

tests/conftest.py

reinhard-mueller/webargs

907a394762403ab4309bc950c93e19eafb92806e

[ "MIT" ]

104

2015-02-03T18:20:00.000Z

2018-12-17T08:11:34.000Z

import pytest pytest.register_assert_rewrite("webargs.testing")

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py

Python

pyrovision/models/__init__.py

frgfm/pyronear

9dd063ac958a5c5e96815bb31c8f75b62ce026e7

[ "Apache-2.0" ]

9

2019-10-01T08:37:49.000Z

2020-05-11T03:58:52.000Z

pyrovision/models/__init__.py

frgfm/pyronear

9dd063ac958a5c5e96815bb31c8f75b62ce026e7

[ "Apache-2.0" ]

71

2019-09-20T18:45:33.000Z

2020-06-01T15:45:26.000Z

pyrovision/models/__init__.py

frgfm/pyronear

9dd063ac958a5c5e96815bb31c8f75b62ce026e7

[ "Apache-2.0" ]

14

2019-09-24T15:19:27.000Z

2020-05-01T14:40:12.000Z

from .resnet import * from .mobilenetv3 import * from .rexnet import *

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py

Python

labnote/__init__.py

LiorZ/labnote

d3732e8ce6414796c1631ac009147e7488012066

[ "BSD-2-Clause-FreeBSD" ]

19

2017-02-23T04:02:54.000Z

2021-02-04T12:34:57.000Z

labnote/__init__.py

LiorZ/labnote

d3732e8ce6414796c1631ac009147e7488012066

[ "BSD-2-Clause-FreeBSD" ]

1

2019-03-06T23:27:46.000Z

labnote/__init__.py

LiorZ/labnote

d3732e8ce6414796c1631ac009147e7488012066

[ "BSD-2-Clause-FreeBSD" ]

4

2017-06-16T03:47:44.000Z

2022-02-18T03:40:49.000Z

""" labnote """ __version__ = 0.9 from labnote.notebook import Notebook from labnote.entry import Entry from labnote.categories import CategoryManager

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py

Python

didyprog/_allennlp/modules/__init__.py

minhnhat93/didyprog

78886ed939d269b9b2bcb192bf849aa34082880c

[ "MIT" ]

57

2018-07-11T09:02:12.000Z

2022-03-16T03:47:19.000Z

didyprog/_allennlp/modules/__init__.py

minhnhat93/didyprog

78886ed939d269b9b2bcb192bf849aa34082880c

[ "MIT" ]

7

2018-11-27T08:07:58.000Z

2020-06-04T21:45:47.000Z

didyprog/_allennlp/modules/__init__.py

minhnhat93/didyprog

78886ed939d269b9b2bcb192bf849aa34082880c

[ "MIT" ]

18

2018-07-11T08:32:26.000Z

2022-03-07T07:45:00.000Z

from .conditional_random_field import ConditionalRandomField

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py

Python

core/models/icnet/__init__.py

matthew-wave/pool

698c140d161f369ef6a198dec9ab8b91a4532fa8

[ "MIT" ]

6

2020-04-17T10:13:28.000Z

2020-10-13T08:16:32.000Z

core/models/icnet/__init__.py

matthew-wave/pool

698c140d161f369ef6a198dec9ab8b91a4532fa8

[ "MIT" ]

null

core/models/icnet/__init__.py

matthew-wave/pool

698c140d161f369ef6a198dec9ab8b91a4532fa8

[ "MIT" ]

1

2021-05-14T08:11:08.000Z

from core.models.icnet.icnet import get_icnet

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a8ed4715c858b6835ad6c7261c815e718240b999

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py

Python

graphql/execution/experimental/tests/skip_test_resolver.py

phil303/graphql-core

f983e19cc8cd818275621e2909fb485cf227fe0c

[ "MIT" ]

null

graphql/execution/experimental/tests/skip_test_resolver.py

phil303/graphql-core

f983e19cc8cd818275621e2909fb485cf227fe0c

[ "MIT" ]

null

graphql/execution/experimental/tests/skip_test_resolver.py

phil303/graphql-core

f983e19cc8cd818275621e2909fb485cf227fe0c

[ "MIT" ]

1

2020-01-17T00:41:46.000Z

import mock import pytest from promise import Promise from ....error import GraphQLError, GraphQLLocatedError from ....language import ast from ....type import (GraphQLEnumType, GraphQLField, GraphQLInt, GraphQLInterfaceType, GraphQLList, GraphQLNonNull, GraphQLObjectType, GraphQLScalarType, GraphQLSchema, GraphQLString, GraphQLUnionType) from ..fragment import Fragment from ..resolver import field_resolver, type_resolver @pytest.mark.parametrize("type,value,expected", [ (GraphQLString, 1, "1"), (GraphQLInt, "1", 1), (GraphQLNonNull(GraphQLString), 0, "0"), (GraphQLNonNull(GraphQLInt), 0, 0), (GraphQLList(GraphQLString), [1, 2], ['1', '2']), (GraphQLList(GraphQLInt), ['1', '2'], [1, 2]), (GraphQLList(GraphQLNonNull(GraphQLInt)), [0], [0]), (GraphQLNonNull(GraphQLList(GraphQLInt)), [], []), ]) def test_type_resolver(type, value, expected): resolver = type_resolver(type, lambda: value) resolved = resolver() assert resolved == expected @pytest.mark.parametrize("type,value,expected", [ (GraphQLString, 1, "1"), (GraphQLInt, "1", 1), (GraphQLNonNull(GraphQLString), 0, "0"), (GraphQLNonNull(GraphQLInt), 0, 0), (GraphQLList(GraphQLString), [1, 2], ['1', '2']), (GraphQLList(GraphQLInt), ['1', '2'], [1, 2]), (GraphQLList(GraphQLNonNull(GraphQLInt)), [0], [0]), (GraphQLNonNull(GraphQLList(GraphQLInt)), [], []), ]) def test_type_resolver_promise(type, value, expected): promise_value = Promise() resolver = type_resolver(type, lambda: promise_value) resolved_promise = resolver() assert not resolved_promise.is_fulfilled promise_value.fulfill(value) assert resolved_promise.is_fulfilled resolved = resolved_promise.get() assert resolved == expected def raises(): raise Exception("raises") def test_resolver_exception(): info = mock.MagicMock() with pytest.raises(GraphQLLocatedError): resolver = type_resolver(GraphQLString, raises, info=info) resolver() def test_field_resolver_mask_exception(): info = mock.MagicMock() exe_context = mock.MagicMock() exe_context.errors = [] field = GraphQLField(GraphQLString, resolver=raises) resolver = field_resolver(field, info=info, exe_context=exe_context) resolved = resolver() assert resolved is None assert len(exe_context.errors) == 1 assert str(exe_context.errors[0]) == 'raises' def test_nonnull_field_resolver_mask_exception(): info = mock.MagicMock() info.parent_type = 'parent_type' info.field_name = 'field_name' exe_context = mock.MagicMock() exe_context.errors = [] field = GraphQLField(GraphQLNonNull(GraphQLString), resolver=raises) resolver = field_resolver(field, info=info, exe_context=exe_context) with pytest.raises(GraphQLLocatedError) as exc_info: resolver() assert str(exc_info.value) == 'raises' def test_nonnull_field_resolver_fails_on_null_value(): info = mock.MagicMock() info.parent_type = 'parent_type' info.field_name = 'field_name' exe_context = mock.MagicMock() exe_context.errors = [] field = GraphQLField(GraphQLNonNull(GraphQLString), resolver=lambda *_: None) resolver = field_resolver(field, info=info, exe_context=exe_context) with pytest.raises(GraphQLError) as exc_info: resolver() assert str(exc_info.value) == 'Cannot return null for non-nullable field parent_type.field_name.' def test_nonnull_list_field_resolver_fails_silently_on_null_value(): info = mock.MagicMock() info.parent_type = 'parent_type' info.field_name = 'field_name' exe_context = mock.MagicMock() exe_context.errors = [] field = GraphQLField(GraphQLList(GraphQLNonNull(GraphQLString)), resolver=lambda *_: ['1', None]) resolver = field_resolver(field, info=info, exe_context=exe_context) assert resolver() is None assert len(exe_context.errors) == 1 assert str(exe_context.errors[0]) == 'Cannot return null for non-nullable field parent_type.field_name.' def test_nonnull_list_field_resolver_fails_on_null_value_top(): from ....pyutils.default_ordered_dict import DefaultOrderedDict from ...base import collect_fields DataType = GraphQLObjectType('DataType', { 'nonNullString': GraphQLField(GraphQLNonNull(GraphQLString), resolver=lambda *_: None), }) info = mock.MagicMock() info.parent_type = 'parent_type' info.field_name = 'field_name' exe_context = mock.MagicMock() exe_context.errors = [] field = GraphQLField(GraphQLNonNull(DataType), resolver=lambda *_: 1) selection_set = ast.SelectionSet(selections=[ ast.Field( name=ast.Name(value='nonNullString'), ) ]) field_asts = collect_fields( exe_context, DataType, selection_set, DefaultOrderedDict(list), set() ) # node_fragment = Fragment(type=Node, field_asts=node_field_asts) datetype_fragment = Fragment(type=DataType, field_asts=field_asts, context=exe_context) resolver = field_resolver(field, info=info, exe_context=exe_context, fragment=datetype_fragment) with pytest.raises(GraphQLError) as exc_info: resolver() assert not exe_context.errors assert str(exc_info.value) == 'Cannot return null for non-nullable field parent_type.field_name.' def test_nonnull_list_field_resolver_fails_on_null_value_top(): from ....pyutils.default_ordered_dict import DefaultOrderedDict from ...base import collect_fields DataType = GraphQLObjectType('DataType', { 'nonNullString': GraphQLField(GraphQLString, resolver=lambda *_: None), }) info = mock.MagicMock() info.parent_type = 'parent_type' info.field_name = 'field_name' exe_context = mock.MagicMock() exe_context.errors = [] field = GraphQLField(GraphQLNonNull(DataType), resolver=lambda *_: 1) selection_set = ast.SelectionSet(selections=[ ast.Field( name=ast.Name(value='nonNullString'), ) ]) field_asts = collect_fields( exe_context, DataType, selection_set, DefaultOrderedDict(list), set() ) # node_fragment = Fragment(type=Node, field_asts=node_field_asts) datetype_fragment = Fragment(type=DataType, field_asts=field_asts, context=exe_context) resolver = field_resolver(field, info=info, exe_context=exe_context, fragment=datetype_fragment) data = resolver() assert data == { 'nonNullString': None }

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d1227ce50816f79af00187566cf0ea6040d361f6

189

py

Python

mathmatical_indunction.py

mushahidmehdi/MITx-6.00.1x

44a1b9bb87b5feb8d5a5ac7a8dec59e689dab5be

[ "MIT" ]

null

mathmatical_indunction.py

mushahidmehdi/MITx-6.00.1x

44a1b9bb87b5feb8d5a5ac7a8dec59e689dab5be

[ "MIT" ]

null

mathmatical_indunction.py

mushahidmehdi/MITx-6.00.1x

44a1b9bb87b5feb8d5a5ac7a8dec59e689dab5be

[ "MIT" ]

null

# for a given numbers of array # for example 1+2+3+4+5+6.........+n = (n(n+1))/2 # Semierly, assume! # for n = 0 LHS ====> 0 ------> (0(1+0))/2 == 0 # k(k+1)/2 +(k+2) == ((k+1)(k+1))/2

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d14810782ac0ccf118cb7e93cf79bf0c47129c8d

106

py

Python

lib/protocols/__init__.py

PetterKraabol/vigilate-lopy

ef82171ab5a662faf528d7df9ebf7f1f09776758

[ "MIT" ]

null

lib/protocols/__init__.py

PetterKraabol/vigilate-lopy

ef82171ab5a662faf528d7df9ebf7f1f09776758

[ "MIT" ]

null

lib/protocols/__init__.py

PetterKraabol/vigilate-lopy

ef82171ab5a662faf528d7df9ebf7f1f09776758

[ "MIT" ]

null

from .protocol import Protocol from .http import HTTP from .lorawan import LoRaWAN from .uart import UART

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d168c0b0fa29bccf4d1d2b8b6835092eb7bdce31

199

py

Python

Network_and_802.11/scapy/route.py

hacky1997/My-Gray-Hacker-Resources

e9b10ac7b0e557a9e624a5a6e761f9af4488d777

[ "MIT" ]

14

2017-06-14T06:10:07.000Z

2019-02-22T03:21:15.000Z

Network_and_802.11/scapy/route.py

rookie-12/My-Gray-Hacker-Resources

e9b10ac7b0e557a9e624a5a6e761f9af4488d777

[ "MIT" ]

1

2021-04-30T21:19:32.000Z

Network_and_802.11/scapy/route.py

rookie-12/My-Gray-Hacker-Resources

e9b10ac7b0e557a9e624a5a6e761f9af4488d777

[ "MIT" ]

7

2015-10-01T09:47:05.000Z

2022-01-21T14:25:37.000Z

#!/usr/bin/env python __author__ = "bt3" from scapy.all import * print conf.route conf.route.add(host='192.168.118.2', gw='192.168.1.114') print conf.route conf.route.resync() print conf.route

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0f05f8df0a1a8b68694335b994001089e2868124

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py

Python

pysnobal/tests/__init__.py

scotthavens/pysnobal

9cff1e6cb2f1da4240132af4e1d2f5740092d2ef

[ "CC0-1.0" ]

1

2022-01-26T16:47:44.000Z

pysnobal/tests/__init__.py

scotthavens/pysnobal

9cff1e6cb2f1da4240132af4e1d2f5740092d2ef

[ "CC0-1.0" ]

null

pysnobal/tests/__init__.py

scotthavens/pysnobal

9cff1e6cb2f1da4240132af4e1d2f5740092d2ef

[ "CC0-1.0" ]

1

2022-02-08T22:31:27.000Z

"""Unit test package for pysnobal."""

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py

Python

tests/unit/__init__.py

hdiogenes/flow_manager

29cacaca73b1c044b47abfced1740705b0b2d1b2

[ "MIT" ]

null

tests/unit/__init__.py

hdiogenes/flow_manager

29cacaca73b1c044b47abfced1740705b0b2d1b2

[ "MIT" ]

79

2017-10-04T17:47:19.000Z

2021-05-30T21:38:19.000Z

tests/unit/__init__.py

hdiogenes/flow_manager

29cacaca73b1c044b47abfced1740705b0b2d1b2

[ "MIT" ]

15

2017-10-05T13:07:51.000Z

2021-06-01T12:16:27.000Z

"""kytos/flow_manager unit tests."""

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null

0

1

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5

0f2c7d6b734963d1aa294bfb2c282e55d7f45049

127

py

Python

app/image_path_finder.py

nvllsvm/Tuatara

d681c33480d321b901f153e8348a4a812b33999c

[ "MIT" ]

null

app/image_path_finder.py

nvllsvm/Tuatara

d681c33480d321b901f153e8348a4a812b33999c

[ "MIT" ]

null

app/image_path_finder.py

nvllsvm/Tuatara

d681c33480d321b901f153e8348a4a812b33999c

[ "MIT" ]

null

from config import image_directory def main(filename): filename = image_directory + filename + '.jpg' return filename

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7e15170668fe1df794116050824010aac1a744ee

178

py

Python

topics/topic_3/8_testing_system.py

VladBaryliuk/my_trainings

10c4bf2147c361ab918c591577a076b0d276ede0

[ "Apache-2.0" ]

null

topics/topic_3/8_testing_system.py

VladBaryliuk/my_trainings

10c4bf2147c361ab918c591577a076b0d276ede0

[ "Apache-2.0" ]

null

topics/topic_3/8_testing_system.py

VladBaryliuk/my_trainings

10c4bf2147c361ab918c591577a076b0d276ede0

[ "Apache-2.0" ]

null

def testing_system(right_answer, Iras_answer): if right_answer == Iras_answer: print("YES") else: print("NO") testing_system(int(input()), int(input()))

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1

0

1

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7e244b1fceff6cfc40dbff642054b1e68a302a54

178

py

Python

vinhos/filters.py

LucasPanao/vinho

1b94a5475e76fcf6efa90cf2e55de82530704f96

[ "MIT" ]

null

vinhos/filters.py

LucasPanao/vinho

1b94a5475e76fcf6efa90cf2e55de82530704f96

[ "MIT" ]

null

vinhos/filters.py

LucasPanao/vinho

1b94a5475e76fcf6efa90cf2e55de82530704f96

[ "MIT" ]

null

import django_filters from .models import Vinhos class VinhoFilter(django_filters.FilterSet): class Meta: model = Vinhos fields = ['nome_vinho', 'tipo_vinho']

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7e345d956ce3a7a8060b5b6ef4375878432424fa

98

py

Python

run_preprocessing.py

PervasiveWellbeingTech/inquire-web-backend

0a078943701472897c288ca1f2683ed749685e92

[ "Apache-2.0" ]

1

2020-10-07T09:35:47.000Z

run_preprocessing.py

PervasiveWellbeingTech/inquire-web-backend

0a078943701472897c288ca1f2683ed749685e92

[ "Apache-2.0" ]

1

2021-06-02T03:08:57.000Z

run_preprocessing.py

PervasiveWellbeingTech/inquire-web-backend

0a078943701472897c288ca1f2683ed749685e92

[ "Apache-2.0" ]

null

from raw_preprocessing.preprocessor import run_parse if __name__ == '__main__': run_parse(10)

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7e74f8a96f8fd4cf427dc7c53233b12ecc13a54e

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py

Python

glidernet_scraper/ogn/ddb/__init__.py

i4nf0x/soarspy

1beb21267c0d8bb8afb75e60bdc4399978144f09

[ "Apache-2.0" ]

null

glidernet_scraper/ogn/ddb/__init__.py

i4nf0x/soarspy

1beb21267c0d8bb8afb75e60bdc4399978144f09

[ "Apache-2.0" ]

null

glidernet_scraper/ogn/ddb/__init__.py

i4nf0x/soarspy

1beb21267c0d8bb8afb75e60bdc4399978144f09

[ "Apache-2.0" ]

null

from ogn.ddb.utils import get_ddb_devices # noqa: F401

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7ea2c9fd000462d8cfa48f59adde1a960878e449

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py

Python

mmdeploy/apis/onnx/__init__.py

grimoire/mmdeploy

e84bc30f4a036dd19cb3af854203922a91098e84

[ "Apache-2.0" ]

746

2021-12-27T10:50:28.000Z

2022-03-31T13:34:14.000Z

mmdeploy/apis/onnx/__init__.py

grimoire/mmdeploy

e84bc30f4a036dd19cb3af854203922a91098e84

[ "Apache-2.0" ]

253

2021-12-28T05:59:13.000Z

2022-03-31T18:22:25.000Z

mmdeploy/apis/onnx/__init__.py

grimoire/mmdeploy

e84bc30f4a036dd19cb3af854203922a91098e84

[ "Apache-2.0" ]

147

2021-12-27T10:50:33.000Z

2022-03-30T10:44:20.000Z

26.5

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7eb708a80d2a8dcfb2340bbf079c30e2f6f313a0

226

py

Python

worlds_worst_serverless/worlds_worst_mapper/guidelines.py

nigelmathes/worlds-worst-serverless

3f46474ce3da7e85671b6e988f2c55e8cee1554f

[ "MIT" ]

null

worlds_worst_serverless/worlds_worst_mapper/guidelines.py

nigelmathes/worlds-worst-serverless

3f46474ce3da7e85671b6e988f2c55e8cee1554f

[ "MIT" ]

11

2020-01-28T23:04:13.000Z

2021-06-06T02:49:23.000Z

worlds_worst_serverless/worlds_worst_mapper/guidelines.py

nigelmathes/worlds-worst-serverless

3f46474ce3da7e85671b6e988f2c55e8cee1554f

[ "MIT" ]

null

ACTIONS_MAP = { "attack": "do_combat", "area": "do_combat", "block": "do_combat", "disrupt": "do_combat", "dodge": "do_combat", "change character": "change_class", "change class": "change_class", }

22.6

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9

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null

1

0

1

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null

0

5

0e4568e6997978f64fee850ce9c9ed7e73a1e467

48

py

Python

dbsl/lib/util/__init__.py

wezacon/DBSL.py

1d9ce5a66f8f24f5b992bca9712ad73daac194b4

[ "MIT" ]

null

dbsl/lib/util/__init__.py

wezacon/DBSL.py

1d9ce5a66f8f24f5b992bca9712ad73daac194b4

[ "MIT" ]

null

dbsl/lib/util/__init__.py

wezacon/DBSL.py

1d9ce5a66f8f24f5b992bca9712ad73daac194b4

[ "MIT" ]

null

from .objects import * from .exceptions import *

24

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null

0

1

0

1

0

5

7eda5b41db0fedc1e6d8440285168a921567160b

179

py

Python

tests/test_manage.py

ptpedroj/hotelapi

5d5eb588b3cd95bff0afdc13cd233fc13cfd7626

[ "FSFAP" ]

null

tests/test_manage.py

ptpedroj/hotelapi

5d5eb588b3cd95bff0afdc13cd233fc13cfd7626

[ "FSFAP" ]

null

tests/test_manage.py

ptpedroj/hotelapi

5d5eb588b3cd95bff0afdc13cd233fc13cfd7626

[ "FSFAP" ]

null

import hotelapi.manage as mgr class TestSettings: def test_app(self): assert hasattr(mgr, "app") def test_manager(self): assert hasattr(mgr, "manager")

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adcc104d838edef5a55185e80a7f8d2af94edd20

181

py

Python

hyperparameter_optimization.py

shomikverma/chemprop

ddaa874fe1f6ef4fbdf6b980c3157bed2ae85faa

[ "MIT" ]

689

2020-02-14T20:22:33.000Z

2022-03-31T13:45:09.000Z

hyperparameter_optimization.py

shomikverma/chemprop

ddaa874fe1f6ef4fbdf6b980c3157bed2ae85faa

[ "MIT" ]

214

2020-02-23T19:54:15.000Z

2022-03-30T21:47:06.000Z

hyperparameter_optimization.py

shomikverma/chemprop

ddaa874fe1f6ef4fbdf6b980c3157bed2ae85faa

[ "MIT" ]

296

2020-02-14T15:39:13.000Z

2022-03-28T16:27:17.000Z

"""Optimizes hyperparameters using Bayesian optimization.""" from chemprop.hyperparameter_optimization import chemprop_hyperopt if __name__ == '__main__': chemprop_hyperopt()

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5

adee65faba20d83d162feaa8214d419a109d2a41

206

py

Python

jobapp/admin.py

GyaniSherlock/Home-Service-Job-Portal

9d6fee66ec18387f786d28c0862c8eedd8835487

[ "MIT" ]

null

jobapp/admin.py

GyaniSherlock/Home-Service-Job-Portal

9d6fee66ec18387f786d28c0862c8eedd8835487

[ "MIT" ]

null

jobapp/admin.py

GyaniSherlock/Home-Service-Job-Portal

9d6fee66ec18387f786d28c0862c8eedd8835487

[ "MIT" ]

null

from django.contrib import admin from .models import * # Register your models here. admin.site.register(Category) admin.site.register(Applicant) admin.site.register(Job) admin.site.register(BookmarkJob)

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adf5526edc2f8e5c750577cc31fcba06fd7d2a2a

137

py

Python

opps/api/admin.py

jeanmask/opps

031c6136c38d43aa6d1ccb25a94f7bcd65ccbf87

[ "MIT" ]

159

2015-01-03T16:36:35.000Z

2022-03-29T20:50:13.000Z

opps/api/admin.py

jeanmask/opps

031c6136c38d43aa6d1ccb25a94f7bcd65ccbf87

[ "MIT" ]

81

2015-01-02T21:26:16.000Z

2021-05-29T12:24:52.000Z

opps/api/admin.py

jeanmask/opps

031c6136c38d43aa6d1ccb25a94f7bcd65ccbf87

[ "MIT" ]

75

2015-01-23T13:41:03.000Z

2021-09-24T03:45:23.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- from django.contrib import admin from .models import ApiKey admin.site.register(ApiKey)

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bc203ec44495b1a5d07ee3fd4120ce00b2cb798c

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py

Python

boa3_test/tests/compiler_tests/test_bytes.py

DanPopa46/neo3-boa

e4ef340744b5bd25ade26f847eac50789b97f3e9

[ "Apache-2.0" ]

null

boa3_test/tests/compiler_tests/test_bytes.py

DanPopa46/neo3-boa

e4ef340744b5bd25ade26f847eac50789b97f3e9

[ "Apache-2.0" ]

null

boa3_test/tests/compiler_tests/test_bytes.py

DanPopa46/neo3-boa

e4ef340744b5bd25ade26f847eac50789b97f3e9

[ "Apache-2.0" ]

null

import unittest from boa3.boa3 import Boa3 from boa3.exception.CompilerError import MismatchedTypes, NotSupportedOperation, UnresolvedOperation from boa3.neo.vm.opcode.Opcode import Opcode from boa3.neo.vm.type.Integer import Integer from boa3_test.tests.boa_test import BoaTest from boa3_test.tests.test_classes.TestExecutionException import TestExecutionException from boa3_test.tests.test_classes.testengine import TestEngine class TestBytes(BoaTest): default_folder: str = 'test_sc/bytes_test' def test_bytes_literal_value(self): data = b'\x01\x02\x03' expected_output = ( Opcode.INITSLOT # function signature + b'\x01' + b'\x00' + Opcode.PUSHDATA1 # a = b'\x01\x02\x03' + Integer(len(data)).to_byte_array(min_length=1) + data + Opcode.STLOC0 + Opcode.RET # return ) path = self.get_contract_path('BytesLiteral.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) def test_bytes_get_value(self): expected_output = ( Opcode.INITSLOT # function signature + b'\x00' + b'\x01' + Opcode.LDARG0 # arg[0] + Opcode.PUSH0 + Opcode.DUP + Opcode.SIGN + Opcode.PUSHM1 + Opcode.JMPNE + Integer(5).to_byte_array(min_length=1, signed=True) + Opcode.OVER + Opcode.SIZE + Opcode.ADD + Opcode.PICKITEM + Opcode.RET # return ) path = self.get_contract_path('BytesGetValue.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', bytes([1, 2, 3])) self.assertEqual(1, result) result = self.run_smart_contract(engine, path, 'Main', b'0') self.assertEqual(48, result) def test_bytes_get_value_negative_index(self): expected_output = ( Opcode.INITSLOT # function signature + b'\x00' + b'\x01' + Opcode.LDARG0 # arg[0] + Opcode.PUSHM1 + Opcode.DUP + Opcode.SIGN + Opcode.PUSHM1 + Opcode.JMPNE + Integer(5).to_byte_array(min_length=1, signed=True) + Opcode.OVER + Opcode.SIZE + Opcode.ADD + Opcode.PICKITEM + Opcode.RET # return ) path = self.get_contract_path('BytesGetValueNegativeIndex.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', bytes([1, 2, 3])) self.assertEqual(3, result) result = self.run_smart_contract(engine, path, 'Main', b'0') self.assertEqual(48, result) def test_bytes_set_value(self): path = self.get_contract_path('BytesSetValue.py') self.assertCompilerLogs(UnresolvedOperation, path) def test_bytes_clear(self): path = self.get_contract_path('BytesClear.py') self.assertCompilerLogs(MismatchedTypes, path) def test_bytes_reverse(self): path = self.get_contract_path('BytesReverse.py') self.assertCompilerLogs(MismatchedTypes, path) def test_bytes_to_int(self): path = self.get_contract_path('BytesToInt.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_int') self.assertEqual(513, result) def test_bytes_to_int_with_builtin(self): path = self.get_contract_path('BytesToIntWithBuiltin.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_int') self.assertEqual(513, result) def test_bytes_to_int_mismatched_types(self): path = self.get_contract_path('BytesToIntWithBuiltinMismatchedTypes.py') self.assertCompilerLogs(MismatchedTypes, path) def test_bytes_to_int_with_byte_array_builtin(self): path = self.get_contract_path('BytesToIntWithBytearrayBuiltin.py') self.assertCompilerLogs(MismatchedTypes, path) def test_bytes_to_bool(self): path = self.get_contract_path('BytesToBool.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_bool', b'\x00') self.assertEqual(False, result) result = self.run_smart_contract(engine, path, 'bytes_to_bool', b'\x01') self.assertEqual(True, result) result = self.run_smart_contract(engine, path, 'bytes_to_bool', b'\x02') self.assertEqual(True, result) def test_bytes_to_bool_with_builtin(self): path = self.get_contract_path('BytesToBoolWithBuiltin.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_bool', b'\x00') self.assertEqual(False, result) result = self.run_smart_contract(engine, path, 'bytes_to_bool', b'\x01') self.assertEqual(True, result) result = self.run_smart_contract(engine, path, 'bytes_to_bool', b'\x02') self.assertEqual(True, result) def test_bytes_to_bool_with_builtin_hard_coded_false(self): path = self.get_contract_path('BytesToBoolWithBuiltinHardCodedFalse.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_bool', expected_result_type=bool) self.assertEqual(False, result) def test_bytes_to_bool_with_builtin_hard_coded_true(self): path = self.get_contract_path('BytesToBoolWithBuiltinHardCodedTrue.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_bool') self.assertEqual(True, result) def test_bytes_to_bool_mismatched_types(self): path = self.get_contract_path('BytesToBoolWithBuiltinMismatchedTypes.py') self.assertCompilerLogs(MismatchedTypes, path) def test_bytes_to_str(self): path = self.get_contract_path('BytesToStr.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_str') self.assertEqual('abc', result) def test_bytes_to_str_with_builtin(self): path = self.get_contract_path('BytesToStrWithBuiltin.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_str') self.assertEqual('123', result) def test_bytes_to_str_mismatched_types(self): path = self.get_contract_path('BytesToStrWithBuiltinMismatchedTypes.py') self.assertCompilerLogs(MismatchedTypes, path) def test_bytes_from_byte_array(self): data = b'\x01\x02\x03' expected_output = ( Opcode.INITSLOT # function signature + b'\x02' + b'\x00' + Opcode.PUSHDATA1 # a = bytearray(b'\x01\x02\x03') + Integer(len(data)).to_byte_array(min_length=1) + data + Opcode.STLOC0 + Opcode.LDLOC0 # b = a + Opcode.STLOC1 + Opcode.RET # return ) path = self.get_contract_path('BytesFromBytearray.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) def test_assign_with_slice(self): path = self.get_contract_path('AssignSlice.py') engine = TestEngine() result = self.run_smart_contract(engine, path, 'main', b'unittest', expected_result_type=bytearray) self.assertEqual(b'unittest'[1:2], result) result = self.run_smart_contract(engine, path, 'main', b'123', expected_result_type=bytearray) self.assertEqual(b'123'[1:2], result) with self.assertRaises(TestExecutionException): self.run_smart_contract(engine, path, 'main', bytearray()) def test_byte_array_get_value(self): expected_output = ( Opcode.INITSLOT # function signature + b'\x00' + b'\x01' + Opcode.LDARG0 # arg[0] + Opcode.PUSH0 + Opcode.DUP + Opcode.SIGN + Opcode.PUSHM1 + Opcode.JMPNE + Integer(5).to_byte_array(min_length=1, signed=True) + Opcode.OVER + Opcode.SIZE + Opcode.ADD + Opcode.PICKITEM + Opcode.RET # return ) path = self.get_contract_path('BytearrayGetValue.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', bytes([1, 2, 3])) self.assertEqual(1, result) result = self.run_smart_contract(engine, path, 'Main', b'0') self.assertEqual(48, result) def test_byte_array_get_value_negative_index(self): expected_output = ( Opcode.INITSLOT # function signature + b'\x00' + b'\x01' + Opcode.LDARG0 # arg[0] + Opcode.PUSHM1 + Opcode.DUP + Opcode.SIGN + Opcode.PUSHM1 + Opcode.JMPNE + Integer(5).to_byte_array(min_length=1, signed=True) + Opcode.OVER + Opcode.SIZE + Opcode.ADD + Opcode.PICKITEM + Opcode.RET # return ) path = self.get_contract_path('BytearrayGetValueNegativeIndex.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', bytes([1, 2, 3])) self.assertEqual(3, result) result = self.run_smart_contract(engine, path, 'Main', b'0') self.assertEqual(48, result) @unittest.skip("bytestring setitem is not working yet") def test_byte_array_set_value(self): expected_output = ( Opcode.INITSLOT # function signature + b'\x00' + b'\x01' + Opcode.LDARG0 # arg[0] = 0x01 + Opcode.PUSH0 + Opcode.DUP + Opcode.SIGN + Opcode.PUSHM1 + Opcode.JMPNE + Integer(5).to_byte_array(min_length=1, signed=True) + Opcode.OVER + Opcode.SIZE + Opcode.ADD + Opcode.PUSH1 + Opcode.SETITEM + Opcode.LDARG0 + Opcode.RET # return ) path = self.get_contract_path('BytearraySetValue.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', b'123') self.assertEqual(b'\x0123', result) result = self.run_smart_contract(engine, path, 'Main', b'0') self.assertEqual(b'\x01', result) @unittest.skip("bytestring setitem is not working yet") def test_byte_array_set_value_negative_index(self): expected_output = ( Opcode.INITSLOT # function signature + b'\x00' + b'\x01' + Opcode.LDARG0 # arg[-1] = 0x01 + Opcode.PUSHM1 + Opcode.DUP + Opcode.SIGN + Opcode.PUSHM1 + Opcode.JMPNE + Integer(5).to_byte_array(min_length=1, signed=True) + Opcode.OVER + Opcode.SIZE + Opcode.ADD + Opcode.PUSH1 + Opcode.SETITEM + Opcode.LDARG0 + Opcode.RET # return ) path = self.get_contract_path('BytearraySetValueNegativeIndex.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', b'123') self.assertEqual(b'12\x01', result) result = self.run_smart_contract(engine, path, 'Main', b'0') self.assertEqual(b'\x01', result) def test_byte_array_literal_value(self): path = self.get_contract_path('BytearrayLiteral.py') self.assertCompilerLogs(MismatchedTypes, path) def test_byte_array_from_literal_bytes(self): data = b'\x01\x02\x03' expected_output = ( Opcode.INITSLOT # function signature + b'\x01' + b'\x00' + Opcode.PUSHDATA1 # a = bytearray(b'\x01\x02\x03') + Integer(len(data)).to_byte_array(min_length=1) + data + Opcode.STLOC0 + Opcode.RET # return ) path = self.get_contract_path('BytearrayFromLiteralBytes.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) def test_byte_array_from_variable_bytes(self): data = b'\x01\x02\x03' expected_output = ( Opcode.INITSLOT # function signature + b'\x02' + b'\x00' + Opcode.PUSHDATA1 # a = b'\x01\x02\x03' + Integer(len(data)).to_byte_array(min_length=1) + data + Opcode.STLOC0 + Opcode.PUSHDATA1 # b = bytearray(a) + Integer(len(data)).to_byte_array(min_length=1) + data + Opcode.STLOC1 + Opcode.RET # return ) path = self.get_contract_path('BytearrayFromVariableBytes.py') output = Boa3.compile(path) self.assertEqual(expected_output, output) def test_byte_array_string(self): path = self.get_contract_path('BytearrayFromString.py') self.assertCompilerLogs(NotSupportedOperation, path) def test_byte_array_append(self): path = self.get_contract_path('BytearrayAppend.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', expected_result_type=bytes) self.assertEqual(b'\x01\x02\x03\x04', result) def test_byte_array_append_with_builtin(self): path = self.get_contract_path('BytearrayAppendWithBuiltin.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', expected_result_type=bytes) self.assertEqual(b'\x01\x02\x03\x04', result) def test_byte_array_append_mutable_sequence_with_builtin(self): path = self.get_contract_path('BytearrayAppendWithMutableSequence.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', expected_result_type=bytes) self.assertEqual(b'\x01\x02\x03\x04', result) def test_byte_array_clear(self): path = self.get_contract_path('BytearrayClear.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', expected_result_type=bytes) self.assertEqual(b'', result) @unittest.skip("reverse items doesn't work with bytestring") def test_byte_array_reverse(self): path = self.get_contract_path('BytearrayReverse.py') Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', expected_result_type=bytes) self.assertEqual(b'\x03\x02\x01', result) def test_byte_array_extend(self): path = self.get_contract_path('BytearrayExtend.py') Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', expected_result_type=bytes) self.assertEqual(b'\x01\x02\x03\x04\x05\x06', result) def test_byte_array_extend_with_builtin(self): path = self.get_contract_path('BytearrayExtendWithBuiltin.py') Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'Main', expected_result_type=bytes) self.assertEqual(b'\x01\x02\x03\x04\x05\x06', result) def test_byte_array_to_int(self): path = self.get_contract_path('BytearrayToInt.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_int') self.assertEqual(513, result) def test_byte_array_to_int_with_builtin(self): path = self.get_contract_path('BytearrayToIntWithBuiltin.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_int') self.assertEqual(513, result) def test_byte_array_to_int_with_bytes_builtin(self): path = self.get_contract_path('BytearrayToIntWithBytesBuiltin.py') output = Boa3.compile(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'bytes_to_int') self.assertEqual(513, result) def test_boa2_byte_array_test(self): path = self.get_contract_path('BytearrayBoa2Test.py') engine = TestEngine() result = self.run_smart_contract(engine, path, 'main', expected_result_type=bytes) self.assertEqual(b'\t\x01\x02', result) def test_boa2_byte_array_test2(self): path = self.get_contract_path('BytearrayBoa2Test2.py') self.assertCompilerLogs(MismatchedTypes, path) def test_boa2_byte_array_test3(self): path = self.get_contract_path('BytearrayBoa2Test3.py') engine = TestEngine() result = self.run_smart_contract(engine, path, 'main') self.assertEqual(b'\x01\x02\xaa\xfe', result) def test_boa2_slice_test(self): path = self.get_contract_path('SliceBoa2Test.py') self.compile_and_save(path) engine = TestEngine() result = self.run_smart_contract(engine, path, 'main', expected_result_type=bytes) self.assertEqual(b'\x01\x02\x03\x04', result) def test_boa2_slice_test2(self): path = self.get_contract_path('SliceBoa2Test2.py') engine = TestEngine() result = self.run_smart_contract(engine, path, 'main', expected_result_type=bytes) self.assertEqual(b'\x02\x03\x04\x02\x03\x04\x05\x06\x01\x02\x03\x04\x03\x04', result)

36.967054

100

0.607916

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19,075

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0.086256

0.03813

0.042536

0.073471

0.83741

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0.783273

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0.289436

19,075

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101

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0.791648

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0.100425

0.042901

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false

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0.018735

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0

null

0

1

0

1

0

null

0

5

cb1b5ef0f04599d16bbe18c6f96fb881138c97b8

57

py

Python

src/loss.py

muzammil360/DL-learn

16e90d099246e75eb7a9cc4a6e0515c0178423e0

[ "MIT" ]

null

src/loss.py

muzammil360/DL-learn

16e90d099246e75eb7a9cc4a6e0515c0178423e0

[ "MIT" ]

null

src/loss.py

muzammil360/DL-learn

16e90d099246e75eb7a9cc4a6e0515c0178423e0

[ "MIT" ]

null

def getLossFunc(): print("This is loss function ") pass

19

32

0.719298

8

57

5.125

1

0

0.157895

57

3

33

19

0.854167

0

0.37931

0

1

0.333333

true

0.333333

0

0.333333

1

0

null

0

1

0

null

0

1

0

5

cb1b9f98857aee2459585f912ff8c55a6ecfb9cd

122

py

Python

src/nerf/__init__.py

qway/nerfmeshes

d983dcbbcfec1337c9f2040969213c6d1ea0c39e

[ "MIT" ]

113

2020-10-30T11:27:43.000Z

2022-03-28T04:28:36.000Z

mesh/src/nerf/__init__.py

ashwinpn/Computer-Vision

9dc3abfe416385171b76e2bad6872e10f36a12b4

[ "MIT" ]

11

2020-09-07T07:15:56.000Z

2022-02-26T19:21:00.000Z

mesh/src/nerf/__init__.py

ashwinpn/Computer-Vision

9dc3abfe416385171b76e2bad6872e10f36a12b4

[ "MIT" ]

17

2020-11-05T06:24:07.000Z

2022-03-18T21:30:35.000Z

from .cfgnode import CfgNode from .tree import * from .nerf_helpers import * from .modules import * from .models import *

20.333333

28

0.762295

17

122

5.411765

0.470588

0.326087

0

0.163934

122

5

29

24.4

0.901961

0

1

0

true

0

1

0

1

0

1

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null

1

0

1

0

null

0

1

0

1

0

5

cb354a6caf06a102f1ddf89d2b6bf1b55d8140d6

660

py

Python

openid/test/test_htmldiscover.py

cjwatson/python-openid

557dc2eac99b29feda2c7f207f7ad6cbe90dde09

[ "Apache-2.0" ]

176

2015-01-04T07:41:11.000Z

2022-03-28T10:03:22.000Z

openid/test/test_htmldiscover.py

cjwatson/python-openid

557dc2eac99b29feda2c7f207f7ad6cbe90dde09

[ "Apache-2.0" ]

44

2018-02-27T21:13:04.000Z

2020-09-02T08:20:59.000Z

openid/test/test_htmldiscover.py

cjwatson/python-openid

557dc2eac99b29feda2c7f207f7ad6cbe90dde09

[ "Apache-2.0" ]

80

2015-01-30T10:26:28.000Z

2022-02-19T20:02:58.000Z

from __future__ import unicode_literals import unittest from openid.consumer.discover import OpenIDServiceEndpoint class TestFromHTML(unittest.TestCase): """Test `OpenIDServiceEndpoint.fromHTML`.""" def test_empty(self): self.assertEqual(OpenIDServiceEndpoint.fromHTML('http://example.url/', ''), []) def test_invalid_html(self): self.assertEqual(OpenIDServiceEndpoint.fromHTML('http://example.url/', "http://not.in.a.link.tag/"), []) def test_no_op_url(self): html = '<html><head><link rel="openid.server"></head></html>' self.assertEqual(OpenIDServiceEndpoint.fromHTML('http://example.url/', html), [])

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6.305556

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null

1

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null

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1

0

1

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5

cb70e73dec595d6fbaa5b9412f6b4c33d3504ed5

134

py

Python

tests/integration_tests/resources/dsl/deployment_update/execute_custom_workflow/modification/push_into_props.py

TS-at-WS/cloudify-manager

3e062e8dec16c89d2ab180d0b761cbf76d3f7ddc

[ "Apache-2.0" ]

124

2015-01-22T22:28:37.000Z

2022-02-26T23:12:06.000Z

tests/integration_tests/resources/dsl/deployment_update/execute_custom_workflow/modification/push_into_props.py

TS-at-WS/cloudify-manager

3e062e8dec16c89d2ab180d0b761cbf76d3f7ddc

[ "Apache-2.0" ]

345

2015-01-08T15:49:40.000Z

2022-03-29T08:33:00.000Z

tests/integration_tests/resources/dsl/deployment_update/execute_custom_workflow/modification/push_into_props.py

TS-at-WS/cloudify-manager

3e062e8dec16c89d2ab180d0b761cbf76d3f7ddc

[ "Apache-2.0" ]

77

2015-01-07T14:04:35.000Z

2022-03-07T22:46:00.000Z

from cloudify import ctx from cloudify.state import ctx_parameters as p ctx.instance.runtime_properties['update_id'] = p.update_id

19.142857

58

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5

0.619048

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134

6

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null

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1

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5

cba9207a7352fe9d4ea90feab57d95b372c82ed3

105

py

Python

231-power-of-two/231-power-of-two.py

MayaScarlet/leetcode-python

8ef0c5cadf2e975957085c0ef84a8c3d90a64b6a

[ "MIT" ]

null

231-power-of-two/231-power-of-two.py

MayaScarlet/leetcode-python

8ef0c5cadf2e975957085c0ef84a8c3d90a64b6a

[ "MIT" ]

null

231-power-of-two/231-power-of-two.py

MayaScarlet/leetcode-python

8ef0c5cadf2e975957085c0ef84a8c3d90a64b6a

[ "MIT" ]

null

class Solution: def isPowerOfTwo(self, n: int) -> bool: return n and not (n & n - 1)

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1

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null

0

1

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1

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5

cbae7c79d8a9d7a30fb918b680ff722a06f6cfdb

649

py

Python

exasol_integration_test_docker_environment/lib/test_environment/database_setup/upload_virtual_schema_jdbc_adapter.py

exasol/integration-test-docker-environment

35850f67cd4cde010f03dd556d1a0f74b3291eb8

[ "MIT" ]

4

2020-06-25T20:47:31.000Z

2021-09-10T15:22:51.000Z

exasol_integration_test_docker_environment/lib/test_environment/database_setup/upload_virtual_schema_jdbc_adapter.py

exasol/integration-test-docker-environment

35850f67cd4cde010f03dd556d1a0f74b3291eb8

[ "MIT" ]

113

2020-06-02T08:51:08.000Z

2022-03-31T08:47:41.000Z

exasol_integration_test_docker_environment/lib/test_environment/database_setup/upload_virtual_schema_jdbc_adapter.py

exasol/integration-test-docker-environment

35850f67cd4cde010f03dd556d1a0f74b3291eb8

[ "MIT" ]

2

2020-05-19T10:57:47.000Z

2020-06-22T13:32:20.000Z

from exasol_integration_test_docker_environment.lib.test_environment.database_setup.upload_file_to_db import \ UploadFileToBucketFS class UploadVirtualSchemaJDBCAdapter(UploadFileToBucketFS): def get_log_file(self): return "/exa/logs/cored/*bucketfsd*" def get_pattern_to_wait_for(self): return "virtualschema-jdbc-adapter.jar.*linked" def get_file_to_upload(self): return "downloads/virtualschema-jdbc-adapter/virtualschema-jdbc-adapter.jar" def get_upload_target(self): return "jdbc_adapter/virtualschema-jdbc-adapter.jar" def get_sync_time_estimation(self) -> int: return 10

30.904762

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649

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0.17234

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649

20

111

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1

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null

0

1

0

1

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5

cbb23736d134ee0303c8c558bc6cfee5b1a9826b

2,720

py

Python

pybamm/geometry/standard_spatial_vars.py

zlgenuine/pybamm

5c43d17225710c5bea8e61b3863688eb7080e678

[ "BSD-3-Clause" ]

null

pybamm/geometry/standard_spatial_vars.py

zlgenuine/pybamm

5c43d17225710c5bea8e61b3863688eb7080e678

[ "BSD-3-Clause" ]

null

pybamm/geometry/standard_spatial_vars.py

zlgenuine/pybamm

5c43d17225710c5bea8e61b3863688eb7080e678

[ "BSD-3-Clause" ]

null

import pybamm whole_cell = ["negative electrode", "separator", "positive electrode"] # Domains at cell centres x_n = pybamm.SpatialVariable( "x_n", domain=["negative electrode"], auxiliary_domains={"secondary": "current collector"}, coord_sys="cartesian", ) x_s = pybamm.SpatialVariable( "x_s", domain=["separator"], auxiliary_domains={"secondary": "current collector"}, coord_sys="cartesian", ) x_p = pybamm.SpatialVariable( "x_p", domain=["positive electrode"], auxiliary_domains={"secondary": "current collector"}, coord_sys="cartesian", ) x = pybamm.SpatialVariable( "x", domain=whole_cell, auxiliary_domains={"secondary": "current collector"}, coord_sys="cartesian", ) y = pybamm.SpatialVariable("y", domain="current collector", coord_sys="cartesian") z = pybamm.SpatialVariable("z", domain="current collector", coord_sys="cartesian") r_n = pybamm.SpatialVariable( "r_n", domain=["negative particle"], auxiliary_domains={ "secondary": "negative electrode", "tertiary": "current collector", }, coord_sys="spherical polar", ) r_p = pybamm.SpatialVariable( "r_p", domain=["positive particle"], auxiliary_domains={ "secondary": "positive electrode", "tertiary": "current collector", }, coord_sys="spherical polar", ) # Domains at cell edges x_n_edge = pybamm.SpatialVariable( "x_n_edge", domain=["negative electrode"], auxiliary_domains={"secondary": "current collector"}, coord_sys="cartesian", ) x_s_edge = pybamm.SpatialVariable( "x_s_edge", domain=["separator"], auxiliary_domains={"secondary": "current collector"}, coord_sys="cartesian", ) x_p_edge = pybamm.SpatialVariable( "x_p_edge", domain=["positive electrode"], auxiliary_domains={"secondary": "current collector"}, coord_sys="cartesian", ) x_edge = pybamm.SpatialVariable( "x_edge", domain=whole_cell, auxiliary_domains={"secondary": "current collector"}, coord_sys="cartesian", ) y_edge = pybamm.SpatialVariable( "y_edge", domain="current collector", coord_sys="cartesian" ) z_edge = pybamm.SpatialVariable( "z_edge", domain="current collector", coord_sys="cartesian" ) r_n_edge = pybamm.SpatialVariable( "r_n_edge", domain=["negative particle"], auxiliary_domains={ "secondary": "negative electrode", "tertiary": "current collector", }, coord_sys="spherical polar", ) r_p_edge = pybamm.SpatialVariable( "r_p_edge", domain=["positive particle"], auxiliary_domains={ "secondary": "positive electrode", "tertiary": "current collector", }, coord_sys="spherical polar", )

26.153846

82

0.673897

287

2,720

6.15331

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0.703284

0.653454

0.607022

0

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2,720

103

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0

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0

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1

0

1

0

1

0

null

0

5

cbca7c58ba6d87fbf125bfc9c3845c0a9d5b281f

548

py

Python

MyPythonDeepLearning/Python/myclass.py

medit74/DeepLearning

a25b72ff2229a376158adda6f8b8f270d9df1e66

[ "Apache-2.0" ]

1

2017-05-17T08:22:03.000Z

MyPythonDeepLearning/Python/myclass.py

medit74/DeepLearning

a25b72ff2229a376158adda6f8b8f270d9df1e66

[ "Apache-2.0" ]

null

MyPythonDeepLearning/Python/myclass.py

medit74/DeepLearning

a25b72ff2229a376158adda6f8b8f270d9df1e66

[ "Apache-2.0" ]

null

''' Created on 2017. 4. 12. @author: Byoungho Kang ''' class Calculator: def __init__(self, first, second): self.first = first self.second = second def plus(self): return self.first + self.second def minus(self): return self.first - self.second def multiply(self): return self.first * self.second def divide(self): return self.first / self.second c = Calculator(3, 4) print(c.plus(), c.minus(), c.multiply(), c.divide())

20.296296

52

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66

548

4.5

0.348485

0.181818

0.252525

0.255892

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0.330292

548

27

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0

1

0

null

0

1

0

1

0

5

cbd54c8de7f6ac13503e29c7d60d52081f60260f

20,915

py

Python

ichnaea/api/locate/locate_v2/tests.py

JaredKerim-Mozilla/ichnaea

cfaef2b903960374050be3ea2e4c1520687de56b

[ "Apache-1.1" ]

null

ichnaea/api/locate/locate_v2/tests.py

JaredKerim-Mozilla/ichnaea

cfaef2b903960374050be3ea2e4c1520687de56b

[ "Apache-1.1" ]

null

ichnaea/api/locate/locate_v2/tests.py

JaredKerim-Mozilla/ichnaea

cfaef2b903960374050be3ea2e4c1520687de56b

[ "Apache-1.1" ]

null

from uuid import uuid1 from sqlalchemy import text from ichnaea.models import ( ApiKey, Radio, ) from ichnaea.api.exceptions import ( DailyLimitExceeded, InvalidAPIKey, LocationNotFound, ParseError, ) from ichnaea.api.locate.locate_v2.schema import LocateV2Schema from ichnaea.tests.base import AppTestCase, TestCase from ichnaea.tests.factories import ( CellFactory, CellAreaFactory, WifiFactory, ) from ichnaea import util class TestLocateV2Schema(TestCase): def test_multiple_radio_fields_uses_radioType(self): schema = LocateV2Schema() data = schema.deserialize({'cellTowers': [{ 'radio': 'gsm', 'radioType': 'cdma', }]}) self.assertEqual(data['cell'][0]['radio'], 'cdma') self.assertFalse('radioType' in data['cell'][0]) class TestLocateV2(AppTestCase): def setUp(self): super(TestLocateV2, self).setUp() self.url = '/v1/geolocate' self.metric = 'geolocate' self.metric_url = 'request.v1.geolocate' def test_ok_cell(self): cell = CellFactory() self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'radioType': cell.radio.name, 'cellTowers': [{ 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid, 'signalStrength': -70, 'timingAdvance': 1}, ]}, status=200) self.check_stats( counter=[self.metric_url + '.200', self.metric + '.api_key.test', self.metric + '.api_log.test.cell_hit'] ) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': cell.lat, 'lng': cell.lon}, 'accuracy': cell.range}) def test_ok_cellarea(self): cell = CellAreaFactory() self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'radioType': cell.radio.name, 'cellTowers': [{ 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'signalStrength': -70, 'timingAdvance': 1}, ]}, status=200) self.check_stats( counter=[self.metric_url + '.200', self.metric + '.api_key.test', self.metric + '.api_log.test.cell_lac_hit'] ) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': cell.lat, 'lng': cell.lon}, 'accuracy': cell.range}) def test_ok_cellarea_when_lacf_enabled(self): cell = CellAreaFactory() self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'radioType': cell.radio.name, 'cellTowers': [{ 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'signalStrength': -70, 'timingAdvance': 1}, ], 'fallbacks': { 'lacf': 1, }, }, status=200) self.check_stats( counter=[self.metric_url + '.200', self.metric + '.api_key.test', self.metric + '.api_log.test.cell_lac_hit'] ) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': cell.lat, 'lng': cell.lon}, 'accuracy': cell.range}) def test_cellarea_not_found_when_lacf_disabled(self): cell = CellAreaFactory() self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'radioType': cell.radio.name, 'cellTowers': [{ 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'signalStrength': -70, 'timingAdvance': 1}, ], 'fallbacks': { 'lacf': 0, }, }, status=404) self.check_stats( counter=[self.metric_url + '.404', self.metric + '.api_key.test'] ) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, LocationNotFound.json_body()) def test_ok_partial_cell(self): cell = CellFactory() self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'cellTowers': [{ 'radioType': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid, 'psc': cell.psc}, { 'radioType': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'psc': cell.psc + 1, }]}, status=200) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': cell.lat, 'lng': cell.lon}, 'accuracy': cell.range}) def test_ok_wifi(self): wifi = WifiFactory() offset = 0.0001 wifis = [ wifi, WifiFactory(lat=wifi.lat + offset), WifiFactory(lat=wifi.lat + offset * 2), WifiFactory(lat=None, lon=None), ] self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'wifiAccessPoints': [ {'macAddress': wifis[0].key, 'channel': 6}, {'macAddress': wifis[1].key, 'frequency': 2437}, {'macAddress': wifis[2].key, 'signalStrength': -77}, {'macAddress': wifis[3].key, 'signalToNoiseRatio': 13}, ]}, status=200) self.check_stats( counter=[self.metric + '.api_key.test', self.metric + '.api_log.test.wifi_hit']) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': wifi.lat + offset, 'lng': wifi.lon}, 'accuracy': wifi.range}) def test_wifi_not_found(self): wifis = WifiFactory.build_batch(2) res = self.app.post_json( '%s?key=test' % self.url, { 'wifiAccessPoints': [ {'macAddress': wifis[0].key}, {'macAddress': wifis[1].key}, ]}, status=404) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, LocationNotFound.json_body()) # Make sure to get two counters, a timer, and no traceback self.check_stats( counter=[self.metric + '.api_key.test', self.metric + '.api_log.test.wifi_miss', (self.metric_url + '.404', 1)], timer=[self.metric_url]) def test_cell_mcc_mnc_strings(self): # mcc and mnc are officially defined as strings, where '01' is # different from '1'. In practice many systems ours included treat # them as integers, so both of these are encoded as 1 instead. # Some clients sends us these values as strings, some as integers, # so we want to make sure we support both. cell = CellFactory(mnc=1) self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'cellTowers': [{ 'radioType': cell.radio.name, 'mobileCountryCode': str(cell.mcc), 'mobileNetworkCode': '01', 'locationAreaCode': cell.lac, 'cellId': cell.cid}, ]}, status=200) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': cell.lat, 'lng': cell.lon}, 'accuracy': cell.range}) def test_geoip_fallback(self): london = self.geoip_data['London'] wifis = WifiFactory.build_batch(4) res = self.app.post_json( '%s?key=test' % self.url, {'wifiAccessPoints': [ {'macAddress': wifis[0].key}, {'macAddress': wifis[1].key}, {'macAddress': wifis[2].key}, {'macAddress': wifis[3].key}, ]}, extra_environ={'HTTP_X_FORWARDED_FOR': london['ip']}, status=200) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': london['latitude'], 'lng': london['longitude']}, 'accuracy': london['accuracy']}) def test_empty_request_means_geoip(self): london = self.geoip_data['London'] res = self.app.post_json( '%s?key=test' % self.url, {}, extra_environ={'HTTP_X_FORWARDED_FOR': london['ip']}, status=200) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': london['latitude'], 'lng': london['longitude']}, 'accuracy': london['accuracy']}) def test_incomplete_request_means_geoip(self): london = self.geoip_data['London'] res = self.app.post_json( '%s?key=test' % self.url, {'wifiAccessPoints': []}, extra_environ={'HTTP_X_FORWARDED_FOR': london['ip']}, status=200) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': london['latitude'], 'lng': london['longitude']}, 'accuracy': london['accuracy']}) def test_parse_error(self): res = self.app.post('%s?key=test' % self.url, '\xae', status=400) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, ParseError.json_body()) self.check_stats(counter=[self.metric + '.api_key.test']) def test_no_api_key(self): cell = CellFactory() self.session.flush() res = self.app.post_json( self.url, { 'cellTowers': [{ 'radioType': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, ] }, status=400) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, InvalidAPIKey.json_body()) self.check_stats( counter=[self.metric + '.no_api_key']) def test_unknown_api_key(self): cell = CellFactory() self.session.flush() res = self.app.post_json( '%s?key=unknown_key' % self.url, { 'radioType': cell.radio.name, 'cellTowers': [ {'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, ] }, status=400) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, InvalidAPIKey.json_body()) self.check_stats( counter=[self.metric + '.unknown_api_key']) def test_api_key_limit(self): london = self.geoip_data['London'] api_key = uuid1().hex self.session.add(ApiKey(valid_key=api_key, maxreq=5, shortname='dis')) self.session.flush() # exhaust today's limit dstamp = util.utcnow().strftime('%Y%m%d') key = 'apilimit:%s:%s' % (api_key, dstamp) self.redis_client.incr(key, 10) res = self.app.post_json( '%s?key=%s' % (self.url, api_key), {}, extra_environ={'HTTP_X_FORWARDED_FOR': london['ip']}, status=403) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, DailyLimitExceeded.json_body()) def test_lte_radio(self): cell = CellFactory(radio=Radio.lte) self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'cellTowers': [{ 'radio': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, ]}, status=200) self.check_stats( counter=[self.metric_url + '.200', self.metric + '.api_key.test']) self.assertEqual(res.content_type, 'application/json') location = res.json['location'] self.assertAlmostEquals(location['lat'], cell.lat) self.assertAlmostEquals(location['lng'], cell.lon) self.assertEqual(res.json['accuracy'], cell.range) def test_ok_cell_radio_in_celltowers(self): # This test covers a bug related to FxOS calling the # geolocate API incorrectly. cell = CellFactory() self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'cellTowers': [ {'radio': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, ]}, status=200) self.assertEqual(res.json, {'location': {'lat': cell.lat, 'lng': cell.lon}, 'accuracy': cell.range}) def test_ok_cell_radiotype_in_celltowers(self): # This test covers an extension to the geolocate API cell = CellFactory() self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'cellTowers': [ {'radioType': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, ]}, status=200) self.assertEqual(res.json, {'location': {'lat': cell.lat, 'lng': cell.lon}, 'accuracy': cell.range}) def test_ok_cell_radio_in_celltowers_dupes(self): # This test covers a bug related to FxOS calling the # geolocate API incorrectly. cell = CellFactory() self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'cellTowers': [ {'radio': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, {'radio': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, ]}, status=200) self.assertEqual(res.json, {'location': {'lat': cell.lat, 'lng': cell.lon}, 'accuracy': cell.range}) def test_inconsistent_cell_radio_in_towers(self): cell = CellFactory(radio=Radio.umts, range=15000) cell2 = CellFactory(radio=Radio.gsm, range=35000, lat=cell.lat + 0.0002, lon=cell.lon) self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'radioType': Radio.cdma.name, 'cellTowers': [ {'radio': 'wcdma', 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, {'radio': cell2.radio.name, 'mobileCountryCode': cell2.mcc, 'mobileNetworkCode': cell2.mnc, 'locationAreaCode': cell2.lac, 'cellId': cell2.cid}, ]}, status=200) location = res.json['location'] self.assertAlmostEquals(location['lat'], cell.lat) self.assertAlmostEquals(location['lng'], cell.lon) self.assertEqual(res.json['accuracy'], cell.range) def test_inconsistent_cell_radio_type_in_towers(self): cell = CellFactory(radio=Radio.umts, range=15000) cell2 = CellFactory(radio=Radio.gsm, range=35000, lat=cell.lat + 0.0002, lon=cell.lon) self.session.flush() res = self.app.post_json( '%s?key=test' % self.url, { 'radioType': Radio.cdma.name, 'cellTowers': [ {'radio': 'cdma', 'radioType': 'wcdma', 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, {'radioType': cell2.radio.name, 'mobileCountryCode': cell2.mcc, 'mobileNetworkCode': cell2.mnc, 'locationAreaCode': cell2.lac, 'cellId': cell2.cid}, ]}, status=200) location = res.json['location'] self.assertAlmostEquals(location['lat'], cell.lat) self.assertAlmostEquals(location['lng'], cell.lon) self.assertEqual(res.json['accuracy'], cell.range) class TestLocateV2Errors(AppTestCase): # this is a standalone class to ensure DB isolation for dropping tables def tearDown(self): self.setup_tables(self.db_rw.engine) super(TestLocateV2Errors, self).tearDown() def test_database_error(self): london = self.geoip_data['London'] self.session.execute(text('drop table wifi;')) self.session.execute(text('drop table cell;')) cell = CellFactory.build() wifis = WifiFactory.build_batch(2) res = self.app.post_json( '/v1/geolocate?key=test', { 'cellTowers': [{ 'radioType': cell.radio.name, 'mobileCountryCode': cell.mcc, 'mobileNetworkCode': cell.mnc, 'locationAreaCode': cell.lac, 'cellId': cell.cid}, ], 'wifiAccessPoints': [ {'macAddress': wifis[0].key}, {'macAddress': wifis[1].key}, ]}, extra_environ={'HTTP_X_FORWARDED_FOR': london['ip']}, status=200) self.assertEqual(res.content_type, 'application/json') self.assertEqual(res.json, {'location': {'lat': london['latitude'], 'lng': london['longitude']}, 'accuracy': london['accuracy']}) self.check_stats( timer=['request.v1.geolocate'], counter=[ 'request.v1.geolocate.200', 'geolocate.geoip_hit', ]) self.check_raven([('ProgrammingError', 2)])

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null

0

1

0

null

0

5

1db0b37efe2a3b98a1d227ee6b1ae2aa250d2373

270

py

Python

src/freeway/errors.py

cesioarg/freeway

1c81bfd4e8bfc42910bb1b4f7cb98253b0165973

[ "MIT" ]

null

src/freeway/errors.py

cesioarg/freeway

1c81bfd4e8bfc42910bb1b4f7cb98253b0165973

[ "MIT" ]

null

src/freeway/errors.py

cesioarg/freeway

1c81bfd4e8bfc42910bb1b4f7cb98253b0165973

[ "MIT" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- # cython: language_level=2, boundscheck=False class NoValidVersion(Exception): pass class VersionZero(Exception): pass class ExceededPaddingVersion(Exception): pass class NoVersionNumber(Exception): pass

13.5

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0

1

0

5

1de9f88abbe2761b701e1c15ff3e37d40e33d2b0

117

py

Python

openet/tests/test_interp.py

pblankenau2/openet-core-beta

685c08bd50a346c3b2893d32a9ddd3881ff7fd0f

[ "Apache-2.0" ]

1

2020-11-17T02:58:35.000Z

openet/tests/test_interp.py

pblankenau2/openet-core-beta

685c08bd50a346c3b2893d32a9ddd3881ff7fd0f

[ "Apache-2.0" ]

null

openet/tests/test_interp.py

pblankenau2/openet-core-beta

685c08bd50a346c3b2893d32a9ddd3881ff7fd0f

[ "Apache-2.0" ]

1

2020-11-17T02:58:52.000Z

import ee import pytest import openet.interp as interp def test_ee_init(): assert ee.Number(1).getInfo() == 1

13

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117

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null

0

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0

1

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1

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5

1dffb4d2e246611414741ac0e3967e4c20e86eaf

128

py

Python

boa3_test/test_sc/relational_test/ListEqualityWithSlice.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

25

2020-07-22T19:37:43.000Z

2022-03-08T03:23:55.000Z

boa3_test/test_sc/relational_test/ListEqualityWithSlice.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

419

2020-04-23T17:48:14.000Z

2022-03-31T13:17:45.000Z

boa3_test/test_sc/relational_test/ListEqualityWithSlice.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

15

2020-05-21T21:54:24.000Z

2021-11-18T06:17:24.000Z

from typing import List from boa3.builtin import public @public def main(a: List[str], b: str) -> bool: return a[0] == b

14.222222

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0.664063

22

128

3.863636

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0.019802

0.210938

128

8

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1

0

null

0

1

0

5

3804d28953813a7541e3498b8a15a24dee164ae2

65

py

Python

transformer/__init__.py

ShouryaMehra/FastSpeech-Fast-and-High-Quality-End-to-End-Text-to-Speech

64e820671e6c792512ff14c59639d93ce5e989b3

[ "MIT" ]

null

transformer/__init__.py

ShouryaMehra/FastSpeech-Fast-and-High-Quality-End-to-End-Text-to-Speech

64e820671e6c792512ff14c59639d93ce5e989b3

[ "MIT" ]

null

transformer/__init__.py

ShouryaMehra/FastSpeech-Fast-and-High-Quality-End-to-End-Text-to-Speech

64e820671e6c792512ff14c59639d93ce5e989b3

[ "MIT" ]

null

from .Models import Encoder, Decoder from .Layers import PostNet

32.5

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null

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1

0

1

0

1

0

5

6974a14ef1c934ceded3a9d38b3165061ea39cb3

201

py

Python

commerce/auctions/admin.py

pedrogiudici/Auctions

fc7faac67208068bf069cbf5ea22ee2bc30bd41a

[ "MIT" ]

null

commerce/auctions/admin.py

pedrogiudici/Auctions

fc7faac67208068bf069cbf5ea22ee2bc30bd41a

[ "MIT" ]

null

commerce/auctions/admin.py

pedrogiudici/Auctions

fc7faac67208068bf069cbf5ea22ee2bc30bd41a

[ "MIT" ]

null

from django.contrib import admin from .models import AuctionListing, Bid, Comment # Register your models here. admin.site.register(AuctionListing) admin.site.register(Bid) admin.site.register(Comment)

28.714286

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0.820896

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null

0

1

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1

0

5

698203476403fdf7d97d8b8bd0d02349007db233

3,516

py

Python

module_utils/network_lsr/nm/connection.py

spetrosi/network

ef655447b3ce8d43bf7d93c1eddcfac62ee3d418

[ "BSD-3-Clause" ]

1

2019-07-26T19:01:42.000Z

roles/linux-system-roles.network/module_utils/network_lsr/nm/connection.py

ptoal/toallab-automation

833f589d56696eb7e2c3815416c428889e828d5c

[ "MIT" ]

null

roles/linux-system-roles.network/module_utils/network_lsr/nm/connection.py

ptoal/toallab-automation

833f589d56696eb7e2c3815416c428889e828d5c

[ "MIT" ]

null

# SPDX-License-Identifier: BSD-3-Clause # Handle NM.RemoteConnection import logging # Relative import is not support by ansible 2.8 yet # pylint: disable=import-error, no-name-in-module from ansible.module_utils.network_lsr.nm import client # noqa:E501 from ansible.module_utils.network_lsr.nm import error # noqa:E501 # pylint: enable=import-error, no-name-in-module def delete_remote_connection(nm_profile, timeout, check_mode): if not nm_profile: logging.info("NULL NM.RemoteConnection, no need to delete") return False if not check_mode: main_loop = client.get_mainloop(timeout) user_data = main_loop nm_profile.delete_async( main_loop.cancellable, _nm_profile_delete_call_back, user_data, ) logging.debug( "Deleting profile {id}/{uuid} with timeout {timeout}".format( id=nm_profile.get_id(), uuid=nm_profile.get_uuid(), timeout=timeout ) ) main_loop.run() return True def _nm_profile_delete_call_back(nm_profile, result, user_data): main_loop = user_data if main_loop.is_cancelled: return try: success = nm_profile.delete_finish(result) except Exception as e: main_loop.fail( error.LsrNetworkNmError( "Connection deletion aborted on {id}/{uuid}: error={error}".format( id=nm_profile.get_id(), uuid=nm_profile.get_uuid(), error=e ) ) ) if success: main_loop.quit() else: main_loop.fail( error.LsrNetworkNmError( "Connection deletion aborted on {id}/{uuid}: error=unknown".format( id=nm_profile.get_id(), uuid=nm_profile.get_uuid() ) ) ) def volatilize_remote_connection(nm_profile, timeout, check_mode): if not nm_profile: logging.info("NULL NM.RemoteConnection, no need to volatilize") return False if not check_mode: main_loop = client.get_mainloop(timeout) user_data = main_loop nm_profile.update2( None, # settings client.NM.SettingsUpdate2Flags.IN_MEMORY_ONLY | client.NM.SettingsUpdate2Flags.VOLATILE, None, # args main_loop.cancellable, _nm_profile_volatile_update2_call_back, user_data, ) logging.debug( "Volatilizing profile {id}/{uuid} with timeout {timeout}".format( id=nm_profile.get_id(), uuid=nm_profile.get_uuid(), timeout=timeout ) ) main_loop.run() return True def _nm_profile_volatile_update2_call_back(nm_profile, result, user_data): main_loop = user_data if main_loop.is_cancelled: return try: success = nm_profile.update2_finish(result) except Exception as e: main_loop.fail( error.LsrNetworkNmError( "Connection volatilize aborted on {id}/{uuid}: error={error}".format( id=nm_profile.get_id(), uuid=nm_profile.get_uuid(), error=e ) ) ) if success: main_loop.quit() else: main_loop.fail( error.LsrNetworkNmError( "Connection volatilize aborted on {id}/{uuid}: error=unknown".format( id=nm_profile.get_id(), uuid=nm_profile.get_uuid() ) ) )

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1

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null

0

5

69a554503ab1c27b046019936ea5f73c761fb6bd

111

py

Python

cart/tests.py

hcNick/django-cart

0f1974095864c2f25554914356506f850dbbb338

[ "MIT" ]

1

2016-03-10T16:17:25.000Z

cart/tests.py

miguelchavez/django-cart

72cffa20abd68fdb03493027ccda28e7047323ac

[ "MIT" ]

null

cart/tests.py

miguelchavez/django-cart

72cffa20abd68fdb03493027ccda28e7047323ac

[ "MIT" ]

null

from django.test import TestCase import cart class CartTestCase(TestCase): def setUp(self): pass

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null

0

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null

0

1

0

1

0

5

69bb0e084527ef199bf1e733b8d241b1df022278

65

py

Python

pynsett/inference/__init__.py

fractalego/python-nlulite

982b780adedebf2c8a1e119f0f8b46ae72a9c384

[ "MIT" ]

26

2019-01-12T21:52:36.000Z

2022-03-30T11:28:52.000Z

pynsett/inference/__init__.py

fractalego/python-nlulite

982b780adedebf2c8a1e119f0f8b46ae72a9c384

[ "MIT" ]

2

2022-02-04T12:03:10.000Z

2022-02-09T13:24:07.000Z

pynsett/inference/__init__.py

fractalego/python-nlulite

982b780adedebf2c8a1e119f0f8b46ae72a9c384

[ "MIT" ]

3

2019-08-18T18:45:48.000Z

2022-02-04T11:39:38.000Z

from pynsett.inference.forward_inference import ForwardInference

32.5

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1

0

5

69d5079f55a4dad86946c29a1ee41c94a3fa54e9

203

py

Python

maintenance_calendar/parser/json/json_calendar_parser.py

Fiware/ops.Maintenance-calendar

636244f70e03ba45c943b68b847cad16ce3b66c8

[ "Apache-2.0" ]

null

maintenance_calendar/parser/json/json_calendar_parser.py

Fiware/ops.Maintenance-calendar

636244f70e03ba45c943b68b847cad16ce3b66c8

[ "Apache-2.0" ]

null

maintenance_calendar/parser/json/json_calendar_parser.py

Fiware/ops.Maintenance-calendar

636244f70e03ba45c943b68b847cad16ce3b66c8

[ "Apache-2.0" ]

null

from flask import json from maintenance_calendar.parser.json.json_parser import JSONParser class JSONCalendarParser(JSONParser): def to_dict(self, data): return json.loads(data)['calendar']

29

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203

7

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false

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null

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1

0

null

0

1

0

5

69f0b5ed24cdad2aca0583b5a6e05bf60da4a532

112

py

Python

pyticket/test.py

Lithimlin/pyticket

7ebefd2cd0cf24b195032f44aa6ffb8787ab10bd

[ "MIT-0", "MIT" ]

3

2019-06-07T13:39:39.000Z

2021-01-21T20:42:43.000Z

pyticket/test.py

Lithimlin/pyticket

7ebefd2cd0cf24b195032f44aa6ffb8787ab10bd

[ "MIT-0", "MIT" ]

32

2019-04-26T10:41:32.000Z

2021-06-08T04:09:27.000Z

pyticket/test.py

Lithimlin/pyticket

7ebefd2cd0cf24b195032f44aa6ffb8787ab10bd

[ "MIT-0", "MIT" ]

2

2019-08-15T08:00:26.000Z

2021-06-11T08:11:10.000Z

from django.test import TestCase class CronCommandtest(TestCase): def test_cron_command(self): pass

22.4

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5.857143

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false

0.25

0

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0

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null

0

1

0

1

0

1

0

5

69f48837768ee7bb01e7652006e58eb8d225f121

466

py

Python

anagrams/test_.py

technolingo/AlgoStructuresPy

4ac95542dec48b61dab3a0f33c5bacbe5a3cb3f1

[ "MIT" ]

null

anagrams/test_.py

technolingo/AlgoStructuresPy

4ac95542dec48b61dab3a0f33c5bacbe5a3cb3f1

[ "MIT" ]

null

anagrams/test_.py

technolingo/AlgoStructuresPy

4ac95542dec48b61dab3a0f33c5bacbe5a3cb3f1

[ "MIT" ]

null

from .index import are_anagrams def test_are_anagrams_true(): assert are_anagrams('', '') is True assert are_anagrams('a', 'a') is True assert are_anagrams('hello', 'llohe') is True assert are_anagrams('Whoa! Hi!', 'Hi! Whoa!') is True def test_are_anagrams_false(): assert are_anagrams('One One', 'Two two two') is False assert are_anagrams('One one', 'One one c') is False assert are_anagrams('tree, bench', 'fence, yard') is False

31.066667

62

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466

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0.183607

0

0.182403

466

14

63

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true

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1

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null

0

1

0

1

0

5

0e01c0381ef90e35bd2a65ecd86e3eefcd8102bd

96

py

Python

settings/__init__.py

siehr/django-testing-framework

7e411227afff1a5463ebc73ae5cb2c537f0d4f69

[ "MIT" ]

null

settings/__init__.py

siehr/django-testing-framework

7e411227afff1a5463ebc73ae5cb2c537f0d4f69

[ "MIT" ]

70

2021-03-06T14:36:42.000Z

2022-03-30T10:00:54.000Z

settings/__init__.py

siehr/django-testing-framework

7e411227afff1a5463ebc73ae5cb2c537f0d4f69

[ "MIT" ]

1

2022-02-02T14:05:43.000Z

import os, sys try: from .local import * except ImportError: from .development import *

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0e0a8b45be3ec1fbd9a8346f1964d9f36a50b5c7

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py

Python

tests/__init__.py

njamaleddine/django-csvtojson

82dde0a97c717eea58852016b7ff88898f21d02e

[ "MIT" ]

1

2015-11-21T03:16:14.000Z

tests/__init__.py

njamaleddine/django-csvtojson

82dde0a97c717eea58852016b7ff88898f21d02e

[ "MIT" ]

5

2015-09-29T03:30:27.000Z

2015-10-01T02:03:57.000Z

tests/__init__.py

njamaleddine/django-csvtojson

82dde0a97c717eea58852016b7ff88898f21d02e

[ "MIT" ]

null

""" TODO: Write some tests """

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0e12ed270b513824d2e27efff85df855cc4e3a59

44

py

Python

plusseg/data/samplers/__init__.py

tonysy/SegmentationToolbox.PyTorch

4d487dd81d0101bc5cdb7b2337776fdf1b5546ff

[ "MIT" ]

13

2019-07-26T11:33:15.000Z

2021-09-22T06:48:52.000Z

plusseg/data/samplers/__init__.py

tonysy/SegmentationToolbox.PyTorch

4d487dd81d0101bc5cdb7b2337776fdf1b5546ff

[ "MIT" ]

1

2018-11-05T14:07:07.000Z

plusseg/data/samplers/__init__.py

tonysy/SegmentationToolbox.PyTorch

4d487dd81d0101bc5cdb7b2337776fdf1b5546ff

[ "MIT" ]

2

2019-07-26T11:33:32.000Z

2020-03-04T13:47:50.000Z

from .distributed import DistributedSampler

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38645ffdf0584ed64f3c713910593cc78c86fc86

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py

Python

alphacsc/tests/test_init_d.py

vishalbelsare/alphacsc

7b7f2f3b0456ab338e95924c76828a26b3b8e4b2

[ "BSD-3-Clause" ]

null

alphacsc/tests/test_init_d.py

vishalbelsare/alphacsc

7b7f2f3b0456ab338e95924c76828a26b3b8e4b2

[ "BSD-3-Clause" ]

null

alphacsc/tests/test_init_d.py

vishalbelsare/alphacsc

7b7f2f3b0456ab338e95924c76828a26b3b8e4b2

[ "BSD-3-Clause" ]

null

import pytest import numpy as np import functools from numpy.testing import assert_allclose from alphacsc.init_dict import init_dictionary from alphacsc.update_d_multi import prox_uv, prox_d from alphacsc.update_d_multi import check_solver_and_constraints from alphacsc.learn_d_z_multi import learn_d_z_multi from alphacsc.utils import check_random_state from alphacsc.tests.conftest import parametrize_solver_and_constraint @parametrize_solver_and_constraint def test_init_array(rank1, solver_d, uv_constraint): n_trials, n_channels, n_times = 5, 3, 100 n_times_atom, n_atoms = 10, 4 _, uv_constraint_ = check_solver_and_constraints( rank1, solver_d, uv_constraint ) if rank1: expected_shape = (n_atoms, n_channels + n_times_atom) prox = functools.partial(prox_uv, uv_constraint=uv_constraint_, n_channels=n_channels) else: expected_shape = (n_atoms, n_channels, n_times_atom) prox = prox_d X = np.random.randn(n_trials, n_channels, n_times) # Test that init_dictionary is doing what we expect for D_init array D_init = np.random.randn(*expected_shape) D_hat = init_dictionary(X, n_atoms, n_times_atom, D_init=D_init, rank1=rank1, uv_constraint=uv_constraint_) D_init = prox(D_init) assert_allclose(D_hat, D_init) assert id(D_hat) != id(D_init) # Test that learn_d_z_multi is doing what we expect for D_init array D_init = np.random.randn(*expected_shape) _, _, D_hat, _, _ = learn_d_z_multi( X, n_atoms, n_times_atom, D_init=D_init, n_iter=0, rank1=rank1, solver_d=solver_d, uv_constraint=uv_constraint ) D_init = prox(D_init) assert_allclose(D_hat, D_init) @parametrize_solver_and_constraint def test_init_random(rank1, solver_d, uv_constraint): """""" n_trials, n_channels, n_times = 5, 3, 100 n_times_atom, n_atoms = 10, 4 _, uv_constraint_ = check_solver_and_constraints( rank1, solver_d, uv_constraint ) if rank1: expected_shape = (n_atoms, n_channels + n_times_atom) prox = functools.partial(prox_uv, uv_constraint=uv_constraint_, n_channels=n_channels) else: expected_shape = (n_atoms, n_channels, n_times_atom) prox = prox_d X = np.random.randn(n_trials, n_channels, n_times) # Test that init_dictionary is doing what we expect for D_init random random_state = 42 D_hat = init_dictionary(X, n_atoms, n_times_atom, D_init='random', rank1=rank1, uv_constraint=uv_constraint_, random_state=random_state) rng = check_random_state(random_state) D_init = rng.randn(*expected_shape) D_init = prox(D_init) assert_allclose(D_hat, D_init, err_msg="The random state is not correctly " "used in init_dictionary .") # Test that learn_d_z_multi is doing what we expect for D_init random random_state = 27 _, _, D_hat, _, _ = learn_d_z_multi( X, n_atoms, n_times_atom, D_init='random', n_iter=0, rank1=rank1, solver_d=solver_d, uv_constraint=uv_constraint, random_state=random_state ) rng = check_random_state(random_state) D_init = rng.randn(*expected_shape) D_init = prox(D_init) assert_allclose(D_hat, D_init, err_msg="The random state is not correctly " "used in learn_d_z_multi.") @pytest.mark.parametrize("rank1", [True, False]) @pytest.mark.parametrize("D_init", [ None, 'random', 'chunk', 'kmeans' ]) def test_init_shape(D_init, rank1): n_trials, n_channels, n_times = 5, 3, 100 n_times_atom, n_atoms = 10, 4 X = np.random.randn(n_trials, n_channels, n_times) expected_shape = (n_atoms, n_channels, n_times_atom) if rank1: expected_shape = (n_atoms, n_channels + n_times_atom) # Test that init_dictionary returns correct shape uv_hat = init_dictionary(X, n_atoms, n_times_atom, D_init=D_init, rank1=rank1, uv_constraint='separate', random_state=42) assert uv_hat.shape == expected_shape

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5

38a4c5ebee9b5218e3d9ded7230d99f7c382195d

110

py

Python

test/sample2.py

benmcp/gulp-pylint

91c2bcb85dff2cf94306494b81fb3f7d6fcf2a20

[ "MIT" ]

1

2018-05-20T22:51:22.000Z

test/sample2.py

benmcp/gulp-pylint

91c2bcb85dff2cf94306494b81fb3f7d6fcf2a20

[ "MIT" ]

null

test/sample2.py

benmcp/gulp-pylint

91c2bcb85dff2cf94306494b81fb3f7d6fcf2a20

[ "MIT" ]

null

""" Sample module docstring """ def world(): """ Sample function docstring """ print('world')

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null

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null

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1

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5

38d950706ed3250ee91162a4b027671d7c248e09

216

py

Python

django/contrib/gis/db/models/sql/__init__.py

webjunkie/django

5dbca13f3baa2e1bafd77e84a80ad6d8a074712e

[ "BSD-3-Clause" ]

790

2015-01-03T02:13:39.000Z

2020-05-10T19:53:57.000Z

django/contrib/gis/db/models/sql/__init__.py

mradziej/django

5d38965743a369981c9a738a298f467f854a2919

[ "BSD-3-Clause" ]

1,361

2015-01-08T23:09:40.000Z

2020-04-14T00:03:04.000Z

django/contrib/gis/db/models/sql/__init__.py

mradziej/django

5d38965743a369981c9a738a298f467f854a2919

[ "BSD-3-Clause" ]

155

2015-01-08T22:59:31.000Z

2020-04-08T08:01:53.000Z

from django.contrib.gis.db.models.sql.conversion import AreaField, DistanceField, GeomField from django.contrib.gis.db.models.sql.query import GeoQuery from django.contrib.gis.db.models.sql.where import GeoWhereNode

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null

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38dd49a19e584194c110356bc1befd7919afa65e

19

py

Python

chargebee/version.py

Uszczi/chargebee-python

f98a749961631aefd88e7d530f35cabd422d924b

[ "MIT" ]

null

chargebee/version.py

Uszczi/chargebee-python

f98a749961631aefd88e7d530f35cabd422d924b

[ "MIT" ]

null

chargebee/version.py

Uszczi/chargebee-python

f98a749961631aefd88e7d530f35cabd422d924b

[ "MIT" ]

null

VERSION = '2.14.0'

9.5

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null

0

5

2a0e8f07521a2a8e0124b62c02cc3f018412c3b2

337

py

Python

Codewars/Create_phone_number - (6 kyu).py

maxcohen31/A-bored-math-student

007beb4dabf7b4406f48e9a3a967c29d032eab89

[ "MIT" ]

null

Codewars/Create_phone_number - (6 kyu).py

maxcohen31/A-bored-math-student

007beb4dabf7b4406f48e9a3a967c29d032eab89

[ "MIT" ]

null

Codewars/Create_phone_number - (6 kyu).py

maxcohen31/A-bored-math-student

007beb4dabf7b4406f48e9a3a967c29d032eab89

[ "MIT" ]

null

# Create phone number def create_phone_number(n): full_str = ''.join([str(numb) for numb in x]) return f'({full_str[0:3]})' + ' ' + f'{full_str[3:6]}' + '-' + f'{full_str[6:10]}' def create_phone_number_2(x): phone_number = "({}{}{}) {}{}{}-{}{}{}{}".format(*x) return phone_number

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5

2a18a94110a1afc079cd9bfd87a3040bb111fc9a

41

py

Python

tests/__init__.py

bibby/pypi-uploader

2adbe84542042d479618e5d6bc55a4453fda7d0a

[ "MIT" ]

null

tests/__init__.py

bibby/pypi-uploader

2adbe84542042d479618e5d6bc55a4453fda7d0a

[ "MIT" ]

1

2019-10-24T16:57:02.000Z

2019-10-28T15:03:43.000Z

tests/__init__.py

bibby/pypi-uploader

2adbe84542042d479618e5d6bc55a4453fda7d0a

[ "MIT" ]

1

2018-12-19T18:35:51.000Z

"""Tests for the :mod:`pypiuploader`."""

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1

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1

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null

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5

2a4a7fdc11b163be207a41d963ccf15df8532b2e

85

py

Python

aws-s3-django-postgresql-rest/app/core/admin.py

MdSauravChowdhury/cheat-project

8602d1479e0b2adad48265404e4509ab6a45b8e3

[ "MIT" ]

null

aws-s3-django-postgresql-rest/app/core/admin.py

MdSauravChowdhury/cheat-project

8602d1479e0b2adad48265404e4509ab6a45b8e3

[ "MIT" ]

null

aws-s3-django-postgresql-rest/app/core/admin.py

MdSauravChowdhury/cheat-project

8602d1479e0b2adad48265404e4509ab6a45b8e3

[ "MIT" ]

null

from django.contrib import admin from .models import S3Box admin.site.register(S3Box)

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5

2a86ff4084e5661b92ba759f7bd1d2a93fb84d40

127

py

Python

core/fabkit/system/__init__.py

fabrickit/fabkit

ca099c7e543efb8f5c1d19453c8ceada0584e563

[ "MIT" ]

null

core/fabkit/system/__init__.py

fabrickit/fabkit

ca099c7e543efb8f5c1d19453c8ceada0584e563

[ "MIT" ]

null

core/fabkit/system/__init__.py

fabrickit/fabkit

ca099c7e543efb8f5c1d19453c8ceada0584e563

[ "MIT" ]

null

# coding: utf-8 from package import Package # noqa from service import Service # noqa from observer import Observer # noqa

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5

aa5657852d191bdd8e1f86af6fd8ad08e7c4671b

128

py

Python

py_tdlib/constructors/input_passport_element_utility_bill.py

Mr-TelegramBot/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

24

2018-10-05T13:04:30.000Z

2020-05-12T08:45:34.000Z

py_tdlib/constructors/input_passport_element_utility_bill.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

3

2019-06-26T07:20:20.000Z

2021-05-24T13:06:56.000Z

py_tdlib/constructors/input_passport_element_utility_bill.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

5

2018-10-05T14:29:28.000Z

2020-08-11T15:04:10.000Z

from ..factory import Type class inputPassportElementUtilityBill(Type): utility_bill = None # type: "inputPersonalDocument"

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5

aa99affc8e83729d9348702b0aeac610e8b7ea8d

7,368

py

Python

algorithms/queens-attack-2.py

gajubadge11/HackerRank-1

7b136ccaa1ed47ae737467ace6b494c720ccb942

[ "MIT" ]

340

2018-06-17T19:45:56.000Z

2022-03-22T02:26:15.000Z

algorithms/queens-attack-2.py

gajubadge11/HackerRank-1

7b136ccaa1ed47ae737467ace6b494c720ccb942

[ "MIT" ]

3

2021-02-02T17:17:29.000Z

2021-05-18T10:06:04.000Z

algorithms/queens-attack-2.py

gajubadge11/HackerRank-1

7b136ccaa1ed47ae737467ace6b494c720ccb942

[ "MIT" ]

229

2019-04-20T08:28:49.000Z

2022-03-31T04:23:52.000Z

#!/bin/python3 import sys from collections import defaultdict from math import fabs def check_diag(queen, obst): if queen[1] == obst[1]: return 0 check = (queen[0] - obst[0])/(queen[1] - obst[1]) if fabs(check) == 1.0: return int(check) else: return 0 def queensAttack(n, k, r_q, c_q, obstacles): queen = [r_q, c_q] res = 0 obst_by_row = list(filter(lambda x: x[0] == r_q, obstacles)) obst_by_col = list(filter(lambda x: x[1] == c_q, obstacles)) obst_by_plus_diag = list(filter(lambda x: check_diag(queen, x) == 1, obstacles)) obst_by_neg_diag = list(filter(lambda x: check_diag(queen, x) == -1, obstacles)) if not obst_by_col: res += n-1 else: obst_higher = list(filter(lambda x: x[0] > r_q, obst_by_col)) if obst_higher: min_higher = min(obst_higher, key = lambda x: x[0])[0] else: min_higher = n+1 obst_lower = list(filter(lambda x: x[0] < r_q, obst_by_col)) if obst_lower: max_lower = max(obst_lower, key = lambda x: x[0])[0] else: max_lower = 0 #print("high = {} low = {}".format(min_higher, max_lower)) res += min_higher - max_lower - 2 if not obst_by_row: res += n-1 else: obst_higher = list(filter(lambda x: x[1] > c_q, obst_by_row)) if obst_higher: min_higher = min(obst_higher, key = lambda x: x[1])[1] else: min_higher = n+1 obst_lower = list(filter(lambda x: x[1] < c_q, obst_by_row)) if obst_lower: max_lower = max(obst_lower, key = lambda x: x[1])[1] else: max_lower = 0 #print("high = {} low = {}".format(min_higher, max_lower)) res += min_higher - max_lower - 2 # diagonals if not obst_by_plus_diag: res += n-1 - abs(r_q - c_q) #res += min(n - c_q, n - r_q) + min(c_q - 1, r_q - 1) # = n-1 + min(-c_q, -r_q) + min(c_q, r_q) #print("res = {}".format(res)) else: obst_higher = list(filter(lambda x: x[0] > r_q, obst_by_plus_diag)) if obst_higher: min_higher = min(obst_higher, key = lambda x: x[0])[0] else: min_higher = n+1 obst_lower = list(filter(lambda x: x[0] < r_q, obst_by_plus_diag)) if obst_lower: max_lower = max(obst_lower, key = lambda x: x[0])[0] else: max_lower = 0 #print("high = {} low = {}".format(min_higher, max_lower)) res += min_higher - max_lower - 2 - abs(r_q - c_q) if not obst_by_neg_diag: #print("n - c_q + r_q = {} - {} + {}".format(n, c_q, r_q)) #res += n-1 - abs(n - c_q + r_q) #print("res = {}".format(res)) #res += min(n - c_q, r_q - 1) + min(c_q - 1, n - r_q) # 2 variants: # res += n - c_q + n - r_q = 2n - c_q - r_q # res += r_q - 1 + c_q - 1 = r_q + c_q - 2 res += min(n - c_q, r_q - 1) res += min(c_q - 1, n - r_q) else: obst_higher = list(filter(lambda x: x[0] > r_q, obst_by_neg_diag)) if obst_higher: min_higher = min(obst_higher, key = lambda x: x[0])[1] else: min_higher = n+1 obst_lower = list(filter(lambda x: x[0] < r_q, obst_by_neg_diag)) if obst_lower: max_lower = max(obst_lower, key = lambda x: x[0])[1] else: max_lower = 0 print("high = {} low = {}".format(min_higher, max_lower)) print("r_q = {} c_q = {}".format(r_q, c_q)) #res += min_higher - max_lower - 2 - abs(n - c_q + r_q) if max_lower != 0: res += max_lower - c_q - 1 if min_higher != n+1: res += c_q - min_higher - 1 return res # naive def queensAttack_naive(n, k, r_q, c_q, obstacles): obst_by_row = list(filter(lambda x: x[0] == r_q, obstacles)) obst_by_col = list(filter(lambda x: x[1] == c_q, obstacles)) obs_dict = gen_obs_dict(obstacles) res = 0 if not obst_by_col: res += n-1 else: for row_ind in range(r_q+1, n+1): #if not [row_ind, c_q] in obstacles: key = str(row_ind) + "-" + str(c_q) if obs_dict[key] != -1: res += 1 else: break for row_ind in range(r_q-1, 0, -1): #if not [row_ind, c_q] in obstacles: key = str(row_ind) + "-" + str(c_q) if obs_dict[key] != -1: res += 1 else: break if not obst_by_row: res += n-1 else: for col_ind in range(c_q+1, n+1): #if not [r_q, col_ind] in obstacles: key = str(r_q) + "-" + str(col_ind) if obs_dict[key] != -1: res += 1 else: break for col_ind in range(c_q-1, 0, -1): #if not [r_q, col_ind] in obstacles: key = str(r_q) + "-" + str(col_ind) if obs_dict[key] != -1: res += 1 else: break row_ind, col_ind = r_q+1, c_q+1 while col_ind != 0 and row_ind != 0 and col_ind != n+1 and row_ind != n+1: #if not [row_ind, col_ind] in obstacles: key = str(row_ind) + "-" + str(col_ind) if obs_dict[key] != -1: res += 1 row_ind += 1 col_ind += 1 else: break row_ind, col_ind = r_q-1, c_q+1 while col_ind != 0 and row_ind != 0 and col_ind != n+1 and row_ind != n+1: #if not [row_ind, col_ind] in obstacles: key = str(row_ind) + "-" + str(col_ind) if obs_dict[key] != -1: res += 1 row_ind -= 1 col_ind += 1 else: break row_ind, col_ind = r_q+1, c_q-1 while col_ind != 0 and row_ind != 0 and col_ind != n+1 and row_ind != n+1: #if not [row_ind, col_ind] in obstacles: key = str(row_ind) + "-" + str(col_ind) if obs_dict[key] != -1: res += 1 row_ind += 1 col_ind -= 1 else: break row_ind, col_ind = r_q-1, c_q-1 while col_ind != 0 and row_ind != 0 and col_ind != n+1 and row_ind != n+1: #if not [row_ind, col_ind] in obstacles: key = str(row_ind) + "-" + str(col_ind) if obs_dict[key] != -1: res += 1 row_ind -= 1 col_ind -= 1 else: break return res def gen_obs_dict(obstacles): dict_out = defaultdict(int) for obs in obstacles: row, col = obs[0], obs[1] key = str(row) + "-" + str(col) dict_out[key] = -1 return dict_out if __name__ == "__main__": n, k = [int(x) for x in input().strip().split(' ')] r_q, c_q = [int(x) for x in input().strip().split(' ')] obstacles = [] for obstacles_i in range(k): obstacles_t = [int(obstacles_temp) for obstacles_temp in input().strip().split(' ')] obstacles.append(obstacles_t) result = queensAttack_naive(n, k, r_q, c_q, obstacles) print(result)

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Python

pyladiesbrasilbot/utils/constants.py

naanadr/pyladies-bot

72328c7b255b48449f58f966a50e62cb6259cf79

[ "MIT" ]

3

2020-11-02T14:41:41.000Z

2020-11-02T19:16:00.000Z

pyladiesbrasilbot/utils/constants.py

yzakius/pyladies-bot

72328c7b255b48449f58f966a50e62cb6259cf79

[ "MIT" ]

7

2020-10-21T19:08:06.000Z

2020-10-22T20:19:22.000Z

pyladiesbrasilbot/utils/constants.py

naanadr/ladies-bot

72328c7b255b48449f58f966a50e62cb6259cf79

[ "MIT" ]

1

2022-02-25T13:07:24.000Z

DEFAULT_PHOTO_WELCOME = "pyladiesbrasilbot/files/welcome_pyladies_default.png" DEFAULT_PICKEL_FILE_PHOTO = "pyladiesbrasilbot/files/photos.pickle"

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