ytzi/the-stack-dedup-python-filtered-docstrings

32833472f753245d568128df8a1f79f7efbe1fb7

549

py

Python

Scripts/hello_world.py

hasauino/Python

c94ea3a15f8310c95b7aaabaaa82f59dbf748a85

[ "MIT" ]

null

Scripts/hello_world.py

hasauino/Python

c94ea3a15f8310c95b7aaabaaa82f59dbf748a85

[ "MIT" ]

null

Scripts/hello_world.py

hasauino/Python

c94ea3a15f8310c95b7aaabaaa82f59dbf748a85

[ "MIT" ]

null

print "Salam Alaikom !" import sys # if statement ------------------------------- if False: print "hi" print "Hello Wolrd!" if True: print "1" print "2" # array -------------------------------------- days = ["Monday", 'Tuesday', 'Wednesday', 'Thursday', 'Friday'] print days[0]; a=1; b=2 # -------------------------------------------- print a,b,'\n' if len(sys.argv)>1: print 'passed arguments are: ',str(sys.argv) if len(sys.argv)==1: print 'passed argument is: ',str(sys.argv[0]) raw_input("\n\nPress the enter key to exit")

14.837838

46

0.500911

print "Salam Alaikom !" import sys # if statement ------------------------------- if False: print "hi" print "Hello Wolrd!" if True: print "1" print "2" # array -------------------------------------- days = ["Monday", 'Tuesday', 'Wednesday', 'Thursday', 'Friday'] print days[0]; a=1; b=2 # -------------------------------------------- print a,b,'\n' if len(sys.argv)>1: print 'passed arguments are: ',str(sys.argv) if len(sys.argv)==1: print 'passed argument is: ',str(sys.argv[0]) raw_input("\n\nPress the enter key to exit")

0

a365a4252c5d814005389ed06e5f4dcda0f48f17

504

py

Python

tests/test.py

rose-okoth/News-API

1c19fe74903105599a40c53e68de61eccd993a46

[ "Unlicense", "MIT" ]

null

tests/test.py

rose-okoth/News-API

1c19fe74903105599a40c53e68de61eccd993a46

[ "Unlicense", "MIT" ]

null

tests/test.py

rose-okoth/News-API

1c19fe74903105599a40c53e68de61eccd993a46

[ "Unlicense", "MIT" ]

null

import unittest from app.models import News News=news.News class NewsTest(unittest.TestCase): ''' Test class to test the behaviour of the news class ''' if __name__ == '__main__': unittest.main()

26.526316

180

0.68254

import unittest from app.models import News News=news.News class NewsTest(unittest.TestCase): ''' Test class to test the behaviour of the news class ''' def setUp(self): self.new_news = News('CNN','CNN','Surviving in a pandemic','Effects of Covid 19 in the past year',2021-2-22,'https://cnn.com','https://image.tmdb.org/t/p/w500/khsjha27hbs') def test_instance(self): self.assertTrue(isinstance(self.new_news,News)) if __name__ == '__main__': unittest.main()

235

0

54

b155700b84e2bb0d3b9d155501dd2186f8955f11

2,095

py

Python

pygraph/functions/searching/astar.py

schlpbch/pygraph

037bb2f32503fecb60d62921f9766d54109f15e2

[ "MIT" ]

62

2015-08-24T14:51:17.000Z

2021-08-03T03:19:15.000Z

pygraph/functions/searching/astar.py

schlpbch/pygraph

037bb2f32503fecb60d62921f9766d54109f15e2

[ "MIT" ]

3

2017-10-31T16:41:51.000Z

2020-04-13T20:49:39.000Z

pygraph/functions/searching/astar.py

schlpbch/pygraph

037bb2f32503fecb60d62921f9766d54109f15e2

[ "MIT" ]

30

2017-04-18T01:42:56.000Z

2021-09-06T09:49:07.000Z

"""Implements A* Search functionality.""" from ...helpers import PriorityQueue from ...exceptions import NonexistentNodeError def a_star_search(graph, start, goal): """Runs an A* search on the specified graph to find a path from the ''start'' node to the ''goal'' node. Returns a list of nodes specifying a minimal path between the two nodes. If no path exists (disconnected components), returns an empty list. """ all_nodes = graph.get_all_node_ids() if start not in all_nodes: raise NonexistentNodeError(start) if goal not in all_nodes: raise NonexistentNodeError(goal) came_from, cost_so_far, goal_reached = _a_star_search_internal(graph, start, goal) if goal_reached: path = reconstruct_path(came_from, start, goal) path.reverse() return path else: return [] # A* Search Helpers def _a_star_search_internal(graph, start, goal): """Performs an A* search, returning information about whether the goal node was reached and path cost information that can be used to reconstruct the path. """ frontier = PriorityQueue() frontier.put(start, 0) came_from = {start: None} cost_so_far = {start: 0} goal_reached = False while not frontier.empty(): current = frontier.get() if current == goal: goal_reached = True break for next_node in graph.neighbors(current): new_cost = cost_so_far[current] + graph.edge_cost(current, next_node) if next_node not in cost_so_far or new_cost < cost_so_far[next_node]: cost_so_far[next_node] = new_cost priority = new_cost + heuristic(goal, next_node) frontier.put(next_node, priority) came_from[next_node] = current return came_from, cost_so_far, goal_reached

31.742424

108

0.663962

"""Implements A* Search functionality.""" from ...helpers import PriorityQueue from ...exceptions import NonexistentNodeError def a_star_search(graph, start, goal): """Runs an A* search on the specified graph to find a path from the ''start'' node to the ''goal'' node. Returns a list of nodes specifying a minimal path between the two nodes. If no path exists (disconnected components), returns an empty list. """ all_nodes = graph.get_all_node_ids() if start not in all_nodes: raise NonexistentNodeError(start) if goal not in all_nodes: raise NonexistentNodeError(goal) came_from, cost_so_far, goal_reached = _a_star_search_internal(graph, start, goal) if goal_reached: path = reconstruct_path(came_from, start, goal) path.reverse() return path else: return [] # A* Search Helpers def heuristic(a, b): return 1 def _a_star_search_internal(graph, start, goal): """Performs an A* search, returning information about whether the goal node was reached and path cost information that can be used to reconstruct the path. """ frontier = PriorityQueue() frontier.put(start, 0) came_from = {start: None} cost_so_far = {start: 0} goal_reached = False while not frontier.empty(): current = frontier.get() if current == goal: goal_reached = True break for next_node in graph.neighbors(current): new_cost = cost_so_far[current] + graph.edge_cost(current, next_node) if next_node not in cost_so_far or new_cost < cost_so_far[next_node]: cost_so_far[next_node] = new_cost priority = new_cost + heuristic(goal, next_node) frontier.put(next_node, priority) came_from[next_node] = current return came_from, cost_so_far, goal_reached def reconstruct_path(came_from, start, goal): current = goal path = [current] while current != start: current = came_from[current] path.append(current) return path

186

0

45

e1d9d2d9a20f6919f3eaa0b19980f164fdc47b5f

30,254

py

Python

addons/survey/models/survey_question.py

SHIVJITH/Odoo_Machine_Test

310497a9872db7844b521e6dab5f7a9f61d365a4

[ "Apache-2.0" ]

null

addons/survey/models/survey_question.py

SHIVJITH/Odoo_Machine_Test

310497a9872db7844b521e6dab5f7a9f61d365a4

[ "Apache-2.0" ]

null

addons/survey/models/survey_question.py

SHIVJITH/Odoo_Machine_Test

310497a9872db7844b521e6dab5f7a9f61d365a4

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Part of Odoo. See LICENSE file for full copyright and licensing details. import collections import json import itertools import operator from odoo import api, fields, models, tools, _ from odoo.exceptions import ValidationError class SurveyQuestion(models.Model): """ Questions that will be asked in a survey. Each question can have one of more suggested answers (eg. in case of multi-answer checkboxes, radio buttons...). Technical note: survey.question is also the model used for the survey's pages (with the "is_page" field set to True). A page corresponds to a "section" in the interface, and the fact that it separates the survey in actual pages in the interface depends on the "questions_layout" parameter on the survey.survey model. Pages are also used when randomizing questions. The randomization can happen within a "page". Using the same model for questions and pages allows to put all the pages and questions together in a o2m field (see survey.survey.question_and_page_ids) on the view side and easily reorganize your survey by dragging the items around. It also removes on level of encoding by directly having 'Add a page' and 'Add a question' links on the tree view of questions, enabling a faster encoding. However, this has the downside of making the code reading a little bit more complicated. Efforts were made at the model level to create computed fields so that the use of these models still seems somewhat logical. That means: - A survey still has "page_ids" (question_and_page_ids filtered on is_page = True) - These "page_ids" still have question_ids (questions located between this page and the next) - These "question_ids" still have a "page_id" That makes the use and display of these information at view and controller levels easier to understand. """ _name = 'survey.question' _description = 'Survey Question' _rec_name = 'title' _order = 'sequence,id' @api.model # question generic data title = fields.Char('Title', required=True, translate=True) description = fields.Html( 'Description', translate=True, sanitize=False, # TDE TODO: sanitize but find a way to keep youtube iframe media stuff help="Use this field to add additional explanations about your question or to illustrate it with pictures or a video") survey_id = fields.Many2one('survey.survey', string='Survey', ondelete='cascade') scoring_type = fields.Selection(related='survey_id.scoring_type', string='Scoring Type', readonly=True) sequence = fields.Integer('Sequence', default=10) # page specific is_page = fields.Boolean('Is a page?') question_ids = fields.One2many('survey.question', string='Questions', compute="_compute_question_ids") questions_selection = fields.Selection( related='survey_id.questions_selection', readonly=True, help="If randomized is selected, add the number of random questions next to the section.") random_questions_count = fields.Integer( 'Random questions count', default=1, help="Used on randomized sections to take X random questions from all the questions of that section.") # question specific page_id = fields.Many2one('survey.question', string='Page', compute="_compute_page_id", store=True) question_type = fields.Selection([ ('text_box', 'Multiple Lines Text Box'), ('char_box', 'Single Line Text Box'), ('numerical_box', 'Numerical Value'), ('date', 'Date'), ('datetime', 'Datetime'), ('simple_choice', 'Multiple choice: only one answer'), ('multiple_choice', 'Multiple choice: multiple answers allowed'), ('matrix', 'Matrix')], string='Question Type', compute='_compute_question_type', readonly=False, store=True) is_scored_question = fields.Boolean( 'Scored', compute='_compute_is_scored_question', readonly=False, store=True, copy=True, help="Include this question as part of quiz scoring. Requires an answer and answer score to be taken into account.") # -- scoreable/answerable simple answer_types: numerical_box / date / datetime answer_numerical_box = fields.Float('Correct numerical answer', help="Correct number answer for this question.") answer_date = fields.Date('Correct date answer', help="Correct date answer for this question.") answer_datetime = fields.Datetime('Correct datetime answer', help="Correct date and time answer for this question.") answer_score = fields.Float('Score', help="Score value for a correct answer to this question.") # -- char_box save_as_email = fields.Boolean( "Save as user email", compute='_compute_save_as_email', readonly=False, store=True, copy=True, help="If checked, this option will save the user's answer as its email address.") save_as_nickname = fields.Boolean( "Save as user nickname", compute='_compute_save_as_nickname', readonly=False, store=True, copy=True, help="If checked, this option will save the user's answer as its nickname.") # -- simple choice / multiple choice / matrix suggested_answer_ids = fields.One2many( 'survey.question.answer', 'question_id', string='Types of answers', copy=True, help='Labels used for proposed choices: simple choice, multiple choice and columns of matrix') allow_value_image = fields.Boolean('Images on answers', help='Display images in addition to answer label. Valid only for simple / multiple choice questions.') # -- matrix matrix_subtype = fields.Selection([ ('simple', 'One choice per row'), ('multiple', 'Multiple choices per row')], string='Matrix Type', default='simple') matrix_row_ids = fields.One2many( 'survey.question.answer', 'matrix_question_id', string='Matrix Rows', copy=True, help='Labels used for proposed choices: rows of matrix') # -- display & timing options column_nb = fields.Selection([ ('12', '1'), ('6', '2'), ('4', '3'), ('3', '4'), ('2', '6')], string='Number of columns', default='12', help='These options refer to col-xx-[12|6|4|3|2] classes in Bootstrap for dropdown-based simple and multiple choice questions.') is_time_limited = fields.Boolean("The question is limited in time", help="Currently only supported for live sessions.") time_limit = fields.Integer("Time limit (seconds)") # -- comments (simple choice, multiple choice, matrix (without count as an answer)) comments_allowed = fields.Boolean('Show Comments Field') comments_message = fields.Char('Comment Message', translate=True, default=lambda self: _("If other, please specify:")) comment_count_as_answer = fields.Boolean('Comment Field is an Answer Choice') # question validation validation_required = fields.Boolean('Validate entry') validation_email = fields.Boolean('Input must be an email') validation_length_min = fields.Integer('Minimum Text Length', default=0) validation_length_max = fields.Integer('Maximum Text Length', default=0) validation_min_float_value = fields.Float('Minimum value', default=0.0) validation_max_float_value = fields.Float('Maximum value', default=0.0) validation_min_date = fields.Date('Minimum Date') validation_max_date = fields.Date('Maximum Date') validation_min_datetime = fields.Datetime('Minimum Datetime') validation_max_datetime = fields.Datetime('Maximum Datetime') validation_error_msg = fields.Char('Validation Error message', translate=True, default=lambda self: _("The answer you entered is not valid.")) constr_mandatory = fields.Boolean('Mandatory Answer') constr_error_msg = fields.Char('Error message', translate=True, default=lambda self: _("This question requires an answer.")) # answers user_input_line_ids = fields.One2many( 'survey.user_input.line', 'question_id', string='Answers', domain=[('skipped', '=', False)], groups='survey.group_survey_user') # Conditional display is_conditional = fields.Boolean( string='Conditional Display', copy=False, help="""If checked, this question will be displayed only if the specified conditional answer have been selected in a previous question""") triggering_question_id = fields.Many2one( 'survey.question', string="Triggering Question", copy=False, compute="_compute_triggering_question_id", store=True, readonly=False, help="Question containing the triggering answer to display the current question.", domain="""[('survey_id', '=', survey_id), '&', ('question_type', 'in', ['simple_choice', 'multiple_choice']), '|', ('sequence', '<', sequence), '&', ('sequence', '=', sequence), ('id', '<', id)]""") triggering_answer_id = fields.Many2one( 'survey.question.answer', string="Triggering Answer", copy=False, compute="_compute_triggering_answer_id", store=True, readonly=False, help="Answer that will trigger the display of the current question.", domain="[('question_id', '=', triggering_question_id)]") _sql_constraints = [ ('positive_len_min', 'CHECK (validation_length_min >= 0)', 'A length must be positive!'), ('positive_len_max', 'CHECK (validation_length_max >= 0)', 'A length must be positive!'), ('validation_length', 'CHECK (validation_length_min <= validation_length_max)', 'Max length cannot be smaller than min length!'), ('validation_float', 'CHECK (validation_min_float_value <= validation_max_float_value)', 'Max value cannot be smaller than min value!'), ('validation_date', 'CHECK (validation_min_date <= validation_max_date)', 'Max date cannot be smaller than min date!'), ('validation_datetime', 'CHECK (validation_min_datetime <= validation_max_datetime)', 'Max datetime cannot be smaller than min datetime!'), ('positive_answer_score', 'CHECK (answer_score >= 0)', 'An answer score for a non-multiple choice question cannot be negative!'), ('scored_datetime_have_answers', "CHECK (is_scored_question != True OR question_type != 'datetime' OR answer_datetime is not null)", 'All "Is a scored question = True" and "Question Type: Datetime" questions need an answer'), ('scored_date_have_answers', "CHECK (is_scored_question != True OR question_type != 'date' OR answer_date is not null)", 'All "Is a scored question = True" and "Question Type: Date" questions need an answer') ] @api.depends('is_page') @api.depends('survey_id.question_and_page_ids.is_page', 'survey_id.question_and_page_ids.sequence') def _compute_question_ids(self): """Will take all questions of the survey for which the index is higher than the index of this page and lower than the index of the next page.""" for question in self: if question.is_page: next_page_index = False for page in question.survey_id.page_ids: if page._index() > question._index(): next_page_index = page._index() break question.question_ids = question.survey_id.question_ids.filtered( lambda q: q._index() > question._index() and (not next_page_index or q._index() < next_page_index) ) else: question.question_ids = self.env['survey.question'] @api.depends('survey_id.question_and_page_ids.is_page', 'survey_id.question_and_page_ids.sequence') def _compute_page_id(self): """Will find the page to which this question belongs to by looking inside the corresponding survey""" for question in self: if question.is_page: question.page_id = None else: page = None for q in question.survey_id.question_and_page_ids.sorted(): if q == question: break if q.is_page: page = q question.page_id = page @api.depends('question_type', 'validation_email') @api.depends('question_type') @api.depends('is_conditional') def _compute_triggering_question_id(self): """ Used as an 'onchange' : Reset the triggering question if user uncheck 'Conditional Display' Avoid CacheMiss : set the value to False if the value is not set yet.""" for question in self: if not question.is_conditional or question.triggering_question_id is None: question.triggering_question_id = False @api.depends('triggering_question_id') def _compute_triggering_answer_id(self): """ Used as an 'onchange' : Reset the triggering answer if user unset or change the triggering question or uncheck 'Conditional Display'. Avoid CacheMiss : set the value to False if the value is not set yet.""" for question in self: if not question.triggering_question_id \ or question.triggering_question_id != question.triggering_answer_id.question_id\ or question.triggering_answer_id is None: question.triggering_answer_id = False @api.depends('question_type', 'scoring_type', 'answer_date', 'answer_datetime', 'answer_numerical_box') def _compute_is_scored_question(self): """ Computes whether a question "is scored" or not. Handles following cases: - inconsistent Boolean=None edge case that breaks tests => False - survey is not scored => False - 'date'/'datetime'/'numerical_box' question types w/correct answer => True (implied without user having to activate, except for numerical whose correct value is 0.0) - 'simple_choice / multiple_choice': set to True even if logic is a bit different (coming from answers) - question_type isn't scoreable (note: choice questions scoring logic handled separately) => False """ for question in self: if question.is_scored_question is None or question.scoring_type == 'no_scoring': question.is_scored_question = False elif question.question_type == 'date': question.is_scored_question = bool(question.answer_date) elif question.question_type == 'datetime': question.is_scored_question = bool(question.answer_datetime) elif question.question_type == 'numerical_box' and question.answer_numerical_box: question.is_scored_question = True elif question.question_type in ['simple_choice', 'multiple_choice']: question.is_scored_question = True else: question.is_scored_question = False # ------------------------------------------------------------ # VALIDATION # ------------------------------------------------------------ def validate_question(self, answer, comment=None): """ Validate question, depending on question type and parameters for simple choice, text, date and number, answer is simply the answer of the question. For other multiple choices questions, answer is a list of answers (the selected choices or a list of selected answers per question -for matrix type-): - Simple answer : answer = 'example' or 2 or question_answer_id or 2019/10/10 - Multiple choice : answer = [question_answer_id1, question_answer_id2, question_answer_id3] - Matrix: answer = { 'rowId1' : [colId1, colId2,...], 'rowId2' : [colId1, colId3, ...] } return dict {question.id (int): error (str)} -> empty dict if no validation error. """ self.ensure_one() if isinstance(answer, str): answer = answer.strip() # Empty answer to mandatory question if self.constr_mandatory and not answer and self.question_type not in ['simple_choice', 'multiple_choice']: return {self.id: self.constr_error_msg} # because in choices question types, comment can count as answer if answer or self.question_type in ['simple_choice', 'multiple_choice']: if self.question_type == 'char_box': return self._validate_char_box(answer) elif self.question_type == 'numerical_box': return self._validate_numerical_box(answer) elif self.question_type in ['date', 'datetime']: return self._validate_date(answer) elif self.question_type in ['simple_choice', 'multiple_choice']: return self._validate_choice(answer, comment) elif self.question_type == 'matrix': return self._validate_matrix(answer) return {} def _index(self): """We would normally just use the 'sequence' field of questions BUT, if the pages and questions are created without ever moving records around, the sequence field can be set to 0 for all the questions. However, the order of the recordset is always correct so we can rely on the index method.""" self.ensure_one() return list(self.survey_id.question_and_page_ids).index(self) # ------------------------------------------------------------ # STATISTICS / REPORTING # ------------------------------------------------------------ def _prepare_statistics(self, user_input_lines): """ Compute statistical data for questions by counting number of vote per choice on basis of filter """ all_questions_data = [] for question in self: question_data = {'question': question, 'is_page': question.is_page} if question.is_page: all_questions_data.append(question_data) continue # fetch answer lines, separate comments from real answers all_lines = user_input_lines.filtered(lambda line: line.question_id == question) if question.question_type in ['simple_choice', 'multiple_choice', 'matrix']: answer_lines = all_lines.filtered( lambda line: line.answer_type == 'suggestion' or ( line.answer_type == 'char_box' and question.comment_count_as_answer) ) comment_line_ids = all_lines.filtered(lambda line: line.answer_type == 'char_box') else: answer_lines = all_lines comment_line_ids = self.env['survey.user_input.line'] skipped_lines = answer_lines.filtered(lambda line: line.skipped) done_lines = answer_lines - skipped_lines question_data.update( answer_line_ids=answer_lines, answer_line_done_ids=done_lines, answer_input_done_ids=done_lines.mapped('user_input_id'), answer_input_skipped_ids=skipped_lines.mapped('user_input_id'), comment_line_ids=comment_line_ids) question_data.update(question._get_stats_summary_data(answer_lines)) # prepare table and graph data table_data, graph_data = question._get_stats_data(answer_lines) question_data['table_data'] = table_data question_data['graph_data'] = json.dumps(graph_data) all_questions_data.append(question_data) return all_questions_data def _get_stats_data_answers(self, user_input_lines): """ Statistics for question.answer based questions (simple choice, multiple choice.). A corner case with a void record survey.question.answer is added to count comments that should be considered as valid answers. This small hack allow to have everything available in the same standard structure. """ suggested_answers = [answer for answer in self.mapped('suggested_answer_ids')] if self.comment_count_as_answer: suggested_answers += [self.env['survey.question.answer']] count_data = dict.fromkeys(suggested_answers, 0) for line in user_input_lines: if line.suggested_answer_id or (line.value_char_box and self.comment_count_as_answer): count_data[line.suggested_answer_id] += 1 table_data = [{ 'value': _('Other (see comments)') if not sug_answer else sug_answer.value, 'suggested_answer': sug_answer, 'count': count_data[sug_answer] } for sug_answer in suggested_answers] graph_data = [{ 'text': _('Other (see comments)') if not sug_answer else sug_answer.value, 'count': count_data[sug_answer] } for sug_answer in suggested_answers] return table_data, graph_data class SurveyQuestionAnswer(models.Model): """ A preconfigured answer for a question. This model stores values used for * simple choice, multiple choice: proposed values for the selection / radio; * matrix: row and column values; """ _name = 'survey.question.answer' _rec_name = 'value' _order = 'sequence, id' _description = 'Survey Label' question_id = fields.Many2one('survey.question', string='Question', ondelete='cascade') matrix_question_id = fields.Many2one('survey.question', string='Question (as matrix row)', ondelete='cascade') sequence = fields.Integer('Label Sequence order', default=10) value = fields.Char('Suggested value', translate=True, required=True) value_image = fields.Image('Image', max_width=256, max_height=256) is_correct = fields.Boolean('Is a correct answer') answer_score = fields.Float('Score for this choice', help="A positive score indicates a correct choice; a negative or null score indicates a wrong answer") @api.constrains('question_id', 'matrix_question_id') def _check_question_not_empty(self): """Ensure that field question_id XOR field matrix_question_id is not null""" for label in self: if not bool(label.question_id) != bool(label.matrix_question_id): raise ValidationError(_("A label must be attached to only one question."))

53.928699

162

0.658888

# -*- coding: utf-8 -*- # Part of Odoo. See LICENSE file for full copyright and licensing details. import collections import json import itertools import operator from odoo import api, fields, models, tools, _ from odoo.exceptions import ValidationError class SurveyQuestion(models.Model): """ Questions that will be asked in a survey. Each question can have one of more suggested answers (eg. in case of multi-answer checkboxes, radio buttons...). Technical note: survey.question is also the model used for the survey's pages (with the "is_page" field set to True). A page corresponds to a "section" in the interface, and the fact that it separates the survey in actual pages in the interface depends on the "questions_layout" parameter on the survey.survey model. Pages are also used when randomizing questions. The randomization can happen within a "page". Using the same model for questions and pages allows to put all the pages and questions together in a o2m field (see survey.survey.question_and_page_ids) on the view side and easily reorganize your survey by dragging the items around. It also removes on level of encoding by directly having 'Add a page' and 'Add a question' links on the tree view of questions, enabling a faster encoding. However, this has the downside of making the code reading a little bit more complicated. Efforts were made at the model level to create computed fields so that the use of these models still seems somewhat logical. That means: - A survey still has "page_ids" (question_and_page_ids filtered on is_page = True) - These "page_ids" still have question_ids (questions located between this page and the next) - These "question_ids" still have a "page_id" That makes the use and display of these information at view and controller levels easier to understand. """ _name = 'survey.question' _description = 'Survey Question' _rec_name = 'title' _order = 'sequence,id' @api.model def default_get(self, fields): defaults = super(SurveyQuestion, self).default_get(fields) if (not fields or 'question_type' in fields): defaults['question_type'] = False if defaults.get('is_page') == True else 'text_box' return defaults # question generic data title = fields.Char('Title', required=True, translate=True) description = fields.Html( 'Description', translate=True, sanitize=False, # TDE TODO: sanitize but find a way to keep youtube iframe media stuff help="Use this field to add additional explanations about your question or to illustrate it with pictures or a video") survey_id = fields.Many2one('survey.survey', string='Survey', ondelete='cascade') scoring_type = fields.Selection(related='survey_id.scoring_type', string='Scoring Type', readonly=True) sequence = fields.Integer('Sequence', default=10) # page specific is_page = fields.Boolean('Is a page?') question_ids = fields.One2many('survey.question', string='Questions', compute="_compute_question_ids") questions_selection = fields.Selection( related='survey_id.questions_selection', readonly=True, help="If randomized is selected, add the number of random questions next to the section.") random_questions_count = fields.Integer( 'Random questions count', default=1, help="Used on randomized sections to take X random questions from all the questions of that section.") # question specific page_id = fields.Many2one('survey.question', string='Page', compute="_compute_page_id", store=True) question_type = fields.Selection([ ('text_box', 'Multiple Lines Text Box'), ('char_box', 'Single Line Text Box'), ('numerical_box', 'Numerical Value'), ('date', 'Date'), ('datetime', 'Datetime'), ('simple_choice', 'Multiple choice: only one answer'), ('multiple_choice', 'Multiple choice: multiple answers allowed'), ('matrix', 'Matrix')], string='Question Type', compute='_compute_question_type', readonly=False, store=True) is_scored_question = fields.Boolean( 'Scored', compute='_compute_is_scored_question', readonly=False, store=True, copy=True, help="Include this question as part of quiz scoring. Requires an answer and answer score to be taken into account.") # -- scoreable/answerable simple answer_types: numerical_box / date / datetime answer_numerical_box = fields.Float('Correct numerical answer', help="Correct number answer for this question.") answer_date = fields.Date('Correct date answer', help="Correct date answer for this question.") answer_datetime = fields.Datetime('Correct datetime answer', help="Correct date and time answer for this question.") answer_score = fields.Float('Score', help="Score value for a correct answer to this question.") # -- char_box save_as_email = fields.Boolean( "Save as user email", compute='_compute_save_as_email', readonly=False, store=True, copy=True, help="If checked, this option will save the user's answer as its email address.") save_as_nickname = fields.Boolean( "Save as user nickname", compute='_compute_save_as_nickname', readonly=False, store=True, copy=True, help="If checked, this option will save the user's answer as its nickname.") # -- simple choice / multiple choice / matrix suggested_answer_ids = fields.One2many( 'survey.question.answer', 'question_id', string='Types of answers', copy=True, help='Labels used for proposed choices: simple choice, multiple choice and columns of matrix') allow_value_image = fields.Boolean('Images on answers', help='Display images in addition to answer label. Valid only for simple / multiple choice questions.') # -- matrix matrix_subtype = fields.Selection([ ('simple', 'One choice per row'), ('multiple', 'Multiple choices per row')], string='Matrix Type', default='simple') matrix_row_ids = fields.One2many( 'survey.question.answer', 'matrix_question_id', string='Matrix Rows', copy=True, help='Labels used for proposed choices: rows of matrix') # -- display & timing options column_nb = fields.Selection([ ('12', '1'), ('6', '2'), ('4', '3'), ('3', '4'), ('2', '6')], string='Number of columns', default='12', help='These options refer to col-xx-[12|6|4|3|2] classes in Bootstrap for dropdown-based simple and multiple choice questions.') is_time_limited = fields.Boolean("The question is limited in time", help="Currently only supported for live sessions.") time_limit = fields.Integer("Time limit (seconds)") # -- comments (simple choice, multiple choice, matrix (without count as an answer)) comments_allowed = fields.Boolean('Show Comments Field') comments_message = fields.Char('Comment Message', translate=True, default=lambda self: _("If other, please specify:")) comment_count_as_answer = fields.Boolean('Comment Field is an Answer Choice') # question validation validation_required = fields.Boolean('Validate entry') validation_email = fields.Boolean('Input must be an email') validation_length_min = fields.Integer('Minimum Text Length', default=0) validation_length_max = fields.Integer('Maximum Text Length', default=0) validation_min_float_value = fields.Float('Minimum value', default=0.0) validation_max_float_value = fields.Float('Maximum value', default=0.0) validation_min_date = fields.Date('Minimum Date') validation_max_date = fields.Date('Maximum Date') validation_min_datetime = fields.Datetime('Minimum Datetime') validation_max_datetime = fields.Datetime('Maximum Datetime') validation_error_msg = fields.Char('Validation Error message', translate=True, default=lambda self: _("The answer you entered is not valid.")) constr_mandatory = fields.Boolean('Mandatory Answer') constr_error_msg = fields.Char('Error message', translate=True, default=lambda self: _("This question requires an answer.")) # answers user_input_line_ids = fields.One2many( 'survey.user_input.line', 'question_id', string='Answers', domain=[('skipped', '=', False)], groups='survey.group_survey_user') # Conditional display is_conditional = fields.Boolean( string='Conditional Display', copy=False, help="""If checked, this question will be displayed only if the specified conditional answer have been selected in a previous question""") triggering_question_id = fields.Many2one( 'survey.question', string="Triggering Question", copy=False, compute="_compute_triggering_question_id", store=True, readonly=False, help="Question containing the triggering answer to display the current question.", domain="""[('survey_id', '=', survey_id), '&', ('question_type', 'in', ['simple_choice', 'multiple_choice']), '|', ('sequence', '<', sequence), '&', ('sequence', '=', sequence), ('id', '<', id)]""") triggering_answer_id = fields.Many2one( 'survey.question.answer', string="Triggering Answer", copy=False, compute="_compute_triggering_answer_id", store=True, readonly=False, help="Answer that will trigger the display of the current question.", domain="[('question_id', '=', triggering_question_id)]") _sql_constraints = [ ('positive_len_min', 'CHECK (validation_length_min >= 0)', 'A length must be positive!'), ('positive_len_max', 'CHECK (validation_length_max >= 0)', 'A length must be positive!'), ('validation_length', 'CHECK (validation_length_min <= validation_length_max)', 'Max length cannot be smaller than min length!'), ('validation_float', 'CHECK (validation_min_float_value <= validation_max_float_value)', 'Max value cannot be smaller than min value!'), ('validation_date', 'CHECK (validation_min_date <= validation_max_date)', 'Max date cannot be smaller than min date!'), ('validation_datetime', 'CHECK (validation_min_datetime <= validation_max_datetime)', 'Max datetime cannot be smaller than min datetime!'), ('positive_answer_score', 'CHECK (answer_score >= 0)', 'An answer score for a non-multiple choice question cannot be negative!'), ('scored_datetime_have_answers', "CHECK (is_scored_question != True OR question_type != 'datetime' OR answer_datetime is not null)", 'All "Is a scored question = True" and "Question Type: Datetime" questions need an answer'), ('scored_date_have_answers', "CHECK (is_scored_question != True OR question_type != 'date' OR answer_date is not null)", 'All "Is a scored question = True" and "Question Type: Date" questions need an answer') ] @api.depends('is_page') def _compute_question_type(self): for question in self: if not question.question_type or question.is_page: question.question_type = False @api.depends('survey_id.question_and_page_ids.is_page', 'survey_id.question_and_page_ids.sequence') def _compute_question_ids(self): """Will take all questions of the survey for which the index is higher than the index of this page and lower than the index of the next page.""" for question in self: if question.is_page: next_page_index = False for page in question.survey_id.page_ids: if page._index() > question._index(): next_page_index = page._index() break question.question_ids = question.survey_id.question_ids.filtered( lambda q: q._index() > question._index() and (not next_page_index or q._index() < next_page_index) ) else: question.question_ids = self.env['survey.question'] @api.depends('survey_id.question_and_page_ids.is_page', 'survey_id.question_and_page_ids.sequence') def _compute_page_id(self): """Will find the page to which this question belongs to by looking inside the corresponding survey""" for question in self: if question.is_page: question.page_id = None else: page = None for q in question.survey_id.question_and_page_ids.sorted(): if q == question: break if q.is_page: page = q question.page_id = page @api.depends('question_type', 'validation_email') def _compute_save_as_email(self): for question in self: if question.question_type != 'char_box' or not question.validation_email: question.save_as_email = False @api.depends('question_type') def _compute_save_as_nickname(self): for question in self: if question.question_type != 'char_box': question.save_as_nickname = False @api.depends('is_conditional') def _compute_triggering_question_id(self): """ Used as an 'onchange' : Reset the triggering question if user uncheck 'Conditional Display' Avoid CacheMiss : set the value to False if the value is not set yet.""" for question in self: if not question.is_conditional or question.triggering_question_id is None: question.triggering_question_id = False @api.depends('triggering_question_id') def _compute_triggering_answer_id(self): """ Used as an 'onchange' : Reset the triggering answer if user unset or change the triggering question or uncheck 'Conditional Display'. Avoid CacheMiss : set the value to False if the value is not set yet.""" for question in self: if not question.triggering_question_id \ or question.triggering_question_id != question.triggering_answer_id.question_id\ or question.triggering_answer_id is None: question.triggering_answer_id = False @api.depends('question_type', 'scoring_type', 'answer_date', 'answer_datetime', 'answer_numerical_box') def _compute_is_scored_question(self): """ Computes whether a question "is scored" or not. Handles following cases: - inconsistent Boolean=None edge case that breaks tests => False - survey is not scored => False - 'date'/'datetime'/'numerical_box' question types w/correct answer => True (implied without user having to activate, except for numerical whose correct value is 0.0) - 'simple_choice / multiple_choice': set to True even if logic is a bit different (coming from answers) - question_type isn't scoreable (note: choice questions scoring logic handled separately) => False """ for question in self: if question.is_scored_question is None or question.scoring_type == 'no_scoring': question.is_scored_question = False elif question.question_type == 'date': question.is_scored_question = bool(question.answer_date) elif question.question_type == 'datetime': question.is_scored_question = bool(question.answer_datetime) elif question.question_type == 'numerical_box' and question.answer_numerical_box: question.is_scored_question = True elif question.question_type in ['simple_choice', 'multiple_choice']: question.is_scored_question = True else: question.is_scored_question = False # ------------------------------------------------------------ # VALIDATION # ------------------------------------------------------------ def validate_question(self, answer, comment=None): """ Validate question, depending on question type and parameters for simple choice, text, date and number, answer is simply the answer of the question. For other multiple choices questions, answer is a list of answers (the selected choices or a list of selected answers per question -for matrix type-): - Simple answer : answer = 'example' or 2 or question_answer_id or 2019/10/10 - Multiple choice : answer = [question_answer_id1, question_answer_id2, question_answer_id3] - Matrix: answer = { 'rowId1' : [colId1, colId2,...], 'rowId2' : [colId1, colId3, ...] } return dict {question.id (int): error (str)} -> empty dict if no validation error. """ self.ensure_one() if isinstance(answer, str): answer = answer.strip() # Empty answer to mandatory question if self.constr_mandatory and not answer and self.question_type not in ['simple_choice', 'multiple_choice']: return {self.id: self.constr_error_msg} # because in choices question types, comment can count as answer if answer or self.question_type in ['simple_choice', 'multiple_choice']: if self.question_type == 'char_box': return self._validate_char_box(answer) elif self.question_type == 'numerical_box': return self._validate_numerical_box(answer) elif self.question_type in ['date', 'datetime']: return self._validate_date(answer) elif self.question_type in ['simple_choice', 'multiple_choice']: return self._validate_choice(answer, comment) elif self.question_type == 'matrix': return self._validate_matrix(answer) return {} def _validate_char_box(self, answer): # Email format validation # all the strings of the form "<something>@<anything>.<extension>" will be accepted if self.validation_email: if not tools.email_normalize(answer): return {self.id: _('This answer must be an email address')} # Answer validation (if properly defined) # Length of the answer must be in a range if self.validation_required: if not (self.validation_length_min <= len(answer) <= self.validation_length_max): return {self.id: self.validation_error_msg} return {} def _validate_numerical_box(self, answer): try: floatanswer = float(answer) except ValueError: return {self.id: _('This is not a number')} if self.validation_required: # Answer is not in the right range with tools.ignore(Exception): if not (self.validation_min_float_value <= floatanswer <= self.validation_max_float_value): return {self.id: self.validation_error_msg} return {} def _validate_date(self, answer): isDatetime = self.question_type == 'datetime' # Checks if user input is a date try: dateanswer = fields.Datetime.from_string(answer) if isDatetime else fields.Date.from_string(answer) except ValueError: return {self.id: _('This is not a date')} if self.validation_required: # Check if answer is in the right range if isDatetime: min_date = fields.Datetime.from_string(self.validation_min_datetime) max_date = fields.Datetime.from_string(self.validation_max_datetime) dateanswer = fields.Datetime.from_string(answer) else: min_date = fields.Date.from_string(self.validation_min_date) max_date = fields.Date.from_string(self.validation_max_date) dateanswer = fields.Date.from_string(answer) if (min_date and max_date and not (min_date <= dateanswer <= max_date))\ or (min_date and not min_date <= dateanswer)\ or (max_date and not dateanswer <= max_date): return {self.id: self.validation_error_msg} return {} def _validate_choice(self, answer, comment): # Empty comment if self.constr_mandatory \ and not answer \ and not (self.comments_allowed and self.comment_count_as_answer and comment): return {self.id: self.constr_error_msg} return {} def _validate_matrix(self, answers): # Validate that each line has been answered if self.constr_mandatory and len(self.matrix_row_ids) != len(answers): return {self.id: self.constr_error_msg} return {} def _index(self): """We would normally just use the 'sequence' field of questions BUT, if the pages and questions are created without ever moving records around, the sequence field can be set to 0 for all the questions. However, the order of the recordset is always correct so we can rely on the index method.""" self.ensure_one() return list(self.survey_id.question_and_page_ids).index(self) # ------------------------------------------------------------ # STATISTICS / REPORTING # ------------------------------------------------------------ def _prepare_statistics(self, user_input_lines): """ Compute statistical data for questions by counting number of vote per choice on basis of filter """ all_questions_data = [] for question in self: question_data = {'question': question, 'is_page': question.is_page} if question.is_page: all_questions_data.append(question_data) continue # fetch answer lines, separate comments from real answers all_lines = user_input_lines.filtered(lambda line: line.question_id == question) if question.question_type in ['simple_choice', 'multiple_choice', 'matrix']: answer_lines = all_lines.filtered( lambda line: line.answer_type == 'suggestion' or ( line.answer_type == 'char_box' and question.comment_count_as_answer) ) comment_line_ids = all_lines.filtered(lambda line: line.answer_type == 'char_box') else: answer_lines = all_lines comment_line_ids = self.env['survey.user_input.line'] skipped_lines = answer_lines.filtered(lambda line: line.skipped) done_lines = answer_lines - skipped_lines question_data.update( answer_line_ids=answer_lines, answer_line_done_ids=done_lines, answer_input_done_ids=done_lines.mapped('user_input_id'), answer_input_skipped_ids=skipped_lines.mapped('user_input_id'), comment_line_ids=comment_line_ids) question_data.update(question._get_stats_summary_data(answer_lines)) # prepare table and graph data table_data, graph_data = question._get_stats_data(answer_lines) question_data['table_data'] = table_data question_data['graph_data'] = json.dumps(graph_data) all_questions_data.append(question_data) return all_questions_data def _get_stats_data(self, user_input_lines): if self.question_type == 'simple_choice': return self._get_stats_data_answers(user_input_lines) elif self.question_type == 'multiple_choice': table_data, graph_data = self._get_stats_data_answers(user_input_lines) return table_data, [{'key': self.title, 'values': graph_data}] elif self.question_type == 'matrix': return self._get_stats_graph_data_matrix(user_input_lines) return [line for line in user_input_lines], [] def _get_stats_data_answers(self, user_input_lines): """ Statistics for question.answer based questions (simple choice, multiple choice.). A corner case with a void record survey.question.answer is added to count comments that should be considered as valid answers. This small hack allow to have everything available in the same standard structure. """ suggested_answers = [answer for answer in self.mapped('suggested_answer_ids')] if self.comment_count_as_answer: suggested_answers += [self.env['survey.question.answer']] count_data = dict.fromkeys(suggested_answers, 0) for line in user_input_lines: if line.suggested_answer_id or (line.value_char_box and self.comment_count_as_answer): count_data[line.suggested_answer_id] += 1 table_data = [{ 'value': _('Other (see comments)') if not sug_answer else sug_answer.value, 'suggested_answer': sug_answer, 'count': count_data[sug_answer] } for sug_answer in suggested_answers] graph_data = [{ 'text': _('Other (see comments)') if not sug_answer else sug_answer.value, 'count': count_data[sug_answer] } for sug_answer in suggested_answers] return table_data, graph_data def _get_stats_graph_data_matrix(self, user_input_lines): suggested_answers = self.mapped('suggested_answer_ids') matrix_rows = self.mapped('matrix_row_ids') count_data = dict.fromkeys(itertools.product(matrix_rows, suggested_answers), 0) for line in user_input_lines: if line.matrix_row_id and line.suggested_answer_id: count_data[(line.matrix_row_id, line.suggested_answer_id)] += 1 table_data = [{ 'row': row, 'columns': [{ 'suggested_answer': sug_answer, 'count': count_data[(row, sug_answer)] } for sug_answer in suggested_answers], } for row in matrix_rows] graph_data = [{ 'key': sug_answer.value, 'values': [{ 'text': row.value, 'count': count_data[(row, sug_answer)] } for row in matrix_rows ] } for sug_answer in suggested_answers] return table_data, graph_data def _get_stats_summary_data(self, user_input_lines): stats = {} if self.question_type in ['simple_choice', 'multiple_choice']: stats.update(self._get_stats_summary_data_choice(user_input_lines)) elif self.question_type == 'numerical_box': stats.update(self._get_stats_summary_data_numerical(user_input_lines)) if self.question_type in ['numerical_box', 'date', 'datetime']: stats.update(self._get_stats_summary_data_scored(user_input_lines)) return stats def _get_stats_summary_data_choice(self, user_input_lines): right_inputs, partial_inputs = self.env['survey.user_input'], self.env['survey.user_input'] right_answers = self.suggested_answer_ids.filtered(lambda label: label.is_correct) if self.question_type == 'multiple_choice': for user_input, lines in tools.groupby(user_input_lines, operator.itemgetter('user_input_id')): user_input_answers = self.env['survey.user_input.line'].concat(*lines).filtered(lambda l: l.answer_is_correct).mapped('suggested_answer_id') if user_input_answers and user_input_answers < right_answers: partial_inputs += user_input elif user_input_answers: right_inputs += user_input else: right_inputs = user_input_lines.filtered(lambda line: line.answer_is_correct).mapped('user_input_id') return { 'right_answers': right_answers, 'right_inputs_count': len(right_inputs), 'partial_inputs_count': len(partial_inputs), } def _get_stats_summary_data_numerical(self, user_input_lines): all_values = user_input_lines.filtered(lambda line: not line.skipped).mapped('value_numerical_box') lines_sum = sum(all_values) return { 'numerical_max': max(all_values, default=0), 'numerical_min': min(all_values, default=0), 'numerical_average': round(lines_sum / (len(all_values) or 1), 2), } def _get_stats_summary_data_scored(self, user_input_lines): return { 'common_lines': collections.Counter( user_input_lines.filtered(lambda line: not line.skipped).mapped('value_%s' % self.question_type) ).most_common(5) if self.question_type != 'datetime' else [], 'right_inputs_count': len(user_input_lines.filtered(lambda line: line.answer_is_correct).mapped('user_input_id')) } class SurveyQuestionAnswer(models.Model): """ A preconfigured answer for a question. This model stores values used for * simple choice, multiple choice: proposed values for the selection / radio; * matrix: row and column values; """ _name = 'survey.question.answer' _rec_name = 'value' _order = 'sequence, id' _description = 'Survey Label' question_id = fields.Many2one('survey.question', string='Question', ondelete='cascade') matrix_question_id = fields.Many2one('survey.question', string='Question (as matrix row)', ondelete='cascade') sequence = fields.Integer('Label Sequence order', default=10) value = fields.Char('Suggested value', translate=True, required=True) value_image = fields.Image('Image', max_width=256, max_height=256) is_correct = fields.Boolean('Is a correct answer') answer_score = fields.Float('Score for this choice', help="A positive score indicates a correct choice; a negative or null score indicates a wrong answer") @api.constrains('question_id', 'matrix_question_id') def _check_question_not_empty(self): """Ensure that field question_id XOR field matrix_question_id is not null""" for label in self: if not bool(label.question_id) != bool(label.matrix_question_id): raise ValidationError(_("A label must be attached to only one question."))

7,456

0

401

64bcde3e3778f24206da1450da29a5bf8fcaeb50

1,448

py

Python

gcloud_dataproc/submit.py

macarthur-lab/hail-elasticsearch-pipelines

7082681fd125e4f23a512aeff49853c5fc0f3136

[ "MIT" ]

15

2017-11-22T14:48:04.000Z

2020-10-05T18:22:24.000Z

gcloud_dataproc/submit.py

macarthur-lab/hail-elasticsearch-pipelines

7082681fd125e4f23a512aeff49853c5fc0f3136

[ "MIT" ]

86

2017-12-14T23:45:29.000Z

2020-10-13T18:15:54.000Z

gcloud_dataproc/submit.py

macarthur-lab/hail-elasticsearch-pipelines

7082681fd125e4f23a512aeff49853c5fc0f3136

[ "MIT" ]

7

2019-01-29T09:08:10.000Z

2020-02-25T16:22:57.000Z

#!/usr/bin/env python import argparse import os import subprocess import tempfile if __name__ == '__main__': p = argparse.ArgumentParser() p.add_argument("-c", "--cluster", default="no-vep") p.add_argument("script") args, unparsed_args = p.parse_known_args() submit(args.script, unparsed_args, cluster=args.cluster)

33.674419

148

0.674724

#!/usr/bin/env python import argparse import os import subprocess import tempfile def submit(script, script_args_list, cluster='no-vep', wait_for_job=True, use_existing_scripts_zip=False, region=None, spark_env=None, job_id=None): script_args = " ".join(['"%s"' % arg for arg in script_args_list]) hail_scripts_zip = os.path.join(tempfile.gettempdir(), 'hail_scripts.zip') os.chdir(os.path.join(os.path.dirname(__file__), "..")) if use_existing_scripts_zip and os.path.exists(hail_scripts_zip): print('Using existing scripts zip file') else: os.system( "zip -r %(hail_scripts_zip)s hail_scripts kubernetes sv_pipeline download_and_create_reference_datasets/v02/hail_scripts" % locals()) command = f"""gcloud dataproc jobs submit pyspark \ --cluster={cluster} \ --py-files={hail_scripts_zip} \ {f'--properties="spark.executorEnv.{spark_env}"' if spark_env else ''} \ {f'--region={region}' if region else ''} \ {f'--id={job_id}' if job_id else ''} \ {'' if wait_for_job else '--async'} \ "{script}" -- {script_args} """ print(command) subprocess.check_call(command, shell=True) if __name__ == '__main__': p = argparse.ArgumentParser() p.add_argument("-c", "--cluster", default="no-vep") p.add_argument("script") args, unparsed_args = p.parse_known_args() submit(args.script, unparsed_args, cluster=args.cluster)

1,083

0

23

309813fa77ab295af0296cf9deb86684b7f31eaa

1,827

py

Python

wavelet/compression/compressor_magnitude.py

AP-Atul/wavelets-ext

00ced22462c369584ebd32f9b5f357f092de0142

[ "MIT" ]

4

2021-02-01T07:43:10.000Z

2021-04-27T06:58:54.000Z

wavelet/compression/compressor_magnitude.py

AP-Atul/wavelets-ext

00ced22462c369584ebd32f9b5f357f092de0142

[ "MIT" ]

null

wavelet/compression/compressor_magnitude.py

AP-Atul/wavelets-ext

00ced22462c369584ebd32f9b5f357f092de0142

[ "MIT" ]

null

""" Compression using the average of signal as a magnitude """ import numpy as np from .compressor import Compressor class CompressorMagnitude: """ The average of the signal is used to perform the compression on the input data signal. Check the Compressor class on how the thresholding is done with the magnitude Attributes ---------- __magnitude: float magnitude calculated using the average of the signal __compressor: Compressor object to call the compress function using the magnitude calculated """ def compress(self, data): """ Apply thresholding techniques to remove the signal below the magnitude Parameters ---------- data: array_like input data signal, mostly coefficients output of the decompose Returns ------- array_like thresholded data/ coefficients """ self.__magnitude = np.sum(data, axis=0) lenD = len(data) return self.__compressor.compress(data, (self.__magnitude / lenD)) def getCompressionRate(self, data): """ Run the compression calculation on the data to check how well the compressor performed Parameters ---------- data: array_like input data from the final step of re-construction Returns ------- float percentage of the compression """ return self.__compressor.calculateCompressionRate(data) def getMagnitude(self): """ Returns the calculated magnitude Returns ------- float calculated magnitude """ return self.__magnitude

25.375

84

0.605911

""" Compression using the average of signal as a magnitude """ import numpy as np from .compressor import Compressor class CompressorMagnitude: """ The average of the signal is used to perform the compression on the input data signal. Check the Compressor class on how the thresholding is done with the magnitude Attributes ---------- __magnitude: float magnitude calculated using the average of the signal __compressor: Compressor object to call the compress function using the magnitude calculated """ def __init__(self): self.__magnitude = 0. self.__compressor = Compressor() def compress(self, data): """ Apply thresholding techniques to remove the signal below the magnitude Parameters ---------- data: array_like input data signal, mostly coefficients output of the decompose Returns ------- array_like thresholded data/ coefficients """ self.__magnitude = np.sum(data, axis=0) lenD = len(data) return self.__compressor.compress(data, (self.__magnitude / lenD)) def getCompressionRate(self, data): """ Run the compression calculation on the data to check how well the compressor performed Parameters ---------- data: array_like input data from the final step of re-construction Returns ------- float percentage of the compression """ return self.__compressor.calculateCompressionRate(data) def getMagnitude(self): """ Returns the calculated magnitude Returns ------- float calculated magnitude """ return self.__magnitude

69

0

27

96186744d6789db434bb6817cc7c93a3fee17ace

2,246

py

Python

mkcloud.py

JunhoYeo/mkcloud

2a4629fdbbf954a55283f8d3ba5e430a221e4b94

[ "MIT" ]

1

2018-08-13T23:51:57.000Z

mkcloud.py

JunhoYeo/mkcloud

2a4629fdbbf954a55283f8d3ba5e430a221e4b94

[ "MIT" ]

null

mkcloud.py

JunhoYeo/mkcloud

2a4629fdbbf954a55283f8d3ba5e430a221e4b94

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- from wordcloud import WordCloud, ImageColorGenerator from PIL import Image import numpy as np import random if __name__ == '__main__': import re import multidict as multidict text = getFrequencyDictForText(open('lorem-ipsum.txt').read()) mkcloud('lorem-ipsum.png', text, '#FFF2CC', '#F030A8')

35.09375

94

0.601514

#!/usr/bin/env python3 # -*- coding: utf-8 -*- from wordcloud import WordCloud, ImageColorGenerator from PIL import Image import numpy as np import random def mkcloud(filename, dic, theme_start, theme_end): def linear_gradient(n=10): ''' returns a gradient list of (n) colors between two hex colors. start_hex and finish_hex should be the full six-digit color string, inlcuding the number sign ("#FFFFFF") ''' # https://gist.github.com/RoboDonut/83ec5909621a6037f275799032e97563 start = tuple(int(theme_start.lstrip('#')[i:i+2], 16) for i in (0, 2 ,4)) end = tuple(int(theme_end.lstrip('#')[i:i+2], 16) for i in (0, 2 ,4)) RGB_list = [start] for t in range(1, n): curr_vector = tuple([ int(start[j] + (float(t)/(n-1))*(end[j]-start[j])) for j in range(3) ]) RGB_list.append(curr_vector) return ['#%02x%02x%02x'%i for i in RGB_list] colors = linear_gradient() def color_from_theme(word, font_size, position, orientation, random_state=None, **kwargs): return random.choice(colors) font_path = './NotoSansCJKkr-Regular.otf' x, y = np.ogrid[:800, :800] mask = (x - 400) ** 2 + (y - 400) ** 2 > 360 ** 2 mask = 255 * mask.astype(int) wc = WordCloud( color_func=color_from_theme, font_path=font_path, background_color="rgba(255, 255, 255, 0)", mode="RGBA", mask=mask, width=800, height=800 ) wc.generate_from_frequencies(dic) wc.to_file(filename) if __name__ == '__main__': import re import multidict as multidict def getFrequencyDictForText(sentence): fullTermsDict = multidict.MultiDict() tmpDict = {} for text in sentence.split(" "): if re.match("a|the|an|the|to|in|for|of|or|by|with|is|on|that|be", text): continue val = tmpDict.get(text, 0) tmpDict[text.lower()] = val + 1 for key in tmpDict: fullTermsDict.add(key, tmpDict[key]) return dict(fullTermsDict) text = getFrequencyDictForText(open('lorem-ipsum.txt').read()) mkcloud('lorem-ipsum.png', text, '#FFF2CC', '#F030A8')

1,833

0

50

8119d973649690caaf8fc15259c7a1f12bccb05a

289

py

Python

fe_cipher/constants/areas.py

uakihir0/fecipher

dd5c2a0d47d2701570b43f4906bdec993f4d571c

[ "MIT" ]

3

2020-01-16T10:53:26.000Z

2020-01-16T10:53:40.000Z

fe_cipher/constants/areas.py

uakihir0/fecipher

dd5c2a0d47d2701570b43f4906bdec993f4d571c

[ "MIT" ]

null

fe_cipher/constants/areas.py

uakihir0/fecipher

dd5c2a0d47d2701570b43f4906bdec993f4d571c

[ "MIT" ]

1

2020-01-16T11:08:15.000Z

# -*- coding: utf-8 -*- from enum import Enum # エリア定義

11.56

23

0.435986

# -*- coding: utf-8 -*- from enum import Enum # エリア定義 class Areas(Enum): # デッキ Deck = 1 # 手札 Hand = 2 # 絆 Bond = 3 # 前衛 FrontLine = 4 # 後衛 BackLine = 5 # 退避 Retreat = 6 # 支援 Support = 7 # オーブ Orb = 8 # 無限 Mugen = 9

0

249

22

395b142680f5cde9c72f9f6f5f6119c63915dae1

4,052

py

Python

attention.py

dsj96/TITS

c84f04bdb9f1f0af5f6cca1e6a10151e4dae162d

[ "MIT" ]

2

2021-12-05T16:34:05.000Z

2021-12-30T00:25:29.000Z

attention.py

dsj96/CTVI-master

ea9c4dc812ff871c7ccb2e3748e35d3b634920d0

[ "MIT" ]

null

attention.py

dsj96/CTVI-master

ea9c4dc812ff871c7ccb2e3748e35d3b634920d0

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F from torch.nn.functional import softmax import torch.optim as optim from torch.autograd import Variable import math import numpy as np from utils import write_pkl, read_pkl if __name__ == "__main__": '''self-attention''' input_data = torch.tensor(np.arange(24.).reshape(2,3,4),dtype=torch.float32) attention = Multi_Head_SelfAttention(num_head=3,num_vocab=3,input_dim=4,hidden_dim=5,out_dim=5) output_data = attention(input_data) print("output_data: \n",output_data) '''position encoder''' # input_data = torch.tensor([[[1,0,1,0],[0,2,0,2],[1,1,1,1]], [[1,0,1,0],[0,2,0,2],[1,1,1,1]] ],dtype=torch.float32) # print("input_data:\n",input_data) # positional_encoder = PositionalEncoder(d_model=4) # 该参数代表输出的嵌入维度，因为需要和输入的 # output_data = positional_encoder(input_data) # print("output_data:\n", output_data)

37.174312

121

0.628825

import torch import torch.nn as nn import torch.nn.functional as F from torch.nn.functional import softmax import torch.optim as optim from torch.autograd import Variable import math import numpy as np from utils import write_pkl, read_pkl class SelfAttention(nn.Module): def __init__(self, num_vocab, input_dim, hidden_dim): super(SelfAttention, self).__init__() self.num_vocab = num_vocab self.input_dim = input_dim self.hidden_dim = hidden_dim self.query_W = nn.Linear(input_dim, hidden_dim) self.key_W = nn.Linear(input_dim, hidden_dim) self.value_W = nn.Linear(input_dim, hidden_dim) self.position_encoder = PositionalEncoder(d_model=hidden_dim) self.init() def init(self): stdv = 1. / math.sqrt(self.query_W.weight.size(1)) self.query_W.weight.data.uniform_(-stdv, stdv) stdv = 1. / math.sqrt(self.query_W.weight.size(1)) self.key_W.weight.data.uniform_(-stdv, stdv) stdv = 1. / math.sqrt(self.query_W.weight.size(1)) self.key_W.weight.data.uniform_(-stdv, stdv) def forward(self, input_data): query_M = self.query_W(input_data) key_M = self.key_W(input_data) value_M = self.value_W(input_data) attn_scores = query_M @ key_M.transpose(-1,-2) attn_scores = attn_scores / math.sqrt(self.hidden_dim) attn_scores_softmax = softmax(attn_scores, dim=-1) outputs = self.position_encoder(attn_scores_softmax.bmm(value_M)) return outputs class Multi_Head_SelfAttention(nn.Module): def __init__(self, num_head, num_vocab, input_dim, hidden_dim, out_dim): super(Multi_Head_SelfAttention, self).__init__() self.num_head = num_head self.num_vocab = num_vocab self.input_dim = input_dim self.hidden_dim = hidden_dim self.fn = nn.Linear(num_head*hidden_dim, out_dim) self.at_block_list = [] for i in range(self.num_head): self.at_block_list.append(SelfAttention(self.num_vocab, self.input_dim, self.hidden_dim)) def forward(self, input_data): output_list = [] for i in range(self.num_head): cur_output = self.at_block_list[i](input_data) output_list.append(cur_output) output_M = torch.cat(output_list,dim=-1) outputs = self.fn(output_M) return outputs class PositionalEncoder(nn.Module): def __init__(self, d_model, max_seq_len = 30): super(PositionalEncoder, self).__init__() self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") self.d_model = d_model self.max_seq_len = max_seq_len self.pe = torch.zeros((self.max_seq_len, self.d_model), requires_grad=False) for pos in range(self.max_seq_len): for i in range(0, self.d_model, 2): self.pe[pos, i] = \ math.sin(pos / (10000 ** ((2 * i)/self.d_model))) if i+1< self.d_model: self.pe[pos, i + 1] = \ math.cos(pos / (10000 ** ((2 * (i + 1))/self.d_model))) def forward(self, x): seq_len = x.shape[1] x = x + self.pe[:seq_len,:self.d_model] return x if __name__ == "__main__": '''self-attention''' input_data = torch.tensor(np.arange(24.).reshape(2,3,4),dtype=torch.float32) attention = Multi_Head_SelfAttention(num_head=3,num_vocab=3,input_dim=4,hidden_dim=5,out_dim=5) output_data = attention(input_data) print("output_data: \n",output_data) '''position encoder''' # input_data = torch.tensor([[[1,0,1,0],[0,2,0,2],[1,1,1,1]], [[1,0,1,0],[0,2,0,2],[1,1,1,1]] ],dtype=torch.float32) # print("input_data:\n",input_data) # positional_encoder = PositionalEncoder(d_model=4) # 该参数代表输出的嵌入维度，因为需要和输入的 # output_data = positional_encoder(input_data) # print("output_data:\n", output_data)

2,776

45

276

9bf0c5caf42b14da0e2cf82be9da2e2e41b653cd

840

py

Python

sqlite_dissect/tests/case_export_test.py

Defense-Cyber-Crime-Center/sqlite-dissect

e1a6c19928bc092bf7aeaff71072634f77a452ea

[ "MIT" ]

12

2021-10-21T21:23:51.000Z

2022-03-13T03:01:53.000Z

sqlite_dissect/tests/case_export_test.py

Defense-Cyber-Crime-Center/sqlite-dissect

e1a6c19928bc092bf7aeaff71072634f77a452ea

[ "MIT" ]

21

2021-09-13T17:00:33.000Z

2022-03-31T12:56:56.000Z

sqlite_dissect/tests/case_export_test.py

kchason/sqlite-dissect

e1a6c19928bc092bf7aeaff71072634f77a452ea

[ "MIT" ]

1

2021-10-21T22:00:07.000Z

import os import unittest from main import main from sqlite_dissect.utilities import DotDict class TestCASEExport(unittest.TestCase): """ This class tests a parsing of a file and ensuring that it properly generates a CASE export file. """

27.096774

100

0.627381

import os import unittest from main import main from sqlite_dissect.utilities import DotDict class TestCASEExport(unittest.TestCase): """ This class tests a parsing of a file and ensuring that it properly generates a CASE export file. """ def test_case_output(self): # Build the arguments for the testing args = { 'log_level': 'debug', 'export': ['case'], 'directory': 'output', 'sqlite_file': 'test_files/chinook.db' } # Convert the dictionary to a dot-accessible object for the main parsing args = DotDict(args) # Call the main argument main(args) # Ensure the case.json file exists self.assertTrue(os.path.exists('output/case.json')) self.assertTrue(os.path.isfile('output/case.json'))

559

0

27

f2f782820b6e0361ff854c10c04a57c67e53f14a

3,489

py

Python

bot.py

victor-tsai/discord-bot

44ef9bcaa69c5ea682be56efe88df091dc0784c3

[ "MIT" ]

null

bot.py

victor-tsai/discord-bot

44ef9bcaa69c5ea682be56efe88df091dc0784c3

[ "MIT" ]

null

bot.py

victor-tsai/discord-bot

44ef9bcaa69c5ea682be56efe88df091dc0784c3

[ "MIT" ]

null

#!/usr/bin/python3 import requests from discord.ext import commands TOKEN = "Your Discord token here" OWNER_ID = 0 # Your user ID here RTT_USERNAME = "Realtime Trains API username" RTT_PASSWORD = "Realtime Trains API password" ## BOT SETUP bot = commands.Bot(command_prefix = ">") # Comment to respond to messages from anyone @bot.check ## UTILITY FUNCTIONS ## COMMANDS @bot.command() @bot.command() @bot.command() bot.run(TOKEN)

37.117021

109

0.518487

#!/usr/bin/python3 import requests from discord.ext import commands TOKEN = "Your Discord token here" OWNER_ID = 0 # Your user ID here RTT_USERNAME = "Realtime Trains API username" RTT_PASSWORD = "Realtime Trains API password" ## BOT SETUP bot = commands.Bot(command_prefix = ">") # Comment to respond to messages from anyone @bot.check def isOwner(ctx): async def predicate(ctx): return ctx.author.id == OWNER_ID return commands.check(predicate) ## UTILITY FUNCTIONS def rttDepartures(station): rttData = requests.get("https://api.rtt.io/api/v1/json/search/"+station, auth = (RTT_USERNAME, RTT_PASSWORD)) rttJson = rttData.json() rttColour = 0xFF0000 try: rttTitle = ("Departures from **%s**, powered by **Realtime Trains**" % rttJson["location"]["name"]) rttDescription = (" ID | Time | Live | Plat | Destination\n" + "-" * 41 + "\n") if rttJson["services"] == None: rttDescription = "No services at the moment." else: for service in rttJson["services"]: if len(rttDescription)<1800: try: trainID = service["runningIdentity"] except KeyError: trainID = service["trainIdentity"] depTime = service["locationDetail"]["gbttBookedDeparture"] depTimeFormatted = depTime[:2] + ":" + depTime[2:] try: liveTime = service["locationDetail"]["realtimeDeparture"] liveTimeFormatted = liveTime[:2] + ":" + liveTime[2:] except KeyError: liveTimeFormatted = " N/A " try: # | 10A* | # | 12B | # | 13 | # | 6 | MAX_PLAT_CHARS = 4 platform = service["locationDetail"]["platform"] if service["locationDetail"]["platformChanged"]: platform += "*" if len(platform) < MAX_PLAT_CHARS: platform += " " * (MAX_PLAT_CHARS - len(platform)) except KeyError: platform = "----" destination = service["locationDetail"]["destination"][0]["description"] rttDescription += ("%s | %s | %s | %s | %s\n" % (trainID, depTimeFormatted, liveTimeFormatted, platform, destination)) except KeyError: rttTitle = "Please give me a valid NRS (3 letters) or TIPLOC (7 characters) code." rttDescription = ("It appears that you took a wrong route back at " + "Croxley Green Jn, as the rails to this station don't appear to exist " + "anymore. Just in case there was meant to be a station here, we've told " + "the permanent way team and they'll have a look into it.") rttMessage = rttTitle + "\n```" + rttDescription + "```" return rttMessage ## COMMANDS @bot.command() async def ping(ctx): await ctx.send("pong") @bot.command() async def logout(ctx): await ctx.bot.logout() @bot.command() async def trains(ctx, station): await ctx.send(rttDepartures(station)) bot.run(TOKEN)

2,935

0

110

42e8e2aaaeb8d0c7280bc8c0f0d4326303a7a369

558

py

Python

Mundo_1/aula07.py

GabrielProdi/Python_CursoEmVideo

8bfff1b9a73d09c8f42dc3778f895525f1bc946d

[ "MIT" ]

null

Mundo_1/aula07.py

GabrielProdi/Python_CursoEmVideo

8bfff1b9a73d09c8f42dc3778f895525f1bc946d

[ "MIT" ]

null

Mundo_1/aula07.py

GabrielProdi/Python_CursoEmVideo

8bfff1b9a73d09c8f42dc3778f895525f1bc946d

[ "MIT" ]

null

#Operadores Aritmeticos n1 = int( input('Digite um número: ' ) ) n2 = int( input('Digite outro número: ' ) ) soma = n1 + n2 prod = n1 * n2 div = n1 / n2 divint = n1 // n2 exp = n1 ** n2 resto = n1 % n2 # {: } os dois pontos formatam o valor da mascara conforme as diretrizes #quebra de linha é \n # end= escrever o conteudo no final do print print( 'A soma é {}, \no produto é {} \ne a divisão é {:.2}. '.format( soma, prod, div ), end='' ) print( 'A divisão inteira é {}, \na potenciação é {} \ne o resto da divisão é {}'.format( divint, exp, resto ) )

32.823529

112

0.629032

#Operadores Aritmeticos n1 = int( input('Digite um número: ' ) ) n2 = int( input('Digite outro número: ' ) ) soma = n1 + n2 prod = n1 * n2 div = n1 / n2 divint = n1 // n2 exp = n1 ** n2 resto = n1 % n2 # {: } os dois pontos formatam o valor da mascara conforme as diretrizes #quebra de linha é \n # end= escrever o conteudo no final do print print( 'A soma é {}, \no produto é {} \ne a divisão é {:.2}. '.format( soma, prod, div ), end='' ) print( 'A divisão inteira é {}, \na potenciação é {} \ne o resto da divisão é {}'.format( divint, exp, resto ) )

0

596d64b56e4d8d8991ebc5da5fab0164bcddc3e1

3,156

py

Python

regression/gallery/contour9.py

b8raoult/magics

eb2c86ec6e392e89c90044128dc671f22283d6ad

[ "ECL-2.0", "Apache-2.0" ]

41

2018-12-07T23:10:50.000Z

2022-02-19T03:01:49.000Z

regression/gallery/contour9.py

b8raoult/magics

eb2c86ec6e392e89c90044128dc671f22283d6ad

[ "ECL-2.0", "Apache-2.0" ]

59

2019-01-04T15:43:30.000Z

2022-03-31T09:48:15.000Z

regression/gallery/contour9.py

b8raoult/magics

eb2c86ec6e392e89c90044128dc671f22283d6ad

[ "ECL-2.0", "Apache-2.0" ]

13

2019-01-07T14:36:33.000Z

2021-09-06T14:48:36.000Z

# (C) Copyright 1996-2016 ECMWF. # # This software is licensed under the terms of the Apache Licence Version 2.0 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0. # In applying this licence, ECMWF does not waive the privileges and immunities # granted to it by virtue of its status as an intergovernmental organisation nor # does it submit to any jurisdiction. from Magics.macro import * #Loading GRIB file data = mgrib(grib_input_file_name='2m_temperature.grib',grib_field_position=1) #Setting output output = output( output_formats = ['png'], output_name = 'contour9', output_name_first_page_number = 'off') #Setting the geographical area area = mmap( subpage_lower_left_latitude = 34.5, subpage_lower_left_longitude = -10.67, subpage_map_projection = 'cylindrical', subpage_upper_right_latitude = 71.05, subpage_upper_right_longitude = 31.55, ) #Setting the coastlines background = mcoast( map_coastline_land_shade = 'on', map_coastline_land_shade_colour = 'cream') foreground = mcoast( map_coastline_land_shade = 'off', map_grid_line_style = 'dash', map_grid_colour = 'grey', map_label = 'on', map_coastline_colour = 'black') #Defining the contour contour = mcont( contour = 'off', contour_highlight_frequency = 100, contour_highlight_thickness = 5, contour_hilo = 'off', contour_interval = 2.0, contour_label = 'off', contour_level_selection_type = 'interval', contour_line_thickness = 3, contour_shade = 'on', contour_shade_colour_list = ['rgb(0.3,0.3,0.3)', 'rgb(0.4,0.4,0.4)', 'rgb(0.5,0.5,0.5)', 'rgb(0.6,0.6,0.6)', 'rgb(0.7,0.7,0.7)', 'rgb(0.8,0.8,0.8)', 'rgb(0.35,0,0.6)', 'rgb(0.5,0,0.9)', 'rgb(0.6,0.2,1)', 'rgb(0.75,0.4,1)', 'rgb(0.85,0.6,1)', 'rgb(0,0,0.75)', 'rgb(0,0,1)', 'rgb(0.2,0.4,1)', 'rgb(0.4,0.7,1)', 'rgb(0.6,0.9,1)', 'rgb(0,0.55,0.19)', 'rgb(0.15,0.75,0.1)', 'rgb(0.5,0.85,0)', 'rgb(0.65,0.95,0)', 'rgb(0.8,1,0.2)', 'rgb(0.65,0.65,0)', 'rgb(0.8,0.8,0)', 'rgb(0.92,0.92,0)', 'rgb(1,1,0)', 'rgb(1,1,0.6)', 'rgb(0.85,0.45,0)', 'rgb(1,0.5,0)', 'rgb(1,0.62,0)', 'rgb(1,0.74,0)', 'rgb(1,0.85,0)', 'rgb(0.6,0,0)', 'rgb(0.8,0,0)', 'rgb(1,0,0)', 'rgb(1,0.4,0.4)', 'rgb(1,0.6,0.6)', 'rgb(1,0.75,0.75)'], contour_shade_colour_method = 'list', contour_shade_max_level = 42.0, contour_shade_method = 'area_fill', contour_shade_min_level = -32.0, legend = 'on', ) #Picking the grib metadata title = mtext( text_lines = ['2m temperature (Range: -32 .. 42)','<magics_title/>'], text_justification = 'left', text_font_size = 0.6, text_colour = 'charcoal') #Plotting plot(output,area,background,data,title,contour,foreground) #For documentation only tofortran('contour9',output,area,data,background,contour,foreground,title) tomv4('contour9',contour) tohtml('contour9',data,contour)

43.232877

709

0.606781

# (C) Copyright 1996-2016 ECMWF. # # This software is licensed under the terms of the Apache Licence Version 2.0 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0. # In applying this licence, ECMWF does not waive the privileges and immunities # granted to it by virtue of its status as an intergovernmental organisation nor # does it submit to any jurisdiction. from Magics.macro import * #Loading GRIB file data = mgrib(grib_input_file_name='2m_temperature.grib',grib_field_position=1) #Setting output output = output( output_formats = ['png'], output_name = 'contour9', output_name_first_page_number = 'off') #Setting the geographical area area = mmap( subpage_lower_left_latitude = 34.5, subpage_lower_left_longitude = -10.67, subpage_map_projection = 'cylindrical', subpage_upper_right_latitude = 71.05, subpage_upper_right_longitude = 31.55, ) #Setting the coastlines background = mcoast( map_coastline_land_shade = 'on', map_coastline_land_shade_colour = 'cream') foreground = mcoast( map_coastline_land_shade = 'off', map_grid_line_style = 'dash', map_grid_colour = 'grey', map_label = 'on', map_coastline_colour = 'black') #Defining the contour contour = mcont( contour = 'off', contour_highlight_frequency = 100, contour_highlight_thickness = 5, contour_hilo = 'off', contour_interval = 2.0, contour_label = 'off', contour_level_selection_type = 'interval', contour_line_thickness = 3, contour_shade = 'on', contour_shade_colour_list = ['rgb(0.3,0.3,0.3)', 'rgb(0.4,0.4,0.4)', 'rgb(0.5,0.5,0.5)', 'rgb(0.6,0.6,0.6)', 'rgb(0.7,0.7,0.7)', 'rgb(0.8,0.8,0.8)', 'rgb(0.35,0,0.6)', 'rgb(0.5,0,0.9)', 'rgb(0.6,0.2,1)', 'rgb(0.75,0.4,1)', 'rgb(0.85,0.6,1)', 'rgb(0,0,0.75)', 'rgb(0,0,1)', 'rgb(0.2,0.4,1)', 'rgb(0.4,0.7,1)', 'rgb(0.6,0.9,1)', 'rgb(0,0.55,0.19)', 'rgb(0.15,0.75,0.1)', 'rgb(0.5,0.85,0)', 'rgb(0.65,0.95,0)', 'rgb(0.8,1,0.2)', 'rgb(0.65,0.65,0)', 'rgb(0.8,0.8,0)', 'rgb(0.92,0.92,0)', 'rgb(1,1,0)', 'rgb(1,1,0.6)', 'rgb(0.85,0.45,0)', 'rgb(1,0.5,0)', 'rgb(1,0.62,0)', 'rgb(1,0.74,0)', 'rgb(1,0.85,0)', 'rgb(0.6,0,0)', 'rgb(0.8,0,0)', 'rgb(1,0,0)', 'rgb(1,0.4,0.4)', 'rgb(1,0.6,0.6)', 'rgb(1,0.75,0.75)'], contour_shade_colour_method = 'list', contour_shade_max_level = 42.0, contour_shade_method = 'area_fill', contour_shade_min_level = -32.0, legend = 'on', ) #Picking the grib metadata title = mtext( text_lines = ['2m temperature (Range: -32 .. 42)','<magics_title/>'], text_justification = 'left', text_font_size = 0.6, text_colour = 'charcoal') #Plotting plot(output,area,background,data,title,contour,foreground) #For documentation only tofortran('contour9',output,area,data,background,contour,foreground,title) tomv4('contour9',contour) tohtml('contour9',data,contour)

0

2a71651e70b4a7528bd63355ddd1957a197426fa

154,019

py

Python

ui/psychsim_rc.py

richardyang/psychsim

191497d72077fe95cde94a2004a8be6e926c121f

[ "MIT" ]

1

2016-07-19T16:56:46.000Z

ui/psychsim_rc.py

richardyang/psychsim

191497d72077fe95cde94a2004a8be6e926c121f

[ "MIT" ]

1

2018-08-27T22:31:16.000Z

ui/psychsim_rc.py

richardyang/psychsim

191497d72077fe95cde94a2004a8be6e926c121f

[ "MIT" ]

1

2019-09-06T03:05:35.000Z

# -*- coding: utf-8 -*- # Resource object code # # Created: Mon Dec 22 15:59:06 2014 # by: The Resource Compiler for PyQt (Qt v4.8.6) # # WARNING! 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65.317642

96

0.727274

# -*- coding: utf-8 -*- # Resource object code # # Created: Mon Dec 22 15:59:06 2014 # by: The Resource Compiler for PyQt (Qt v4.8.6) # # WARNING! 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\xba\x93\x34\x38\x43\xba\x62\x43\x35\x34\x03\x9d\x38\xc7\xbf\x62\ \x03\x34\x10\x25\x36\x48\x83\x3b\xc6\x6c\xc4\xf2\xab\x46\xaa\x23\ \xcb\x66\x43\xb3\x1e\x64\x36\x78\x6b\xa3\x6c\x2c\xbc\x62\xec\x34\ \x3c\x54\x56\xc0\x2b\x36\x20\x43\x35\x38\x83\xbd\x52\x03\x0d\x89\ \xe6\x64\x06\x87\x44\xc0\x23\xb1\x24\x85\x88\x67\x9d\xc3\x16\x85\ \x85\x93\x78\x44\xb2\x50\x28\x72\x10\xc8\x31\x35\x27\x0c\x99\x5c\ \x6a\x1e\xcc\xd0\x6c\x52\x6f\x64\x43\x39\x34\xa8\x32\xfd\xda\x48\ \xb0\xc4\xdc\xa0\x50\x99\xc5\x45\xb2\x08\x8b\x81\xe4\x0d\x92\x84\ \x52\x92\x30\x8a\x4b\x30\xc4\x63\x8e\xc4\x44\xf0\x47\x45\xfc\xa7\ \xa0\xbc\xc4\x32\x21\x14\x57\xe8\x89\x49\x8c\xc3\x26\x05\xc7\x7d\ \x58\x1a\xca\xc0\xc4\x56\x70\x04\xde\x84\x05\xee\x64\x04\x6f\x7a\ \x6d\x38\x9c\x03\xa0\xa0\xd0\xb3\xfc\xc9\x39\x9c\xc3\xe2\xfe\x87\ \x93\x50\xd7\x4b\x40\x13\x31\x1d\xc7\x71\x54\x84\x37\x04\x04\x00\ \x3b\ " qt_resource_name = "\ \x00\x0c\ \x07\x0d\xbe\x16\ \x00\x70\ \x00\x73\x00\x79\x00\x63\x00\x68\x00\x73\x00\x69\x00\x6d\x00\x2e\x00\x67\x00\x69\x00\x66\ " qt_resource_struct = "\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x01\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\ " def qInitResources(): QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data) def qCleanupResources(): QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data) qInitResources()

195

0

46

ec4441541b2c6be31fc394effb8172bbc4f5104c

457

py

Python

moreover/base/config.py

moriW/moreover

330b49f4888211d2502208c13c3fff49a24124ad

[ "MIT" ]

null

moreover/base/config.py

moriW/moreover

330b49f4888211d2502208c13c3fff49a24124ad

[ "MIT" ]

null

moreover/base/config.py

moriW/moreover

330b49f4888211d2502208c13c3fff49a24124ad

[ "MIT" ]

null

#! /bin/python # config store & parse # # @file: config # @time: 2022/02/05 # @author: Mori # import json from tornado.util import ObjectDict global_config = ObjectDict()

19.041667

50

0.691466

#! /bin/python # config store & parse # # @file: config # @time: 2022/02/05 # @author: Mori # import json from tornado.util import ObjectDict global_config = ObjectDict() def define(config: str, default_value: str): if config in global_config: raise KeyError(f"{config} already exists") global_config[config] = default_value def parse_config_file(file: str): with open(file, "r") as _f: global_config.update(json.load(_f))

236

0

46

536db5165bdc70a8820e97cc1b002c271c3566b3

4,824

py

Python

noolite/noolite/noolite.py

andvikt/ha_addons

98343e6465516b821008abd58c38f5f4306e0d41

[ "Apache-2.0" ]

null

noolite/noolite/noolite.py

andvikt/ha_addons

98343e6465516b821008abd58c38f5f4306e0d41

[ "Apache-2.0" ]

null

noolite/noolite/noolite.py

andvikt/ha_addons

98343e6465516b821008abd58c38f5f4306e0d41

[ "Apache-2.0" ]

null

import asyncio from datetime import datetime import serial from logger import root_logger from . import const from .typing import NooliteCommand, BaseNooliteRemote, MotionSensor from typing import Dict, Callable import typing lg = root_logger.getChild('noolite') def _get_tty(tty_name) -> serial.Serial: """ Подключение к последовательному порту :param tty_name: имя порта :return: """ serial_port = serial.Serial(tty_name, 9600, timeout=2) if not serial_port.is_open: serial_port.open() serial_port.flushInput() serial_port.flushOutput() return serial_port

33.041096

119

0.583126

import asyncio from datetime import datetime import serial from logger import root_logger from . import const from .typing import NooliteCommand, BaseNooliteRemote, MotionSensor from typing import Dict, Callable import typing lg = root_logger.getChild('noolite') class NotApprovedError(Exception): pass class Noolite: def __init__( self, tty_name: str, loop: typing.Optional[asyncio.AbstractEventLoop], ): self.callbacks: Dict[int, Callable] = {} self.global_cbs = [] self._cmd_log: typing.Dict[int, datetime] = {} self.event_que: asyncio.Queue[BaseNooliteRemote] = asyncio.Queue() self.tty = _get_tty(tty_name) self.loop = loop self.loop.add_reader(self.tty.fd, self._handle_tty) self.wait_ftr: typing.Optional[asyncio.Future] = None self.wait_cmd: typing.Optional[NooliteCommand] = None self.send_lck = asyncio.Lock() def _handle_tty(self): """ Хендлер входящих данных от адаптера :return: """ while self.tty.in_waiting >= 17: in_bytes = self.tty.read(17) resp = NooliteCommand(*(x for x in in_bytes)) lg.debug(f'< %s', list(in_bytes)) if self._cancel_waiting(resp): return asyncio.create_task(self.handle_command(resp)) def _cancel_waiting(self, msg: NooliteCommand): """ Отменяет ожидание подвтерждения, возвращает истину если ожидание было, ложь, если нет :return: """ if isinstance(self.wait_ftr, asyncio.Future) \ and msg.ch == self.wait_cmd.ch \ and msg.mode == self.wait_cmd.mode: self.wait_ftr.set_result(True) lg.debug(f'{"Approved:".rjust(20, " ")} {self.wait_cmd}') return True else: return False @property async def in_commands(self): """ Возвращает пришедшие команды в бесконечном цикле :return: """ while True: yield await self.event_que.get() async def handle_command(self, resp: NooliteCommand): """ При приеме входящего сообщения нужно вызвать этот метод :param resp: :return: """ try: dispatcher, name = const.dispatchers.get(resp.cmd, (None, None)) if name: lg.debug(f'dispatching {name}') if dispatcher is None: dispatcher = BaseNooliteRemote remote = dispatcher(resp) if isinstance(remote, MotionSensor): l = self._cmd_log.get(remote.channel) self._cmd_log[remote.channel] = datetime.now() if l is not None: td = (datetime.now() - l).total_seconds() if td < const.MOTION_JITTER: lg.debug(f'anti-jitter: {resp}') return await self.event_que.put(remote) except Exception: lg.exception(f'handling {resp}') raise async def send_command(self, command: typing.Union[NooliteCommand, bytearray]): """ Отправляет команды, асинхронно, ждет подтверждения уже отправленной команды :param command: :return: """ # отправляем только одну команду до получения подтверждения async with self.send_lck: if isinstance(command, NooliteCommand): cmd = command.as_tuple() else: cmd = command lg.debug(f'> {cmd}') self.tty.write(bytearray(cmd)) # отправляем команду и ждем секунду, если придет ответ, то ожидание будет отменено с ошибкой CancelledError # - значит от модуля пришел ответ о подтверждении команды, в противном случае поднимаем ошибку о том что # команда не подтверждена if command.commit is None: return True self.wait_ftr = self.loop.create_future() self.wait_cmd = command try: await asyncio.wait_for(self.wait_ftr, command.commit) await asyncio.sleep(0.05) except asyncio.CancelledError: return True except asyncio.TimeoutError: raise NotApprovedError(command) finally: self.wait_ftr = None self.wait_cmd = None def _get_tty(tty_name) -> serial.Serial: """ Подключение к последовательному порту :param tty_name: имя порта :return: """ serial_port = serial.Serial(tty_name, 9600, timeout=2) if not serial_port.is_open: serial_port.open() serial_port.flushInput() serial_port.flushOutput() return serial_port

600

4,056

46

9aee6f1dfe827e83a81f5a8a41f450caac1713ea

5,555

py

Python

tests/test_fixtures.py

eSchwander/airbyte-tentacle

da1957d9150fccb4ea8fdcd6567e2fb5aa62853d

[ "Unlicense" ]

null

tests/test_fixtures.py

eSchwander/airbyte-tentacle

da1957d9150fccb4ea8fdcd6567e2fb5aa62853d

[ "Unlicense" ]

null

tests/test_fixtures.py

eSchwander/airbyte-tentacle

da1957d9150fccb4ea8fdcd6567e2fb5aa62853d

[ "Unlicense" ]

null

import pytest from airbyte_dto_factory import * from airbyte_config_model import * @pytest.fixture def dummy_source_dto(): """ Creates a dummy SourceDto """ source = SourceDto() source.source_definition_id = 'ef69ef6e-aa7f-4af1-a01d-ef775033524e' source.source_id = '7d95ec85-47c6-42d4-a7a2-8e5c22c810d2' source.workspace_id = 'f3b9e848-790c-4cdd-a475-5c6bb156dc10' source.connection_configuration = { 'access_token': '**********' } source.name = 'apache/superset' source.source_name = 'GitHub' source.tag = 'tag1' return source @pytest.fixture def dummy_destination_dto(): """ Creates a dummy DestinationDto """ destination = DestinationDto() destination.destination_definition_id = '25c5221d-dce2-4163-ade9-739ef790f503' destination.destination_id = 'a41cb2f8-fcce-4c91-adfe-37c4586609f5' destination.workspace_id = 'f3b9e848-790c-4cdd-a475-5c6bb156dc10' destination.connection_configuration = { 'database': 'postgres', 'host': 'hostname.com', 'port': '5432', 'schema': 'demo', 'username': 'devrel_master', 'password': '**********' } destination.name = 'devrel-rds' destination.destination_name = 'Postgres' destination.tag = 'tag2' return destination @pytest.fixture def dummy_source_definitions(): """ Create a dummy source definition (as dict) """ source_definitions = [{'sourceDefinitionId': 'c2281cee-86f9-4a86-bb48-d23286b4c7bd', 'name': 'Slack', 'dockerRepository': 'airbyte/source-slack', 'dockerImageTag': '0.1.9', 'documentationUrl': 'https://docs.airbyte.io/integrations/sources/slack', 'icon': 'icon.png'}, {'sourceDefinitionId': 'ef69ef6e-aa7f-4af1-a01d-ef775033524e', 'name': 'GitHub', 'dockerRepository': 'airbyte/source-github-singer', 'dockerImageTag': '0.1.7', 'documentationUrl': 'https://hub.docker.com/r/airbyte/source-github-singer', 'icon': None}] return source_definitions @pytest.fixture def dummy_destination_definitions(): """ c=Create a dummy destination definition (as dict) """ destination_definitions = [{'destinationDefinitionId': '22f6c74f-5699-40ff-833c-4a879ea40133', 'name': 'BigQuery', 'dockerRepository': 'airbyte/destination-bigquery', 'dockerImageTag': '0.3.12', 'documentationUrl': 'https://docs.airbyte.io/integrations/destinations/bigquery', 'icon': None}, {'destinationDefinitionId': '25c5221d-dce2-4163-ade9-739ef790f503', 'name': 'Postgres', 'dockerRepository': 'airbyte/destination-postgres', 'dockerImageTag': '0.3.5', 'documentationUrl': 'https://docs.airbyte.io/integrations/destinations/postgres', 'icon': None}] return destination_definitions @pytest.fixture def dummy_source_dict(): """ Creates a dummy source dict """ source_dict = { 'sourceDefinitionId': 'ef69ef6e-aa7f-4af1-a01d-ef775033524e', 'sourceId': '7d95ec85-47c6-42d4-a7a2-8e5c22c810d2', 'workspaceId': 'f3b9e848-790c-4cdd-a475-5c6bb156dc10', 'connectionConfiguration': {'access_token': '**********'}, 'name': 'apache/superset', 'sourceName': 'GitHub', 'tag': 'tag1' } return source_dict @pytest.fixture def dummy_destination_dict(): """ Creates a dummy destination dict """ destination_dict = { 'destinationDefinitionId': '25c5221d-dce2-4163-ade9-739ef790f503', 'destinationId': 'a41cb2f8-fcce-4c91-adfe-37c4586609f5', 'workspaceId': 'f3b9e848-790c-4cdd-a475-5c6bb156dc10', 'connectionConfiguration': { 'database': 'postgres', 'host': 'hostname.com', 'port': '5432', 'schema': 'demo', 'username': 'devrel_master', 'password': '**********' }, 'name': 'devrel-rds', 'destinationName': 'Postgres', 'tag': 'tag2' } return destination_dict @pytest.fixture def dummy_airbyte_dto_factory(dummy_source_definitions, dummy_destination_definitions): """ Create a dummy AirbyteDtoFactory given a set of dummy source and destination definitions """ dto_factory = AirbyteDtoFactory(dummy_source_definitions, dummy_destination_definitions) return dto_factory @pytest.fixture def dummy_secrets_dict(): """ Create dummy secrets for the dummy sources and destinations (as dict) """ secrets_dict = { 'sources': { 'GitHub': {'access_token': 'ghp_SECRET_TOKEN'}, 'Slack': {'token': 'SLACK_SECRET_TOKEN'} }, 'destinations': { 'Postgres': {'password': 'SECRET_POSTGRES_PASSWORD'} } } return secrets_dict @pytest.fixture

35.83871

130

0.607381

import pytest from airbyte_dto_factory import * from airbyte_config_model import * @pytest.fixture def dummy_source_dto(): """ Creates a dummy SourceDto """ source = SourceDto() source.source_definition_id = 'ef69ef6e-aa7f-4af1-a01d-ef775033524e' source.source_id = '7d95ec85-47c6-42d4-a7a2-8e5c22c810d2' source.workspace_id = 'f3b9e848-790c-4cdd-a475-5c6bb156dc10' source.connection_configuration = { 'access_token': '**********' } source.name = 'apache/superset' source.source_name = 'GitHub' source.tag = 'tag1' return source @pytest.fixture def dummy_destination_dto(): """ Creates a dummy DestinationDto """ destination = DestinationDto() destination.destination_definition_id = '25c5221d-dce2-4163-ade9-739ef790f503' destination.destination_id = 'a41cb2f8-fcce-4c91-adfe-37c4586609f5' destination.workspace_id = 'f3b9e848-790c-4cdd-a475-5c6bb156dc10' destination.connection_configuration = { 'database': 'postgres', 'host': 'hostname.com', 'port': '5432', 'schema': 'demo', 'username': 'devrel_master', 'password': '**********' } destination.name = 'devrel-rds' destination.destination_name = 'Postgres' destination.tag = 'tag2' return destination @pytest.fixture def dummy_source_definitions(): """ Create a dummy source definition (as dict) """ source_definitions = [{'sourceDefinitionId': 'c2281cee-86f9-4a86-bb48-d23286b4c7bd', 'name': 'Slack', 'dockerRepository': 'airbyte/source-slack', 'dockerImageTag': '0.1.9', 'documentationUrl': 'https://docs.airbyte.io/integrations/sources/slack', 'icon': 'icon.png'}, {'sourceDefinitionId': 'ef69ef6e-aa7f-4af1-a01d-ef775033524e', 'name': 'GitHub', 'dockerRepository': 'airbyte/source-github-singer', 'dockerImageTag': '0.1.7', 'documentationUrl': 'https://hub.docker.com/r/airbyte/source-github-singer', 'icon': None}] return source_definitions @pytest.fixture def dummy_destination_definitions(): """ c=Create a dummy destination definition (as dict) """ destination_definitions = [{'destinationDefinitionId': '22f6c74f-5699-40ff-833c-4a879ea40133', 'name': 'BigQuery', 'dockerRepository': 'airbyte/destination-bigquery', 'dockerImageTag': '0.3.12', 'documentationUrl': 'https://docs.airbyte.io/integrations/destinations/bigquery', 'icon': None}, {'destinationDefinitionId': '25c5221d-dce2-4163-ade9-739ef790f503', 'name': 'Postgres', 'dockerRepository': 'airbyte/destination-postgres', 'dockerImageTag': '0.3.5', 'documentationUrl': 'https://docs.airbyte.io/integrations/destinations/postgres', 'icon': None}] return destination_definitions @pytest.fixture def dummy_source_dict(): """ Creates a dummy source dict """ source_dict = { 'sourceDefinitionId': 'ef69ef6e-aa7f-4af1-a01d-ef775033524e', 'sourceId': '7d95ec85-47c6-42d4-a7a2-8e5c22c810d2', 'workspaceId': 'f3b9e848-790c-4cdd-a475-5c6bb156dc10', 'connectionConfiguration': {'access_token': '**********'}, 'name': 'apache/superset', 'sourceName': 'GitHub', 'tag': 'tag1' } return source_dict @pytest.fixture def dummy_destination_dict(): """ Creates a dummy destination dict """ destination_dict = { 'destinationDefinitionId': '25c5221d-dce2-4163-ade9-739ef790f503', 'destinationId': 'a41cb2f8-fcce-4c91-adfe-37c4586609f5', 'workspaceId': 'f3b9e848-790c-4cdd-a475-5c6bb156dc10', 'connectionConfiguration': { 'database': 'postgres', 'host': 'hostname.com', 'port': '5432', 'schema': 'demo', 'username': 'devrel_master', 'password': '**********' }, 'name': 'devrel-rds', 'destinationName': 'Postgres', 'tag': 'tag2' } return destination_dict @pytest.fixture def dummy_airbyte_dto_factory(dummy_source_definitions, dummy_destination_definitions): """ Create a dummy AirbyteDtoFactory given a set of dummy source and destination definitions """ dto_factory = AirbyteDtoFactory(dummy_source_definitions, dummy_destination_definitions) return dto_factory @pytest.fixture def dummy_secrets_dict(): """ Create dummy secrets for the dummy sources and destinations (as dict) """ secrets_dict = { 'sources': { 'GitHub': {'access_token': 'ghp_SECRET_TOKEN'}, 'Slack': {'token': 'SLACK_SECRET_TOKEN'} }, 'destinations': { 'Postgres': {'password': 'SECRET_POSTGRES_PASSWORD'} } } return secrets_dict @pytest.fixture def dummy_populated_airbyte_config_model(dummy_source_dto, dummy_destination_dto): config_model = AirbyteConfigModel() config_model.sources[dummy_source_dto.source_id] = dummy_source_dto config_model.destinations[dummy_destination_dto.destination_id] = dummy_destination_dto return config_model

289

0

22

2de2341754414a1f6e7e2477849cb8c74ee43b69

2,109

py

Python

qubot/config/config.py

anthonykrivonos/qubot

0cc9623a22fe75a0c8d4a08ac8adc96184dc2ae7

[ "MIT" ]

2

2021-02-14T03:53:50.000Z

2021-03-23T17:59:20.000Z

qubot/config/config.py

anthonykrivonos/qubot

0cc9623a22fe75a0c8d4a08ac8adc96184dc2ae7

[ "MIT" ]

null

qubot/config/config.py

anthonykrivonos/qubot

0cc9623a22fe75a0c8d4a08ac8adc96184dc2ae7

[ "MIT" ]

null

from typing import List class QubotConfigTerminalInfo: """ Abstracts information on the terminal nodes to find. """ class QubotConfigModelParameters: """ Abstracts information on the Q-Learning model parameters. """ def __init__(self, alpha=0.5, gamma=0.6, epsilon=1, decay=0.01, train_episodes=1000, test_episodes=100, step_limit=100): """ Initializes the model configuration parameters. :param alpha: Higher alpha => consider more recent information (learning rate). :param gamma: Higher gamma => long term rewards. :param epsilon: Higher epsilon => favor exploitation. :param decay: Higher decay => epsilon decreases faster (more randomness). :param train_episodes: The number of episodes to train Qubot on. :param test_episodes: The number of episodes to test Qubot on. :param step_limit: Maximum number of steps to take before force-exiting the episode. """ self.alpha = alpha self.gamma = gamma self.epsilon = epsilon self.decay = decay self.train_episodes = train_episodes self.test_episodes = test_episodes self.step_limit = step_limit class QubotDriverParameters: """ Abstracts information on the Selenium Driver parameters. """ def __init__(self, use_cache: bool = False, max_urls: int = 10): """ Initializes the Selenium configuration parameters. :param use_cache: Use the cache when scraping the website under test? :param max_urls: Maximum number of recursive URLs to visit during scraping. """ self.use_cache = use_cache self.max_urls = max_urls

42.18

133

0.688004

from typing import List class QubotConfigTerminalInfo: """ Abstracts information on the terminal nodes to find. """ def __init__(self, terminal_ids: List[str] = None, terminal_classes: List[str] = None, terminal_contains_text: List[str] = None): self.terminal_ids = terminal_ids if terminal_ids is not None else [] self.terminal_classes = terminal_classes if terminal_classes is not None else [] self.terminal_contains_text = terminal_contains_text if terminal_contains_text is not None else [] class QubotConfigModelParameters: """ Abstracts information on the Q-Learning model parameters. """ def __init__(self, alpha=0.5, gamma=0.6, epsilon=1, decay=0.01, train_episodes=1000, test_episodes=100, step_limit=100): """ Initializes the model configuration parameters. :param alpha: Higher alpha => consider more recent information (learning rate). :param gamma: Higher gamma => long term rewards. :param epsilon: Higher epsilon => favor exploitation. :param decay: Higher decay => epsilon decreases faster (more randomness). :param train_episodes: The number of episodes to train Qubot on. :param test_episodes: The number of episodes to test Qubot on. :param step_limit: Maximum number of steps to take before force-exiting the episode. """ self.alpha = alpha self.gamma = gamma self.epsilon = epsilon self.decay = decay self.train_episodes = train_episodes self.test_episodes = test_episodes self.step_limit = step_limit class QubotDriverParameters: """ Abstracts information on the Selenium Driver parameters. """ def __init__(self, use_cache: bool = False, max_urls: int = 10): """ Initializes the Selenium configuration parameters. :param use_cache: Use the cache when scraping the website under test? :param max_urls: Maximum number of recursive URLs to visit during scraping. """ self.use_cache = use_cache self.max_urls = max_urls

381

0

26

07baeeac2fe71021abc2ba135d5e09a36888cf1c

2,416

py

Python

jom/freq.py

JoM-Lab/JoM

cd03fd401ebbd8133c8b4816115bb87e2fd24690

[ "MIT" ]

1

2016-03-10T04:52:56.000Z

jom/freq.py

JoM-Lab/JoM

cd03fd401ebbd8133c8b4816115bb87e2fd24690

[ "MIT" ]

null

jom/freq.py

JoM-Lab/JoM

cd03fd401ebbd8133c8b4816115bb87e2fd24690

[ "MIT" ]

null

#!/usr/bin/env python3 # coding: utf-8 from __future__ import unicode_literals, print_function from collections import Counter from .db import new_session, Tweet import string import re zh = re.compile(r"[\u4e00-\u9fa5]+") other = re.compile(r"[a-zA-Z0-9_]+") bad = ("_ 1 2 3 4 5 I O RT The a and are be bit co com for gt http https html in " "is it jpg ly me media my not of on org p pbs png r s status t that the this to " "twimg via www you").split() alphanum = set(string.ascii_letters + string.digits) def freq(texts, limit=400, p=12): '''Find the most frequent words and their frequencies in a set of texts. :param texts: a list of strings :type texts: List[str] :param int limit: a soft limit to cut off some words :param int p: longest word length :return: list of words and frequencies :rtype: List[(str, int)] ''' cnt = Counter() cntE = Counter() for l in texts: # find all Chinese for w in zh.findall(l): saw = set() for ln in range(2, p+1): # all length for i in range(len(w)-(ln-1)): # all start pos saw.add(w[i:i+ln].strip('的').lstrip('了')) for v in saw: cnt[v] += 1 # English words and digits for w in other.findall(l): cntE[w] += 1 for w in bad: cntE[w] = 0 # remove # find top `limit` ones freqs = cnt.most_common(limit) # initialize results as top 10 English words & digits results = list(cntE.most_common(10)) # already in results filt = Counter() # from longest to shortest for ln in range(p, 1, -1): # find all with this length but a part of longer ones cur = [(k, v) for k, v in freqs if len(k) == ln] # filter some with `filt` cur = [(k, v) for k, v in cur if k not in filt or filt[k] * 2 < v] cur.sort(key=lambda t: t[1], reverse=True) results.extend(cur) # put all parts into `filt` for w, v in cur: for l in range(2, ln): for i in range(len(w)-(l-1)): filt[w[i:i+l]] += v # print(results) return results if __name__ == '__main__': session = new_session() texts = [i.text for i in session.query(Tweet.text).filter(Tweet.sender == 'masked')] cnt = freq(texts) print(sorted([(v, k) for k, v in cnt], reverse=True))

34.514286

88

0.579056

#!/usr/bin/env python3 # coding: utf-8 from __future__ import unicode_literals, print_function from collections import Counter from .db import new_session, Tweet import string import re zh = re.compile(r"[\u4e00-\u9fa5]+") other = re.compile(r"[a-zA-Z0-9_]+") bad = ("_ 1 2 3 4 5 I O RT The a and are be bit co com for gt http https html in " "is it jpg ly me media my not of on org p pbs png r s status t that the this to " "twimg via www you").split() alphanum = set(string.ascii_letters + string.digits) def freq(texts, limit=400, p=12): '''Find the most frequent words and their frequencies in a set of texts. :param texts: a list of strings :type texts: List[str] :param int limit: a soft limit to cut off some words :param int p: longest word length :return: list of words and frequencies :rtype: List[(str, int)] ''' cnt = Counter() cntE = Counter() for l in texts: # find all Chinese for w in zh.findall(l): saw = set() for ln in range(2, p+1): # all length for i in range(len(w)-(ln-1)): # all start pos saw.add(w[i:i+ln].strip('的').lstrip('了')) for v in saw: cnt[v] += 1 # English words and digits for w in other.findall(l): cntE[w] += 1 for w in bad: cntE[w] = 0 # remove # find top `limit` ones freqs = cnt.most_common(limit) # initialize results as top 10 English words & digits results = list(cntE.most_common(10)) # already in results filt = Counter() # from longest to shortest for ln in range(p, 1, -1): # find all with this length but a part of longer ones cur = [(k, v) for k, v in freqs if len(k) == ln] # filter some with `filt` cur = [(k, v) for k, v in cur if k not in filt or filt[k] * 2 < v] cur.sort(key=lambda t: t[1], reverse=True) results.extend(cur) # put all parts into `filt` for w, v in cur: for l in range(2, ln): for i in range(len(w)-(l-1)): filt[w[i:i+l]] += v # print(results) return results if __name__ == '__main__': session = new_session() texts = [i.text for i in session.query(Tweet.text).filter(Tweet.sender == 'masked')] cnt = freq(texts) print(sorted([(v, k) for k, v in cnt], reverse=True))

0

6fdd4da2f419ff8d134e23b97de8a08353bf1a3a

429

py

Python

utils/sms.py

ljygit/12306

3de32a7046a2cfef35c1a2793172607237bc7ef7

[ "MIT" ]

1

2020-06-22T10:18:09.000Z

utils/sms.py

ljygit/12306

3de32a7046a2cfef35c1a2793172607237bc7ef7

[ "MIT" ]

8

2021-03-19T03:19:50.000Z

2022-03-11T23:58:15.000Z

utils/sms.py

Mr-Mei/12306-

ff6f027497962c34c8ad6df0138e617a7dc8be71

[ "MIT" ]

1

2019-11-18T23:17:07.000Z

from twilio.rest import Client if __name__ == '__main__': from configure import ACCOUNT_SID,AUTO_TOKEN,FROM_NUM,TO_NUM msg = '测试一下，亲爱的路人' send_sms(ACCOUNT_SID,AUTO_TOKEN,FROM_NUM,TO_NUM,msg)

30.642857

64

0.72028

from twilio.rest import Client def send_sms(account_sid,auth_token,from_man,to_man,msg): client = Client(account_sid, auth_token) message = client.messages.create( to=to_man, from_=from_man, body=msg) return message.sid if __name__ == '__main__': from configure import ACCOUNT_SID,AUTO_TOKEN,FROM_NUM,TO_NUM msg = '测试一下，亲爱的路人' send_sms(ACCOUNT_SID,AUTO_TOKEN,FROM_NUM,TO_NUM,msg)

203

0

23

a8b0a4469467b3bf1e3dba6386f211a25e5876c2

1,513

py

Python

revolve.py

safsaf150/revolve

ff12ac6992c99116b9d571dc277165362d8d5602

[ "Apache-2.0" ]

null

revolve.py

safsaf150/revolve

ff12ac6992c99116b9d571dc277165362d8d5602

[ "Apache-2.0" ]

null

revolve.py

safsaf150/revolve

ff12ac6992c99116b9d571dc277165362d8d5602

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 import os import sys from pyrevolve import parser from pyrevolve.util import Supervisor here = os.path.dirname(os.path.abspath(__file__)) rvpath = os.path.abspath(os.path.join(here, '..', 'revolve')) sys.path.append(os.path.dirname(os.path.abspath(__file__))) class OnlineEvolutionSupervisor(Supervisor): """ Supervisor class that adds some output filtering for ODE errors """ def write_stderr(self, data): """ :param data: :return: """ if 'ODE Message 3' in data: self.ode_errors += 1 elif data.strip(): sys.stderr.write(data) if self.ode_errors >= 100: self.ode_errors = 0 sys.stderr.write('ODE Message 3 (100)\n') if __name__ == "__main__": settings = parser.parse_args() manager_settings = sys.argv[1:] supervisor = OnlineEvolutionSupervisor( manager_cmd=settings.manager, manager_args=manager_settings, world_file=settings.world, simulator_cmd=settings.simulator_cmd, simulator_args=["--verbose"], plugins_dir_path=os.path.join(rvpath, 'build', 'lib'), models_dir_path=os.path.join(rvpath, 'models') ) if settings.manager is None: ret = supervisor.launch_simulator() else: ret = supervisor.launch() sys.exit(ret)

27.509091

72

0.636484

#!/usr/bin/env python3 import os import sys from pyrevolve import parser from pyrevolve.util import Supervisor here = os.path.dirname(os.path.abspath(__file__)) rvpath = os.path.abspath(os.path.join(here, '..', 'revolve')) sys.path.append(os.path.dirname(os.path.abspath(__file__))) class OnlineEvolutionSupervisor(Supervisor): """ Supervisor class that adds some output filtering for ODE errors """ def __init__(self, *args, **kwargs): super(OnlineEvolutionSupervisor, self).__init__(*args, **kwargs) self.ode_errors = 0 def write_stderr(self, data): """ :param data: :return: """ if 'ODE Message 3' in data: self.ode_errors += 1 elif data.strip(): sys.stderr.write(data) if self.ode_errors >= 100: self.ode_errors = 0 sys.stderr.write('ODE Message 3 (100)\n') if __name__ == "__main__": settings = parser.parse_args() manager_settings = sys.argv[1:] supervisor = OnlineEvolutionSupervisor( manager_cmd=settings.manager, manager_args=manager_settings, world_file=settings.world, simulator_cmd=settings.simulator_cmd, simulator_args=["--verbose"], plugins_dir_path=os.path.join(rvpath, 'build', 'lib'), models_dir_path=os.path.join(rvpath, 'models') ) if settings.manager is None: ret = supervisor.launch_simulator() else: ret = supervisor.launch() sys.exit(ret)

116

0

27

5a6c067c4c899f822dcfbcf61b4d8154e18f0052

509

py

Python

src/jvm/io/fsq/twofishes/scripts/refresh-store.py

jglesner/fsqio

436dd3a7667fd23f638bf96bdcd9ec83266a2319

[ "Apache-2.0" ]

252

2016-01-08T23:12:13.000Z

2022-01-17T16:31:49.000Z

src/jvm/io/fsq/twofishes/scripts/refresh-store.py

jglesner/fsqio

436dd3a7667fd23f638bf96bdcd9ec83266a2319

[ "Apache-2.0" ]

67

2016-01-13T17:34:12.000Z

2021-08-04T18:50:24.000Z

src/jvm/io/fsq/twofishes/scripts/refresh-store.py

jglesner/fsqio

436dd3a7667fd23f638bf96bdcd9ec83266a2319

[ "Apache-2.0" ]

59

2016-03-25T20:49:03.000Z

2021-08-04T05:36:38.000Z

#!/usr/bin/python import urllib2 import json import sys from optparse import OptionParser usage = "usage: %prog [options] host" parser = OptionParser(usage = usage) parser.add_option("-t", "--token", dest="token", default="", type='string', help="token") (options, args) = parser.parse_args() if len(args) != 1: parser.print_usage() sys.exit(1) host = args[0] data = { "token": options.token } dataStr = json.dumps(data) print urllib2.urlopen('http://%s/private/refreshStore' % host, dataStr).read()

24.238095

78

0.695481

#!/usr/bin/python import urllib2 import json import sys from optparse import OptionParser usage = "usage: %prog [options] host" parser = OptionParser(usage = usage) parser.add_option("-t", "--token", dest="token", default="", type='string', help="token") (options, args) = parser.parse_args() if len(args) != 1: parser.print_usage() sys.exit(1) host = args[0] data = { "token": options.token } dataStr = json.dumps(data) print urllib2.urlopen('http://%s/private/refreshStore' % host, dataStr).read()

0

9dbd5ad7e1294e12a9fb2519e92fbb06c8562dc1

4,723

py

Python

eplist/web_sources/anidb.py

djt5019/episode_renamer

84d3dda24b54c70a489c2a6bcb9c7c2c2dadfba9

[ "Unlicense" ]

null

eplist/web_sources/anidb.py

djt5019/episode_renamer

84d3dda24b54c70a489c2a6bcb9c7c2c2dadfba9

[ "Unlicense" ]

null

eplist/web_sources/anidb.py

djt5019/episode_renamer

84d3dda24b54c70a489c2a6bcb9c7c2c2dadfba9

[ "Unlicense" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals import re import difflib import logging import functools from string import punctuation as punct from eplist import utils from eplist.episode import Episode from eplist.settings import Settings try: from bs4 import BeautifulSoup Soup = functools.partial(BeautifulSoup) except ImportError: try: from BeautifulSoup import BeautifulStoneSoup as Soup except ImportError: logging.critical("Error: BeautifulSoup was not found, unable to parse AniDB") priority = 3 anidb_client = 'eprenamer' anidb_version = '1' anidb_proto = '1' anidb_http_url = 'http://api.anidb.net:9001/httpapi?{}' anidb_request = "request=anime&client={}&clientver={}&protover={}&aid={{}}" anidb_request = anidb_request.format(anidb_client, anidb_version, anidb_proto) anidb_http_url = anidb_http_url.format(anidb_request) def _parse_local(title): """ Try to find the anime ID (aid) in the dump file provided by AniDB """ if not utils.file_exists_in_resources('animetitles.dat'): logging.warning("AniDB database file not found, unable to poll AniDB at this time") logging.warning("Try using the --update-db option to download an copy of it") return -1 logging.info("Searching the AniDB database file") title = title.lower() regex = re.compile(r'(?P<aid>\d+)\|(?P<type>\d)\|(?P<lang>.+)\|(?P<title>.*)') sequence = difflib.SequenceMatcher(lambda x: x in punct, title.lower()) guesses = [] with utils.open_file_in_resources('animetitles.dat') as f: for line in f: res = regex.search(line) if not res: continue original_title = utils.encode(res.group('title').lower()) clean_title = utils.prepare_title(utils.encode(res.group('title'))).lower() if utils.prepare_title(title) in (original_title, clean_title): return int(res.group('aid')) sequence.set_seq2(clean_title.lower()) ratio = sequence.quick_ratio() if ratio > .80: d = dict(ratio=ratio, aid=res.group('aid'), title=original_title) guesses.append(d) if guesses: logging.info("{} possibilities".format(len(guesses))) guesses = sorted(guesses, key=lambda x: x['ratio']) aid = guesses[0]['aid'] name = guesses[0]['title'] logging.error("Closest show to '{}' on AniDB is '{}'' with id {}".format(title, name, aid)) for guess in guesses[1:]: logging.info("Similar show {} [{}] also found".format(guess['title'], guess['aid'])) return -1 def _connect_HTTP(aid): """ Connect to AniDB using the public HTTP Api, this is used as an alternative to the UDP connection function """ url = anidb_http_url.format(aid) resp = utils.get_url_descriptor(url) if resp is None: return utils.show_not_found soup = Soup(resp.content) if soup.find('error'): logging.error("Temporally banned from AniDB, most likely due to flooding") return [] episodes = soup.findAll('episode') if not episodes: return utils.show_not_found eplist = [] for e in episodes: # 1 is a normal episode, 2 is a special # with beautifulsoup3 it returns a list of attribute dictionaries # rather than just a single dictionary like in bs4 if 'type' in e.epno.attrs: ep_type = e.epno.attrs['type'] else: ep_type = e.epno.attrs[0][1] if ep_type not in ('1', '2'): continue title = e.find('title', {'xml:lang': 'en'}) title = title.getText() if ep_type == '1': epNum = int(e.epno.getText()) type_ = "Episode" else: epNum = int(e.epno.getText()[1:]) type_ = "OVA" e = Episode(title=title, number=epNum, count=epNum, type=type_) eplist.append(e) return eplist

27.619883

109

0.629261

# -*- coding: utf-8 -*- from __future__ import unicode_literals import re import difflib import logging import functools from string import punctuation as punct from eplist import utils from eplist.episode import Episode from eplist.settings import Settings try: from bs4 import BeautifulSoup Soup = functools.partial(BeautifulSoup) except ImportError: try: from BeautifulSoup import BeautifulStoneSoup as Soup except ImportError: logging.critical("Error: BeautifulSoup was not found, unable to parse AniDB") priority = 3 anidb_client = 'eprenamer' anidb_version = '1' anidb_proto = '1' anidb_http_url = 'http://api.anidb.net:9001/httpapi?{}' anidb_request = "request=anime&client={}&clientver={}&protover={}&aid={{}}" anidb_request = anidb_request.format(anidb_client, anidb_version, anidb_proto) anidb_http_url = anidb_http_url.format(anidb_request) def _parse_local(title): """ Try to find the anime ID (aid) in the dump file provided by AniDB """ if not utils.file_exists_in_resources('animetitles.dat'): logging.warning("AniDB database file not found, unable to poll AniDB at this time") logging.warning("Try using the --update-db option to download an copy of it") return -1 logging.info("Searching the AniDB database file") title = title.lower() regex = re.compile(r'(?P<aid>\d+)\|(?P<type>\d)\|(?P<lang>.+)\|(?P<title>.*)') sequence = difflib.SequenceMatcher(lambda x: x in punct, title.lower()) guesses = [] with utils.open_file_in_resources('animetitles.dat') as f: for line in f: res = regex.search(line) if not res: continue original_title = utils.encode(res.group('title').lower()) clean_title = utils.prepare_title(utils.encode(res.group('title'))).lower() if utils.prepare_title(title) in (original_title, clean_title): return int(res.group('aid')) sequence.set_seq2(clean_title.lower()) ratio = sequence.quick_ratio() if ratio > .80: d = dict(ratio=ratio, aid=res.group('aid'), title=original_title) guesses.append(d) if guesses: logging.info("{} possibilities".format(len(guesses))) guesses = sorted(guesses, key=lambda x: x['ratio']) aid = guesses[0]['aid'] name = guesses[0]['title'] logging.error("Closest show to '{}' on AniDB is '{}'' with id {}".format(title, name, aid)) for guess in guesses[1:]: logging.info("Similar show {} [{}] also found".format(guess['title'], guess['aid'])) return -1 def _connect_UDP(aid): ## Todo: make this work so we stop relying on the http protocol raise NotImplementedError("I will get to this later... promise.") if not Settings.anidb_username or not Settings.anidb_password: raise ValueError("Username/Password required to poll AniDB") def _connect_HTTP(aid): """ Connect to AniDB using the public HTTP Api, this is used as an alternative to the UDP connection function """ url = anidb_http_url.format(aid) resp = utils.get_url_descriptor(url) if resp is None: return utils.show_not_found soup = Soup(resp.content) if soup.find('error'): logging.error("Temporally banned from AniDB, most likely due to flooding") return [] episodes = soup.findAll('episode') if not episodes: return utils.show_not_found eplist = [] for e in episodes: # 1 is a normal episode, 2 is a special # with beautifulsoup3 it returns a list of attribute dictionaries # rather than just a single dictionary like in bs4 if 'type' in e.epno.attrs: ep_type = e.epno.attrs['type'] else: ep_type = e.epno.attrs[0][1] if ep_type not in ('1', '2'): continue title = e.find('title', {'xml:lang': 'en'}) title = title.getText() if ep_type == '1': epNum = int(e.epno.getText()) type_ = "Episode" else: epNum = int(e.epno.getText()[1:]) type_ = "OVA" e = Episode(title=title, number=epNum, count=epNum, type=type_) eplist.append(e) return eplist def poll(title=""): try: Soup except NameError: return utils.show_not_found aid = _parse_local(title.lower()) if aid < 0: return utils.show_not_found logging.info("Found AID: {}".format(aid)) if utils.able_to_poll('AniDB'): episodes = _connect_HTTP(aid) if episodes: return episodes return utils.show_not_found

650

0

46

d2fdf77b2d8c1bb4d3bf7464c2a44161dda68f02

1,284

py

Python

replot.py

MQSchleich/dylightful

6abbb690c8387c522c9bff21c72b5c66aab77ede

[ "MIT" ]

null

replot.py

MQSchleich/dylightful

6abbb690c8387c522c9bff21c72b5c66aab77ede

[ "MIT" ]

5

2022-02-05T12:47:42.000Z

2022-03-16T11:42:20.000Z

replot.py

MQSchleich/dylightful

6abbb690c8387c522c9bff21c72b5c66aab77ede

[ "MIT" ]

null

import os import numpy as np from dylightful.utilities import load_parsed_dyno, get_dir from dylightful.parser import load_env_partners_mixed from dylightful.bar_plot import make_barplot dirname = os.path.dirname(__file__) save_dir = "/media/julian/INTENSO/ZIKV/" name = "ZIKV-Pro-427-1_dynophore" traj_path = save_dir + name + ".json" prefix = "ligand" pml = save_dir + name + ".pml" ligand_path = save_dir + name + "_time_series.json" topology = save_dir + "topo0.pdb" trajectory = save_dir + "trajectory.dcd" traj_path = os.path.join(dirname, traj_path) time_ser, num_obs = load_parsed_dyno(traj_path=ligand_path) time_ser = time_ser print(type(time_ser)) print(time_ser.shape) print(time_ser[0:2, :]) # traj_path = os.path.join(dirname, traj_path) # env_partners = load_env_partners_mixed(json_path=traj_path) # env_partner_arr = [] # for partner in env_partners.keys(): # env_partner_arr.append(env_partners[partner]) # env_partner_arr = np.array(env_partner_arr) # time_ser = env_partner_arr.T # print(type(time_ser)) # print(time_ser.shape) # print(time_ser[0:2,:]) save_path = get_dir(traj_path) base = save_dir make_barplot( time_ser=time_ser, ylabel="Ligand Perspective", yticks=np.arange(time_ser.shape[1]), prefix=prefix, save_path=save_path, )

29.181818

61

0.760125

import os import numpy as np from dylightful.utilities import load_parsed_dyno, get_dir from dylightful.parser import load_env_partners_mixed from dylightful.bar_plot import make_barplot dirname = os.path.dirname(__file__) save_dir = "/media/julian/INTENSO/ZIKV/" name = "ZIKV-Pro-427-1_dynophore" traj_path = save_dir + name + ".json" prefix = "ligand" pml = save_dir + name + ".pml" ligand_path = save_dir + name + "_time_series.json" topology = save_dir + "topo0.pdb" trajectory = save_dir + "trajectory.dcd" traj_path = os.path.join(dirname, traj_path) time_ser, num_obs = load_parsed_dyno(traj_path=ligand_path) time_ser = time_ser print(type(time_ser)) print(time_ser.shape) print(time_ser[0:2, :]) # traj_path = os.path.join(dirname, traj_path) # env_partners = load_env_partners_mixed(json_path=traj_path) # env_partner_arr = [] # for partner in env_partners.keys(): # env_partner_arr.append(env_partners[partner]) # env_partner_arr = np.array(env_partner_arr) # time_ser = env_partner_arr.T # print(type(time_ser)) # print(time_ser.shape) # print(time_ser[0:2,:]) save_path = get_dir(traj_path) base = save_dir make_barplot( time_ser=time_ser, ylabel="Ligand Perspective", yticks=np.arange(time_ser.shape[1]), prefix=prefix, save_path=save_path, )

0

bda70b28893b7d71639ed4e417576078ac6f4740

733

py

Python

opta/commands/help.py

pecigonzalo/opta

0259f128ad3cfc4a96fe1f578833de28b2f19602

[ "Apache-2.0" ]

null

opta/commands/help.py

pecigonzalo/opta

0259f128ad3cfc4a96fe1f578833de28b2f19602

[ "Apache-2.0" ]

null

opta/commands/help.py

pecigonzalo/opta

0259f128ad3cfc4a96fe1f578833de28b2f19602

[ "Apache-2.0" ]

null

from typing import Optional import click from click import Context from opta.exceptions import UserErrors @click.command() @click.pass_context @click.argument("command", required=False) def help(context: Context, command: Optional[str]) -> None: """ Get help for Opta. Example: opta help opta help apply """ command_context = context.parent.command # type: ignore if command is not None: try: command_context = command_context.commands[command] # type: ignore except KeyError: raise UserErrors( "Invalid Command. Please use correct commands mentioned in `opta help|-h|--help " ) print(command_context.get_help(context))

23.645161

97

0.661664

from typing import Optional import click from click import Context from opta.exceptions import UserErrors @click.command() @click.pass_context @click.argument("command", required=False) def help(context: Context, command: Optional[str]) -> None: """ Get help for Opta. Example: opta help opta help apply """ command_context = context.parent.command # type: ignore if command is not None: try: command_context = command_context.commands[command] # type: ignore except KeyError: raise UserErrors( "Invalid Command. Please use correct commands mentioned in `opta help|-h|--help " ) print(command_context.get_help(context))

0

05c583400c5f51e6d3818158d9d2a62630174a12

1,286

py

Python

codereviewr/urls.py

percyperez/codereviewr

d7bc927455559389354f615cf7c130e7122e04ef

[ "MIT" ]

2

2015-12-08T13:40:32.000Z

2016-05-08T06:22:14.000Z

codereviewr/urls.py

na/codereviewr

c1045f2e9a16d64398306dbf9124b4f59ef2fdbb

[ "MIT" ]

null

codereviewr/urls.py

na/codereviewr

c1045f2e9a16d64398306dbf9124b4f59ef2fdbb

[ "MIT" ]

null

from django.conf.urls.defaults import * from django.contrib.comments.feeds import LatestCommentsFeed from django.views.generic.simple import direct_to_template, redirect_to from codereviewr.settings import PROJECT_PATH, DEBUG from codereviewr.feeds import * #feeds dictionary feeds = { 'code': CodeFeed, 'comments': LatestCommentsFeed, 'language': LanguageFeed, 'latest': LatestFeed, 'user': UserFeed, } urlpatterns = patterns('', (r'^code/', include('codereviewr.code.urls')), # Admin (r'^admin/code/language/refresh/$', 'code.views.refresh_languages'), (r'^admin/', include('django.contrib.admin.urls')), # OpenID (r'^openid/$', 'openid_cr.views.begin', {'redirect_to': '/openid/complete/'}), (r'^openid/complete/$', 'openid_cr.views.complete'), (r'^openid/signout/$', 'openid_cr.views.signout'), # account registration (r'^accounts/', include('registration.urls')), #for homepage - testing (r'^$', direct_to_template, {'template': 'homepage.html'}), #Feeds (r'^feeds/(?P<url>.*)/$', 'django.contrib.syndication.views.feed', {'feed_dict': feeds}), ) if DEBUG: urlpatterns += patterns('', (r'^media/(.*)$', 'django.views.static.serve', {'document_root': '%s/../media' % (PROJECT_PATH)}) )

30.619048

105

0.662519

from django.conf.urls.defaults import * from django.contrib.comments.feeds import LatestCommentsFeed from django.views.generic.simple import direct_to_template, redirect_to from codereviewr.settings import PROJECT_PATH, DEBUG from codereviewr.feeds import * #feeds dictionary feeds = { 'code': CodeFeed, 'comments': LatestCommentsFeed, 'language': LanguageFeed, 'latest': LatestFeed, 'user': UserFeed, } urlpatterns = patterns('', (r'^code/', include('codereviewr.code.urls')), # Admin (r'^admin/code/language/refresh/$', 'code.views.refresh_languages'), (r'^admin/', include('django.contrib.admin.urls')), # OpenID (r'^openid/$', 'openid_cr.views.begin', {'redirect_to': '/openid/complete/'}), (r'^openid/complete/$', 'openid_cr.views.complete'), (r'^openid/signout/$', 'openid_cr.views.signout'), # account registration (r'^accounts/', include('registration.urls')), #for homepage - testing (r'^$', direct_to_template, {'template': 'homepage.html'}), #Feeds (r'^feeds/(?P<url>.*)/$', 'django.contrib.syndication.views.feed', {'feed_dict': feeds}), ) if DEBUG: urlpatterns += patterns('', (r'^media/(.*)$', 'django.views.static.serve', {'document_root': '%s/../media' % (PROJECT_PATH)}) )

0

41c0d02a489f00ea9b52cab70a55f753870dba52

2,483

py

Python

save_preds.py

somepago/dbViz

aeea84c42a32efafebbb29c3d944204aa74963cf

[ "Apache-2.0" ]

22

2022-03-16T10:04:43.000Z

2022-03-24T22:57:23.000Z

save_preds.py

somepago/dbViz

aeea84c42a32efafebbb29c3d944204aa74963cf

[ "Apache-2.0" ]

null

save_preds.py

somepago/dbViz

aeea84c42a32efafebbb29c3d944204aa74963cf

[ "Apache-2.0" ]

2

2022-03-19T07:13:39.000Z

2022-03-29T06:09:53.000Z

'''Train CIFAR10 with PyTorch.''' import torch import random import os import argparse from model import get_model from data import get_data, make_planeloader from utils import get_loss_function, get_scheduler, get_random_images, produce_plot, get_noisy_images, AttackPGD from evaluation import decision_boundary from options import options from utils import simple_lapsed_time ''' This module calculates and saves prediction arrays for different saved models. E.g. if you have saved models with the structure: /path/to/saved/models - model_1.pth - model_2.pth - model_3.pth then this script will make a new folder /path/to/saved/models/predictions which will save the following prediction arrays: /path/to/save/models/predictions - model_1_preds.pth - model_2_preds.pth - model_3_preds.pth Note: the original model paths should be of the form: ResNet18.pth ... i.e. the name of the model used should be the same as the model in model.py ''' args = options().parse_args() print(args) device = 'cuda' if torch.cuda.is_available() else 'cpu' torch.manual_seed(args.set_data_seed) trainloader, testloader = get_data(args) paths = [os.path.join(args.load_net, p) for p in os.listdir(args.load_net) if 'pred' not in p] for path in paths: os.makedirs(os.path.join(args.load_net, path, 'predictions'), exist_ok=True) for p in sorted(os.listdir(path)): if 'pred' not in p: if 'wide' in path.lower(): args.net = 'WideResNet' # Here the net path is saved like '/path/to/saved/models/WideResNet_10.pth' args.widen_factor = int(path.split('/')[-1].split('.')[0].split('_')[1]) else: args.net = path.split('/')[-1].split('.')[0] net = get_model(args, device) temp_path = os.path.join(path,p) net.load_state_dict(torch.load(temp_path)) pred_arr = [] for run in range(args.epochs): random.seed(a=(args.set_data_seed+run), version=2) images, labels, image_ids = get_random_images(testloader.dataset) planeloader = make_planeloader(images, args) preds = decision_boundary(args, net, planeloader, device) pred_arr.append(torch.stack(preds).argmax(1).cpu()) torch.save(pred_arr, os.path.join(args.load_net, path, 'predictions') + '/' + temp_path.split('/')[-1].split('.pth')[0] + '_preds.pth')

37.059701

147

0.664921

'''Train CIFAR10 with PyTorch.''' import torch import random import os import argparse from model import get_model from data import get_data, make_planeloader from utils import get_loss_function, get_scheduler, get_random_images, produce_plot, get_noisy_images, AttackPGD from evaluation import decision_boundary from options import options from utils import simple_lapsed_time ''' This module calculates and saves prediction arrays for different saved models. E.g. if you have saved models with the structure: /path/to/saved/models - model_1.pth - model_2.pth - model_3.pth then this script will make a new folder /path/to/saved/models/predictions which will save the following prediction arrays: /path/to/save/models/predictions - model_1_preds.pth - model_2_preds.pth - model_3_preds.pth Note: the original model paths should be of the form: ResNet18.pth ... i.e. the name of the model used should be the same as the model in model.py ''' args = options().parse_args() print(args) device = 'cuda' if torch.cuda.is_available() else 'cpu' torch.manual_seed(args.set_data_seed) trainloader, testloader = get_data(args) paths = [os.path.join(args.load_net, p) for p in os.listdir(args.load_net) if 'pred' not in p] for path in paths: os.makedirs(os.path.join(args.load_net, path, 'predictions'), exist_ok=True) for p in sorted(os.listdir(path)): if 'pred' not in p: if 'wide' in path.lower(): args.net = 'WideResNet' # Here the net path is saved like '/path/to/saved/models/WideResNet_10.pth' args.widen_factor = int(path.split('/')[-1].split('.')[0].split('_')[1]) else: args.net = path.split('/')[-1].split('.')[0] net = get_model(args, device) temp_path = os.path.join(path,p) net.load_state_dict(torch.load(temp_path)) pred_arr = [] for run in range(args.epochs): random.seed(a=(args.set_data_seed+run), version=2) images, labels, image_ids = get_random_images(testloader.dataset) planeloader = make_planeloader(images, args) preds = decision_boundary(args, net, planeloader, device) pred_arr.append(torch.stack(preds).argmax(1).cpu()) torch.save(pred_arr, os.path.join(args.load_net, path, 'predictions') + '/' + temp_path.split('/')[-1].split('.pth')[0] + '_preds.pth')

0

aa2541d0b8aba2e6c7ed95ea73a4a7d1006eb805

7,820

py

Python

data_preprocessing/flatten.py

billylegota/ECE-380L-Term-Project

9838449e7e4b40e4444fdcb0f7e23cf43e87e0f1

[ "MIT" ]

null

data_preprocessing/flatten.py

billylegota/ECE-380L-Term-Project

9838449e7e4b40e4444fdcb0f7e23cf43e87e0f1

[ "MIT" ]

null

data_preprocessing/flatten.py

billylegota/ECE-380L-Term-Project

9838449e7e4b40e4444fdcb0f7e23cf43e87e0f1

[ "MIT" ]

null

"""flatten.py -- Flattens HDF5 dataset. """ import glob import math import os import h5py import numpy as np import scipy.io def flatten(source: str, dest: str, packets_per_chunk: int = 1000, synthetic: bool = False, silent: bool = True, constant_features_path: str = 'constant_features.mat') -> (int, int): """Flatten an HDF5 dataset. :param source: path to original dataset. :param dest: path to store flattened dataset. :param packets_per_chunk: number of packets to process at a time. Ideally the number of symbols per chunk is < 1000. :param synthetic: flag the source dataset as being synthetic (changes data input format). :param silent: suppress output. :param constant_features_path: path to constant features. :return: tuple containing the number of (symbols, packets) converted. """ data = h5py.File(source, 'r') num_packets = len(data['rxLltfFftOut1']) # Load constant features. This contains the indices for data and pilot tones. constant_features = scipy.io.loadmat(constant_features_path, squeeze_me=True) constant_features = constant_features['constant'] # Values in `constant_features.mat` are one-indexed so we subtract one for zero-indexed. he_ltf_data_indices = constant_features['iMDataTone_Heltf'][()].astype(np.int32) - 1 he_ltf_pilot_indices = constant_features['iMPilotTone_Heltf'][()].astype(np.int32) - 1 data_indices = constant_features['iMDataTone_HePpdu'][()].astype(np.int32) - 1 pilot_indices = constant_features['iMPilotTone_HePpdu'][()].astype(np.int32) - 1 # Create the file to write the data to. output = h5py.File(dest, 'w') for chunk in range(math.ceil(num_packets / packets_per_chunk)): chunk_indices = np.arange(chunk * packets_per_chunk, min((chunk + 1) * packets_per_chunk, num_packets)) # Fixes bug with h5py version on TACC. chunk_indices = list(chunk_indices) # Load L-LTF fields. rx_l_ltf_1 = np.array(data['rxLltfFftOut1'][chunk_indices]) rx_l_ltf_2 = np.array(data['rxLltfFftOut2'][chunk_indices]) # Load HE-LTF and split into data and pilot. rx_he_ltf = np.array(data['rxHeltfFftOut'][chunk_indices]) rx_he_ltf_data = rx_he_ltf[:, he_ltf_data_indices] rx_he_ltf_pilot = rx_he_ltf[:, he_ltf_pilot_indices] # Load RX and TX data symbols and split into data and pilot, keeping track of the corresponding LTF fields. # FIXME: This is very slow. On the other hand, I can't be bothered to make it faster since it only runs once. ltf_indices = [] rx_symbols = [] rx_ref_data = [] tx_symbols = [] if synthetic: for i, j in enumerate(chunk_indices): iterator = (data['rxHePpduFftOut'][j], data['rxHePpdutoneMappedFreq'][j], data['txConstellation'][j]) for rx_symbol, rx_ref_symbol, tx_symbol in zip(*iterator): ltf_indices.append(i) rx_symbols.append(rx_symbol) rx_ref_data.append(rx_ref_symbol) tx_symbols.append(tx_symbol) else: for i, j in enumerate(chunk_indices): iterator = (data[f'rxHePpduFftOut{j}'], data[f'rxHePpdutoneMappedFreq{j}'], data[f'txConstellation{j}']) for rx_symbol, rx_ref_symbol, tx_symbol in zip(*iterator): ltf_indices.append(i) rx_symbols.append(rx_symbol) rx_ref_data.append(rx_ref_symbol) tx_symbols.append(tx_symbol) num_symbols = len(ltf_indices) ltf_indices = np.array(ltf_indices) rx_symbols = np.array(rx_symbols) rx_ref_data = np.array(rx_ref_data) tx_symbols = np.array(tx_symbols) rx_data = rx_symbols[:, data_indices] rx_pilot = rx_symbols[:, pilot_indices] tx_data = tx_symbols[:, data_indices] tx_pilot = tx_symbols[:, pilot_indices] # Duplicate the entries in the LTF fields so that we have `num_symbols` entries. rx_l_ltf_1 = np.array([rx_l_ltf_1[ltf_indices[i]] for i in range(num_symbols)]) rx_l_ltf_2 = np.array([rx_l_ltf_2[ltf_indices[i]] for i in range(num_symbols)]) rx_he_ltf_data = np.array([rx_he_ltf_data[ltf_indices[i]] for i in range(num_symbols)]) rx_he_ltf_pilot = np.array([rx_he_ltf_pilot[ltf_indices[i]] for i in range(num_symbols)]) # Lump the arrays together and save them. arrays = { 'rx_l_ltf_1': rx_l_ltf_1, 'rx_l_ltf_2': rx_l_ltf_2, 'rx_he_ltf_data': rx_he_ltf_data, 'rx_he_ltf_pilot': rx_he_ltf_pilot, 'rx_data': rx_data, 'rx_pilot': rx_pilot, 'rx_ref_data': rx_ref_data, 'tx_data': tx_data, 'tx_pilot': tx_pilot } for key, value in arrays.items(): if key not in output: output.create_dataset(name=key, data=value, maxshape=(None, *value.shape[1:]), chunks=True) else: output[key].resize(output[key].shape[0] + value.shape[0], axis=0) output[key][-value.shape[0]:] = value if not silent: print(f'Wrote {num_symbols} symbols in {len(chunk_indices)} packets.') if not silent: print(f'TOTAL: {output["rx_l_ltf_1"].shape[0]} symbols in {num_packets} packets.') return output['rx_l_ltf_1'].shape[0], num_packets def flatten_dir(source_dir: str, dest_dir: str, packets_per_chunk: int = 1000, synthetic: bool = False, silent: bool = True, force: bool = False, constant_features_path: str = 'constant_features.mat') -> (int, int): """Flatten all HDF5 files in a directory and place them in another. :param source_dir: source directory. :param dest_dir: destination directory. :param packets_per_chunk: number of packets to process at a time. :param synthetic: flag the source dataset as being synthetic (changes data input format). :param silent: suppress output. :param force: force reprocessing of already-processed files. :param constant_features_path: path to constant features. :return: tuple containing the number of (symbols, packets) converted. """ total_symbols = 0 total_packets = 0 for source in glob.glob(f'{source_dir}/*.h5'): if 'flat' in source: if not silent: print(f'{source} is already flattened. Skipping.') print() continue dest = f'{dest_dir}/{os.path.splitext(os.path.basename(source))[0]}_flat.h5' if not force and os.path.exists(dest): if not silent: print(f'{dest_dir} exists. Skipping.') print() continue num_symbols, num_packets = flatten(source, dest, packets_per_chunk, synthetic=synthetic, silent=silent, constant_features_path=constant_features_path) total_symbols += num_symbols total_packets += num_packets if not silent: print() if not silent: print(f'TOTAL: {total_symbols} symbols in {total_packets} packets.') if __name__ == '__main__': main()

42.27027

120

0.649105

"""flatten.py -- Flattens HDF5 dataset. """ import glob import math import os import h5py import numpy as np import scipy.io def flatten(source: str, dest: str, packets_per_chunk: int = 1000, synthetic: bool = False, silent: bool = True, constant_features_path: str = 'constant_features.mat') -> (int, int): """Flatten an HDF5 dataset. :param source: path to original dataset. :param dest: path to store flattened dataset. :param packets_per_chunk: number of packets to process at a time. Ideally the number of symbols per chunk is < 1000. :param synthetic: flag the source dataset as being synthetic (changes data input format). :param silent: suppress output. :param constant_features_path: path to constant features. :return: tuple containing the number of (symbols, packets) converted. """ data = h5py.File(source, 'r') num_packets = len(data['rxLltfFftOut1']) # Load constant features. This contains the indices for data and pilot tones. constant_features = scipy.io.loadmat(constant_features_path, squeeze_me=True) constant_features = constant_features['constant'] # Values in `constant_features.mat` are one-indexed so we subtract one for zero-indexed. he_ltf_data_indices = constant_features['iMDataTone_Heltf'][()].astype(np.int32) - 1 he_ltf_pilot_indices = constant_features['iMPilotTone_Heltf'][()].astype(np.int32) - 1 data_indices = constant_features['iMDataTone_HePpdu'][()].astype(np.int32) - 1 pilot_indices = constant_features['iMPilotTone_HePpdu'][()].astype(np.int32) - 1 # Create the file to write the data to. output = h5py.File(dest, 'w') for chunk in range(math.ceil(num_packets / packets_per_chunk)): chunk_indices = np.arange(chunk * packets_per_chunk, min((chunk + 1) * packets_per_chunk, num_packets)) # Fixes bug with h5py version on TACC. chunk_indices = list(chunk_indices) # Load L-LTF fields. rx_l_ltf_1 = np.array(data['rxLltfFftOut1'][chunk_indices]) rx_l_ltf_2 = np.array(data['rxLltfFftOut2'][chunk_indices]) # Load HE-LTF and split into data and pilot. rx_he_ltf = np.array(data['rxHeltfFftOut'][chunk_indices]) rx_he_ltf_data = rx_he_ltf[:, he_ltf_data_indices] rx_he_ltf_pilot = rx_he_ltf[:, he_ltf_pilot_indices] # Load RX and TX data symbols and split into data and pilot, keeping track of the corresponding LTF fields. # FIXME: This is very slow. On the other hand, I can't be bothered to make it faster since it only runs once. ltf_indices = [] rx_symbols = [] rx_ref_data = [] tx_symbols = [] if synthetic: for i, j in enumerate(chunk_indices): iterator = (data['rxHePpduFftOut'][j], data['rxHePpdutoneMappedFreq'][j], data['txConstellation'][j]) for rx_symbol, rx_ref_symbol, tx_symbol in zip(*iterator): ltf_indices.append(i) rx_symbols.append(rx_symbol) rx_ref_data.append(rx_ref_symbol) tx_symbols.append(tx_symbol) else: for i, j in enumerate(chunk_indices): iterator = (data[f'rxHePpduFftOut{j}'], data[f'rxHePpdutoneMappedFreq{j}'], data[f'txConstellation{j}']) for rx_symbol, rx_ref_symbol, tx_symbol in zip(*iterator): ltf_indices.append(i) rx_symbols.append(rx_symbol) rx_ref_data.append(rx_ref_symbol) tx_symbols.append(tx_symbol) num_symbols = len(ltf_indices) ltf_indices = np.array(ltf_indices) rx_symbols = np.array(rx_symbols) rx_ref_data = np.array(rx_ref_data) tx_symbols = np.array(tx_symbols) rx_data = rx_symbols[:, data_indices] rx_pilot = rx_symbols[:, pilot_indices] tx_data = tx_symbols[:, data_indices] tx_pilot = tx_symbols[:, pilot_indices] # Duplicate the entries in the LTF fields so that we have `num_symbols` entries. rx_l_ltf_1 = np.array([rx_l_ltf_1[ltf_indices[i]] for i in range(num_symbols)]) rx_l_ltf_2 = np.array([rx_l_ltf_2[ltf_indices[i]] for i in range(num_symbols)]) rx_he_ltf_data = np.array([rx_he_ltf_data[ltf_indices[i]] for i in range(num_symbols)]) rx_he_ltf_pilot = np.array([rx_he_ltf_pilot[ltf_indices[i]] for i in range(num_symbols)]) # Lump the arrays together and save them. arrays = { 'rx_l_ltf_1': rx_l_ltf_1, 'rx_l_ltf_2': rx_l_ltf_2, 'rx_he_ltf_data': rx_he_ltf_data, 'rx_he_ltf_pilot': rx_he_ltf_pilot, 'rx_data': rx_data, 'rx_pilot': rx_pilot, 'rx_ref_data': rx_ref_data, 'tx_data': tx_data, 'tx_pilot': tx_pilot } for key, value in arrays.items(): if key not in output: output.create_dataset(name=key, data=value, maxshape=(None, *value.shape[1:]), chunks=True) else: output[key].resize(output[key].shape[0] + value.shape[0], axis=0) output[key][-value.shape[0]:] = value if not silent: print(f'Wrote {num_symbols} symbols in {len(chunk_indices)} packets.') if not silent: print(f'TOTAL: {output["rx_l_ltf_1"].shape[0]} symbols in {num_packets} packets.') return output['rx_l_ltf_1'].shape[0], num_packets def flatten_dir(source_dir: str, dest_dir: str, packets_per_chunk: int = 1000, synthetic: bool = False, silent: bool = True, force: bool = False, constant_features_path: str = 'constant_features.mat') -> (int, int): """Flatten all HDF5 files in a directory and place them in another. :param source_dir: source directory. :param dest_dir: destination directory. :param packets_per_chunk: number of packets to process at a time. :param synthetic: flag the source dataset as being synthetic (changes data input format). :param silent: suppress output. :param force: force reprocessing of already-processed files. :param constant_features_path: path to constant features. :return: tuple containing the number of (symbols, packets) converted. """ total_symbols = 0 total_packets = 0 for source in glob.glob(f'{source_dir}/*.h5'): if 'flat' in source: if not silent: print(f'{source} is already flattened. Skipping.') print() continue dest = f'{dest_dir}/{os.path.splitext(os.path.basename(source))[0]}_flat.h5' if not force and os.path.exists(dest): if not silent: print(f'{dest_dir} exists. Skipping.') print() continue num_symbols, num_packets = flatten(source, dest, packets_per_chunk, synthetic=synthetic, silent=silent, constant_features_path=constant_features_path) total_symbols += num_symbols total_packets += num_packets if not silent: print() if not silent: print(f'TOTAL: {total_symbols} symbols in {total_packets} packets.') def main(): import argparse # noinspection PyTypeChecker parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('source', help='directory to flatten', type=str) parser.add_argument('dest', help='directory to store result', type=str) parser.add_argument('--synthetic', help='flag the source dataset as being synthetic', action='store_true') args = parser.parse_args() flatten_dir(args.source, args.dest, synthetic=args.synthetic, silent=False) if __name__ == '__main__': main()

509

0

23

79f8e6aa646486ac4177d50c3694c1c7632c0a4a

461

py

Python

lpbm/lib/slugify.py

fmichea/lpbm

172772d562e2f1aa4aba72599150f95f89bdf6ce

[ "BSD-3-Clause" ]

1

2015-11-09T11:30:41.000Z

lpbm/lib/slugify.py

fmichea/lpbm

172772d562e2f1aa4aba72599150f95f89bdf6ce

[ "BSD-3-Clause" ]

1

2015-04-28T07:02:21.000Z

2016-01-23T19:12:11.000Z

lpbm/lib/slugify.py

fmichea/lpbm

172772d562e2f1aa4aba72599150f95f89bdf6ce

[ "BSD-3-Clause" ]

2

2016-01-11T17:55:42.000Z

2018-03-19T19:03:15.000Z

import string import unicodedata SLUG_CHARS_DISPLAY = '[a-z0-9-]' _SLUG_CHARS = string.ascii_lowercase + string.digits + '-' _SLUG_SIZE = 50 def slugify(text): '''Returns the slug of a string (that can be used in an URL for example.''' slug = unicodedata.normalize('NFKD', text).encode('ascii', 'ignore') slug = slug.decode('utf-8').lower().replace(' ', '-') slug = ''.join(c for c in slug if c in _SLUG_CHARS) return slug[:_SLUG_SIZE]

27.117647

79

0.668113

import string import unicodedata SLUG_CHARS_DISPLAY = '[a-z0-9-]' _SLUG_CHARS = string.ascii_lowercase + string.digits + '-' _SLUG_SIZE = 50 def slugify(text): '''Returns the slug of a string (that can be used in an URL for example.''' slug = unicodedata.normalize('NFKD', text).encode('ascii', 'ignore') slug = slug.decode('utf-8').lower().replace(' ', '-') slug = ''.join(c for c in slug if c in _SLUG_CHARS) return slug[:_SLUG_SIZE]

0

5427b466a12fe41de8c9198002e141c9edef8f1f

610

py

Python

Chapter09/wifi-sniff.py

PacktPublishing/Python-Penetration-Testing-Cookbook

74eba54a5d9921db0c4679cb4374a742118d4be8

[ "MIT" ]

48

2017-12-08T16:38:09.000Z

2022-03-20T12:49:31.000Z

Chapter09/wifi-sniff.py

shamiul94/Python-Penetration-Testing-Cookbook

a152f14bf7eb1fde2612808f47d7609b58d48980

[ "MIT" ]

null

Chapter09/wifi-sniff.py

shamiul94/Python-Penetration-Testing-Cookbook

a152f14bf7eb1fde2612808f47d7609b58d48980

[ "MIT" ]

34

2017-12-28T14:01:10.000Z

2022-03-16T15:54:30.000Z

from scapy.all import * ap_list = [] sniff(iface='en0', prn=ssid, count=10, timeout=3, store=0) # for packet in sniff(offline='sample.pcap', prn=changePacketParameters): # packets.append(packet) # for packet in packets: # if packet.haslayer(TCP): # writeToPcapFile(packet) # print(packet.show())

30.5

73

0.595082

from scapy.all import * ap_list = [] def ssid(pkt): # print(pkt.show()) if pkt.haslayer(Dot11): print(pkt.show()) if pkt.type == 0 and pkt.subtype == 8: if pkt.addr2 not in ap_list: ap_list.append(pkt.addr2) print("AP: %s SSID: %s" % (pkt.addr2, pkt.info)) sniff(iface='en0', prn=ssid, count=10, timeout=3, store=0) # for packet in sniff(offline='sample.pcap', prn=changePacketParameters): # packets.append(packet) # for packet in packets: # if packet.haslayer(TCP): # writeToPcapFile(packet) # print(packet.show())

266

0

22

072d438eba683fe36f066d77044cc9fbcf982237

6,298

py

Python

python/rain/client/data.py

aimof/rain

86b77666e1310888ad483c7976c2c99f3d5bfeaa

[ "MIT" ]

null

python/rain/client/data.py

aimof/rain

86b77666e1310888ad483c7976c2c99f3d5bfeaa

[ "MIT" ]

null

python/rain/client/data.py

aimof/rain

86b77666e1310888ad483c7976c2c99f3d5bfeaa

[ "MIT" ]

null

import capnp import tarfile import io from .session import get_active_session from ..common import RainException, ids, ID from ..common.attributes import attributes_to_capnp from ..common.content_type import check_content_type, encode_value from ..common import DataType def blob(value, label="const", content_type=None, encode=None): """ Create a constant data object with accompanying data. Given `value` may be either `bytes` or any object to be encoded with `encoding` content type. Strings are encoded with utf-8 by default. Specify at most one of `content_type` and `encode`. """ if content_type is not None: if encode is not None: raise RainException("Specify only one of content_type and encode") if not isinstance(value, bytes): raise RainException("content_type only allowed for `bytes`") if encode is None and isinstance(value, str): encode = "text:utf-8" if content_type is not None: raise RainException("content_type not allowed for `str`, use `encode=...`") if encode is not None: check_content_type(encode) value = encode_value(value, content_type=encode) content_type = encode if not isinstance(value, bytes): raise RainException( "Invalid blob type (only str or bytes are allowed without `encode`)") dataobj = DataObject(label, content_type=content_type) dataobj.data = value return dataobj def pickled(val, label="pickle"): """ Create a data object with pickled `val`. A shorthand for `blob(val, ancode='pickle')`. The default label is "pickle". """ return blob(val, encode='pickle', label=label) def to_data(obj): """Convert an object to DataObject/DataObjectPart""" if isinstance(obj, DataObject): return obj from .task import Task if isinstance(obj, Task): if len(obj.outputs) == 1: return obj.outputs[0] if len(obj.outputs) == 0: raise RainException("{} does not have any output".format(obj)) else: raise RainException("{} returns multiple outputs".format(obj)) if isinstance(obj, str) or isinstance(obj, bytes): raise RainException( "Instance of {!r} cannot be used as a data object.\n" "Hint: Wrap it with `blob` to use it as data object." .format(type(obj))) raise RainException( "Instance of {!r} cannot be used as a data object.\n" "Hint: Wrap it with `pickled` or `blob(encode=...)` to use it as a data object." .format(type(obj)))

31.49

93

0.618292

import capnp import tarfile import io from .session import get_active_session from ..common import RainException, ids, ID from ..common.attributes import attributes_to_capnp from ..common.content_type import check_content_type, encode_value from ..common import DataType class DataObject: id = None # Flag if data object should be kept on server _keep = False # State of object # None = Not submitted state = None # Value of data object (value can be filled by client if it is constant, # or by fetching from server) data = None def __init__(self, label=None, session=None, data_type=DataType.BLOB, content_type=None): assert isinstance(data_type, DataType) if session is None: session = get_active_session() self.session = session self.label = label self.id = session._register_dataobj(self) assert isinstance(self.id, ID) self.attributes = { "spec": {"content_type": content_type} } self.data_type = data_type @property def content_type(self): return self.attributes["spec"]["content_type"] def _free(self): """Set flag that object is not available on the server """ self._keep = False def unkeep(self): """Remove data object from the server""" self.session.unkeep((self,)) def keep(self): """Set flag that is object should be kept on the server""" if self.state is not None: raise RainException("Cannot keep submitted task") self._keep = True def is_kept(self): """Returns the value of self._keep""" return self._keep def to_capnp(self, out): ids.id_to_capnp(self.id, out.id) out.keep = self._keep if self.label: out.label = self.label out.dataType = self.data_type.to_capnp() if self.data is not None: out.data = self.data out.hasData = True else: out.hasData = False attributes_to_capnp(self.attributes, out.attributes) def wait(self): self.session.wait((self,)) def fetch(self): """ Fetch the object data and update its state. Returns: DataInstance """ return self.session.fetch(self) def update(self): self.session.update((self,)) def __del__(self): if self.state is not None and self._keep: try: self.session.client._unkeep((self,)) except capnp.lib.capnp.KjException: # Ignore capnp exception, since this constructor may be # called when connection is closed pass def __reduce__(self): """Speciaization to replace with subworker.unpickle_input_object in Python task args while (cloud)pickling.""" from . import pycode from ..subworker import subworker if pycode._global_pickle_inputs is None: # call normal __reduce__ return super().__reduce__() base_name, counter, inputs, input_proto = pycode._global_pickle_inputs input_name = "{}{{{}}}".format(base_name, counter) pycode._global_pickle_inputs[1] += 1 inputs.append((input_name, self)) return (subworker.unpickle_input_object, (input_name, len(inputs) - 1, input_proto.load, input_proto.content_type)) def __repr__(self): t = " [D]" if self.data_type == DataType.DIRECTORY else "" return "<DObj {}{} id={} {}>".format( self.label, t, self.id, self.attributes) def blob(value, label="const", content_type=None, encode=None): """ Create a constant data object with accompanying data. Given `value` may be either `bytes` or any object to be encoded with `encoding` content type. Strings are encoded with utf-8 by default. Specify at most one of `content_type` and `encode`. """ if content_type is not None: if encode is not None: raise RainException("Specify only one of content_type and encode") if not isinstance(value, bytes): raise RainException("content_type only allowed for `bytes`") if encode is None and isinstance(value, str): encode = "text:utf-8" if content_type is not None: raise RainException("content_type not allowed for `str`, use `encode=...`") if encode is not None: check_content_type(encode) value = encode_value(value, content_type=encode) content_type = encode if not isinstance(value, bytes): raise RainException( "Invalid blob type (only str or bytes are allowed without `encode`)") dataobj = DataObject(label, content_type=content_type) dataobj.data = value return dataobj def pickled(val, label="pickle"): """ Create a data object with pickled `val`. A shorthand for `blob(val, ancode='pickle')`. The default label is "pickle". """ return blob(val, encode='pickle', label=label) def directory(path=None, label="const_dir"): f = io.BytesIO() tf = tarfile.open(fileobj=f, mode="w") tf.add(path, ".") tf.close() data = f.getvalue() dataobj = DataObject(label, data_type=DataType.DIRECTORY) dataobj.data = data return dataobj def to_data(obj): """Convert an object to DataObject/DataObjectPart""" if isinstance(obj, DataObject): return obj from .task import Task if isinstance(obj, Task): if len(obj.outputs) == 1: return obj.outputs[0] if len(obj.outputs) == 0: raise RainException("{} does not have any output".format(obj)) else: raise RainException("{} returns multiple outputs".format(obj)) if isinstance(obj, str) or isinstance(obj, bytes): raise RainException( "Instance of {!r} cannot be used as a data object.\n" "Hint: Wrap it with `blob` to use it as data object." .format(type(obj))) raise RainException( "Instance of {!r} cannot be used as a data object.\n" "Hint: Wrap it with `pickled` or `blob(encode=...)` to use it as a data object." .format(type(obj)))

1,689

1,925

46

0e8a820f45484929c8266b2b20f11189f4b1fe60

3,211

py

Python

legate/pandas/core/bitmask.py

marcinz/legate.pandas

94c21c436f59c06cfba454c6569e9f5d7109d839

[ "Apache-2.0" ]

67

2021-04-12T18:06:55.000Z

2022-03-28T06:51:05.000Z

legate/pandas/core/bitmask.py

marcinz/legate.pandas

94c21c436f59c06cfba454c6569e9f5d7109d839

[ "Apache-2.0" ]

2

2021-06-22T00:30:36.000Z

2021-07-01T22:12:43.000Z

legate/pandas/core/bitmask.py

marcinz/legate.pandas

94c21c436f59c06cfba454c6569e9f5d7109d839

[ "Apache-2.0" ]

6

2021-04-14T21:28:00.000Z

2022-03-22T09:45:25.000Z

# Copyright 2021 NVIDIA Corporation # # 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 legate.pandas.common import types as ty from legate.pandas.config import OpCode from legate.pandas.core.pattern import Map, Projection, ScalarMap

28.669643

74

0.678293

# Copyright 2021 NVIDIA Corporation # # 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 legate.pandas.common import types as ty from legate.pandas.config import OpCode from legate.pandas.core.pattern import Map, Projection, ScalarMap class Bitmask(object): alloc_type = ty.uint8 def __init__(self, runtime, storage): self._runtime = runtime self._storage = storage self._compact_bitmask = None @property def region(self): return self._storage.region @property def field_id(self): return self._storage.field_id @property def dtype(self): return self._storage.dtype @property def num_pieces(self): return self._storage.num_pieces @property def launch_domain(self): return self._storage.launch_domain @property def storage(self): return self._storage.storage @property def ispace(self): return self._storage.ispace @property def primary_ipart(self): return self._storage.primary_ipart @property def fspace(self): return self._storage.fspace @property def compact_bitmask(self): if self._compact_bitmask is None: result = self._storage.storage.create_new_field(self.dtype) result.set_primary_ipart(self.primary_ipart) plan = Map(self._runtime, OpCode.TO_BITMASK) proj = Projection(self._storage.primary_ipart) plan.add_output_only(result) plan.add_scalar_arg(False, ty.bool) plan.add_scalar_arg(0, ty.uint32) plan.add_input(self._storage, proj) plan.add_scalar_arg(False, ty.bool) plan.add_scalar_arg(0, ty.uint32) plan.execute(self.launch_domain) self._compact_bitmask = result return self._compact_bitmask def clone(self): return Bitmask(self._runtime, self._storage.clone()) def set_primary_ipart(self, ipart): self._storage.set_primary_ipart(ipart) def get_view(self, ipart): return self._runtime.create_region_partition(self.region, ipart) # XXX: This method should be used with caution as it gets blocked # on a future internally def has_nulls(self): return self.count_nulls() > 0 def count_nulls(self): from .column import Column plan = ScalarMap(self._runtime, OpCode.COUNT_NULLS, ty.uint64) boolmask = Column(self._runtime, self._storage) boolmask.add_to_plan(plan, True) counts = plan.execute(self.launch_domain) return counts.sum().get_value() def to_raw_address(self): return self._storage.to_raw_address()

1,721

730

23

0a2586d7e1874e8ca79ba94674abca86141dfa90

5,066

py

Python

backend/config/settings/base.py

code-for-canada/django-nginx-reactjs-docker

12b2f79872273bb0ac4736d709b8e0904bc54258

[ "MIT" ]

3

2019-01-04T10:53:03.000Z

2020-01-29T16:20:38.000Z

backend/config/settings/base.py

code-for-canada/django-nginx-reactjs-docker

12b2f79872273bb0ac4736d709b8e0904bc54258

[ "MIT" ]

215

2019-01-04T11:34:03.000Z

2019-07-22T13:36:18.000Z

backend/config/settings/base.py

code-for-canada/django-nginx-reactjs-docker

12b2f79872273bb0ac4736d709b8e0904bc54258

[ "MIT" ]

8

2019-01-08T22:45:11.000Z

2020-01-29T16:20:40.000Z

""" Django settings for backend project. Generated by 'django-admin startproject' using Django 2.1.4. Since the start of the project, we have upgraded the version to 2.1.7 For more information on this file, see https://docs.djangoproject.com/en/2.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.1/ref/settings/ """ import os import datetime # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = "%qviowlmp*kitbai+y!%1y=jdl_o3_#7+_ud6l9uwn$$=bxt1y" ALLOWED_HOSTS = "*" CORS_ORIGIN_ALLOW_ALL = True # Application definition INSTALLED_APPS = [ # Personal, "custom_models", # BASE "django.contrib.admin", "django.contrib.auth", "django.contrib.contenttypes", "django.contrib.sessions", "django.contrib.messages", "django.contrib.staticfiles", # Requirements "corsheaders", "rest_framework", "djoser", "rest_framework_swagger", "rest_framework.authtoken", ] MIDDLEWARE = [ "django.middleware.security.SecurityMiddleware", "django.contrib.sessions.middleware.SessionMiddleware", "django.middleware.common.CommonMiddleware", "django.middleware.csrf.CsrfViewMiddleware", "django.contrib.auth.middleware.AuthenticationMiddleware", "django.contrib.messages.middleware.MessageMiddleware", "django.middleware.clickjacking.XFrameOptionsMiddleware", "corsheaders.middleware.CorsMiddleware", ] ROOT_URLCONF = "config.urls" WSGI_APPLICATION = "config.wsgi.application" TEMPLATES = [ { "BACKEND": "django.template.backends.django.DjangoTemplates", "DIRS": [], "APP_DIRS": True, "OPTIONS": { "context_processors": [ "django.template.context_processors.debug", "django.template.context_processors.request", "django.contrib.auth.context_processors.auth", "django.contrib.messages.context_processors.messages", ] }, } ] # Password validation # https://docs.djangoproject.com/en/2.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { "NAME": "django.contrib.auth.password_validation.UserAttributeSimilarityValidator" }, {"NAME": "django.contrib.auth.password_validation.MinimumLengthValidator"}, {"NAME": "django.contrib.auth.password_validation.CommonPasswordValidator"}, {"NAME": "django.contrib.auth.password_validation.NumericPasswordValidator"}, ] REST_FRAMEWORK = { "DEFAULT_PERMISSION_CLASSES": ( "rest_framework.permissions.IsAuthenticatedOrReadOnly", ), "DEFAULT_AUTHENTICATION_CLASSES": ( "rest_framework.authentication.SessionAuthentication", "rest_framework.authentication.BasicAuthentication", "rest_framework_jwt.authentication.JSONWebTokenAuthentication", ), } LANGUAGE_CODE = "en-us" TIME_ZONE = "Canada/Eastern" USE_I18N = True USE_L10N = True USE_TZ = True CORS_ALLOW_HEADERS = [ "accept", "accept-encoding", "authorization", "content-disposition", "content-type", "origin", "user-agent", "x-csrftoken", "x-requested-with", ] # Allow the user to log in by email or username AUTH_USER_MODEL = "custom_models.User" # JWT settings for authentication JWT_AUTH = { "JWT_EXPIRATION_DELTA": datetime.timedelta(hours=1), "JWT_ALLOW_REFRESH": True, } SIMPLE_JWT = {"AUTH_HEADER_TYPES": ("JWT",)} # Swagger settings for documentation SWAGGER_SETTINGS = { "LOGIN_URL": "rest_framework:login", "LOGOUT_URL": "rest_framework:logout", } # Djoser settings for Rest Login (https://djoser.readthedocs.io/en/latest/settings.html) DJOSER = { "SET_PASSWORD_RETYPE": True, "SEND_ACTIVATION_EMAIL": False, "PERMISSIONS": { # Admin Only "activation": ["rest_framework.permissions.IsAdminUser"], # "set_username": ["rest_framework.permissions.IsAdminUser"], "user_delete": ["rest_framework.permissions.IsAdminUser"], "user_list": ["rest_framework.permissions.IsAdminUser"], "password_reset": ["rest_framework.permissions.IsAdminUser"], # Authenticated "token_destroy": ["rest_framework.permissions.IsAuthenticated"], # Current User or Admin "user": ["djoser.permissions.CurrentUserOrAdmin"], "set_password": ["djoser.permissions.CurrentUserOrAdmin"], # Any "password_reset_confirm": ["rest_framework.permissions.AllowAny"], "user_create": ["rest_framework.permissions.AllowAny"], "token_create": ["rest_framework.permissions.AllowAny"], }, }

32.267516

91

0.681603

""" Django settings for backend project. Generated by 'django-admin startproject' using Django 2.1.4. Since the start of the project, we have upgraded the version to 2.1.7 For more information on this file, see https://docs.djangoproject.com/en/2.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.1/ref/settings/ """ import os import datetime # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = "%qviowlmp*kitbai+y!%1y=jdl_o3_#7+_ud6l9uwn$$=bxt1y" ALLOWED_HOSTS = "*" CORS_ORIGIN_ALLOW_ALL = True # Application definition INSTALLED_APPS = [ # Personal, "custom_models", # BASE "django.contrib.admin", "django.contrib.auth", "django.contrib.contenttypes", "django.contrib.sessions", "django.contrib.messages", "django.contrib.staticfiles", # Requirements "corsheaders", "rest_framework", "djoser", "rest_framework_swagger", "rest_framework.authtoken", ] MIDDLEWARE = [ "django.middleware.security.SecurityMiddleware", "django.contrib.sessions.middleware.SessionMiddleware", "django.middleware.common.CommonMiddleware", "django.middleware.csrf.CsrfViewMiddleware", "django.contrib.auth.middleware.AuthenticationMiddleware", "django.contrib.messages.middleware.MessageMiddleware", "django.middleware.clickjacking.XFrameOptionsMiddleware", "corsheaders.middleware.CorsMiddleware", ] ROOT_URLCONF = "config.urls" WSGI_APPLICATION = "config.wsgi.application" TEMPLATES = [ { "BACKEND": "django.template.backends.django.DjangoTemplates", "DIRS": [], "APP_DIRS": True, "OPTIONS": { "context_processors": [ "django.template.context_processors.debug", "django.template.context_processors.request", "django.contrib.auth.context_processors.auth", "django.contrib.messages.context_processors.messages", ] }, } ] # Password validation # https://docs.djangoproject.com/en/2.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { "NAME": "django.contrib.auth.password_validation.UserAttributeSimilarityValidator" }, {"NAME": "django.contrib.auth.password_validation.MinimumLengthValidator"}, {"NAME": "django.contrib.auth.password_validation.CommonPasswordValidator"}, {"NAME": "django.contrib.auth.password_validation.NumericPasswordValidator"}, ] REST_FRAMEWORK = { "DEFAULT_PERMISSION_CLASSES": ( "rest_framework.permissions.IsAuthenticatedOrReadOnly", ), "DEFAULT_AUTHENTICATION_CLASSES": ( "rest_framework.authentication.SessionAuthentication", "rest_framework.authentication.BasicAuthentication", "rest_framework_jwt.authentication.JSONWebTokenAuthentication", ), } LANGUAGE_CODE = "en-us" TIME_ZONE = "Canada/Eastern" USE_I18N = True USE_L10N = True USE_TZ = True CORS_ALLOW_HEADERS = [ "accept", "accept-encoding", "authorization", "content-disposition", "content-type", "origin", "user-agent", "x-csrftoken", "x-requested-with", ] # Allow the user to log in by email or username AUTH_USER_MODEL = "custom_models.User" # JWT settings for authentication JWT_AUTH = { "JWT_EXPIRATION_DELTA": datetime.timedelta(hours=1), "JWT_ALLOW_REFRESH": True, } SIMPLE_JWT = {"AUTH_HEADER_TYPES": ("JWT",)} # Swagger settings for documentation SWAGGER_SETTINGS = { "LOGIN_URL": "rest_framework:login", "LOGOUT_URL": "rest_framework:logout", } # Djoser settings for Rest Login (https://djoser.readthedocs.io/en/latest/settings.html) DJOSER = { "SET_PASSWORD_RETYPE": True, "SEND_ACTIVATION_EMAIL": False, "PERMISSIONS": { # Admin Only "activation": ["rest_framework.permissions.IsAdminUser"], # "set_username": ["rest_framework.permissions.IsAdminUser"], "user_delete": ["rest_framework.permissions.IsAdminUser"], "user_list": ["rest_framework.permissions.IsAdminUser"], "password_reset": ["rest_framework.permissions.IsAdminUser"], # Authenticated "token_destroy": ["rest_framework.permissions.IsAuthenticated"], # Current User or Admin "user": ["djoser.permissions.CurrentUserOrAdmin"], "set_password": ["djoser.permissions.CurrentUserOrAdmin"], # Any "password_reset_confirm": ["rest_framework.permissions.AllowAny"], "user_create": ["rest_framework.permissions.AllowAny"], "token_create": ["rest_framework.permissions.AllowAny"], }, }

0

c01ab772ffcdea63e59f9b9d308e786b82109257

433

py

Python

openrec/tf1/recommenders/__init__.py

pbaiz/openrec

a00de2345844858194ef43ab6845342114a5be93

[ "Apache-2.0" ]

399

2018-01-04T15:24:02.000Z

2022-03-31T09:39:05.000Z

openrec/tf1/recommenders/__init__.py

pbaiz/openrec

a00de2345844858194ef43ab6845342114a5be93

[ "Apache-2.0" ]

26

2018-01-14T04:01:28.000Z

2022-02-09T23:36:32.000Z

openrec/tf1/recommenders/__init__.py

pbaiz/openrec

a00de2345844858194ef43ab6845342114a5be93

[ "Apache-2.0" ]

97

2017-12-22T07:07:35.000Z

2022-01-24T19:04:02.000Z

from openrec.tf1.recommenders.recommender import Recommender from openrec.tf1.recommenders.bpr import BPR from openrec.tf1.recommenders.pmf import PMF from openrec.tf1.recommenders.ucml import UCML from openrec.tf1.recommenders.vbpr import VBPR from openrec.tf1.recommenders.vanilla_youtube_rec import VanillaYouTubeRec from openrec.tf1.recommenders.youtube_rec import YouTubeRec from openrec.tf1.recommenders.rnn_rec import RNNRec

43.3

74

0.86836

from openrec.tf1.recommenders.recommender import Recommender from openrec.tf1.recommenders.bpr import BPR from openrec.tf1.recommenders.pmf import PMF from openrec.tf1.recommenders.ucml import UCML from openrec.tf1.recommenders.vbpr import VBPR from openrec.tf1.recommenders.vanilla_youtube_rec import VanillaYouTubeRec from openrec.tf1.recommenders.youtube_rec import YouTubeRec from openrec.tf1.recommenders.rnn_rec import RNNRec

0

708f01c2e192ca13b47544b19668cfceb08b35f7

18,306

py

Python

project/src/main/python/backTest/factorAnalysis/updateStockPool.py

daifengqi/big-data-hft

013747ca3c2ca984eeac723fd5d8f8e3458b840c

[ "MIT" ]

1

2022-03-07T09:32:40.000Z

project/src/main/python/backTest/factorAnalysis/updateStockPool.py

daifengqi/big-data-hft

013747ca3c2ca984eeac723fd5d8f8e3458b840c

[ "MIT" ]

null

project/src/main/python/backTest/factorAnalysis/updateStockPool.py

daifengqi/big-data-hft

013747ca3c2ca984eeac723fd5d8f8e3458b840c

[ "MIT" ]

1

2022-03-03T16:22:37.000Z

import copy import itertools import os import time import numpy as np import pandas as pd import scipy.io as scio import yaml import factorAnalysisIOTools as IOTools from factorAnalysisCalTools import prepare_RET_dict, time_horizon_dict if __name__ == '__main__': config_path = r"D:\HX_proj\factorAnalysis\updateStockPoolConfig.yaml" updateSP = UpdateStockPool(config_path) updateSP.update_stock_info() updateSP.update_stock_pool_basic() updateSP.update_stock_HS300() updateSP.update_stock_ZZ500() updateSP.update_stock_ZZ800() stock_pool_name = 'STOCK_POOL_basic' stock_pool_path = f"E:\\data\\interday\\{stock_pool_name}.pkl" update_benchmark_return(stock_pool_path=stock_pool_path,stock_pool_name=stock_pool_name,benchmark_ret_save_dir = r"E:\data\interday")

54.159763

149

0.689282

import copy import itertools import os import time import numpy as np import pandas as pd import scipy.io as scio import yaml import factorAnalysisIOTools as IOTools from factorAnalysisCalTools import prepare_RET_dict, time_horizon_dict def save_df(this: pd.DataFrame,config: dict,file_name): file_path = os.path.join(config['utility_data_dir'],config[file_name]+".pkl") if os.path.exists(file_path): that = pd.read_pickle(file_path) this = that.append(this) this.drop_duplicates(subset=['date','code'],inplace=True,keep='last') this.to_pickle(file_path) def loadmat2df_interday(path): temp = scio.loadmat(path) this = pd.DataFrame(temp['SCORE'], index=temp['TRADE_DT'].squeeze().tolist(), columns=[x[0] for x in temp['STOCK_CODE'].squeeze()]) return this class LoadStockInfo(): def __init__(self,config): self.config = config temp = scio.loadmat(os.path.join(config['utility_data_dir'],config['SIZE_file_name']+".mat")) self.all_date_mat = temp['TRADE_DT'].squeeze() self.all_code_mat = [x[0] for x in temp['STOCK_CODE'].squeeze()] self.start_date = self.all_date_mat[self.all_date_mat>=config['start_date']][0] self.end_date = self.all_date_mat[self.all_date_mat<=config['end_date']][-1] self.start_indexer = np.where(self.all_date_mat==self.start_date)[0][0] self.end_indexer = np.where(self.all_date_mat==self.end_date)[0][0] self.date_list = self.all_date_mat[self.start_indexer:self.end_indexer+1] self.date_code_product = np.array(list(itertools.product(self.date_list,self.all_code_mat))) # self.date_code_product = np.array(list(itertools.product(self.date_list,self.all_code_mat)),dtype=[('date','int'),('code','object')]) def load_arr(self,file_name,start_back_days=0,end_forward_days=0): path = os.path.join( self.config['utility_data_dir'], self.config[file_name]+".mat" ) # log--20210804：对于ZX_1的数据，他们的STOCK_CODE的顺序和数量和其他的可能不一样 # 查找self.all_code_mat的code在stkcd里面的位置，对应的score里面取出这些地方的元素，相当于reindex一下 # update: 直接读取df，然后reindex，然后取value score = loadmat2df_interday(path).reindex(index=self.all_date_mat,columns=self.all_code_mat).values print(file_name,score.shape) start = max(self.start_indexer-start_back_days,0) end = min(self.end_indexer+end_forward_days+1,len(score)) data = score[start:end] pad_width_axis0 = ( max(start_back_days-self.start_indexer,0), max(self.end_indexer+end_forward_days+1-len(score),0) ) if pad_width_axis0 != (0,0): data = np.pad(data, pad_width=(pad_width_axis0,(0,0)),mode='edge') return data def update_limit_300_688(self,start_back_days=0,end_forward_days=0): code_300 = np.array([x.startswith("300") for x in self.all_code_mat]) code_688 = np.array([x.startswith("688") for x in self.all_code_mat]) chg_date_300 = np.array([x>=20200824 for x in self.all_date_mat]) code_300_score = np.tile(code_300,(len(chg_date_300),1)) code_688_score = np.tile(code_688,(len(chg_date_300),1)) chg_date_300_score = np.tile(chg_date_300.reshape(-1,1),(1,len(code_300))) assert code_300_score.shape == (len(self.all_date_mat),len(self.all_code_mat)), "code_300 shape wrong" start = max(self.start_indexer-start_back_days,0) end = min(self.end_indexer+end_forward_days+1,len(code_300_score)) code_300_data = code_300_score[start:end] code_688_data = code_688_score[start:end] chg_date_data = chg_date_300_score[start:end] return code_300_data,code_688_data,chg_date_data class UpdateStockPool(): def __init__(self,config_path): with open(config_path) as f: self.config = yaml.load(f.read(),Loader=yaml.FullLoader) self.config['STOCK_INFO_file_path'] = os.path.join(self.config['utility_data_dir'],self.config['STOCK_INFO_file_name']+".pkl") def update_stock_info(self): config = copy.deepcopy(self.config) stock_info_loader = LoadStockInfo(config) t = time.time() # ADJFACTOR_2d_forward1 = stock_info_loader.load_arr('ADJFACTOR_file_name',end_forward_days=1)[1:] # OPEN_2d_forward1 = stock_info_loader.load_arr('ADJFACTOR_file_name',end_forward_days=1)[1:] # ADJOPEN_2d_forward1 = ADJFACTOR_2d_forward1*OPEN_2d_forward1 FF_CAPITAL_2d = stock_info_loader.load_arr('FF_CAPITAL_file_name') PRECLOSE_2d_forward1 = stock_info_loader.load_arr('PRECLOSE_file_name',end_forward_days=1)[1:] # RETURN_TWAP_Q1_2d = stock_info_loader.load_arr('RETURN_TWAP_Q1_file_name',end_forward_days=1) FCT_HF_TWAP_H1_forward1 = stock_info_loader.load_arr('FCT_HF_TWAP_H1_file_name',end_forward_days=1)[1:] RETURN_2d = stock_info_loader.load_arr('RETURN_file_name',end_forward_days=1) # 20210917: 更新计算涨跌停的方法，算涨跌停的时候，20200824开始创业板涨幅停调整到了20% # 创业板通过stock_code前3位等于300识别；还有科创板，前3位是688；科创板自上市以来就是20%涨跌幅，创业板是20200824开始改20%的 code_300_data,code_688_data,chg_date_data = stock_info_loader.update_limit_300_688() lmt1_t0 = (abs(RETURN_2d)>0.195)[:-1] lmt2_t0 = (abs(RETURN_2d)>0.095)[:-1] & (code_688_data==False) & (chg_date_data==False) lmt3_t0 = (abs(RETURN_2d)>0.095)[:-1] & (code_688_data==False) & (code_300_data==False) LIMIT_UD_t0_1d = (lmt1_t0 | lmt2_t0 | lmt3_t0).reshape(-1,) # 20211007: ADJOPEN*limit_ratio*5/6=LIMIT_PRICE_THRESHOLD_H1 lmt1_t1 = (abs(FCT_HF_TWAP_H1_forward1/PRECLOSE_2d_forward1-1)>0.195*5/6) lmt2_t1 = (abs(FCT_HF_TWAP_H1_forward1/PRECLOSE_2d_forward1-1)>0.095*5/6) & (code_688_data==False) & (chg_date_data==False) lmt3_t1 = (abs(FCT_HF_TWAP_H1_forward1/PRECLOSE_2d_forward1-1)>0.095*5/6) & (code_688_data==False) & (code_300_data==False) LIMIT_UD_t1_1d = (lmt1_t1 | lmt2_t1 | lmt3_t1).reshape(-1,) LIMIT_UD_filter_t0_t1_1d = ((LIMIT_UD_t0_1d + LIMIT_UD_t1_1d) == 0) # LIMIT_UD_t0_1d = ((abs(RETURN_TWAP_Q1_2d)>0.095)[:-1]).reshape(-1,) # LIMIT_UD_t1_1d = ((abs(RETURN_TWAP_Q1_2d)>0.095)[1:]).reshape(-1,) # LIMIT_UD_filter_t0_t1_1d = (LIMIT_UD_t0_1d + LIMIT_UD_t1_1d) == 0 ADJFACTOR_2d = stock_info_loader.load_arr('ADJFACTOR_file_name') VWAP_2d = stock_info_loader.load_arr('VWAP_file_name') CLOSE_2d = stock_info_loader.load_arr('CLOSE_file_name') AMOUNT_1d = stock_info_loader.load_arr('AMOUNT_file_name').reshape(-1,) ADJVWAP_1d = (ADJFACTOR_2d*VWAP_2d).reshape(-1,) ADJCLOSE_1d = (ADJFACTOR_2d*CLOSE_2d).reshape(-1,) CLOSE_1d = CLOSE_2d.reshape(-1,) FF_SIZE_1d = (FF_CAPITAL_2d*VWAP_2d).reshape(-1,) ADJFACTOR_2d_back19 = stock_info_loader.load_arr('ADJFACTOR_file_name',start_back_days=19) VOLUME_2d_back19 = stock_info_loader.load_arr('VOLUME_file_name',start_back_days=19) ADJVOLUME_2d_back19 = VOLUME_2d_back19/ADJFACTOR_2d_back19 ADJVOLUME_ma20_2d = pd.DataFrame(ADJVOLUME_2d_back19).rolling(20).mean().values[19:] ADJVOLUME_ma20_1d = ADJVOLUME_ma20_2d.reshape(-1,) ADJVOLUME_ma20_q20_1d = np.nanquantile(ADJVOLUME_ma20_2d, q=0.2,axis=1,keepdims=False) ADJVOLUME_ma20_q20_1d = np.repeat(ADJVOLUME_ma20_q20_1d, repeats=ADJVOLUME_ma20_2d.shape[1]) FF_CAPITAL_ma20_2d = stock_info_loader.load_arr('FF_CAPITAL_file_name',start_back_days=19) FF_CAPITAL_ma20_2d = pd.DataFrame(FF_CAPITAL_ma20_2d).rolling(20).mean().values[19:] FF_CAPITAL_ma20_1d = FF_CAPITAL_ma20_2d.reshape(-1,) FF_CAPITAL_ma20_q20_1d = np.nanquantile(FF_CAPITAL_ma20_2d, q=0.2,axis=1,keepdims=False) FF_CAPITAL_ma20_q20_1d = np.repeat(FF_CAPITAL_ma20_q20_1d, repeats=FF_CAPITAL_ma20_2d.shape[1]) TOTAL_TRADEDAYS_1d = stock_info_loader.load_arr('TOTAL_TRADEDAYS_file_name').reshape(-1,) HS300_member_1d = stock_info_loader.load_arr('HS300_member_file_name').reshape(-1,) ZZ500_member_1d = stock_info_loader.load_arr('ZZ500_member_file_name').reshape(-1,) ISST_1d = stock_info_loader.load_arr('ISST_file_name').reshape(-1,) ISTRADEDAY_1d = stock_info_loader.load_arr('ISTRADEDAY_file_name').reshape(-1,) ZX_1_1d = stock_info_loader.load_arr('ZX_1_file_name').reshape(-1,) SIZE_1d = stock_info_loader.load_arr('SIZE_file_name').reshape(-1,) LIQUIDTY_1d = stock_info_loader.load_arr('LIQUIDTY_file_name').reshape(-1,) MOMENTUM_1d = stock_info_loader.load_arr('MOMENTUM_file_name').reshape(-1,) RESVOL_1d = stock_info_loader.load_arr('RESVOL_file_name').reshape(-1,) SIZENL_1d = stock_info_loader.load_arr('SIZENL_file_name').reshape(-1,) SRISK_1d = stock_info_loader.load_arr('SRISK_file_name').reshape(-1,) ADP_1d = stock_info_loader.load_arr('ADP_file_name').reshape(-1,) BETA_1d = stock_info_loader.load_arr('BETA_file_name').reshape(-1,) BTOP_1d = stock_info_loader.load_arr('BTOP_file_name').reshape(-1,) EARNYILD_1d = stock_info_loader.load_arr('EARNYILD_file_name').reshape(-1,) GROWTH_1d = stock_info_loader.load_arr('GROWTH_file_name').reshape(-1,) LEVERAGE_1d = stock_info_loader.load_arr('LEVERAGE_file_name').reshape(-1,) print("IO time",time.time()-t) t = time.time() STOCK_INFO_2d = np.stack( [ SIZE_1d,ZX_1_1d,ADJVWAP_1d,ADJCLOSE_1d,CLOSE_1d,AMOUNT_1d,FF_SIZE_1d, HS300_member_1d,ZZ500_member_1d,ISST_1d, ISTRADEDAY_1d,TOTAL_TRADEDAYS_1d,LIMIT_UD_t0_1d,LIMIT_UD_t1_1d,LIMIT_UD_filter_t0_t1_1d, ADJVOLUME_ma20_1d,ADJVOLUME_ma20_q20_1d,FF_CAPITAL_ma20_1d,FF_CAPITAL_ma20_q20_1d, LIQUIDTY_1d,MOMENTUM_1d,RESVOL_1d,SIZENL_1d,SRISK_1d, ADP_1d,BETA_1d,BTOP_1d,EARNYILD_1d,GROWTH_1d,LEVERAGE_1d ], axis=1 ) print("concate time",time.time()-t) t = time.time() date_code_product_2d = stock_info_loader.date_code_product STOCK_INFO_cols_name = [ 'SIZE','ZX_1','ADJVWAP','ADJCLOSE','CLOSE','AMOUNT','FF_SIZE','HS300_member','ZZ500_member', 'ISST','ISTRADEDAY','TOTAL_TRADEDAYS','LIMIT_UD_t0','LIMIT_UD_t1','LIMIT_UD_filter_t0_t1_1d', 'ADJVOLUME_ma20','ADJVOLUME_ma20_q20','FF_CAPITAL_ma20','FF_CAPITAL_ma20_q20', 'LIQUIDTY','MOMENTUM','RESVOL','SIZENL','SRISK', 'ADP','BETA','BTOP','EARNYILD','GROWTH','LEVERAGE', 'date','code' ] STOCK_INFO_df = pd.DataFrame(STOCK_INFO_2d.astype('float32'),columns=STOCK_INFO_cols_name[:-2]) STOCK_INFO_df['date'] = date_code_product_2d[:,0].astype('int') STOCK_INFO_df['code'] = date_code_product_2d[:,1] print("form df time: ",time.time()-t) t = time.time() save_df(STOCK_INFO_df,self.config,'STOCK_INFO_file_name') self.STOCK_INFO = STOCK_INFO_df print("save time",time.time()-t) def update_stock_pool_basic(self,STOCK_INFO_file_path=None): ''' T0当天结束计算的factor，这个SP用于分组，后续可能在真的计算分组return的时候，需要再筛选一个能否在第二天买入的SP_T1，（对于分析因子的影响？？？） SP_basic： - 全市场 # - T0当天没有涨跌停（RETURN的abs大于0.095） # - T1当天没有涨跌停 - 不是ST - 是TRADEDAY - 上市满一年（STOCK_INFO.datetime-STOCK_INFO.list_date > 365） ''' if hasattr(self, 'STOCK_INFO'): STOCK_INFO = self.STOCK_INFO else: if STOCK_INFO_file_path is None: STOCK_INFO_file_path=self.config['STOCK_INFO_file_path'] STOCK_INFO = pd.read_pickle(STOCK_INFO_file_path) STOCK_INFO = STOCK_INFO[(STOCK_INFO.date>=self.config['start_date'])&(STOCK_INFO.date<=self.config['end_date'])] filter_basic = (STOCK_INFO['ISTRADEDAY']==1.0) & (STOCK_INFO['TOTAL_TRADEDAYS']>250) & (STOCK_INFO['ISST']==0.0) STOCK_POOL_basic = STOCK_INFO.loc[filter_basic,self.config['STOCK_POOL_cols']] save_df(STOCK_POOL_basic,self.config,'STOCK_POOL_basic_file_name') def update_stock_pool_cap_vol_drop20(self,STOCK_INFO_file_path=None): ''' T0当天结束计算的factor，这个SP用于分组，后续可能在真的计算分组return的时候，需要再筛选一个能否在第二天买入的SP_T1，（对于分析因子的影响？？？） SP_cap_vol_drop20： - 全市场 - 去除流动性后20%（过去20天的voluma ma大于截面的q20） - 去除流通市值后20% - T0当天没有涨跌停（RETURN的abs大于0.095） - T1当天没有涨跌停 - 不是ST - 是TRADEDAY - 上市满一年（STOCK_INFO.datetime-STOCK_INFO.list_date > 365） ''' if hasattr(self, 'STOCK_INFO'): STOCK_INFO = self.STOCK_INFO else: if STOCK_INFO_file_path is None: STOCK_INFO_file_path=self.config['STOCK_INFO_file_path'] STOCK_INFO = pd.read_pickle(STOCK_INFO_file_path) STOCK_INFO = STOCK_INFO[(STOCK_INFO.date>=self.config['start_date'])&(STOCK_INFO.date<=self.config['end_date'])] filter_basic = ( STOCK_INFO['ADJVOLUME_ma20']>STOCK_INFO['ADJVOLUME_ma20_q20'])&\ (STOCK_INFO['FF_CAPITAL_ma20']>STOCK_INFO['FF_CAPITAL_ma20_q20'])&\ (STOCK_INFO['ISTRADEDAY']==1.0) & (STOCK_INFO['TOTAL_TRADEDAYS']>250) & (STOCK_INFO['ISST']==0.0) STOCK_POOL_basic = STOCK_INFO.loc[filter_basic,self.config['STOCK_POOL_cols']] save_df(STOCK_POOL_basic,self.config,'STOCK_POOL_cap_vol_drop20_file_name') def update_stock_HS300(self,STOCK_INFO_file_path=None): ''' 满足basic的要求且是HS300里面的成分股 ''' if hasattr(self, 'STOCK_INFO'): STOCK_INFO = self.STOCK_INFO else: if STOCK_INFO_file_path is None: STOCK_INFO_file_path=self.config['STOCK_INFO_file_path'] STOCK_INFO = pd.read_pickle(STOCK_INFO_file_path) STOCK_INFO = STOCK_INFO[(STOCK_INFO.date>=self.config['start_date'])&(STOCK_INFO.date<=self.config['end_date'])] filter_HS300 = (STOCK_INFO['HS300_member']==1.0) & (STOCK_INFO['LIMIT_UD_t0'] == 0.0) &\ (STOCK_INFO['ISTRADEDAY']==1.0) & (STOCK_INFO['TOTAL_TRADEDAYS']>250) & (STOCK_INFO['ISST']==0.0) STOCK_POOL_HS300 = STOCK_INFO.loc[filter_HS300,self.config['STOCK_POOL_cols']] save_df(STOCK_POOL_HS300,self.config,'STOCK_POOL_HS300_file_name') def update_stock_ZZ500(self,STOCK_INFO_file_path=None): if hasattr(self, 'STOCK_INFO'): STOCK_INFO = self.STOCK_INFO else: if STOCK_INFO_file_path is None: STOCK_INFO_file_path=self.config['STOCK_INFO_file_path'] STOCK_INFO = pd.read_pickle(STOCK_INFO_file_path) STOCK_INFO = STOCK_INFO[(STOCK_INFO.date>=self.config['start_date'])&(STOCK_INFO.date<=self.config['end_date'])] filter_ZZ500 = (STOCK_INFO['ZZ500_member']==1.0) &\ (STOCK_INFO['ISTRADEDAY']==1.0) & (STOCK_INFO['TOTAL_TRADEDAYS']>250) & (STOCK_INFO['ISST']==0.0) STOCK_POOL_ZZ500 = STOCK_INFO.loc[filter_ZZ500,self.config['STOCK_POOL_cols']] save_df(STOCK_POOL_ZZ500,self.config,'STOCK_POOL_ZZ500_file_name') def update_stock_ZZ800(self,STOCK_INFO_file_path=None): if hasattr(self, 'STOCK_INFO'): STOCK_INFO = self.STOCK_INFO else: if STOCK_INFO_file_path is None: STOCK_INFO_file_path=self.config['STOCK_INFO_file_path'] STOCK_INFO = pd.read_pickle(STOCK_INFO_file_path) STOCK_INFO = STOCK_INFO[(STOCK_INFO.date>=self.config['start_date'])&(STOCK_INFO.date<=self.config['end_date'])] filter_ZZ500 = ((STOCK_INFO['ZZ500_member']==1.0) | (STOCK_INFO['HS300_member']==1.0))&\ (STOCK_INFO['ISTRADEDAY']==1.0) & (STOCK_INFO['TOTAL_TRADEDAYS']>250) & (STOCK_INFO['ISST']==0.0) STOCK_POOL_ZZ500 = STOCK_INFO.loc[filter_ZZ500,self.config['STOCK_POOL_cols']] save_df(STOCK_POOL_ZZ500,self.config,'STOCK_POOL_ZZ800_file_name') def update_stock_800(self,STOCK_INFO_file_path=None): if hasattr(self, 'STOCK_INFO'): STOCK_INFO = self.STOCK_INFO else: if STOCK_INFO_file_path is None: STOCK_INFO_file_path=self.config['STOCK_INFO_file_path'] STOCK_INFO = pd.read_pickle(STOCK_INFO_file_path) STOCK_INFO = STOCK_INFO[(STOCK_INFO.date>=self.config['start_date'])&(STOCK_INFO.date<=self.config['end_date'])] filter_ZZ500 = ((STOCK_INFO['ZZ500_member']==1.0) | (STOCK_INFO['HS300_member']==1.0))&\ (STOCK_INFO['ISTRADEDAY']==1.0) & (STOCK_INFO['TOTAL_TRADEDAYS']>250) & (STOCK_INFO['ISST']==0.0) STOCK_POOL_ZZ500 = STOCK_INFO.loc[filter_ZZ500,self.config['STOCK_POOL_cols']] save_df(STOCK_POOL_ZZ500,self.config,'STOCK_POOL_800_file_name') def update_benchmark_return(stock_pool=None,stock_pool_path=None,stock_pool_name=None,benchmark_ret_save_dir=None): if stock_pool is None: stock_pool = pd.read_pickle(stock_pool_path) stock_pool_adjvwap = stock_pool.pivot(index='date',columns='code',values='ADJVWAP') stock_pool_adjclose = stock_pool.pivot(index='date',columns='code',values='ADJCLOSE') RET_dict = prepare_RET_dict(stock_pool_adjvwap, stock_pool_adjclose) benchmark_ret_list = [] for RET_key, RET_tn in RET_dict.items(): RET_tn = RET_tn/time_horizon_dict[RET_key] benchmark_ret_list.append(pd.DataFrame(RET_tn.mean(axis=1),columns=[RET_key])) IOTools.save_this(pd.concat(benchmark_ret_list,axis=1), benchmark_ret_save_dir,f'BENCHMARK_RETURN_{stock_pool_name.replace("STOCK_POOL_","")}') if __name__ == '__main__': config_path = r"D:\HX_proj\factorAnalysis\updateStockPoolConfig.yaml" updateSP = UpdateStockPool(config_path) updateSP.update_stock_info() updateSP.update_stock_pool_basic() updateSP.update_stock_HS300() updateSP.update_stock_ZZ500() updateSP.update_stock_ZZ800() stock_pool_name = 'STOCK_POOL_basic' stock_pool_path = f"E:\\data\\interday\\{stock_pool_name}.pkl" update_benchmark_return(stock_pool_path=stock_pool_path,stock_pool_name=stock_pool_name,benchmark_ret_save_dir = r"E:\data\interday")

14,104

3,919

201

5dd0ee9d6513012c54587e1dc2268e195652a1f7

2,585

py

Python

examples/PyGame/orientation_control_osc.py

elsuizo/abr_control

d7d47a1c152dfcb8d1a3093083d53f19cc4922d6

[ "BSD-3-Clause" ]

1

2021-07-07T13:26:38.000Z

examples/PyGame/orientation_control_osc.py

elsuizo/abr_control

d7d47a1c152dfcb8d1a3093083d53f19cc4922d6

[ "BSD-3-Clause" ]

null

examples/PyGame/orientation_control_osc.py

elsuizo/abr_control

d7d47a1c152dfcb8d1a3093083d53f19cc4922d6

[ "BSD-3-Clause" ]

null

""" Running operational space control with the PyGame display. The arm will move the end-effector to a target orientation, which can be changed by pressing the left/right arrow keys. """ import numpy as np from os import environ environ['PYGAME_HIDE_SUPPORT_PROMPT'] = '1' import pygame from abr_control.arms import threejoint as arm # from abr_control.arms import twojoint as arm from abr_control.interfaces import PyGame from abr_control.utils import transformations from abr_control.controllers import OSC, Damping # initialize our robot config robot_config = arm.Config(use_cython=True) # create our arm simulation arm_sim = arm.ArmSim(robot_config) # damp the movements of the arm damping = Damping(robot_config, kv=10) # create operational space controller ctrlr = OSC(robot_config, kp=50, null_controllers=[damping], # control (gamma) out of [x, y, z, alpha, beta, gamma] ctrlr_dof = [False, False, False, False, False, True]) # create our interface interface = PyGame(robot_config, arm_sim, dt=.001, on_keypress=on_keypress) interface.connect() interface.theta = -3 * np.pi / 4 feedback = interface.get_feedback() R = robot_config.R('EE', feedback['q']) interface.on_keypress(interface, None) try: print('\nSimulation starting...') print('Press left or right arrow to change target orientation angle.\n') count = 0 while 1: # get arm feedback feedback = interface.get_feedback() hand_xyz = robot_config.Tx('EE', feedback['q']) target = np.hstack([np.zeros(3), interface.target_angles]) u = ctrlr.generate( q=feedback['q'], dq=feedback['dq'], target=target, ) # apply the control signal, step the sim forward interface.send_forces( u, update_display=True if count % 20 == 0 else False) count += 1 finally: # stop and reset the simulation interface.disconnect() print('Simulation terminated...')

30.05814

76

0.670019

""" Running operational space control with the PyGame display. The arm will move the end-effector to a target orientation, which can be changed by pressing the left/right arrow keys. """ import numpy as np from os import environ environ['PYGAME_HIDE_SUPPORT_PROMPT'] = '1' import pygame from abr_control.arms import threejoint as arm # from abr_control.arms import twojoint as arm from abr_control.interfaces import PyGame from abr_control.utils import transformations from abr_control.controllers import OSC, Damping # initialize our robot config robot_config = arm.Config(use_cython=True) # create our arm simulation arm_sim = arm.ArmSim(robot_config) # damp the movements of the arm damping = Damping(robot_config, kv=10) # create operational space controller ctrlr = OSC(robot_config, kp=50, null_controllers=[damping], # control (gamma) out of [x, y, z, alpha, beta, gamma] ctrlr_dof = [False, False, False, False, False, True]) def on_keypress(self, key): if key == pygame.K_LEFT: self.theta += np.pi / 10 if key == pygame.K_RIGHT: self.theta -= np.pi / 10 print('theta: ', self.theta) # set the target orientation to be the initial EE # orientation rotated by theta R_theta = np.array([ [np.cos(interface.theta), -np.sin(interface.theta), 0], [np.sin(interface.theta), np.cos(interface.theta), 0], [0, 0, 1]]) R_target = np.dot(R_theta, R) self.target_angles = transformations.euler_from_matrix( R_target, axes='sxyz') # create our interface interface = PyGame(robot_config, arm_sim, dt=.001, on_keypress=on_keypress) interface.connect() interface.theta = -3 * np.pi / 4 feedback = interface.get_feedback() R = robot_config.R('EE', feedback['q']) interface.on_keypress(interface, None) try: print('\nSimulation starting...') print('Press left or right arrow to change target orientation angle.\n') count = 0 while 1: # get arm feedback feedback = interface.get_feedback() hand_xyz = robot_config.Tx('EE', feedback['q']) target = np.hstack([np.zeros(3), interface.target_angles]) u = ctrlr.generate( q=feedback['q'], dq=feedback['dq'], target=target, ) # apply the control signal, step the sim forward interface.send_forces( u, update_display=True if count % 20 == 0 else False) count += 1 finally: # stop and reset the simulation interface.disconnect() print('Simulation terminated...')

551

0

23

ec3070556999b4b313c77a9f09b9213babe68567

419

py

Python

test/test_utils/test_next_version/test_get_current_calver_tags.py

132nd-etcher/epab

5226d3a36580f8cc50cf5dcac426adb1350a2c9b

[ "MIT" ]

2

2018-12-13T06:49:10.000Z

2018-12-13T07:37:49.000Z

test/test_utils/test_next_version/test_get_current_calver_tags.py

etcher-be/epab

5226d3a36580f8cc50cf5dcac426adb1350a2c9b

[ "MIT" ]

109

2018-08-22T04:25:56.000Z

2019-10-17T05:10:21.000Z

test/test_utils/test_next_version/test_get_current_calver_tags.py

etcher-be/epab

5226d3a36580f8cc50cf5dcac426adb1350a2c9b

[ "MIT" ]

1

2018-02-25T05:53:18.000Z

# coding=utf-8 import pytest import epab.utils from epab.utils import _next_version as nv @pytest.mark.long

26.1875

56

0.72315

# coding=utf-8 import pytest import epab.utils from epab.utils import _next_version as nv @pytest.mark.long def test_get_current_calver_tags(repo: epab.utils.Repo): calver = '2018.1.1' assert len(nv._get_current_calver_tags(calver)) == 0 repo.tag(f'{calver}.1') assert len(nv._get_current_calver_tags(calver)) == 1 repo.tag(f'{calver}.2') assert len(nv._get_current_calver_tags(calver)) == 2

286

0

22

ff5902120c035db34bdcd8cb1814c2eb99ed8af1

3,843

py

Python

irods/rule.py

MaastrichtUniversity/python-irodsclient

e6e8b37205edeb94c57f3d30786b56cccd91d985

[ "Xnet", "X11" ]

null

irods/rule.py

MaastrichtUniversity/python-irodsclient

e6e8b37205edeb94c57f3d30786b56cccd91d985

[ "Xnet", "X11" ]

null

irods/rule.py

MaastrichtUniversity/python-irodsclient

e6e8b37205edeb94c57f3d30786b56cccd91d985

[ "Xnet", "X11" ]

null

from __future__ import absolute_import from irods.message import iRODSMessage, StringStringMap, RodsHostAddress, STR_PI, MsParam, MsParamArray, RuleExecutionRequest from irods.api_number import api_number from io import open as io_open from irods.message import Message, StringProperty

38.049505

148

0.577934

from __future__ import absolute_import from irods.message import iRODSMessage, StringStringMap, RodsHostAddress, STR_PI, MsParam, MsParamArray, RuleExecutionRequest from irods.api_number import api_number from io import open as io_open from irods.message import Message, StringProperty class RemoveRuleMessage(Message): #define RULE_EXEC_DEL_INP_PI "str ruleExecId[NAME_LEN];" _name = 'RULE_EXEC_DEL_INP_PI' ruleExecId = StringProperty() def __init__(self,id_): super(RemoveRuleMessage,self).__init__() self.ruleExecId = str(id_) class Rule(object): def __init__(self, session, rule_file=None, body='', params=None, output=''): self.session = session self.params = {} self.output = '' if rule_file: self.load(rule_file) else: self.body = '@external\n' + body # overwrite params and output if received arguments if params is not None: self.params = params if output != '': self.output = output def remove_by_id(self,*ids): with self.session.pool.get_connection() as conn: for id_ in ids: request = iRODSMessage("RODS_API_REQ", msg=RemoveRuleMessage(id_), int_info=api_number['RULE_EXEC_DEL_AN']) conn.send(request) response = conn.recv() if response.int_info != 0: raise RuntimeError("Error removing rule {id_}".format(**locals())) def load(self, rule_file, encoding = 'utf-8'): self.body = '@external\n' # parse rule file with io_open(rule_file, encoding = encoding) as f: for line in f: # parse input line if line.strip().lower().startswith('input'): input_header, input_line = line.split(None, 1) # sanity check if input_header.lower() != 'input': raise ValueError # parse *param0="value0",*param1="value1",... for pair in input_line.split(','): label, value = pair.split('=') self.params[label.strip()] = value.strip() # parse output line elif line.strip().lower().startswith('output'): output_header, output_line = line.split(None, 1) # sanity check if output_header.lower() != 'output': raise ValueError # use line as is self.output = output_line.strip() # parse rule else: self.body += line def execute(self, session_clean_up=False): # rule input param_array = [] for label, value in self.params.items(): inOutStruct = STR_PI(myStr=value) param_array.append(MsParam(label=label, type='STR_PI', inOutStruct=inOutStruct)) inpParamArray = MsParamArray(paramLen=len(param_array), oprType=0, MsParam_PI=param_array) # rule body addr = RodsHostAddress(hostAddr='', rodsZone='', port=0, dummyInt=0) condInput = StringStringMap({}) message_body = RuleExecutionRequest(myRule=self.body, addr=addr, condInput=condInput, outParamDesc=self.output, inpParamArray=inpParamArray) request = iRODSMessage("RODS_API_REQ", msg=message_body, int_info=api_number['EXEC_MY_RULE_AN']) with self.session.pool.get_connection() as conn: conn.send(request) response = conn.recv() out_param_array = response.get_main_message(MsParamArray) if session_clean_up: self.session.cleanup() return out_param_array

3,237

166

153

8a090a8ec15b5e802b163d342a26be6e4d9b7783

786

py

Python

guitab_knn/midi.py

bestvibes/guitab

b3491bab9bc7390eb3722ada44e0284731abf521

[ "MIT" ]

1

2022-03-02T09:36:28.000Z

guitab_container/webapp/webapp/midi.py

bestvibes/guitab

b3491bab9bc7390eb3722ada44e0284731abf521

[ "MIT" ]

3

2020-02-12T00:40:58.000Z

2021-06-10T20:15:45.000Z

guitab_container/webapp/webapp/midi.py

bestvibes/guitab

b3491bab9bc7390eb3722ada44e0284731abf521

[ "MIT" ]

2

2020-09-23T16:26:46.000Z

2022-02-16T23:57:39.000Z

# Array showing guitar string's relative pitches, in semi-tones, with "0" being low E # ["Low E", "A", "D", "G", "B", "High E"] strings = [40, 45, 50, 55, 60, 65];

30.230769

93

0.577608

# Array showing guitar string's relative pitches, in semi-tones, with "0" being low E # ["Low E", "A", "D", "G", "B", "High E"] strings = [40, 45, 50, 55, 60, 65]; def midi_to_label(midi): if (midi < strings[0]): raise ValueError("Note " + note + " is not playable on a guitar in standard tuning.") idealString = 0 for string, string_midi in enumerate(strings): if (midi < string_midi): break idealString = string label = [-1, -1, -1, -1, -1, -1] label[idealString] = midi - strings[idealString]; return label def label_to_midi(label): outp = [] for string, fret in enumerate(label): if (fret != -1): outp.append(fret + strings[string]) else: outp.append(-1) return outp

577

0

46

6521a65a212f3bc8e3643ac8cc5a646502debdc4

2,029

py

Python

kalliope/core/EventManager.py

Z3RO1/KalliopeZERO

4a9d4660e561f43387e8de4616f530ecf36cbbae

[ "MIT" ]

1

2017-10-09T18:02:32.000Z

kalliope/core/EventManager.py

ngoales/kalliope

b1e58f2d1e949f572d48026603159992c0ce20ca

[ "MIT" ]

null

kalliope/core/EventManager.py

ngoales/kalliope

b1e58f2d1e949f572d48026603159992c0ce20ca

[ "MIT" ]

1

2021-11-21T19:08:15.000Z

from apscheduler.schedulers.background import BackgroundScheduler from apscheduler.triggers.cron import CronTrigger from kalliope.core.ConfigurationManager import BrainLoader from kalliope.core.SynapseLauncher import SynapseLauncher from kalliope.core import Utils from kalliope.core.Models import Event

40.58

110

0.576639

from apscheduler.schedulers.background import BackgroundScheduler from apscheduler.triggers.cron import CronTrigger from kalliope.core.ConfigurationManager import BrainLoader from kalliope.core.SynapseLauncher import SynapseLauncher from kalliope.core import Utils from kalliope.core.Models import Event class EventManager(object): def __init__(self, synapses): Utils.print_info('Starting event manager') self.scheduler = BackgroundScheduler() self.synapses = synapses self.load_events() self.scheduler.start() def load_events(self): """ For each received synapse that have an event as signal, we add a new job scheduled to launch the synapse :return: """ for synapse in self.synapses: for signal in synapse.signals: # if the signal is an event we add it to the task list if type(signal) == Event: my_cron = CronTrigger(year=signal.year, month=signal.month, day=signal.day, week=signal.week, day_of_week=signal.day_of_week, hour=signal.hour, minute=signal.minute, second=signal.second) Utils.print_info("Add synapse name \"%s\" to the scheduler: %s" % (synapse.name, my_cron)) self.scheduler.add_job(self.run_synapse_by_name, my_cron, args=[synapse.name]) @staticmethod def run_synapse_by_name(synapse_name): """ This method will run the synapse """ Utils.print_info("Event triggered, running synapse: %s" % synapse_name) # get a brain brain_loader = BrainLoader() brain = brain_loader.brain SynapseLauncher.start_synapse_by_name(synapse_name, brain=brain)

197

1,503

23

9a8f0064512347b712e42bdfed88fe249599ba83

6,616

py

Python

Lib/turtledemo/nim.py

sireliah/polish-python

605df4944c2d3bc25f8bf6964b274c0a0d297cc3

[ "PSF-2.0" ]

1

2018-06-21T18:21:24.000Z

Lib/turtledemo/nim.py

sireliah/polish-python

605df4944c2d3bc25f8bf6964b274c0a0d297cc3

[ "PSF-2.0" ]

null

Lib/turtledemo/nim.py

sireliah/polish-python

605df4944c2d3bc25f8bf6964b274c0a0d297cc3

[ "PSF-2.0" ]

null

""" turtle-example-suite: tdemo_nim.py Play nim against the computer. The player who takes the last stick jest the winner. Implements the model-view-controller design pattern. """ zaimportuj turtle zaimportuj random zaimportuj time SCREENWIDTH = 640 SCREENHEIGHT = 480 MINSTICKS = 7 MAXSTICKS = 31 HUNIT = SCREENHEIGHT // 12 WUNIT = SCREENWIDTH // ((MAXSTICKS // 5) * 11 + (MAXSTICKS % 5) * 2) SCOLOR = (63, 63, 31) HCOLOR = (255, 204, 204) COLOR = (204, 204, 255) dla z w range(3): s = state[z] ^ xored jeżeli s <= state[z]: move = (z, s) zwróć move rand = random.randint(m > 1, state[z]-1) zwróć z, rand klasa NimModel(object): albo_inaczej self.player == 0: self.player = 1 row, col = computerzug(self.sticks) self.move(row, col) self.player = 0 def game_over(self): zwróć self.sticks == [0, 0, 0] def notify_move(self, row, col): jeżeli self.sticks[row] <= col: zwróć self.move(row, col) klasa Stick(turtle.Turtle): self.game.controller.notify_move(self.row, self.col) klasa NimView(object): self.display("... a moment please ...") self.screen.tracer(Prawda) def display(self, msg1, msg2=Nic): self.screen.tracer(Nieprawda) self.writer.clear() jeżeli msg2 jest nie Nic: self.writer.goto(0, - SCREENHEIGHT // 2 + 48) self.writer.pencolor("red") self.writer.write(msg2, align="center", font=("Courier",18,"bold")) self.writer.goto(0, - SCREENHEIGHT // 2 + 20) self.writer.pencolor("black") self.writer.write(msg1, align="center", font=("Courier",14,"bold")) self.screen.tracer(Prawda) def setup(self): self.screen.tracer(Nieprawda) dla row w range(3): dla col w range(self.model.sticks[row]): self.sticks[(row, col)].color(SCOLOR) dla row w range(3): dla col w range(self.model.sticks[row], MAXSTICKS): self.sticks[(row, col)].color("white") self.display("Your turn! Click leftmost stick to remove.") self.screen.tracer(Prawda) def notify_move(self, row, col, maxspalte, player): jeżeli player == 0: farbe = HCOLOR dla s w range(col, maxspalte): self.sticks[(row, s)].color(farbe) inaczej: self.display(" ... thinking ... ") time.sleep(0.5) self.display(" ... thinking ... aaah ...") farbe = COLOR dla s w range(maxspalte-1, col-1, -1): time.sleep(0.2) self.sticks[(row, s)].color(farbe) self.display("Your turn! Click leftmost stick to remove.") def notify_over(self): jeżeli self.game.model.winner == 0: msg2 = "Congrats. You're the winner!!!" inaczej: msg2 = "Sorry, the computer jest the winner." self.display("To play again press space bar. To leave press ESC.", msg2) def clear(self): jeżeli self.game.state == Nim.OVER: self.screen.clear() klasa NimController(object): self.game.screen.onkey(self.game.model.setup, "space") self.game.screen.onkey(self.game.view.clear, "Escape") self.game.view.display("Press space bar to start game") self.game.screen.listen() def notify_move(self, row, col): jeżeli self.BUSY: zwróć self.BUSY = Prawda self.game.model.notify_move(row, col) self.BUSY = Nieprawda klasa Nim(object): CREATED = 0 RUNNING = 1 OVER = 2 def main(): mainscreen = turtle.Screen() mainscreen.mode("standard") mainscreen.setup(SCREENWIDTH, SCREENHEIGHT) nim = Nim(mainscreen) zwróć "EVENTLOOP" jeżeli __name__ == "__main__": main() turtle.mainloop()

29.145374

83

0.57104

""" turtle-example-suite: tdemo_nim.py Play nim against the computer. The player who takes the last stick jest the winner. Implements the model-view-controller design pattern. """ zaimportuj turtle zaimportuj random zaimportuj time SCREENWIDTH = 640 SCREENHEIGHT = 480 MINSTICKS = 7 MAXSTICKS = 31 HUNIT = SCREENHEIGHT // 12 WUNIT = SCREENWIDTH // ((MAXSTICKS // 5) * 11 + (MAXSTICKS % 5) * 2) SCOLOR = (63, 63, 31) HCOLOR = (255, 204, 204) COLOR = (204, 204, 255) def randomrow(): zwróć random.randint(MINSTICKS, MAXSTICKS) def computerzug(state): xored = state[0] ^ state[1] ^ state[2] jeżeli xored == 0: zwróć randommove(state) dla z w range(3): s = state[z] ^ xored jeżeli s <= state[z]: move = (z, s) zwróć move def randommove(state): m = max(state) dopóki Prawda: z = random.randint(0,2) jeżeli state[z] > (m > 1): przerwij rand = random.randint(m > 1, state[z]-1) zwróć z, rand klasa NimModel(object): def __init__(self, game): self.game = game def setup(self): jeżeli self.game.state nie w [Nim.CREATED, Nim.OVER]: zwróć self.sticks = [randomrow(), randomrow(), randomrow()] self.player = 0 self.winner = Nic self.game.view.setup() self.game.state = Nim.RUNNING def move(self, row, col): maxspalte = self.sticks[row] self.sticks[row] = col self.game.view.notify_move(row, col, maxspalte, self.player) jeżeli self.game_over(): self.game.state = Nim.OVER self.winner = self.player self.game.view.notify_over() albo_inaczej self.player == 0: self.player = 1 row, col = computerzug(self.sticks) self.move(row, col) self.player = 0 def game_over(self): zwróć self.sticks == [0, 0, 0] def notify_move(self, row, col): jeżeli self.sticks[row] <= col: zwróć self.move(row, col) klasa Stick(turtle.Turtle): def __init__(self, row, col, game): turtle.Turtle.__init__(self, visible=Nieprawda) self.row = row self.col = col self.game = game x, y = self.coords(row, col) self.shape("square") self.shapesize(HUNIT/10.0, WUNIT/20.0) self.speed(0) self.pu() self.goto(x,y) self.color("white") self.showturtle() def coords(self, row, col): packet, remainder = divmod(col, 5) x = (3 + 11 * packet + 2 * remainder) * WUNIT y = (2 + 3 * row) * HUNIT zwróć x - SCREENWIDTH // 2 + WUNIT // 2, SCREENHEIGHT // 2 - y - HUNIT // 2 def makemove(self, x, y): jeżeli self.game.state != Nim.RUNNING: zwróć self.game.controller.notify_move(self.row, self.col) klasa NimView(object): def __init__(self, game): self.game = game self.screen = game.screen self.mousuń = game.model self.screen.colormode(255) self.screen.tracer(Nieprawda) self.screen.bgcolor((240, 240, 255)) self.writer = turtle.Turtle(visible=Nieprawda) self.writer.pu() self.writer.speed(0) self.sticks = {} dla row w range(3): dla col w range(MAXSTICKS): self.sticks[(row, col)] = Stick(row, col, game) self.display("... a moment please ...") self.screen.tracer(Prawda) def display(self, msg1, msg2=Nic): self.screen.tracer(Nieprawda) self.writer.clear() jeżeli msg2 jest nie Nic: self.writer.goto(0, - SCREENHEIGHT // 2 + 48) self.writer.pencolor("red") self.writer.write(msg2, align="center", font=("Courier",18,"bold")) self.writer.goto(0, - SCREENHEIGHT // 2 + 20) self.writer.pencolor("black") self.writer.write(msg1, align="center", font=("Courier",14,"bold")) self.screen.tracer(Prawda) def setup(self): self.screen.tracer(Nieprawda) dla row w range(3): dla col w range(self.model.sticks[row]): self.sticks[(row, col)].color(SCOLOR) dla row w range(3): dla col w range(self.model.sticks[row], MAXSTICKS): self.sticks[(row, col)].color("white") self.display("Your turn! Click leftmost stick to remove.") self.screen.tracer(Prawda) def notify_move(self, row, col, maxspalte, player): jeżeli player == 0: farbe = HCOLOR dla s w range(col, maxspalte): self.sticks[(row, s)].color(farbe) inaczej: self.display(" ... thinking ... ") time.sleep(0.5) self.display(" ... thinking ... aaah ...") farbe = COLOR dla s w range(maxspalte-1, col-1, -1): time.sleep(0.2) self.sticks[(row, s)].color(farbe) self.display("Your turn! Click leftmost stick to remove.") def notify_over(self): jeżeli self.game.model.winner == 0: msg2 = "Congrats. You're the winner!!!" inaczej: msg2 = "Sorry, the computer jest the winner." self.display("To play again press space bar. To leave press ESC.", msg2) def clear(self): jeżeli self.game.state == Nim.OVER: self.screen.clear() klasa NimController(object): def __init__(self, game): self.game = game self.sticks = game.view.sticks self.BUSY = Nieprawda dla stick w self.sticks.values(): stick.onclick(stick.makemove) self.game.screen.onkey(self.game.model.setup, "space") self.game.screen.onkey(self.game.view.clear, "Escape") self.game.view.display("Press space bar to start game") self.game.screen.listen() def notify_move(self, row, col): jeżeli self.BUSY: zwróć self.BUSY = Prawda self.game.model.notify_move(row, col) self.BUSY = Nieprawda klasa Nim(object): CREATED = 0 RUNNING = 1 OVER = 2 def __init__(self, screen): self.state = Nim.CREATED self.screen = screen self.mousuń = NimModel(self) self.view = NimView(self) self.controller = NimController(self) def main(): mainscreen = turtle.Screen() mainscreen.mode("standard") mainscreen.setup(SCREENWIDTH, SCREENHEIGHT) nim = Nim(mainscreen) zwróć "EVENTLOOP" jeżeli __name__ == "__main__": main() turtle.mainloop()

2,372

0

308

528cf1b59e68183f561c087b20046483ff243394

918

py

Python

port_scanner.py

nemzyxt/port-scanner

52378c2d5e5c6ff7f7b74018a27a6dee1f566c54

[ "MIT" ]

null

port_scanner.py

nemzyxt/port-scanner

52378c2d5e5c6ff7f7b74018a27a6dee1f566c54

[ "MIT" ]

null

port_scanner.py

nemzyxt/port-scanner

52378c2d5e5c6ff7f7b74018a27a6dee1f566c54

[ "MIT" ]

null

#Author : Nemuel Wainaina import socket from colorama import init, Fore #some color, haha init() GREEN = Fore.GREEN BLUE = Fore.BLUE RED = Fore.RED GRAY = Fore.LIGHTBLACK_EX RESET = Fore.RESET def is_port_open(target, port): ''' This function simply attempts to create a connection to the target machine on the specified port and based on whether or not the connection is successful, prints to the user whether or not the port is open ''' try: s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect((target, port)) print(f"{GREEN}[+] Port {port} is Open {RESET}") return True except: #Comment out the line in order to exclude the results for closed ports print(f"{GRAY}[-] Port {port} is Closed {RESET}") return False finally: s.close()

24.810811

79

0.611111

#Author : Nemuel Wainaina import socket from colorama import init, Fore #some color, haha init() GREEN = Fore.GREEN BLUE = Fore.BLUE RED = Fore.RED GRAY = Fore.LIGHTBLACK_EX RESET = Fore.RESET def is_port_open(target, port): ''' This function simply attempts to create a connection to the target machine on the specified port and based on whether or not the connection is successful, prints to the user whether or not the port is open ''' try: s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect((target, port)) print(f"{GREEN}[+] Port {port} is Open {RESET}") return True except: #Comment out the line in order to exclude the results for closed ports print(f"{GRAY}[-] Port {port} is Closed {RESET}") return False finally: s.close()

0

a83c3aaee2d1d702fdd7e9f3c5ea7dd431a4b156

2,290

py

Python

generate_split.py

ruoyunz/caltech-ee148-spring2020-hw02

671b08cd914134f06db2c1eeec3fa4d4d3e0cd5f

[ "MIT" ]

null

generate_split.py

ruoyunz/caltech-ee148-spring2020-hw02

671b08cd914134f06db2c1eeec3fa4d4d3e0cd5f

[ "MIT" ]

null

generate_split.py

ruoyunz/caltech-ee148-spring2020-hw02

671b08cd914134f06db2c1eeec3fa4d4d3e0cd5f

[ "MIT" ]

null

import numpy as np import os import json import cv2 import sys np.random.seed(2020) # to ensure you always get the same train/test split data_path = '../data/RedLights2011_Medium' gts_path = '../data/hw02_annotations' split_path = '../data/hw02_splits' os.makedirs(split_path, exist_ok=True) # create directory if needed split_test = True # set to True and run when annotations are available train_frac = 0.85 # get sorted list of files: file_names = sorted(os.listdir(data_path)) # remove any non-JPEG files: file_names = [f for f in file_names if '.jpg' in f] # split file names into train and test file_names_train = [] file_names_test = [] np.random.shuffle(file_names) file_names_train = file_names[0:(int(train_frac * len(file_names)))] file_names_test = file_names[(int(train_frac * len(file_names))):] assert (len(file_names_train) + len(file_names_test)) == len(file_names) assert len(np.intersect1d(file_names_train,file_names_test)) == 0 np.save(os.path.join(split_path,'file_names_train.npy'),file_names_train) np.save(os.path.join(split_path,'file_names_test.npy'),file_names_test) # Function for viewing annotations one by one if needed if split_test: with open(os.path.join(gts_path, 'formatted_annotations_students.json'),'r') as f: gts = json.load(f) # Use file_names_train and file_names_test to apply the split to the # annotations gts_train = {} gts_test = {} for i in range(len(file_names_train)): gts_train[file_names_train[i]] = gts[file_names_train[i]] for i in range(len(file_names_test)): gts_test[file_names_test[i]] = gts[file_names_test[i]] with open(os.path.join(gts_path, 'annotations_train.json'),'w') as f: json.dump(gts_train,f) with open(os.path.join(gts_path, 'annotations_test.json'),'w') as f: json.dump(gts_test,f)

30.945946

86

0.676419

import numpy as np import os import json import cv2 import sys np.random.seed(2020) # to ensure you always get the same train/test split data_path = '../data/RedLights2011_Medium' gts_path = '../data/hw02_annotations' split_path = '../data/hw02_splits' os.makedirs(split_path, exist_ok=True) # create directory if needed split_test = True # set to True and run when annotations are available train_frac = 0.85 # get sorted list of files: file_names = sorted(os.listdir(data_path)) # remove any non-JPEG files: file_names = [f for f in file_names if '.jpg' in f] # split file names into train and test file_names_train = [] file_names_test = [] np.random.shuffle(file_names) file_names_train = file_names[0:(int(train_frac * len(file_names)))] file_names_test = file_names[(int(train_frac * len(file_names))):] assert (len(file_names_train) + len(file_names_test)) == len(file_names) assert len(np.intersect1d(file_names_train,file_names_test)) == 0 np.save(os.path.join(split_path,'file_names_train.npy'),file_names_train) np.save(os.path.join(split_path,'file_names_test.npy'),file_names_test) # Function for viewing annotations one by one if needed def view_annotation(fs): for i in range(len(fs)): img = cv2.imread(os.path.join(data_path,fs[i]),cv2.IMREAD_COLOR) preds = gts_stud[fs[i]] for p in preds2: (r, c, r2, c2) = p cv2.rectangle(img, (int(c), int(r)), (int(c2), int(r2)), (0, 255, 0), 1) cv2.imshow('image',img) ch = cv2.waitKey(0) if ch == 27: exit() if split_test: with open(os.path.join(gts_path, 'formatted_annotations_students.json'),'r') as f: gts = json.load(f) # Use file_names_train and file_names_test to apply the split to the # annotations gts_train = {} gts_test = {} for i in range(len(file_names_train)): gts_train[file_names_train[i]] = gts[file_names_train[i]] for i in range(len(file_names_test)): gts_test[file_names_test[i]] = gts[file_names_test[i]] with open(os.path.join(gts_path, 'annotations_train.json'),'w') as f: json.dump(gts_train,f) with open(os.path.join(gts_path, 'annotations_test.json'),'w') as f: json.dump(gts_test,f)

403

0

22

d56872c67420ffe628e90c16e0f0ea52e9d094f4

1,738

py

Python

src/utils/pythonSrc/watchFaceParser/models/elements/common/clockHandElement.py

chm-dev/amazfitGTSwatchfaceBundle

4cb04be5215de16628418e9b38152a35d5372d3e

[ "MIT" ]

49

2019-12-18T11:24:56.000Z

2022-03-28T09:56:27.000Z

src/utils/pythonSrc/watchFaceParser/models/elements/common/clockHandElement.py

chm-dev/amazfitGTSwatchfaceBundle

4cb04be5215de16628418e9b38152a35d5372d3e

[ "MIT" ]

6

2020-01-08T21:31:15.000Z

2022-03-25T19:13:26.000Z

src/utils/pythonSrc/watchFaceParser/models/elements/common/clockHandElement.py

chm-dev/amazfitGTSwatchfaceBundle

4cb04be5215de16628418e9b38152a35d5372d3e

[ "MIT" ]

6

2019-12-27T17:30:24.000Z

2021-09-30T08:11:01.000Z

import logging from watchFaceParser.models.elements.basic.compositeElement import CompositeElement

31.035714

118

0.664557

import logging from watchFaceParser.models.elements.basic.compositeElement import CompositeElement class ClockHandElement(CompositeElement): def __init__(self, parameter, parent, name = None): self._onlyBorder = False self._color = None self._center = None self._shape = [] self._centerImage = None super(ClockHandElement, self).__init__(parameters = None, parameter = parameter, parent = parent, name = name) def getOnlyBorder(self): return self._onlyBorder def getColor(self): return self._color def getCenter(self): return self._center def getShape(self): return self._shape def getCenterImage(self): return self._centerImage def draw4(self, drawer, resources, value, total): assert(type(resources) == list) if self.getCenterImage(): angle = 360 - int(value * 360. / total) self.getCenterImage().draw2(drawer, resources, angle, self.getCenter()) def createChildForParameter(self, parameter): parameterId = parameter.getId() if parameterId == 5: from watchFaceParser.models.elements.common.imageElement import ImageElement self._centerImage = ImageElement(parameter = parameter, parent = self, name = 'Image') return self._centerImage elif parameterId == 3: from watchFaceParser.models.elements.common.coordinatesElement import CoordinatesElement self._center = CoordinatesElement(parameter = parameter, parent = self, name = 'CenterOffset') return self._center else: return super(ClockHandElement, self).createChildForParameter(parameter)

1,371

20

238

1431c36367740490b243f3436653ce18816364f6

2,356

py

Python

src/ygopro/urldecode.py

o7878x/pytoolk

eb5edfbd5a8907b9705c4042013bf7c828e2fdf3

[ "MIT" ]

null

src/ygopro/urldecode.py

o7878x/pytoolk

eb5edfbd5a8907b9705c4042013bf7c828e2fdf3

[ "MIT" ]

null

src/ygopro/urldecode.py

o7878x/pytoolk

eb5edfbd5a8907b9705c4042013bf7c828e2fdf3

[ "MIT" ]

null

import logging import time import typing from urllib.parse import urlparse, parse_qs import fire YGO_SCHEME = 'ygo' YGO_NETLOC = 'deck' DEFAULT_HEADER = '#created by ...\n' CARD_SEP_SYM = '_' CARD_MULTI_SYM = '*' DEFAULT_SYM = '#' NO_SYM = '!' MAIN_HEADER = 'main\n' EXTRA_HEADER = 'extra\n' SIDE_HEADER = 'side\n' DEFAULT_YDK_NAME: str = "default" + "_" + str(int(time.time())) if __name__ == '__main__': fire.Fire(save_file)

23.79798

91

0.64983

import logging import time import typing from urllib.parse import urlparse, parse_qs import fire YGO_SCHEME = 'ygo' YGO_NETLOC = 'deck' DEFAULT_HEADER = '#created by ...\n' CARD_SEP_SYM = '_' CARD_MULTI_SYM = '*' DEFAULT_SYM = '#' NO_SYM = '!' MAIN_HEADER = 'main\n' EXTRA_HEADER = 'extra\n' SIDE_HEADER = 'side\n' DEFAULT_YDK_NAME: str = "default" + "_" + str(int(time.time())) def decode_url(url: str) -> str: res = urlparse(url) if not res: logging.info('can not parse url') return '' if res.scheme != YGO_SCHEME or res.netloc != YGO_NETLOC: logging.info('it is not a YGO link') return '' qs = parse_qs(res.query) if not qs: logging.info('can not parse query') return '' return get_deck_str(qs) def get_code_arr(part_str: str) -> typing.List: res = [] if not part_str: return res parts = str.split(part_str, CARD_SEP_SYM) for counted_part in parts: code_count_pair = str.split(counted_part, CARD_MULTI_SYM) pair_len = len(code_count_pair) if pair_len == 1: res.append(counted_part) elif pair_len == 2: res += [code_count_pair[0]] * int(code_count_pair[1]) return res def get_target_field_str(target_dict: typing.Dict, field_name: str, index: int = 0) -> str: res = "" try: res = target_dict[field_name][index] except KeyError: logging.info("key error") finally: return res def get_deck_str(query_dict: typing.Dict) -> str: main_deck_arr = get_code_arr(get_target_field_str(query_dict, 'main')) print(main_deck_arr) extra_deck_arr = get_code_arr(get_target_field_str(query_dict, 'extra')) side_deck_arr = get_code_arr(get_target_field_str(query_dict, 'side')) target_str = DEFAULT_HEADER target_str += (DEFAULT_SYM + MAIN_HEADER + '\n'.join(main_deck_arr)) target_str += '\n' target_str += (DEFAULT_SYM + EXTRA_HEADER + '\n'.join(extra_deck_arr)) target_str += '\n' target_str += (NO_SYM + SIDE_HEADER + '\n'.join(side_deck_arr)) return target_str def save_file(origin_url: str, file_name: str = DEFAULT_YDK_NAME): res_str = decode_url(origin_url) with open('.'.join([file_name, 'ydk']), 'w') as f: f.write(res_str) if __name__ == '__main__': fire.Fire(save_file)

1,797

0

115

7b1edf412d6711b1edca18fb5738889669261b6e

21,465

py

Python

tests/test_page.py

crempp/mdweb

ce3c26e4b7b2dfba0ac793534a06581a8c214570

[ "MIT" ]

12

2015-07-31T07:53:57.000Z

2021-08-09T18:05:55.000Z

tests/test_page.py

crempp/mdweb

ce3c26e4b7b2dfba0ac793534a06581a8c214570

[ "MIT" ]

59

2015-07-31T07:44:16.000Z

2020-08-20T19:54:22.000Z

tests/test_page.py

crempp/mdweb

ce3c26e4b7b2dfba0ac793534a06581a8c214570

[ "MIT" ]

1

2016-02-22T22:57:17.000Z

# -*- coding: utf-8 -*- """Tests for the MDWeb Navigation parser. Tests to write * Handle symlinks * File already open * Non supported extension (.xls) * Permissions Maybe test? * atime, mtime * large file """ import datetime from pyfakefs import fake_filesystem_unittest from unittest import skip try: # Python >= 3.3 from unittest import mock except ImportError: # Python < 3.3 import mock from mdweb.Page import PageMetaInf, Page, load_page from mdweb.Exceptions import ( PageMetaInfFieldException, PageParseException, ContentException, ) class TestPageMeta(fake_filesystem_unittest.TestCase): """PageMetaInf object tests.""" def setUp(self): """Create fake filesystem.""" self.setUpPyfakefs() def test_parse_empty_string(self): """Empty string should parse successfully.""" file_string = u"" meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertIsNone(meta_inf.date) self.assertIsNone(meta_inf.description) self.assertIsNone(meta_inf.nav_name) self.assertEqual(meta_inf.order, 0) self.assertIsNone(meta_inf.template) self.assertIsNone(meta_inf.title) def test_parse_some_fields(self): """A few defined fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Date: February 1st, 2016 """ meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 0) self.assertIsNone(meta_inf.template) self.assertEqual(meta_inf.title, u'MDWeb') def test_parse_all_fields(self): """All available fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date: February 1st, 2016 Order: 1 Template: page_home.html Nav Name: Home Page Sitemap Changefreq: Monthly Sitemap Priority: 0.5 Teaser: This is a teaser paragraph that will be availble to pages Teaser Image: /contentassets/home/00041_thumb.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Chad Rempp') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') self.assertEqual(meta_inf.nav_name, u'Home Page') self.assertEqual(meta_inf.sitemap_changefreq, u'Monthly') self.assertEqual(meta_inf.sitemap_priority, u'0.5') self.assertEqual(meta_inf.teaser, u'This is a teaser paragraph that will be availble to pages') self.assertEqual(meta_inf.teaser_image, u'/contentassets/home/00041_thumb.jpg') def test_metainf_spacing(self): """Spacing should not matter in parsing.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date : February 1st, 2016 Order: 1 Template: page_home.html """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Chad Rempp') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') def test_comments(self): """Comments should be skipped during parsing.""" file_string = u"""# This is a comment Title: MDWeb Description: The minimalistic markdown NaCMS #Author: Chad Rempp #Date: February 1st, 2016 Order: 1 Template: page_home.html # # Nothing to see here """ meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertIsNone(meta_inf.date) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') def test_unicode(self): """Parser should handle unicode.""" file_string = u"""Title: советских Description: ᚠᛇᚻ᛫ᛒᛦᚦ᛫ᚠᚱᚩᚠᚢᚱ᛫ᚠᛁᚱᚪ᛫ᚷᛖᚻᚹᛦᛚᚳᚢᛗ Author: Οδυσσέα Ελύτη Date: February 1st, 2016 Order: 1 Template: ღმერთსი.html """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Οδυσσέα Ελύτη') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'ᚠᛇᚻ᛫ᛒᛦᚦ᛫ᚠᚱᚩᚠᚢᚱ᛫ᚠᛁᚱᚪ᛫ᚷᛖᚻᚹᛦᛚᚳᚢᛗ') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'ღმერთსი.html') self.assertEqual(meta_inf.title, u'советских') def test_parse_multiline_field(self): """Multiline fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date: February 1st, 2016 Order: 1 Template: page_home.html Nav Name: Home Page Sitemap Changefreq: Monthly Sitemap Priority: 0.5 Teaser: This is a teaser paragraph that will be available to pages and the teaser may span multiple lines indented with whitespace even if the line looks like a metainf field Not A Field: This won't get parsed as a field Teaser Image: /contentassets/home/00041_thumb.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.teaser, u'This is a teaser paragraph that will be available to pages and the teaser may span multiple lines indented with whitespace even if the line looks like a metainf field Not A Field: This won\'t get parsed as a field') def test_parse_custom_field(self): """Multiline fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Summary Image: blah.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.custom_summary_image, u'blah.jpg') @skip def test_unpublished_page(self): """Unpublished pages should have the correct attr value.""" self.assertEqual(1, 2) class TestPage(fake_filesystem_unittest.TestCase): """Page object tests.""" def setUp(self): """Create fake filesystem.""" self.setUpPyfakefs() def test_page_instantiation(self): """A page should be instantiated with appropriate attributes.""" file_string = u"This is a page" self.fs.create_file('/my/content/about/history.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/about/history.md')) self.assertEqual(page.page_path, '/my/content/about/history.md') self.assertEqual(page.url_path, 'about/history') self.fs.create_file('/my/content/super/deep/url/path/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/super/deep/url/path/index.md')) self.assertEqual(page.page_path, '/my/content/super/deep/url/path/index.md') self.assertEqual(page.url_path, 'super/deep/url/path') def test_unparsable_path(self): """An unparsable page path should raise PageParseException.""" file_string = u"" self.fs.create_file('/my/content/index', contents=file_string) # Not an MD file self.assertRaises(PageParseException, load_page, '/my/content', '/my/content/index') @mock.patch('mdweb.Page.PageMetaInf') def test_repr(self, mock_page_meta_inf): """A Page object should return the proper repr.""" file_string = u"" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) self.assertEqual(str(page), '/my/content/index.md') @mock.patch('mdweb.Page.PageMetaInf') def test_parse_empty_file(self, mock_page_meta_inf): """An empty file should parse properly.""" file_string = u"" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with('') self.assertEqual(page.markdown_str, '') self.assertEqual(page.page_html, '') def test_no_file(self): """If the path has no file a ContentException should be raised.""" self.assertRaises(ContentException, load_page, '/my/content', '/my/content/index.md') @mock.patch('mdweb.Page.PageMetaInf') def test_no_meta_inf(self, mock_page_meta_inf): """A page with no meta information should parse.""" # pylint: disable=C0301 # pylint: disable=E501 file_string = u"""Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.""" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with('') self.assertEqual(page.markdown_str, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_meta_inf(self, mock_page_meta_inf): """A page with meta info should parse the content and meta inf.""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_slash_star_slash(self, mock_page_meta_inf): """A page with /*/ in the content should parse corectly. Regression test for https://github.com/crempp/mdweb/issues/47""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. This is a link that blows up the parser [asdf](https://web.archive.org/web/*/http://site.com) The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. This is a link that blows up the parser [asdf](https://web.archive.org/web/*/http://site.com) The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. This is a link that blows up the parser <a href="https://web.archive.org/web/*/http://site.com">asdf</a> The quick brown fox jumped over the lazy dog's back.''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_second_metainf(self, mock_page_meta_inf): """A page with a second metainf should only parse the first""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. Here is another metainf block ```metainf Title: Fake Block ``` The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. Here is another metainf block ```metainf Title: Fake Block ``` The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. Here is another metainf block <code>metainf Title: Fake Block</code> The quick brown fox jumped over the lazy dog's back.''') @mock.patch('mdweb.Page.PageMetaInf') def test_markdown_formatting(self, mock_page_meta_inf): """Markdown should parse correctly. We won't test this extensively as we should trust the markdown libraries to test themselves. """ file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Examples taken from https://daringfireball.net/projects/markdown/basics A First Level Header ==================== A Second Level Header --------------------- Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back. ### Header 3 > This is a blockquote. > > This is the second paragraph in the blockquote. > > ## This is an H2 in a blockquote --------------------------------------- Some of these words *are emphasized*. Some of these words _are emphasized also_. Use two asterisks for **strong emphasis**. Or, if you prefer, __use two underscores instead__. --------------------------------------- * Candy. * Gum. * Booze. --------------------------------------- 1. Red 2. Green 3. Blue --------------------------------------- * A list item. With multiple paragraphs. * Another item in the list. --------------------------------------- This is an [example link](http://example.com/). This is an [example link](http://example.com/ "With a Title"). --------------------------------------- I get 10 times more traffic from [Google][1] than from [Yahoo][2] or [MSN][3]. [1]: http://google.com/ "Google" [2]: http://search.yahoo.com/ "Yahoo Search" [3]: http://search.msn.com/ "MSN Search" I start my morning with a cup of coffee and [The New York Times][NY Times]. [ny times]: http://www.nytimes.com/ --------------------------------------- ![alt text](/path/to/img.jpg "Title") ![alt text][id] [id]: /path/to/img.jpg "Title" --------------------------------------- I strongly recommend against using any `<blink>` tags. I wish SmartyPants used named entities like `—` instead of decimal-encoded entites like `—`. If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes: <blockquote> For example. </blockquote> ---------------------------------------''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Examples taken from https://daringfireball.net/projects/markdown/basics A First Level Header ==================== A Second Level Header --------------------- Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back. ### Header 3 > This is a blockquote. > > This is the second paragraph in the blockquote. > > ## This is an H2 in a blockquote --------------------------------------- Some of these words *are emphasized*. Some of these words _are emphasized also_. Use two asterisks for **strong emphasis**. Or, if you prefer, __use two underscores instead__. --------------------------------------- * Candy. * Gum. * Booze. --------------------------------------- 1. Red 2. Green 3. Blue --------------------------------------- * A list item. With multiple paragraphs. * Another item in the list. --------------------------------------- This is an [example link](http://example.com/). This is an [example link](http://example.com/ "With a Title"). --------------------------------------- I get 10 times more traffic from [Google][1] than from [Yahoo][2] or [MSN][3]. [1]: http://google.com/ "Google" [2]: http://search.yahoo.com/ "Yahoo Search" [3]: http://search.msn.com/ "MSN Search" I start my morning with a cup of coffee and [The New York Times][NY Times]. [ny times]: http://www.nytimes.com/ --------------------------------------- ![alt text](/path/to/img.jpg "Title") ![alt text][id] [id]: /path/to/img.jpg "Title" --------------------------------------- I strongly recommend against using any `<blink>` tags. I wish SmartyPants used named entities like `—` instead of decimal-encoded entites like `—`. If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes: <blockquote> For example. </blockquote> ---------------------------------------''') # pylint: disable=C0301 # pylint: disable=E501 self.assertEqual(page.page_html, '''Examples taken from https://daringfireball.net/projects/markdown/basics <h1>A First Level Header</h1> <h2>A Second Level Header</h2> Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back. <h3>Header 3</h3> <blockquote> This is a blockquote. This is the second paragraph in the blockquote. <h2>This is an H2 in a blockquote</h2> </blockquote> <hr /> Some of these words are emphasized. Some of these words are emphasized also. Use two asterisks for strong emphasis. Or, if you prefer, use two underscores instead. <hr /> <ul> <li>Candy.</li> <li>Gum.</li> <li>Booze.</li> </ul> <hr /> <ol> <li>Red</li> <li>Green</li> <li>Blue</li> </ol> <hr /> <ul> <li> A list item. With multiple paragraphs. </li> <li> Another item in the list. </li> </ul> <hr /> This is an <a href="http://example.com/">example link</a>. This is an <a href="http://example.com/" title="With a Title">example link</a>. <hr /> I get 10 times more traffic from <a href="http://google.com/" title="Google">Google</a> than from <a href="http://search.yahoo.com/" title="Yahoo Search">Yahoo</a> or <a href="http://search.msn.com/" title="MSN Search">MSN</a>. I start my morning with a cup of coffee and <a href="http://www.nytimes.com/">The New York Times</a>. <hr /> <img alt="alt text" src="/path/to/img.jpg" title="Title" /> <img alt="alt text" src="/path/to/img.jpg" title="Title" /> <hr /> I strongly recommend against using any <code><blink></code> tags. I wish SmartyPants used named entities like <code>&mdash;</code> instead of decimal-encoded entites like <code>&#8212;</code>. If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes: <pre><code><blockquote> For example. </blockquote> </code></pre> <hr />''')

29.283765

259

0.646261

# -*- coding: utf-8 -*- """Tests for the MDWeb Navigation parser. Tests to write * Handle symlinks * File already open * Non supported extension (.xls) * Permissions Maybe test? * atime, mtime * large file """ import datetime from pyfakefs import fake_filesystem_unittest from unittest import skip try: # Python >= 3.3 from unittest import mock except ImportError: # Python < 3.3 import mock from mdweb.Page import PageMetaInf, Page, load_page from mdweb.Exceptions import ( PageMetaInfFieldException, PageParseException, ContentException, ) class TestPageMeta(fake_filesystem_unittest.TestCase): """PageMetaInf object tests.""" def setUp(self): """Create fake filesystem.""" self.setUpPyfakefs() def test_parse_empty_string(self): """Empty string should parse successfully.""" file_string = u"" meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertIsNone(meta_inf.date) self.assertIsNone(meta_inf.description) self.assertIsNone(meta_inf.nav_name) self.assertEqual(meta_inf.order, 0) self.assertIsNone(meta_inf.template) self.assertIsNone(meta_inf.title) def test_parse_some_fields(self): """A few defined fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Date: February 1st, 2016 """ meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 0) self.assertIsNone(meta_inf.template) self.assertEqual(meta_inf.title, u'MDWeb') def test_parse_all_fields(self): """All available fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date: February 1st, 2016 Order: 1 Template: page_home.html Nav Name: Home Page Sitemap Changefreq: Monthly Sitemap Priority: 0.5 Teaser: This is a teaser paragraph that will be availble to pages Teaser Image: /contentassets/home/00041_thumb.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Chad Rempp') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') self.assertEqual(meta_inf.nav_name, u'Home Page') self.assertEqual(meta_inf.sitemap_changefreq, u'Monthly') self.assertEqual(meta_inf.sitemap_priority, u'0.5') self.assertEqual(meta_inf.teaser, u'This is a teaser paragraph that will be availble to pages') self.assertEqual(meta_inf.teaser_image, u'/contentassets/home/00041_thumb.jpg') def test_metainf_spacing(self): """Spacing should not matter in parsing.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date : February 1st, 2016 Order: 1 Template: page_home.html """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Chad Rempp') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') def test_comments(self): """Comments should be skipped during parsing.""" file_string = u"""# This is a comment Title: MDWeb Description: The minimalistic markdown NaCMS #Author: Chad Rempp #Date: February 1st, 2016 Order: 1 Template: page_home.html # # Nothing to see here """ meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertIsNone(meta_inf.date) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') def test_unicode(self): """Parser should handle unicode.""" file_string = u"""Title: советских Description: ᚠᛇᚻ᛫ᛒᛦᚦ᛫ᚠᚱᚩᚠᚢᚱ᛫ᚠᛁᚱᚪ᛫ᚷᛖᚻᚹᛦᛚᚳᚢᛗ Author: Οδυσσέα Ελύτη Date: February 1st, 2016 Order: 1 Template: ღმერთსი.html """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Οδυσσέα Ελύτη') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'ᚠᛇᚻ᛫ᛒᛦᚦ᛫ᚠᚱᚩᚠᚢᚱ᛫ᚠᛁᚱᚪ᛫ᚷᛖᚻᚹᛦᛚᚳᚢᛗ') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'ღმერთსი.html') self.assertEqual(meta_inf.title, u'советских') def test_parse_multiline_field(self): """Multiline fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date: February 1st, 2016 Order: 1 Template: page_home.html Nav Name: Home Page Sitemap Changefreq: Monthly Sitemap Priority: 0.5 Teaser: This is a teaser paragraph that will be available to pages and the teaser may span multiple lines indented with whitespace even if the line looks like a metainf field Not A Field: This won't get parsed as a field Teaser Image: /contentassets/home/00041_thumb.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.teaser, u'This is a teaser paragraph that will be available to pages and the teaser may span multiple lines indented with whitespace even if the line looks like a metainf field Not A Field: This won\'t get parsed as a field') def test_parse_custom_field(self): """Multiline fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Summary Image: blah.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.custom_summary_image, u'blah.jpg') @skip def test_unpublished_page(self): """Unpublished pages should have the correct attr value.""" self.assertEqual(1, 2) class TestPage(fake_filesystem_unittest.TestCase): """Page object tests.""" def setUp(self): """Create fake filesystem.""" self.setUpPyfakefs() def test_page_instantiation(self): """A page should be instantiated with appropriate attributes.""" file_string = u"This is a page" self.fs.create_file('/my/content/about/history.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/about/history.md')) self.assertEqual(page.page_path, '/my/content/about/history.md') self.assertEqual(page.url_path, 'about/history') self.fs.create_file('/my/content/super/deep/url/path/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/super/deep/url/path/index.md')) self.assertEqual(page.page_path, '/my/content/super/deep/url/path/index.md') self.assertEqual(page.url_path, 'super/deep/url/path') def test_unparsable_path(self): """An unparsable page path should raise PageParseException.""" file_string = u"" self.fs.create_file('/my/content/index', contents=file_string) # Not an MD file self.assertRaises(PageParseException, load_page, '/my/content', '/my/content/index') @mock.patch('mdweb.Page.PageMetaInf') def test_repr(self, mock_page_meta_inf): """A Page object should return the proper repr.""" file_string = u"" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) self.assertEqual(str(page), '/my/content/index.md') @mock.patch('mdweb.Page.PageMetaInf') def test_parse_empty_file(self, mock_page_meta_inf): """An empty file should parse properly.""" file_string = u"" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with('') self.assertEqual(page.markdown_str, '') self.assertEqual(page.page_html, '') def test_no_file(self): """If the path has no file a ContentException should be raised.""" self.assertRaises(ContentException, load_page, '/my/content', '/my/content/index.md') @mock.patch('mdweb.Page.PageMetaInf') def test_no_meta_inf(self, mock_page_meta_inf): """A page with no meta information should parse.""" # pylint: disable=C0301 # pylint: disable=E501 file_string = u"""Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.""" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with('') self.assertEqual(page.markdown_str, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_meta_inf(self, mock_page_meta_inf): """A page with meta info should parse the content and meta inf.""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_slash_star_slash(self, mock_page_meta_inf): """A page with /*/ in the content should parse corectly. Regression test for https://github.com/crempp/mdweb/issues/47""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. This is a link that blows up the parser [asdf](https://web.archive.org/web/*/http://site.com) The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. This is a link that blows up the parser [asdf](https://web.archive.org/web/*/http://site.com) The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. This is a link that blows up the parser <a href="https://web.archive.org/web/*/http://site.com">asdf</a> The quick brown fox jumped over the lazy dog's back.''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_second_metainf(self, mock_page_meta_inf): """A page with a second metainf should only parse the first""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. Here is another metainf block ```metainf Title: Fake Block ``` The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. Here is another metainf block ```metainf Title: Fake Block ``` The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. Here is another metainf block <code>metainf Title: Fake Block</code> The quick brown fox jumped over the lazy dog's back.''') @mock.patch('mdweb.Page.PageMetaInf') def test_markdown_formatting(self, mock_page_meta_inf): """Markdown should parse correctly. We won't test this extensively as we should trust the markdown libraries to test themselves. """ file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Examples taken from https://daringfireball.net/projects/markdown/basics A First Level Header ==================== A Second Level Header --------------------- Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back. ### Header 3 > This is a blockquote. > > This is the second paragraph in the blockquote. > > ## This is an H2 in a blockquote --------------------------------------- Some of these words *are emphasized*. Some of these words _are emphasized also_. Use two asterisks for **strong emphasis**. Or, if you prefer, __use two underscores instead__. --------------------------------------- * Candy. * Gum. * Booze. --------------------------------------- 1. Red 2. Green 3. Blue --------------------------------------- * A list item. With multiple paragraphs. * Another item in the list. --------------------------------------- This is an [example link](http://example.com/). This is an [example link](http://example.com/ "With a Title"). --------------------------------------- I get 10 times more traffic from [Google][1] than from [Yahoo][2] or [MSN][3]. [1]: http://google.com/ "Google" [2]: http://search.yahoo.com/ "Yahoo Search" [3]: http://search.msn.com/ "MSN Search" I start my morning with a cup of coffee and [The New York Times][NY Times]. [ny times]: http://www.nytimes.com/ --------------------------------------- ![alt text](/path/to/img.jpg "Title") ![alt text][id] [id]: /path/to/img.jpg "Title" --------------------------------------- I strongly recommend against using any `<blink>` tags. I wish SmartyPants used named entities like `—` instead of decimal-encoded entites like `—`. If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes: <blockquote> For example. </blockquote> ---------------------------------------''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Examples taken from https://daringfireball.net/projects/markdown/basics A First Level Header ==================== A Second Level Header --------------------- Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back. ### Header 3 > This is a blockquote. > > This is the second paragraph in the blockquote. > > ## This is an H2 in a blockquote --------------------------------------- Some of these words *are emphasized*. Some of these words _are emphasized also_. Use two asterisks for **strong emphasis**. Or, if you prefer, __use two underscores instead__. --------------------------------------- * Candy. * Gum. * Booze. --------------------------------------- 1. Red 2. Green 3. Blue --------------------------------------- * A list item. With multiple paragraphs. * Another item in the list. --------------------------------------- This is an [example link](http://example.com/). This is an [example link](http://example.com/ "With a Title"). --------------------------------------- I get 10 times more traffic from [Google][1] than from [Yahoo][2] or [MSN][3]. [1]: http://google.com/ "Google" [2]: http://search.yahoo.com/ "Yahoo Search" [3]: http://search.msn.com/ "MSN Search" I start my morning with a cup of coffee and [The New York Times][NY Times]. [ny times]: http://www.nytimes.com/ --------------------------------------- ![alt text](/path/to/img.jpg "Title") ![alt text][id] [id]: /path/to/img.jpg "Title" --------------------------------------- I strongly recommend against using any `<blink>` tags. I wish SmartyPants used named entities like `—` instead of decimal-encoded entites like `—`. If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes: <blockquote> For example. </blockquote> ---------------------------------------''') # pylint: disable=C0301 # pylint: disable=E501 self.assertEqual(page.page_html, '''Examples taken from https://daringfireball.net/projects/markdown/basics <h1>A First Level Header</h1> <h2>A Second Level Header</h2> Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back. <h3>Header 3</h3> <blockquote> This is a blockquote. This is the second paragraph in the blockquote. <h2>This is an H2 in a blockquote</h2> </blockquote> <hr /> Some of these words are emphasized. Some of these words are emphasized also. Use two asterisks for strong emphasis. Or, if you prefer, use two underscores instead. <hr /> <ul> <li>Candy.</li> <li>Gum.</li> <li>Booze.</li> </ul> <hr /> <ol> <li>Red</li> <li>Green</li> <li>Blue</li> </ol> <hr /> <ul> <li> A list item. With multiple paragraphs. </li> <li> Another item in the list. </li> </ul> <hr /> This is an <a href="http://example.com/">example link</a>. This is an <a href="http://example.com/" title="With a Title">example link</a>. <hr /> I get 10 times more traffic from <a href="http://google.com/" title="Google">Google</a> than from <a href="http://search.yahoo.com/" title="Yahoo Search">Yahoo</a> or <a href="http://search.msn.com/" title="MSN Search">MSN</a>. I start my morning with a cup of coffee and <a href="http://www.nytimes.com/">The New York Times</a>. <hr /> <img alt="alt text" src="/path/to/img.jpg" title="Title" /> <img alt="alt text" src="/path/to/img.jpg" title="Title" /> <hr /> I strongly recommend against using any <code><blink></code> tags. I wish SmartyPants used named entities like <code>&mdash;</code> instead of decimal-encoded entites like <code>&#8212;</code>. If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes: <pre><code><blockquote> For example. </blockquote> </code></pre> <hr />''')

0

2d857a8f033972ecd5bd933956e549a665614872

1,080

py

Python

day13/shuttlebus2.py

fpeterek/aoc-2020

ae08a96c2213e94d204fc11051e2a9f535d62973

[ "MIT" ]

null

day13/shuttlebus2.py

fpeterek/aoc-2020

ae08a96c2213e94d204fc11051e2a9f535d62973

[ "MIT" ]

null

day13/shuttlebus2.py

fpeterek/aoc-2020

ae08a96c2213e94d204fc11051e2a9f535d62973

[ "MIT" ]

null

if __name__ == '__main__': run()

26.341463

96

0.591667

class Bus: def __init__(self, number: int, offset: int, begin: int = 0): self.number = number self.offset = offset self.begin = begin def load_file(filename: str) -> tuple[int, list[int]]: with open(filename) as f: timestamp = int(f.readline()) buses = f.readline().split(',') return [Bus(int(bus), offset) for offset, bus in enumerate(buses) if bus and bus != 'x'] def lcm(x: int, y: int, begin: int = 0, offset: int = 0) -> int: delta = x multiply = begin if begin else delta while (multiply < offset) or ((multiply + offset) % y): multiply += delta return multiply def find(b1: Bus, b2: Bus) -> Bus: period = lcm(b1.number, b2.number) t1 = lcm(x=b1.number, y=b2.number, begin=b1.begin, offset=b2.offset) return Bus(number=period, offset=0, begin=t1) def run() -> None: buses = load_file('in.txt') while len(buses) > 1: b1, b2 = buses.pop(0), buses.pop(0) buses.insert(0, find(b1, b2)) print(buses[0].begin) if __name__ == '__main__': run()

905

-11

142

2467cce351ee3950d6051b279111c2511b02732a

76

py

Python

pytest_harvest/tests_raw/conftest.py

keszybz/python-pytest-harvest

ef11d3addeae51168ab892b7806c2b4c270e2a82

[ "BSD-3-Clause" ]

36

2018-11-07T19:32:08.000Z

2022-03-19T10:24:48.000Z

pytest_harvest/tests_raw/conftest.py

keszybz/python-pytest-harvest

ef11d3addeae51168ab892b7806c2b4c270e2a82

[ "BSD-3-Clause" ]

55

2018-11-13T10:58:30.000Z

2022-01-06T10:32:53.000Z

pytest_harvest/tests_raw/conftest.py

keszybz/python-pytest-harvest

ef11d3addeae51168ab892b7806c2b4c270e2a82

[ "BSD-3-Clause" ]

4

2019-10-05T09:50:09.000Z

2021-03-31T20:33:16.000Z

# This is actually not even needed apparently # pytest_plugins = ["harvest"]

38

45

0.763158

# This is actually not even needed apparently # pytest_plugins = ["harvest"]

0

0cab310479ab3cc6d73dc8671b51f36e59625a28

456

py

Python

fly/ModelCreate.py

cheburakshu/fly

d452af4b83e4cb0f8d0094bf1e0c1b407d39bdf5

[ "Apache-2.0" ]

null

fly/ModelCreate.py

cheburakshu/fly

d452af4b83e4cb0f8d0094bf1e0c1b407d39bdf5

[ "Apache-2.0" ]

null

fly/ModelCreate.py

cheburakshu/fly

d452af4b83e4cb0f8d0094bf1e0c1b407d39bdf5

[ "Apache-2.0" ]

null

#fly from .ModelIO import ModelIO from .ModelConfig import ModelConfig

26.823529

81

0.64693

#fly from .ModelIO import ModelIO from .ModelConfig import ModelConfig class ModelCreate(object): def __init__(self,*args,**kwargs): self._ModelConfig = ModelConfig(kwargs.get('filename')) #*args,**kwargs) self._modelNames = self._ModelConfig.getModels() self._model = None def create(self,*args,**kwargs): self._model = ModelIO(*args,**kwargs) def getModel(self): return self._model

265

5

110

d4aeef5e3912b8f3cd0610d8270c456d1f413716

17,328

py

Python

pedal/core/feedback.py

acbart/python-analysis

3cd2cc22d50a414ae6b62c74d2643be4742238d4

[ "MIT" ]

14

2019-08-22T03:40:23.000Z

2022-03-13T00:30:53.000Z

pedal/core/feedback.py

pedal-edu/pedal

3cd2cc22d50a414ae6b62c74d2643be4742238d4

[ "MIT" ]

74

2019-09-12T04:35:56.000Z

2022-01-26T19:21:32.000Z

pedal/core/feedback.py

acbart/python-analysis

3cd2cc22d50a414ae6b62c74d2643be4742238d4

[ "MIT" ]

2

2018-09-16T22:39:15.000Z

2018-09-17T12:53:28.000Z

""" Simple data classes for storing feedback to present to learners. """ __all__ = ['Feedback', 'FeedbackKind', 'FeedbackCategory', "CompositeFeedbackFunction", "FeedbackResponse"] from pedal.core.formatting import FeedbackFieldWrapper from pedal.core.location import Location from pedal.core.report import MAIN_REPORT from pedal.core.feedback_category import FeedbackKind, FeedbackCategory, FeedbackStatus PEDAL_DEVELOPERS = ["Austin Cory Bart <acbart@udel.edu>", "Luke Gusukuma <lukesg08@vt.edu>"] class Feedback: """ A class for storing raw feedback. Attributes: label (str): An internal name for this specific piece of feedback. The label should be an underscore-separated string following the same conventions as names in Python. They do not have to be globally unique, but labels should be as unique as possible (especially within a category). tool (str, optional): An internal name for indicating the tool that created this feedback. Should be taken directly from the Tool itself. If `None`, then this was not created by a tool but directly by the control script. category (str): A human-presentable name showable to the learner, indicating what sort of feedback this falls into (e.g., "runtime", "syntax", "algorithm"). More than one feedback will be in a category, but a feedback cannot be in more than one category. kind (str): The pedagogical role of this feedback, e.g., "misconception", "mistake", "hint", "constraint". Usually, a piece of Feedback is pointing out a mistake, but feedback can also be used for various other purposes. justification (str): An instructor-facing string briefly describing why this feedback was selected. Serves as a "TL;DR" for this feedback category, useful for debugging why a piece of feedback appeared. priority (str): An indication of how important this feedback is relative to other types of feedback in the same category. Might be "high/medium/low". Exactly how this gets used is up to the resolver, but typicaly it helps break ties. valence (int): Indicates whether this is negative, positive, or neutral feedback. Either 1, -1, or 0. title (str, optional): A formal, student-facing title for this feedback. If None, indicates that the :py:attr:`~pedal.core.feedback.Feedback.label` should be used instead. message (str): A markdown-formatted message (aka also supporting HTML) that could be rendered to the user. message_template (str): A markdown-formatted message template that will be used if a ``message`` is None. Any ``fields`` will be injected into the template IF the ``condition`` is met. fields (Dict[str,Any]): The raw data that was used to interpolate the template to produce the message. location (:py:attr:`~pedal.core.location.Location` or int): Information about specific locations relevant to this message. score (int): A numeric score to modify the students' total score, indicating their overall performance. It is ultimately up to the Resolver to decide how to combine all the different scores; a typical strategy would be to add all the scores together for any non-muted feedback. correct (bool): Indicates that the entire submission should be considered correct (success) and that the task is now finished. muted (bool): Whether this piece of feedback is something that should be shown to a student. There are various use cases for muted feedback: they can serve as flags for later conditionals, suppressed default kinds of feedback, or perhaps feedback that is interesting for analysis but not pedagogically helpful to give to the student. They will still contribute to overall score, but not to the correcntess of the submission. unscored (bool): Whether or not this piece of feedback contributes to the score/correctness. else_message (str): A string to render as a message when a NEGATIVE valence feedback is NOT triggered, or a POSITIVE valence feedback IS triggered. TODO: Should we also have an else_message_template? Probably. activate (bool): Used for default feedback objects without a custom condition, to indicate whether they should be considered triggered. Defaults to True; setting this to False means that the feedback object will be deactivated. Note that most inheriting Feedback Functions will not respect this parameter. author (List[str]): A list of names/emails that indicate who created this piece of feedback. They can be either names, emails, or combinations in the style of `"Cory Bart <acbart@udel.edu>"`. version (str): A version string in the style of Semantic Version (semvar) such as `"0.0.1"`. The last (third) digit should be incremented for small bug fixes/changes. The middle (second) digit should be used for more serious and intense changes. The first digit should be incremented when changes are made on exposure to learners or some other evidence-based motivation. tags (list[:py:class:`~pedal.core.tag.Tag`]): Any tags that you want to attach to this feedback. parent (int, str, or `pedal.core.feedback.Feedback`): Information about what logical grouping within the submission this belongs to. Various tools can chunk up a submission (e.g., by section), they can use this field to keep track of how that decision was made. Resolvers can also use this information to organize feedback or to report multiple categories. report (:py:class:`~pedal.core.report.Report`): The Report object to attach this feedback to. Defaults to MAIN_REPORT. Unspecified fields will be filled in by inspecting the current Feedback Function context. """ POSITIVE_VALENCE = 1 NEUTRAL_VALENCE = 0 NEGATIVE_VALENCE = -1 CATEGORIES = FeedbackCategory KINDS = FeedbackKind label = None category = None justification = None constant_fields = None fields = None field_names = None kind = None title = None message = None message_template = None else_message = None priority = None valence = None location = None score = None correct = None muted = None unscored = None tool = None version = '1.0.0' author = PEDAL_DEVELOPERS tags = None parent = None activate: bool _status: str _exception: Exception or None _met_condition: bool _stored_args: tuple _stored_kwargs: dict #MAIN_REPORT def _handle_condition(self): """ Actually handle the condition check, updating message and report. """ # Self-attach to a given report? self._exception = None try: self._met_condition = self.condition(*self._stored_args, **self._stored_kwargs) # Generate the message field as needed if self._met_condition: self.message = self._get_message() self._status = FeedbackStatus.ACTIVE else: self._status = FeedbackStatus.INACTIVE except Exception as e: self._met_condition = False self._exception = e self._status = FeedbackStatus.ERROR if self.report is not None: if self._met_condition: self.report.add_feedback(self) else: self.report.add_ignored_feedback(self) # Free up these temporary fields after condition is handled # del self._stored_args # del self._stored_kwargs if self._exception is not None: raise self._exception def condition(self, *args, **kwargs): """ Detect if this feedback is present in the code. Defaults to true through the `activate` parameter. Returns: bool: Whether or not this feedback's condition was detected. """ return self.activate def _get_message(self): """ Determines the appropriate value for the message. It will attempt to use this instance's message, but if it's not available then it will try to generate one from the message_template. Then, it returns a generic message. You can override this to create a truly dynamic message, if you want. Returns: str: The message for this feedback. """ if self.message is not None: return self.message if self.message_template is not None: fields = {field: FeedbackFieldWrapper(field, value, self.report.format) for field, value in self.fields.items()} return self.message_template.format(**fields) return "No feedback message provided" def _get_child_feedback(self, feedback, active): """ Callback function that Reports will call when a new piece of feedback is being considered. By default, does nothing. This is useful for :py:class:`pedal.core.group.FeedbackGroup`, most other feedbacks will just not care. The ``active`` parameter controls whether or not the condition for the feedback was met. """ def __str__(self): """ Create a string representation of this piece of Feedback for quick, dev purposes. Returns: str: String representation """ return "<Feedback ({},{})>".format(self.category, self.label) def __repr__(self): """ Create a string representation of this piece of Feedback that displays considerably more information. Returns: str: String representation with more data """ metadata = "" if self.tool is not None: metadata += ", tool=" + self.tool if self.category is not None: metadata += ", category=" + self.category if self.priority is not None: metadata += ", priority=" + self.priority if self.parent is not None: metadata += ", parent=" + str(self.parent.label) return "Feedback({}{})".format(self.label, metadata) def update_location(self, location): """ Updates both the fields and location attribute. TODO: Handle less information intelligently. """ if isinstance(location, int): location = Location(location) self.location = location self.fields['location'] = location class FeedbackResponse(Feedback): """ An extension of :py:class:`~pedal.core.feedback.Feedback` that is meant to indicate that the class should not have any condition behind its response. """ def CompositeFeedbackFunction(*functions): """ Decorator for functions that return multiple types of feedback functions. Args: functions (callable): A list of callable functions. Returns: callable: The decorated function. """ def CompositeFeedbackFunction_with_attrs(function): """ Args: function: Returns: """ CompositeFeedbackFunction_with_attrs.functions = functions return function return CompositeFeedbackFunction_with_attrs class FeedbackGroup(Feedback): """ An extension of :py:class:`~pedal.core.feedback.Feedback` that is meant to indicate that this class will start a new Group context within the report and do something interesting with any children it gets. """ DEFAULT_CATEGORY_PRIORITY = [ "highest", # Static Feedback.CATEGORIES.SYNTAX, Feedback.CATEGORIES.MISTAKES, Feedback.CATEGORIES.INSTRUCTOR, Feedback.CATEGORIES.ALGORITHMIC, # Dynamic Feedback.CATEGORIES.RUNTIME, Feedback.CATEGORIES.STUDENT, Feedback.CATEGORIES.SPECIFICATION, Feedback.CATEGORIES.POSITIVE, Feedback.CATEGORIES.INSTRUCTIONS, Feedback.CATEGORIES.UNKNOWN, "lowest" ]

39.381818

118

0.627539

""" Simple data classes for storing feedback to present to learners. """ __all__ = ['Feedback', 'FeedbackKind', 'FeedbackCategory', "CompositeFeedbackFunction", "FeedbackResponse"] from pedal.core.formatting import FeedbackFieldWrapper from pedal.core.location import Location from pedal.core.report import MAIN_REPORT from pedal.core.feedback_category import FeedbackKind, FeedbackCategory, FeedbackStatus PEDAL_DEVELOPERS = ["Austin Cory Bart <acbart@udel.edu>", "Luke Gusukuma <lukesg08@vt.edu>"] class Feedback: """ A class for storing raw feedback. Attributes: label (str): An internal name for this specific piece of feedback. The label should be an underscore-separated string following the same conventions as names in Python. They do not have to be globally unique, but labels should be as unique as possible (especially within a category). tool (str, optional): An internal name for indicating the tool that created this feedback. Should be taken directly from the Tool itself. If `None`, then this was not created by a tool but directly by the control script. category (str): A human-presentable name showable to the learner, indicating what sort of feedback this falls into (e.g., "runtime", "syntax", "algorithm"). More than one feedback will be in a category, but a feedback cannot be in more than one category. kind (str): The pedagogical role of this feedback, e.g., "misconception", "mistake", "hint", "constraint". Usually, a piece of Feedback is pointing out a mistake, but feedback can also be used for various other purposes. justification (str): An instructor-facing string briefly describing why this feedback was selected. Serves as a "TL;DR" for this feedback category, useful for debugging why a piece of feedback appeared. priority (str): An indication of how important this feedback is relative to other types of feedback in the same category. Might be "high/medium/low". Exactly how this gets used is up to the resolver, but typicaly it helps break ties. valence (int): Indicates whether this is negative, positive, or neutral feedback. Either 1, -1, or 0. title (str, optional): A formal, student-facing title for this feedback. If None, indicates that the :py:attr:`~pedal.core.feedback.Feedback.label` should be used instead. message (str): A markdown-formatted message (aka also supporting HTML) that could be rendered to the user. message_template (str): A markdown-formatted message template that will be used if a ``message`` is None. Any ``fields`` will be injected into the template IF the ``condition`` is met. fields (Dict[str,Any]): The raw data that was used to interpolate the template to produce the message. location (:py:attr:`~pedal.core.location.Location` or int): Information about specific locations relevant to this message. score (int): A numeric score to modify the students' total score, indicating their overall performance. It is ultimately up to the Resolver to decide how to combine all the different scores; a typical strategy would be to add all the scores together for any non-muted feedback. correct (bool): Indicates that the entire submission should be considered correct (success) and that the task is now finished. muted (bool): Whether this piece of feedback is something that should be shown to a student. There are various use cases for muted feedback: they can serve as flags for later conditionals, suppressed default kinds of feedback, or perhaps feedback that is interesting for analysis but not pedagogically helpful to give to the student. They will still contribute to overall score, but not to the correcntess of the submission. unscored (bool): Whether or not this piece of feedback contributes to the score/correctness. else_message (str): A string to render as a message when a NEGATIVE valence feedback is NOT triggered, or a POSITIVE valence feedback IS triggered. TODO: Should we also have an else_message_template? Probably. activate (bool): Used for default feedback objects without a custom condition, to indicate whether they should be considered triggered. Defaults to True; setting this to False means that the feedback object will be deactivated. Note that most inheriting Feedback Functions will not respect this parameter. author (List[str]): A list of names/emails that indicate who created this piece of feedback. They can be either names, emails, or combinations in the style of `"Cory Bart <acbart@udel.edu>"`. version (str): A version string in the style of Semantic Version (semvar) such as `"0.0.1"`. The last (third) digit should be incremented for small bug fixes/changes. The middle (second) digit should be used for more serious and intense changes. The first digit should be incremented when changes are made on exposure to learners or some other evidence-based motivation. tags (list[:py:class:`~pedal.core.tag.Tag`]): Any tags that you want to attach to this feedback. parent (int, str, or `pedal.core.feedback.Feedback`): Information about what logical grouping within the submission this belongs to. Various tools can chunk up a submission (e.g., by section), they can use this field to keep track of how that decision was made. Resolvers can also use this information to organize feedback or to report multiple categories. report (:py:class:`~pedal.core.report.Report`): The Report object to attach this feedback to. Defaults to MAIN_REPORT. Unspecified fields will be filled in by inspecting the current Feedback Function context. """ POSITIVE_VALENCE = 1 NEUTRAL_VALENCE = 0 NEGATIVE_VALENCE = -1 CATEGORIES = FeedbackCategory KINDS = FeedbackKind label = None category = None justification = None constant_fields = None fields = None field_names = None kind = None title = None message = None message_template = None else_message = None priority = None valence = None location = None score = None correct = None muted = None unscored = None tool = None version = '1.0.0' author = PEDAL_DEVELOPERS tags = None parent = None activate: bool _status: str _exception: Exception or None _met_condition: bool _stored_args: tuple _stored_kwargs: dict #MAIN_REPORT def __init__(self, *args, label=None, category=None, justification=None, fields=None, field_names=None, kind=None, title=None, message=None, message_template=None, else_message=None, priority=None, valence=None, location=None, score=None, correct=None, muted=None, unscored=None, tool=None, version=None, author=None, tags=None, parent=None, report=MAIN_REPORT, delay_condition=False, activate=True, **kwargs): # Internal data self.report = report # Metadata if label is not None: self.label = label else: self.label = self.__class__.__name__ # Condition if category is not None: self.category = category if justification is not None: self.justification = justification self.activate = activate # Response if kind is not None: self.kind = kind if priority is not None: self.priority = priority if valence is not None: self.valence = valence # Presentation if fields is not None: self.fields = fields else: self.fields = {} if self.constant_fields is not None: self.fields.update(self.constant_fields) if field_names is not None: self.field_names = field_names if title is not None: self.title = title elif self.title is None: self.title = label if message is not None: self.message = message if message_template is not None: self.message_template = message_template if else_message is not None: self.else_message = else_message # Locations if isinstance(location, int): location = Location(location) # TODO: Handle tuples (Line, Col) and (Filename, Line, Col), and # possibly lists thereof if location is not None: self.location = location # Result if score is not None: self.score = score if correct is not None: self.correct = correct if muted is not None: self.muted = muted if unscored is not None: self.unscored = unscored # Metadata if tool is not None: self.tool = tool if version is not None: self.version = version if author is not None: self.author = author if tags is not None: self.tags = tags # Organizational if parent is not None: self.parent = parent if self.parent is None: # Might inherit from Report's current group self.parent = self.report.get_current_group() if self.field_names is not None: for field_name in self.field_names: self.fields[field_name] = kwargs.get(field_name) for key, value in kwargs.items(): self.fields[key] = value if 'location' not in self.fields and self.location is not None: self.fields['location'] = self.location # Potentially delay the condition check self._stored_args = args self._stored_kwargs = kwargs if delay_condition: self._met_condition = False self._status = FeedbackStatus.DELAYED else: self._handle_condition() def _handle_condition(self): """ Actually handle the condition check, updating message and report. """ # Self-attach to a given report? self._exception = None try: self._met_condition = self.condition(*self._stored_args, **self._stored_kwargs) # Generate the message field as needed if self._met_condition: self.message = self._get_message() self._status = FeedbackStatus.ACTIVE else: self._status = FeedbackStatus.INACTIVE except Exception as e: self._met_condition = False self._exception = e self._status = FeedbackStatus.ERROR if self.report is not None: if self._met_condition: self.report.add_feedback(self) else: self.report.add_ignored_feedback(self) # Free up these temporary fields after condition is handled # del self._stored_args # del self._stored_kwargs if self._exception is not None: raise self._exception def condition(self, *args, **kwargs): """ Detect if this feedback is present in the code. Defaults to true through the `activate` parameter. Returns: bool: Whether or not this feedback's condition was detected. """ return self.activate def _get_message(self): """ Determines the appropriate value for the message. It will attempt to use this instance's message, but if it's not available then it will try to generate one from the message_template. Then, it returns a generic message. You can override this to create a truly dynamic message, if you want. Returns: str: The message for this feedback. """ if self.message is not None: return self.message if self.message_template is not None: fields = {field: FeedbackFieldWrapper(field, value, self.report.format) for field, value in self.fields.items()} return self.message_template.format(**fields) return "No feedback message provided" def _get_child_feedback(self, feedback, active): """ Callback function that Reports will call when a new piece of feedback is being considered. By default, does nothing. This is useful for :py:class:`pedal.core.group.FeedbackGroup`, most other feedbacks will just not care. The ``active`` parameter controls whether or not the condition for the feedback was met. """ def __xor__(self, other): if isinstance(other, Feedback): self.muted = bool(self) and not bool(other) self.unscored = self.muted other.muted = bool(other) and not bool(self) other.unscored = other.muted if isinstance(other, bool): self.muted = bool(self) and not bool(other) self.unscored = self.muted def __rxor__(self, other): return self.__xor__(other) def __bool__(self): return bool(self._met_condition) def __str__(self): """ Create a string representation of this piece of Feedback for quick, dev purposes. Returns: str: String representation """ return "<Feedback ({},{})>".format(self.category, self.label) def __repr__(self): """ Create a string representation of this piece of Feedback that displays considerably more information. Returns: str: String representation with more data """ metadata = "" if self.tool is not None: metadata += ", tool=" + self.tool if self.category is not None: metadata += ", category=" + self.category if self.priority is not None: metadata += ", priority=" + self.priority if self.parent is not None: metadata += ", parent=" + str(self.parent.label) return "Feedback({}{})".format(self.label, metadata) def update_location(self, location): """ Updates both the fields and location attribute. TODO: Handle less information intelligently. """ if isinstance(location, int): location = Location(location) self.location = location self.fields['location'] = location def _fields_to_json(self): return self.fields.copy() def to_json(self): return { 'correct': self.correct, 'score': self.score, 'title': self.title, 'message': self.message, 'label': self.label, 'active': bool(self), 'muted': self.muted, 'unscored': self.unscored, 'category': self.category, 'kind': self.kind, 'valence': self.valence, 'version': self.version, 'fields': self._fields_to_json(), 'justification': self.justification, 'priority': self.priority, 'location': self.location.to_json() if self.location is not None else None } class FeedbackResponse(Feedback): """ An extension of :py:class:`~pedal.core.feedback.Feedback` that is meant to indicate that the class should not have any condition behind its response. """ def CompositeFeedbackFunction(*functions): """ Decorator for functions that return multiple types of feedback functions. Args: functions (callable): A list of callable functions. Returns: callable: The decorated function. """ def CompositeFeedbackFunction_with_attrs(function): """ Args: function: Returns: """ CompositeFeedbackFunction_with_attrs.functions = functions return function return CompositeFeedbackFunction_with_attrs class FeedbackGroup(Feedback): """ An extension of :py:class:`~pedal.core.feedback.Feedback` that is meant to indicate that this class will start a new Group context within the report and do something interesting with any children it gets. """ DEFAULT_CATEGORY_PRIORITY = [ "highest", # Static Feedback.CATEGORIES.SYNTAX, Feedback.CATEGORIES.MISTAKES, Feedback.CATEGORIES.INSTRUCTOR, Feedback.CATEGORIES.ALGORITHMIC, # Dynamic Feedback.CATEGORIES.RUNTIME, Feedback.CATEGORIES.STUDENT, Feedback.CATEGORIES.SPECIFICATION, Feedback.CATEGORIES.POSITIVE, Feedback.CATEGORIES.INSTRUCTIONS, Feedback.CATEGORIES.UNKNOWN, "lowest" ]

4,740

0

162

25d93ebd57650e95d922e302d78dcc9e2626544e

1,501

py

Python

oops_fhir/r4/code_system/precision_estimate_type.py

Mikuana/oops_fhir

77963315d123756b7d21ae881f433778096a1d25

[ "MIT" ]

null

oops_fhir/r4/code_system/precision_estimate_type.py

Mikuana/oops_fhir

77963315d123756b7d21ae881f433778096a1d25

[ "MIT" ]

null

oops_fhir/r4/code_system/precision_estimate_type.py

Mikuana/oops_fhir

77963315d123756b7d21ae881f433778096a1d25

[ "MIT" ]

null

from pathlib import Path from fhir.resources.codesystem import CodeSystem from oops_fhir.utils import CodeSystemConcept __all__ = ["PrecisionEstimateType"] _resource = CodeSystem.parse_file(Path(__file__).with_suffix(".json")) class PrecisionEstimateType: """ PrecisionEstimateType Method of reporting variability of estimates, such as confidence intervals, interquartile range or standard deviation. Status: draft - Version: 4.0.1 Copyright None http://terminology.hl7.org/CodeSystem/precision-estimate-type """ ci = CodeSystemConcept( { "code": "CI", "definition": "confidence interval.", "display": "confidence interval", } ) """ confidence interval confidence interval. """ iqr = CodeSystemConcept( { "code": "IQR", "definition": "interquartile range.", "display": "interquartile range", } ) """ interquartile range interquartile range. """ sd = CodeSystemConcept( { "code": "SD", "definition": "standard deviation.", "display": "standard deviation", } ) """ standard deviation standard deviation. """ se = CodeSystemConcept( {"code": "SE", "definition": "standard error.", "display": "standard error"} ) """ standard error standard error. """

19.493506

84

0.588274

from pathlib import Path from fhir.resources.codesystem import CodeSystem from oops_fhir.utils import CodeSystemConcept __all__ = ["PrecisionEstimateType"] _resource = CodeSystem.parse_file(Path(__file__).with_suffix(".json")) class PrecisionEstimateType: """ PrecisionEstimateType Method of reporting variability of estimates, such as confidence intervals, interquartile range or standard deviation. Status: draft - Version: 4.0.1 Copyright None http://terminology.hl7.org/CodeSystem/precision-estimate-type """ ci = CodeSystemConcept( { "code": "CI", "definition": "confidence interval.", "display": "confidence interval", } ) """ confidence interval confidence interval. """ iqr = CodeSystemConcept( { "code": "IQR", "definition": "interquartile range.", "display": "interquartile range", } ) """ interquartile range interquartile range. """ sd = CodeSystemConcept( { "code": "SD", "definition": "standard deviation.", "display": "standard deviation", } ) """ standard deviation standard deviation. """ se = CodeSystemConcept( {"code": "SE", "definition": "standard error.", "display": "standard error"} ) """ standard error standard error. """ class Meta: resource = _resource

0

19

27

b9dac44e185c9b124e9894a09b40bf74c9e25e50

43,059

py

Python

onezone/zone.py

aemerick/onezone

3a3c9a6542d0d8b9de7d18b94f866205dd3210b6

[ "MIT" ]

null

onezone/zone.py

aemerick/onezone

3a3c9a6542d0d8b9de7d18b94f866205dd3210b6

[ "MIT" ]

null

onezone/zone.py

aemerick/onezone

3a3c9a6542d0d8b9de7d18b94f866205dd3210b6

[ "MIT" ]

1

2021-05-10T20:15:16.000Z

""" Author : A. Emerick Date : May 2016 Purpose: """ __author__ = "aemerick <emerick@astro.columbia.edu>" # external import numpy as np #from collections import OrderedDict import os, h5py from scipy.interpolate import interp1d try: import dill as pickle except: print("WARNING: Dill unavailable, attempting to use pickle, which may crash") try: import pickle as pickle except: print("WARNING: cPickle unavailable, using pickle - data dumps will be slow") import pickle # internal from . import imf as imf #from . import star as star from onezone.cython_ext import cython_star as star from . import config as config from .constants import CONST as const from . import performance_tools as perf def restart(filename): """ Restart evolution from chosen picked output file """ zone = pickle.load( open(filename, 'r')) zone.evolve() return class Zone: """ Zone Class Single zone gas reservoir attached to star formation and chemical enrichment models. Parameters for a given simulation can be set using config. Zone initializes a simulation using initial conditions parameters set in config. Once initialized and abundances are set, simulation can be evolved: >>> sim = Zone() >>> sim.set_initial_abundances(list_of_element_names) >>> sim.evolve() I/O controlled by config parameters, but can be done manually with a full (pickle) dump or an output of summary statistics: >>> sim.write_full_pickle() >>> sim.write_summary_output() """ def set_initial_abundances(self, elements, abundances = None): """ Set initial abundances using a list of desired elements and associated abundances. If no abundances are provided, all are set to zero except H and He. Abundances dict does not have to be complete """ self.initial_abundances = {} # OrderedDict() if abundances == None: abundances = {'empty' : 0.0} for e in elements: if e in abundances.keys(): self.initial_abundances[e] = abundances[e] elif e == 'H': self.initial_abundances[e] = 0.75*(1.0 - self.Z) elif e == 'He': self.initial_abundances[e] = 0.25*(1.0 - self.Z) elif e == 'm_metal': self.initial_abundances[e] = self.Z elif e == 'm_tot': self.initial_abundances[e] = 1.0 else: self.initial_abundances[e] = 0.0 for e in self.initial_abundances.keys(): self.species_masses[e] = self.M_gas * self.initial_abundances[e] self.halo_masses[e] = 0.0 # # One day, set this as list with second list of conditionals # so one can (at runtime) arbitrarily track on any condition # self.special_mass_accumulator = {} # OrderedDict() self.special_mass_accumulator['m_massive'] = 0.0 return None def _accumulate_new_sn(self): """ Looks through all stars, checking to see if any new SN or SNIa occured in current timestep. Adds these to the counters """ star_type = list(self.all_stars.property_asarray('type')) #if np.size(star_type) > 1: self.N_SNIa += star_type.count('new_SNIa_remnant') self.N_SNII += star_type.count('new_remnant') return def evolve(self): """ Evolves the system until the end time assigned in config, using a constant timestep. This handles the formation of new stars, gas inflow and outflow, enrichment from stars, and outputs. """ config.global_values.profiler.start_timer("total_time",True) while self.t <= config.zone.t_final: config.global_values.profiler.start_timer('compute_dt') self._compute_dt() config.global_values.profiler.end_timer('compute_dt') # # Check if output conditions are met # config.global_values.profiler.start_timer('check_output') self._check_output() config.global_values.profiler.end_timer('check_output') # # I) Evolve stars, computing ejecta rates and abundances # config.global_values.profiler.start_timer('evolve_stars') self._evolve_stars() config.global_values.profiler.end_timer('evolve_stars') # # II) Sum up and store number of supernovae # config.global_values.profiler.start_timer('accumulate_sn') self._accumulate_new_sn() config.global_values.profiler.end_timer('accumulate_sn') # # III) Compute SFR and make new stars # config.global_values.profiler.start_timer('compute_sfr') self._compute_sfr() config.global_values.profiler.end_timer('compute_sfr') config.global_values.profiler.start_timer('make_stars') self.M_sf = self._make_new_stars() config.global_values.profiler.end_timer('make_stars') # # IV) Compute inflow and outflow # config.global_values.profiler.start_timer('outflow_inflow_mdot') self._compute_outflow() self._compute_inflow() self._compute_mdot_dm() config.global_values.profiler.end_timer('outflow_inflow_mdot') # # V) Add/remove gas from zone due to inflow, # outflow, SF, and stellar ejecta # abundances = self.abundances temp1 = abundances['m_metal'] * 1.0 new_gas_mass = self.M_gas + (self.Mdot_in + self.Mdot_ej_masses['m_tot'] -\ self.Mdot_out) * self.dt - self.M_sf +\ self.SN_ej_masses['m_tot'] # # VI) Check if reservoir is empty # if self.M_gas <= 0: self.M_gas = 0.0 _my_print("Gas in zone depleted. Ending simulation") break # # VII) Compute increase / decrease of individual abundances # for e in self.species_masses.keys(): self.species_masses[e] = self.species_masses[e] + (self.Mdot_in * self.Mdot_in_abundances(e) +\ self.Mdot_ej_masses[e] -\ self.Mdot_out_species[e]) * self.dt -\ self.M_sf * abundances[e] + self.SN_ej_masses[e] self.halo_masses[e] = self.halo_masses[e] + self.Mdot_out_species[e] * self.dt # no halo accretion for now. self.M_gas = new_gas_mass self.M_DM = self.M_DM + self.Mdot_DM * self.dt # # VII) i) ensure metallicity is consistent with new abundances # self._update_metallicity() # # VIII) End of evolution, increment counters # config.global_values.profiler.start_timer('update_globals') self.t += self.dt self._cycle_number += 1 self._update_globals() config.global_values.profiler.end_timer('update_globals') outstr = "======================================================\n" +\ "===== Cycle = %00005i time = %5.5E =======\n"%(self._cycle_number,self.t) +\ "======================================================\n" config.global_values.profiler.write_performance(outstr=outstr) # # At end of simulation, force summary and dump # outputs # config.global_values.profiler.end_timer("total_time") config.global_values.profiler.write_performance(outstr=outstr) self._check_output(force=True) self._clean_up() return @property @property def abundances(self): """ Returns dictionary of abundances """ abund = {} for x in self.species_masses.keys(): abund[x] = self.species_masses[x] / self.M_gas return abund @property def Mdot_in_abundances(self, e): """ Inflow abundances """ if e == 'H': abund = 0.75 elif e == 'He': abund = 0.25 elif e == 'm_tot': abund = 1.0 else: abund = 0.0 return abund @property @property def _evolve_stars(self): """ Evolve stars using star list methods, and compute the total amount of ejecta from winds and supernova """ # # zero mass accumulators before evolving # for key in self.species_masses.keys(): self.Mdot_ej_masses[key] = 0.0 self.SN_ej_masses[key] = 0.0 # # advance each star one timestep # optional mass arguments mean stars add # to ejecta bins during evolution (winds and SN) # to limit number of loops through star list # self.all_stars.evolve(self.t, self.dt, ej_masses = self.Mdot_ej_masses, sn_masses = self.SN_ej_masses, special_accumulator = self.special_mass_accumulator) self.Mdot_ej = self.Mdot_ej_masses['m_tot'] * config.units.time for e in self.species_masses.keys(): self.Mdot_ej_masses[e] *= config.units.time return # # set total dM/dt from all stellar winds # # self.Mdot_ej = 0.0 # mass_loss_rate = self.all_stars.property_asarray('Mdot_ej') * config.units.time # self.Mdot_ej = np.sum( mass_loss_rate ) # # set dM/dt for all species # add up SN ejecta # # i = 0 # for e in self.species_masses.iterkeys(): # # add wind ejecta abundaces from "stars" and stars that may have formed SN # but were alive for part of timestep. # # self.Mdot_ej_masses[e] = np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'star') * self.all_stars.property_asarray('Mdot_ej','star')) # self.Mdot_ej_masses[e] += np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'new_WD') * self.all_stars.property_asarray('Mdot_ej', 'new_WD')) # self.Mdot_ej_masses[e] += np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'new_remnant') * self.all_stars.property_asarray('Mdot_ej','new_remnant')) # self.Mdot_ej_masses[e] *= config.units.time # # self.SN_ej_masses[e] = np.sum(self.all_stars.species_asarray('SN_ej_' + e, 'new_SNIa_remnant')) # self.SN_ej_masses[e] += np.sum(self.all_stars.species_asarray('SN_ej_' + e, 'new_remnant')) # i = i + 1 # # # # return def _make_new_stars(self, M_sf = -1): """ Sample IMF to make new stars. Includes methods to handle low SFR's, i.e. when SFR * dt < maximum star mass """ # # compute the amount of gas to convert # into stars this timestep. Otherwise, make fixed # mass of stars # if (M_sf < 0.0): M_sf = self.dt * self.Mdot_sf if config.zone.use_SF_mass_reservoir and M_sf > 0.0: # # Accumulate mass into "reservoir" and wait until # this is surpassed to form stars # self._M_sf_reservoir += M_sf if (self._M_sf_reservoir > config.zone.SF_mass_reservoir_size): # sample from IMF until M_sf is reached M_sf = self._M_sf_reservoir self._M_sf_reservoir = 0.0 # reset counter else: M_sf = 0.0 elif (config.zone.use_stochastic_mass_sampling and\ M_sf < config.zone.stochastic_sample_mass) and M_sf > 0.0: # # Prevent undersampling the IMF by requiring minimum mass # threshold. Allow SF to happen stochastically when M_sf is # below this threshold # probability_of_sf = M_sf / config.zone.stochastic_sample_mass if (probability_of_sf > np.random.random()): M_sf = config.zone.stochastic_sample_mass else: M_sf = 0.0 # # Make new stars if M_gas->star > 0 # if M_sf > 0.0: # sample from IMF and sum sampled stars # to get actual star formation mass config.global_values.profiler.start_timer('make_stars-imf',True) star_masses = config.zone.imf.sample(M = M_sf) config.global_values.profiler.end_timer('make_stars-imf') M_sf = np.sum(star_masses) if config.zone.minimum_star_particle_mass > 0: select = star_masses > config.zone.minimum_star_particle_mass i_unresolved = 0 if np.size(star_masses[star_masses<=config.zone.minimum_star_particle_mass]) > 0: i_unresolved = 1 # add each new star to the star list ids = np.zeros(np.size(star_masses[select]) + i_unresolved) if np.size(ids) == 1: ids = [ids] i = 0 config.global_values.profiler.start_timer('make_stars-add',True) for i,m in enumerate(star_masses[select]): ids[i] = self._assign_particle_id() self.all_stars.add_new_star( star.Star(M=m,Z=self.Z, abundances=self.abundances, tform=self.t,id=ids[i])) if i_unresolved > 0: if i > 0: i = i + 1 ids[i] = self._assign_particle_id() M_unresolved = np.sum( star_masses[star_masses<=config.zone.minimum_star_particle_mass]) self.all_stars.add_new_star( star.Star(M=M_unresolved,Z=self.Z, abundances=self.abundances,tform=self.t, id= ids[i], star_type = "unresolved_star")) config.global_values.profiler.end_timer('make_stars-add') else: # add each new star to the star list ids = np.zeros(np.size(star_masses)) for i,m in enumerate(star_masses): ids[i] = self._assign_particle_id() self.all_stars.add_new_star( star.Star(M=m, Z=self.Z, abundances=self.abundances, tform=self.t,id=ids[i])) return M_sf def _assign_particle_id(self): """ Generates unique, consecutive ID for particle """ if (not hasattr(self, '_global_id_counter')): self._global_id_counter = 0 num = self._global_id_counter self._global_id_counter += 1 return num def _compute_mdot_dm(self): """ For cosmological simulations, computes growth of DM halo """ self.Mdot_DM = 0.0 if not config.zone.cosmological_evolution: return self.Mdot_DM = 46.1 * ( self.M_DM / 1.0E12 )**(1.1) *\ (1.0 + 1.11 * self.current_redshift) *\ np.sqrt( config.units.omega_matter * (1.0 + self.current_redshift)**3 + config.units.omega_lambda) self.Mdot_DM *= const.yr_to_s self.Mdot_DM /= config.units.time return def _compute_inflow(self): """ Compute inflow rate, as a function of outflow """ self.Mdot_in = config.zone.inflow_factor * self.Mdot_out return def _compute_outflow(self): """ Compute outflow rate, as a function of SFR """ # If either of the discrete SF sampling methods are used, # outflow should be determined by mass of stars formed, not # rate factor = config.zone.mass_loading_factor if config.zone.cosmological_evolution: factor = factor * (1.0 + self.current_redshift)**(-config.zone.mass_loading_index/2.0) elif config.zone.mass_outflow_method == 1: # mass outflow is controlled by a mass loading factor parameter if config.zone.use_SF_mass_reservoir or config.zone.use_stochastic_mass_sampling: self.Mdot_out = config.zone.mass_loading_factor * self.M_sf / self.dt else: self.Mdot_out = config.zone.mass_loading_factor * self.Mdot_sf elif config.zone.mass_outflow_method == 4: self.Mdot_out = self._interpolate_tabulated_outflow('m_tot') * config.zone.outflow_factor * self.Mdot_sf * self.M_gas for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self.Mdot_ej_masses[e] * config.zone.wind_ejection_fraction +\ (self.SN_ej_masses[e] * config.zone.sn_ejection_fraction / self.dt) for e in ['H','He']: # throw out ambient self.Mdot_out_species[e] = self.Mdot_out * self.abundances[e] elif config.zone.mass_outflow_method == 2 or config.zone.mass_outflow_method == 3: # these are fractional outflow rates: self.Mdot_out = self._interpolate_tabulated_outflow('m_tot') # get total outflow rate for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self._interpolate_tabulated_outflow(e) # for each species if config.zone.mass_outflow_method == 2: # outflow depends on sfr # multiply by SFR and current total amount of each species self.Mdot_out = self.Mdot_out * self.Mdot_sf * self.M_gas for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self.Mdot_out_species[e] * self.Mdot_sf * (self.M_gas * self.abundances[e]) else: # outflow is a fixed fraction of injection - use mass loading factor for total, H, and He self.Mdot_out = config.zone.mass_loading_factor * (self.M_sf / self.dt) for e in self.abundances.keys(): self.Mdot_out_species[e] = (self.Mdot_ej_masses[e] + self.SN_ej_masses[e]) / self.dt # converted to a rate for consistency #if 'H' in self.Mdot_out_species.keys(): self.Mdot_out_species['H'] = self.Mdot_out * self.abundances['H'] #if 'He' in self.Mdot_out_species.keys(): self.Mdot_out_species['He'] = self.Mdot_out * self.abundances['He'] return @property def _compute_sfr(self): """ Compute SFR using method set in config """ if config.zone.star_formation_method == 0: # no star formation self.Mdot_sf = 0.0 elif config.zone.star_formation_method == 1: # constant, user supplied SFR self.Mdot_sf = config.zone.constant_SFR elif config.zone.star_formation_method == 2 : self.Mdot_sf = config.zone.SFR_efficiency * self.M_gas elif config.zone.star_formation_method == 3: self.Mdot_sf = config.zone.SFR_dyn_efficiency * self.M_gas / self.t_dyn elif config.zone.star_formation_method == 4 : # interpolate SFR from tabulated SFH self.Mdot_sf = self._interpolate_SFR() return def _check_output(self, force = False): """ Checks output conditions, output if any are met """ if force: self.write_output() self.write_full_pickle() self.write_summary_output() return # # Otherwise output based on user supplied conditions # # # check for full write out # if( (self.t - self._t_last_dump) >= config.io.dt_dump and\ config.io.dt_dump > 0 ): self._t_last_dump = self.t self.write_output() if( self._cycle_number == 0 or\ ((self._cycle_number - self._cycle_last_dump) >= config.io.cycle_dump )\ and config.io.cycle_dump > 0 ): self._cycle_last_dump = self._cycle_number self.write_output() if( (self.t - self._t_last_pickle) >= config.io.dt_pickle and\ config.io.dt_pickle > 0 ): self._t_last_pickle = self.t self.write_full_pickle() if( self._cycle_number == 0 or\ ((self._cycle_number - self._cycle_last_pickle) >= config.io.cycle_pickle )\ and config.io.cycle_pickle > 0 ): self._cycle_last_pickle = self._cycle_number self.write_full_pickle() # # now check for partial (summary) writes # if( self._cycle_number == 0 or\ (self._cycle_number - self._cycle_last_summary >= config.io.cycle_summary)\ and config.io.cycle_summary > 0): self._cycle_last_summary = self._cycle_number self.write_summary_output() if( ((self.t - self._t_last_summary) > config.io.dt_summary) and config.io.dt_summary > 0 ): self._t_last_summary = self.t self.write_summary_output() return def write_output(self): """ Output the full information needed to reconstruct the simulation. This is the mass, metallicity, birth mass, age, abundance, and type for each star, along with the current gas mass, dark matter mass, sfr, and gas abundances. """ # make an HDF5 file to write out to name = config.io.dump_output_basename + "_%0004i"%(self._output_number) + '.h5' hf = h5py.File(name, 'w') zone_grp = hf.create_group('zone') star_grp = hf.create_group('star') params = hf.create_group('parameters') # save parameters for param_list, grpname in [ (config.units,'units'),\ (config.zone,'zone'),\ (config.stars,'stars'),\ (config.io,'io'), (config.data,'data_table')]: subgrp = params.create_group(grpname) for p in dir(param_list): # There may be a better way to do this, but I don't want to have # to explicityly state any params, just print all. Need to skip # all objects or functions though if ('__' in p) or\ callable( getattr(param_list, p))\ or (p[0] == '_') or p == 'imf': continue #print p, getattr(param_list,p) val = getattr(param_list,p) if val is None: val = "None" subgrp.attrs[p] = val # # save meta-data as attributes # self._accumulate_summary_data() hf.attrs['current_time'] = self.t # # Save zone parameters. This is anything to do with gas or DM # properties zone_grp.attrs['M_gas'] = self.M_gas zone_grp.attrs['M_DM'] = self.M_DM zone_grp.attrs['M_star'] = self._summary_data['M_star'] zone_grp.attrs['M_star_o'] = self._summary_data['M_star_o'] zone_grp.attrs['Z_gas'] = self.Z for e in self.abundances.keys(): zone_grp.attrs[e] = self.abundances[e] zone_grp.attrs[e + '_mass'] = self.species_masses[e] # # Save star parameters as lists of values # star_dict = {} # OrderedDict() _gather_properties = { 'mass' : 'mass', 'birth_mass' : 'birth_mass', 'metallicity' : 'metallicity', 'age' : 'age'} for k in _gather_properties: star_dict[k] = np.asarray(self.all_stars.property_asarray( _gather_properties[k])) star_dict['type'] = np.asarray(self.all_stars.property_asarray('type')).astype('S') Nstars = np.size(star_dict['mass']) if Nstars > 1: # there has to be a better way to do this... but various iterations # of the below did not work b/c of the different variable types... # doing this the slow way...... # star_data = [None]*Nstars # for i in np.arange(Nstars): # star_data[i] = (star_dict['id'][i], star_dict['type'][i], # star_dict['initial_mass'][i], # star_dict['masses'][i], star_dict['age'][i], # star_dict['metallicity'][i]) # star_data = np.array(star_data, dtype = [ ('id',star_dict['id'].dtype), # ('type',star_dict['type'].dtype), # ('birth_mass',star_dict['initial_mass'].dtype), # ('mass',star_dict['masses'].dtype), # ('age',star_dict['age'].dtype), # ('metallicity',star_dict['metallicity'].dtype)]) # star_data = np.column_stack( # (star_dict['masses'].astype('float64'), star_dict['initial_mass'].astype('float64'), # star_dict['metallicity'].astype('float64'), star_dict['id'].astype('int64'), # star_dict['type'].astype('str'), # star_dict['age'].astype('float64'))).ravel().view([ ('mass', np.dtype('float64')), # ('initial_mass', np.dtype('float64')), # ('metallicity', np.dtype('float64')), # ('id', np.dtype('int64')), # ('type', np.dtype('str')), # ('age', np.dtype('float64'))]) for k in star_dict.keys(): star_grp.create_dataset(k, data=star_dict[k]) else: Nstars = 0 star_data = np.zeros(1) for k in star_dict.keys(): star_grp.create_dataset(k, data = star_data) star_grp.attrs['number_of_stars'] = Nstars hf.close() self._output_number += 1 return def write_full_pickle(self): """ Pickle current simulation """ name = str(config.io.pickle_output_basename + "_%00004i"%(self.pickle_output_number)) _my_print("Writing full dump output as " + name + " at time t = %4.4f"%(self.t)) pickle.dump( self , open(name, "wb"), -1) self.pickle_output_number += 1 return def _accumulate_summary_data(self): """ Set up list of all of the data to output. Sum over particle properties to do this. """ self._summary_data = {} # OrderedDict() self._summary_data['t'] = self.t self._summary_data['M_gas'] = self.M_gas self._summary_data['M_DM'] = self.M_DM self._summary_data['M_star'] = np.sum(self.all_stars.M()) self._summary_data['M_star_o'] = np.sum( self.all_stars.M_o()) self._summary_data['Z_gas'] = self.Z self._summary_data['Z_star'] = np.average( self.all_stars.Z() ) self._summary_data['N_star'] = self.N_stars self._summary_data['N_SNIa'] = self.N_SNIa self._summary_data['N_SNII'] = self.N_SNII sum_names = ['Mdot_ej', 'L_FUV', 'L_LW', 'Q0', 'Q1'] for n in sum_names: self._summary_data[n] = np.sum(np.asarray(self.all_stars.property_asarray(n))) self._summary_data['L_bol'] = np.sum(np.asarray(self.all_stars.property_asarray('luminosity'))) self._summary_data['L_wind'] = np.sum(np.asarray(self.all_stars.property_asarray('mechanical_luminosity'))) self._summary_data['L_Q0'] = np.sum(self.all_stars.property_asarray('Q0') * self.all_stars.property_asarray('E0')) self._summary_data['L_Q1'] = np.sum(self.all_stars.property_asarray('Q1') * self.all_stars.property_asarray('E1')) # now do all of the abundances for e in self.abundances.keys(): self._summary_data[e] = self.abundances[e] self._summary_data[e + '_mass'] = self.species_masses[e] self._summary_data[e + '_halo_mass'] = self.halo_masses[e] for key in self.special_mass_accumulator.keys(): self._summary_data[key] = self.special_mass_accumulator[key] if config.io.radiation_binned_output: condition_1 = {'mass': lambda x : (x.M_o >= 1.0) * (x.M_o < 8.0) * (x.properties['type'] == 'star')} condition_2 = {'mass': lambda x : (x.M_o >= 8.0) * (x.M_o < 16.0) * (x.properties['type'] == 'star')} condition_3 = {'mass': lambda x : (x.M_o >= 16.0) * (x.M_o < 24.0) * (x.properties['type'] == 'star')} condition_4 = {'mass': lambda x : (x.M_o >= 24.0) * (x.M_o < 1000.0) * (x.properties['type'] == 'star')} self._summary_data['low_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_1) *\ self.all_stars.property_asarray('E0', subset_condition = condition_1)) self._summary_data['int_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_2) *\ self.all_stars.property_asarray('E0', subset_condition = condition_2)) self._summary_data['high_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_3) *\ self.all_stars.property_asarray('E0', subset_condition = condition_3)) self._summary_data['vhigh_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_4) *\ self.all_stars.property_asarray('E0', subset_condition = condition_4)) self._summary_data['low_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_1) *\ self.all_stars.property_asarray('E1', subset_condition = condition_1)) self._summary_data['int_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_2) *\ self.all_stars.property_asarray('E1', subset_condition = condition_2)) self._summary_data['high_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_3) *\ self.all_stars.property_asarray('E1', subset_condition = condition_3)) self._summary_data['vhigh_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_4) *\ self.all_stars.property_asarray('E1', subset_condition = condition_4)) FUV_1 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_1) FUV_2 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_2) FUV_3 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_3) FUV_4 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_4) self._summary_data['low_mass_LFUV'] = np.sum(FUV_1) self._summary_data['int_mass_LFUV'] = np.sum(FUV_2) self._summary_data['high_mass_LFUV'] = np.sum(FUV_3) self._summary_data['vhigh_mass_LFUV'] = np.sum(FUV_4) LW_1 = self.all_stars.property_asarray('L_LW', subset_condition = condition_1) LW_2 = self.all_stars.property_asarray('L_LW', subset_condition = condition_2) LW_3 = self.all_stars.property_asarray('L_LW', subset_condition = condition_3) LW_4 = self.all_stars.property_asarray('L_LW', subset_condition = condition_4) self._summary_data['low_mass_LLW'] = np.sum(LW_1) self._summary_data['int_mass_LLW'] = np.sum(LW_2) self._summary_data['high_mass_LLW'] = np.sum(LW_3) self._summary_data['vhigh_mass_LLW'] = np.sum(LW_4) self._summary_data['low_mass_count'] = np.size(FUV_1) self._summary_data['int_mass_count'] = np.size(FUV_2) self._summary_data['high_mass_count'] = np.size(FUV_3) self._summary_data['vhigh_mass_count'] = np.size(FUV_4) return def write_summary_output(self): """ Write out summary output by appending to ASCII file. Filename is overwritten at first write out, so be careful. """ self._accumulate_summary_data() ncol = np.size(self._summary_data.keys()) if self._summary_output_number == 0: # print the header only once header = " " + " ".join(list(self._summary_data.keys())) + "\n" f = open(config.io.summary_output_filename,'w') f.write(header) else: f = open(config.io.summary_output_filename, 'a') fmt = "%5.5E "*ncol + "\n" # output_val = list(self._summary_data.values()) # f.write(fmt% ()) #print(self._summary_data) #print(self._summary_data.values()) f.writelines("%5.5E "% x for x in self._summary_data.values() ) f.write("\n") self._summary_output_number += 1 self._summary_data.clear() f.close()

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""" Author : A. Emerick Date : May 2016 Purpose: """ __author__ = "aemerick <emerick@astro.columbia.edu>" # external import numpy as np #from collections import OrderedDict import os, h5py from scipy.interpolate import interp1d try: import dill as pickle except: print("WARNING: Dill unavailable, attempting to use pickle, which may crash") try: import pickle as pickle except: print("WARNING: cPickle unavailable, using pickle - data dumps will be slow") import pickle # internal from . import imf as imf #from . import star as star from onezone.cython_ext import cython_star as star from . import config as config from .constants import CONST as const from . import performance_tools as perf def restart(filename): """ Restart evolution from chosen picked output file """ zone = pickle.load( open(filename, 'r')) zone.evolve() return class Zone: """ Zone Class Single zone gas reservoir attached to star formation and chemical enrichment models. Parameters for a given simulation can be set using config. Zone initializes a simulation using initial conditions parameters set in config. Once initialized and abundances are set, simulation can be evolved: >>> sim = Zone() >>> sim.set_initial_abundances(list_of_element_names) >>> sim.evolve() I/O controlled by config parameters, but can be done manually with a full (pickle) dump or an output of summary statistics: >>> sim.write_full_pickle() >>> sim.write_summary_output() """ def __init__(self): #if config.global_values.profile_performance: config.global_values.profiler =\ perf.PerformanceTimer(config.global_values.profile_performance) # # important values and stars # self.M_gas = config.zone.initial_gas_mass self.M_DM = config.zone.initial_dark_matter_mass self.all_stars = star.StarList() self.Z = config.zone.initial_metallicity self._M_sf_reservoir = 0.0 self._SFR_initialized = False # only for SF method 4 self._mass_loading_initialized = False # only for mass_outflow_method 2 self.initial_abundances = config.zone.initial_abundances self.species_masses = {} # OrderedDict() self.halo_masses = {} # add other phase models? # # some private things # self._t_last_dump = 0.0 self._t_last_summary = 0.0 self._t_last_pickle = 0.0 self._cycle_number = 0 self._cycle_last_dump = 0 self._cycle_last_summary = 0 self.pickle_output_number = 0 self._summary_output_number = 0 self._output_number = 0 self.t = config.zone.t_o self.dt = config.zone.dt self._summary_data = {} self.Mdot_ej = 0.0 self.Mdot_DM = 0.0 self.Mdot_out = 0.0 self.Mdot_out_species = {} # OrderedDict() self.Mdot_ej_masses = {} # OrderedDict() self.SN_ej_masses = {} # OrderedDict() self.N_SNIa = 0 self.N_SNII = 0 # # Create stars if starting with initial cluster # for e in config.zone.species_to_track: self.species_masses[e] = 0.0 self.Mdot_out_species[e] = 0.0 self.halo_masses[e] = 0.0 if (config.zone.initial_stellar_mass > 0.0): self._make_new_stars( M_sf = config.zone.initial_stellar_mass ) self._compute_dt() self._update_globals() return def set_initial_abundances(self, elements, abundances = None): """ Set initial abundances using a list of desired elements and associated abundances. If no abundances are provided, all are set to zero except H and He. Abundances dict does not have to be complete """ self.initial_abundances = {} # OrderedDict() if abundances == None: abundances = {'empty' : 0.0} for e in elements: if e in abundances.keys(): self.initial_abundances[e] = abundances[e] elif e == 'H': self.initial_abundances[e] = 0.75*(1.0 - self.Z) elif e == 'He': self.initial_abundances[e] = 0.25*(1.0 - self.Z) elif e == 'm_metal': self.initial_abundances[e] = self.Z elif e == 'm_tot': self.initial_abundances[e] = 1.0 else: self.initial_abundances[e] = 0.0 for e in self.initial_abundances.keys(): self.species_masses[e] = self.M_gas * self.initial_abundances[e] self.halo_masses[e] = 0.0 # # One day, set this as list with second list of conditionals # so one can (at runtime) arbitrarily track on any condition # self.special_mass_accumulator = {} # OrderedDict() self.special_mass_accumulator['m_massive'] = 0.0 return None def _accumulate_new_sn(self): """ Looks through all stars, checking to see if any new SN or SNIa occured in current timestep. Adds these to the counters """ star_type = list(self.all_stars.property_asarray('type')) #if np.size(star_type) > 1: self.N_SNIa += star_type.count('new_SNIa_remnant') self.N_SNII += star_type.count('new_remnant') return def evolve(self): """ Evolves the system until the end time assigned in config, using a constant timestep. This handles the formation of new stars, gas inflow and outflow, enrichment from stars, and outputs. """ config.global_values.profiler.start_timer("total_time",True) while self.t <= config.zone.t_final: config.global_values.profiler.start_timer('compute_dt') self._compute_dt() config.global_values.profiler.end_timer('compute_dt') # # Check if output conditions are met # config.global_values.profiler.start_timer('check_output') self._check_output() config.global_values.profiler.end_timer('check_output') # # I) Evolve stars, computing ejecta rates and abundances # config.global_values.profiler.start_timer('evolve_stars') self._evolve_stars() config.global_values.profiler.end_timer('evolve_stars') # # II) Sum up and store number of supernovae # config.global_values.profiler.start_timer('accumulate_sn') self._accumulate_new_sn() config.global_values.profiler.end_timer('accumulate_sn') # # III) Compute SFR and make new stars # config.global_values.profiler.start_timer('compute_sfr') self._compute_sfr() config.global_values.profiler.end_timer('compute_sfr') config.global_values.profiler.start_timer('make_stars') self.M_sf = self._make_new_stars() config.global_values.profiler.end_timer('make_stars') # # IV) Compute inflow and outflow # config.global_values.profiler.start_timer('outflow_inflow_mdot') self._compute_outflow() self._compute_inflow() self._compute_mdot_dm() config.global_values.profiler.end_timer('outflow_inflow_mdot') # # V) Add/remove gas from zone due to inflow, # outflow, SF, and stellar ejecta # abundances = self.abundances temp1 = abundances['m_metal'] * 1.0 new_gas_mass = self.M_gas + (self.Mdot_in + self.Mdot_ej_masses['m_tot'] -\ self.Mdot_out) * self.dt - self.M_sf +\ self.SN_ej_masses['m_tot'] # # VI) Check if reservoir is empty # if self.M_gas <= 0: self.M_gas = 0.0 _my_print("Gas in zone depleted. Ending simulation") break # # VII) Compute increase / decrease of individual abundances # for e in self.species_masses.keys(): self.species_masses[e] = self.species_masses[e] + (self.Mdot_in * self.Mdot_in_abundances(e) +\ self.Mdot_ej_masses[e] -\ self.Mdot_out_species[e]) * self.dt -\ self.M_sf * abundances[e] + self.SN_ej_masses[e] self.halo_masses[e] = self.halo_masses[e] + self.Mdot_out_species[e] * self.dt # no halo accretion for now. self.M_gas = new_gas_mass self.M_DM = self.M_DM + self.Mdot_DM * self.dt # # VII) i) ensure metallicity is consistent with new abundances # self._update_metallicity() # # VIII) End of evolution, increment counters # config.global_values.profiler.start_timer('update_globals') self.t += self.dt self._cycle_number += 1 self._update_globals() config.global_values.profiler.end_timer('update_globals') outstr = "======================================================\n" +\ "===== Cycle = %00005i time = %5.5E =======\n"%(self._cycle_number,self.t) +\ "======================================================\n" config.global_values.profiler.write_performance(outstr=outstr) # # At end of simulation, force summary and dump # outputs # config.global_values.profiler.end_timer("total_time") config.global_values.profiler.write_performance(outstr=outstr) self._check_output(force=True) self._clean_up() return def _clean_up(self): # delete / close things that need closing here. Call other # clean-up routines config.io._clean_up() return def _update_globals(self): config.global_values.time = self.t return @property def current_redshift(self): t_h = config.units.hubble_time z = (2.0 * t_h / (3.0*self.t))**(2.0/3.0) - 1.0 return z def _update_metallicity(self): if config.zone.constant_metallicity: return self.Z = self.species_masses['m_metal'] / self.M_gas return @property def abundances(self): """ Returns dictionary of abundances """ abund = {} for x in self.species_masses.keys(): abund[x] = self.species_masses[x] / self.M_gas return abund @property def halo_abundances(self): abund={} for x in self.species_masses.keys(): abund[x] = self.halo_masses[x] / self.halo_masses['m_tot'] return abund def Mdot_in_abundances(self, e): """ Inflow abundances """ if e == 'H': abund = 0.75 elif e == 'He': abund = 0.25 elif e == 'm_tot': abund = 1.0 else: abund = 0.0 return abund @property def N_stars(self): return self.all_stars.N_stars() @property def M_stars(self): return np.sum(self.all_stars.M()) def _compute_dt(self): if config.zone.adaptive_timestep: lifetimes = np.asarray(self.all_stars.property_asarray('lifetime','star')) if np.size(lifetimes) > 1: max_dt = config.zone.max_dt * const.Myr / config.units.time min_lifetime = np.min( lifetimes ) / (config.units.time) self.dt = np.min( [min_lifetime / (1.0 * config.zone.timestep_safety_factor), max_dt] ) return def _evolve_stars(self): """ Evolve stars using star list methods, and compute the total amount of ejecta from winds and supernova """ # # zero mass accumulators before evolving # for key in self.species_masses.keys(): self.Mdot_ej_masses[key] = 0.0 self.SN_ej_masses[key] = 0.0 # # advance each star one timestep # optional mass arguments mean stars add # to ejecta bins during evolution (winds and SN) # to limit number of loops through star list # self.all_stars.evolve(self.t, self.dt, ej_masses = self.Mdot_ej_masses, sn_masses = self.SN_ej_masses, special_accumulator = self.special_mass_accumulator) self.Mdot_ej = self.Mdot_ej_masses['m_tot'] * config.units.time for e in self.species_masses.keys(): self.Mdot_ej_masses[e] *= config.units.time return # # set total dM/dt from all stellar winds # # self.Mdot_ej = 0.0 # mass_loss_rate = self.all_stars.property_asarray('Mdot_ej') * config.units.time # self.Mdot_ej = np.sum( mass_loss_rate ) # # set dM/dt for all species # add up SN ejecta # # i = 0 # for e in self.species_masses.iterkeys(): # # add wind ejecta abundaces from "stars" and stars that may have formed SN # but were alive for part of timestep. # # self.Mdot_ej_masses[e] = np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'star') * self.all_stars.property_asarray('Mdot_ej','star')) # self.Mdot_ej_masses[e] += np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'new_WD') * self.all_stars.property_asarray('Mdot_ej', 'new_WD')) # self.Mdot_ej_masses[e] += np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'new_remnant') * self.all_stars.property_asarray('Mdot_ej','new_remnant')) # self.Mdot_ej_masses[e] *= config.units.time # # self.SN_ej_masses[e] = np.sum(self.all_stars.species_asarray('SN_ej_' + e, 'new_SNIa_remnant')) # self.SN_ej_masses[e] += np.sum(self.all_stars.species_asarray('SN_ej_' + e, 'new_remnant')) # i = i + 1 # # # # return def _make_new_stars(self, M_sf = -1): """ Sample IMF to make new stars. Includes methods to handle low SFR's, i.e. when SFR * dt < maximum star mass """ # # compute the amount of gas to convert # into stars this timestep. Otherwise, make fixed # mass of stars # if (M_sf < 0.0): M_sf = self.dt * self.Mdot_sf if config.zone.use_SF_mass_reservoir and M_sf > 0.0: # # Accumulate mass into "reservoir" and wait until # this is surpassed to form stars # self._M_sf_reservoir += M_sf if (self._M_sf_reservoir > config.zone.SF_mass_reservoir_size): # sample from IMF until M_sf is reached M_sf = self._M_sf_reservoir self._M_sf_reservoir = 0.0 # reset counter else: M_sf = 0.0 elif (config.zone.use_stochastic_mass_sampling and\ M_sf < config.zone.stochastic_sample_mass) and M_sf > 0.0: # # Prevent undersampling the IMF by requiring minimum mass # threshold. Allow SF to happen stochastically when M_sf is # below this threshold # probability_of_sf = M_sf / config.zone.stochastic_sample_mass if (probability_of_sf > np.random.random()): M_sf = config.zone.stochastic_sample_mass else: M_sf = 0.0 # # Make new stars if M_gas->star > 0 # if M_sf > 0.0: # sample from IMF and sum sampled stars # to get actual star formation mass config.global_values.profiler.start_timer('make_stars-imf',True) star_masses = config.zone.imf.sample(M = M_sf) config.global_values.profiler.end_timer('make_stars-imf') M_sf = np.sum(star_masses) if config.zone.minimum_star_particle_mass > 0: select = star_masses > config.zone.minimum_star_particle_mass i_unresolved = 0 if np.size(star_masses[star_masses<=config.zone.minimum_star_particle_mass]) > 0: i_unresolved = 1 # add each new star to the star list ids = np.zeros(np.size(star_masses[select]) + i_unresolved) if np.size(ids) == 1: ids = [ids] i = 0 config.global_values.profiler.start_timer('make_stars-add',True) for i,m in enumerate(star_masses[select]): ids[i] = self._assign_particle_id() self.all_stars.add_new_star( star.Star(M=m,Z=self.Z, abundances=self.abundances, tform=self.t,id=ids[i])) if i_unresolved > 0: if i > 0: i = i + 1 ids[i] = self._assign_particle_id() M_unresolved = np.sum( star_masses[star_masses<=config.zone.minimum_star_particle_mass]) self.all_stars.add_new_star( star.Star(M=M_unresolved,Z=self.Z, abundances=self.abundances,tform=self.t, id= ids[i], star_type = "unresolved_star")) config.global_values.profiler.end_timer('make_stars-add') else: # add each new star to the star list ids = np.zeros(np.size(star_masses)) for i,m in enumerate(star_masses): ids[i] = self._assign_particle_id() self.all_stars.add_new_star( star.Star(M=m, Z=self.Z, abundances=self.abundances, tform=self.t,id=ids[i])) return M_sf def _assign_particle_id(self): """ Generates unique, consecutive ID for particle """ if (not hasattr(self, '_global_id_counter')): self._global_id_counter = 0 num = self._global_id_counter self._global_id_counter += 1 return num def _compute_mdot_dm(self): """ For cosmological simulations, computes growth of DM halo """ self.Mdot_DM = 0.0 if not config.zone.cosmological_evolution: return self.Mdot_DM = 46.1 * ( self.M_DM / 1.0E12 )**(1.1) *\ (1.0 + 1.11 * self.current_redshift) *\ np.sqrt( config.units.omega_matter * (1.0 + self.current_redshift)**3 + config.units.omega_lambda) self.Mdot_DM *= const.yr_to_s self.Mdot_DM /= config.units.time return def _compute_inflow(self): """ Compute inflow rate, as a function of outflow """ self.Mdot_in = config.zone.inflow_factor * self.Mdot_out return def _compute_outflow(self): """ Compute outflow rate, as a function of SFR """ # If either of the discrete SF sampling methods are used, # outflow should be determined by mass of stars formed, not # rate factor = config.zone.mass_loading_factor if config.zone.cosmological_evolution: factor = factor * (1.0 + self.current_redshift)**(-config.zone.mass_loading_index/2.0) elif config.zone.mass_outflow_method == 1: # mass outflow is controlled by a mass loading factor parameter if config.zone.use_SF_mass_reservoir or config.zone.use_stochastic_mass_sampling: self.Mdot_out = config.zone.mass_loading_factor * self.M_sf / self.dt else: self.Mdot_out = config.zone.mass_loading_factor * self.Mdot_sf elif config.zone.mass_outflow_method == 4: self.Mdot_out = self._interpolate_tabulated_outflow('m_tot') * config.zone.outflow_factor * self.Mdot_sf * self.M_gas for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self.Mdot_ej_masses[e] * config.zone.wind_ejection_fraction +\ (self.SN_ej_masses[e] * config.zone.sn_ejection_fraction / self.dt) for e in ['H','He']: # throw out ambient self.Mdot_out_species[e] = self.Mdot_out * self.abundances[e] elif config.zone.mass_outflow_method == 2 or config.zone.mass_outflow_method == 3: # these are fractional outflow rates: self.Mdot_out = self._interpolate_tabulated_outflow('m_tot') # get total outflow rate for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self._interpolate_tabulated_outflow(e) # for each species if config.zone.mass_outflow_method == 2: # outflow depends on sfr # multiply by SFR and current total amount of each species self.Mdot_out = self.Mdot_out * self.Mdot_sf * self.M_gas for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self.Mdot_out_species[e] * self.Mdot_sf * (self.M_gas * self.abundances[e]) else: # outflow is a fixed fraction of injection - use mass loading factor for total, H, and He self.Mdot_out = config.zone.mass_loading_factor * (self.M_sf / self.dt) for e in self.abundances.keys(): self.Mdot_out_species[e] = (self.Mdot_ej_masses[e] + self.SN_ej_masses[e]) / self.dt # converted to a rate for consistency #if 'H' in self.Mdot_out_species.keys(): self.Mdot_out_species['H'] = self.Mdot_out * self.abundances['H'] #if 'He' in self.Mdot_out_species.keys(): self.Mdot_out_species['He'] = self.Mdot_out * self.abundances['He'] return @property def t_dyn(self): if not config.zone.cosmological_evolution: _my_print("Error: Cannot compute cosmological dynamical time with non-cosmological simulation") raise NotImplementedError return 0.1 * config.units.hubble_time * (1.0 + self.current_redshift)**(-3.0/2.0) def _compute_sfr(self): """ Compute SFR using method set in config """ if config.zone.star_formation_method == 0: # no star formation self.Mdot_sf = 0.0 elif config.zone.star_formation_method == 1: # constant, user supplied SFR self.Mdot_sf = config.zone.constant_SFR elif config.zone.star_formation_method == 2 : self.Mdot_sf = config.zone.SFR_efficiency * self.M_gas elif config.zone.star_formation_method == 3: self.Mdot_sf = config.zone.SFR_dyn_efficiency * self.M_gas / self.t_dyn elif config.zone.star_formation_method == 4 : # interpolate SFR from tabulated SFH self.Mdot_sf = self._interpolate_SFR() return def _interpolate_tabulated_outflow(self, species): if not self._mass_loading_initialized: self._initialize_tabulated_mass_outflow() t = self.t + self.dt*0.5 if np.size(self._tabulated_outflow_t) > 1: # allow constant if t < self._tabulated_outflow_t[0]: _my_print("Current time below minimum time in tabulated outflow rates %3.3E %3.3E"%(t, self._tabulated_outflow_t[0])) raise ValueError if t > self._tabulated_outflow_t[-1]: _my_print("Current time above maximum time in tabulated outflow %3.3E %3.3E"%(t, self._tabulated_outflow_t[-1])) _my_print("Assuming this is expected behavior. Saving and exiting.") self._check_output(force = True) raise ValueError return self._outflow_interpolation_generator(species)(t) def _interpolate_SFR(self): if not self._SFR_initialized: self._initialize_tabulated_sfr() t = self.t + self.dt*0.5 if t < self._tabulated_SFR_t[0]: _my_print("Current time below minimum time in tabulated SFR %3.3E %3.3E"%(t, self._tabulated_SFR_t[0])) raise ValueError if t > self._tabulated_SFR_t[-1]: if t - 0.5*self.dt <= self._tabulated_SFR_t[-1]: # likely on final time step t = self.t else: _my_print("Current time above maximum time in tabulated SFR %3.3E %3.3E"%(t, self._tabulated_SFR_t[-1])) _my_print("Assuming this is expected behavior. Saving and exiting.") self._check_output(force = True) raise ValueError return self._SFR_interpolation_function(t) def _initialize_tabulated_sfr(self): if not (config.zone.SFR_filename is None): if not os.path.isfile(config.zone.SFR_filename): _my_print(config.zone.SFR_filename + " does not exist. Must set to use tabulated SFR") raise ValueError else: _my_print("Must set config.zone.SFR_file to use tabulated SFR") raise ValueError data = np.genfromtxt(config.zone.SFR_filename, names = True) self._tabulated_SFR_t = data['t'] * const.Myr / config.units.time # in Myr self._tabulated_SFR = data['SFR'] / const.yr_to_s * config.units.time self._SFR_interpolation_function = interp1d(self._tabulated_SFR_t, self._tabulated_SFR, kind = 'linear') self._SFR_initialized = True return def _initialize_tabulated_mass_outflow(self): if not (config.zone.outflow_filename is None): if not os.path.isfile(config.zone.outflow_filename): _my_print(config.zone.outflow_filename + " does not exist. Must set properly to use tabulated outflow rates") raise ValueError else: _my_print("Must set config.zone.outflow_filename to use tabulated outflow rates") raise ValueError # skip header assuming this is generated by galaxy_analysis generation utilities data = np.genfromtxt(config.zone.outflow_filename, names = True, skip_header = 5) self._tabulated_outflow_t = data['t'] * const.Myr / config.units.time species = [x for x in data.dtype.names if x is not 't'] self._tabulated_outflow = {} for e in species: self._tabulated_outflow[e] = data[e] for e in ['H','He']: # if not provided, take H and He outflows as the same as the ambient / total # mass outflow. Fine if majority of H/He ejected is ambient ISM (likely). # this is o.k. to do since outflow rates are scaled fractional if not (e in self._tabulated_outflow.keys()): self._tabulated_outflow[e] = 1.0*self._tabulated_outflow['m_tot'] if np.size(data['t']) == 1: # for constant values (no time evolution) self._outflow_interpolation_generator = lambda _e : lambda t : self._tabulated_outflow[_e] else: self._outflow_interpolation_generator = lambda _e : interp1d(self._tabulated_outflow_t, self._tabulated_outflow[_e], kind = 'linear') self.Mdot_out_species = {} # set up dictionary to store outflow rates for e in species + ['H','He']: self.Mdot_out_species[e] = 0.0 self._mass_loading_initialized = True return def _check_output(self, force = False): """ Checks output conditions, output if any are met """ if force: self.write_output() self.write_full_pickle() self.write_summary_output() return # # Otherwise output based on user supplied conditions # # # check for full write out # if( (self.t - self._t_last_dump) >= config.io.dt_dump and\ config.io.dt_dump > 0 ): self._t_last_dump = self.t self.write_output() if( self._cycle_number == 0 or\ ((self._cycle_number - self._cycle_last_dump) >= config.io.cycle_dump )\ and config.io.cycle_dump > 0 ): self._cycle_last_dump = self._cycle_number self.write_output() if( (self.t - self._t_last_pickle) >= config.io.dt_pickle and\ config.io.dt_pickle > 0 ): self._t_last_pickle = self.t self.write_full_pickle() if( self._cycle_number == 0 or\ ((self._cycle_number - self._cycle_last_pickle) >= config.io.cycle_pickle )\ and config.io.cycle_pickle > 0 ): self._cycle_last_pickle = self._cycle_number self.write_full_pickle() # # now check for partial (summary) writes # if( self._cycle_number == 0 or\ (self._cycle_number - self._cycle_last_summary >= config.io.cycle_summary)\ and config.io.cycle_summary > 0): self._cycle_last_summary = self._cycle_number self.write_summary_output() if( ((self.t - self._t_last_summary) > config.io.dt_summary) and config.io.dt_summary > 0 ): self._t_last_summary = self.t self.write_summary_output() return def write_output(self): """ Output the full information needed to reconstruct the simulation. This is the mass, metallicity, birth mass, age, abundance, and type for each star, along with the current gas mass, dark matter mass, sfr, and gas abundances. """ # make an HDF5 file to write out to name = config.io.dump_output_basename + "_%0004i"%(self._output_number) + '.h5' hf = h5py.File(name, 'w') zone_grp = hf.create_group('zone') star_grp = hf.create_group('star') params = hf.create_group('parameters') # save parameters for param_list, grpname in [ (config.units,'units'),\ (config.zone,'zone'),\ (config.stars,'stars'),\ (config.io,'io'), (config.data,'data_table')]: subgrp = params.create_group(grpname) for p in dir(param_list): # There may be a better way to do this, but I don't want to have # to explicityly state any params, just print all. Need to skip # all objects or functions though if ('__' in p) or\ callable( getattr(param_list, p))\ or (p[0] == '_') or p == 'imf': continue #print p, getattr(param_list,p) val = getattr(param_list,p) if val is None: val = "None" subgrp.attrs[p] = val # # save meta-data as attributes # self._accumulate_summary_data() hf.attrs['current_time'] = self.t # # Save zone parameters. This is anything to do with gas or DM # properties zone_grp.attrs['M_gas'] = self.M_gas zone_grp.attrs['M_DM'] = self.M_DM zone_grp.attrs['M_star'] = self._summary_data['M_star'] zone_grp.attrs['M_star_o'] = self._summary_data['M_star_o'] zone_grp.attrs['Z_gas'] = self.Z for e in self.abundances.keys(): zone_grp.attrs[e] = self.abundances[e] zone_grp.attrs[e + '_mass'] = self.species_masses[e] # # Save star parameters as lists of values # star_dict = {} # OrderedDict() _gather_properties = { 'mass' : 'mass', 'birth_mass' : 'birth_mass', 'metallicity' : 'metallicity', 'age' : 'age'} for k in _gather_properties: star_dict[k] = np.asarray(self.all_stars.property_asarray( _gather_properties[k])) star_dict['type'] = np.asarray(self.all_stars.property_asarray('type')).astype('S') Nstars = np.size(star_dict['mass']) if Nstars > 1: # there has to be a better way to do this... but various iterations # of the below did not work b/c of the different variable types... # doing this the slow way...... # star_data = [None]*Nstars # for i in np.arange(Nstars): # star_data[i] = (star_dict['id'][i], star_dict['type'][i], # star_dict['initial_mass'][i], # star_dict['masses'][i], star_dict['age'][i], # star_dict['metallicity'][i]) # star_data = np.array(star_data, dtype = [ ('id',star_dict['id'].dtype), # ('type',star_dict['type'].dtype), # ('birth_mass',star_dict['initial_mass'].dtype), # ('mass',star_dict['masses'].dtype), # ('age',star_dict['age'].dtype), # ('metallicity',star_dict['metallicity'].dtype)]) # star_data = np.column_stack( # (star_dict['masses'].astype('float64'), star_dict['initial_mass'].astype('float64'), # star_dict['metallicity'].astype('float64'), star_dict['id'].astype('int64'), # star_dict['type'].astype('str'), # star_dict['age'].astype('float64'))).ravel().view([ ('mass', np.dtype('float64')), # ('initial_mass', np.dtype('float64')), # ('metallicity', np.dtype('float64')), # ('id', np.dtype('int64')), # ('type', np.dtype('str')), # ('age', np.dtype('float64'))]) for k in star_dict.keys(): star_grp.create_dataset(k, data=star_dict[k]) else: Nstars = 0 star_data = np.zeros(1) for k in star_dict.keys(): star_grp.create_dataset(k, data = star_data) star_grp.attrs['number_of_stars'] = Nstars hf.close() self._output_number += 1 return def write_full_pickle(self): """ Pickle current simulation """ name = str(config.io.pickle_output_basename + "_%00004i"%(self.pickle_output_number)) _my_print("Writing full dump output as " + name + " at time t = %4.4f"%(self.t)) pickle.dump( self , open(name, "wb"), -1) self.pickle_output_number += 1 return def _accumulate_summary_data(self): """ Set up list of all of the data to output. Sum over particle properties to do this. """ self._summary_data = {} # OrderedDict() self._summary_data['t'] = self.t self._summary_data['M_gas'] = self.M_gas self._summary_data['M_DM'] = self.M_DM self._summary_data['M_star'] = np.sum(self.all_stars.M()) self._summary_data['M_star_o'] = np.sum( self.all_stars.M_o()) self._summary_data['Z_gas'] = self.Z self._summary_data['Z_star'] = np.average( self.all_stars.Z() ) self._summary_data['N_star'] = self.N_stars self._summary_data['N_SNIa'] = self.N_SNIa self._summary_data['N_SNII'] = self.N_SNII sum_names = ['Mdot_ej', 'L_FUV', 'L_LW', 'Q0', 'Q1'] for n in sum_names: self._summary_data[n] = np.sum(np.asarray(self.all_stars.property_asarray(n))) self._summary_data['L_bol'] = np.sum(np.asarray(self.all_stars.property_asarray('luminosity'))) self._summary_data['L_wind'] = np.sum(np.asarray(self.all_stars.property_asarray('mechanical_luminosity'))) self._summary_data['L_Q0'] = np.sum(self.all_stars.property_asarray('Q0') * self.all_stars.property_asarray('E0')) self._summary_data['L_Q1'] = np.sum(self.all_stars.property_asarray('Q1') * self.all_stars.property_asarray('E1')) # now do all of the abundances for e in self.abundances.keys(): self._summary_data[e] = self.abundances[e] self._summary_data[e + '_mass'] = self.species_masses[e] self._summary_data[e + '_halo_mass'] = self.halo_masses[e] for key in self.special_mass_accumulator.keys(): self._summary_data[key] = self.special_mass_accumulator[key] if config.io.radiation_binned_output: condition_1 = {'mass': lambda x : (x.M_o >= 1.0) * (x.M_o < 8.0) * (x.properties['type'] == 'star')} condition_2 = {'mass': lambda x : (x.M_o >= 8.0) * (x.M_o < 16.0) * (x.properties['type'] == 'star')} condition_3 = {'mass': lambda x : (x.M_o >= 16.0) * (x.M_o < 24.0) * (x.properties['type'] == 'star')} condition_4 = {'mass': lambda x : (x.M_o >= 24.0) * (x.M_o < 1000.0) * (x.properties['type'] == 'star')} self._summary_data['low_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_1) *\ self.all_stars.property_asarray('E0', subset_condition = condition_1)) self._summary_data['int_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_2) *\ self.all_stars.property_asarray('E0', subset_condition = condition_2)) self._summary_data['high_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_3) *\ self.all_stars.property_asarray('E0', subset_condition = condition_3)) self._summary_data['vhigh_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_4) *\ self.all_stars.property_asarray('E0', subset_condition = condition_4)) self._summary_data['low_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_1) *\ self.all_stars.property_asarray('E1', subset_condition = condition_1)) self._summary_data['int_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_2) *\ self.all_stars.property_asarray('E1', subset_condition = condition_2)) self._summary_data['high_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_3) *\ self.all_stars.property_asarray('E1', subset_condition = condition_3)) self._summary_data['vhigh_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_4) *\ self.all_stars.property_asarray('E1', subset_condition = condition_4)) FUV_1 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_1) FUV_2 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_2) FUV_3 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_3) FUV_4 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_4) self._summary_data['low_mass_LFUV'] = np.sum(FUV_1) self._summary_data['int_mass_LFUV'] = np.sum(FUV_2) self._summary_data['high_mass_LFUV'] = np.sum(FUV_3) self._summary_data['vhigh_mass_LFUV'] = np.sum(FUV_4) LW_1 = self.all_stars.property_asarray('L_LW', subset_condition = condition_1) LW_2 = self.all_stars.property_asarray('L_LW', subset_condition = condition_2) LW_3 = self.all_stars.property_asarray('L_LW', subset_condition = condition_3) LW_4 = self.all_stars.property_asarray('L_LW', subset_condition = condition_4) self._summary_data['low_mass_LLW'] = np.sum(LW_1) self._summary_data['int_mass_LLW'] = np.sum(LW_2) self._summary_data['high_mass_LLW'] = np.sum(LW_3) self._summary_data['vhigh_mass_LLW'] = np.sum(LW_4) self._summary_data['low_mass_count'] = np.size(FUV_1) self._summary_data['int_mass_count'] = np.size(FUV_2) self._summary_data['high_mass_count'] = np.size(FUV_3) self._summary_data['vhigh_mass_count'] = np.size(FUV_4) return def write_summary_output(self): """ Write out summary output by appending to ASCII file. Filename is overwritten at first write out, so be careful. """ self._accumulate_summary_data() ncol = np.size(self._summary_data.keys()) if self._summary_output_number == 0: # print the header only once header = " " + " ".join(list(self._summary_data.keys())) + "\n" f = open(config.io.summary_output_filename,'w') f.write(header) else: f = open(config.io.summary_output_filename, 'a') fmt = "%5.5E "*ncol + "\n" # output_val = list(self._summary_data.values()) # f.write(fmt% ()) #print(self._summary_data) #print(self._summary_data.values()) f.writelines("%5.5E "% x for x in self._summary_data.values() ) f.write("\n") self._summary_output_number += 1 self._summary_data.clear() f.close() def _my_print(string): print('[Zone]: ' + string)

8,130

0

396

5613da50aa1d3dd12fedcbd4b7b022564dee7bea

5,965

py

Python

graph.py

cbsteh/PySawit

fcec4f19270b9ddef0530c3e22f41aea2dd0153e

[ "MIT" ]

15

2017-10-20T23:57:57.000Z

2021-09-04T00:34:27.000Z

graph.py

cbsteh/PySawit

fcec4f19270b9ddef0530c3e22f41aea2dd0153e

[ "MIT" ]

3

2017-10-23T14:47:26.000Z

2019-02-22T00:37:20.000Z

graph.py

cbsteh/PySawit

fcec4f19270b9ddef0530c3e22f41aea2dd0153e

[ "MIT" ]

6

2019-01-13T02:20:26.000Z

2021-11-02T15:55:09.000Z

""" Graphing the program flow module. This module aids in understanding the flow of program by creating a visual map (network graph or map) of the program flow path. The graph map is in DOT and GML (XML) types. !!! warning "Required installation" * pycallgraph (run `pip install pycallgraph`) * [Graphviz](http://www.graphviz.org) visualization software # Author - Christopher Teh Boon Sung ------------------------------------ """ import os import re import pycallgraph from pycallgraph.output import GraphvizOutput class Graph(GraphvizOutput): """ Graph class. Creates a network map by showing/tracing the program flow. DOT and GML (XML) files will be created to show the flow. Use a dedicated Graph Editor like [yEd]( http://www.yworks.com/products/yed) to view the network map. Inherits the `pycallgraph.output.GraphvizOutput` class to modify certain default output/behavior. Override the following base methods ```text prepare_graph_attributes node edge done update ``` # METHODS trace: traces the program flow and creates (.dot) DOT and (.gml) GML files """ def __init__(self, **kwargs): """ Create and initialize the Graph object. # Arguments kwargs (dict): change any attributes or initialize new attributes with this dictionary """ self.graph_attributes = None GraphvizOutput.__init__(self, **kwargs) def prepare_graph_attributes(self): """ Override to change the default attributes for graph, nodes, and edges. # Returns None: """ # change the font name and size and to have arrows for edges self.graph_attributes = { 'graph': { 'overlap': 'scalexy', 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', # black }, 'node': { 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', 'style': 'filled', 'shape': 'rect', }, 'edge': { 'arrowhead': 'normal', 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', } } def node(self, key, attr): """ Override to delete newlines and number and length of function calls in node labels. # Returns str: node label """ for k in attr.keys(): attr[k] = re.sub(r'\\n.*', '', attr[k]) return '"{}" [{}];'.format(key, self.attrs_from_dict(attr)) def edge(self, edge, attr): """ Override to delete edge labels. # Returns str: edge label """ return '"{0.src_func}" -> "{0.dst_func}"'.format(edge, self.attrs_from_dict(attr)) def done(self): """ Override to avoid creating the graph picture file. # Returns None: """ pass # do nothing (bypass the parent's done function) def update(self): """ Override to avoid warning message to implement all abstract methods. Does nothing. # Returns None: """ pass @staticmethod def _colorize(txt, cls_dict): """ Change the color of nodes depending on class. !!! note `_colorize` is a static method. # Arguments txt (str): DOT text cls_dict (dict): node colors (`None` by default) # Returns str: color text """ # cls is the class name; clr is its node color (in hexadecimal, must be 8 letters long) for cls, clr in cls_dict.items(): fmt = cls + r'\..*color = "#.{8}"' for match in re.finditer(fmt, txt): nend = match.end() txt = txt[:nend - 9] + clr + txt[nend - 1:] # substitute for the desired color return txt def trace(self, fn, fname, exclude_from_trace=None, strings_to_delete=None, class_colors=None): """ Trace the program flow and creates DOT (*.dot) and GML (*.gml) files. # Arguments fn (object): function to call for the entry point to trace the program flow fname (str): filename for graph files (do not supply file extension) exclude_from_trace (list): names (`str`) to exclude from trace (`None` by default) strings_to_delete (list): text (`str`) to remove from graph files (`None` by default) class_colors (dict): node colors (`None` by default) # Returns None: """ # 1. filter out some unwanted functions and classes: config = pycallgraph.Config() if exclude_from_trace is not None: config.trace_filter = pycallgraph.GlobbingFilter(exclude=exclude_from_trace) # 2. trace the program flow: with pycallgraph.PyCallGraph(output=self, config=config): fn() # entry point for tracing the program flow dotstr = self.generate() # 3. customize the output: # 3a. delete strings if strings_to_delete is not None: for rx in strings_to_delete: dotstr = rx.sub('', dotstr) # 3b. customization: change color for class nodes if class_colors is not None: dotstr = Graph._colorize(dotstr, class_colors) # 4. create the DOT file fname_dot = fname + '.dot' with open(fname_dot, 'wt') as fdot: fdot.write(dotstr) # 5. create the GML (XML) file fname_gml = fname + '.gml' cmd = 'dot ' + fname_dot + ' | gv2gml >' + fname_gml os.system(cmd) # use the dot.exe to convert the DOT file into GML file

29.529703

99

0.555407

""" Graphing the program flow module. This module aids in understanding the flow of program by creating a visual map (network graph or map) of the program flow path. The graph map is in DOT and GML (XML) types. !!! warning "Required installation" * pycallgraph (run `pip install pycallgraph`) * [Graphviz](http://www.graphviz.org) visualization software # Author - Christopher Teh Boon Sung ------------------------------------ """ import os import re import pycallgraph from pycallgraph.output import GraphvizOutput class Graph(GraphvizOutput): """ Graph class. Creates a network map by showing/tracing the program flow. DOT and GML (XML) files will be created to show the flow. Use a dedicated Graph Editor like [yEd]( http://www.yworks.com/products/yed) to view the network map. Inherits the `pycallgraph.output.GraphvizOutput` class to modify certain default output/behavior. Override the following base methods ```text prepare_graph_attributes node edge done update ``` # METHODS trace: traces the program flow and creates (.dot) DOT and (.gml) GML files """ def __init__(self, **kwargs): """ Create and initialize the Graph object. # Arguments kwargs (dict): change any attributes or initialize new attributes with this dictionary """ self.graph_attributes = None GraphvizOutput.__init__(self, **kwargs) def prepare_graph_attributes(self): """ Override to change the default attributes for graph, nodes, and edges. # Returns None: """ # change the font name and size and to have arrows for edges self.graph_attributes = { 'graph': { 'overlap': 'scalexy', 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', # black }, 'node': { 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', 'style': 'filled', 'shape': 'rect', }, 'edge': { 'arrowhead': 'normal', 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', } } def node(self, key, attr): """ Override to delete newlines and number and length of function calls in node labels. # Returns str: node label """ for k in attr.keys(): attr[k] = re.sub(r'\\n.*', '', attr[k]) return '"{}" [{}];'.format(key, self.attrs_from_dict(attr)) def edge(self, edge, attr): """ Override to delete edge labels. # Returns str: edge label """ return '"{0.src_func}" -> "{0.dst_func}"'.format(edge, self.attrs_from_dict(attr)) def done(self): """ Override to avoid creating the graph picture file. # Returns None: """ pass # do nothing (bypass the parent's done function) def update(self): """ Override to avoid warning message to implement all abstract methods. Does nothing. # Returns None: """ pass @staticmethod def _colorize(txt, cls_dict): """ Change the color of nodes depending on class. !!! note `_colorize` is a static method. # Arguments txt (str): DOT text cls_dict (dict): node colors (`None` by default) # Returns str: color text """ # cls is the class name; clr is its node color (in hexadecimal, must be 8 letters long) for cls, clr in cls_dict.items(): fmt = cls + r'\..*color = "#.{8}"' for match in re.finditer(fmt, txt): nend = match.end() txt = txt[:nend - 9] + clr + txt[nend - 1:] # substitute for the desired color return txt def trace(self, fn, fname, exclude_from_trace=None, strings_to_delete=None, class_colors=None): """ Trace the program flow and creates DOT (*.dot) and GML (*.gml) files. # Arguments fn (object): function to call for the entry point to trace the program flow fname (str): filename for graph files (do not supply file extension) exclude_from_trace (list): names (`str`) to exclude from trace (`None` by default) strings_to_delete (list): text (`str`) to remove from graph files (`None` by default) class_colors (dict): node colors (`None` by default) # Returns None: """ # 1. filter out some unwanted functions and classes: config = pycallgraph.Config() if exclude_from_trace is not None: config.trace_filter = pycallgraph.GlobbingFilter(exclude=exclude_from_trace) # 2. trace the program flow: with pycallgraph.PyCallGraph(output=self, config=config): fn() # entry point for tracing the program flow dotstr = self.generate() # 3. customize the output: # 3a. delete strings if strings_to_delete is not None: for rx in strings_to_delete: dotstr = rx.sub('', dotstr) # 3b. customization: change color for class nodes if class_colors is not None: dotstr = Graph._colorize(dotstr, class_colors) # 4. create the DOT file fname_dot = fname + '.dot' with open(fname_dot, 'wt') as fdot: fdot.write(dotstr) # 5. create the GML (XML) file fname_gml = fname + '.gml' cmd = 'dot ' + fname_dot + ' | gv2gml >' + fname_gml os.system(cmd) # use the dot.exe to convert the DOT file into GML file

0

ef2e3c6b09aa1fe3a4d3f5db2221c153a8e6b8df

5,728

py

Python

main.py

HJaen/dad-bot

7ccfa7cf84f0eb5e6c42e8a4cbef56aeb11520b0

[ "MIT" ]

null

main.py

HJaen/dad-bot

7ccfa7cf84f0eb5e6c42e8a4cbef56aeb11520b0

[ "MIT" ]

null

main.py

HJaen/dad-bot

7ccfa7cf84f0eb5e6c42e8a4cbef56aeb11520b0

[ "MIT" ]

null

# A Discord bot that does typical dad things # By Jason Saini and James Nguyen # Created: January 31, 2021 # Modified: January 20, 2022 import discord from os import getenv from requests import get, Session from dadjokes import Dadjoke from pyowm import OWM from dotenv import load_dotenv import yfinance as yf # setup client and tokens load_dotenv('token.env') client = discord.Client() DISCORD_TOKEN = getenv('DISCORD_TOKEN') WEATHER_TOKEN = getenv('WEATHER_TOKEN') COIN_TOKEN = getenv('COIN_TOKEN') OWNER_ID = getenv('OWNER_ID') owm = OWM(WEATHER_TOKEN) mgr = owm.weather_manager() cmc = Session() cmc.headers.update({'Accepts': 'application/json', 'X-CMC_PRO_API_KEY': COIN_TOKEN}) cmc_url = 'https://pro-api.coinmarketcap.com' @client.event @client.event client.run(DISCORD_TOKEN)

30.306878

181

0.678247

# A Discord bot that does typical dad things # By Jason Saini and James Nguyen # Created: January 31, 2021 # Modified: January 20, 2022 import discord from os import getenv from requests import get, Session from dadjokes import Dadjoke from pyowm import OWM from dotenv import load_dotenv import yfinance as yf # setup client and tokens load_dotenv('token.env') client = discord.Client() DISCORD_TOKEN = getenv('DISCORD_TOKEN') WEATHER_TOKEN = getenv('WEATHER_TOKEN') COIN_TOKEN = getenv('COIN_TOKEN') OWNER_ID = getenv('OWNER_ID') owm = OWM(WEATHER_TOKEN) mgr = owm.weather_manager() cmc = Session() cmc.headers.update({'Accepts': 'application/json', 'X-CMC_PRO_API_KEY': COIN_TOKEN}) cmc_url = 'https://pro-api.coinmarketcap.com' def get_quote(): response = get('https://zenquotes.io/api/random') json_data = response.json() quote = 'You know, ' + json_data[0]['a'] + ' said "' + json_data[0]['q'] + '" I think that\'ll help.' return quote def get_i_am_joke(message): words = message.content.split(' ') try: if 'i\'m' in message.content: while (words[0] != 'i\'m'): words.pop(0) words.pop(0) else: while (words[0] != 'i' and words[1] != 'am'): words.pop(0) words.pop(0) words.pop(0) except: words = message.author.name joke = ' '.join(words) return joke def get_weather(message): location = '' words = message.content.split(' ') try: # parse for location in message location = words[words.index('in') + 1].capitalize() if location[-1] == '?': location = location[:-1] observation = mgr.weather_at_place(location) except: # if we have an invalid location, use Hollywood (real-life Dimmsdale) print('Invalid location : ' + location) observation = mgr.weather_at_place('Hollywood') # get weather w = observation.weather weather = w.detailed_status.capitalize() weather_dict = w.temperature('fahrenheit') temperature = weather_dict.get('temp') # return weather as dict return {'location': location, 'temperature': temperature, 'weather': weather} def get_stock(message): words = message.content.split(' ') try: # ticker after the word 'stock' stock_ticker = words[words.index('stock') + 1].upper() stock = yf.Ticker(stock_ticker) # determine if the ticket exists in domestic US market stock.info['symbol'] except: print('Invalid stock : ' + stock_ticker) stock = yf.Ticker('MSFT') # return dict of stock info return stock.info def get_crypto(message): words = message.content.split(' ') try: crypto_symbol = words[words.index('crypto') + 1].upper() except: print('Invalid crypto :') [print(word) for word in words] crypto_symbol = 'BTC' response = cmc.get('https://pro-api.coinmarketcap.com/v1/cryptocurrency/quotes/latest', params={'symbol': crypto_symbol}) crypto_price = response.json()['data'][crypto_symbol]['quote']['USD']['price'] return {'symbol': crypto_symbol, 'price': crypto_price} @client.event async def on_ready(): print('We have logged in as {0.user}!'.format(client)) return async def shutdown(self,ctx): if ctx.message.author.id == OWNER_ID: #replace OWNERID with your user id print("shutdown") try: await self.bot.logout() except: print("EnvironmentError") self.bot.clear() else: await ctx.send("You do not own this bot!") @client.event async def on_message(message): if message.author == client.user: return message.content = message.content.lower() #greets user if (message.content.startswith('hello') or message.content.startswith('hi')) and 'dad' in message.content: await message.channel.send('Hi, Timmy! Oh you\'re not my Timmy, sorry there, friend!') return #tells a random dad joke if 'joke' in message.content and 'dad' in message.content: dadjoke = Dadjoke() await message.channel.send(dadjoke.joke) return # tells 'hi [], i'm dad' joke if 'i\'m' in message.content or 'i am' in message.content: joke = get_i_am_joke(message) await message.channel.send(f'Hi, {joke.capitalize()}! I\'m Dad Bot!') return # tells weather if 'weather' in message.content: weather_dict = get_weather(message) await message.channel.send('In {0}, the weather\'s {1} and it\'s {2}\xb0F today!'.format(weather_dict['location'], weather_dict['weather'].lower(), weather_dict['temperature'])) return # sends help information to user if 'help' in message.content: await message.channel.send('Say hi to Your Dad Bot by saying Hi or Hello Dad\n' 'Ask for the weather. (Like \"How\'s the weather like in Orlando?\"\n' 'Ask me to tell a joke!\n' 'Ask me for quotes!\n' 'Start a sentence with \'I\'m\'\n' 'Ask me about stocks Like \"How\'s stock AAPL doing?\"') return # tells a random quote if 'quote' in message.content and 'dad' in message.content: quote = get_quote() await message.channel.send(quote) return # tells stock trading price if 'stock' in message.content: stock_dict = get_stock(message) await message.channel.send('Looks like {0} is trading for ${1:.2f}.'.format(stock_dict['symbol'], stock_dict['regularMarketOpen'])) return # tells crypto trading price if 'crypto' in message.content: crypto_dict = get_crypto(message) await message.channel.send('Looks like {0} is trading for ${1:.6f}.'.format(crypto_dict['symbol'], crypto_dict['price'])) return if ('thanks' in message.content or 'thank you' in message.content) and 'dad' in message.content: await message.channel.send('You\'re welcome, Timmy, even if you\'re not my Timmy.') return else: return client.run(DISCORD_TOKEN)

4,754

0

182

85051de1f6a5e87b6148a3d81c6e5f3a6fea82ef

3,160

py

Python

dogbot/bot/listeners/material.py

moondropx/dogbot

4883b558e92c8fdcdbef97240cfa8252ec343eb4

[ "Apache-2.0" ]

6

2017-08-01T09:06:59.000Z

2018-06-23T11:28:51.000Z

dogbot/bot/listeners/material.py

moondropx/dogbot

4883b558e92c8fdcdbef97240cfa8252ec343eb4

[ "Apache-2.0" ]

null

dogbot/bot/listeners/material.py

moondropx/dogbot

4883b558e92c8fdcdbef97240cfa8252ec343eb4

[ "Apache-2.0" ]

2

2017-08-14T04:35:57.000Z

2019-05-26T05:57:58.000Z

import getopt import shlex from config import config from dogbot.cqsdk.utils import reply from dogbot.models import * def material(bot, message): """用法: -material [-h] [-r [-o]] 职业 -h : 打印本帮助 -r : 逆查 -o : 珠子逆查职业 : 职业名, 可以是日文原文或者黑话. 原文一概采用未cc的初始职业名. 也接受单位的日文原文或者黑话. 例: -matrial 士兵 -matrial -r 月影 -matrial -r -o アルケミスト """ try: cmd, *args = shlex.split(message.text) except ValueError: return False if not cmd[0] in config['trigger']: return False if not cmd[1:] == 'material': return False try: options, args = getopt.gnu_getopt(args, 'hro') except getopt.GetoptError: # 格式不对 reply(bot, message, material.__doc__) return True # 拆参数 is_reverse = False is_orb = False for o, a in options: if o == '-r': # 反查 is_reverse = True elif o == '-o': # 珠子反查 is_orb = True elif o == '-h': # 帮助 reply(bot, message, material.__doc__) return True # 必须要有职业参数 if len(args) < 1: reply(bot, message, material.__doc__) return True target_name = args[0] target = Class.objects(Q(name=target_name) | Q(translate=target_name) | Q(nickname=target_name)).first() if not target: target = Unit.objects(Q(name=target_name) | Q(nickname=target_name)).first() if target: target = target.class_ if not target: reply(bot, message, '没找到这个职业/单位...') return True msg = '{}({}):\n'.format(target.name, target.translate) if not is_reverse: # 查询素材 if target.cc_material: msg += '\nCC素材: ' for mat in target.cc_material: msg += '[{}] '.format(mat.translate) else: msg += '\n该职业没有CC' if target.awake_material: msg += '\n觉醒素材: ' for mat in target.awake_material: msg += '[{}] '.format(mat.translate) msg += '\n珠子: ' for mat in target.awake_orb: msg += '({}) '.format(mat.translate) else: msg += '\n该职业没有觉醒' else: # 反查 if not is_orb: cc_usage = Class.objects(cc_material=target) if cc_usage: msg += '\nCC所用: ' for usage in cc_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业不会被CC所使用' awake_usage = Class.objects(awake_material=target) if awake_usage: msg += '\n觉醒所用: ' for usage in awake_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业不会被觉醒所使用' else: orb_usage = Class.objects(awake_orb=target) if orb_usage: msg += '\n珠子所用: ' for usage in orb_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业并不是珠子' reply(bot, message, msg) return True

25.691057

108

0.496203

import getopt import shlex from config import config from dogbot.cqsdk.utils import reply from dogbot.models import * def material(bot, message): """用法: -material [-h] [-r [-o]] 职业 -h : 打印本帮助 -r : 逆查 -o : 珠子逆查职业 : 职业名, 可以是日文原文或者黑话. 原文一概采用未cc的初始职业名. 也接受单位的日文原文或者黑话. 例: -matrial 士兵 -matrial -r 月影 -matrial -r -o アルケミスト """ try: cmd, *args = shlex.split(message.text) except ValueError: return False if not cmd[0] in config['trigger']: return False if not cmd[1:] == 'material': return False try: options, args = getopt.gnu_getopt(args, 'hro') except getopt.GetoptError: # 格式不对 reply(bot, message, material.__doc__) return True # 拆参数 is_reverse = False is_orb = False for o, a in options: if o == '-r': # 反查 is_reverse = True elif o == '-o': # 珠子反查 is_orb = True elif o == '-h': # 帮助 reply(bot, message, material.__doc__) return True # 必须要有职业参数 if len(args) < 1: reply(bot, message, material.__doc__) return True target_name = args[0] target = Class.objects(Q(name=target_name) | Q(translate=target_name) | Q(nickname=target_name)).first() if not target: target = Unit.objects(Q(name=target_name) | Q(nickname=target_name)).first() if target: target = target.class_ if not target: reply(bot, message, '没找到这个职业/单位...') return True msg = '{}({}):\n'.format(target.name, target.translate) if not is_reverse: # 查询素材 if target.cc_material: msg += '\nCC素材: ' for mat in target.cc_material: msg += '[{}] '.format(mat.translate) else: msg += '\n该职业没有CC' if target.awake_material: msg += '\n觉醒素材: ' for mat in target.awake_material: msg += '[{}] '.format(mat.translate) msg += '\n珠子: ' for mat in target.awake_orb: msg += '({}) '.format(mat.translate) else: msg += '\n该职业没有觉醒' else: # 反查 if not is_orb: cc_usage = Class.objects(cc_material=target) if cc_usage: msg += '\nCC所用: ' for usage in cc_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业不会被CC所使用' awake_usage = Class.objects(awake_material=target) if awake_usage: msg += '\n觉醒所用: ' for usage in awake_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业不会被觉醒所使用' else: orb_usage = Class.objects(awake_orb=target) if orb_usage: msg += '\n珠子所用: ' for usage in orb_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业并不是珠子' reply(bot, message, msg) return True

0

74dd66fe68b737ebf12160e8d8200121aab64bd4

7,981

py

Python

controlimcap/decoders/cfattention.py

SikandarBakht/asg2cap

d8a6360eaccdb8c3add5f9c4f6fd72764e47e762

[ "MIT" ]

169

2020-03-15T08:41:39.000Z

2022-03-30T09:36:17.000Z

controlimcap/decoders/cfattention.py

wtr850/asg2cap

97a1d866d4a2b86c1f474bb168518f97eb2f8b96

[ "MIT" ]

25

2020-05-23T15:14:00.000Z

2022-03-10T06:20:31.000Z

controlimcap/decoders/cfattention.py

wtr850/asg2cap

97a1d866d4a2b86c1f474bb168518f97eb2f8b96

[ "MIT" ]

25

2020-04-02T10:08:01.000Z

2021-12-09T12:10:10.000Z

import torch import torch.nn as nn import torch.nn.functional as F import caption.utils.inference import caption.decoders.vanilla from framework.modules.embeddings import Embedding from framework.modules.global_attention import GlobalAttention

40.719388

109

0.712943

import torch import torch.nn as nn import torch.nn.functional as F import caption.utils.inference import caption.decoders.vanilla from framework.modules.embeddings import Embedding from framework.modules.global_attention import GlobalAttention class ContentFlowAttentionDecoder(caption.decoders.attention.BUTDAttnDecoder): def __init__(self, config): super().__init__(config) memory_size = self.config.attn_size if self.config.memory_same_key_value else self.config.attn_input_size self.address_layer = nn.Sequential( nn.Linear(self.config.hidden_size + memory_size, memory_size), nn.ReLU(), nn.Linear(memory_size, 1 + 3)) def forward(self, inputs, enc_globals, enc_memories, enc_masks, flow_edges, return_attn=False): ''' Args: inputs: (batch, dec_seq_len) enc_globals: (batch, hidden_size) enc_memories: (batch, enc_seq_len, attn_input_size) enc_masks: (batch, enc_seq_len) Returns: logits: (batch*seq_len, num_words) ''' batch_size, max_attn_len = enc_masks.size() device = inputs.device states = self.init_dec_state(batch_size) # zero init state # initialize content attention memory_keys, memory_values = self.gen_memory_key_value(enc_memories) # initialize location attention score: (batch, max_attn_len) prev_attn_score = torch.zeros((batch_size, max_attn_len)).to(device) prev_attn_score[:, 0] = 1 step_outs, step_attns = [], [] for t in range(inputs.size(1)): wordids = inputs[:, t] if t > 0 and self.config.schedule_sampling: sample_rate = torch.rand(wordids.size(0)).to(wordids.device) sample_mask = sample_rate < self.config.ss_rate prob = self.softmax(step_outs[-1]).detach() # detach grad sampled_wordids = torch.multinomial(prob, 1).view(-1) wordids.masked_scatter_(sample_mask, sampled_wordids) embed = self.embedding(wordids) h_attn_lstm, c_attn_lstm = self.attn_lstm( torch.cat([states[0][1], enc_globals, embed], dim=1), (states[0][0], states[1][0])) prev_memory = torch.sum(prev_attn_score.unsqueeze(2) * memory_values, 1) address_params = self.address_layer(torch.cat([h_attn_lstm, prev_memory], 1)) interpolate_gate = torch.sigmoid(address_params[:, :1]) flow_gate = torch.softmax(address_params[:, 1:], dim=1) # content_attn_score: (batch, max_attn_len) content_attn_score, content_attn_memory = self.attn(h_attn_lstm, memory_keys, memory_values, enc_masks) # location attention flow: (batch, max_attn_len) flow_attn_score_1 = torch.einsum('bts,bs->bt', flow_edges, prev_attn_score) flow_attn_score_2 = torch.einsum('bts,bs->bt',flow_edges, flow_attn_score_1) # (batch, max_attn_len, 3) flow_attn_score = torch.stack([x.view(batch_size, max_attn_len) \ for x in [prev_attn_score, flow_attn_score_1, flow_attn_score_2]], 2) flow_attn_score = torch.sum(flow_gate.unsqueeze(1) * flow_attn_score, 2) # content + location interpolation attn_score = interpolate_gate * content_attn_score + (1 - interpolate_gate) * flow_attn_score # final attention step_attns.append(attn_score) prev_attn_score = attn_score attn_memory = torch.sum(attn_score.unsqueeze(2) * memory_values, 1) # next layer with attended context h_lang_lstm, c_lang_lstm = self.lang_lstm( torch.cat([h_attn_lstm, attn_memory], dim=1), (states[0][1], states[1][1])) outs = h_lang_lstm logit = self.calc_logits_with_rnn_outs(outs) step_outs.append(logit) states = (torch.stack([h_attn_lstm, h_lang_lstm], dim=0), torch.stack([c_attn_lstm, c_lang_lstm], dim=0)) logits = torch.stack(step_outs, 1) logits = logits.view(-1, self.config.num_words) if return_attn: return logits, step_attns return logits def step_fn(self, words, step, **kwargs): states = kwargs['states'] enc_globals = kwargs['enc_globals'] memory_keys = kwargs['memory_keys'] memory_values = kwargs['memory_values'] memory_masks = kwargs['memory_masks'] prev_attn_score = kwargs['prev_attn_score'] flow_edges = kwargs['flow_edges'] batch_size, max_attn_len = memory_masks.size() embed = self.embedding(words.squeeze(1)) h_attn_lstm, c_attn_lstm = self.attn_lstm( torch.cat([states[0][1], enc_globals, embed], dim=1), (states[0][0], states[1][0])) prev_memory = torch.sum(prev_attn_score.unsqueeze(2) * memory_values, 1) address_params = self.address_layer(torch.cat([h_attn_lstm, prev_memory], 1)) interpolate_gate = torch.sigmoid(address_params[:, :1]) flow_gate = torch.softmax(address_params[:, 1:], dim=1) # content_attn_score: (batch, max_attn_len) content_attn_score, content_attn_memory = self.attn(h_attn_lstm, memory_keys, memory_values, memory_masks) # location attention flow: (batch, max_attn_len) flow_attn_score_1 = torch.einsum('bts,bs->bt', flow_edges, prev_attn_score) flow_attn_score_2 = torch.einsum('bts,bs->bt', flow_edges, flow_attn_score_1) flow_attn_score = torch.stack([x.view(batch_size, max_attn_len) \ for x in [prev_attn_score, flow_attn_score_1, flow_attn_score_2]], 2) flow_attn_score = torch.sum(flow_gate.unsqueeze(1) * flow_attn_score, 2) # content + location interpolation attn_score = interpolate_gate * content_attn_score + (1 - interpolate_gate) * flow_attn_score # final attention attn_memory = torch.sum(attn_score.unsqueeze(2) * memory_values, 1) h_lang_lstm, c_lang_lstm = self.lang_lstm( torch.cat([h_attn_lstm, attn_memory], dim=1), (states[0][1], states[1][1])) logits = self.calc_logits_with_rnn_outs(h_lang_lstm) logprobs = self.log_softmax(logits) states = (torch.stack([h_attn_lstm, h_lang_lstm], dim=0), torch.stack([c_attn_lstm, c_lang_lstm], dim=0)) kwargs['prev_attn_score'] = attn_score kwargs['states'] = states return logprobs, kwargs def sample_decode(self, words, enc_globals, enc_memories, enc_masks, flow_edges, greedy=True): '''Args: words: (batch, ) enc_globals: (batch, hidden_size) enc_memories: (batch, enc_seq_len, attn_input_size) enc_masks: (batch, enc_seq_len) flow_edges: sparse matrix, (batch*max_attn_len, batch*max_attn_len) ''' batch_size, max_attn_len = enc_masks.size() device = enc_masks.device states = self.init_dec_state(batch_size) memory_keys, memory_values = self.gen_memory_key_value(enc_memories) prev_attn_score = torch.zeros((batch_size, max_attn_len)).to(device) prev_attn_score[:, 0] = 1 seq_words, seq_word_logprobs = caption.utils.inference.sample_decode( words, self.step_fn, self.config.max_words_in_sent, greedy=greedy, states=states, enc_globals=enc_globals, memory_keys=memory_keys, memory_values=memory_values, memory_masks=enc_masks, prev_attn_score=prev_attn_score, flow_edges=flow_edges) return seq_words, seq_word_logprobs def beam_search_decode(self, words, enc_globals, enc_memories, enc_masks, flow_edges): batch_size, max_attn_len = enc_masks.size() device = enc_masks.device states = self.init_dec_state(batch_size) memory_keys, memory_values = self.gen_memory_key_value(enc_memories) prev_attn_score = torch.zeros((batch_size, max_attn_len)).to(device) prev_attn_score[:, 0] = 1 sent_pool = caption.utils.inference.beam_search_decode(words, self.step_fn, self.config.max_words_in_sent, beam_width=self.config.beam_width, sent_pool_size=self.config.sent_pool_size, expand_fn=self.expand_fn, select_fn=self.select_fn, memory_keys=memory_keys, memory_values=memory_values, memory_masks=enc_masks, states=states, enc_globals=enc_globals, prev_attn_score=prev_attn_score, flow_edges=flow_edges) return sent_pool

3,279

4,432

23

4efa79d9536678c909e0b8038a228049bf6499be

662

py

Python

2_parameters/test_params.py

fwph/pytest-examples

720b1002e43e5986db808395c9d4bdc1ca5b1638

[ "MIT" ]

4

2016-07-20T14:29:01.000Z

2017-12-07T09:23:51.000Z

2_parameters/test_params.py

fwph/pytest-examples

720b1002e43e5986db808395c9d4bdc1ca5b1638

[ "MIT" ]

null

2_parameters/test_params.py

fwph/pytest-examples

720b1002e43e5986db808395c9d4bdc1ca5b1638

[ "MIT" ]

null

import pytest @pytest.mark.parametrize(['x', 'y', 'ans'], [(1, 1, 2), (1, 2, 3), (1, 3, 4), (1, 4, 5)]) @pytest.mark.parametrize(['x', 'y', 'ans'], [(1, 1, 2), pytest.mark.xfail((1, 1, 3), reason='bad mojo'), ('ug', 'ly', 'ugly'), pytest.mark.skip(('cth', 'ulu', 'cthulu'))], ids=['good', 'bad', 'ugly', 'evil'])

31.52381

74

0.350453

import pytest @pytest.mark.parametrize(['x', 'y', 'ans'], [(1, 1, 2), (1, 2, 3), (1, 3, 4), (1, 4, 5)]) def test_addition(x, y, ans): assert x + y == ans @pytest.mark.parametrize(['x', 'y', 'ans'], [(1, 1, 2), pytest.mark.xfail((1, 1, 3), reason='bad mojo'), ('ug', 'ly', 'ugly'), pytest.mark.skip(('cth', 'ulu', 'cthulu'))], ids=['good', 'bad', 'ugly', 'evil']) def test_addition_extra(x, y, ans): assert x + y == ans

70

0

44

35dd4db4651fde50d5a6898decf9c51ba241f80d

713

py

Python

xml/parse_xml.py

bruce-webber/python-intro

78881eb65951e2c4451df1d62da1b7d79f5b1970

[ "CC-BY-4.0" ]

null

xml/parse_xml.py

bruce-webber/python-intro

78881eb65951e2c4451df1d62da1b7d79f5b1970

[ "CC-BY-4.0" ]

null

xml/parse_xml.py

bruce-webber/python-intro

78881eb65951e2c4451df1d62da1b7d79f5b1970

[ "CC-BY-4.0" ]

null

""" This is a demonstration of xml.etree (part of the standard library), which is used to parse, modify and create XML files. """ import xml.etree.ElementTree as ET tree = ET.parse('country_data.xml') root = tree.getroot() # The top level tag. print(root.tag) # The tag of the first sub-element. print(root[0].tag) # The attributes of the first sub-element. print(root[0].attrib) print() # The names of the countries and their neighbors. for country in root: if 'name' in country.attrib: print(country.attrib['name']) for element in country: if element.tag == 'neighbor': if 'name' in element.attrib: print(' ' + element.attrib['name'])

25.464286

82

0.650771

""" This is a demonstration of xml.etree (part of the standard library), which is used to parse, modify and create XML files. """ import xml.etree.ElementTree as ET tree = ET.parse('country_data.xml') root = tree.getroot() # The top level tag. print(root.tag) # The tag of the first sub-element. print(root[0].tag) # The attributes of the first sub-element. print(root[0].attrib) print() # The names of the countries and their neighbors. for country in root: if 'name' in country.attrib: print(country.attrib['name']) for element in country: if element.tag == 'neighbor': if 'name' in element.attrib: print(' ' + element.attrib['name'])

0

d1757e88944234f1f3f71b7e8f9c445336ae06cf

618

py

Python

schedule/models/event.py

rankrh/soli

8f19945a175106064591d09a53d07fcbfa26b7da

[ "MIT" ]

null

schedule/models/event.py

rankrh/soli

8f19945a175106064591d09a53d07fcbfa26b7da

[ "MIT" ]

null

schedule/models/event.py

rankrh/soli

8f19945a175106064591d09a53d07fcbfa26b7da

[ "MIT" ]

2

2019-09-07T15:10:14.000Z

2020-09-04T01:51:19.000Z

from django.db import models from django.db.models import CASCADE from schedule.models.calendar import Calendar from schedule.models.eventType import EventType

34.333333

75

0.749191

from django.db import models from django.db.models import CASCADE from schedule.models.calendar import Calendar from schedule.models.eventType import EventType class Event(models.Model): class Meta: db_table = "event" app_label = "schedule" calendar = models.ForeignKey(Calendar, on_delete=CASCADE) event_type = models.ForeignKey(EventType, on_delete=CASCADE, null=True) start = models.DateTimeField(null=True) end = models.DateTimeField(null=True, blank=True) name = models.CharField(max_length=64) description = models.CharField(max_length=1024, null=True, blank=True)

0

434

23

0f1243eea047ef5906118e7ffee57622af60818f

719

py

Python

examples/read_eeprom.py

Galch/pysoem

7dbc6c2aec9f26c7cff911c3aeef0fc73f6c71cc

[ "MIT" ]

48

2018-05-17T09:25:59.000Z

2022-03-18T08:54:36.000Z

examples/read_eeprom.py

Galch/pysoem

7dbc6c2aec9f26c7cff911c3aeef0fc73f6c71cc

[ "MIT" ]

52

2019-07-26T06:54:55.000Z

2022-03-31T09:42:20.000Z

examples/read_eeprom.py

Galch/pysoem

7dbc6c2aec9f26c7cff911c3aeef0fc73f6c71cc

[ "MIT" ]

23

2019-03-07T02:37:47.000Z

2022-03-18T08:53:45.000Z

"""Prints name and description of available network adapters.""" import sys import pysoem if __name__ == '__main__': print('script started') if len(sys.argv) > 1: read_eeprom_of_first_slave(sys.argv[1]) else: print('give ifname as script argument')

21.147059

83

0.585535

"""Prints name and description of available network adapters.""" import sys import pysoem def read_eeprom_of_first_slave(ifname): master = pysoem.Master() master.open(ifname) if master.config_init() > 0: first_slave = master.slaves[0] for i in range(0, 0x80, 2): print('{:04x}:'.format(i), end='') print('|'.join('{:02x}'.format(x) for x in first_slave.eeprom_read(i))) else: print('no slave available') master.close() if __name__ == '__main__': print('script started') if len(sys.argv) > 1: read_eeprom_of_first_slave(sys.argv[1]) else: print('give ifname as script argument')

413

0

23

8129a772f7f24252ee1ca4c2af3fd32a8236f8a3

380

py

Python

scan_lib/neros.py

Lannix/ScanNet

3a2783017ff7b9d53fd3610b28f46370c01b9145

[ "Apache-2.0" ]

null

scan_lib/neros.py

Lannix/ScanNet

3a2783017ff7b9d53fd3610b28f46370c01b9145

[ "Apache-2.0" ]

null

scan_lib/neros.py

Lannix/ScanNet

3a2783017ff7b9d53fd3610b28f46370c01b9145

[ "Apache-2.0" ]

null

from scan_lib import nero as n CONSTANT_EPOH = 100 CONSTANT_EPOH_1 = 10

22.352941

80

0.715789

from scan_lib import nero as n CONSTANT_EPOH = 100 CONSTANT_EPOH_1 = 10 def go_to_HELL(): n.save_model(n.trening_model(0, CONSTANT_EPOH)) # предобучение и сохранение for i in range(1,2000): n.save_model(n.trening_model(1, CONSTANT_EPOH_1)) n.save_model(n.trening_model(2, CONSTANT_EPOH_1)) n.save_model(n.trening_model(3, CONSTANT_EPOH_1))

302

0

23

9a8c6517db70701e563affe64146a10b0e74c08e

2,034

py

Python

tklife/__main__.py

Aesonus/TkLife

8e8f585be7f522134b9a5746b22185c2394d3d8d

[ "MIT" ]

null

tklife/__main__.py

Aesonus/TkLife

8e8f585be7f522134b9a5746b22185c2394d3d8d

[ "MIT" ]

4

2021-05-02T17:33:19.000Z

2021-05-16T18:53:51.000Z

tklife/__main__.py

Aesonus/TkLife

8e8f585be7f522134b9a5746b22185c2394d3d8d

[ "MIT" ]

null

"""Shows a sample tklife application""" from tkinter import StringVar, Widget from tkinter.constants import END from tkinter.ttk import Button, Entry, Label from .widgets import NewTable from .constants import COLUMNSPAN, PADX, PADY from .mixins import generate_event_for from . import Main from .arrange import Autogrid PADDING = { PADX: 6, PADY: 6 } @generate_event_for def show_dialog_for(widget): """Example of event generation decorator for a function""" return '<<ShowDialog>>' App().mainloop()

33.9

150

0.657325

"""Shows a sample tklife application""" from tkinter import StringVar, Widget from tkinter.constants import END from tkinter.ttk import Button, Entry, Label from .widgets import NewTable from .constants import COLUMNSPAN, PADX, PADY from .mixins import generate_event_for from . import Main from .arrange import Autogrid PADDING = { PADX: 6, PADY: 6 } @generate_event_for def show_dialog_for(widget): """Example of event generation decorator for a function""" return '<<ShowDialog>>' class App(Main): def __init__(self, **kwargs): super().__init__(**kwargs) self.title('Sample Application') def _create_vars(self): self.entry_var = StringVar(value="Test Value") def _create_widgets(self): Label(self, text='Example Entry:') Entry(self, textvariable=self.entry_var) button = Button(self, text='Show Dialog') button.configure(command=self.show_dialog_for(button)) button = Button(self, text='Show For This Button',) button.configure(command=show_dialog_for(button)) def get_widget_text(widget: Entry): return widget.get() table = NewTable(self, headers=(('Test', get_widget_text), ('The', get_widget_text), ('Table', get_widget_text), )) widgets_ = [] for row in range(4): for col in range(3): widgets_.append(Entry(table.table)) widgets_[-1].insert(0, 'Row {}; Col {}'.format(row, col)) table.cell_widgets = widgets_ def _layout_widgets(self): for widget, grid_coords in Autogrid((2, 1), 1).zip_dicts(self.winfo_children(), grid_kwargs_list=({}, {},), fill_grid_kwargs={COLUMNSPAN: 2}): widget.grid(**grid_coords, **PADDING) def _create_events(self): self.bind('<<ShowDialog>>', lambda e: print(e.widget)) @generate_event_for def show_dialog_for(self, widget): """Example of event generation decorator for an instance method""" return '<<ShowDialog>>' App().mainloop()

1,190

300

23

8cc875fd00221a9cb482a6ff240319c6dd13b16b

9,868

py

Python

aiida/tools/dbexporters/tcod_plugins/__init__.py

astamminger/aiida_core

b01ad8236f21804f273c9d2a0365ecee62255cbb

[ "BSD-2-Clause" ]

null

aiida/tools/dbexporters/tcod_plugins/__init__.py

astamminger/aiida_core

b01ad8236f21804f273c9d2a0365ecee62255cbb

[ "BSD-2-Clause" ]

null

aiida/tools/dbexporters/tcod_plugins/__init__.py

astamminger/aiida_core

b01ad8236f21804f273c9d2a0365ecee62255cbb

[ "BSD-2-Clause" ]

null

# -*- coding: utf-8 -*- ########################################################################### # Copyright (c), The AiiDA team. All rights reserved. # # This file is part of the AiiDA code. # # # # The code is hosted on GitHub at https://github.com/aiidateam/aiida_core # # For further information on the license, see the LICENSE.txt file # # For further information please visit http://www.aiida.net # ########################################################################### def TcodExporterFactory(module): """ Return a suitable BaseTcodtranslator subclass. """ from aiida.common.pluginloader import BaseFactory return BaseFactory(module, BaseTcodtranslator, 'aiida.tools.dbexporters.tcod_plugins') class BaseTcodtranslator(object): """ Base translator from calculation-specific input and output parameters to TCOD CIF dictionary tags. """ _plugin_type_string = None @classmethod def get_software_package(cls,calc,**kwargs): """ Returns the package or program name that was used to produce the structure. Only package or program name should be used, e.g. 'VASP', 'psi3', 'Abinit', etc. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_package_version(cls,calc,**kwargs): """ Returns software package version used to compute and produce the computed structure file. Only version designator should be used, e.g. '3.4.0', '2.1rc3'. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_package_compilation_timestamp(cls,calc,**kwargs): """ Returns the timestamp of package/program compilation in ISO 8601 format. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_executable_path(cls,calc,**kwargs): """ Returns the file-system path to the executable that was run for this computation. """ try: code = calc.inp.code if not code.is_local(): return code.get_attr('remote_exec_path') except Exception: return None return None @classmethod def get_total_energy(cls,calc,**kwargs): """ Returns the total energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_one_electron_energy(cls,calc,**kwargs): """ Returns one electron energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_exchange_correlation_energy(cls,calc,**kwargs): """ Returns exchange correlation (XC) energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_ewald_energy(cls,calc,**kwargs): """ Returns Ewald energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_hartree_energy(cls,calc,**kwargs): """ Returns Hartree energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_fermi_energy(cls,calc,**kwargs): """ Returns Fermi energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_number_of_electrons(cls,calc,**kwargs): """ Returns the number of electrons. """ raise NotImplementedError("not implemented in base class") @classmethod def get_computation_wallclock_time(cls,calc,**kwargs): """ Returns the computation wallclock time in seconds. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_symbol(cls,calc,**kwargs): """ Returns a list of atom types. Each atom site MUST occur only once in this list. List MUST be sorted. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_valence_configuration(cls,calc,**kwargs): """ Returns valence configuration of each atom type. The list order MUST be the same as of get_atom_type_symbol(). """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_basisset(cls,calc,**kwargs): """ Returns a list of basisset names for each atom type. The list order MUST be the same as of get_atom_type_symbol(). """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_x(cls,calc,**kwargs): """ Returns a list of x components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_y(cls,calc,**kwargs): """ Returns a list of y components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_z(cls,calc,**kwargs): """ Returns a list of z components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_X(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector X. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_Y(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector Y. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_Z(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector Z. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_X(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector X. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_Y(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector Y. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_Z(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector Z. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_smearing_method(cls,calc,**kwargs): """ Returns the smearing method name as string. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_smearing_method_other(cls,calc,**kwargs): """ Returns the smearing method name as string if the name is different from specified in cif_dft.dic. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_Methfessel_Paxton_order(cls,calc,**kwargs): """ Returns the order of Methfessel-Paxton approximation if used. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_wavefunctions(cls,calc,**kwargs): """ Returns kinetic energy cutoff for wavefunctions in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_charge_density(cls,calc,**kwargs): """ Returns kinetic energy cutoff for charge density in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_EEX(cls,calc,**kwargs): """ Returns kinetic energy cutoff for exact exchange (EEX) operator in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_atom_type(cls,calc,**kwargs): """ Returns a list of atom types. Each atom type MUST occur only once in this list. List MUST be sorted. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_type(cls,calc,**kwargs): """ Returns a list of pseudopotential types. List MUST be sorted by atom types. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_type_other_name(cls,calc,**kwargs): """ Returns a list of other pseudopotential type names. List MUST be sorted by atom types. """ raise NotImplementedError("not implemented in base class")

34.027586

90

0.631334

# -*- coding: utf-8 -*- ########################################################################### # Copyright (c), The AiiDA team. All rights reserved. # # This file is part of the AiiDA code. # # # # The code is hosted on GitHub at https://github.com/aiidateam/aiida_core # # For further information on the license, see the LICENSE.txt file # # For further information please visit http://www.aiida.net # ########################################################################### def TcodExporterFactory(module): """ Return a suitable BaseTcodtranslator subclass. """ from aiida.common.pluginloader import BaseFactory return BaseFactory(module, BaseTcodtranslator, 'aiida.tools.dbexporters.tcod_plugins') class BaseTcodtranslator(object): """ Base translator from calculation-specific input and output parameters to TCOD CIF dictionary tags. """ _plugin_type_string = None @classmethod def get_software_package(cls,calc,**kwargs): """ Returns the package or program name that was used to produce the structure. Only package or program name should be used, e.g. 'VASP', 'psi3', 'Abinit', etc. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_package_version(cls,calc,**kwargs): """ Returns software package version used to compute and produce the computed structure file. Only version designator should be used, e.g. '3.4.0', '2.1rc3'. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_package_compilation_timestamp(cls,calc,**kwargs): """ Returns the timestamp of package/program compilation in ISO 8601 format. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_executable_path(cls,calc,**kwargs): """ Returns the file-system path to the executable that was run for this computation. """ try: code = calc.inp.code if not code.is_local(): return code.get_attr('remote_exec_path') except Exception: return None return None @classmethod def get_total_energy(cls,calc,**kwargs): """ Returns the total energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_one_electron_energy(cls,calc,**kwargs): """ Returns one electron energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_exchange_correlation_energy(cls,calc,**kwargs): """ Returns exchange correlation (XC) energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_ewald_energy(cls,calc,**kwargs): """ Returns Ewald energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_hartree_energy(cls,calc,**kwargs): """ Returns Hartree energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_fermi_energy(cls,calc,**kwargs): """ Returns Fermi energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_number_of_electrons(cls,calc,**kwargs): """ Returns the number of electrons. """ raise NotImplementedError("not implemented in base class") @classmethod def get_computation_wallclock_time(cls,calc,**kwargs): """ Returns the computation wallclock time in seconds. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_symbol(cls,calc,**kwargs): """ Returns a list of atom types. Each atom site MUST occur only once in this list. List MUST be sorted. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_valence_configuration(cls,calc,**kwargs): """ Returns valence configuration of each atom type. The list order MUST be the same as of get_atom_type_symbol(). """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_basisset(cls,calc,**kwargs): """ Returns a list of basisset names for each atom type. The list order MUST be the same as of get_atom_type_symbol(). """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_x(cls,calc,**kwargs): """ Returns a list of x components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_y(cls,calc,**kwargs): """ Returns a list of y components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_z(cls,calc,**kwargs): """ Returns a list of z components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_X(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector X. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_Y(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector Y. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_Z(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector Z. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_X(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector X. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_Y(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector Y. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_Z(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector Z. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_smearing_method(cls,calc,**kwargs): """ Returns the smearing method name as string. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_smearing_method_other(cls,calc,**kwargs): """ Returns the smearing method name as string if the name is different from specified in cif_dft.dic. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_Methfessel_Paxton_order(cls,calc,**kwargs): """ Returns the order of Methfessel-Paxton approximation if used. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_wavefunctions(cls,calc,**kwargs): """ Returns kinetic energy cutoff for wavefunctions in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_charge_density(cls,calc,**kwargs): """ Returns kinetic energy cutoff for charge density in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_EEX(cls,calc,**kwargs): """ Returns kinetic energy cutoff for exact exchange (EEX) operator in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_atom_type(cls,calc,**kwargs): """ Returns a list of atom types. Each atom type MUST occur only once in this list. List MUST be sorted. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_type(cls,calc,**kwargs): """ Returns a list of pseudopotential types. List MUST be sorted by atom types. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_type_other_name(cls,calc,**kwargs): """ Returns a list of other pseudopotential type names. List MUST be sorted by atom types. """ raise NotImplementedError("not implemented in base class")

0

d14b244e69a897030f5533e366ea8b8c35a26b69

11,778

py

Python

edgedb/asyncio_client.py

ambv/edgedb-python

28de03948f1281110f8d11884683e08e2b593e91

[ "Apache-2.0" ]

null

edgedb/asyncio_client.py

ambv/edgedb-python

28de03948f1281110f8d11884683e08e2b593e91

[ "Apache-2.0" ]

null

edgedb/asyncio_client.py

ambv/edgedb-python

28de03948f1281110f8d11884683e08e2b593e91

[ "Apache-2.0" ]

null

# # This source file is part of the EdgeDB open source project. # # Copyright 2019-present MagicStack Inc. and the EdgeDB authors. # # 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 asyncio import logging import socket import ssl import typing from . import abstract from . import base_client from . import compat from . import con_utils from . import errors from . import transaction from .protocol import asyncio_proto __all__ = ( 'create_async_client', 'AsyncIOClient' ) logger = logging.getLogger(__name__) class AsyncIOClient(base_client.BaseClient, abstract.AsyncIOExecutor): """A lazy connection pool. A Client can be used to manage a set of connections to the database. Connections are first acquired from the pool, then used, and then released back to the pool. Once a connection is released, it's reset to close all open cursors and other resources *except* prepared statements. Clients are created by calling :func:`~edgedb.asyncio_client.create_async_client`. """ __slots__ = () _impl_class = _AsyncIOPoolImpl async def aclose(self): """Attempt to gracefully close all connections in the pool. Wait until all pool connections are released, close them and shut down the pool. If any error (including cancellation) occurs in ``aclose()`` the pool will terminate by calling AsyncIOClient.terminate() . It is advisable to use :func:`python:asyncio.wait_for` to set a timeout. """ await self._impl.aclose()

30.434109

79

0.616403

# # This source file is part of the EdgeDB open source project. # # Copyright 2019-present MagicStack Inc. and the EdgeDB authors. # # 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 asyncio import logging import socket import ssl import typing from . import abstract from . import base_client from . import compat from . import con_utils from . import errors from . import transaction from .protocol import asyncio_proto __all__ = ( 'create_async_client', 'AsyncIOClient' ) logger = logging.getLogger(__name__) class AsyncIOConnection(base_client.BaseConnection): __slots__ = ("_loop",) _close_exceptions = (Exception, asyncio.CancelledError) def __init__(self, loop, *args, **kwargs): super().__init__(*args, **kwargs) self._loop = loop def is_closed(self): protocol = self._protocol return protocol is None or not protocol.connected async def connect_addr(self, addr, timeout): try: await compat.wait_for(self._connect_addr(addr), timeout) except asyncio.TimeoutError as e: raise TimeoutError from e async def sleep(self, seconds): await asyncio.sleep(seconds) def _protocol_factory(self): return asyncio_proto.AsyncIOProtocol(self._params, self._loop) async def _connect_addr(self, addr): tr = None try: if isinstance(addr, str): # UNIX socket tr, pr = await self._loop.create_unix_connection( self._protocol_factory, addr ) else: try: tr, pr = await self._loop.create_connection( self._protocol_factory, *addr, ssl=self._params.ssl_ctx ) except ssl.CertificateError as e: raise con_utils.wrap_error(e) from e except ssl.SSLError as e: raise con_utils.wrap_error(e) from e else: con_utils.check_alpn_protocol( tr.get_extra_info('ssl_object') ) except socket.gaierror as e: # All name resolution errors are considered temporary raise errors.ClientConnectionFailedTemporarilyError(str(e)) from e except OSError as e: raise con_utils.wrap_error(e) from e except Exception: if tr is not None: tr.close() raise pr.set_connection(self) try: await pr.connect() except OSError as e: if tr is not None: tr.close() raise con_utils.wrap_error(e) from e except Exception: if tr is not None: tr.close() raise self._protocol = pr self._addr = addr def _dispatch_log_message(self, msg): for cb in self._log_listeners: self._loop.call_soon(cb, self, msg) class _PoolConnectionHolder(base_client.PoolConnectionHolder): __slots__ = () _event_class = asyncio.Event async def close(self, *, wait=True): if self._con is None: return if wait: await self._con.close() else: self._pool._loop.create_task(self._con.close()) async def wait_until_released(self, timeout=None): await self._release_event.wait() class _AsyncIOPoolImpl(base_client.BasePoolImpl): __slots__ = ('_loop',) _holder_class = _PoolConnectionHolder def __init__( self, connect_args, *, max_concurrency: typing.Optional[int], connection_class, ): if not issubclass(connection_class, AsyncIOConnection): raise TypeError( f'connection_class is expected to be a subclass of ' f'edgedb.asyncio_client.AsyncIOConnection, ' f'got {connection_class}') self._loop = None super().__init__( connect_args, lambda *args: connection_class(self._loop, *args), max_concurrency=max_concurrency, ) def _ensure_initialized(self): if self._loop is None: self._loop = asyncio.get_event_loop() self._queue = asyncio.LifoQueue(maxsize=self._max_concurrency) self._first_connect_lock = asyncio.Lock() self._resize_holder_pool() def _set_queue_maxsize(self, maxsize): self._queue._maxsize = maxsize async def _maybe_get_first_connection(self): async with self._first_connect_lock: if self._working_addr is None: return await self._get_first_connection() async def acquire(self, timeout=None): self._ensure_initialized() async def _acquire_impl(): ch = await self._queue.get() # type: _PoolConnectionHolder try: proxy = await ch.acquire() # type: AsyncIOConnection except (Exception, asyncio.CancelledError): self._queue.put_nowait(ch) raise else: # Record the timeout, as we will apply it by default # in release(). ch._timeout = timeout return proxy if self._closing: raise errors.InterfaceError('pool is closing') if timeout is None: return await _acquire_impl() else: return await compat.wait_for( _acquire_impl(), timeout=timeout) async def _release(self, holder): if not isinstance(holder._con, AsyncIOConnection): raise errors.InterfaceError( f'release() received invalid connection: ' f'{holder._con!r} does not belong to any connection pool' ) timeout = None # Use asyncio.shield() to guarantee that task cancellation # does not prevent the connection from being returned to the # pool properly. return await asyncio.shield(holder.release(timeout)) async def aclose(self): """Attempt to gracefully close all connections in the pool. Wait until all pool connections are released, close them and shut down the pool. If any error (including cancellation) occurs in ``close()`` the pool will terminate by calling _AsyncIOPoolImpl.terminate() . It is advisable to use :func:`python:asyncio.wait_for` to set a timeout. """ if self._closed: return if not self._loop: self._closed = True return self._closing = True try: warning_callback = self._loop.call_later( 60, self._warn_on_long_close) release_coros = [ ch.wait_until_released() for ch in self._holders] await asyncio.gather(*release_coros) close_coros = [ ch.close() for ch in self._holders] await asyncio.gather(*close_coros) except (Exception, asyncio.CancelledError): self.terminate() raise finally: warning_callback.cancel() self._closed = True self._closing = False def _warn_on_long_close(self): logger.warning( 'AsyncIOClient.aclose() is taking over 60 seconds to complete. ' 'Check if you have any unreleased connections left. ' 'Use asyncio.wait_for() to set a timeout for ' 'AsyncIOClient.aclose().') class AsyncIOIteration(transaction.BaseTransaction, abstract.AsyncIOExecutor): __slots__ = ("_managed",) def __init__(self, retry, client, iteration): super().__init__(retry, client, iteration) self._managed = False async def __aenter__(self): if self._managed: raise errors.InterfaceError( 'cannot enter context: already in an `async with` block') self._managed = True return self async def __aexit__(self, extype, ex, tb): self._managed = False return await self._exit(extype, ex) async def _ensure_transaction(self): if not self._managed: raise errors.InterfaceError( "Only managed retriable transactions are supported. " "Use `async with transaction:`" ) await super()._ensure_transaction() class AsyncIORetry(transaction.BaseRetry): def __aiter__(self): return self async def __anext__(self): # Note: when changing this code consider also # updating Retry.__next__. if self._done: raise StopAsyncIteration if self._next_backoff: await asyncio.sleep(self._next_backoff) self._done = True iteration = AsyncIOIteration(self, self._owner, self._iteration) self._iteration += 1 return iteration class AsyncIOClient(base_client.BaseClient, abstract.AsyncIOExecutor): """A lazy connection pool. A Client can be used to manage a set of connections to the database. Connections are first acquired from the pool, then used, and then released back to the pool. Once a connection is released, it's reset to close all open cursors and other resources *except* prepared statements. Clients are created by calling :func:`~edgedb.asyncio_client.create_async_client`. """ __slots__ = () _impl_class = _AsyncIOPoolImpl async def ensure_connected(self): await self._impl.ensure_connected() return self async def aclose(self): """Attempt to gracefully close all connections in the pool. Wait until all pool connections are released, close them and shut down the pool. If any error (including cancellation) occurs in ``aclose()`` the pool will terminate by calling AsyncIOClient.terminate() . It is advisable to use :func:`python:asyncio.wait_for` to set a timeout. """ await self._impl.aclose() def transaction(self) -> AsyncIORetry: return AsyncIORetry(self) async def __aenter__(self): return await self.ensure_connected() async def __aexit__(self, exc_type, exc_val, exc_tb): await self.aclose() def create_async_client( dsn=None, *, max_concurrency=None, host: str = None, port: int = None, credentials: str = None, credentials_file: str = None, user: str = None, password: str = None, database: str = None, tls_ca: str = None, tls_ca_file: str = None, tls_security: str = None, wait_until_available: int = 30, timeout: int = 10, ): return AsyncIOClient( connection_class=AsyncIOConnection, max_concurrency=max_concurrency, # connect arguments dsn=dsn, host=host, port=port, credentials=credentials, credentials_file=credentials_file, user=user, password=password, database=database, tls_ca=tls_ca, tls_ca_file=tls_ca_file, tls_security=tls_security, wait_until_available=wait_until_available, timeout=timeout, )

7,257

2,160

300

19ede42cce4f823c3fdc894067745de7b0edc547

181

py

Python

mobie/validation/__init__.py

mobie-org/mobie-utils-python

0281db2bf3726103b762a50e40849e30942dd6ec

[ "MIT" ]

1

2020-03-03T01:33:06.000Z

mobie/validation/__init__.py

platybrowser/mmb-python

0281db2bf3726103b762a50e40849e30942dd6ec

[ "MIT" ]

4

2020-05-15T09:27:59.000Z

2020-05-29T19:15:00.000Z

mobie/validation/__init__.py

platybrowser/mmb-python

0281db2bf3726103b762a50e40849e30942dd6ec

[ "MIT" ]

2

2020-06-08T07:06:01.000Z

2020-06-08T07:08:08.000Z

from .dataset import validate_dataset from .metadata import validate_source_metadata, validate_view_metadata from .project import validate_project from .views import validate_views

36.2

70

0.878453

from .dataset import validate_dataset from .metadata import validate_source_metadata, validate_view_metadata from .project import validate_project from .views import validate_views

0

86965314682fe859926efa3c62312c76b8803870

1,918

py

Python

examples/test_trading.py

testnet-exchange/python-viabtc-api

be7be15944004498be8da9e4435020d97408a352

[ "Apache-2.0" ]

33

2018-07-31T07:50:15.000Z

2020-08-04T13:51:40.000Z

examples/test_trading.py

urantialife/python-viabtc-api

be7be15944004498be8da9e4435020d97408a352

[ "Apache-2.0" ]

7

2018-08-23T14:48:11.000Z

2019-07-15T02:17:12.000Z

examples/test_trading.py

urantialife/python-viabtc-api

be7be15944004498be8da9e4435020d97408a352

[ "Apache-2.0" ]

20

2018-08-08T16:29:41.000Z

2020-08-04T13:51:43.000Z

import sys from ViaBTCAPI.ViaBTCAPI import ViaBTCAPI EXCHANGE_URL = "http://localhost:8080/" USER_ID = 1 USER_ID_2 = 2 UPDATE_MONEY = 0.1 ORDER_PRICE = 0.1 if len(sys.argv) > 1: EXCHANGE_URL = sys.argv[1] api = ViaBTCAPI(EXCHANGE_URL) # get consts from exchange resp = api.market_list() m = resp["result"][0] market, stock, money = m["name"], m["stock"], m["money"] # balance change r = api.balance_query(user_id=USER_ID, asset=money) balance_before = float(r["result"][money]["available"]) _ = api.balance_update(user_id=USER_ID, asset=money, amount=UPDATE_MONEY) r = api.balance_query(user_id=USER_ID, asset=money) balance_after = float(r["result"][money]["available"]) assert(balance_after == balance_before + UPDATE_MONEY) # limit order creation r = api.order_put_limit( user_id=USER_ID, market=market, side='BUY', amount=UPDATE_MONEY, price=ORDER_PRICE, taker_fee_rate=0, maker_fee_rate=0) r = api.order_depth(market=market, limit=10) bid_prices = [float(b[0]) for b in r["result"]["bids"]] assert(ORDER_PRICE in bid_prices) bid_volume = [float(b[1]) for b in r["result"]["bids"] if float(b[0]) == ORDER_PRICE][0] # create the second user and execute the order _ = api.balance_update(user_id=USER_ID_2, asset=stock, amount=bid_volume) r = api.order_put_limit( user_id=USER_ID_2, market=market, side='SELL', amount=bid_volume, price=ORDER_PRICE, taker_fee_rate=0, maker_fee_rate=0) r = api.order_depth(market=market, limit=10) prices = [float(b[0]) for b in r["result"]["bids"] + r["result"]["asks"]] assert(ORDER_PRICE not in prices) # reset balances for user_id in [USER_ID, USER_ID_2]: for asset in [money, stock]: r = api.balance_query(user_id=user_id, asset=asset) balance_current = float(r["result"][asset]["available"]) r = api.balance_update(user_id=user_id, asset=asset, amount=(-1) * balance_current) print("All tests have been passed!")

31.442623

91

0.717935

import sys from ViaBTCAPI.ViaBTCAPI import ViaBTCAPI EXCHANGE_URL = "http://localhost:8080/" USER_ID = 1 USER_ID_2 = 2 UPDATE_MONEY = 0.1 ORDER_PRICE = 0.1 if len(sys.argv) > 1: EXCHANGE_URL = sys.argv[1] api = ViaBTCAPI(EXCHANGE_URL) # get consts from exchange resp = api.market_list() m = resp["result"][0] market, stock, money = m["name"], m["stock"], m["money"] # balance change r = api.balance_query(user_id=USER_ID, asset=money) balance_before = float(r["result"][money]["available"]) _ = api.balance_update(user_id=USER_ID, asset=money, amount=UPDATE_MONEY) r = api.balance_query(user_id=USER_ID, asset=money) balance_after = float(r["result"][money]["available"]) assert(balance_after == balance_before + UPDATE_MONEY) # limit order creation r = api.order_put_limit( user_id=USER_ID, market=market, side='BUY', amount=UPDATE_MONEY, price=ORDER_PRICE, taker_fee_rate=0, maker_fee_rate=0) r = api.order_depth(market=market, limit=10) bid_prices = [float(b[0]) for b in r["result"]["bids"]] assert(ORDER_PRICE in bid_prices) bid_volume = [float(b[1]) for b in r["result"]["bids"] if float(b[0]) == ORDER_PRICE][0] # create the second user and execute the order _ = api.balance_update(user_id=USER_ID_2, asset=stock, amount=bid_volume) r = api.order_put_limit( user_id=USER_ID_2, market=market, side='SELL', amount=bid_volume, price=ORDER_PRICE, taker_fee_rate=0, maker_fee_rate=0) r = api.order_depth(market=market, limit=10) prices = [float(b[0]) for b in r["result"]["bids"] + r["result"]["asks"]] assert(ORDER_PRICE not in prices) # reset balances for user_id in [USER_ID, USER_ID_2]: for asset in [money, stock]: r = api.balance_query(user_id=user_id, asset=asset) balance_current = float(r["result"][asset]["available"]) r = api.balance_update(user_id=user_id, asset=asset, amount=(-1) * balance_current) print("All tests have been passed!")

0

ea5282e356e5e5fd276625a31e5b9590f02122ed

1,066

py

Python

Speech Synthesis/SS.py

saber1malek/HelpMate

d69ee6cc1e67fca3e87fa6ea132a0569e4667994

[ "MIT" ]

3

2020-06-07T08:56:40.000Z

2020-06-07T13:00:21.000Z

Speech Synthesis/SS.py

saber1malek/HelpMate

d69ee6cc1e67fca3e87fa6ea132a0569e4667994

[ "MIT" ]

1

2020-06-07T09:06:12.000Z

Speech Synthesis/SS.py

saber1malek/HelpMate

d69ee6cc1e67fca3e87fa6ea132a0569e4667994

[ "MIT" ]

1

2020-06-07T07:13:55.000Z

# HelpMate Speech Synthesis Connection 2020 from google.cloud import texttospeech # Instantiates a client client = texttospeech.TextToSpeechClient() # Set the text input to be synthesized synthesis_input = texttospeech.types.SynthesisInput(text="Hello, World!") # Build the voice request, select the language code ("en-US") and the ssml # voice gender ("neutral") voice = texttospeech.types.VoiceSelectionParams( language_code='en-US', ssml_gender=texttospeech.enums.SsmlVoiceGender.NEUTRAL) # Select the type of audio file you want returned audio_config = texttospeech.types.AudioConfig( audio_encoding=texttospeech.enums.AudioEncoding.MP3) # Perform the text-to-speech request on the text input with the selected # voice parameters and audio file type response = client.synthesize_speech(synthesis_input, voice, audio_config) # The response's audio_content is binary. with open('output.mp3', 'wb') as out: # Write the response to the output file. out.write(response.audio_content) print('Audio content written to file "output.mp3"')

35.533333

74

0.77955

# HelpMate Speech Synthesis Connection 2020 from google.cloud import texttospeech # Instantiates a client client = texttospeech.TextToSpeechClient() # Set the text input to be synthesized synthesis_input = texttospeech.types.SynthesisInput(text="Hello, World!") # Build the voice request, select the language code ("en-US") and the ssml # voice gender ("neutral") voice = texttospeech.types.VoiceSelectionParams( language_code='en-US', ssml_gender=texttospeech.enums.SsmlVoiceGender.NEUTRAL) # Select the type of audio file you want returned audio_config = texttospeech.types.AudioConfig( audio_encoding=texttospeech.enums.AudioEncoding.MP3) # Perform the text-to-speech request on the text input with the selected # voice parameters and audio file type response = client.synthesize_speech(synthesis_input, voice, audio_config) # The response's audio_content is binary. with open('output.mp3', 'wb') as out: # Write the response to the output file. out.write(response.audio_content) print('Audio content written to file "output.mp3"')

0

45ea4555c4079a2cc54d9816af5099cce9311f97

4,128

py

Python

triggerflow/dags/dag.py

Dahk/triggerflow-examples

c492942ab911615d144a1375f4bc7933831203bd

[ "Apache-2.0" ]

38

2020-06-11T08:05:21.000Z

2022-03-17T10:21:18.000Z

triggerflow/dags/dag.py

Dahk/triggerflow-examples

c492942ab911615d144a1375f4bc7933831203bd

[ "Apache-2.0" ]

1

2020-07-07T15:47:56.000Z

triggerflow/dags/dag.py

Dahk/triggerflow-examples

c492942ab911615d144a1375f4bc7933831203bd

[ "Apache-2.0" ]

7

2020-05-18T16:32:06.000Z

2021-11-30T17:11:12.000Z

import re import json from typing import Optional, List, Dict from . import operators from .models.baseoperator import BaseOperator from .dagrun import DAGRun from ..cache import TriggerflowCache from .other.notebook import display_graph

35.895652

115

0.637355

import re import json from typing import Optional, List, Dict from . import operators from .models.baseoperator import BaseOperator from .dagrun import DAGRun from ..cache import TriggerflowCache from .other.notebook import display_graph class DAG: def __init__(self, dag_id): """ Initialize an empty DAG object :param dag_id: DAG identifier (can only contain alphanumeric characters, hyphens and underscores) """ # Check DAG id pattern = r"[a-zA-Z0-9_\-]+" if not re.fullmatch(pattern, dag_id): raise Exception("Dag id \"{}\" does not match pattern {}".format(dag_id, pattern)) self.dag_id = dag_id self.event_sources = {} self.__tasks = set() @property def initial_tasks(self): return [task for task in self.__tasks if not task.upstream_relatives] @property def final_tasks(self): return [task for task in self.__tasks if not task.downstream_relatives] @property def tasks(self) -> List[BaseOperator]: return list(self.__tasks) @property def tasks_dict(self) -> Dict[str, BaseOperator]: return {task.task_id: task for task in self.__tasks} def add_task(self, task): if task.task_id in [task.task_id for task in self.tasks]: raise Exception('A task with ID {} is already registered in the dag'.format(task.task_id)) self.__tasks.add(task) def run(self): if self.dag_id is None: raise Exception('DAG id must be set') return DAGRun.from_dag_def(self).run() def show(self): return display_graph(self) def json_marshal(self): return { 'dag_id': self.dag_id, 'event_sources': [event_source.get_json_eventsource() for event_source in self.event_sources.values()], 'initial_tasks': [task.task_id for task in self.initial_tasks], 'final_tasks': [task.task_id for task in self.final_tasks], 'tasks': {task.task_id: task.json_marshal() for task in self.__tasks} } def json_unmarshal(self, json_dag): # Instantiate all operator objects tasks = {} for task_name, task_json in json_dag['tasks'].items(): operator_class = getattr(operators, task_json['operator']['class']) tasks[task_name] = operator_class(task_id=task_name, dag=self, **task_json['operator']['parameters']) # Set up dependencies for task_name, task_json in json_dag['tasks'].items(): task_obj = tasks[task_name] upstream_relatives = [tasks[up_rel] for up_rel in task_json['upstream_relatives']] if upstream_relatives: task_obj.set_upstream(upstream_relatives) downstream_relatives = [tasks[down_rel] for down_rel in task_json['downstream_relatives']] if downstream_relatives: task_obj.set_downstream(downstream_relatives) def save(self): with TriggerflowCache(path='dags', file_name=self.dag_id + '.json', method='w') as dag_file: dag_file.write(json.dumps(self.json_marshal(), indent=4)) return self def load(self): with TriggerflowCache(path='dags', file_name=self.dag_id + '.json', method='r') as dag_file: dag_json = json.loads(dag_file.read()) self.json_unmarshal(dag_json) return self def export_to_json(self, dest_path: Optional[str] = '.', dest_file: Optional[str] = None): if dest_file is None: dest_file = self.dag_id if not dest_file.endswith('.json'): dest_file += '.json' dag_json = self.json_marshal() path = '/'.join([dest_path, dest_file]) with open(path, 'w') as dag_file: dag_file.write(json.dumps(dag_json, indent=4)) return self @classmethod def import_from_json(cls, src_file: str): with open(src_file, 'r') as dag_file: dag_json = json.loads(dag_file.read()) dag_obj = cls(dag_json['dag_id']) dag_obj.json_unmarshal(dag_json) return dag_obj

2,957

907

23

53010981e0eedacff4461e5e4a9beb5fada6a61c

7,649

py

Python

arbitrage/private_markets/anxpro.py

queenvictoria/bitcoin-arbitrage

12b6304684416fa2a7b2bb61c19e87b4572577c1

[ "Unlicense" ]

2

2016-02-27T03:52:01.000Z

2017-10-23T18:47:31.000Z

arbitrage/private_markets/anxpro.py

queenvictoria/bitcoin-arbitrage

12b6304684416fa2a7b2bb61c19e87b4572577c1

[ "Unlicense" ]

null

arbitrage/private_markets/anxpro.py

queenvictoria/bitcoin-arbitrage

12b6304684416fa2a7b2bb61c19e87b4572577c1

[ "Unlicense" ]

null

# Copyright (C) 2013, Maxime Biais <maxime@biais.org> from .market import Market import time import base64 import hmac import urllib.request import urllib.parse import urllib.error import urllib.request import urllib.error import urllib.parse import hashlib import sys import json import re import logging import config

39.225641

95

0.577723

# Copyright (C) 2013, Maxime Biais <maxime@biais.org> from .market import Market import time import base64 import hmac import urllib.request import urllib.parse import urllib.error import urllib.request import urllib.error import urllib.parse import hashlib import sys import json import re import logging import config class PrivateANXPro(Market): def __init__(self): super().__init__() self.base_url = "https://anxpro.com/api/2/" self.order_path = {"method": "POST", "path": "generic/private/order/result"} self.open_orders_path = {"method": "POST", "path": "generic/private/orders"} self.info_path = {"method": "POST", "path": "money/info"} self.withdraw_path = {"method": "POST", "path": "generic/bitcoin/send_simple"} self.deposit_path = {"method": "POST", "path": "generic/bitcoin/address"} self.key = config.anxpro_api_key self.secret = config.anxpro_api_secret self.get_info() def _create_nonce(self): return int(time.time() * 1000000) def _change_currency_url(self, url, currency): return re.sub(r'BTC\w{3}', r'BTC' + currency, url) def _to_int_price(self, price, currency): ret_price = None if currency in ["USD", "EUR", "GBP", "PLN", "CAD", "AUD", "CHF", "CNY", "NZD", "RUB", "DKK", "HKD", "SGD", "THB"]: ret_price = price ret_price = int(price * 100000) elif currency in ["JPY", "SEK"]: ret_price = price ret_price = int(price * 1000) return ret_price def _to_int_amount(self, amount): amount = amount return int(amount * 100000000) def _from_int_amount(self, amount): return amount / 100000000. def _from_int_price(self, amount): # FIXME: should take JPY and SEK into account return amount / 100000. def _send_request(self, url, params, extra_headers=None): urlparams = urllib.parse.urlencode(dict(params)) secret_message = url["path"] + chr(0) + urlparams secret_from_b64 = base64.b64decode(bytes(self.secret, "UTF-8")) hmac_secret = hmac.new(secret_from_b64, secret_message.encode("UTF-8"), hashlib.sha512) hmac_sign = base64.b64encode(hmac_secret.digest()) headers = { 'Rest-Key': self.key, 'Rest-Sign': hmac_sign.decode("UTF-8"), 'Content-type': 'application/x-www-form-urlencoded', 'Accept': 'application/json, text/javascript, */*; q=0.01', 'User-Agent': 'Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)' } if extra_headers is not None: for k, v in extra_headers.items(): headers[k] = v try: req = urllib.request.Request(self.base_url + url['path'], bytes(urlparams, "UTF-8"), headers) response = urllib.request.urlopen(req) if response.getcode() == 200: jsonstr = response.read() return json.loads(str(jsonstr, "UTF-8")) except Exception as err: logging.error('Can\'t request ANXPro, %s' % err) return None def trade(self, amount, ttype, price=None): if price: price = self._to_int_price(price, self.currency) amount = self._to_int_amount(amount) self.buy_path["path"] = self._change_currency_url( self.buy_path["path"], self.currency) params = [("nonce", self._create_nonce()), ("amount_int", str(amount)), ("type", ttype)] if price: params.append(("price_int", str(price))) response = self._send_request(self.buy_path, params) if response and "result" in response and \ response["result"] == "success": return response["return"] return None def _buy(self, amount, price): return self.trade(amount, "bid", price) def _sell(self, amount, price): return self.trade(amount, "ask", price) def withdraw(self, amount, address): params = [("nonce", self._create_nonce()), ("amount_int", str(self._to_int_amount(amount))), ("address", address)] response = self._send_request(self.withdraw_path, params) if response and "result" in response and \ response["result"] == "success": return response["return"] return None def deposit(self): params = [("nonce", self._create_nonce())] response = self._send_request(self.deposit_path, params) if response and "result" in response and \ response["result"] == "success": return response["return"] return None class PrivateANXProAUD(PrivateANXPro): def __init__(self): super().__init__() self.ticker_path = {"method": "GET", "path": "BTCAUD/public/ticker"} self.buy_path = {"method": "POST", "path": "BTCAUD/private/order/add"} self.sell_path = {"method": "POST", "path": "BTCAUD/private/order/add"} self.currency = "AUD" def get_info(self): params = [("nonce", self._create_nonce())] response = self._send_request(self.info_path, params) if response and "result" in response and response["result"] == "success": self.btc_balance = self._from_int_amount(int( response["data"]["Wallets"]["BTC"]["Balance"]["value_int"])) self.aud_balance = self._from_int_price(int( response["data"]["Wallets"]["AUD"]["Balance"]["value_int"])) self.usd_balance = self.fc.convert(self.aud_balance, "AUD", "USD") self.eur_balance = self.fc.convert(self.aud_balance, "AUD", "EUR") funds = response["data"]["Wallets"] if self.pair1_name in funds: self.pair1_balance = self._from_int_amount( int(funds[self.pair1_name]["Balance"]["value_int"]) ) if self.pair2_name in funds: self.pair2_balance = self._from_int_amount( int(funds[self.pair2_name]["Balance"]["value_int"]) ) return 1 return None class PrivateANXProUSD(PrivateANXPro): def __init__(self): super().__init__() self.ticker_path = {"method": "GET", "path": "BTCUSD/public/ticker"} self.buy_path = {"method": "POST", "path": "BTCUSD/private/order/add"} self.sell_path = {"method": "POST", "path": "BTCUSD/private/order/add"} self.currency = "USD" def get_info(self): params = [("nonce", self._create_nonce())] response = self._send_request(self.info_path, params) if response and "result" in response and response["result"] == "success": self.btc_balance = self._from_int_amount(int( response["data"]["Wallets"]["BTC"]["Balance"]["value_int"])) self.usd_balance = self._from_int_price(int( response["data"]["Wallets"]["USD"]["Balance"]["value_int"])) funds = response["data"]["Wallets"] if self.pair1_name in funds: self.pair1_balance = self._from_int_amount( int(funds[self.pair1_name]["Balance"]["value_int"]) ) if self.pair2_name in funds: self.pair2_balance = self._from_int_amount( int(funds[self.pair2_name]["Balance"]["value_int"]) ) return 1 return None

6,761

41

525

f3f1716e28d3670b76dc0d585daaea68d8eeab2d

2,442

py

Python

zeus/migrations/0f81e9efc84a_add_pending_artifact.py

conrad-kronos/zeus

ddb6bc313e51fb22222b30822b82d76f37dbbd35

[ "Apache-2.0" ]

221

2017-07-03T17:29:21.000Z

2021-12-07T19:56:59.000Z

zeus/migrations/0f81e9efc84a_add_pending_artifact.py

conrad-kronos/zeus

ddb6bc313e51fb22222b30822b82d76f37dbbd35

[ "Apache-2.0" ]

298

2017-07-04T18:08:14.000Z

2022-03-03T22:24:51.000Z

zeus/migrations/0f81e9efc84a_add_pending_artifact.py

conrad-kronos/zeus

ddb6bc313e51fb22222b30822b82d76f37dbbd35

[ "Apache-2.0" ]

24

2017-07-15T13:46:45.000Z

2020-08-16T16:14:45.000Z

"""add_pending_artifact Revision ID: 0f81e9efc84a Revises: 61a1763b9c8d Create Date: 2019-10-24 15:13:36.705288 """ import zeus.db.types from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = "0f81e9efc84a" down_revision = "61a1763b9c8d" branch_labels = () depends_on = None

32.56

85

0.638411

"""add_pending_artifact Revision ID: 0f81e9efc84a Revises: 61a1763b9c8d Create Date: 2019-10-24 15:13:36.705288 """ import zeus.db.types from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = "0f81e9efc84a" down_revision = "61a1763b9c8d" branch_labels = () depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table( "pending_artifact", sa.Column("provider", sa.String(), nullable=False), sa.Column("external_job_id", sa.String(length=64), nullable=False), sa.Column("external_build_id", sa.String(length=64), nullable=False), sa.Column("hook_id", zeus.db.types.guid.GUID(), nullable=False), sa.Column("name", sa.String(length=256), nullable=False), sa.Column("type", sa.String(length=64), nullable=True), sa.Column("file", zeus.db.types.file.File(), nullable=False), sa.Column("repository_id", zeus.db.types.guid.GUID(), nullable=False), sa.Column("id", zeus.db.types.guid.GUID(), nullable=False), sa.Column( "date_created", sa.TIMESTAMP(timezone=True), server_default=sa.text("now()"), nullable=False, ), sa.ForeignKeyConstraint(["hook_id"], ["hook.id"], ondelete="CASCADE"), sa.ForeignKeyConstraint( ["repository_id"], ["repository.id"], ondelete="CASCADE" ), sa.PrimaryKeyConstraint("id"), ) op.create_index( "idx_pending_artifact", "pending_artifact", ["repository_id", "provider", "external_job_id", "external_build_id"], unique=False, ) op.create_index( op.f("ix_pending_artifact_hook_id"), "pending_artifact", ["hook_id"], unique=False, ) op.create_index( op.f("ix_pending_artifact_repository_id"), "pending_artifact", ["repository_id"], unique=False, ) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_index( op.f("ix_pending_artifact_repository_id"), table_name="pending_artifact" ) op.drop_index(op.f("ix_pending_artifact_hook_id"), table_name="pending_artifact") op.drop_index("idx_pending_artifact", table_name="pending_artifact") op.drop_table("pending_artifact") # ### end Alembic commands ###

2,071

0

46

04fc4ab0e7caeb7ba6bcedac53f83e0735e59840

5,148

py

Python

fixed_width.py

supakeen/fixed-width

57e9ae06ee5d77f2390f8377a9b7842f3596b04e

[ "MIT" ]

null

fixed_width.py

supakeen/fixed-width

57e9ae06ee5d77f2390f8377a9b7842f3596b04e

[ "MIT" ]

null

fixed_width.py

supakeen/fixed-width

57e9ae06ee5d77f2390f8377a9b7842f3596b04e

[ "MIT" ]

null

""" Copyright 2021 supakeen Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import enum from typing import Optional, Any class _context: """Contexts are for storing various flags about what happened to types used within them.""" overflow: bool promotion: bool class _value: """A value, we store the raw 'python' integer and only go into/out of bits and fixed width on certain operations. This allows for easier conversion during calculation. """ class default(_context): """Some default values that do generally what people expect, these mimic the `c_stdint` context and are exported on the module level directly for short imports.""" _signed_behavior = _behavior( overflow=_behavior_overflow.TRUNCATE, promotion=_behavior_promotion.EXCEPTION, ) i8 = _signed(8, _signed_behavior) i16 = _signed(16, _signed_behavior) i32 = _signed(32, _signed_behavior) i64 = _signed(64, _signed_behavior) _unsigned_behavior = _behavior( overflow=_behavior_overflow.TRUNCATE, promotion=_behavior_promotion.EXCEPTION, ) u8 = _unsigned(8, _unsigned_behavior) u16 = _unsigned(16, _unsigned_behavior) u32 = _unsigned(32, _unsigned_behavior) u64 = _unsigned(64, _unsigned_behavior) # Exporting the `default` context for short imports. i8 = default.i8 i16 = default.i16 i32 = default.i32 i64 = default.i64 u8 = default.u8 u16 = default.u16 u32 = default.u32 u64 = default.u64

27.677419

80

0.698718

""" Copyright 2021 supakeen Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import enum from typing import Optional, Any class _storage(enum.Enum): TWOS_COMPLEMENT = enum.auto() class _behavior_overflow(enum.Enum): EXCEPTION = enum.auto() TRUNCATE = enum.auto() class _behavior_promotion(enum.Enum): EXCEPTION = enum.auto() class _behavior: overflow: _behavior_overflow promotion: _behavior_promotion def __init__(self, overflow, promotion): self.overflow = overflow self.promotion = promotion def __repr__(self) -> str: return f"_behavior({self.overflow=}, {self.promotion=})" class _context: """Contexts are for storing various flags about what happened to types used within them.""" overflow: bool promotion: bool def __init__(self): self.overflow = False self.promotion = False def __enter__(self): return self def __exit__(self, exc_type, exc_value, exc_traceback): pass class _value: """A value, we store the raw 'python' integer and only go into/out of bits and fixed width on certain operations. This allows for easier conversion during calculation. """ def __init__(self, rule, integer: int, context: Optional[_context] = None): self._rule = rule self._integer = integer self._context = context def __int__(self) -> int: if self._rule._behavior.overflow == _behavior_overflow.TRUNCATE: return self._integer & (2 ** self._rule._width - 1) else: self._integer & (2 ** self._rule._width - 1) def __repr__(self) -> str: return f"_value({self._integer=}, {self._rule=})" def __add__(self, other: Any): if isinstance(other, int): other = self._rule(other) class _type: _context: Optional[_context] _width: int _behavior: _behavior _storage: _storage def __init__( self, width: int, behavior: _behavior, context: Optional[_context] = None, ) -> None: self._width = width self._behavior = behavior self._context = context self._storage = _storage.TWOS_COMPLEMENT def __call__(self, integer: int): return _value(self, integer, self._context) def __repr__(self) -> str: return f"_{self.__class__.__name__}({self._width=}, {self._behavior=})" class _unsigned(_type): pass class _signed(_type): pass class c_stdint(_context): _signed_behavior = _behavior( overflow=_behavior_overflow.TRUNCATE, promotion=_behavior_promotion.EXCEPTION, ) int8_t = _signed(8, _signed_behavior) int16_t = _signed(16, _signed_behavior) int32_t = _signed(32, _signed_behavior) int64_t = _signed(64, _signed_behavior) _unsigned_behavior = _behavior( overflow=_behavior_overflow.TRUNCATE, promotion=_behavior_promotion.EXCEPTION, ) uint8_t = _unsigned(8, _unsigned_behavior) uint16_t = _unsigned(16, _unsigned_behavior) uint32_t = _unsigned(32, _unsigned_behavior) uint64_t = _unsigned(64, _unsigned_behavior) class default(_context): """Some default values that do generally what people expect, these mimic the `c_stdint` context and are exported on the module level directly for short imports.""" _signed_behavior = _behavior( overflow=_behavior_overflow.TRUNCATE, promotion=_behavior_promotion.EXCEPTION, ) i8 = _signed(8, _signed_behavior) i16 = _signed(16, _signed_behavior) i32 = _signed(32, _signed_behavior) i64 = _signed(64, _signed_behavior) _unsigned_behavior = _behavior( overflow=_behavior_overflow.TRUNCATE, promotion=_behavior_promotion.EXCEPTION, ) u8 = _unsigned(8, _unsigned_behavior) u16 = _unsigned(16, _unsigned_behavior) u32 = _unsigned(32, _unsigned_behavior) u64 = _unsigned(64, _unsigned_behavior) # Exporting the `default` context for short imports. i8 = default.i8 i16 = default.i16 i32 = default.i32 i64 = default.i64 u8 = default.u8 u16 = default.u16 u32 = default.u32 u64 = default.u64

1,189

1,106

373

67cbdb578387f31a0a05cd7f49b7dda4d7c9a62c

172

py

Python

16-coroutine/example_16_1.py

hua372494277/fluent_python_example-code

07577e3e3ca822ab0e769bbaa22477fd988edb36

[ "MIT" ]

null

16-coroutine/example_16_1.py

hua372494277/fluent_python_example-code

07577e3e3ca822ab0e769bbaa22477fd988edb36

[ "MIT" ]

null

16-coroutine/example_16_1.py

hua372494277/fluent_python_example-code

07577e3e3ca822ab0e769bbaa22477fd988edb36

[ "MIT" ]

null

my_coro = simple_coroutine() next(my_coro) my_coro.send(42)

21.5

39

0.674419

def simple_coroutine(): print('-> coroutine started') x = yield print('-> coroutine received: ', x) my_coro = simple_coroutine() next(my_coro) my_coro.send(42)

90

0

22

a6bb3f10026fd14c5e3cb38dc7884cfc0cad2c28

193

py

Python

example_project/urls.py

justquick/django-sentry

07988759144524ba49bc63b308663244d1a69d04

[ "BSD-3-Clause" ]

1

2016-03-21T18:56:31.000Z

example_project/urls.py

justquick/django-sentry

07988759144524ba49bc63b308663244d1a69d04

[ "BSD-3-Clause" ]

null

example_project/urls.py

justquick/django-sentry

07988759144524ba49bc63b308663244d1a69d04

[ "BSD-3-Clause" ]

null

from django.conf.urls.defaults import * urlpatterns = patterns('', url(r'^trigger-500$', 'sentry.tests.views.raise_exc', name='sentry-raise-exc'), url(r'^', include('sentry.urls')), )

27.571429

83

0.668394

from django.conf.urls.defaults import * urlpatterns = patterns('', url(r'^trigger-500$', 'sentry.tests.views.raise_exc', name='sentry-raise-exc'), url(r'^', include('sentry.urls')), )

0

6ffdeaa033eaf21fe518e29893f1e57af448e9e1

2,012

py

Python

cruft/_commands/utils/diff.py

appunni-dishq/cruft

afa89a2856008bec49b31a90b6e3dd3c1eee24a9

[ "MIT" ]

null

cruft/_commands/utils/diff.py

appunni-dishq/cruft

afa89a2856008bec49b31a90b6e3dd3c1eee24a9

[ "MIT" ]

null

cruft/_commands/utils/diff.py

appunni-dishq/cruft

afa89a2856008bec49b31a90b6e3dd3c1eee24a9

[ "MIT" ]

null

from pathlib import Path from subprocess import PIPE, run # nosec from typing import List from cruft import exceptions def get_diff(repo0: Path, repo1: Path) -> str: """Compute the raw diff between two repositories.""" try: diff = run( _git_diff("--no-ext-diff", "--no-color", str(repo0), str(repo1)), cwd=str(repo0), stdout=PIPE, stderr=PIPE, ).stdout.decode() except UnicodeDecodeError: raise exceptions.ChangesetUnicodeError() # By default, git diff --no-index will output full paths like so: # --- a/tmp/tmpmp34g21y/remote/.coveragerc # +++ b/tmp/tmpmp34g21y/local/.coveragerc # We don't want this as we may need to apply the diff later on. # Note that diff headers contain repo0 and repo1 with both "a" and "b" # prefixes: headers for new files have a/repo1, headers for deleted files # have b/repo0. for repo in [repo0, repo1]: diff = diff.replace("a" + str(repo), "a").replace("b" + str(repo), "b") # This replacement is needed for renamed/moved files to be recognized properly # Renamed files in the diff don't have the "a" or "b" prefix and instead look like # /tmp/tmpmp34g21y/remote/.coveragerc # If we replace repo paths which are like /tmp/tmpmp34g21y/remote # we would end up with /.coveragerc which doesn't work. # We also need to replace the trailing slash. As a result, we only do # this after the above replacement is made as the trailing slash is needed there. diff = diff.replace(str(repo0) + "/", "").replace(str(repo1) + "/", "") return diff def display_diff(repo0: Path, repo1: Path): """Displays the diff between two repositories.""" run(_git_diff(str(repo0), str(repo1)))

42.808511

100

0.656064

from pathlib import Path from subprocess import PIPE, run # nosec from typing import List from cruft import exceptions def _git_diff(*args: str) -> List[str]: # https://git-scm.com/docs/git-diff#Documentation/git-diff.txt---binary support for binary patch return ["git", "-c", "diff.noprefix=", "diff", "--no-index", "--relative", "--binary", *args] def get_diff(repo0: Path, repo1: Path) -> str: """Compute the raw diff between two repositories.""" try: diff = run( _git_diff("--no-ext-diff", "--no-color", str(repo0), str(repo1)), cwd=str(repo0), stdout=PIPE, stderr=PIPE, ).stdout.decode() except UnicodeDecodeError: raise exceptions.ChangesetUnicodeError() # By default, git diff --no-index will output full paths like so: # --- a/tmp/tmpmp34g21y/remote/.coveragerc # +++ b/tmp/tmpmp34g21y/local/.coveragerc # We don't want this as we may need to apply the diff later on. # Note that diff headers contain repo0 and repo1 with both "a" and "b" # prefixes: headers for new files have a/repo1, headers for deleted files # have b/repo0. for repo in [repo0, repo1]: diff = diff.replace("a" + str(repo), "a").replace("b" + str(repo), "b") # This replacement is needed for renamed/moved files to be recognized properly # Renamed files in the diff don't have the "a" or "b" prefix and instead look like # /tmp/tmpmp34g21y/remote/.coveragerc # If we replace repo paths which are like /tmp/tmpmp34g21y/remote # we would end up with /.coveragerc which doesn't work. # We also need to replace the trailing slash. As a result, we only do # this after the above replacement is made as the trailing slash is needed there. diff = diff.replace(str(repo0) + "/", "").replace(str(repo1) + "/", "") return diff def display_diff(repo0: Path, repo1: Path): """Displays the diff between two repositories.""" run(_git_diff(str(repo0), str(repo1)))

217

0

23

fe150d05608dcd1ad34cb5b7bf40af7c9cb0ade8

6,990

py

Python

octopus/modules/doaj/models.py

CottageLabs/magnificent-octopus-oacwellcome-fork

b1c8c412cf9a3fe66fca1c8e92ed074c9821663e

[ "Apache-2.0" ]

2

2016-02-22T04:31:30.000Z

2021-08-03T23:58:36.000Z

octopus/modules/doaj/models.py

CottageLabs/magnificent-octopus-oacwellcome-fork

b1c8c412cf9a3fe66fca1c8e92ed074c9821663e

[ "Apache-2.0" ]

9

2015-01-04T14:00:05.000Z

2021-12-13T19:35:07.000Z

octopus/modules/doaj/models.py

CottageLabs/magnificent-octopus-oacwellcome-fork

b1c8c412cf9a3fe66fca1c8e92ed074c9821663e

[ "Apache-2.0" ]

3

2016-09-09T13:39:45.000Z

2018-02-19T14:23:12.000Z

from octopus.lib import dataobj BASE_ARTICLE_STRUCT = { "fields": { "id": {"coerce": "unicode"}, # Note that we'll leave these in for ease of use by the "created_date": {"coerce": "utcdatetime"}, # caller, but we'll need to ignore them on the conversion "last_updated": {"coerce": "utcdatetime"} # to the real object }, "objects": ["admin", "bibjson"], "structs": { "admin": { "fields": { "in_doaj": {"coerce": "bool", "get__default": False}, "publisher_record_id": {"coerce": "unicode"}, "upload_id": {"coerce": "unicode"} } }, "bibjson": { "fields": { "title": {"coerce": "unicode", "set__ignore_none": True}, "year": {"coerce": "unicode", "set__ignore_none": True}, "month": {"coerce": "unicode", "set__ignore_none": True}, "abstract": {"coerce": "unicode", "set__ignore_none": True} }, "lists": { "identifier": {"contains": "object"}, "link": {"contains": "object"}, "author": {"contains": "object"}, "keywords": {"coerce": "unicode", "contains": "field"}, "subject": {"contains": "object"}, }, "objects": [ "journal", ], "structs": { "identifier": { "fields": { "type": {"coerce": "unicode"}, "id": {"coerce": "unicode"} } }, "link": { "fields": { "type": {"coerce": "unicode"}, "url": {"coerce": "url"}, "content_type": {"coerce": "unicde"} } }, "author": { "fields": { "name": {"coerce": "unicode"}, "email": {"coerce": "unicode"}, "affiliation": {"coerce": "unicode"} } }, "journal": { "fields": { "start_page": {"coerce": "unicode", "set__ignore_none": True}, "end_page": {"coerce": "unicode", "set__ignore_none": True}, "volume": {"coerce": "unicode", "set__ignore_none": True}, "number": {"coerce": "unicode", "set__ignore_none": True}, "publisher": {"coerce": "unicode", "set__ignore_none": True}, "title": {"coerce": "unicode", "set__ignore_none": True}, "country": {"coerce": "unicode", "set__ignore_none": True} }, "lists": { "license": {"contains": "object"}, "language": {"coerce": "unicode", "contains": "field", "set__ignore_none": True} }, "structs": { "license": { "fields": { "title": {"coerce": "unicode"}, "type": {"coerce": "unicode"}, "url": {"coerce": "unicode"}, "version": {"coerce": "unicode"}, "open_access": {"coerce": "bool"}, } } } }, "subject": { "fields": { "scheme": {"coerce": "unicode"}, "term": {"coerce": "unicode"}, "code": {"coerce": "unicode"} } }, } } } } ARTICLE_REQUIRED = { "required": ["bibjson"], "structs": { "bibjson": { "required": [ "title", "author", # One author required "identifier" # One type of identifier is required ], "structs": { "identifier": { "required": ["type", "id"] }, "link": { "required": ["type", "url"] }, "author": { "required": ["name"] }, } } } }

34.097561

109

0.425322

from octopus.lib import dataobj BASE_ARTICLE_STRUCT = { "fields": { "id": {"coerce": "unicode"}, # Note that we'll leave these in for ease of use by the "created_date": {"coerce": "utcdatetime"}, # caller, but we'll need to ignore them on the conversion "last_updated": {"coerce": "utcdatetime"} # to the real object }, "objects": ["admin", "bibjson"], "structs": { "admin": { "fields": { "in_doaj": {"coerce": "bool", "get__default": False}, "publisher_record_id": {"coerce": "unicode"}, "upload_id": {"coerce": "unicode"} } }, "bibjson": { "fields": { "title": {"coerce": "unicode", "set__ignore_none": True}, "year": {"coerce": "unicode", "set__ignore_none": True}, "month": {"coerce": "unicode", "set__ignore_none": True}, "abstract": {"coerce": "unicode", "set__ignore_none": True} }, "lists": { "identifier": {"contains": "object"}, "link": {"contains": "object"}, "author": {"contains": "object"}, "keywords": {"coerce": "unicode", "contains": "field"}, "subject": {"contains": "object"}, }, "objects": [ "journal", ], "structs": { "identifier": { "fields": { "type": {"coerce": "unicode"}, "id": {"coerce": "unicode"} } }, "link": { "fields": { "type": {"coerce": "unicode"}, "url": {"coerce": "url"}, "content_type": {"coerce": "unicde"} } }, "author": { "fields": { "name": {"coerce": "unicode"}, "email": {"coerce": "unicode"}, "affiliation": {"coerce": "unicode"} } }, "journal": { "fields": { "start_page": {"coerce": "unicode", "set__ignore_none": True}, "end_page": {"coerce": "unicode", "set__ignore_none": True}, "volume": {"coerce": "unicode", "set__ignore_none": True}, "number": {"coerce": "unicode", "set__ignore_none": True}, "publisher": {"coerce": "unicode", "set__ignore_none": True}, "title": {"coerce": "unicode", "set__ignore_none": True}, "country": {"coerce": "unicode", "set__ignore_none": True} }, "lists": { "license": {"contains": "object"}, "language": {"coerce": "unicode", "contains": "field", "set__ignore_none": True} }, "structs": { "license": { "fields": { "title": {"coerce": "unicode"}, "type": {"coerce": "unicode"}, "url": {"coerce": "unicode"}, "version": {"coerce": "unicode"}, "open_access": {"coerce": "bool"}, } } } }, "subject": { "fields": { "scheme": {"coerce": "unicode"}, "term": {"coerce": "unicode"}, "code": {"coerce": "unicode"} } }, } } } } ARTICLE_REQUIRED = { "required": ["bibjson"], "structs": { "bibjson": { "required": [ "title", "author", # One author required "identifier" # One type of identifier is required ], "structs": { "identifier": { "required": ["type", "id"] }, "link": { "required": ["type", "url"] }, "author": { "required": ["name"] }, } } } } class Journal(dataobj.DataObj): def __init__(self, raw=None): super(Journal, self).__init__(raw, expose_data=True) def all_issns(self): issns = [] # get the issns from the identifiers record idents = self.bibjson.identifier if idents is not None: for ident in idents: if ident.type in ["pissn", "eissn"]: issns.append(ident.id) # FIXME: this could be made better by having the Journal struct here too, but for # the time being a catch on an AttributeError will suffice try: hist = self.bibjson.history except AttributeError: hist = None if hist is not None: for h in hist: idents = h.bibjson.identifier if idents is not None: for ident in idents: if ident.type in ["pissn", "eissn"]: issns.append(ident.id) return issns class Article(dataobj.DataObj): def __init__(self, raw=None): self._add_struct(BASE_ARTICLE_STRUCT) super(Article, self).__init__(raw, expose_data=True) def add_identifier(self, type, id): if type is None or id is None: return self._add_to_list("bibjson.identifier", {"type" : type, "id" : id}) def get_identifier(self, type): for id in self._get_list("bibjson.identifier"): if id.get("type") == type: return id.get("id") return None def add_link(self, type, url): if type is None or url is None: return self._add_to_list("bibjson.link", {"type" : type, "url" : url}) def get_link(self, type): for link in self._get_list("bibjson.link"): if link.get("type") == type: return link.get("url") return None def add_author(self, name): if name is None: return self._add_to_list("bibjson.author", {"name" : name}) def is_api_valid(self): try: a = ArticleValidator(self.data) except Exception as e: return False return True class ArticleValidator(dataobj.DataObj): def __init__(self, raw=None): self._add_struct(BASE_ARTICLE_STRUCT) self._add_struct(ARTICLE_REQUIRED) super(ArticleValidator, self).__init__(raw, expose_data=True)

2,057

39

336

e33d9c4b1e510869e7210b59656c9fa8baeead13

959

py

Python

h3m/rmg/dispatch_gen.py

dmitrystril/homm3tools

5687f581a4eb5e7b0e8f48794d7be4e3b0a8cc8b

[ "MIT" ]

113

2015-08-09T08:36:55.000Z

2022-03-21T10:42:46.000Z

h3m/rmg/dispatch_gen.py

dmitrystril/homm3tools

5687f581a4eb5e7b0e8f48794d7be4e3b0a8cc8b

[ "MIT" ]

40

2015-08-23T06:36:34.000Z

2022-01-03T21:19:40.000Z

h3m/rmg/dispatch_gen.py

dmitrystril/homm3tools

5687f581a4eb5e7b0e8f48794d7be4e3b0a8cc8b

[ "MIT" ]

27

2015-08-09T08:40:39.000Z

2022-03-28T08:03:12.000Z

import sys from random import * def dispatch_gen(settings, rmgseed = 0): """ Short function that prepares map generation and then dispatches to generation modules """ # Seed with a specific seed if one was provided if rmgseed != 0: print("seed:" + str(rmgseed)) seed(rmgseed) module_name = "modules.%s.__init__" % settings.module_name rmg_module = __import__(module_name, fromlist=[module_name]) max_attempts = 5 for i in range(max_attempts): hmap = None print("[i]At attempt %d of %d for for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) hmap = rmg_module.gen(settings) if hmap != None: print("[+]Successful at attempt %d/%d for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) break else: print("[!]Failed at attempt %d/%d for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) return hmap

31.966667

134

0.713243

import sys from random import * def dispatch_gen(settings, rmgseed = 0): """ Short function that prepares map generation and then dispatches to generation modules """ # Seed with a specific seed if one was provided if rmgseed != 0: print("seed:" + str(rmgseed)) seed(rmgseed) module_name = "modules.%s.__init__" % settings.module_name rmg_module = __import__(module_name, fromlist=[module_name]) max_attempts = 5 for i in range(max_attempts): hmap = None print("[i]At attempt %d of %d for for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) hmap = rmg_module.gen(settings) if hmap != None: print("[+]Successful at attempt %d/%d for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) break else: print("[!]Failed at attempt %d/%d for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) return hmap

0

82c564532f62f466d26f2f89f9095a93136b4581

1,793

py

Python

openff/benchmark/analysis/metrics.py

openforcefield/openff-benchmark

e27320922e7583e313eaf32119de863d23842217

[ "MIT" ]

6

2021-01-27T14:06:57.000Z

2022-03-01T12:54:42.000Z

openff/benchmark/analysis/metrics.py

openforcefield/openff-benchmark

e27320922e7583e313eaf32119de863d23842217

[ "MIT" ]

83

2020-07-31T18:10:47.000Z

2022-03-07T22:59:24.000Z

openff/benchmark/analysis/metrics.py

openforcefield/openff-benchmark

e27320922e7583e313eaf32119de863d23842217

[ "MIT" ]

1

2022-03-03T04:06:32.000Z

#!/usr/bin/env python """ metrics.py Metrics calculation for the analysis/report part of the openff-benchmark workflow By: David F. Hahn Version: Nov 25 2020 """ import numpy as np from rdkit import Chem from rdkit.Chem import TorsionFingerprints def calc_tfd(ref_mol, query_mol): """ Calculate Torsion Fingerprint Deviation between two molecular structures. RDKit is required for TFD calculation. References ---------- Modified from the following code: https://github.com/MobleyLab/benchmarkff/03_analysis/compare_ffs.py TFD reference: https://pubs.acs.org/doi/10.1021/ci2002318 Parameters ---------- ref_mol : RDKit RDMol query_mol : RDKit RDMol Returns ------- tfd : float Torsion Fingerprint Deviation between ref and query molecules """ # check if the molecules are the same # tfd requires the two molecules must be instances of the same molecule rsmiles = Chem.MolToSmiles(ref_mol) qsmiles = Chem.MolToSmiles(query_mol) if rsmiles != qsmiles: print( f"- WARNING: The reference mol {ref_mol.GetProp('_Name')} and " f"query mol {query_mol.GetProp('_Name')} do NOT have the same " f"SMILES strings as determined by RDKit MolToSmiles. " f"\n {rsmiles}\n {qsmiles}" ) tfd = np.nan # calculate the TFD else: try: tfd = TorsionFingerprints.GetTFDBetweenMolecules(ref_mol, query_mol) # triggered for molecules such as urea except IndexError: print( f"- Error calculating TFD on molecule {ref_mol.GetProp('_Name')}." " Possibly no non-terminal rotatable bonds found." ) tfd = np.nan return tfd

26.761194

82

0.636921

#!/usr/bin/env python """ metrics.py Metrics calculation for the analysis/report part of the openff-benchmark workflow By: David F. Hahn Version: Nov 25 2020 """ import numpy as np from rdkit import Chem from rdkit.Chem import TorsionFingerprints def calc_tfd(ref_mol, query_mol): """ Calculate Torsion Fingerprint Deviation between two molecular structures. RDKit is required for TFD calculation. References ---------- Modified from the following code: https://github.com/MobleyLab/benchmarkff/03_analysis/compare_ffs.py TFD reference: https://pubs.acs.org/doi/10.1021/ci2002318 Parameters ---------- ref_mol : RDKit RDMol query_mol : RDKit RDMol Returns ------- tfd : float Torsion Fingerprint Deviation between ref and query molecules """ # check if the molecules are the same # tfd requires the two molecules must be instances of the same molecule rsmiles = Chem.MolToSmiles(ref_mol) qsmiles = Chem.MolToSmiles(query_mol) if rsmiles != qsmiles: print( f"- WARNING: The reference mol {ref_mol.GetProp('_Name')} and " f"query mol {query_mol.GetProp('_Name')} do NOT have the same " f"SMILES strings as determined by RDKit MolToSmiles. " f"\n {rsmiles}\n {qsmiles}" ) tfd = np.nan # calculate the TFD else: try: tfd = TorsionFingerprints.GetTFDBetweenMolecules(ref_mol, query_mol) # triggered for molecules such as urea except IndexError: print( f"- Error calculating TFD on molecule {ref_mol.GetProp('_Name')}." " Possibly no non-terminal rotatable bonds found." ) tfd = np.nan return tfd

0

54f7bd38aa77922afb64699b585c50bd6c3ab6db

2,429

py

Python

simple_rest_client_example/resources.py

allisson/pythonbrasil-2018-exemplos

e106ba6d4833185566d4d306e8c108c97987350c

[ "MIT" ]

3

2018-10-17T12:34:12.000Z

2021-06-18T01:00:33.000Z

simple_rest_client_example/resources.py

allisson/pythonbrasil-2018-exemplos

e106ba6d4833185566d4d306e8c108c97987350c

[ "MIT" ]

null

simple_rest_client_example/resources.py

allisson/pythonbrasil-2018-exemplos

e106ba6d4833185566d4d306e8c108c97987350c

[ "MIT" ]

1

2018-10-22T12:52:34.000Z

from simple_rest_client.resource import AsyncResource, Resource films_actions = { 'list': { 'method': 'GET', 'url': 'films' }, 'retrieve': { 'method': 'GET', 'url': 'films/{}', }, 'schema': { 'method': 'GET', 'url': 'films/schema', }, } people_actions = { 'list': { 'method': 'GET', 'url': 'people' }, 'retrieve': { 'method': 'GET', 'url': 'people/{}', }, 'schema': { 'method': 'GET', 'url': 'people/schema', }, } planets_actions = { 'list': { 'method': 'GET', 'url': 'planets' }, 'retrieve': { 'method': 'GET', 'url': 'planets/{}', }, 'schema': { 'method': 'GET', 'url': 'planets/schema', }, } species_actions = { 'list': { 'method': 'GET', 'url': 'species' }, 'retrieve': { 'method': 'GET', 'url': 'species/{}', }, 'schema': { 'method': 'GET', 'url': 'species/schema', }, } starships_actions = { 'list': { 'method': 'GET', 'url': 'starships' }, 'retrieve': { 'method': 'GET', 'url': 'starships/{}', }, 'schema': { 'method': 'GET', 'url': 'starships/schema', }, } vehicles_actions = { 'list': { 'method': 'GET', 'url': 'vehicles' }, 'retrieve': { 'method': 'GET', 'url': 'vehicles/{}', }, 'schema': { 'method': 'GET', 'url': 'vehicles/schema', }, }

17.22695

63

0.532318

from simple_rest_client.resource import AsyncResource, Resource films_actions = { 'list': { 'method': 'GET', 'url': 'films' }, 'retrieve': { 'method': 'GET', 'url': 'films/{}', }, 'schema': { 'method': 'GET', 'url': 'films/schema', }, } people_actions = { 'list': { 'method': 'GET', 'url': 'people' }, 'retrieve': { 'method': 'GET', 'url': 'people/{}', }, 'schema': { 'method': 'GET', 'url': 'people/schema', }, } planets_actions = { 'list': { 'method': 'GET', 'url': 'planets' }, 'retrieve': { 'method': 'GET', 'url': 'planets/{}', }, 'schema': { 'method': 'GET', 'url': 'planets/schema', }, } species_actions = { 'list': { 'method': 'GET', 'url': 'species' }, 'retrieve': { 'method': 'GET', 'url': 'species/{}', }, 'schema': { 'method': 'GET', 'url': 'species/schema', }, } starships_actions = { 'list': { 'method': 'GET', 'url': 'starships' }, 'retrieve': { 'method': 'GET', 'url': 'starships/{}', }, 'schema': { 'method': 'GET', 'url': 'starships/schema', }, } vehicles_actions = { 'list': { 'method': 'GET', 'url': 'vehicles' }, 'retrieve': { 'method': 'GET', 'url': 'vehicles/{}', }, 'schema': { 'method': 'GET', 'url': 'vehicles/schema', }, } class FilmsAsyncResource(AsyncResource): actions = films_actions class FilmsResource(Resource): actions = films_actions class PeopleAsyncResource(AsyncResource): actions = people_actions class PeopleResource(Resource): actions = people_actions class PlanetsAsyncResource(AsyncResource): actions = planets_actions class PlanetsResource(Resource): actions = planets_actions class SpeciesAsyncResource(AsyncResource): actions = species_actions class SpeciesResource(Resource): actions = species_actions class StarshipsAsyncResource(AsyncResource): actions = starships_actions class StarshipsResource(Resource): actions = starships_actions class VehiclesAsyncResource(AsyncResource): actions = vehicles_actions class VehiclesResource(Resource): actions = vehicles_actions

0

552

276

2924a841e050929bf5200ad6aa6ce38ce0e83e43

2,035

py

Python

examples/OLX/gen.py

godber/banky

a3c41b810b16cce737f0ca7e2f1a10a32c3a5d66

[ "MIT" ]

null

examples/OLX/gen.py

godber/banky

a3c41b810b16cce737f0ca7e2f1a10a32c3a5d66

[ "MIT" ]

null

examples/OLX/gen.py

godber/banky

a3c41b810b16cce737f0ca7e2f1a10a32c3a5d66

[ "MIT" ]

null

#!/usr/bin/env python ''' Generates an EdX style XML question from the provided YAML question file. ''' from pathlib import Path from random import sample import click import yaml from lxml import etree @click.command() @click.argument('file_name') if __name__ == '__main__': gen()

31.796875

85

0.69828

#!/usr/bin/env python ''' Generates an EdX style XML question from the provided YAML question file. ''' from pathlib import Path from random import sample import click import yaml from lxml import etree @click.command() @click.argument('file_name') def gen(file_name): # Read and parse the YAML file containing the question try: f = open(file_name) question = yaml.safe_load(f) f.close() except Exception as e: raise e problem = etree.Element('problem') multiplechoiceresponse = etree.Element('multiplechoiceresponse') problem.append(multiplechoiceresponse) # Adding the label to multiplechoiceresponse label = etree.Element('label') label.text = question['label'] multiplechoiceresponse.append(label) # Adding the choicegroup to multiplechoiceresponse choicegroup = etree.Element('choicegroup', type='MultipleChoice') multiplechoiceresponse.append(choicegroup) # FIXME: Do I have to move this down? # Create a list of tuples like (choice, True or False) choice_list = [ (choice_value, truth_value) for truth_value in question['choices'] for choice_value in question['choices'][truth_value] ] # Randomize the choice_list using `random.sample` then create the choice # elements and add them to choicegroup. Note that since the truthiness # values are boolean True or False, the correct value will be True or False # (with first character capitalized), unlike the example EdX XML for (choice_text, truthiness) in sample(choice_list, k=len(choice_list)): choice = etree.Element("choice", correct=str(truthiness)) choice.text = choice_text choicegroup.append(choice) outfile = Path(Path(file_name).stem + '.xml') if outfile.exists(): print('WARNING: File exists, overwriting %s.' % outfile) # Write out the XML to a file. et = etree.ElementTree(problem) et.write(str(outfile), pretty_print=True) if __name__ == '__main__': gen()

1,721

0

22

e31990aebb31cb9c87884c60bbda3ef72156d0f7

695

py

Python

AveriguaNBisiestosRangoTiempo.py

brown9804/Python_DiversosAlgortimos

e9ff0fbe761f24a49a30a513d50824ca56cafaa3

[ "Apache-2.0" ]

3

2018-06-28T21:06:53.000Z

2018-07-01T20:39:30.000Z

AveriguaNBisiestosRangoTiempo.py

brown9804/Python_DiversosAlgortimos

e9ff0fbe761f24a49a30a513d50824ca56cafaa3

[ "Apache-2.0" ]

null

AveriguaNBisiestosRangoTiempo.py

brown9804/Python_DiversosAlgortimos

e9ff0fbe761f24a49a30a513d50824ca56cafaa3

[ "Apache-2.0" ]

null

#Python3 #Permite calcular cuantos años han sido bisiestos en un rango de años ###### DEFINICIONES ###### ###### IMPLEMENTACION ###### an1 = int(input("Digite el año mayor que desea comparar ")) an2 = int(input("Digite el año menor ")) dif = an1 - an2 cont = 0 for indice in range (an2, an1+1): if bisiesto(indice) == True: cont = cont + 1 print ("La diferencia entre ", an1, " y ", an2, " es de ", dif) if (cont >0): print ("Entre este intervalo de años hay ", cont, " años bisiestos ") else: print("No hay años bisiestos en este intervalo ")

26.730769

71

0.617266

#Python3 #Permite calcular cuantos años han sido bisiestos en un rango de años ###### DEFINICIONES ###### def bisiesto(year): if (year % 400 == 0) or ((year % 4 == 0) and (year % 100 != 0)): return True else: return False ###### IMPLEMENTACION ###### an1 = int(input("Digite el año mayor que desea comparar ")) an2 = int(input("Digite el año menor ")) dif = an1 - an2 cont = 0 for indice in range (an2, an1+1): if bisiesto(indice) == True: cont = cont + 1 print ("La diferencia entre ", an1, " y ", an2, " es de ", dif) if (cont >0): print ("Entre este intervalo de años hay ", cont, " años bisiestos ") else: print("No hay años bisiestos en este intervalo ")

100

0

22

401ef2ec5e7636f6f94cccb2e06d145d92e2d554

2,792

py

Python

supriya/commands/GroupFreeAllRequest.py

deeuu/supriya

14fcb5316eccb4dafbe498932ceff56e1abb9d27

[ "MIT" ]

null

supriya/commands/GroupFreeAllRequest.py

deeuu/supriya

14fcb5316eccb4dafbe498932ceff56e1abb9d27

[ "MIT" ]

null

supriya/commands/GroupFreeAllRequest.py

deeuu/supriya

14fcb5316eccb4dafbe498932ceff56e1abb9d27

[ "MIT" ]

null

import supriya.osc from supriya.commands.Request import Request from supriya.enums import RequestId class GroupFreeAllRequest(Request): """ A /g_freeAll request. :: >>> import supriya >>> server = supriya.Server.default().boot() >>> group = supriya.Group().allocate() >>> group.extend([supriya.Synth(), supriya.Group()]) >>> group[1].extend([supriya.Synth(), supriya.Group()]) >>> group[1][1].extend([supriya.Synth(), supriya.Group()]) :: >>> print(server) NODE TREE 0 group 1 group 1000 group 1001 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1002 group 1003 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1004 group 1005 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1006 group :: >>> request = supriya.commands.GroupFreeAllRequest(group) >>> request.to_osc() OscMessage('/g_freeAll', 1000) :: >>> with server.osc_protocol.capture() as transcript: ... request.communicate(server=server) ... _ = server.sync() ... :: >>> for entry in transcript: ... (entry.label, entry.message) ... ('S', OscMessage('/g_freeAll', 1000)) ('S', OscMessage('/sync', 2)) ('R', OscMessage('/n_end', 1001, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1003, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1005, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1006, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/n_end', 1004, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/n_end', 1002, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/synced', 2)) :: >>> print(server) NODE TREE 0 group 1 group 1000 group :: >>> print(server.query_local_nodes(True)) NODE TREE 0 group 1 group 1000 group """ ### CLASS VARIABLES ### request_id = RequestId.GROUP_FREE_ALL ### INITIALIZER ### ### PUBLIC METHODS ### ### PUBLIC PROPERTIES ### @property

27.372549

95

0.493911

import supriya.osc from supriya.commands.Request import Request from supriya.enums import RequestId class GroupFreeAllRequest(Request): """ A /g_freeAll request. :: >>> import supriya >>> server = supriya.Server.default().boot() >>> group = supriya.Group().allocate() >>> group.extend([supriya.Synth(), supriya.Group()]) >>> group[1].extend([supriya.Synth(), supriya.Group()]) >>> group[1][1].extend([supriya.Synth(), supriya.Group()]) :: >>> print(server) NODE TREE 0 group 1 group 1000 group 1001 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1002 group 1003 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1004 group 1005 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1006 group :: >>> request = supriya.commands.GroupFreeAllRequest(group) >>> request.to_osc() OscMessage('/g_freeAll', 1000) :: >>> with server.osc_protocol.capture() as transcript: ... request.communicate(server=server) ... _ = server.sync() ... :: >>> for entry in transcript: ... (entry.label, entry.message) ... ('S', OscMessage('/g_freeAll', 1000)) ('S', OscMessage('/sync', 2)) ('R', OscMessage('/n_end', 1001, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1003, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1005, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1006, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/n_end', 1004, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/n_end', 1002, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/synced', 2)) :: >>> print(server) NODE TREE 0 group 1 group 1000 group :: >>> print(server.query_local_nodes(True)) NODE TREE 0 group 1 group 1000 group """ ### CLASS VARIABLES ### request_id = RequestId.GROUP_FREE_ALL ### INITIALIZER ### def __init__(self, group_id): Request.__init__(self) self._group_id = group_id ### PUBLIC METHODS ### def to_osc(self, *, with_placeholders=False): request_id = self.request_name group_id = int(self.group_id) message = supriya.osc.OscMessage(request_id, group_id) return message ### PUBLIC PROPERTIES ### @property def group_id(self): return self._group_id

288

0

80

617d920f815b114aee02c2dc33fc7ac71fb36f20

3,426

py

Python

code/agents/on_policy/ppo.py

arjunchandra/continuous-rl

8f3c655c6a4b2e9d15a6b052e5466c0a75191a08

[ "MIT" ]

17

2019-03-29T18:30:36.000Z

2021-10-17T15:38:22.000Z

code/agents/on_policy/ppo.py

arjunchandra/continuous-rl

8f3c655c6a4b2e9d15a6b052e5466c0a75191a08

[ "MIT" ]

1

2019-04-22T22:40:30.000Z

2019-04-24T21:45:07.000Z

code/agents/on_policy/ppo.py

ctallec/continuous-rl

8f3c655c6a4b2e9d15a6b052e5466c0a75191a08

[ "MIT" ]

5

2019-04-29T16:26:18.000Z

2020-01-23T07:17:49.000Z

from itertools import chain from logging import info import torch from mylog import log from memory.trajectory import Trajectory from optimizer import setup_optimizer from agents.on_policy.online_agent import OnlineAgent from actors.on_policy.online_actor import OnlineActor from critics.on_policy.online_critic import OnlineCritic class PPOAgent(OnlineAgent): """One variant of Proximal Policy Optimizaation agent :args T: number of max steps used for bootstrapping (to be computationnally efficient, bootstrapping horizon is variable). :args actor: actor used :args critic: critic used :args opt_name: 'rmsprop' ('sgd' deprecated) :args lr: unscaled learning rate :args dt: framerate :args weigth_decay: weight decay """

39.37931

100

0.643608

from itertools import chain from logging import info import torch from mylog import log from memory.trajectory import Trajectory from optimizer import setup_optimizer from agents.on_policy.online_agent import OnlineAgent from actors.on_policy.online_actor import OnlineActor from critics.on_policy.online_critic import OnlineCritic class PPOAgent(OnlineAgent): """One variant of Proximal Policy Optimizaation agent :args T: number of max steps used for bootstrapping (to be computationnally efficient, bootstrapping horizon is variable). :args actor: actor used :args critic: critic used :args opt_name: 'rmsprop' ('sgd' deprecated) :args lr: unscaled learning rate :args dt: framerate :args weigth_decay: weight decay """ def __init__(self, T: int, actor: OnlineActor, critic: OnlineCritic, learn_per_step: int, batch_size: int, opt_name: str, lr: float, dt: float, weight_decay: float): OnlineAgent.__init__(self, T=T, actor=actor, critic=critic) self._learn_per_step = learn_per_step self._batch_size = batch_size self._optimizer = setup_optimizer( chain(self._actor._policy_function.parameters(), self._critic._v_function.parameters()), opt_name=opt_name, lr=lr, dt=dt, inverse_gradient_magnitude=1, weight_decay=weight_decay) def learn(self) -> None: if (self._count + 1) % self._T != 0: return None traj = Trajectory.tobatch(*self._current_trajectories).to(self._device) v, v_target = self._critic.value_batch(traj) obs_flat = traj.obs.flatten(0, 1) actions_flat = traj.actions.flatten(0, 1) distr_flat = self._actor._distr_generator( self._actor.policy(traj.obs.flatten(0, 1))) old_distr = distr_flat.copy() old_logp = distr_flat.log_prob(actions_flat).clone().detach() old_v = v.flatten().clone().detach() critic_value_flat = (v_target - v).flatten() full_batch_size = traj.length * traj.batch_size for ep in range(self._learn_per_step): perm = torch.randperm(full_batch_size) for start in range(0, full_batch_size // self._batch_size, self._batch_size): idxs = perm[start:start+self._batch_size] v = self._critic.value(obs_flat[idxs]).squeeze() critic_loss = self._critic.loss( v, v_target.flatten()[idxs].detach(), old_v[idxs].detach()) loss_actor = self._actor.loss( distr=self._actor._distr_generator(self._actor.policy(obs_flat[idxs])), actions=actions_flat[idxs], critic_value=critic_value_flat[idxs], old_logp=old_logp[idxs], old_distr=old_distr[idxs] ) loss = loss_actor + critic_loss self._optimizer.zero_grad() loss.backward() self._optimizer.step() critic_loss = critic_loss.mean().item() critic_value = critic_value_flat.mean().item() info(f'At step {self._count}, critic loss: {critic_loss}') info(f'At step {self._count}, critic value: {critic_value}') log("loss/critic", critic_loss, self._count) log("value/critic", critic_value, self._count) self._actor.log() self._critic.log()

2,601

0

53

db4f23ef884783a4a230a932eac3a80a44e8dffd

4,569

py

Python

code/tasks/REGEX/trainers/executor.py

khanhptnk/iliad

3eb4f11c1d3cdb6784fd2f78a83ce07f984d3825

[ "MIT" ]

7

2021-06-10T22:17:13.000Z

2022-03-03T05:58:55.000Z

code/tasks/REGEX/trainers/executor.py

khanhptnk/iliad

3eb4f11c1d3cdb6784fd2f78a83ce07f984d3825

[ "MIT" ]

null

code/tasks/REGEX/trainers/executor.py

khanhptnk/iliad

3eb4f11c1d3cdb6784fd2f78a83ce07f984d3825

[ "MIT" ]

null

import logging import os import sys sys.path.append('..') import itertools import json import random import torch from misc import util

29.101911

78

0.516743

import logging import os import sys sys.path.append('..') import itertools import json import random import torch from misc import util class ExecutorTrainer(object): def __init__(self, config): self.config = config self.random = random.Random(self.config.seed) def do_rollout(self, batch, executor, is_eval): src_words = [] tgt_words = [] instructions = [] batch_size = len(batch) for item in batch: src_words.append(item['src_word']) tgt_words.append(item['tgt_word']) instructions.append(item['instruction']) executor.init(src_words, instructions, is_eval) t = 0 golds = [None] * batch_size while not executor.has_terminated(): for i in range(batch_size): if t + 1 < len(tgt_words[i]): golds[i] = tgt_words[i][t + 1] else: golds[i] = '<PAD>' executor.act(gold_actions=golds) t += 1 def train(self, datasets, executor): max_iters = self.config.trainer.max_iters log_every = self.config.trainer.log_every i_iter = 0 total_loss = 0 best_eval_loss = 1e9 best_eval_acc = -1e9 for batch in datasets['train'].iterate_batches(): i_iter += 1 self.do_rollout(batch, executor, False) loss = executor.learn() total_loss += loss if i_iter % log_every == 0: avg_loss = total_loss / log_every total_loss = 0 log_str = 'Train iter %d (%d%%): ' % \ (i_iter, i_iter / max_iters * 100) log_str += 'loss = %.4f' % avg_loss logging.info('') logging.info(log_str) # Save last model executor.save('last') # Save best model eval_info = self.evaluate(datasets['val'], executor) eval_loss = eval_info['loss'] eval_acc = eval_info['acc'] eval_preds = eval_info['pred'] if eval_acc > best_eval_acc: logging.info('New best acc: %.1f' % eval_acc) best_eval_acc = eval_acc executor.save('best_dev') self.save_preds('best_dev', eval_preds) self.save_preds('last', eval_preds) if i_iter >= max_iters: break def evaluate(self, dataset, executor, save_pred=False): losses = [] all_preds = [] is_match = [] for i, batch in enumerate(dataset.iterate_batches()): with torch.no_grad(): # Compute loss on unseen data self.do_rollout(batch, executor, False) loss = executor.compute_loss().item() losses.append(loss) # Make predictions src_words = [item['src_word'] for item in batch] instructions = [item['instruction'] for item in batch] preds = executor.predict(src_words, instructions) for item, pred in zip(batch, preds): new_item = {} new_item.update(item) pred = ''.join(pred) gold = ''.join(new_item['tgt_word']) new_item['pred'] = pred is_match.append(gold == pred) new_item['is_match'] = is_match[-1] new_item['src_word'] = ''.join(new_item['src_word']) new_item['tgt_word'] = ''.join(new_item['tgt_word']) new_item['instruction'] = ' '.join(new_item['instruction']) all_preds.append(new_item) avg_loss = sum(losses) / len(losses) acc = sum(is_match) / len(is_match) * 100 log_str = 'Evaluation on %s: ' % dataset.split log_str += 'loss = %.1f' % avg_loss log_str += ', acc = %.1f' % acc logging.info(log_str) if save_pred: self.save_preds(dataset.split, all_preds) eval_info = { 'acc' : acc, 'loss': avg_loss, 'pred': all_preds, } return eval_info def save_preds(self, filename, all_preds): file_path = '%s/%s' % (self.config.experiment_dir, filename + '.pred') with open(file_path, 'w') as f: json.dump(all_preds, f, indent=2) logging.info('Saved eval info to %s' % file_path)

4,262

9

158

d5d37258f5db0c94fe2805ed35fc6221e3fda39b

11,999

py

Python

DICOM/ParametricMapsDictionary.py

QIB-Sheffield/WEASEL

e4dad345fd6f347cfac990708252844a7cbcd025

[ "Apache-2.0" ]

2

2021-02-10T09:07:15.000Z

2021-03-16T17:05:24.000Z

DICOM/ParametricMapsDictionary.py

QIB-Sheffield/WEASEL

e4dad345fd6f347cfac990708252844a7cbcd025

[ "Apache-2.0" ]

102

2021-01-20T11:14:21.000Z

2021-12-12T17:34:42.000Z

DICOM/ParametricMapsDictionary.py

QIB-Sheffield/WEASEL

e4dad345fd6f347cfac990708252844a7cbcd025

[ "Apache-2.0" ]

1

2021-01-29T09:28:05.000Z

""" This module is used in `SaveDICOM_Image.py` and used as the optional argument `parametric_map` in write functions of `Classes.py` and in "writeNewPixelArray" of `DeveloperTools.py`. The functions in this module capture special versions of DICOM with unique parameters/attributes/values. **How to use:** provide the parametric_map in the functions mentioned previously as a string. This string is the name of one of the functions in the ParametricClass (eg. parametric_map="RGB" or parametric_map="SEG") """ import pydicom from pydicom.dataset import Dataset from pydicom.sequence import Sequence import numpy as np import datetime import struct # Could insert a method regarding ROI colours, like in ITK-SNAP??? # rwv_sequence = Sequence() # dicom.RealWorldValueMappingSequence = rwv_sequence # rwv_slope = Dataset() # rwv_slope.RealWorldValueSlope = 1 # rwv_sequence.append(rwv_slope) # quantity_def = Dataset() # quantity_def_sequence = Sequence() # quantity_def.QuantityDefinitionSequence = quantity_def_sequence # value_type = Dataset() # value_type.ValueType = "CODE" # quantity_def_sequence.append(value_type) # concept_code = Dataset() # concept_code_sequence = Sequence() # concept_code.ConceptCodeSequence = concept_code_sequence # code_code = Dataset() # code_code.CodeValue = "113041" # code_code.CodingSchemeDesignator = "DCM" # code_code.CodeMeaning = "Apparent Diffusion Coefficient" # concept_code_sequence.append(code_code) # rwv_sequence.append(quantity_def) # measure_units = Dataset() # measure_units_sequence = Sequence() # measure_units.MeasurementUnitsCodeSequence = measure_units_sequence # measure_code = Dataset() # measure_code.CodeValue = "um2/s" # measure_code.CodingSchemeDesignator = "UCUM" # measure_code.CodeMeaning = "um2/s" # measure_units_sequence.append(measure_code) # rwv_sequence.append(measure_units)

51.497854

215

0.685557

""" This module is used in `SaveDICOM_Image.py` and used as the optional argument `parametric_map` in write functions of `Classes.py` and in "writeNewPixelArray" of `DeveloperTools.py`. The functions in this module capture special versions of DICOM with unique parameters/attributes/values. **How to use:** provide the parametric_map in the functions mentioned previously as a string. This string is the name of one of the functions in the ParametricClass (eg. parametric_map="RGB" or parametric_map="SEG") """ import pydicom from pydicom.dataset import Dataset from pydicom.sequence import Sequence import numpy as np import datetime import struct def editDicom(newDicom, imageArray, parametricMap): callCase = ParametricClass() callCase.selectParametricMap(newDicom, imageArray, parametricMap) dt = datetime.datetime.now() timeStr = dt.strftime('%H%M%S') # long format with micro seconds newDicom.PerformedProcedureStepStartDate = dt.strftime('%Y%m%d') newDicom.PerformedProcedureStepStartTime = timeStr newDicom.PerformedProcedureStepDescription = "Post-processing application" return newDicom class ParametricClass(object): def selectParametricMap(self, dicom, imageArray, argument): methodName = argument method = getattr(self, methodName, lambda: "No valid Parametric Map chosen") return method(dicom, imageArray) def RGB(self, dicom, imageArray): dicom.PhotometricInterpretation = 'RGB' dicom.SamplesPerPixel = 3 dicom.BitsAllocated = 8 dicom.BitsStored = 8 dicom.HighBit = 7 dicom.add_new(0x00280006, 'US', 0) # Planar Configuration dicom.RescaleSlope = 1 dicom.RescaleIntercept = 0 pixelArray = imageArray.astype(np.uint8) # Should we multiply by 255? dicom.WindowCenter = int((np.amax(imageArray) - np.amin(imageArray)) / 2) dicom.WindowWidth = np.absolute(int(np.amax(imageArray) - np.amin(imageArray))) dicom.PixelData = pixelArray.tobytes() return def ADC(self, dicom, imageArray): # The commented parts are to apply when we decide to include Parametric Map IOD. No readers can deal with this yet # dicom.SOPClassUID = '1.2.840.10008.5.1.4.1.1.67' dicom.SeriesDescription = "Apparent Diffusion Coefficient (um2/s)" dicom.Modality = "RWV" dicom.FrameLaterality = "U" dicom.DerivedPixelContrast = "ADC" dicom.BitsAllocated = 32 dicom.PixelRepresentation = 1 dicom.PhotometricInterpretation = "MONOCHROME2" dicom.PixelAspectRatio = ["1", "1"] # Need to have a better look at this dicom.RescaleSlope = 1 dicom.RescaleIntercept = 0 # Rotate the image back to the original orientation imageArray = np.transpose(imageArray) dicom.Rows = np.shape(imageArray)[-2] dicom.Columns = np.shape(imageArray)[-1] dicom.WindowCenter = int((np.amax(imageArray) - np.amin(imageArray)) / 2) dicom.WindowWidth = np.absolute(int(np.amax(imageArray) - np.amin(imageArray))) dicom.FloatPixelData = bytes(imageArray.astype(np.float32).flatten()) del dicom.PixelData, dicom.BitsStored, dicom.HighBit dicom.RealWorldValueMappingSequence = [Dataset(), Dataset(), Dataset(), Dataset()] dicom.RealWorldValueMappingSequence[0].QuantityDefinitionSequence = [Dataset(), Dataset()] dicom.RealWorldValueMappingSequence[0].QuantityDefinitionSequence[0].ValueType = "CODE" dicom.RealWorldValueMappingSequence[0].QuantityDefinitionSequence[1].ConceptCodeSequence = [Dataset(), Dataset(), Dataset()] dicom.RealWorldValueMappingSequence[0].QuantityDefinitionSequence[1].ConceptCodeSequence[0].CodeValue = "113041" dicom.RealWorldValueMappingSequence[0].QuantityDefinitionSequence[1].ConceptCodeSequence[1].CodingSchemeDesignator = "DCM" dicom.RealWorldValueMappingSequence[0].QuantityDefinitionSequence[1].ConceptCodeSequence[2].CodeMeaning = "Apparent Diffusion Coefficient" dicom.RealWorldValueMappingSequence[1].MeasurementUnitsCodeSequence = [Dataset(), Dataset(), Dataset()] dicom.RealWorldValueMappingSequence[1].MeasurementUnitsCodeSequence[0].CodeValue = "um2/s" dicom.RealWorldValueMappingSequence[1].MeasurementUnitsCodeSequence[1].CodingSchemeDesignator = "UCUM" dicom.RealWorldValueMappingSequence[1].MeasurementUnitsCodeSequence[2].CodeMeaning = "um2/s" dicom.RealWorldValueMappingSequence[2].RealWorldValueSlope = 1 anatomyString = dicom.BodyPartExamined saveAnatomicalInfo(anatomyString, dicom.RealWorldValueMappingSequence[3]) return def T2Star(self, dicom, imageArray): dicom.PixelSpacing = [3, 3] # find a mechanism to pass reconstruct pixel here return def SEG(self, dicom, imageArray): #dicom.SOPClassUID = '1.2.840.10008.5.1.4.1.1.66.4' # WILL NOT BE USED HERE - This is for PACS. There will be another one for DICOM Standard # The commented parts are to apply when we decide to include SEG IOD. No readers can deal with this yet dicom.BitsAllocated = 8 # According to Federov DICOM Standard this should be 1-bit dicom.BitsStored = 8 dicom.HighBit = 7 #dicom.SmallestImagePixelValue = 0 #dicom.LargestImagePixelValue = int(np.amax(imageArray)) # max 255 dicom.add_new('0x00280106', 'US', 0) # Minimum dicom.add_new('0x00280107', 'US', int(np.amax(imageArray))) # Maximum dicom.PixelRepresentation = 0 dicom.SamplesPerPixel = 1 #dicom.WindowCenter = 0.5 #dicom.WindowWidth = 1.1 dicom.add_new('0x00281050', 'DS', 0.5) # WindowCenter dicom.add_new('0x00281051', 'DS', 1.1) # WindowWidth #dicom.RescaleIntercept = 0 #dicom.RescaleSlope = 1 dicom.add_new('0x00281052', 'DS', 0) # RescaleIntercept dicom.add_new('0x00281053', 'DS', 1) # RescaleSlope dicom.LossyImageCompression = '00' pixelArray = np.transpose(imageArray.astype(np.uint8)) # Should we multiply by 255? dicom.PixelData = pixelArray.tobytes() dicom.Modality = 'SEG' dicom.SegmentationType = 'FRACTIONAL' dicom.MaximumFractionalValue = int(np.amax(imageArray)) # max 255 dicom.SegmentationFractionalType = 'OCCUPANCY' # Segment Labels if hasattr(dicom, "ImageComments"): dicom.ContentDescription = dicom.ImageComments.split('_')[-1] # 'Image segmentation' segment_numbers = np.unique(pixelArray) segment_dictionary = dict(list(enumerate(segment_numbers))) segment_label = dicom.ImageComments.split('_')[-1] segment_dictionary[0] = 'Background' segment_dictionary[1] = segment_label for key in segment_dictionary: dicom.SegmentSequence = [Dataset(), Dataset(), Dataset(), Dataset(), Dataset(), Dataset()] dicom.SegmentSequence[0].SegmentAlgorithmType = 'MANUAL' dicom.SegmentSequence[1].SegmentNumber = key dicom.SegmentSequence[2].SegmentDescription = str(segment_dictionary[key]) dicom.SegmentSequence[3].SegmentLabel = str(segment_dictionary[key]) dicom.SegmentSequence[4].SegmentAlgorithmName = "Weasel" if hasattr(dicom, "BodyPartExamined"): anatomyString = dicom.BodyPartExamined saveAnatomicalInfo(anatomyString, dicom.SegmentSequence[5]) else: dicom.ContentDescription = "Mask with no label" return def Registration(self, dicom, imageArray): dicom.Modality = "REG" return def Signal(self, dicom, imageArray): dicom.Modality = "RWV" dicom.DerivedPixelContrast = "GraphPlot" dicom.PhotometricInterpretation = "MONOCHROME2" dicom.RescaleSlope = 1 dicom.RescaleIntercept = 0 imageArray = np.transpose(imageArray.astype(np.float32)) center = (np.amax(imageArray) + np.amin(imageArray)) / 2 width = np.amax(imageArray) - np.amin(imageArray) dicom.add_new('0x00281050', 'DS', center) dicom.add_new('0x00281051', 'DS', width) dicom.BitsAllocated = 32 dicom.Rows = np.shape(imageArray)[0] dicom.Columns = np.shape(imageArray)[1] dicom.FloatPixelData = bytes(imageArray.flatten()) del dicom.PixelData, dicom.BitsStored, dicom.HighBit return # Could insert a method regarding ROI colours, like in ITK-SNAP??? def saveAnatomicalInfo(anatomyString, dicom): try: # FOR NOW, THE PRIORITY WILL BE ON KIDNEY if "KIDNEY" or "ABDOMEN" in anatomyString.upper(): dicom.AnatomicRegionSequence = [Dataset(), Dataset(), Dataset()] dicom.AnatomicRegionSequence[0].CodeValue = "T-71000" dicom.AnatomicRegionSequence[1].CodingSchemeDesignator = "SRT" dicom.AnatomicRegionSequence[2].CodeMeaning = "Kidney" elif "LIVER" in anatomyString.upper(): dicom.AnatomicRegionSequence = [Dataset(), Dataset(), Dataset()] dicom.AnatomicRegionSequence[0].CodeValue = "T-62000" dicom.AnatomicRegionSequence[1].CodingSchemeDesignator = "SRT" dicom.AnatomicRegionSequence[2].CodeMeaning = "Liver" elif "PROSTATE" in anatomyString.upper(): dicom.AnatomicRegionSequence = [Dataset(), Dataset(), Dataset()] dicom.AnatomicRegionSequence[0].CodeValue = "T-9200B" dicom.AnatomicRegionSequence[1].CodingSchemeDesignator = "SRT" dicom.AnatomicRegionSequence[2].CodeMeaning = "Prostate" elif "BODY" in anatomyString.upper(): dicom.AnatomicRegionSequence = [Dataset(), Dataset(), Dataset()] dicom.AnatomicRegionSequence[0].CodeValue = "P5-0905E" dicom.AnatomicRegionSequence[1].CodingSchemeDesignator = "LN" dicom.AnatomicRegionSequence[2].CodeMeaning = "MRI whole body" except: pass return # Series, Instance and Class for Reference #newDicom.ReferencedSeriesSequence = [Dataset(), Dataset()] #newDicom.ReferencedSeriesSequence[0].SeriesInstanceUID = dicom_data.SeriesInstanceUID #newDicom.ReferencedSeriesSequence[1].ReferencedInstanceSequence = [Dataset(), Dataset()] #newDicom.ReferencedSeriesSequence[1].ReferencedInstanceSequence[0].ReferencedSOPClassUID = dicom_data.SOPClassUID #newDicom.ReferencedSeriesSequence[1].ReferencedInstanceSequence[1].ReferencedSOPInstanceUID = dicom_data.SOPInstanceUID # rwv_sequence = Sequence() # dicom.RealWorldValueMappingSequence = rwv_sequence # rwv_slope = Dataset() # rwv_slope.RealWorldValueSlope = 1 # rwv_sequence.append(rwv_slope) # quantity_def = Dataset() # quantity_def_sequence = Sequence() # quantity_def.QuantityDefinitionSequence = quantity_def_sequence # value_type = Dataset() # value_type.ValueType = "CODE" # quantity_def_sequence.append(value_type) # concept_code = Dataset() # concept_code_sequence = Sequence() # concept_code.ConceptCodeSequence = concept_code_sequence # code_code = Dataset() # code_code.CodeValue = "113041" # code_code.CodingSchemeDesignator = "DCM" # code_code.CodeMeaning = "Apparent Diffusion Coefficient" # concept_code_sequence.append(code_code) # rwv_sequence.append(quantity_def) # measure_units = Dataset() # measure_units_sequence = Sequence() # measure_units.MeasurementUnitsCodeSequence = measure_units_sequence # measure_code = Dataset() # measure_code.CodeValue = "um2/s" # measure_code.CodingSchemeDesignator = "UCUM" # measure_code.CodeMeaning = "um2/s" # measure_units_sequence.append(measure_code) # rwv_sequence.append(measure_units)

9,657

9

258

4f5dc02bbb6371303a2f5b9a9f2436c462178b54

670

py

Python

templates/dags/example_dag.py

dfedde/terraform-aws-ecs-airflow

e928c9272d8735809341e1225551e00cb83270de

[ "MIT" ]

42

2020-10-30T11:54:08.000Z

2022-03-21T11:02:32.000Z

templates/dags/example_dag.py

dfedde/terraform-aws-ecs-airflow

e928c9272d8735809341e1225551e00cb83270de

[ "MIT" ]

20

2020-11-18T15:12:08.000Z

2022-02-07T15:36:54.000Z

templates/dags/example_dag.py

dfedde/terraform-aws-ecs-airflow

e928c9272d8735809341e1225551e00cb83270de

[ "MIT" ]

24

2020-11-19T21:00:57.000Z

2022-03-21T11:02:36.000Z

from datetime import timedelta, datetime from airflow import DAG from airflow.operators.dummy_operator import DummyOperator from airflow import AirflowException args = { "owner": "dataroots", "start_date": datetime(2020, 10, 12), } with DAG( dag_id="example_dag", catchup=False, max_active_runs=1, default_args=args, schedule_interval="*/5 * * * *" ) as dag: task_a = DummyOperator( task_id="task_a" ) task_b = DummyOperator( task_id="task_b" ) task_c = DummyOperator( task_id="task_c" ) task_d = DummyOperator( task_id="task_d" ) task_a >> [task_b, task_c] >> task_d

19.142857

58

0.638806

from datetime import timedelta, datetime from airflow import DAG from airflow.operators.dummy_operator import DummyOperator from airflow import AirflowException args = { "owner": "dataroots", "start_date": datetime(2020, 10, 12), } with DAG( dag_id="example_dag", catchup=False, max_active_runs=1, default_args=args, schedule_interval="*/5 * * * *" ) as dag: task_a = DummyOperator( task_id="task_a" ) task_b = DummyOperator( task_id="task_b" ) task_c = DummyOperator( task_id="task_c" ) task_d = DummyOperator( task_id="task_d" ) task_a >> [task_b, task_c] >> task_d

0

541ef5d535e996184c73e8580bacc44fd0c90d6d

1,582

py

Python

tests/operation/test_bump_sequence.py

Shaptic/py-stellar-base

f5fa47f4d96f215889d99249fb25c7be002f5cf3

[ "Apache-2.0" ]

null

tests/operation/test_bump_sequence.py

Shaptic/py-stellar-base

f5fa47f4d96f215889d99249fb25c7be002f5cf3

[ "Apache-2.0" ]

27

2022-01-12T10:55:38.000Z

2022-03-28T01:38:24.000Z

tests/operation/test_bump_sequence.py

Shaptic/py-stellar-base

f5fa47f4d96f215889d99249fb25c7be002f5cf3

[ "Apache-2.0" ]

2

2021-12-02T12:42:03.000Z

2021-12-07T20:53:10.000Z

import pytest from stellar_sdk import BumpSequence, Operation from . import *

32.958333

99

0.569532

import pytest from stellar_sdk import BumpSequence, Operation from . import * class TestBumpSequence: @pytest.mark.parametrize( "bump_to, source, xdr", [ pytest.param( 1234567890, None, "AAAAAAAAAAsAAAAASZYC0g==", id="without_source" ), pytest.param( 1234567890, kp1.public_key, "AAAAAQAAAABiXz1Zw/ieWRoG2l4IxdbkvfDRUDq5wyKBSUnrCR5doQAAAAsAAAAASZYC0g==", id="with_source_public_key", ), pytest.param( 1234567890, muxed1, "AAAAAQAAAQAAAAAAAAAAAWJfPVnD+J5ZGgbaXgjF1uS98NFQOrnDIoFJSesJHl2hAAAACwAAAABJlgLS", id="with_source_muxed_account", ), pytest.param( 1234567890, muxed1.account_muxed, "AAAAAQAAAQAAAAAAAAAAAWJfPVnD+J5ZGgbaXgjF1uS98NFQOrnDIoFJSesJHl2hAAAACwAAAABJlgLS", id="with_source_muxed_account_strkey", ), pytest.param( 0, kp1.public_key, "AAAAAQAAAABiXz1Zw/ieWRoG2l4IxdbkvfDRUDq5wyKBSUnrCR5doQAAAAsAAAAAAAAAAA==", id="bump_to_0", ), ], ) def test_xdr(self, bump_to, source, xdr): op = BumpSequence(bump_to, source) assert op.bump_to == bump_to check_source(op.source, source) xdr_object = op.to_xdr_object() assert xdr_object.to_xdr() == xdr assert Operation.from_xdr_object(xdr_object) == op

281

1,197

23

d2d300c5b67883d38f70b2c1b58d33ec2b7b239c

6,778

py

Python

solver.py

aelkouk/rainfall_runoff

7ab984c77abbef38c768fea9993b0cfecaca3e67

[ "MIT" ]

null

solver.py

aelkouk/rainfall_runoff

7ab984c77abbef38c768fea9993b0cfecaca3e67

[ "MIT" ]

null

solver.py

aelkouk/rainfall_runoff

7ab984c77abbef38c768fea9993b0cfecaca3e67

[ "MIT" ]

null

# Purpose: Implement time stepping scheme to solve individual and coupled state equations # Record of revisions: # Date Programmer Description of change # ======== ============= ===================== # 09-2020 A. Elkouk Original code import numpy as np # ---------------------------------------------------------------------------------------------------------------------- # Explicit (forward) Euler method # ---------------------------------------------------------------------------------------------------------------------- def explicitEuler(f_S, S0, T, dt, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) S0 : float State initial condition at t=0 T : float or int Time period [days] dt : float or int Time step [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated state for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) t = np.zeros(n + 1) dS = np.zeros(n + 1) dS[0] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt dS[k + 1] = dS[k] + (dt * f_S(dS[k], **kwargs)) if dS[k + 1] < 0.0: dS[k + 1] = 0.0 return dS, t def explicitEuler_coupled_states(f_S, S0, T, dt, precip, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps Parameters ---------- f_S : function Coupled state function of the model sub-domains (e.g. canopy, unsaturated zone, and saturated zone) S0 : array_like State initial conditions at t=0 (e.g. [canopy, unsaturated zone, and saturated zone]) T : float or int Time period [days] dt : float or int Time step [days] precip : array_like Precipitation flux [mm days^-1] at n=T/dt time step kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated states for n=T/dt time steps with shape (n, nbr_states) RO : ndarray Total runoff [mm day^-1] for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) nS = len(S0) t = np.zeros(n + 1) dS = np.zeros((n + 1, nS)) RO = np.zeros(n + 1) dS[0, :] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt Sk, RO_k = f_S(dS[k], precip[k], **kwargs) RO[k] = RO_k dS[k + 1, :] = dS[k, :] + (dt * np.array(Sk)) dS = np.where(dS < 0.0, 0.0, dS) return dS, RO, t # ---------------------------------------------------------------------------------------------------------------------- # Heun's method # ---------------------------------------------------------------------------------------------------------------------- def Heun(f_S, S0, T, dt, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps using the explicit Heun's method Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) S0 : float State initial condition at t=0 T : float or int Time period [days] dt : float or int Time step [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated state for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) t = np.zeros(n + 1) dS = np.zeros(n + 1) dS[0] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt K1 = f_S(dS[k], **kwargs) K2 = f_S((K1 * dt) + dS[k], **kwargs) dS[k + 1] = dS[k] + (0.5 * dt * (K1 + K2)) if dS[k + 1] < 0.0: dS[k + 1] = 0.0 return dS, t def Heun_ndt(f_S, Si, dt, T, **kwargs): """ Solve dS/dt = f_S(S, t), S(t=t_i)=Si, at t=T with n steps (n=T/dt), using the explicit Heun's method Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) Si : float State at time t=t_i dt : float or int Time step [days] T : float or int Time period [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : float Integrated state at t=ndt with n=T/dt """ n = int(T / dt) dS = Si for _ in range(n): K1 = f_S(dS, **kwargs) K2 = f_S((K1 * dt) + dS, **kwargs) dS = dS + (0.5 * dt * (K1 + K2)) return dS def Heun_adaptive_substep(f_S, Si, dt, T, tau_r, tau_abs, s=0.9, rmin=0.1, rmax=4.0, EPS=10 ** (-10), **kwargs): """ Solve dS/dt = f_S(S, t), S(t=t_i)=Si, using the explicit Heun's method with numerical error control and adaptive sub stepping Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) Si : float State at time t=t_i dt : float or int Time step [days] T : float or int Time period [days] tau_r : float Relative truncation error tolerance tau_abs : float Absolute truncation error tolerance s : float Safety factor rmin, rmax : float Step size multiplier constraints EPS : float Machine constant kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : list Integrated state time : list Time steps [days] """ t = 0 dS = [Si] time = [t] while t < T: t += dt y1 = Heun_ndt(f_S, Si, dt, dt, **kwargs) y2 = Heun_ndt(f_S, Si, dt/2, dt, **kwargs) err = abs(y1 - y2) diff = err - ((tau_r * abs(y2)) + tau_abs) if diff < 0: Si = y2 dS.append(Si) time.append(dt) dt = dt * min(s * np.sqrt((tau_r * abs(y2) + tau_abs) / (max(err, EPS))), rmax) elif diff > 0: t -= dt dt = dt * max(s * np.sqrt((tau_r * abs(y2) + tau_abs) / (max(err, EPS))), rmin) return dS, time

30.669683

121

0.482001

# Purpose: Implement time stepping scheme to solve individual and coupled state equations # Record of revisions: # Date Programmer Description of change # ======== ============= ===================== # 09-2020 A. Elkouk Original code import numpy as np # ---------------------------------------------------------------------------------------------------------------------- # Explicit (forward) Euler method # ---------------------------------------------------------------------------------------------------------------------- def explicitEuler(f_S, S0, T, dt, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) S0 : float State initial condition at t=0 T : float or int Time period [days] dt : float or int Time step [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated state for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) t = np.zeros(n + 1) dS = np.zeros(n + 1) dS[0] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt dS[k + 1] = dS[k] + (dt * f_S(dS[k], **kwargs)) if dS[k + 1] < 0.0: dS[k + 1] = 0.0 return dS, t def explicitEuler_coupled_states(f_S, S0, T, dt, precip, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps Parameters ---------- f_S : function Coupled state function of the model sub-domains (e.g. canopy, unsaturated zone, and saturated zone) S0 : array_like State initial conditions at t=0 (e.g. [canopy, unsaturated zone, and saturated zone]) T : float or int Time period [days] dt : float or int Time step [days] precip : array_like Precipitation flux [mm days^-1] at n=T/dt time step kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated states for n=T/dt time steps with shape (n, nbr_states) RO : ndarray Total runoff [mm day^-1] for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) nS = len(S0) t = np.zeros(n + 1) dS = np.zeros((n + 1, nS)) RO = np.zeros(n + 1) dS[0, :] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt Sk, RO_k = f_S(dS[k], precip[k], **kwargs) RO[k] = RO_k dS[k + 1, :] = dS[k, :] + (dt * np.array(Sk)) dS = np.where(dS < 0.0, 0.0, dS) return dS, RO, t # ---------------------------------------------------------------------------------------------------------------------- # Heun's method # ---------------------------------------------------------------------------------------------------------------------- def Heun(f_S, S0, T, dt, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps using the explicit Heun's method Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) S0 : float State initial condition at t=0 T : float or int Time period [days] dt : float or int Time step [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated state for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) t = np.zeros(n + 1) dS = np.zeros(n + 1) dS[0] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt K1 = f_S(dS[k], **kwargs) K2 = f_S((K1 * dt) + dS[k], **kwargs) dS[k + 1] = dS[k] + (0.5 * dt * (K1 + K2)) if dS[k + 1] < 0.0: dS[k + 1] = 0.0 return dS, t def Heun_ndt(f_S, Si, dt, T, **kwargs): """ Solve dS/dt = f_S(S, t), S(t=t_i)=Si, at t=T with n steps (n=T/dt), using the explicit Heun's method Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) Si : float State at time t=t_i dt : float or int Time step [days] T : float or int Time period [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : float Integrated state at t=ndt with n=T/dt """ n = int(T / dt) dS = Si for _ in range(n): K1 = f_S(dS, **kwargs) K2 = f_S((K1 * dt) + dS, **kwargs) dS = dS + (0.5 * dt * (K1 + K2)) return dS def Heun_adaptive_substep(f_S, Si, dt, T, tau_r, tau_abs, s=0.9, rmin=0.1, rmax=4.0, EPS=10 ** (-10), **kwargs): """ Solve dS/dt = f_S(S, t), S(t=t_i)=Si, using the explicit Heun's method with numerical error control and adaptive sub stepping Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) Si : float State at time t=t_i dt : float or int Time step [days] T : float or int Time period [days] tau_r : float Relative truncation error tolerance tau_abs : float Absolute truncation error tolerance s : float Safety factor rmin, rmax : float Step size multiplier constraints EPS : float Machine constant kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : list Integrated state time : list Time steps [days] """ t = 0 dS = [Si] time = [t] while t < T: t += dt y1 = Heun_ndt(f_S, Si, dt, dt, **kwargs) y2 = Heun_ndt(f_S, Si, dt/2, dt, **kwargs) err = abs(y1 - y2) diff = err - ((tau_r * abs(y2)) + tau_abs) if diff < 0: Si = y2 dS.append(Si) time.append(dt) dt = dt * min(s * np.sqrt((tau_r * abs(y2) + tau_abs) / (max(err, EPS))), rmax) elif diff > 0: t -= dt dt = dt * max(s * np.sqrt((tau_r * abs(y2) + tau_abs) / (max(err, EPS))), rmin) return dS, time

0

2ec73a56298eb3c73e3a8b581f56a8d1965c7550

1,260

py

Python

specs/env/when.py

bitgn/ml-pipelines

904b6fa200aac1638491658c2d51ea40c33cbffa

[ "BSD-2-Clause" ]

7

2019-07-25T05:36:21.000Z

2020-08-23T18:04:53.000Z

specs/env/when.py

bitgn/ml-pipelines

904b6fa200aac1638491658c2d51ea40c33cbffa

[ "BSD-2-Clause" ]

1

2019-08-18T14:05:49.000Z

2019-08-18T17:51:39.000Z

specs/env/when.py

bitgn/ml-pipelines

904b6fa200aac1638491658c2d51ea40c33cbffa

[ "BSD-2-Clause" ]

4

2019-08-18T13:42:45.000Z

2021-04-04T11:15:21.000Z

from typing import Optional, Callable, Any import grpc import requests as r import env import urllib.parse as url import inspect from client import ml_pipelines as cl import test_api as api

24.705882

90

0.692857

from typing import Optional, Callable, Any import grpc import requests as r import env import urllib.parse as url import inspect from client import ml_pipelines as cl import test_api as api def view_dataset(project, dataset): return _get_page("view_dataset", env.urls.view_dataset(project, dataset)) def search_datasets(query): return _get_page(f"search datasets for {query}", env.urls.search_datasets(query)) def view_project(project_id): return _get_page("view project", env.urls.view_project(project_id)) def list_datasets(): return _get_page("list datasets", env.urls.list_datasets()) def list_projects(): return _get_page("list projects", env.urls.list_projects()) def client(l: Callable[[cl.Client], Any], text:Optional[str]=None): def _(c: cl.Client): try: return l(c) except cl.ClientError as e: return e if not text: text = '('+inspect.getsource(l).replace("when.client(lambda c:", "").strip('\n ,') return env.When(web_action=None, client_action=_, text=text) def _get_page(text, uri): def _(c: r.Session, base: str): full = url.urljoin(base, uri) return c.get(full) return env.When(web_action=_, text=text, client_action=None)

901

0

161

e7600c142bd7e27a405fac85062163bfc718090f

134

py

Python

mybitbank/libs/jsonrpc/authproxy.py

zonedoutspace/mybitbank

85d28726117a3c1ca76be5772d30c9edae1df7f4

[ "MIT" ]

15

2015-08-29T12:35:59.000Z

2018-02-06T06:26:26.000Z

mybitbank/libs/jsonrpc/authproxy.py

FireWalkerX/mybitbank

945e604e5fee3914c7c98a25c2c34831ba0ad946

[ "MIT" ]

null

mybitbank/libs/jsonrpc/authproxy.py

FireWalkerX/mybitbank

945e604e5fee3914c7c98a25c2c34831ba0ad946

[ "MIT" ]

19

2015-02-03T21:32:51.000Z

2021-11-06T12:08:26.000Z

from mybitbank.libs.bitcoinrpc.authproxy import AuthServiceProxy, JSONRPCException __all__ = ['AuthServiceProxy', 'JSONRPCException']

44.666667

82

0.843284

from mybitbank.libs.bitcoinrpc.authproxy import AuthServiceProxy, JSONRPCException __all__ = ['AuthServiceProxy', 'JSONRPCException']

0

c316d4e0585be0a5ee8136f55d032f0e3e48ad80

51,673

py

Python

pineboolib/plugins/sql/flmysql_myisam2.py

deavid/pineboo

acc96ab6d5b8bb182990af6dea4bf0986af15549

[ "MIT" ]

2

2015-09-19T16:54:49.000Z

2016-09-12T08:06:29.000Z

pineboolib/plugins/sql/flmysql_myisam2.py

deavid/pineboo

acc96ab6d5b8bb182990af6dea4bf0986af15549

[ "MIT" ]

1

2017-08-14T17:07:14.000Z

2017-08-15T00:22:47.000Z

pineboolib/plugins/sql/flmysql_myisam2.py

deavid/pineboo

acc96ab6d5b8bb182990af6dea4bf0986af15549

[ "MIT" ]

9

2015-01-15T18:15:42.000Z

2019-05-05T18:53:00.000Z

""" Module for MYISAM2 driver. """ from PyQt5.Qt import qWarning, QApplication, QRegExp # type: ignore from PyQt5.QtXml import QDomDocument # type: ignore from PyQt5.QtWidgets import QMessageBox, QWidget # type: ignore from pineboolib.core.utils.utils_base import auto_qt_translate_text from pineboolib.application.utils.check_dependencies import check_dependencies from pineboolib.application.database.pnsqlquery import PNSqlQuery from pineboolib.application.database.pnsqlcursor import PNSqlCursor from pineboolib.core.utils.utils_base import text2bool from pineboolib.application.metadata.pnfieldmetadata import PNFieldMetaData from pineboolib.fllegacy import flapplication from pineboolib.fllegacy.flutil import FLUtil from pineboolib.application import project import traceback from pineboolib import logging from PyQt5.QtCore import QTime, QDate, QDateTime, Qt # type: ignore from typing import Any, Iterable, Optional, Union, List, Dict, cast logger = logging.getLogger(__name__) class FLMYSQL_MYISAM2(object): """MYISAM2 Driver class.""" version_: str conn_ = None name_: str alias_: str lastError_: Optional[str] cursorsArray_: Dict[str, Any] # IApiCursor noInnoDB: bool mobile_: bool pure_python_: bool defaultPort_: int cursor_ = None db_ = None engine_ = None session_ = None declarative_base_ = None def __init__(self): """Create empty driver.""" self.version_ = "0.8" self.conn_ = None self.name_ = "FLMYSQL_MyISAM2" self.open_ = False self.alias_ = "MySQL MyISAM (PyMySQL)" self.cursorsArray_ = {} self.noInnoDB = True self._dbname = None self.mobile_ = True self.pure_python_ = True self.defaultPort_ = 3306 self.rowsFetched: Dict[str, int] = {} self.active_create_index = True self.db_ = None self.engine_ = None self.session_ = None self.declarative_base_ = None self.lastError_ = None def version(self) -> str: """Get driver version.""" return self.version_ def driverName(self) -> str: """Get driver name.""" return self.name_ def pure_python(self) -> bool: """Return if this driver is pure python.""" return self.pure_python_ def safe_load(self) -> Any: """Check dependencies for this driver.""" return check_dependencies({"pymysql": "PyMySQL", "sqlalchemy": "sqlAlchemy"}, False) def mobile(self) -> bool: """Check if is suitable for mobile platform.""" return self.mobile_ def isOpen(self) -> bool: """Return if driver has an open connection.""" return self.open_ def DBName(self) -> Any: """Return database name.""" return self._dbname def connect(self, db_name, db_host, db_port, db_userName, db_password) -> Any: """Connect to a database.""" self._dbname = db_name check_dependencies({"pymysql": "PyMySQL", "sqlalchemy": "sqlAlchemy"}) from sqlalchemy import create_engine # type: ignore import pymysql try: self.conn_ = pymysql.connect( host=db_host, user=db_userName, password=db_password, db=db_name, charset="utf8", autocommit=True, ) self.engine_ = create_engine( "mysql+mysqldb://%s:%s@%s:%s/%s" % (db_userName, db_password, db_host, db_port, db_name) ) except pymysql.Error as e: if project._splash: project._splash.hide() if "Unknown database" in str(e): if project._DGI and not project.DGI.localDesktop(): return False ret = QMessageBox.warning( QWidget(), "Pineboo", "La base de datos %s no existe.\n¿Desea crearla?" % db_name, cast(QMessageBox, QMessageBox.Ok | QMessageBox.No), ) if ret == QMessageBox.No: return False else: try: tmpConn = pymysql.connect( host=db_host, user=db_userName, password=db_password, charset="utf8", autocommit=True, ) cursor = tmpConn.cursor() try: cursor.execute("CREATE DATABASE %s" % db_name) except Exception: print("ERROR: FLMYSQL2.connect", traceback.format_exc()) cursor.execute("ROLLBACK") cursor.close() return False cursor.close() return self.connect(db_name, db_host, db_port, db_userName, db_password) except Exception: qWarning(traceback.format_exc()) QMessageBox.information( QWidget(), "Pineboo", "ERROR: No se ha podido crear la Base de Datos %s" % db_name, QMessageBox.Ok, ) print("ERROR: No se ha podido crear la Base de Datos %s" % db_name) return False else: QMessageBox.information( QWidget(), "Pineboo", "Error de conexión\n%s" % str(e), QMessageBox.Ok ) return False if self.conn_: self.open_ = True # self.conn_.autocommit(True) # self.conn_.set_character_set('utf8') return self.conn_ def cursor(self) -> Any: """Get current cursor for db.""" if not self.conn_: raise Exception("Not connected") if not self.cursor_: self.cursor_ = self.conn_.cursor() return self.cursor_ def engine(self) -> Any: """Get current driver engine.""" return self.engine_ def session(self) -> None: """Get sqlAlchemy session.""" if self.session_ is None: from sqlalchemy.orm import sessionmaker # type: ignore # from sqlalchemy import event # from pineboolib.pnobjectsfactory import before_commit, after_commit Session = sessionmaker(bind=self.engine()) self.session_ = Session() # event.listen(Session, 'before_commit', before_commit, self.session_) # event.listen(Session, 'after_commit', after_commit, self.session_) def declarative_base(self) -> Any: """Get sqlAlchemy declarative base.""" if self.declarative_base_ is None: from sqlalchemy.ext.declarative import declarative_base # type: ignore self.declarative_base_ = declarative_base() return self.declarative_base_ def formatValueLike(self, type_, v: Any, upper) -> str: """Format value for database LIKE expression.""" res = "IS NULL" if v: if type_ == "bool": s = str(v[0]).upper() if s == flapplication.aqApp.tr("Sí")[0].upper(): res = "=1" elif flapplication.aqApp.tr("No")[0].upper(): res = "=0" elif type_ == "date": from pineboolib.application.utils.date_conversion import date_dma_to_amd date_amd = date_dma_to_amd(str(v)) if date_amd: res = " LIKE '%" + date_amd + "'" else: logger.warning("formatValueLike: failed to convert %s to ISO date format", v) elif type_ == "time": t = v.toTime() res = " LIKE '" + t.toString(Qt.ISODate) + "%'" else: res = str(v) if upper: res = res.upper() res = " LIKE '" + res + "%'" return res def formatValue(self, type_, v: Any, upper) -> Union[str, bool, None]: """Format value for database WHERE comparison.""" # util = FLUtil() s: Union[str, bool, None] = None # if v == None: # v = "" # TODO: psycopg2.mogrify ??? if v is None: return "NULL" if type_ == "bool" or type_ == "unlock": s = text2bool(v) elif type_ == "date": # val = util.dateDMAtoAMD(v) val = v if val is None: s = "Null" else: s = "'%s'" % val elif type_ == "time": s = "'%s'" % v elif type_ in ("uint", "int", "double", "serial"): if s == "Null": s = "0" else: s = v elif type_ in ("string", "stringlist"): if v == "": s = "Null" else: if type_ == "string": v = auto_qt_translate_text(v) if upper and type_ == "string": v = v.upper() s = "'%s'" % v elif type_ == "pixmap": if v.find("'") > -1: v = self.normalizeValue(v) s = "'%s'" % v else: s = v # print ("PNSqlDriver(%s).formatValue(%s, %s) = %s" % (self.name_, type_, v, s)) return s def tables(self, type_name=None) -> list: """Introspect tables in database.""" tl: List[str] = [] if not self.isOpen(): return tl q_tables = PNSqlQuery() q_tables.exec_("show tables") while q_tables.next(): tl.append(q_tables.value(0)) return tl def nextSerialVal(self, table, field) -> Any: """Get next serial value for given table and field.""" if not self.isOpen(): logger.warning("%s::beginTransaction: Database not open", self.name_) return None # if not self.transaction(): # self.setLastError("No se puede iniciar la transacción", "BEGIN WORK") # return None max = 0 cur_max = 0 updateQry = False ret = None q = PNSqlQuery() q.setSelect("max(%s)" % field) q.setFrom(table) q.setWhere("1 = 1") if not q.exec_(): logger.warning("not exec sequence") return None if q.first() and q.value(0) is not None: max = q.value(0) if not self.conn_: raise Exception("must be connected") cursor = self.conn_.cursor() strQry: Optional[str] = "SELECT seq FROM flseqs WHERE tabla = '%s' AND campo ='%s'" % ( table, field, ) try: cur_max = 0 cursor.execute(strQry) line = cursor.fetchone() if line: cur_max = line[0] except Exception: logger.warning( "%s:: La consulta a la base de datos ha fallado", self.name_, traceback.format_exc() ) self.rollbackTransaction() return if cur_max > 0: updateQry = True ret = cur_max else: ret = max ret += 1 strQry = None if updateQry: if ret > cur_max: strQry = "UPDATE flseqs SET seq=%s WHERE tabla = '%s' AND campo = '%s'" % ( ret, table, field, ) else: strQry = "INSERT INTO flseqs (tabla,campo,seq) VALUES('%s','%s',%s)" % ( table, field, ret, ) if strQry is not None: try: cursor.execute(strQry) except Exception: logger.warning( "%s:: La consulta a la base de datos ha fallado\n %s", self.name_, traceback.format_exc(), ) self.rollbackTransaction() return # if not self.commitTransaction(): # qWarning("%s:: No se puede aceptar la transacción" % self.name_) # return None return ret def queryUpdate(self, name, update, filter) -> str: """Return a templates UPDATE sql.""" sql = "UPDATE %s SET %s WHERE %s" % (name, update, filter) return sql def savePoint(self, n) -> bool: """Perform a transaction savepoint.""" if n == 0: return True if not self.isOpen(): logger.warning("%s::savePoint: Database not open", self.name_) return False cursor = self.cursor() try: cursor.execute("SAVEPOINT sv_%s" % n) except Exception: self.setLastError("No se pudo crear punto de salvaguarda", "SAVEPOINT sv_%s" % n) logger.warning( "MySQLDriver:: No se pudo crear punto de salvaguarda SAVEPOINT sv_%s \n %s ", n, traceback.format_exc(), ) return False return True def canSavePoint(self) -> bool: """Retrieve if this driver can perform savepoints.""" return False def canTransaction(self) -> bool: """Retrieve if this driver can perform transactions.""" return False def rollbackSavePoint(self, n) -> bool: """Rollback transaction to last savepoint.""" if n == 0: return True if not self.isOpen(): logger.warning("%s::rollbackSavePoint: Database not open", self.name_) return False cursor = self.cursor() try: cursor.execute("ROLLBACK TO SAVEPOINT sv_%s" % n) except Exception: self.setLastError( "No se pudo rollback a punto de salvaguarda", "ROLLBACK TO SAVEPOINTt sv_%s" % n ) logger.warning( "%s:: No se pudo rollback a punto de salvaguarda ROLLBACK TO SAVEPOINT sv_%s\n %s", self.name_, n, traceback.format_exc(), ) return False return True def setLastError(self, text, command) -> None: """Set last error from database.""" self.lastError_ = "%s (%s)" % (text, command) def lastError(self) -> Optional[str]: """Get last error happened on database.""" return self.lastError_ def commitTransaction(self) -> bool: """Commit database transaction.""" if not self.isOpen(): logger.warning("%s::commitTransaction: Database not open", self.name_) cursor = self.cursor() try: cursor.execute("COMMIT") except Exception: self.setLastError("No se pudo aceptar la transacción", "COMMIT") logger.warning( "%s:: No se pudo aceptar la transacción COMMIT\n %s", self.name_, traceback.format_exc(), ) return False return True def rollbackTransaction(self) -> bool: """Rollback database transaction.""" if not self.isOpen(): logger.warning("%s::rollbackTransaction: Database not open", self.name_) cursor = self.cursor() if self.canSavePoint(): try: cursor.execute("ROLLBACK") except Exception: self.setLastError("No se pudo deshacer la transacción", "ROLLBACK") logger.warning( "%s:: No se pudo deshacer la transacción ROLLBACK\n %s", self.name_, traceback.format_exc(), ) return False else: qWarning( "%s:: No se pudo deshacer la transacción ROLLBACK\n %s" % (self.name_, traceback.format_exc()) ) return True def transaction(self) -> bool: """Start new database transaction.""" if not self.isOpen(): logger.warning("%s::transaction: Database not open", self.name_) cursor = self.cursor() try: cursor.execute("START TRANSACTION") except Exception: self.setLastError("No se pudo crear la transacción", "BEGIN WORK") logger.warning( "%s:: No se pudo crear la transacción BEGIN\n %s", self.name_, traceback.format_exc(), ) return False return True def releaseSavePoint(self, n) -> bool: """Remove named savepoint from database.""" if n == 0: return True if not self.isOpen(): qWarning("%s::releaseSavePoint: Database not open" % self.name_) return False cursor = self.cursor() try: cursor.execute("RELEASE SAVEPOINT sv_%s" % n) except Exception: self.setLastError( "No se pudo release a punto de salvaguarda", "RELEASE SAVEPOINT sv_%s" % n ) qWarning( "MySQLDriver:: No se pudo release a punto de salvaguarda RELEASE SAVEPOINT sv_%s\n %s" % (n, traceback.format_exc()) ) return False return True def setType(self, type_, leng=None) -> str: """Template a SQL data type.""" if leng: return "::%s(%s)" % (type_, leng) else: return "::%s" % type_ def refreshQuery(self, curname, fields, table, where, cursor, conn) -> None: """Perform a query.""" if curname not in self.cursorsArray_.keys(): self.cursorsArray_[curname] = cursor sql = "SELECT %s FROM %s WHERE %s " % (fields, table, where) sql = self.fix_query(sql) try: self.cursorsArray_[curname].execute(sql) except Exception: print("*", sql) qWarning("CursorTableModel.Refresh\n %s" % traceback.format_exc()) def fix_query(self, val: str) -> str: """Fix values on SQL.""" ret_ = val.replace("'true'", "1") ret_ = ret_.replace("'false'", "0") ret_ = ret_.replace("'0'", "0") ret_ = ret_.replace("'1'", "1") # ret_ = ret_.replace(";", "") return ret_ def useThreads(self) -> bool: """Return if this driver supports threads.""" return False def useTimer(self) -> bool: """Return if this driver supports timer.""" return True def fetchAll(self, cursor, tablename, where_filter, fields, curname) -> List[Any]: """Fetch all pending rows on cursor.""" if curname not in self.rowsFetched.keys(): self.rowsFetched[curname] = 0 rowsF = [] try: rows = list(self.cursorsArray_[curname]) if self.rowsFetched[curname] < len(rows): i = 0 for row in rows: i += 1 if i > self.rowsFetched[curname]: rowsF.append(row) self.rowsFetched[curname] = i except Exception: logger.error("%s:: fetchAll:%s", self.name_, traceback.format_exc()) return rowsF def existsTable(self, name) -> bool: """Return if table exists.""" if not self.isOpen(): return False t = PNSqlQuery() t.setForwardOnly(True) ok = t.exec_("SHOW TABLES LIKE '%s'" % name) if ok: ok = t.next() return ok def sqlCreateTable(self, tmd) -> Optional[str]: """Create a table from given MTD.""" # util = FLUtil() if not tmd: return None primaryKey = None sql = "CREATE TABLE %s (" % tmd.name() # seq = None fieldList = tmd.fieldList() unlocks = 0 for field in fieldList: if field.type() == "unlock": unlocks += 1 if unlocks > 1: qWarning(u"%s : No se ha podido crear la tabla %s" % (self.name_, tmd.name())) qWarning(u"%s : Hay mas de un campo tipo unlock. Solo puede haber uno." % self.name_) return None i = 1 for field in fieldList: sql = sql + field.name() if field.type() == "int": sql += " INT" elif field.type() in ["uint", "serial"]: sql += " INT UNSIGNED" elif field.type() in ("bool", "unlock"): sql += " BOOL" elif field.type() == "double": sql += " DECIMAL(%s,%s)" % ( field.partInteger() + field.partDecimal() + 5, field.partDecimal() + 5, ) elif field.type() == "time": sql += " TIME" elif field.type() == "date": sql += " DATE" elif field.type() in ["pixmap", "stringlist"]: sql += " MEDIUMTEXT" elif field.type() == "string": if field.length() > 0: if field.length() > 255: sql += " VARCHAR" else: sql += " CHAR" sql += "(%s)" % field.length() else: sql += " CHAR(255)" elif field.type() == "bytearray": sql = sql + " LONGBLOB" if field.isPrimaryKey(): if primaryKey is None: sql += " PRIMARY KEY" primaryKey = field.name() else: qWarning( QApplication.tr("FLManager : Tabla-> ") + tmd.name() + QApplication.tr( " . Se ha intentado poner una segunda clave primaria para el campo " ) + field.name() + QApplication.tr(" , pero el campo ") + primaryKey + QApplication.tr( " ya es clave primaria. Sólo puede existir una clave primaria en FLTableMetaData," " use FLCompoundKey para crear claves compuestas." ) ) return None else: if field.isUnique(): sql += " UNIQUE" if not field.allowNull(): sql += " NOT NULL" else: sql += " NULL" if not i == len(fieldList): sql += "," i = i + 1 engine = ") ENGINE=INNODB" if not self.noInnoDB else ") ENGINE=MyISAM" sql += engine sql += " DEFAULT CHARACTER SET = utf8 COLLATE = utf8_bin" qWarning("NOTICE: CREATE TABLE (%s%s)" % (tmd.name(), engine)) return sql def Mr_Proper(self) -> None: """Cleanup database like mr.proper.""" util = FLUtil() if not self.db_: raise Exception("must be connected") self.db_.dbAux().transaction() qry = PNSqlQuery(None, "dbAux") qry2 = PNSqlQuery(None, "dbAux") qry3 = PNSqlQuery(None, "dbAux") # qry4 = PNSqlQuery(None, "dbAux") # qry5 = PNSqlQuery(None, "dbAux") steps = 0 self.active_create_index = False rx = QRegExp("^.*\\d{6,9}$") if rx in self.tables(): listOldBks = self.tables()[rx] else: listOldBks = [] qry.exec_( "select nombre from flfiles where nombre regexp" "'.*[[:digit:]][[:digit:]][[:digit:]][[:digit:]]-[[:digit:]][[:digit:]].*:[[:digit:]][[:digit:]]$' or nombre regexp" "'.*alteredtable[[:digit:]][[:digit:]][[:digit:]][[:digit:]].*' or (bloqueo=0 and nombre like '%.mtd')" ) util.createProgressDialog(util.tr("Borrando backups"), len(listOldBks) + qry.size() + 2) while qry.next(): item = qry.value(0) util.setLabelText(util.tr("Borrando registro %s") % item) qry2.exec_("DELETE FROM flfiles WHERE nombre ='%s'" % item) if item.find("alteredtable") > -1: if self.existsTable(item.replace(".mtd", "")): util.setLabelText(util.tr("Borrando tabla %s" % item)) qry2.exec_("DROP TABLE %s CASCADE" % item.replace(".mtd", "")) steps = steps + 1 util.setProgress(steps) for item in listOldBks: if self.existsTable(item): util.setLabelText(util.tr("Borrando tabla %s" % item)) qry2.exec_("DROP TABLE %s CASCADE" % item) steps = steps + 1 util.setProgress(steps) util.setLabelText(util.tr("Inicializando cachés")) steps = steps + 1 util.setProgress(steps) qry.exec_("DELETE FROM flmetadata") qry.exec_("DELETE FROM flvar") self.db_.manager().cleanupMetaData() # self.db_.driver().commit() util.destroyProgressDialog() steps = 0 qry3.exec_("SHOW TABLES") util.createProgressDialog(util.tr("Comprobando base de datos"), qry3.size()) while qry3.next(): item = qry3.value(0) # print("Comprobando", item) # qry2.exec_("alter table %s convert to character set utf8 collate utf8_bin" % item) mustAlter = self.mismatchedTable(item, item) if mustAlter: conte = self.db_.managerModules().content("%s.mtd" % item) if conte: msg = util.tr( "La estructura de los metadatos de la tabla '%s' y su " "estructura interna en la base de datos no coinciden. " "Intentando regenerarla." % item ) logger.warning("%s", msg) self.alterTable2(conte, conte, None, True) steps = steps + 1 util.setProgress(steps) self.db_.dbAux().driver().transaction() self.active_create_index = True steps = 0 # sqlCursor = PNSqlCursor(None, True, self.db_.dbAux()) engine = "MyISAM" if self.noInnoDB else "INNODB" convert_engine = False do_ques = True sqlQuery = PNSqlQuery(None, self.db_.dbAux()) sql_query2 = PNSqlQuery(None, self.db_.dbAux()) if sqlQuery.exec_("SHOW TABLES"): util.setTotalSteps(sqlQuery.size()) while sqlQuery.next(): item = sqlQuery.value(0) steps = steps + 1 util.setProgress(steps) util.setLabelText(util.tr("Creando índices para %s" % item)) mtd = self.db_.manager().metadata(item, True) if not mtd: continue fL = mtd.fieldList() if not fL: continue for it in fL: if not it or not it.type() == "pixmap": continue cur = PNSqlCursor(item, True, self.db_.dbAux()) cur.select(it.name() + " not like 'RK@%'") while cur.next(): v = cur.value(it.name()) if v is None: continue v = self.db_.manager().storeLargeValue(mtd, v) if v: buf = cur.primeUpdate() buf.setValue(it.name(), v) cur.update(False) # sqlCursor.setName(item, True) # self.db_.dbAux().driver().commit() sql_query2.exec_( "show table status where Engine='%s' and Name='%s'" % (engine, item) ) if not sql_query2.next(): if do_ques: res = QMessageBox.question( None, util.tr("Mr. Proper"), util.tr( "Existen tablas que no son del tipo %s utilizado por el driver de la conexión actual.\n" "Ahora es posible convertirlas, pero asegurése de tener una COPIA DE SEGURIDAD,\n" "se pueden peder datos en la conversión de forma definitiva.\n\n" "¿ Quiere convertirlas ?" % (engine) ), QMessageBox.Yes, QMessageBox.No, ) if res == QMessageBox.Yes: convert_engine = True do_ques = False if convert_engine: conte = self.db_.managerModules().content("%s.mtd" % item) self.alterTable2(conte, conte, None, True) self.active_create_index = False util.destroyProgressDialog() def alterTable(self, mtd1, mtd2, key: Optional[str], force=False) -> bool: """Alter a table following mtd instructions.""" return self.alterTable2(mtd1, mtd2, key, force) def hasCheckColumn(self, mtd) -> bool: """Retrieve if MTD has a check column.""" field_list = mtd.fieldList() if not field_list: return False for field in field_list: if field.isCheck() or field.name().endswith("_check_column"): return True return False def alterTable2(self, mtd1, mtd2, key: Optional[str], force=False) -> bool: """Alter a table following mtd instructions.""" if not self.db_: raise Exception("must be connected") util = FLUtil() oldMTD = None newMTD = None doc = QDomDocument("doc") docElem = None if not util.domDocumentSetContent(doc, mtd1): print("FLManager::alterTable : " + util.tr("Error al cargar los metadatos.")) else: docElem = doc.documentElement() oldMTD = self.db_.manager().metadata(docElem, True) if oldMTD and oldMTD.isQuery(): return True if oldMTD and self.hasCheckColumn(oldMTD): return False if not util.domDocumentSetContent(doc, mtd2): print("FLManager::alterTable : " + util.tr("Error al cargar los metadatos.")) return False else: docElem = doc.documentElement() newMTD = self.db_.manager().metadata(docElem, True) if not oldMTD: oldMTD = newMTD if not oldMTD.name() == newMTD.name(): print( "FLManager::alterTable : " + util.tr("Los nombres de las tablas nueva y vieja difieren.") ) if oldMTD and not oldMTD == newMTD: del oldMTD if newMTD: del newMTD return False oldPK = oldMTD.primaryKey() newPK = newMTD.primaryKey() if not oldPK == newPK: print( "FLManager::alterTable : " + util.tr("Los nombres de las claves primarias difieren.") ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if not force and self.db_.manager().checkMetaData(oldMTD, newMTD): if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return True if not self.db_.manager().existsTable(oldMTD.name()): print( "FLManager::alterTable : " + util.tr("La tabla %1 antigua de donde importar los registros no existe.").arg( oldMTD.name() ) ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False fieldList = oldMTD.fieldList() # oldField = None if not fieldList: print("FLManager::alterTable : " + util.tr("Los antiguos metadatos no tienen campos.")) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False fieldNamesOld = [] if not force: for it in fieldList: if newMTD.field(it.name()) is not None: fieldNamesOld.append(it.name()) renameOld = "%salteredtable%s" % ( oldMTD.name()[0:5], QDateTime().currentDateTime().toString("ddhhssz"), ) if not self.db_.dbAux(): if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False # self.db_.dbAux().transaction() fieldList = newMTD.fieldList() if not fieldList: qWarning("FLManager::alterTable : " + util.tr("Los nuevos metadatos no tienen campos")) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False q = PNSqlQuery(None, "dbAux") in_sql = "ALTER TABLE %s RENAME TO %s" % (oldMTD.name(), renameOld) logger.warning(in_sql) if not q.exec_(in_sql): qWarning( "FLManager::alterTable : " + util.tr("No se ha podido renombrar la tabla antigua.") ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if not self.db_.manager().createTable(newMTD): self.db_.dbAux().rollbackTransaction() if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False self.db_.dbAux().transaction() if not force and key and len(key) == 40: c = PNSqlCursor("flfiles", True, self.db_.dbAux()) # oldCursor.setModeAccess(oldCursor.Browse) c.setForwardOnly(True) c.setFilter("nombre='%s.mtd'" % renameOld) c.select() if not c.next(): # c.setModeAccess(c.Insert) # c.refreshBuffer() # c.setValueBuffer("nombre","%s.mtd" % renameOld) # c.setValueBuffer("contenido", mtd1) # c.setValueBuffer("sha", key) # c.commitBuffer() in_sql = ( "INSERT INTO flfiles(nombre,contenido,idmodulo,sha) VALUES ('%s.mtd','%s','%s','%s')" % ( renameOld, mtd1, self.db_.managerModules().idModuleOfFile("%s.mtd" % oldMTD.name()), key, ) ) logger.warning(in_sql) q.exec_(in_sql) ok = False if force and fieldNamesOld: # sel = fieldNamesOld.join(",") # in_sql = "INSERT INTO %s(%s) SELECT %s FROM %s" % (newMTD.name(), sel, sel, renameOld) # logger.warning(in_sql) # ok = q.exec_(in_sql) if not ok: self.db_.dbAux().rollbackTransaction() if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return self.alterTable2(mtd1, mtd2, key, True) if not ok: from pymysql.cursors import DictCursor oldCursor = self.conn_.cursor(DictCursor) # print("Lanzando!!", "SELECT * FROM %s WHERE 1 = 1" % (renameOld)) oldCursor.execute("SELECT * FROM %s WHERE 1 = 1" % (renameOld)) result_set = oldCursor.fetchall() totalSteps = len(result_set) # oldCursor = PNSqlCursor(renameOld, True, "dbAux") # oldCursor.setModeAccess(oldCursor.Browse) # oldCursor.setForwardOnly(True) # oldCursor.select() # totalSteps = oldCursor.size() util.createProgressDialog( util.tr("Reestructurando registros para %s...") % newMTD.alias(), totalSteps ) util.setLabelText(util.tr("Tabla modificada")) step = 0 newBuffer = None newField = None listRecords = [] newBufferInfo = self.recordInfo2(newMTD.name()) vector_fields = {} default_values = {} v = None for it2 in fieldList: oldField = oldMTD.field(it2.name()) if ( oldField is None or not result_set or oldField.name() not in result_set[0].keys() ): if oldField is None: oldField = it2 if it2.type() != PNFieldMetaData.Serial: v = it2.defaultValue() step += 1 default_values[str(step)] = v step += 1 vector_fields[str(step)] = it2 step += 1 vector_fields[str(step)] = oldField # step2 = 0 ok = True x = 0 for row in result_set: x += 1 newBuffer = newBufferInfo i = 0 while i < step: v = None if str(i + 1) in default_values.keys(): i += 1 v = default_values[str(i)] i += 1 newField = vector_fields[str(i)] i += 1 oldField = vector_fields[str(i)] else: i += 1 newField = vector_fields[str(i)] i += 1 oldField = vector_fields[str(i)] v = row[newField.name()] if ( (not oldField.allowNull() or not newField.allowNull()) and (v is None) and newField.type() != PNFieldMetaData.Serial ): defVal = newField.defaultValue() if defVal is not None: v = defVal if v is not None and newField.type() == "string" and newField.length() > 0: v = v[: newField.length()] if (not oldField.allowNull() or not newField.allowNull()) and v is None: if oldField.type() == PNFieldMetaData.Serial: v = int(self.nextSerialVal(newMTD.name(), newField.name())) elif oldField.type() in ["int", "uint", "bool", "unlock"]: v = 0 elif oldField.type() == "double": v = 0.0 elif oldField.type() == "time": v = QTime.currentTime() elif oldField.type() == "date": v = QDate.currentDate() else: v = "NULL"[: newField.length()] # new_b = [] for buffer in newBuffer: if buffer[0] == newField.name(): new_buffer = [] new_buffer.append(buffer[0]) new_buffer.append(buffer[1]) new_buffer.append(newField.allowNull()) new_buffer.append(buffer[3]) new_buffer.append(buffer[4]) new_buffer.append(v) new_buffer.append(buffer[6]) listRecords.append(new_buffer) break # newBuffer.setValue(newField.name(), v) if listRecords: if not self.insertMulti(newMTD.name(), listRecords): ok = False listRecords = [] util.setProgress(totalSteps) util.destroyProgressDialog() if ok: self.db_.dbAux().commit() if force: q.exec_("DROP TABLE %s CASCADE" % renameOld) else: self.db_.dbAux().rollbackTransaction() q.exec_("DROP TABLE %s CASCADE" % oldMTD.name()) q.exec_("ALTER TABLE %s RENAME TO %s" % (renameOld, oldMTD.name())) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return True def insertMulti(self, table_name, records: Iterable) -> bool: """Insert several rows at once.""" if not records: return False if not self.db_: raise Exception("must be connected") mtd = self.db_.manager().metadata(table_name) fList = [] vList = [] cursor_ = self.cursor() for f in records: field = mtd.field(f[0]) if field.generated(): fList.append(field.name()) value = f[5] if field.type() in ("string", "stringlist"): value = self.db_.normalizeValue(value) value = self.formatValue(field.type(), value, False) vList.append(value) sql = """INSERT INTO %s(%s) values (%s)""" % ( table_name, ", ".join(fList), ", ".join(map(str, vList)), ) if not fList: return False try: cursor_.execute(sql) except Exception as exc: print(sql, "\n", exc) return False return True def mismatchedTable(self, table1, tmd_or_table2: str, db_=None) -> bool: """Check if table does not match MTD with database schema.""" if db_ is None: db_ = self.db_ if isinstance(tmd_or_table2, str): mtd = db_.manager().metadata(tmd_or_table2, True) if not mtd: return False mismatch = False processed_fields = [] try: recMtd = self.recordInfo(tmd_or_table2) recBd = self.recordInfo2(table1) if recMtd is None: raise Exception("Error obtaining recordInfo for %s" % tmd_or_table2) # fieldBd = None for fieldMtd in recMtd: # fieldBd = None found = False for field in recBd: if field[0] == fieldMtd[0]: processed_fields.append(field[0]) found = True if self.notEqualsFields(field, fieldMtd): mismatch = True recBd.remove(field) break if not found: if fieldMtd[0] not in processed_fields: mismatch = True break if len(recBd) > 0: mismatch = True except Exception: logger.exception("mismatchedTable: Unexpected error") return mismatch else: return self.mismatchedTable(table1, tmd_or_table2.name(), db_) def recordInfo2(self, tablename) -> List[list]: """Obtain current cursor information on columns.""" if not self.isOpen(): raise Exception("MYISAM2: conn not opened") if not self.conn_: raise Exception("must be connected") info = [] cursor = self.conn_.cursor() cursor.execute("SHOW FIELDS FROM %s" % tablename) # print("Campos", tablename) for field in cursor.fetchall(): col_name = field[0] allow_null = True if field[2] == "NO" else False tipo_ = field[1] if field[1].find("(") > -1: tipo_ = field[1][: field[1].find("(")] # len_ len_ = "0" if field[1].find("(") > -1: len_ = field[1][field[1].find("(") + 1 : field[1].find(")")] precision_ = 0 tipo_ = self.decodeSqlType(tipo_) if tipo_ in ["uint", "int", "double"]: len_ = "0" # print("****", tipo_, field) else: if len_.find(",") > -1: precision_ = int(len_[len_.find(",") :]) len_ = len_[: len_.find(",")] len_n = int(len_) if len_n == 255 and tipo_ == "string": len_n = 0 default_value_ = field[4] primary_key_ = True if field[3] == "PRI" else False # print("***", field) # print("Nombre:", col_name) # print("Tipo:", tipo_) # print("Nulo:", allow_null) # print("longitud:", len_) # print("Precision:", precision_) # print("Defecto:", default_value_) info.append( [col_name, tipo_, allow_null, len_n, precision_, default_value_, primary_key_] ) # info.append(desc[0], desc[1], not desc[6], , part_decimal, default_value, is_primary_key) return info def decodeSqlType(self, t: str) -> str: """Translate types.""" ret = t if t in ["char", "varchar", "text"]: ret = "string" elif t == "int": ret = "uint" elif t == "date": ret = "date" elif t == "mediumtext": ret = "stringlist" elif t == "tinyint": ret = "bool" elif t in ["decimal", "double"]: ret = "double" elif t == "longblob": ret = "bytearray" elif t == "time": ret = "time" else: logger.warning("formato desconocido %s", ret) return ret def recordInfo(self, tablename_or_query: str) -> Optional[List[list]]: """Obtain current cursor information on columns.""" if not self.isOpen(): return None if not self.db_: raise Exception("Must be connected") info = [] if isinstance(tablename_or_query, str): tablename = tablename_or_query doc = QDomDocument(tablename) stream = self.db_.managerModules().contentCached("%s.mtd" % tablename) util = FLUtil() if not util.domDocumentSetContent(doc, stream): print( "FLManager : " + QApplication.tr("Error al cargar los metadatos para la tabla") + tablename ) return self.recordInfo2(tablename) # docElem = doc.documentElement() mtd = self.db_.manager().metadata(tablename, True) if not mtd: return self.recordInfo2(tablename) fL = mtd.fieldList() if not fL: del mtd return self.recordInfo2(tablename) for f in mtd.fieldNames(): field = mtd.field(f) info.append( [ field.name(), field.type(), not field.allowNull(), field.length(), field.partDecimal(), field.defaultValue(), field.isPrimaryKey(), ] ) del mtd return info def notEqualsFields(self, field1: List[Any], field2: List[Any]) -> bool: """Check if two field definitions are equal.""" # print("comparando", field1, field1[1], field2, field2[1]) ret = False try: if not field1[2] == field2[2] and not field2[6]: ret = True if field1[1] == "stringlist" and not field2[1] in ("stringlist", "pixmap"): ret = True elif field1[1] == "string" and ( not field2[1] in ("string", "time", "date") or not field1[3] == field2[3] ): if field1[3] == 0 and field2[3] == 255: pass else: ret = True elif field1[1] == "uint" and not field2[1] in ("int", "uint", "serial"): ret = True elif field1[1] == "bool" and not field2[1] in ("bool", "unlock"): ret = True elif field1[1] == "double" and not field2[1] == "double": ret = True except Exception: print(traceback.format_exc()) return ret def normalizeValue(self, text) -> Optional[str]: """Escape values, suitable to prevent sql injection.""" if text is None: return None import pymysql return pymysql.escape_string(text) # text = text.replace("'", "''") # text = text.replace('\\"', '\\\\"') # text = text.replace("\\n", "\\\\n") # text = text.replace("\\r", "\\\\r") # return text def cascadeSupport(self) -> bool: """Check if database supports CASCADE.""" return True def canDetectLocks(self) -> bool: """Check if driver can detect locks.""" return True def desktopFile(self) -> bool: """Return if this database is a file.""" return False def execute_query(self, q: str) -> Any: """Execute a SQL query.""" if not self.isOpen(): logger.warning("MySQLDriver::execute_query. DB is closed") return False cursor = self.cursor() try: q = self.fix_query(q) cursor.execute(q) except Exception: self.setLastError("No se puedo ejecutar la siguiente query %s" % q, q) logger.warning( "MySQLDriver:: No se puedo ejecutar la siguiente query %s\n %s", q, traceback.format_exc(), ) return cursor

33.751143

128

0.482147

""" Module for MYISAM2 driver. """ from PyQt5.Qt import qWarning, QApplication, QRegExp # type: ignore from PyQt5.QtXml import QDomDocument # type: ignore from PyQt5.QtWidgets import QMessageBox, QWidget # type: ignore from pineboolib.core.utils.utils_base import auto_qt_translate_text from pineboolib.application.utils.check_dependencies import check_dependencies from pineboolib.application.database.pnsqlquery import PNSqlQuery from pineboolib.application.database.pnsqlcursor import PNSqlCursor from pineboolib.core.utils.utils_base import text2bool from pineboolib.application.metadata.pnfieldmetadata import PNFieldMetaData from pineboolib.fllegacy import flapplication from pineboolib.fllegacy.flutil import FLUtil from pineboolib.application import project import traceback from pineboolib import logging from PyQt5.QtCore import QTime, QDate, QDateTime, Qt # type: ignore from typing import Any, Iterable, Optional, Union, List, Dict, cast logger = logging.getLogger(__name__) class FLMYSQL_MYISAM2(object): """MYISAM2 Driver class.""" version_: str conn_ = None name_: str alias_: str lastError_: Optional[str] cursorsArray_: Dict[str, Any] # IApiCursor noInnoDB: bool mobile_: bool pure_python_: bool defaultPort_: int cursor_ = None db_ = None engine_ = None session_ = None declarative_base_ = None def __init__(self): """Create empty driver.""" self.version_ = "0.8" self.conn_ = None self.name_ = "FLMYSQL_MyISAM2" self.open_ = False self.alias_ = "MySQL MyISAM (PyMySQL)" self.cursorsArray_ = {} self.noInnoDB = True self._dbname = None self.mobile_ = True self.pure_python_ = True self.defaultPort_ = 3306 self.rowsFetched: Dict[str, int] = {} self.active_create_index = True self.db_ = None self.engine_ = None self.session_ = None self.declarative_base_ = None self.lastError_ = None def version(self) -> str: """Get driver version.""" return self.version_ def driverName(self) -> str: """Get driver name.""" return self.name_ def pure_python(self) -> bool: """Return if this driver is pure python.""" return self.pure_python_ def safe_load(self) -> Any: """Check dependencies for this driver.""" return check_dependencies({"pymysql": "PyMySQL", "sqlalchemy": "sqlAlchemy"}, False) def mobile(self) -> bool: """Check if is suitable for mobile platform.""" return self.mobile_ def isOpen(self) -> bool: """Return if driver has an open connection.""" return self.open_ def DBName(self) -> Any: """Return database name.""" return self._dbname def connect(self, db_name, db_host, db_port, db_userName, db_password) -> Any: """Connect to a database.""" self._dbname = db_name check_dependencies({"pymysql": "PyMySQL", "sqlalchemy": "sqlAlchemy"}) from sqlalchemy import create_engine # type: ignore import pymysql try: self.conn_ = pymysql.connect( host=db_host, user=db_userName, password=db_password, db=db_name, charset="utf8", autocommit=True, ) self.engine_ = create_engine( "mysql+mysqldb://%s:%s@%s:%s/%s" % (db_userName, db_password, db_host, db_port, db_name) ) except pymysql.Error as e: if project._splash: project._splash.hide() if "Unknown database" in str(e): if project._DGI and not project.DGI.localDesktop(): return False ret = QMessageBox.warning( QWidget(), "Pineboo", "La base de datos %s no existe.\n¿Desea crearla?" % db_name, cast(QMessageBox, QMessageBox.Ok | QMessageBox.No), ) if ret == QMessageBox.No: return False else: try: tmpConn = pymysql.connect( host=db_host, user=db_userName, password=db_password, charset="utf8", autocommit=True, ) cursor = tmpConn.cursor() try: cursor.execute("CREATE DATABASE %s" % db_name) except Exception: print("ERROR: FLMYSQL2.connect", traceback.format_exc()) cursor.execute("ROLLBACK") cursor.close() return False cursor.close() return self.connect(db_name, db_host, db_port, db_userName, db_password) except Exception: qWarning(traceback.format_exc()) QMessageBox.information( QWidget(), "Pineboo", "ERROR: No se ha podido crear la Base de Datos %s" % db_name, QMessageBox.Ok, ) print("ERROR: No se ha podido crear la Base de Datos %s" % db_name) return False else: QMessageBox.information( QWidget(), "Pineboo", "Error de conexión\n%s" % str(e), QMessageBox.Ok ) return False if self.conn_: self.open_ = True # self.conn_.autocommit(True) # self.conn_.set_character_set('utf8') return self.conn_ def cursor(self) -> Any: """Get current cursor for db.""" if not self.conn_: raise Exception("Not connected") if not self.cursor_: self.cursor_ = self.conn_.cursor() return self.cursor_ def engine(self) -> Any: """Get current driver engine.""" return self.engine_ def session(self) -> None: """Get sqlAlchemy session.""" if self.session_ is None: from sqlalchemy.orm import sessionmaker # type: ignore # from sqlalchemy import event # from pineboolib.pnobjectsfactory import before_commit, after_commit Session = sessionmaker(bind=self.engine()) self.session_ = Session() # event.listen(Session, 'before_commit', before_commit, self.session_) # event.listen(Session, 'after_commit', after_commit, self.session_) def declarative_base(self) -> Any: """Get sqlAlchemy declarative base.""" if self.declarative_base_ is None: from sqlalchemy.ext.declarative import declarative_base # type: ignore self.declarative_base_ = declarative_base() return self.declarative_base_ def formatValueLike(self, type_, v: Any, upper) -> str: """Format value for database LIKE expression.""" res = "IS NULL" if v: if type_ == "bool": s = str(v[0]).upper() if s == flapplication.aqApp.tr("Sí")[0].upper(): res = "=1" elif flapplication.aqApp.tr("No")[0].upper(): res = "=0" elif type_ == "date": from pineboolib.application.utils.date_conversion import date_dma_to_amd date_amd = date_dma_to_amd(str(v)) if date_amd: res = " LIKE '%" + date_amd + "'" else: logger.warning("formatValueLike: failed to convert %s to ISO date format", v) elif type_ == "time": t = v.toTime() res = " LIKE '" + t.toString(Qt.ISODate) + "%'" else: res = str(v) if upper: res = res.upper() res = " LIKE '" + res + "%'" return res def formatValue(self, type_, v: Any, upper) -> Union[str, bool, None]: """Format value for database WHERE comparison.""" # util = FLUtil() s: Union[str, bool, None] = None # if v == None: # v = "" # TODO: psycopg2.mogrify ??? if v is None: return "NULL" if type_ == "bool" or type_ == "unlock": s = text2bool(v) elif type_ == "date": # val = util.dateDMAtoAMD(v) val = v if val is None: s = "Null" else: s = "'%s'" % val elif type_ == "time": s = "'%s'" % v elif type_ in ("uint", "int", "double", "serial"): if s == "Null": s = "0" else: s = v elif type_ in ("string", "stringlist"): if v == "": s = "Null" else: if type_ == "string": v = auto_qt_translate_text(v) if upper and type_ == "string": v = v.upper() s = "'%s'" % v elif type_ == "pixmap": if v.find("'") > -1: v = self.normalizeValue(v) s = "'%s'" % v else: s = v # print ("PNSqlDriver(%s).formatValue(%s, %s) = %s" % (self.name_, type_, v, s)) return s def canOverPartition(self) -> bool: return True def tables(self, type_name=None) -> list: """Introspect tables in database.""" tl: List[str] = [] if not self.isOpen(): return tl q_tables = PNSqlQuery() q_tables.exec_("show tables") while q_tables.next(): tl.append(q_tables.value(0)) return tl def nextSerialVal(self, table, field) -> Any: """Get next serial value for given table and field.""" if not self.isOpen(): logger.warning("%s::beginTransaction: Database not open", self.name_) return None # if not self.transaction(): # self.setLastError("No se puede iniciar la transacción", "BEGIN WORK") # return None max = 0 cur_max = 0 updateQry = False ret = None q = PNSqlQuery() q.setSelect("max(%s)" % field) q.setFrom(table) q.setWhere("1 = 1") if not q.exec_(): logger.warning("not exec sequence") return None if q.first() and q.value(0) is not None: max = q.value(0) if not self.conn_: raise Exception("must be connected") cursor = self.conn_.cursor() strQry: Optional[str] = "SELECT seq FROM flseqs WHERE tabla = '%s' AND campo ='%s'" % ( table, field, ) try: cur_max = 0 cursor.execute(strQry) line = cursor.fetchone() if line: cur_max = line[0] except Exception: logger.warning( "%s:: La consulta a la base de datos ha fallado", self.name_, traceback.format_exc() ) self.rollbackTransaction() return if cur_max > 0: updateQry = True ret = cur_max else: ret = max ret += 1 strQry = None if updateQry: if ret > cur_max: strQry = "UPDATE flseqs SET seq=%s WHERE tabla = '%s' AND campo = '%s'" % ( ret, table, field, ) else: strQry = "INSERT INTO flseqs (tabla,campo,seq) VALUES('%s','%s',%s)" % ( table, field, ret, ) if strQry is not None: try: cursor.execute(strQry) except Exception: logger.warning( "%s:: La consulta a la base de datos ha fallado\n %s", self.name_, traceback.format_exc(), ) self.rollbackTransaction() return # if not self.commitTransaction(): # qWarning("%s:: No se puede aceptar la transacción" % self.name_) # return None return ret def queryUpdate(self, name, update, filter) -> str: """Return a templates UPDATE sql.""" sql = "UPDATE %s SET %s WHERE %s" % (name, update, filter) return sql def savePoint(self, n) -> bool: """Perform a transaction savepoint.""" if n == 0: return True if not self.isOpen(): logger.warning("%s::savePoint: Database not open", self.name_) return False cursor = self.cursor() try: cursor.execute("SAVEPOINT sv_%s" % n) except Exception: self.setLastError("No se pudo crear punto de salvaguarda", "SAVEPOINT sv_%s" % n) logger.warning( "MySQLDriver:: No se pudo crear punto de salvaguarda SAVEPOINT sv_%s \n %s ", n, traceback.format_exc(), ) return False return True def canSavePoint(self) -> bool: """Retrieve if this driver can perform savepoints.""" return False def canTransaction(self) -> bool: """Retrieve if this driver can perform transactions.""" return False def rollbackSavePoint(self, n) -> bool: """Rollback transaction to last savepoint.""" if n == 0: return True if not self.isOpen(): logger.warning("%s::rollbackSavePoint: Database not open", self.name_) return False cursor = self.cursor() try: cursor.execute("ROLLBACK TO SAVEPOINT sv_%s" % n) except Exception: self.setLastError( "No se pudo rollback a punto de salvaguarda", "ROLLBACK TO SAVEPOINTt sv_%s" % n ) logger.warning( "%s:: No se pudo rollback a punto de salvaguarda ROLLBACK TO SAVEPOINT sv_%s\n %s", self.name_, n, traceback.format_exc(), ) return False return True def setLastError(self, text, command) -> None: """Set last error from database.""" self.lastError_ = "%s (%s)" % (text, command) def lastError(self) -> Optional[str]: """Get last error happened on database.""" return self.lastError_ def commitTransaction(self) -> bool: """Commit database transaction.""" if not self.isOpen(): logger.warning("%s::commitTransaction: Database not open", self.name_) cursor = self.cursor() try: cursor.execute("COMMIT") except Exception: self.setLastError("No se pudo aceptar la transacción", "COMMIT") logger.warning( "%s:: No se pudo aceptar la transacción COMMIT\n %s", self.name_, traceback.format_exc(), ) return False return True def rollbackTransaction(self) -> bool: """Rollback database transaction.""" if not self.isOpen(): logger.warning("%s::rollbackTransaction: Database not open", self.name_) cursor = self.cursor() if self.canSavePoint(): try: cursor.execute("ROLLBACK") except Exception: self.setLastError("No se pudo deshacer la transacción", "ROLLBACK") logger.warning( "%s:: No se pudo deshacer la transacción ROLLBACK\n %s", self.name_, traceback.format_exc(), ) return False else: qWarning( "%s:: No se pudo deshacer la transacción ROLLBACK\n %s" % (self.name_, traceback.format_exc()) ) return True def transaction(self) -> bool: """Start new database transaction.""" if not self.isOpen(): logger.warning("%s::transaction: Database not open", self.name_) cursor = self.cursor() try: cursor.execute("START TRANSACTION") except Exception: self.setLastError("No se pudo crear la transacción", "BEGIN WORK") logger.warning( "%s:: No se pudo crear la transacción BEGIN\n %s", self.name_, traceback.format_exc(), ) return False return True def releaseSavePoint(self, n) -> bool: """Remove named savepoint from database.""" if n == 0: return True if not self.isOpen(): qWarning("%s::releaseSavePoint: Database not open" % self.name_) return False cursor = self.cursor() try: cursor.execute("RELEASE SAVEPOINT sv_%s" % n) except Exception: self.setLastError( "No se pudo release a punto de salvaguarda", "RELEASE SAVEPOINT sv_%s" % n ) qWarning( "MySQLDriver:: No se pudo release a punto de salvaguarda RELEASE SAVEPOINT sv_%s\n %s" % (n, traceback.format_exc()) ) return False return True def setType(self, type_, leng=None) -> str: """Template a SQL data type.""" if leng: return "::%s(%s)" % (type_, leng) else: return "::%s" % type_ def refreshQuery(self, curname, fields, table, where, cursor, conn) -> None: """Perform a query.""" if curname not in self.cursorsArray_.keys(): self.cursorsArray_[curname] = cursor sql = "SELECT %s FROM %s WHERE %s " % (fields, table, where) sql = self.fix_query(sql) try: self.cursorsArray_[curname].execute(sql) except Exception: print("*", sql) qWarning("CursorTableModel.Refresh\n %s" % traceback.format_exc()) def fix_query(self, val: str) -> str: """Fix values on SQL.""" ret_ = val.replace("'true'", "1") ret_ = ret_.replace("'false'", "0") ret_ = ret_.replace("'0'", "0") ret_ = ret_.replace("'1'", "1") # ret_ = ret_.replace(";", "") return ret_ def refreshFetch(self, number, curname, table, cursor, fields, where_filter) -> None: pass # try: # self.cursorsArray_[curname].fetchmany(number) # except Exception: # qWarning("%s.refreshFetch\n %s" %(self.name_, traceback.format_exc())) def useThreads(self) -> bool: """Return if this driver supports threads.""" return False def useTimer(self) -> bool: """Return if this driver supports timer.""" return True def fetchAll(self, cursor, tablename, where_filter, fields, curname) -> List[Any]: """Fetch all pending rows on cursor.""" if curname not in self.rowsFetched.keys(): self.rowsFetched[curname] = 0 rowsF = [] try: rows = list(self.cursorsArray_[curname]) if self.rowsFetched[curname] < len(rows): i = 0 for row in rows: i += 1 if i > self.rowsFetched[curname]: rowsF.append(row) self.rowsFetched[curname] = i except Exception: logger.error("%s:: fetchAll:%s", self.name_, traceback.format_exc()) return rowsF def existsTable(self, name) -> bool: """Return if table exists.""" if not self.isOpen(): return False t = PNSqlQuery() t.setForwardOnly(True) ok = t.exec_("SHOW TABLES LIKE '%s'" % name) if ok: ok = t.next() return ok def sqlCreateTable(self, tmd) -> Optional[str]: """Create a table from given MTD.""" # util = FLUtil() if not tmd: return None primaryKey = None sql = "CREATE TABLE %s (" % tmd.name() # seq = None fieldList = tmd.fieldList() unlocks = 0 for field in fieldList: if field.type() == "unlock": unlocks += 1 if unlocks > 1: qWarning(u"%s : No se ha podido crear la tabla %s" % (self.name_, tmd.name())) qWarning(u"%s : Hay mas de un campo tipo unlock. Solo puede haber uno." % self.name_) return None i = 1 for field in fieldList: sql = sql + field.name() if field.type() == "int": sql += " INT" elif field.type() in ["uint", "serial"]: sql += " INT UNSIGNED" elif field.type() in ("bool", "unlock"): sql += " BOOL" elif field.type() == "double": sql += " DECIMAL(%s,%s)" % ( field.partInteger() + field.partDecimal() + 5, field.partDecimal() + 5, ) elif field.type() == "time": sql += " TIME" elif field.type() == "date": sql += " DATE" elif field.type() in ["pixmap", "stringlist"]: sql += " MEDIUMTEXT" elif field.type() == "string": if field.length() > 0: if field.length() > 255: sql += " VARCHAR" else: sql += " CHAR" sql += "(%s)" % field.length() else: sql += " CHAR(255)" elif field.type() == "bytearray": sql = sql + " LONGBLOB" if field.isPrimaryKey(): if primaryKey is None: sql += " PRIMARY KEY" primaryKey = field.name() else: qWarning( QApplication.tr("FLManager : Tabla-> ") + tmd.name() + QApplication.tr( " . Se ha intentado poner una segunda clave primaria para el campo " ) + field.name() + QApplication.tr(" , pero el campo ") + primaryKey + QApplication.tr( " ya es clave primaria. Sólo puede existir una clave primaria en FLTableMetaData," " use FLCompoundKey para crear claves compuestas." ) ) return None else: if field.isUnique(): sql += " UNIQUE" if not field.allowNull(): sql += " NOT NULL" else: sql += " NULL" if not i == len(fieldList): sql += "," i = i + 1 engine = ") ENGINE=INNODB" if not self.noInnoDB else ") ENGINE=MyISAM" sql += engine sql += " DEFAULT CHARACTER SET = utf8 COLLATE = utf8_bin" qWarning("NOTICE: CREATE TABLE (%s%s)" % (tmd.name(), engine)) return sql def Mr_Proper(self) -> None: """Cleanup database like mr.proper.""" util = FLUtil() if not self.db_: raise Exception("must be connected") self.db_.dbAux().transaction() qry = PNSqlQuery(None, "dbAux") qry2 = PNSqlQuery(None, "dbAux") qry3 = PNSqlQuery(None, "dbAux") # qry4 = PNSqlQuery(None, "dbAux") # qry5 = PNSqlQuery(None, "dbAux") steps = 0 self.active_create_index = False rx = QRegExp("^.*\\d{6,9}$") if rx in self.tables(): listOldBks = self.tables()[rx] else: listOldBks = [] qry.exec_( "select nombre from flfiles where nombre regexp" "'.*[[:digit:]][[:digit:]][[:digit:]][[:digit:]]-[[:digit:]][[:digit:]].*:[[:digit:]][[:digit:]]$' or nombre regexp" "'.*alteredtable[[:digit:]][[:digit:]][[:digit:]][[:digit:]].*' or (bloqueo=0 and nombre like '%.mtd')" ) util.createProgressDialog(util.tr("Borrando backups"), len(listOldBks) + qry.size() + 2) while qry.next(): item = qry.value(0) util.setLabelText(util.tr("Borrando registro %s") % item) qry2.exec_("DELETE FROM flfiles WHERE nombre ='%s'" % item) if item.find("alteredtable") > -1: if self.existsTable(item.replace(".mtd", "")): util.setLabelText(util.tr("Borrando tabla %s" % item)) qry2.exec_("DROP TABLE %s CASCADE" % item.replace(".mtd", "")) steps = steps + 1 util.setProgress(steps) for item in listOldBks: if self.existsTable(item): util.setLabelText(util.tr("Borrando tabla %s" % item)) qry2.exec_("DROP TABLE %s CASCADE" % item) steps = steps + 1 util.setProgress(steps) util.setLabelText(util.tr("Inicializando cachés")) steps = steps + 1 util.setProgress(steps) qry.exec_("DELETE FROM flmetadata") qry.exec_("DELETE FROM flvar") self.db_.manager().cleanupMetaData() # self.db_.driver().commit() util.destroyProgressDialog() steps = 0 qry3.exec_("SHOW TABLES") util.createProgressDialog(util.tr("Comprobando base de datos"), qry3.size()) while qry3.next(): item = qry3.value(0) # print("Comprobando", item) # qry2.exec_("alter table %s convert to character set utf8 collate utf8_bin" % item) mustAlter = self.mismatchedTable(item, item) if mustAlter: conte = self.db_.managerModules().content("%s.mtd" % item) if conte: msg = util.tr( "La estructura de los metadatos de la tabla '%s' y su " "estructura interna en la base de datos no coinciden. " "Intentando regenerarla." % item ) logger.warning("%s", msg) self.alterTable2(conte, conte, None, True) steps = steps + 1 util.setProgress(steps) self.db_.dbAux().driver().transaction() self.active_create_index = True steps = 0 # sqlCursor = PNSqlCursor(None, True, self.db_.dbAux()) engine = "MyISAM" if self.noInnoDB else "INNODB" convert_engine = False do_ques = True sqlQuery = PNSqlQuery(None, self.db_.dbAux()) sql_query2 = PNSqlQuery(None, self.db_.dbAux()) if sqlQuery.exec_("SHOW TABLES"): util.setTotalSteps(sqlQuery.size()) while sqlQuery.next(): item = sqlQuery.value(0) steps = steps + 1 util.setProgress(steps) util.setLabelText(util.tr("Creando índices para %s" % item)) mtd = self.db_.manager().metadata(item, True) if not mtd: continue fL = mtd.fieldList() if not fL: continue for it in fL: if not it or not it.type() == "pixmap": continue cur = PNSqlCursor(item, True, self.db_.dbAux()) cur.select(it.name() + " not like 'RK@%'") while cur.next(): v = cur.value(it.name()) if v is None: continue v = self.db_.manager().storeLargeValue(mtd, v) if v: buf = cur.primeUpdate() buf.setValue(it.name(), v) cur.update(False) # sqlCursor.setName(item, True) # self.db_.dbAux().driver().commit() sql_query2.exec_( "show table status where Engine='%s' and Name='%s'" % (engine, item) ) if not sql_query2.next(): if do_ques: res = QMessageBox.question( None, util.tr("Mr. Proper"), util.tr( "Existen tablas que no son del tipo %s utilizado por el driver de la conexión actual.\n" "Ahora es posible convertirlas, pero asegurése de tener una COPIA DE SEGURIDAD,\n" "se pueden peder datos en la conversión de forma definitiva.\n\n" "¿ Quiere convertirlas ?" % (engine) ), QMessageBox.Yes, QMessageBox.No, ) if res == QMessageBox.Yes: convert_engine = True do_ques = False if convert_engine: conte = self.db_.managerModules().content("%s.mtd" % item) self.alterTable2(conte, conte, None, True) self.active_create_index = False util.destroyProgressDialog() def alterTable(self, mtd1, mtd2, key: Optional[str], force=False) -> bool: """Alter a table following mtd instructions.""" return self.alterTable2(mtd1, mtd2, key, force) def hasCheckColumn(self, mtd) -> bool: """Retrieve if MTD has a check column.""" field_list = mtd.fieldList() if not field_list: return False for field in field_list: if field.isCheck() or field.name().endswith("_check_column"): return True return False def alterTable2(self, mtd1, mtd2, key: Optional[str], force=False) -> bool: """Alter a table following mtd instructions.""" if not self.db_: raise Exception("must be connected") util = FLUtil() oldMTD = None newMTD = None doc = QDomDocument("doc") docElem = None if not util.domDocumentSetContent(doc, mtd1): print("FLManager::alterTable : " + util.tr("Error al cargar los metadatos.")) else: docElem = doc.documentElement() oldMTD = self.db_.manager().metadata(docElem, True) if oldMTD and oldMTD.isQuery(): return True if oldMTD and self.hasCheckColumn(oldMTD): return False if not util.domDocumentSetContent(doc, mtd2): print("FLManager::alterTable : " + util.tr("Error al cargar los metadatos.")) return False else: docElem = doc.documentElement() newMTD = self.db_.manager().metadata(docElem, True) if not oldMTD: oldMTD = newMTD if not oldMTD.name() == newMTD.name(): print( "FLManager::alterTable : " + util.tr("Los nombres de las tablas nueva y vieja difieren.") ) if oldMTD and not oldMTD == newMTD: del oldMTD if newMTD: del newMTD return False oldPK = oldMTD.primaryKey() newPK = newMTD.primaryKey() if not oldPK == newPK: print( "FLManager::alterTable : " + util.tr("Los nombres de las claves primarias difieren.") ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if not force and self.db_.manager().checkMetaData(oldMTD, newMTD): if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return True if not self.db_.manager().existsTable(oldMTD.name()): print( "FLManager::alterTable : " + util.tr("La tabla %1 antigua de donde importar los registros no existe.").arg( oldMTD.name() ) ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False fieldList = oldMTD.fieldList() # oldField = None if not fieldList: print("FLManager::alterTable : " + util.tr("Los antiguos metadatos no tienen campos.")) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False fieldNamesOld = [] if not force: for it in fieldList: if newMTD.field(it.name()) is not None: fieldNamesOld.append(it.name()) renameOld = "%salteredtable%s" % ( oldMTD.name()[0:5], QDateTime().currentDateTime().toString("ddhhssz"), ) if not self.db_.dbAux(): if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False # self.db_.dbAux().transaction() fieldList = newMTD.fieldList() if not fieldList: qWarning("FLManager::alterTable : " + util.tr("Los nuevos metadatos no tienen campos")) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False q = PNSqlQuery(None, "dbAux") in_sql = "ALTER TABLE %s RENAME TO %s" % (oldMTD.name(), renameOld) logger.warning(in_sql) if not q.exec_(in_sql): qWarning( "FLManager::alterTable : " + util.tr("No se ha podido renombrar la tabla antigua.") ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if not self.db_.manager().createTable(newMTD): self.db_.dbAux().rollbackTransaction() if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False self.db_.dbAux().transaction() if not force and key and len(key) == 40: c = PNSqlCursor("flfiles", True, self.db_.dbAux()) # oldCursor.setModeAccess(oldCursor.Browse) c.setForwardOnly(True) c.setFilter("nombre='%s.mtd'" % renameOld) c.select() if not c.next(): # c.setModeAccess(c.Insert) # c.refreshBuffer() # c.setValueBuffer("nombre","%s.mtd" % renameOld) # c.setValueBuffer("contenido", mtd1) # c.setValueBuffer("sha", key) # c.commitBuffer() in_sql = ( "INSERT INTO flfiles(nombre,contenido,idmodulo,sha) VALUES ('%s.mtd','%s','%s','%s')" % ( renameOld, mtd1, self.db_.managerModules().idModuleOfFile("%s.mtd" % oldMTD.name()), key, ) ) logger.warning(in_sql) q.exec_(in_sql) ok = False if force and fieldNamesOld: # sel = fieldNamesOld.join(",") # in_sql = "INSERT INTO %s(%s) SELECT %s FROM %s" % (newMTD.name(), sel, sel, renameOld) # logger.warning(in_sql) # ok = q.exec_(in_sql) if not ok: self.db_.dbAux().rollbackTransaction() if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return self.alterTable2(mtd1, mtd2, key, True) if not ok: from pymysql.cursors import DictCursor oldCursor = self.conn_.cursor(DictCursor) # print("Lanzando!!", "SELECT * FROM %s WHERE 1 = 1" % (renameOld)) oldCursor.execute("SELECT * FROM %s WHERE 1 = 1" % (renameOld)) result_set = oldCursor.fetchall() totalSteps = len(result_set) # oldCursor = PNSqlCursor(renameOld, True, "dbAux") # oldCursor.setModeAccess(oldCursor.Browse) # oldCursor.setForwardOnly(True) # oldCursor.select() # totalSteps = oldCursor.size() util.createProgressDialog( util.tr("Reestructurando registros para %s...") % newMTD.alias(), totalSteps ) util.setLabelText(util.tr("Tabla modificada")) step = 0 newBuffer = None newField = None listRecords = [] newBufferInfo = self.recordInfo2(newMTD.name()) vector_fields = {} default_values = {} v = None for it2 in fieldList: oldField = oldMTD.field(it2.name()) if ( oldField is None or not result_set or oldField.name() not in result_set[0].keys() ): if oldField is None: oldField = it2 if it2.type() != PNFieldMetaData.Serial: v = it2.defaultValue() step += 1 default_values[str(step)] = v step += 1 vector_fields[str(step)] = it2 step += 1 vector_fields[str(step)] = oldField # step2 = 0 ok = True x = 0 for row in result_set: x += 1 newBuffer = newBufferInfo i = 0 while i < step: v = None if str(i + 1) in default_values.keys(): i += 1 v = default_values[str(i)] i += 1 newField = vector_fields[str(i)] i += 1 oldField = vector_fields[str(i)] else: i += 1 newField = vector_fields[str(i)] i += 1 oldField = vector_fields[str(i)] v = row[newField.name()] if ( (not oldField.allowNull() or not newField.allowNull()) and (v is None) and newField.type() != PNFieldMetaData.Serial ): defVal = newField.defaultValue() if defVal is not None: v = defVal if v is not None and newField.type() == "string" and newField.length() > 0: v = v[: newField.length()] if (not oldField.allowNull() or not newField.allowNull()) and v is None: if oldField.type() == PNFieldMetaData.Serial: v = int(self.nextSerialVal(newMTD.name(), newField.name())) elif oldField.type() in ["int", "uint", "bool", "unlock"]: v = 0 elif oldField.type() == "double": v = 0.0 elif oldField.type() == "time": v = QTime.currentTime() elif oldField.type() == "date": v = QDate.currentDate() else: v = "NULL"[: newField.length()] # new_b = [] for buffer in newBuffer: if buffer[0] == newField.name(): new_buffer = [] new_buffer.append(buffer[0]) new_buffer.append(buffer[1]) new_buffer.append(newField.allowNull()) new_buffer.append(buffer[3]) new_buffer.append(buffer[4]) new_buffer.append(v) new_buffer.append(buffer[6]) listRecords.append(new_buffer) break # newBuffer.setValue(newField.name(), v) if listRecords: if not self.insertMulti(newMTD.name(), listRecords): ok = False listRecords = [] util.setProgress(totalSteps) util.destroyProgressDialog() if ok: self.db_.dbAux().commit() if force: q.exec_("DROP TABLE %s CASCADE" % renameOld) else: self.db_.dbAux().rollbackTransaction() q.exec_("DROP TABLE %s CASCADE" % oldMTD.name()) q.exec_("ALTER TABLE %s RENAME TO %s" % (renameOld, oldMTD.name())) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return True def insertMulti(self, table_name, records: Iterable) -> bool: """Insert several rows at once.""" if not records: return False if not self.db_: raise Exception("must be connected") mtd = self.db_.manager().metadata(table_name) fList = [] vList = [] cursor_ = self.cursor() for f in records: field = mtd.field(f[0]) if field.generated(): fList.append(field.name()) value = f[5] if field.type() in ("string", "stringlist"): value = self.db_.normalizeValue(value) value = self.formatValue(field.type(), value, False) vList.append(value) sql = """INSERT INTO %s(%s) values (%s)""" % ( table_name, ", ".join(fList), ", ".join(map(str, vList)), ) if not fList: return False try: cursor_.execute(sql) except Exception as exc: print(sql, "\n", exc) return False return True def mismatchedTable(self, table1, tmd_or_table2: str, db_=None) -> bool: """Check if table does not match MTD with database schema.""" if db_ is None: db_ = self.db_ if isinstance(tmd_or_table2, str): mtd = db_.manager().metadata(tmd_or_table2, True) if not mtd: return False mismatch = False processed_fields = [] try: recMtd = self.recordInfo(tmd_or_table2) recBd = self.recordInfo2(table1) if recMtd is None: raise Exception("Error obtaining recordInfo for %s" % tmd_or_table2) # fieldBd = None for fieldMtd in recMtd: # fieldBd = None found = False for field in recBd: if field[0] == fieldMtd[0]: processed_fields.append(field[0]) found = True if self.notEqualsFields(field, fieldMtd): mismatch = True recBd.remove(field) break if not found: if fieldMtd[0] not in processed_fields: mismatch = True break if len(recBd) > 0: mismatch = True except Exception: logger.exception("mismatchedTable: Unexpected error") return mismatch else: return self.mismatchedTable(table1, tmd_or_table2.name(), db_) def recordInfo2(self, tablename) -> List[list]: """Obtain current cursor information on columns.""" if not self.isOpen(): raise Exception("MYISAM2: conn not opened") if not self.conn_: raise Exception("must be connected") info = [] cursor = self.conn_.cursor() cursor.execute("SHOW FIELDS FROM %s" % tablename) # print("Campos", tablename) for field in cursor.fetchall(): col_name = field[0] allow_null = True if field[2] == "NO" else False tipo_ = field[1] if field[1].find("(") > -1: tipo_ = field[1][: field[1].find("(")] # len_ len_ = "0" if field[1].find("(") > -1: len_ = field[1][field[1].find("(") + 1 : field[1].find(")")] precision_ = 0 tipo_ = self.decodeSqlType(tipo_) if tipo_ in ["uint", "int", "double"]: len_ = "0" # print("****", tipo_, field) else: if len_.find(",") > -1: precision_ = int(len_[len_.find(",") :]) len_ = len_[: len_.find(",")] len_n = int(len_) if len_n == 255 and tipo_ == "string": len_n = 0 default_value_ = field[4] primary_key_ = True if field[3] == "PRI" else False # print("***", field) # print("Nombre:", col_name) # print("Tipo:", tipo_) # print("Nulo:", allow_null) # print("longitud:", len_) # print("Precision:", precision_) # print("Defecto:", default_value_) info.append( [col_name, tipo_, allow_null, len_n, precision_, default_value_, primary_key_] ) # info.append(desc[0], desc[1], not desc[6], , part_decimal, default_value, is_primary_key) return info def decodeSqlType(self, t: str) -> str: """Translate types.""" ret = t if t in ["char", "varchar", "text"]: ret = "string" elif t == "int": ret = "uint" elif t == "date": ret = "date" elif t == "mediumtext": ret = "stringlist" elif t == "tinyint": ret = "bool" elif t in ["decimal", "double"]: ret = "double" elif t == "longblob": ret = "bytearray" elif t == "time": ret = "time" else: logger.warning("formato desconocido %s", ret) return ret def recordInfo(self, tablename_or_query: str) -> Optional[List[list]]: """Obtain current cursor information on columns.""" if not self.isOpen(): return None if not self.db_: raise Exception("Must be connected") info = [] if isinstance(tablename_or_query, str): tablename = tablename_or_query doc = QDomDocument(tablename) stream = self.db_.managerModules().contentCached("%s.mtd" % tablename) util = FLUtil() if not util.domDocumentSetContent(doc, stream): print( "FLManager : " + QApplication.tr("Error al cargar los metadatos para la tabla") + tablename ) return self.recordInfo2(tablename) # docElem = doc.documentElement() mtd = self.db_.manager().metadata(tablename, True) if not mtd: return self.recordInfo2(tablename) fL = mtd.fieldList() if not fL: del mtd return self.recordInfo2(tablename) for f in mtd.fieldNames(): field = mtd.field(f) info.append( [ field.name(), field.type(), not field.allowNull(), field.length(), field.partDecimal(), field.defaultValue(), field.isPrimaryKey(), ] ) del mtd return info def notEqualsFields(self, field1: List[Any], field2: List[Any]) -> bool: """Check if two field definitions are equal.""" # print("comparando", field1, field1[1], field2, field2[1]) ret = False try: if not field1[2] == field2[2] and not field2[6]: ret = True if field1[1] == "stringlist" and not field2[1] in ("stringlist", "pixmap"): ret = True elif field1[1] == "string" and ( not field2[1] in ("string", "time", "date") or not field1[3] == field2[3] ): if field1[3] == 0 and field2[3] == 255: pass else: ret = True elif field1[1] == "uint" and not field2[1] in ("int", "uint", "serial"): ret = True elif field1[1] == "bool" and not field2[1] in ("bool", "unlock"): ret = True elif field1[1] == "double" and not field2[1] == "double": ret = True except Exception: print(traceback.format_exc()) return ret def normalizeValue(self, text) -> Optional[str]: """Escape values, suitable to prevent sql injection.""" if text is None: return None import pymysql return pymysql.escape_string(text) # text = text.replace("'", "''") # text = text.replace('\\"', '\\\\"') # text = text.replace("\\n", "\\\\n") # text = text.replace("\\r", "\\\\r") # return text def cascadeSupport(self) -> bool: """Check if database supports CASCADE.""" return True def canDetectLocks(self) -> bool: """Check if driver can detect locks.""" return True def desktopFile(self) -> bool: """Return if this database is a file.""" return False def execute_query(self, q: str) -> Any: """Execute a SQL query.""" if not self.isOpen(): logger.warning("MySQLDriver::execute_query. DB is closed") return False cursor = self.cursor() try: q = self.fix_query(q) cursor.execute(q) except Exception: self.setLastError("No se puedo ejecutar la siguiente query %s" % q, q) logger.warning( "MySQLDriver:: No se puedo ejecutar la siguiente query %s\n %s", q, traceback.format_exc(), ) return cursor

297

0

54

93d72bc6802337a6844119c8802b8bf664d50346

2,501

py

Python

doit/support/cmd/errors.py

i386x/doit

61892904940b7ecf29af8ea815b731e242a945f7

[ "MIT" ]

null

doit/support/cmd/errors.py

i386x/doit

61892904940b7ecf29af8ea815b731e242a945f7

[ "MIT" ]

null

doit/support/cmd/errors.py

i386x/doit

61892904940b7ecf29af8ea815b731e242a945f7

[ "MIT" ]

null

# -*- coding: utf-8 -*- #! \file ./doit/support/cmd/errors.py #! \author Jiří Kučera, <sanczes@gmail.com> #! \stamp 2016-02-15 13:19:12 (UTC+01:00, DST+00:00) #! \project DoIt!: Tools and Libraries for Building DSLs #! \license MIT #! \version 0.0.0 #! \fdesc @pyfile.docstr # """\ Command processor's errors.\ """ __license__ = """\ Copyright (c) 2014 - 2017 Jiří Kučera. 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 doit.support.errors import DoItError ERROR_COMMAND_PROCESSOR = DoItError.alloc_codes(1) ERROR_COMMAND = DoItError.alloc_codes(1) class CommandProcessorError(DoItError): """ """ __slots__ = [ 'traceback' ] def __init__(self, tb, emsg): """ """ DoItError.__init__(self, ERROR_COMMAND_PROCESSOR, emsg) self.traceback = tb #-def def __str__(self): """ """ if self.traceback is not None: return "%s %s" % (self.traceback, DoItError.__str__(self)) return DoItError.__str__(self) #-def #-class class CommandError(DoItError): """ """ __slots__ = [ 'ecls', 'emsg', 'tb' ] def __init__(self, ecls, emsg, tb): """ """ DoItError.__init__(self, ERROR_COMMAND, "%s: %s" % (ecls, emsg)) self.ecls = ecls self.emsg = emsg self.tb = tb #-def def __repr__(self): """ """ return "%s(\"%s\")" % (self.ecls, self.emsg) #-def #-class

29.081395

79

0.652139

# -*- coding: utf-8 -*- #! \file ./doit/support/cmd/errors.py #! \author Jiří Kučera, <sanczes@gmail.com> #! \stamp 2016-02-15 13:19:12 (UTC+01:00, DST+00:00) #! \project DoIt!: Tools and Libraries for Building DSLs #! \license MIT #! \version 0.0.0 #! \fdesc @pyfile.docstr # """\ Command processor's errors.\ """ __license__ = """\ Copyright (c) 2014 - 2017 Jiří Kučera. 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 doit.support.errors import DoItError ERROR_COMMAND_PROCESSOR = DoItError.alloc_codes(1) ERROR_COMMAND = DoItError.alloc_codes(1) class CommandProcessorError(DoItError): """ """ __slots__ = [ 'traceback' ] def __init__(self, tb, emsg): """ """ DoItError.__init__(self, ERROR_COMMAND_PROCESSOR, emsg) self.traceback = tb #-def def __str__(self): """ """ if self.traceback is not None: return "%s %s" % (self.traceback, DoItError.__str__(self)) return DoItError.__str__(self) #-def #-class class CommandError(DoItError): """ """ __slots__ = [ 'ecls', 'emsg', 'tb' ] def __init__(self, ecls, emsg, tb): """ """ DoItError.__init__(self, ERROR_COMMAND, "%s: %s" % (ecls, emsg)) self.ecls = ecls self.emsg = emsg self.tb = tb #-def def __repr__(self): """ """ return "%s(\"%s\")" % (self.ecls, self.emsg) #-def #-class

0

bc4091829f8438988183491e40582e30250e0759

4,364

py

Python

nototools/notoconfig.py

dedbbs1/nototools

428f149d7c235ac45fb9255414c77a3529e0c8bf

[ "Apache-2.0" ]

156

2015-06-11T00:03:49.000Z

2019-03-12T10:05:14.000Z

nototools/notoconfig.py

dedbbs1/nototools

428f149d7c235ac45fb9255414c77a3529e0c8bf

[ "Apache-2.0" ]

323

2015-06-09T21:26:40.000Z

2019-04-09T11:09:52.000Z

nototools/notoconfig.py

twardoch/nototools

546beddb96e8eb4d93fa0f4c60793bee56e346ac

[ "Apache-2.0" ]

63

2015-06-09T19:21:58.000Z

2019-03-27T21:52:30.000Z

#!/usr/bin/env python # Copyright 2015 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. """Read config file for noto tools. One could also just define some environment variables, but using Python for this lets you keep your environment and shell prefs clean. This expects a file named '.notoconfig' in the users home directory. It should contain lines consisting of a name, '=' and a path. The expected names are 'noto_tools', 'noto_fonts', 'noto_cjk', 'noto_emoji', and 'noto_source'. The values are absolute paths to the base directories of these noto repositories. Formerly these were a single repository so the paths could all be reached from a single root, but that is no longer the case. """ from os import path _ERR_MSG = """ Could not find ~/.notoconfig or /usr/local/share/noto/config. Nototools uses this file to locate resources it uses, since many resources such as fonts and sample_texts are not installed in locations relative to the nototools python files and scripts. Please create one of the above config files containing a line like the following, where the absolute path to the root of the git repo on your machine follows the '=' character: noto_tools=/path/to/root/of/nototools If you use any of the other noto repos, add similar lines for 'noto_emoji', 'noto_fonts', 'noto_cjk', 'noto_source', or 'noto_fonts_alpha'. """ _values = {} _config_path = None # so we know def _setup(): """The config consists of lines of the form <name> = <value>. values will hold a mapping from the <name> to value. Blank lines and lines starting with '#' are ignored.""" global _config_path paths = [path.expanduser("~/.notoconfig"), "/usr/local/share/noto/config"] for configfile in paths: if path.exists(configfile): with open(configfile, "r") as f: for line in f: line = line.strip() if not line or line.startswith("#"): continue k, v = line.split("=", 1) _values[k.strip()] = v.strip() _config_path = configfile break # This needs to be silent. It causes a makefile error in noto-emoji, # which expects stdout to consist only of the output of a python # script it runs. _setup() # convenience for names we expect. # By default we allow running without a config, since many small tools don't # require it. But if you run code that calls noto_tools and provides no # default, we assume you do require it and raise an exception. def noto_tools(default=""): """Local path to nototools git repo. If this is called, we require config to be set up.""" result = _values.get("noto_tools", default) if result: return result raise Exception(_ERR_MSG) def noto_fonts(default=""): """Local path to noto-font git repo""" return _values.get("noto_fonts", default) def noto_cjk(default=""): """Local path to noto-cjk git repo""" return _values.get("noto_cjk", default) def noto_emoji(default=""): """Local path to noto-emoji git repo""" return _values.get("noto_emoji", default) def noto_source(default=""): """Local path to noto-source git repo""" return _values.get("noto_source", default) def noto_fonts_alpha(default=""): """Local path to noto-fonts-alpha git repo""" return _values.get("noto_fonts_alpha", default) if __name__ == "__main__": keyset = set(_values.keys()) if not keyset: print("no keys defined, probably no notoconfig file was found.") else: wid = max(len(k) for k in keyset) fmt = "%%%ds: %%s" % wid for k in sorted(keyset): print(fmt % (k, get(k))) print("config: %s" % _config_path)

32.81203

78

0.681714

#!/usr/bin/env python # Copyright 2015 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. """Read config file for noto tools. One could also just define some environment variables, but using Python for this lets you keep your environment and shell prefs clean. This expects a file named '.notoconfig' in the users home directory. It should contain lines consisting of a name, '=' and a path. The expected names are 'noto_tools', 'noto_fonts', 'noto_cjk', 'noto_emoji', and 'noto_source'. The values are absolute paths to the base directories of these noto repositories. Formerly these were a single repository so the paths could all be reached from a single root, but that is no longer the case. """ from os import path _ERR_MSG = """ Could not find ~/.notoconfig or /usr/local/share/noto/config. Nototools uses this file to locate resources it uses, since many resources such as fonts and sample_texts are not installed in locations relative to the nototools python files and scripts. Please create one of the above config files containing a line like the following, where the absolute path to the root of the git repo on your machine follows the '=' character: noto_tools=/path/to/root/of/nototools If you use any of the other noto repos, add similar lines for 'noto_emoji', 'noto_fonts', 'noto_cjk', 'noto_source', or 'noto_fonts_alpha'. """ _values = {} _config_path = None # so we know def _setup(): """The config consists of lines of the form <name> = <value>. values will hold a mapping from the <name> to value. Blank lines and lines starting with '#' are ignored.""" global _config_path paths = [path.expanduser("~/.notoconfig"), "/usr/local/share/noto/config"] for configfile in paths: if path.exists(configfile): with open(configfile, "r") as f: for line in f: line = line.strip() if not line or line.startswith("#"): continue k, v = line.split("=", 1) _values[k.strip()] = v.strip() _config_path = configfile break # This needs to be silent. It causes a makefile error in noto-emoji, # which expects stdout to consist only of the output of a python # script it runs. _setup() # convenience for names we expect. # By default we allow running without a config, since many small tools don't # require it. But if you run code that calls noto_tools and provides no # default, we assume you do require it and raise an exception. def noto_tools(default=""): """Local path to nototools git repo. If this is called, we require config to be set up.""" result = _values.get("noto_tools", default) if result: return result raise Exception(_ERR_MSG) def noto_fonts(default=""): """Local path to noto-font git repo""" return _values.get("noto_fonts", default) def noto_cjk(default=""): """Local path to noto-cjk git repo""" return _values.get("noto_cjk", default) def noto_emoji(default=""): """Local path to noto-emoji git repo""" return _values.get("noto_emoji", default) def noto_source(default=""): """Local path to noto-source git repo""" return _values.get("noto_source", default) def noto_fonts_alpha(default=""): """Local path to noto-fonts-alpha git repo""" return _values.get("noto_fonts_alpha", default) def get(key, default=""): return _values.get(key, default) if __name__ == "__main__": keyset = set(_values.keys()) if not keyset: print("no keys defined, probably no notoconfig file was found.") else: wid = max(len(k) for k in keyset) fmt = "%%%ds: %%s" % wid for k in sorted(keyset): print(fmt % (k, get(k))) print("config: %s" % _config_path)

41

0

23

e0b252fafdf6487f16fd80918000aa7a03e2b15b

541

py

Python

src/assets/svg/clear_fill.py

Pure-Peace/vue-adaptive-template

a3f39258ac748eff84c894510cce0f8227358b88

[ "MIT" ]

7

2020-10-27T15:16:05.000Z

2022-02-15T08:01:21.000Z

src/assets/svg/clear_fill.py

Pure-Peace/vue3-vite-ssr

650b4aa24e4684b6a1d93fcf27bf744dfae60215

[ "MIT" ]

3

2021-03-10T19:59:12.000Z

2021-08-31T19:46:45.000Z

src/assets/svg/clear_fill.py

Pure-Peace/vue-adaptive-template

a3f39258ac748eff84c894510cce0f8227358b88

[ "MIT" ]

1

2021-12-21T14:14:51.000Z

import os import re for svg in [file for file in os.listdir(os.getcwd()) if '.svg' in file]: file_path = '{}/{}'.format(os.getcwd(), svg) with open (file_path, 'r', encoding='utf-8') as svg_file: content = svg_file.read() target = re.search('fill=".*?"', content) if target != None: fixed_content = content.replace(target.group(), '') with open (file_path, 'w', encoding='utf-8') as svg_file: svg_file.write(fixed_content) print('done 1') print('all done')

38.642857

72

0.578558

import os import re for svg in [file for file in os.listdir(os.getcwd()) if '.svg' in file]: file_path = '{}/{}'.format(os.getcwd(), svg) with open (file_path, 'r', encoding='utf-8') as svg_file: content = svg_file.read() target = re.search('fill=".*?"', content) if target != None: fixed_content = content.replace(target.group(), '') with open (file_path, 'w', encoding='utf-8') as svg_file: svg_file.write(fixed_content) print('done 1') print('all done')

0

86bcb532ed51c6b1843ed22a561ca6db0f664b44

246

py

Python

util.py

mabruckner/rsstastic

ae00deb9bf9276df5b41be9d95b221c13ba7bf7e

[ "MIT" ]

null

util.py

mabruckner/rsstastic

ae00deb9bf9276df5b41be9d95b221c13ba7bf7e

[ "MIT" ]

null

util.py

mabruckner/rsstastic

ae00deb9bf9276df5b41be9d95b221c13ba7bf7e

[ "MIT" ]

null

import base64

20.5

57

0.727642

import base64 def b64_to_key(data): return base64.urlsafe_b64decode(data).decode('ascii') def key_to_b64(key): return base64.urlsafe_b64encode(key.encode('ascii')) def get_url(key): return '/item/'+key_to_b64(key).decode('ascii')

162

0

69

cf2818a4a563783db22a4d4eba9f7f379db5d084

419

py

Python

decorators.py

oramirezperera/closures

17aa68642448eaa607872e871d8785ecdfe23d8b

[ "MIT" ]

null

decorators.py

oramirezperera/closures

17aa68642448eaa607872e871d8785ecdfe23d8b

[ "MIT" ]

null

decorators.py

oramirezperera/closures

17aa68642448eaa607872e871d8785ecdfe23d8b

[ "MIT" ]

null

from datetime import datetime @execution_time random_func()

22.052632

88

0.653938

from datetime import datetime def execution_time(func): def wrapper(): initial_time = datetime.now() func() final_time = datetime.now() time_elapsed = final_time - initial_time print('The execution time was ' + str(time_elapsed.total_seconds()) + 'seconds') return wrapper @execution_time def random_func(): for _ in range(1,10000000): pass random_func()

311

0

45

44016d8febc11f65a98a21222676ac994b234bb7

5,863

py

Python

pyzoo/zoo/chronos/model/prophet.py

cabuliwallah/analytics-zoo

5e662bd01c5fc7eed412973119594cf2ecea8b11

[ "Apache-2.0" ]

1

2021-06-16T11:42:32.000Z

pyzoo/zoo/chronos/model/prophet.py

cabuliwallah/analytics-zoo

5e662bd01c5fc7eed412973119594cf2ecea8b11

[ "Apache-2.0" ]

null

pyzoo/zoo/chronos/model/prophet.py

cabuliwallah/analytics-zoo

5e662bd01c5fc7eed412973119594cf2ecea8b11

[ "Apache-2.0" ]

null

# Copyright 2018 Analytics Zoo Authors. # # 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 json import pandas as pd from prophet import Prophet from prophet.serialize import model_to_json, model_from_json from zoo.automl.common.metrics import Evaluator from zoo.automl.model.abstract import BaseModel, ModelBuilder

40.157534

99

0.656149

# Copyright 2018 Analytics Zoo Authors. # # 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 json import pandas as pd from prophet import Prophet from prophet.serialize import model_to_json, model_from_json from zoo.automl.common.metrics import Evaluator from zoo.automl.model.abstract import BaseModel, ModelBuilder class ProphetModel(BaseModel): def __init__(self): """ Initialize Model """ self.metric = 'mse' self.model = None self.model_init = False def _build(self, **config): """ build the model and initialize. :param config: hyperparameters for the model """ changepoint_prior_scale = config.get('changepoint_prior_scale', 0.05) seasonality_prior_scale = config.get('seasonality_prior_scale', 10.0) holidays_prior_scale = config.get('holidays_prior_scale', 10.0) seasonality_mode = config.get('seasonality_mode', 'additive') changepoint_range = config.get('changepoint_range', 0.8) self.metric = config.get('metric', self.metric) self.model = Prophet(changepoint_prior_scale=changepoint_prior_scale, seasonality_prior_scale=seasonality_prior_scale, holidays_prior_scale=holidays_prior_scale, changepoint_range=changepoint_range, seasonality_mode=seasonality_mode) def fit_eval(self, data, validation_data, **config): """ Fit on the training data from scratch. :param data: training data, an dataframe with Td rows, and 2 columns, with column 'ds' indicating date and column 'y' indicating target and Td is the time dimension :param validation_data: validation data, should be the same type as data. :return: the evaluation metric value """ if not self.model_init: self._build(**config) self.model_init = True self.model.fit(data) val_metric = self.evaluate(target=validation_data, metrics=[self.metric])[0].item() return {self.metric: val_metric} def predict(self, data=None, horizon=24): """ Predict horizon time-points ahead the input data in fit_eval :param data: Prophet predicts the horizon steps foreward from the training data. So data should be None as it is not used. :param horizon: horizon length to predict :return: predicted result of length horizon """ if data is not None: raise ValueError("We don't support input data currently") if self.model is None: raise Exception("Needs to call fit_eval or restore first before calling predict") future = self.model.make_future_dataframe(periods=horizon) out = self.model.predict(future)[-horizon:] return out def evaluate(self, target, data=None, metrics=['mse']): """ Evaluate on the prediction results. We predict horizon time-points ahead the input data in fit_eval before evaluation, where the horizon length equals the second dimension size of target. :param data: Prophet predicts the horizon steps foreward from the training data. So data should be None as it is not used. :param target: target for evaluation. :param metrics: a list of metrics in string format :return: a list of metric evaluation results """ if data is not None: raise ValueError("We don't support input data currently") if target is None: raise ValueError("Input invalid target of None") if self.model is None: raise Exception("Needs to call fit_eval or restore first before calling evaluate") horizon = len(target) future = self.model.make_future_dataframe(periods=horizon) target_pred = self.predict(horizon=horizon)[['yhat']] return [Evaluator.evaluate(m, target[['y']].values, target_pred.values) for m in metrics] def save(self, checkpoint): if self.model is None: raise Exception("Needs to call fit_eval or restore first before calling save") with open(checkpoint, 'w') as fout: json.dump(model_to_json(self.model), fout) def restore(self, checkpoint): with open(checkpoint, 'r') as fin: self.model = model_from_json(json.load(fin)) self.model_init = True class ProphetBuilder(ModelBuilder): def __init__(self, **prophet_config): """ Initialize Prophet Model :param prophet_config: Other prophet hyperparameters. You may refer to https://facebook.github.io/prophet/docs/diagnostics.html#hyperparameter-tuning for the parameter names to specify. """ self.model_config = prophet_config.copy() def build(self, config): """ Build Prophet Model :param config: Other prophet hyperparameters. You may refer to https://facebook.github.io/prophet/docs/diagnostics.html#hyperparameter-tuning for the parameter names to specify. """ from zoo.chronos.model.prophet import ProphetModel model = ProphetModel() model._build(**config) return model

367

4,627

46

450ca3987d19aeeb31e66048ea9f05f4707a6a4e

2,182

py

Python

mdptools/utils/highlight.py

mholdg16/py-mdptools

ae986edc2097e97cb73331d66f0051ca9f5bd15c

[ "MIT" ]

1

2021-12-15T13:22:48.000Z

mdptools/utils/highlight.py

mholdg16/py-mdptools

ae986edc2097e97cb73331d66f0051ca9f5bd15c

[ "MIT" ]

2

2021-11-09T23:43:48.000Z

2021-11-13T20:41:12.000Z

mdptools/utils/highlight.py

mholdg16/py-mdptools

ae986edc2097e97cb73331d66f0051ca9f5bd15c

[ "MIT" ]

null

# pylint: disable=too-few-public-methods,missing-docstring highlight = Highlight()

22.968421

58

0.579285

# pylint: disable=too-few-public-methods,missing-docstring class COLORS_ENABLED: RESET = "\033[0m" BOLD = "\033[01m" BLACK = "\033[30m" RED = "\033[31m" GREEN = "\033[32m" ORANGE = "\033[33m" BLUE = "\033[34m" PURPLE = "\033[35m" CYAN = "\033[36m" LIGHTGREY = "\033[37m" DARKGREY = "\033[90m" LIGHTRED = "\033[91m" LIGHTGREEN = "\033[92m" YELLOW = "\033[93m" LIGHTBLUE = "\033[94m" PINK = "\033[95m" LIGHTCYAN = "\033[96m" class COLORS_DISABLED: RESET = "" BOLD = "" BLACK = "" RED = "" GREEN = "" ORANGE = "" BLUE = "" PURPLE = "" CYAN = "" LIGHTGREY = "" DARKGREY = "" LIGHTRED = "" LIGHTGREEN = "" YELLOW = "" LIGHTBLUE = "" PINK = "" LIGHTCYAN = "" class Highlight: def __init__(self): self.bc = COLORS_DISABLED def __call__(self, color: str, text: str) -> str: return color + f"{text}" + self.bc.RESET def state(self, text: str): return self.__call__(self.bc.LIGHTCYAN, text) def action(self, text: str): return self.__call__(self.bc.LIGHTGREEN, text) def function(self, text: str): return self.__call__(self.bc.LIGHTBLUE, text) def variable(self, text: str): return self.__call__(self.bc.PINK, text) def string(self, text: str): return self.__call__(self.bc.YELLOW, text) def comment(self, text: str): return self.__call__(self.bc.LIGHTGREY, text) def ok(self, text: str): return self.__call__(self.bc.LIGHTGREEN, text) def fail(self, text: str): return self.__call__(self.bc.LIGHTRED, text) def error(self, text: str): return self.__call__(self.bc.RED, text) def numeral(self, text: str): return self.__call__(self.bc.ORANGE, text) def types(self, text: str): return self.__call__(self.bc.GREEN, text) def note(self, text: str): return self.__call__(self.bc.PURPLE, text) def use_colors(self, value: bool = True): if value: self.bc = COLORS_ENABLED else: self.bc = COLORS_DISABLED highlight = Highlight()

940

683

472

ef71623e2adac2944868d6fb2d5158e9f125310e

35,571

py

Python

interpro7dw/ebi/interpro/ftp/xmlfiles.py

ProteinsWebTeam/interpro7-dw

5ff1886bb767964658574bd39b812d822a894163

[ "Apache-2.0" ]

null

interpro7dw/ebi/interpro/ftp/xmlfiles.py

ProteinsWebTeam/interpro7-dw

5ff1886bb767964658574bd39b812d822a894163

[ "Apache-2.0" ]

1

2020-08-14T23:15:24.000Z

interpro7dw/ebi/interpro/ftp/xmlfiles.py

ProteinsWebTeam/interpro7-dw

5ff1886bb767964658574bd39b812d822a894163

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import json import gzip import math import multiprocessing as mp import os import re import shutil from tempfile import mkstemp from typing import Optional, Sequence from xml.dom.minidom import getDOMImplementation, parseString from xml.parsers.expat import ExpatError import cx_Oracle import MySQLdb import MySQLdb.cursors from interpro7dw import logger from interpro7dw.ebi import pdbe from interpro7dw.ebi.interpro import production as ippro, utils from interpro7dw.utils import DumpFile, KVdb, Store, loadobj, url2dict _DC_STATUSES = {v: k for k, v in utils.DC_STATUSES.items()} _TAGS = { "cazy": "CAZY", "cog": "COG", "genprop": "GENPROP", "ec": "EC", "intenz": "EC", "interpro": "INTERPRO", "pfam": "PFAM", "pdbe": "PDBE", "pirsf": "PIRSF", "prosite": "PROSITE", "prositedoc": "PROSITEDOC", "superfamily": "SSF", "swissprot": "SWISSPROT", "tigrfams": "TIGRFAMs" }

39.132013

79

0.519103

# -*- coding: utf-8 -*- import json import gzip import math import multiprocessing as mp import os import re import shutil from tempfile import mkstemp from typing import Optional, Sequence from xml.dom.minidom import getDOMImplementation, parseString from xml.parsers.expat import ExpatError import cx_Oracle import MySQLdb import MySQLdb.cursors from interpro7dw import logger from interpro7dw.ebi import pdbe from interpro7dw.ebi.interpro import production as ippro, utils from interpro7dw.utils import DumpFile, KVdb, Store, loadobj, url2dict _DC_STATUSES = {v: k for k, v in utils.DC_STATUSES.items()} _TAGS = { "cazy": "CAZY", "cog": "COG", "genprop": "GENPROP", "ec": "EC", "intenz": "EC", "interpro": "INTERPRO", "pfam": "PFAM", "pdbe": "PDBE", "pirsf": "PIRSF", "prosite": "PROSITE", "prositedoc": "PROSITEDOC", "superfamily": "SSF", "swissprot": "SWISSPROT", "tigrfams": "TIGRFAMs" } def _restore_tags(match: re.Match) -> str: tag, key = match.groups() tag = tag.lower() if tag == "cite": return f'<cite idref="{key}"/>' elif tag in _TAGS: return f'<db_xref db="{_TAGS[tag]}" dbkey="{key}"/>' elif tag not in ["mim", "pmid", "pubmed"]: logger.warning(match.group(0)) def _restore_abstract(data: str) -> str: return re.sub(pattern=r"\[([a-z]+):([a-z0-9_.:]+)\]", repl=_restore_tags, string=data, flags=re.I) def export_interpro(url: str, p_entries: str, p_entry2xrefs: str, p_interpro2taxonomy: str, outdir: str, tmpdir: Optional[str] = None): shutil.copy(os.path.join(os.path.dirname(__file__), "interpro.dtd"), outdir) logger.info("loading entries") entries = loadobj(p_entries) interpro_entries = [] deleted_entries = [] for e in entries.values(): if e.database != "interpro": continue elif e.is_deleted: deleted_entries.append(e.accession) else: interpro_entries.append(e.accession) logger.info("creating entry-taxon database") fd, taxdb = mkstemp(dir=tmpdir) os.close(fd) os.remove(taxdb) with DumpFile(p_interpro2taxonomy) as interpro2taxonomy: with KVdb(taxdb, writeback=True) as kvdb: i = 0 for entry_acc, taxon_id, counts in interpro2taxonomy: kvdb[f"{entry_acc}-{taxon_id}"] = str(counts) i += 1 if not i % 1000000: kvdb.sync() logger.info("loading protein counts") con = MySQLdb.connect(**url2dict(url), charset="utf8mb4") cur = MySQLdb.cursors.SSCursor(con) cur.execute( """ SELECT accession, counts FROM webfront_entry """ ) num_proteins = {} for entry_acc, counts in cur: num_proteins[entry_acc] = str(json.loads(counts)["proteins"]) output = os.path.join(outdir, "interpro.xml.gz") with gzip.open(output, "wt", encoding="utf-8") as fh: fh.write('<?xml version="1.0" encoding="UTF-8"?>\n') fh.write('<!DOCTYPE interprodb SYSTEM "interpro.dtd">\n') fh.write("<interprodb>\n") doc = getDOMImplementation().createDocument(None, None, None) # writing <release> section (do not log progress, < 1 sec) elem = doc.createElement("release") databases = {} cur.execute( """ SELECT name, name_alt, type, num_entries, version, release_date FROM webfront_database ORDER BY name_long """ ) for name, name_alt, db_type, entry_count, version, date in cur: databases[name] = name_alt if db_type in ("entry", "protein"): dbinfo = doc.createElement("dbinfo") dbinfo.setAttribute("version", version) dbinfo.setAttribute("dbname", name_alt) dbinfo.setAttribute("entry_count", str(entry_count)) dbinfo.setAttribute("file_date", date.strftime("%d-%b-%y").upper()) elem.appendChild(dbinfo) elem.writexml(fh, addindent=" ", newl="\n") logger.info("loading taxonomic data") key_species = { "3702", # Arabidopsis thaliana "6239", # Caenorhabditis elegans "7955", # Danio rerio "7227", # Drosophila melanogaster "9606", # Homo sapiens "10090", # Mus musculus "367110", # Neurospora crassa "10116", # Rattus norvegicus "559292", # Saccharomyces cerevisiae "284812", # Schizosaccharomyces pombe "4577", # Zea mays } superkingdoms = { "Archaea": None, "Bacteria": None, "Eukaryota": None, "Viruses": None } cur.execute( """ SELECT accession, scientific_name, full_name, lineage FROM webfront_taxonomy """ ) taxa = {} for tax_id, sci_name, full_name, lineage in cur: """ lineage stored as a string with heading/leading whitespaces, and a whitespace between taxa """ taxa[tax_id] = (full_name, lineage.strip().split()) if sci_name in superkingdoms: superkingdoms[sci_name] = tax_id cur.close() con.close() # Raise if a superkingdom is not in the table for sci_name, tax_id in superkingdoms.items(): if tax_id is None: raise ValueError(f"{sci_name}: missing taxon ID") superkingdoms = {tax_id for tax_id in superkingdoms.values()} logger.info("writing entries") with DumpFile(p_entry2xrefs) as entry2xrefs, KVdb(taxdb) as kvdb: for entry_acc, xrefs in entry2xrefs: entry = entries[entry_acc] if entry.database != "interpro" or entry.is_deleted: continue elem = doc.createElement("interpro") elem.setAttribute("id", entry.accession) elem.setAttribute("protein_count", num_proteins[entry_acc]) elem.setAttribute("short_name", entry.short_name) elem.setAttribute("type", entry.type) name = doc.createElement("name") name.appendChild(doc.createTextNode(entry.name)) elem.appendChild(name) text = _restore_abstract('\n'.join(entry.description)) try: _doc = parseString(f"<abstract>{text}</abstract>") except ExpatError as exc: # TODO: use CDATA section for all entries logger.warning(f"{entry_acc}: {exc}") # abstract = doc.createElement("abstract") # abstract.appendChild(doc.createCDATASection(text)) else: abstract = _doc.documentElement elem.appendChild(abstract) if entry.go_terms: go_list = doc.createElement("class_list") for term in entry.go_terms: go_elem = doc.createElement("classification") go_elem.setAttribute("id", term["identifier"]) go_elem.setAttribute("class_type", "GO") _elem = doc.createElement("category") _elem.appendChild( doc.createTextNode(term["category"]["name"]) ) go_elem.appendChild(_elem) _elem = doc.createElement("description") _elem.appendChild( doc.createTextNode(term["name"]) ) go_elem.appendChild(_elem) go_list.appendChild(go_elem) elem.appendChild(go_list) if entry.literature: pub_list = doc.createElement("pub_list") for pub_id in sorted(entry.literature): pub = entry.literature[pub_id] pub_elem = doc.createElement("publication") pub_elem.setAttribute("id", pub_id) _elem = doc.createElement("author_list") if pub["authors"]: _elem.appendChild( doc.createTextNode(", ".join(pub['authors'])) ) else: _elem.appendChild(doc.createTextNode("Unknown")) pub_elem.appendChild(_elem) if pub["title"]: _elem = doc.createElement("title") _elem.appendChild( doc.createTextNode(pub["title"]) ) pub_elem.appendChild(_elem) if pub["URL"]: _elem = doc.createElement("url") _elem.appendChild(doc.createTextNode(pub["URL"])) pub_elem.appendChild(_elem) _elem = doc.createElement("db_xref") if pub["PMID"]: _elem.setAttribute("db", "PUBMED") _elem.setAttribute("dbkey", str(pub["PMID"])) else: _elem.setAttribute("db", "MEDLINE") _elem.setAttribute("dbkey", "MEDLINE") pub_elem.appendChild(_elem) if pub["ISO_journal"]: _elem = doc.createElement("journal") _elem.appendChild( doc.createTextNode(pub["ISO_journal"]) ) pub_elem.appendChild(_elem) if pub["ISBN"]: _elem = doc.createElement("book_title") isbn = f"ISBN:{pub['ISBN']}" _elem.appendChild(doc.createTextNode(isbn)) pub_elem.appendChild(_elem) if pub["volume"] or pub["issue"] or pub["raw_pages"]: _elem = doc.createElement("location") if pub["volume"]: _elem.setAttribute("volume", pub["volume"]) if pub["issue"]: _elem.setAttribute("issue", pub["issue"]) if pub["raw_pages"]: _elem.setAttribute("pages", pub["raw_pages"]) pub_elem.appendChild(_elem) if pub["year"]: _elem = doc.createElement("year") _elem.appendChild( doc.createTextNode(str(pub["year"])) ) pub_elem.appendChild(_elem) pub_list.appendChild(pub_elem) elem.appendChild(pub_list) parent, children = entry.relations if parent: par_elem = doc.createElement("parent_list") _elem = doc.createElement("rel_ref") _elem.setAttribute("ipr_ref", parent) par_elem.appendChild(_elem) elem.appendChild(par_elem) if children: child_list = doc.createElement("child_list") for child in children: _elem = doc.createElement("rel_ref") _elem.setAttribute("ipr_ref", child) child_list.appendChild(_elem) elem.appendChild(child_list) members = [] for database, signatures in entry.integrates.items(): for signature_acc in signatures: members.append(( signature_acc, entries[signature_acc].short_name, database, num_proteins[signature_acc], )) mem_list = doc.createElement("member_list") for member in sorted(members): _elem = doc.createElement("db_xref") _elem.setAttribute("protein_count", member[3]) _elem.setAttribute("db", databases[member[2]]) _elem.setAttribute("dbkey", member[0]) _elem.setAttribute("name", member[1]) mem_list.appendChild(_elem) elem.appendChild(mem_list) # Merge cross-references and pathways cross_refs = {} for key, values in entry.cross_references.items(): cross_refs[databases[key]] = values for key, values in entry.pathways.items(): cross_refs[databases[key]] = [val["id"] for val in values] if cross_refs: xref_list = doc.createElement("external_doc_list") for ref_db in sorted(cross_refs): for ref_id in sorted(cross_refs[ref_db]): _elem = doc.createElement("db_xref") _elem.setAttribute("db", ref_db) _elem.setAttribute("dbkey", ref_id) xref_list.appendChild(_elem) elem.appendChild(xref_list) if xrefs["structures"]: xref_list = doc.createElement("structure_db_links") for pdb_id in sorted(xrefs["structures"]): _elem = doc.createElement("db_xref") _elem.setAttribute("db", "PDB") _elem.setAttribute("dbkey", pdb_id) xref_list.appendChild(_elem) elem.appendChild(xref_list) # Find key species and taxonomic distribution entry_key_species = [] entry_superkingdoms = {} for tax_id in xrefs["taxa"]: full_name, lineage = taxa[tax_id] if tax_id in key_species: entry_key_species.append((full_name, tax_id)) # Find the superkingdom contain this taxon for superkingdom_id in superkingdoms: if superkingdom_id in lineage: break else: continue try: other_lineage = entry_superkingdoms[superkingdom_id] except KeyError: entry_superkingdoms[superkingdom_id] = lineage else: # Compare lineages and find lowest common ancestor i = 0 while i < len(lineage) and i < len(other_lineage): if lineage[i] != other_lineage[i]: break i += 1 # Path to the lowest common ancestor entry_superkingdoms[superkingdom_id] = lineage[:i] # Get lowest common ancestor for each represented superkingdom lowest_common_ancestors = [] for lineage in entry_superkingdoms.values(): # Lowest common ancestor tax_id = lineage[-1] full_name, _ = taxa[tax_id] lowest_common_ancestors.append((full_name, tax_id)) # Write taxonomic distribution tax_dist = doc.createElement("taxonomy_distribution") for full_name, tax_id in sorted(lowest_common_ancestors): _elem = doc.createElement("taxon_data") _elem.setAttribute("name", full_name) key = f"{entry_acc}-{tax_id}" _elem.setAttribute("proteins_count", kvdb[key]) tax_dist.appendChild(_elem) elem.appendChild(tax_dist) if entry_key_species: # Write key species key_spec = doc.createElement("key_species") for full_name, tax_id in sorted(entry_key_species): _elem = doc.createElement("taxon_data") _elem.setAttribute("name", full_name) key = f"{entry_acc}-{tax_id}" _elem.setAttribute("proteins_count", kvdb[key]) key_spec.appendChild(_elem) elem.appendChild(key_spec) elem.writexml(fh, addindent=" ", newl="\n") if deleted_entries: block = doc.createElement("deleted_entries") for entry_acc in sorted(deleted_entries): elem = doc.createElement("del_ref") elem.setAttribute("id", entry_acc) block.appendChild(elem) block.writexml(fh, addindent=" ", newl="\n") fh.write("</interprodb>\n") logger.info(f"temporary file: {os.path.getsize(taxdb)/1024/1024:,.0f} MB") os.remove(taxdb) logger.info("complete") def _create_match(doc, signature: dict, locations: Sequence[dict]): match = doc.createElement("match") match.setAttribute("id", signature["accession"]) match.setAttribute("name", signature["name"]) match.setAttribute("dbname", signature["database"]) match.setAttribute("status", 'T') """ The model is stored in locations, so we get the model from the first location for the match's 'model' attribute """ match.setAttribute("model", locations[0]["model"]) match.setAttribute("evd", signature["evidence"]) if signature["interpro"]: ipr = doc.createElement("ipr") for attname, value in signature["interpro"]: if value: ipr.setAttribute(attname, value) match.appendChild(ipr) for loc in locations: match.appendChild(create_lcn(doc, loc)) return match def create_lcn(doc, location: dict): fragments = location["fragments"] """ We do not have to orginal start/end match positions, so we use the leftmost/rightmost fragment positions. We also reconstruct the fragment string (START-END-STATUS) """ fragments_obj = [] start = fragments[0]["start"] end = 0 for frag in fragments: if frag["end"] > end: end = frag["end"] status = _DC_STATUSES[frag["dc-status"]] fragments_obj.append(f"{frag['start']}-{frag['end']}-{status}") lcn = doc.createElement("lcn") lcn.setAttribute("start", str(start)) lcn.setAttribute("end", str(end)) lcn.setAttribute("fragments", ','.join(fragments_obj)) lcn.setAttribute("score", str(location["score"])) return lcn def _write_match_tmp(signatures: dict, u2variants: dict, p_proteins: str, p_uniprot2matches: str, start: str, stop: Optional[str], output: str): proteins = Store(p_proteins) u2matches = Store(p_uniprot2matches) with open(output, "wt", encoding="utf-8") as fh: doc = getDOMImplementation().createDocument(None, None, None) for uniprot_acc, protein in proteins.range(start, stop): elem = doc.createElement("protein") elem.setAttribute("id", uniprot_acc) elem.setAttribute("name", protein["identifier"]) elem.setAttribute("length", str(protein["length"])) elem.setAttribute("crc64", protein["crc64"]) try: protein_entries = u2matches[uniprot_acc] except KeyError: pass else: for signature_acc in sorted(protein_entries): try: signature = signatures[signature_acc] except KeyError: # InterPro entry continue elem.appendChild( _create_match(doc, signature, protein_entries[signature_acc]) ) finally: elem.writexml(fh, addindent=" ", newl="\n") protein_variants = u2variants.get(uniprot_acc, []) for variant, length, crc64, matches in protein_variants: elem = doc.createElement("protein") elem.setAttribute("id", variant) elem.setAttribute("name", variant) elem.setAttribute("length", str(length)) elem.setAttribute("crc64", crc64) for signature_acc in sorted(matches): try: signature = signatures[signature_acc] except KeyError: # InterPro entry continue elem.appendChild( _create_match(doc, signature, matches[signature_acc]) ) elem.writexml(fh, addindent=" ", newl="\n") def export_matches(pro_url: str, stg_url: str, p_proteins: str, p_uniprot2matches: str, outdir: str, processes: int = 8): shutil.copy(os.path.join(os.path.dirname(__file__), "match_complete.dtd"), outdir) logger.info("loading isoforms") u2variants = {} for accession, variant in ippro.get_isoforms(pro_url).items(): protein_acc = variant["protein_acc"] try: variants = u2variants[protein_acc] except KeyError: variants = u2variants[protein_acc] = [] finally: variants.append(( accession, variant["length"], variant["crc64"], variant["matches"] )) # Sorting variants by accession (so XXXX-1 comes before XXXX-2) for variants in u2variants.values(): variants.sort(key=lambda x: x[0]) logger.info("loading signatures") con = cx_Oracle.connect(pro_url) cur = con.cursor() signatures = ippro.get_signatures(cur) cur.close() con.close() logger.info("spawning processes") processes = max(1, processes - 1) ctx = mp.get_context(method="spawn") workers = [] with Store(p_proteins) as proteins: proteins_per_file = math.ceil(len(proteins) / processes) start_acc = None for i, uniprot_acc in enumerate(proteins): if not i % proteins_per_file: if start_acc: filename = f"match_{len(workers)+1}.xml" filepath = os.path.join(outdir, filename) p = ctx.Process(target=_write_match_tmp, args=(signatures, u2variants, p_proteins, p_uniprot2matches, start_acc, uniprot_acc, filepath)) p.start() workers.append((p, filepath)) start_acc = uniprot_acc filename = f"match_{len(workers) + 1}.xml" filepath = os.path.join(outdir, filename) p = ctx.Process(target=_write_match_tmp, args=(signatures, u2variants, p_proteins, p_uniprot2matches, start_acc, None, filepath)) p.start() workers.append((p, filepath)) logger.info("waiting for processes") con = MySQLdb.connect(**url2dict(stg_url), charset="utf8mb4") cur = con.cursor() cur.execute( """ SELECT name, name_alt, type, num_entries, version, release_date FROM webfront_database ORDER BY name_long """ ) doc = getDOMImplementation().createDocument(None, None, None) elem = doc.createElement("release") for name, name_alt, db_type, entry_count, version, date in cur: if db_type == "entry": dbinfo = doc.createElement("dbinfo") dbinfo.setAttribute("dbname", name_alt) if version: dbinfo.setAttribute("version", version) if entry_count: dbinfo.setAttribute("entry_count", str(entry_count)) if date: dbinfo.setAttribute("file_date", date.strftime("%d-%b-%y").upper()) elem.appendChild(dbinfo) cur.close() con.close() output = os.path.join(outdir, "match_complete.xml.gz") ofh = None for i, (p, filepath) in enumerate(workers): p.join() if i == 0: # First process to complete logger.info("concatenating XML files") # Open file and write header ofh = gzip.open(output, "wt", encoding="utf-8") ofh.write('<?xml version="1.0" encoding="UTF-8"?>\n') ofh.write('<!DOCTYPE interpromatch SYSTEM "match_complete.dtd">\n') ofh.write('<interpromatch>\n') elem.writexml(ofh, addindent=" ", newl="\n") with open(filepath, "rt", encoding="utf-8") as ifh: while (block := ifh.read(1024)) != '': ofh.write(block) os.remove(filepath) logger.info(f"\t{i + 1} / {len(workers)}") ofh.write('</interpromatch>\n') ofh.close() logger.info("complete") def _write_feature_tmp(features: dict, p_proteins: str, p_uniprot2features: str, start: str, stop: Optional[str], output: str): proteins = Store(p_proteins) u2features = Store(p_uniprot2features) with open(output, "wt", encoding="utf-8") as fh: doc = getDOMImplementation().createDocument(None, None, None) # for uniprot_acc, protein in proteins.range(start, stop): for uniprot_acc, protein_features in u2features.range(start, stop): protein = proteins[uniprot_acc] elem = doc.createElement("protein") elem.setAttribute("id", uniprot_acc) elem.setAttribute("name", protein["identifier"]) elem.setAttribute("length", str(protein["length"])) elem.setAttribute("crc64", protein["crc64"]) for feature_acc in sorted(protein_features): feature = features[feature_acc] feature_match = protein_features[feature_acc] match = doc.createElement("match") match.setAttribute("id", feature_acc) match.setAttribute("name", feature["name"]) match.setAttribute("dbname", feature["database"]) match.setAttribute("status", 'T') match.setAttribute("model", feature_acc) match.setAttribute("evd", feature["evidence"]) for loc in sorted(feature_match["locations"]): # there is only one fragment per location pos_start, pos_end, seq_feature = loc lcn = doc.createElement("lcn") lcn.setAttribute("start", str(pos_start)) lcn.setAttribute("end", str(pos_end)) if seq_feature: lcn.setAttribute("sequence-feature", seq_feature) match.appendChild(lcn) elem.appendChild(match) elem.writexml(fh, addindent=" ", newl="\n") def export_features_matches(url: str, p_proteins: str, p_uniprot2features: str, outdir: str, processes: int = 8): shutil.copy(os.path.join(os.path.dirname(__file__), "extra.dtd"), outdir) logger.info("loading features") con = cx_Oracle.connect(url) cur = con.cursor() features = ippro.get_features(cur) cur.close() con.close() logger.info("spawning processes") processes = max(1, processes - 1) ctx = mp.get_context(method="spawn") workers = [] with Store(p_uniprot2features) as proteins: proteins_per_file = math.ceil(len(proteins) / processes) start_acc = None for i, uniprot_acc in enumerate(proteins): if not i % proteins_per_file: if start_acc: filename = f"extra_{len(workers) + 1}.xml" filepath = os.path.join(outdir, filename) p = ctx.Process(target=_write_feature_tmp, args=(features, p_proteins, p_uniprot2features, start_acc, uniprot_acc, filepath)) p.start() workers.append((p, filepath)) start_acc = uniprot_acc filename = f"extra_{len(workers) + 1}.xml" filepath = os.path.join(outdir, filename) p = ctx.Process(target=_write_feature_tmp, args=(features, p_proteins, p_uniprot2features, start_acc, None, filepath)) p.start() workers.append((p, filepath)) logger.info("concatenating XML files") output = os.path.join(outdir, "extra.xml.gz") with gzip.open(output, "wt", encoding="utf-8") as fh: fh.write('<?xml version="1.0" encoding="UTF-8"?>\n') fh.write('<!DOCTYPE interproextra SYSTEM "extra.dtd">\n') fh.write('<interproextra>\n') doc = getDOMImplementation().createDocument(None, None, None) elem = doc.createElement("release") databases = {(f["database"], f["version"]) for f in features.values()} for name, version in sorted(databases): dbinfo = doc.createElement("dbinfo") dbinfo.setAttribute("dbname", name) if version: dbinfo.setAttribute("version", version) elem.appendChild(dbinfo) elem.writexml(fh, addindent=" ", newl="\n") for i, (p, filepath) in enumerate(workers): p.join() with open(filepath, "rt", encoding="utf-8") as tfh: for line in tfh: fh.write(line) os.remove(filepath) logger.info(f"\t{i+1} / {len(workers)}") fh.write('</interproextra>\n') logger.info("complete") def export_structure_matches(pdbe_url: str, p_proteins: str, p_structures: str, outdir:str): shutil.copy(os.path.join(os.path.dirname(__file__), "feature.dtd"), outdir) logger.info("loading structures") uniprot2pdbe = {} for pdb_id, entry in loadobj(p_structures).items(): for uniprot_acc, chains in entry["proteins"].items(): try: uniprot2pdbe[uniprot_acc][pdb_id] = chains except KeyError: uniprot2pdbe[uniprot_acc] = {pdb_id: chains} logger.info("loading CATH/SCOP domains") uni2prot2cath = pdbe.get_cath_domains(pdbe_url) uni2prot2scop = pdbe.get_scop_domains(pdbe_url) logger.info("writing file") output = os.path.join(outdir, "feature.xml.gz") with gzip.open(output, "wt", encoding="utf-8") as fh: fh.write('<?xml version="1.0" encoding="UTF-8"?>\n') fh.write('<!DOCTYPE interprofeature SYSTEM "feature.dtd">\n') fh.write('<interprofeature>\n') with Store(p_proteins) as proteins: doc = getDOMImplementation().createDocument(None, None, None) for uniprot_acc, protein in proteins.items(): pdb_entries = uniprot2pdbe.get(uniprot_acc, {}) cath_entries = uni2prot2cath.get(uniprot_acc, {}) scop_entries = uni2prot2scop.get(uniprot_acc, {}) if pdb_entries or cath_entries or scop_entries: elem = doc.createElement("protein") elem.setAttribute("id", uniprot_acc) elem.setAttribute("name", protein["identifier"]) elem.setAttribute("length", str(protein["length"])) elem.setAttribute("crc64", protein["crc64"]) for pdb_id in sorted(pdb_entries): chains = pdb_entries[pdb_id] for chain_id in sorted(chains): domain = doc.createElement("domain") domain.setAttribute("id", f"{pdb_id}{chain_id}") domain.setAttribute("dbname", "PDB") for loc in chains[chain_id]: start = loc["protein_start"] end = loc["protein_end"] coord = doc.createElement("coord") coord.setAttribute("pdb", pdb_id) coord.setAttribute("chain", chain_id) coord.setAttribute("start", str(start)) coord.setAttribute("end", str(end)) domain.appendChild(coord) elem.appendChild(domain) for domain_id in sorted(cath_entries): entry = cath_entries[domain_id] domain = doc.createElement("domain") domain.setAttribute("id", domain_id) domain.setAttribute("cfn", entry["superfamily"]["id"]) domain.setAttribute("dbname", "CATH") for loc in entry["locations"]: coord = doc.createElement("coord") coord.setAttribute("pdb", entry["pdb_id"]) coord.setAttribute("chain", entry["chain"]) coord.setAttribute("start", str(loc["start"])) coord.setAttribute("end", str(loc["end"])) domain.appendChild(coord) elem.appendChild(domain) for domain_id in sorted(scop_entries): entry = scop_entries[domain_id] domain = doc.createElement("domain") domain.setAttribute("id", domain_id) domain.setAttribute("cfn", entry["superfamily"]["id"]) domain.setAttribute("dbname", "SCOP") for loc in entry["locations"]: coord = doc.createElement("coord") coord.setAttribute("pdb", entry["pdb_id"]) coord.setAttribute("chain", entry["chain"]) coord.setAttribute("start", str(loc["start"])) coord.setAttribute("end", str(loc["end"])) domain.appendChild(coord) elem.appendChild(domain) elem.writexml(fh, addindent=" ", newl="\n") fh.write('</interprofeature>\n') logger.info("complete")

34,377

0

230

6857bd448442ddfa8d293e203ac7bc287e7f8c42

4,119

py

Python

code/plotter_tests.py

twf2360/Newtons_Cradle

84cab9b81765146d1453a68ee0f50f2a7e511c6b

[ "MIT" ]

null

code/plotter_tests.py

twf2360/Newtons_Cradle

84cab9b81765146d1453a68ee0f50f2a7e511c6b

[ "MIT" ]

null

code/plotter_tests.py

twf2360/Newtons_Cradle

84cab9b81765146d1453a68ee0f50f2a7e511c6b

[ "MIT" ]

null

import pytest import math import numpy as np from ball import ball import matplotlib.pyplot as plt import copy from itertools import combinations import sys import pandas as pd from calculator import calculator import json import dataframes from plotter import plotter from random import random ''' in order to test the functions of the plotter class, data must be collected to plot In order to test the simplest aspects - such as that total energy = pe+ke, and conservation of energy, the simulation of a single ball - a simple pendulum - will be tested ''' def test_list_lengths(): ''' lots of lists are created by the plotter class, and the length of them should be known, as it should be the number of iterations in a lot of case ''' ''' as testing class attributes, not results, need to call a new class instance''' theta = math.pi/6 #initial starting angle! get_results = calculator(0.0001,50000) get_results.get_balls(number = 1,positions= [[1 * math.sin(theta), -1 * math.cos(theta)]], velocities= [[0,0]], radii=[0.02], masses=[1], anchors= [[0,0]]) get_results.calculate(approximation='rk2', density=0) plot = plotter('system_states_over_time', 1) assert len(plot.timelist) == 50000 assert len(plot.total_ke_list) == 50000 assert len(plot.total_pe_list) == 50000 assert len(plot.total_energy_by_time) == 50000 assert len(plot.potential_energy_by_time) == 50000 assert len(plot.kinetic_energy_by_time) == 50000 assert len(plot.list_position_by_time) == 50000 def test_energy_addition(): ''' test to ensure that the when adding kinetic and potential energy to get total energy, that the addition is done correctly ''' ''' use is close due to errors in floating point maths''' energies = plotter_init() ke = energies[0] pe = energies[1] total = energies[2] assert (np.isclose(total[0] , (np.add(ke[0] , pe[0])))).all(), "total energy does not equal potential plus kinetic at the start" random_time = 50000 * random() random_time_int = math.floor(random_time) assert (np.isclose(total[random_time_int], (np.add(ke[random_time_int] ,pe[random_time_int])))).all(), "total energy does not equal potential plus kinetic at the a random point" def two_ball_init(): ''' some of the results rely on the tota energy of the system, and therefore this is to check that these things are caluclated correctly with a more complicated system ''' theta = math.pi/6 #initial starting angle! get_results = calculator(0.0001,50000) get_results.get_balls(number = 2,positions= [[1 * math.sin(theta), -1 * math.cos(theta)], [0,-0.4]], velocities= [[0,0], [0,0]], radii=[0.02,0.02], masses=[1,1], anchors= [[0,0], [0.4]]) get_results.calculate(approximation='rk2', density=0) plot = plotter('system_states_over_time', 2) return plot def test_two_ball_energy(): ''' testing that the total energy of the system is calculated correctly - kinetic plus potential. ''' plot = two_ball_init() ke = plot.total_kinetic_energy pe = plot.total_potential_energy total = plot.total_energy() ke_plus_pe = ke + pe assert np.isclose(ke_plus_pe[0], total[0]).all(), "total energy not equal to kinetic plus potential at start" random_time = 50000 * random() random_time_int = math.floor(random_time) assert np.isclose(ke_plus_pe[random_time_int], total[random_time_int]).all(), "total energy not equal to kinetic plus potential at random time"

41.606061

190

0.704783

import pytest import math import numpy as np from ball import ball import matplotlib.pyplot as plt import copy from itertools import combinations import sys import pandas as pd from calculator import calculator import json import dataframes from plotter import plotter from random import random ''' in order to test the functions of the plotter class, data must be collected to plot In order to test the simplest aspects - such as that total energy = pe+ke, and conservation of energy, the simulation of a single ball - a simple pendulum - will be tested ''' def plotter_init(): theta = math.pi/6 #initial starting angle! get_results = calculator(0.0001,50000) get_results.get_balls(number = 1,positions= [[1 * math.sin(theta), -1 * math.cos(theta)]], velocities= [[0,0]], radii=[0.02], masses=[1], anchors= [[0,0]]) get_results.calculate(approximation='rk2', density=0) plot = plotter('system_states_over_time', 1) ke_by_time = plot.total_kinetic_energy() pe_by_time = plot.total_potential_energy() total_e_by_time = plot.total_energy() return [ke_by_time, pe_by_time, total_e_by_time] def test_list_lengths(): ''' lots of lists are created by the plotter class, and the length of them should be known, as it should be the number of iterations in a lot of case ''' ''' as testing class attributes, not results, need to call a new class instance''' theta = math.pi/6 #initial starting angle! get_results = calculator(0.0001,50000) get_results.get_balls(number = 1,positions= [[1 * math.sin(theta), -1 * math.cos(theta)]], velocities= [[0,0]], radii=[0.02], masses=[1], anchors= [[0,0]]) get_results.calculate(approximation='rk2', density=0) plot = plotter('system_states_over_time', 1) assert len(plot.timelist) == 50000 assert len(plot.total_ke_list) == 50000 assert len(plot.total_pe_list) == 50000 assert len(plot.total_energy_by_time) == 50000 assert len(plot.potential_energy_by_time) == 50000 assert len(plot.kinetic_energy_by_time) == 50000 assert len(plot.list_position_by_time) == 50000 def test_energy_addition(): ''' test to ensure that the when adding kinetic and potential energy to get total energy, that the addition is done correctly ''' ''' use is close due to errors in floating point maths''' energies = plotter_init() ke = energies[0] pe = energies[1] total = energies[2] assert (np.isclose(total[0] , (np.add(ke[0] , pe[0])))).all(), "total energy does not equal potential plus kinetic at the start" random_time = 50000 * random() random_time_int = math.floor(random_time) assert (np.isclose(total[random_time_int], (np.add(ke[random_time_int] ,pe[random_time_int])))).all(), "total energy does not equal potential plus kinetic at the a random point" def two_ball_init(): ''' some of the results rely on the tota energy of the system, and therefore this is to check that these things are caluclated correctly with a more complicated system ''' theta = math.pi/6 #initial starting angle! get_results = calculator(0.0001,50000) get_results.get_balls(number = 2,positions= [[1 * math.sin(theta), -1 * math.cos(theta)], [0,-0.4]], velocities= [[0,0], [0,0]], radii=[0.02,0.02], masses=[1,1], anchors= [[0,0], [0.4]]) get_results.calculate(approximation='rk2', density=0) plot = plotter('system_states_over_time', 2) return plot def test_two_ball_energy(): ''' testing that the total energy of the system is calculated correctly - kinetic plus potential. ''' plot = two_ball_init() ke = plot.total_kinetic_energy pe = plot.total_potential_energy total = plot.total_energy() ke_plus_pe = ke + pe assert np.isclose(ke_plus_pe[0], total[0]).all(), "total energy not equal to kinetic plus potential at start" random_time = 50000 * random() random_time_int = math.floor(random_time) assert np.isclose(ke_plus_pe[random_time_int], total[random_time_int]).all(), "total energy not equal to kinetic plus potential at random time"

548

0

23

c67414731c3470e8d42acae5cbdf0fa8ded1e0a9

676

py

Python

example/functions/add.py

osblinnikov/pytorch-binary

61842542c94766ffa21b0fa3ea86a435f802b95f

[ "MIT" ]

293

2018-08-17T14:29:28.000Z

2022-02-28T12:35:48.000Z

example/functions/add.py

osblinnikov/pytorch-binary

61842542c94766ffa21b0fa3ea86a435f802b95f

[ "MIT" ]

1

2018-08-21T14:48:38.000Z

example/functions/add.py

osblinnikov/pytorch-binary

61842542c94766ffa21b0fa3ea86a435f802b95f

[ "MIT" ]

70

2018-08-21T03:39:38.000Z

2022-03-01T07:21:08.000Z

# functions/add.py import torch from torch.autograd import Function from _ext import my_lib

29.391304

68

0.674556

# functions/add.py import torch from torch.autograd import Function from _ext import my_lib class MyAddFunction(Function): def forward(self, input1, input2): output = input1.new() if not input1.is_cuda: my_lib.my_lib_add_forward(input1, input2, output) else: my_lib.my_lib_add_forward_cuda(input1, input2, output) return output def backward(self, grad_output): grad_input = grad_output.new() if not grad_output.is_cuda: my_lib.my_lib_add_backward(grad_output, grad_input) else: my_lib.my_lib_add_backward_cuda(grad_output, grad_input) return grad_input

498

9

76