How to use the_attribute method in Sure

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networkio.py

Source:networkio.py

1from .. core.Edge import Edge2from .. core.Node import Node3from .. core.NodeType import NodeType4from .. core.Network import Network5from ..core.shared_functions import test_kwarg6from ..core.parameters import saved_node_attribute_list7from ..core.parameters import saved_edge_attribute_list8from ..core.parameters import saved_network_attribute_list9def is_float_try(the_string):10    """ Simple test to check if a string can be represented as a 11    floating point.12    """13    try:14        float(the_string)15        return True16    except ValueError:17        return False18    19def string_to_list(the_string, force_to_float = True, sep_char =  ", "):20    """ Convert strings read from file to Python lists21    """22    the_string = the_string.lstrip("[")23    the_string = the_string.rstrip("]")24    the_list = the_string.split(sep_char)25    if the_list[0].startswith("'") & the_list[0].endswith("'"):26        the_list = [x.lstrip("'").rstrip("'") for x in the_list]27    elif the_list[0].startswith("\'") & the_list[0].endswith("\'"):28        the_list = [x.lstrip("\'").rstrip("\'") for x in the_list]    29    for index, the_value in enumerate(the_list):30        31        if is_float_try(the_value) & (force_to_float == True):32            the_list[index] = float(the_value)33        else:34            the_list[index] = the_value35    return the_list    36def pickle_network(the_network, the_filename, **kwargs):37    """ Break apart and save the network38    Arguments:39     the_network: object to save40     filename: effectively a prefix, don't include .pickle, .npy, etc..., these will be added41    kwargs:42     path: directory to save to43    44    """45    # collections does not appear to be well preserved46    # across platforms, so switched to a47    # list to improve pickle portability48    import cPickle49    # don't need to copy since the object50    # will be written to file.51    # from copy import deepcopy52    from numpy import save53    from numpy import load54    import os55    if 'path' in kwargs:56        path = kwargs['path']57    else:58        path = ""59    # We avoid dependence on60    # package classes.  This will ensure models can be61    # fully ported even with base class updates.62    the_node_list_dict = [] 63    the_edge_list_dict = []64    if len(the_network.nodetypes) == 1:65        the_nodes = the_network.nodetypes[0].nodes66        for the_node in the_nodes:67            the_dict = {}68            the_dict[the_node.id] = {}69            for the_attribute in saved_node_attribute_list:70                the_dict[the_node.id][the_attribute] = getattr(the_node, the_attribute)71            the_node_list_dict.append(the_dict)72        for the_edge in the_network.edges:73            the_dict = {}74            the_dict[the_edge.id] = {}75            for the_attribute in saved_edge_attribute_list:76                the_dict[the_edge.id][the_attribute] = getattr(the_edge, the_attribute)77            the_dict[the_edge.id]['nodes'] = [the_edge._nodes[0].id, the_edge._nodes[1].id]78            the_edge_list_dict.append(the_dict)        79        the_network_dict = {}80        the_network_dict['nodes'] = the_node_list_dict81        the_network_dict['edges'] = the_edge_list_dict82        for the_attribute in saved_network_attribute_list:83            if the_attribute in dir(the_network):84                the_network_dict[the_attribute] = getattr(the_network, the_attribute)85        the_network_dict['id'] = the_network.id86        if not the_filename.endswith(".pickle"):87            the_filename += ".pickle"88        fp = open(path + the_filename, "wb")89        cPickle.dump(the_network_dict, fp)90        fp.close()91    else:92        print "Save error. Convert to monopartite network to save."93def load_pickled_network(the_filename, **kwargs):94    """ Load network object from file95    Arguments:96     the_filename: effectively a prefix, don't include .pickle, .npy, etc..., these will be added97    kwargs:98     path: directory to load from99    100    """101    import cPickle102    import os103    if 'path' in kwargs:104        path = kwargs['path']105    else:106        path = ""107    verbose = test_kwarg('verbose', kwargs, [False, True])108    if not the_filename.endswith(".pickle"):109        the_filename += ".pickle"110    111    if verbose:112        print 'Loading network file %s ...' %(path + the_filename)113        114    fp = open(path + the_filename, "rb")115    the_network_dict = cPickle.load(fp)116    fp.close()117    if verbose:118        print '... file loaded. Creating network nodes ...'    119    the_network = Network(the_network_dict['id'])120    for the_attribute in saved_network_attribute_list:121        if the_attribute in dir(the_network):122            setattr(the_network, the_attribute, the_network_dict[the_attribute])123    the_node_list_dict = the_network_dict['nodes']124    the_edge_list_dict = the_network_dict['edges']125    the_node_ids = [x.keys()[0] for x in the_node_list_dict]126    the_nodetype = the_network.nodetypes[0]127    the_nodetype.add_nodes(the_node_ids)128    for the_index, the_node in enumerate(the_nodetype.nodes):129        for the_attribute in saved_node_attribute_list:130            if the_attribute in dir(the_node):131                setattr(the_node, the_attribute, the_node_list_dict[the_index][the_node.id][the_attribute])132    if verbose:133        print '... nodes created. Linking nodes ...'  134    the_node_pair_list = []135    for the_index, the_edge_dict in enumerate(the_edge_list_dict):136        # We allow for updating the edge id here with the new default separation character137        the_edge_dict = the_edge_dict[the_edge_dict.keys()[0]]138        the_node_pair = [the_network.nodetypes[0].nodes.get_by_id(the_edge_dict['nodes'][0]), the_network.nodetypes[0].nodes.get_by_id(the_edge_dict['nodes'][1])]139        the_node_pair_list.append(the_node_pair)140    the_edge_list = the_network.connect_node_pair_list(the_node_pair_list)141                142    for the_index, the_edge in enumerate(the_edge_list):143        the_edge_dict = the_edge_list_dict[the_index]144        the_edge_dict = the_edge_dict[the_edge_dict.keys()[0]]145        for the_attribute in saved_edge_attribute_list:146            if the_attribute in dir(the_edge):147                setattr(the_edge, the_attribute, the_edge_dict[the_attribute])148        149    the_network.update()150    151    return the_network152def create_network_model_from_textfile(network_id, network_file, **kwargs):153    """ Script to build a basic network model154    from a network model. Will reserve annotation,155    initialization for helper functions to call later156    Arguments:157     network_id: string, name of the model158     file_name: name of the network file.  2 columns tab delimited, with node1 node2159    kwargs:160     none, just a pass-through161    Returns:162     network_model163    """164    verbose = test_kwarg('verbose', kwargs, [False, True])165    if verbose:166        print "Reading the network file..."167        168    fp = open(network_file, 'rU')169    the_list = fp.readlines()170    the_list = [x.rstrip("\n") for x in the_list]171    fp.close()172    if verbose:173        print "     ... read the file."  174        print "Creating the nodes..."175    176    the_nodes_1 = []177    the_nodes_2 = []178    for the_entry in the_list:179        the_entry = the_entry.split("\t")180        the_nodes_1.append(the_entry[0])181        the_nodes_2.append(the_entry[1])182    the_nodes = list(set(the_nodes_1 + the_nodes_2))183    the_nodes.sort()184    the_network = Network(network_id)185    the_nodetype = the_network.nodetypes[0]186    the_nodetype.add_nodes(the_nodes)187    # we will define nodes as the default 'monopartite' nodetype188    for the_node in the_nodetype.nodes:189        the_node.set_nodetype(the_nodetype.id)190        191    if verbose:192        print "     ... the nodes are created."193        print "Linking the nodes, this may take a while..."194    the_nodes_1 = [the_network.nodetypes[0].nodes.get_by_id(the_id) for the_id in the_nodes_1]195    the_nodes_2 = [the_network.nodetypes[0].nodes.get_by_id(the_id) for the_id in the_nodes_2]196    # Get rid of duplicate entries197    the_node_pairs = [[the_nodes_1[i], the_nodes_2[i]] for i in range(0, len(the_nodes_1))]198    # Get rid of pairs where node pairs with itself199    the_node_pairs = [x for x in the_node_pairs if (x[0] != x[1])]200        201    the_edge_list = the_network.connect_node_pair_list(the_node_pairs, **kwargs)202    203    the_network.update()204    return the_network205def create_source_dict_from_textfile(source_file, **kwargs):206    """ Script to create a dict of source values.  This207    will attempt to pull more ids with bioservices if more ids are208    specified.209    Arguments:210     source_file: name of the file that contains the sources.211      1 or 2 columns tab delimited, with node /t value_1212      node: id will be used for pairing to netowrk model nodes213      value_1: optional, assumed to be 1.214    kwargs: 215     none, just a pass through216    Returns:217     source_dict218                  219    """220    continue_flag = True221    222    try:223        fp = open(source_file, 'rU')224        the_list = fp.readlines()225        the_list = [x.rstrip("\n") for x in the_list]226        limit_dict = {}227    except:228        print('Cannot load the source file.  Exiting...')229        continue_flag = False230    source_dict = {}231    if continue_flag:232        source_dict = {}233        for the_entry in the_list:234            the_entry = the_entry.split("\t")235            file_node_id = the_entry[0]236            source_dict[file_node_id] = {}237            if len(the_entry) == 1:238                the_value = 1.239            else:240                the_value = float(the_entry[1])241            source_dict[file_node_id]['value'] = the_value242    return source_dict243def read_table_file_to_dict(filename, **kwargs):244    """simple function to extract a dict of dicts as245    {top_key:{key: value}} from an 246    Unix / tab-delineated file.  This is useful for getting 247    node / edge attributes stored in text format.  The first row248    is assumed to be header information.249    Arguments:250     filename251    kwargs:252     top_key: if left blank, the first entry in the first line is taken to253      be the highest level key for the 254     subfield_key_list: a list of fields to include.  Leave blank if all255                        fields are to be included.256     comment_char: Lines starting with this character/string257                  will be ignored258     sep_char: Separation character259     interpret_lists: [True (default), False]260     columns_on_top: [False (default), True]261      if True, the columns will be used262      as the top level keys.263    Returns:264     organized_return_dict265      266    267    """268    if 'top_key' in kwargs:269        top_key = kwargs['top_key']270    else:271        top_key = ''272    if 'subfield_key_list' in kwargs:273        subfield_key_list = kwargs['subfield_key_list']274    else:275        subfield_key_list = []276    if 'comment_char' in kwargs:277        comment_char = kwargs['comment_char']278    else:279        comment_char = ""280    if 'sep_char' in kwargs:281        sep_char = kwargs['sep_char']282    else:283        sep_char = "\t"284    columns_on_top = test_kwarg('columns_on_top',kwargs,[False, True])285        286    force_to_float = test_kwarg('force_to_float', kwargs, [True, False])287    interpret_lists = test_kwarg('interpret_lists', kwargs, [True, False])288    289    fp = open(filename, 'rU')290    the_list = fp.readlines()291    292    the_list = [x.rstrip("\n") for x in the_list]293    294    if (len(comment_char) > 0):295        found_first = False296        while not(found_first):297            if the_list[0].startswith(comment_char):298                the_list.pop(0)299            else:300                found_first = True301                302    if top_key == '':303        firstline = the_list[0].split(sep_char)304        key_index = 0305        top_key = firstline[0]306    else:307        firstline = the_list[0].split(sep_char)308        key_index = firstline.index(top_key)     309    if (len(subfield_key_list) > 0):310        valueindices = [firstline.index(subfield_key) for subfield_key in subfield_key_list]311    else:312        valueindices = [x for x in range(0, len(firstline)) if (x != key_index)]313        subfield_key_list = [firstline[x] for x in valueindices]314    the_list.pop(0)315    316    return_dict={}317    for the_line in the_list:318        if ((len(comment_char) == 0) | (not(the_line.startswith(comment_char)))):319            the_line = the_line.split(sep_char)320            return_dict[the_line[key_index]] = {}321            for index, subfield_key in enumerate(subfield_key_list):322                cur_value = the_line[valueindices[index]]323                if is_float_try(cur_value) & (force_to_float == True):324                    cur_value = float(cur_value)325                else:326                    if ((cur_value.startswith('"')) & (cur_value.endswith(('"')))):327                        # The double-quotes are sometimes inserted before328                        # and after long string/lists329                        # and aren't needed330                        cur_value = cur_value.lstrip('"').rstrip('"')331                    if interpret_lists:332                        if type(cur_value) != list:333                            if ((cur_value.startswith('[')) & (cur_value.endswith((']')))):334                                cur_value = string_to_list(cur_value, force_to_float = force_to_float)335                return_dict[the_line[key_index]][subfield_key] = cur_value336    if columns_on_top:337        organized_return_dict = {}338        for the_column_header in subfield_key_list:339            organized_return_dict[the_column_header] = {}340            for the_row_name in return_dict.keys():341                organized_return_dict[the_column_header][the_row_name] = return_dict[the_row_name][the_column_header]342            343    else:344        organized_return_dict = return_dict345            346    return organized_return_dict347def write_dict_to_textfile(the_filename, the_output_dict, **kwargs):348    """ Write a dict of dicts to a tab-delimited textfile table.349    Arguments:350     the_filename: file to write to351     the_output_dict: the dict to write352    kwargs:353     top_key: string to describe the top key / id in the table.354     subfields_on_top: [False (default), True]355      whether to write to flip the order356      so the subfields become the column headers in357      the table and the top levels keys become the358      row names.359    Returns:360     nothing, just writes to file361     362    """363    from copy import deepcopy364    subfields_on_top = test_kwarg('subfields_on_top',kwargs,[False, True])365    if 'top_key' in kwargs:366        top_key = kwargs['top_key']367    else:368        top_key = 'name'369    if not subfields_on_top:370        all_top_ids = the_output_dict.keys()371        all_subfield_ids = set([])372        for the_key in all_top_ids:373            all_subfield_ids.update(set(the_output_dict[the_key].keys()))374        all_subfield_ids = list(all_subfield_ids)375        all_subfield_ids.sort()376        all_top_ids.sort()377        the_original_dict = deepcopy(the_output_dict)378        the_output_dict = {}379        for the_new_top_key in all_subfield_ids:380            the_output_dict[the_new_top_key] = {}381            for the_new_subfield_key in all_top_ids:382                the_output_dict[the_new_top_key][the_new_subfield_key] = the_original_dict[the_new_subfield_key][the_new_top_key]383    # First we convert to a table to align384    # the columns385    # First scan through and get all the keys                386    all_entries = the_output_dict.keys()387    all_entries.sort()    388    col_names = set([])389    for cur_entry in the_output_dict.keys():390        col_names.update(set(the_output_dict[cur_entry].keys()))391    col_names = [x for x in col_names]392    col_names.sort()393    the_table = []394    the_table.append([])395    the_table[0].append(top_key)396    the_table[0].extend(col_names)397    for row_index, entry in enumerate(all_entries):398        the_table.append([])399        target_row=[]400        target_row.append(entry)401        for target_col_index, cur_col in enumerate(col_names):402            try:403                cur_value = the_output_dict[entry][cur_col]404            except:405                cur_value=''406            target_row.append(cur_value)407        the_table[row_index + 1] = target_row408    409    # Now write the table410    fp = file(the_filename, 'w')411    for row in the_table:412        for colindex, entry in enumerate(row):413            fp.writelines("%s" % entry)414            if colindex == (len(row)-1):415                fp.writelines("\n")416            else:417                fp.writelines("\t")        ...

CeleryTest.py

Source:CeleryTest.py

1# -*- coding: utf-8 -*-2from __future__ import print_function, absolute_import, division3import os4import sys5import unittest6import pickle7sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..', '..'))8from .TaskSpecTest import TaskSpecTest9from eufrates.specs import Celery, WorkflowSpec10from eufrates.operators import Attrib11from eufrates.serializer.dict import DictionarySerializer12from base64 import b64encode13class CeleryTest(TaskSpecTest):14    CORRELATE = Celery15    def create_instance(self):16        if 'testtask' in self.wf_spec.task_specs:17            del self.wf_spec.task_specs['testtask']18        return Celery(self.wf_spec,19                      'testtask', 'call.name',20                      call_args=[Attrib('the_attribute'), 1],21                      description='foo',22                      named_kw=[],23                      dict_kw={}24                      )25    def testTryFire(self):26        pass27    def testRetryFire(self):28        pass29    def testSerializationWithoutKwargs(self):30        new_wf_spec = WorkflowSpec()31        serializer = DictionarySerializer()32        nokw = Celery(self.wf_spec, 'testnokw', 'call.name',33                      call_args=[Attrib('the_attribute'), 1])34        data = nokw.serialize(serializer)35        nokw2 = Celery.deserialize(serializer, new_wf_spec, data)36        self.assertDictEqual(nokw.kwargs, nokw2.kwargs)37        kw = Celery(self.wf_spec, 'testkw', 'call.name',38                    call_args=[Attrib('the_attribute'), 1],39                    some_arg={"key": "value"})40        data = kw.serialize(serializer)41        kw2 = Celery.deserialize(serializer, new_wf_spec, data)42        self.assertDictEqual(kw.kwargs, kw2.kwargs)43        # Has kwargs, but they belong to TaskSpec44        kw_defined = Celery(self.wf_spec, 'testkwdef', 'call.name',45                            call_args=[Attrib('the_attribute'), 1],46                            some_ref=Attrib('value'),47                            defines={"key": "value"})48        data = kw_defined.serialize(serializer)49        kw_defined2 = Celery.deserialize(serializer, new_wf_spec, data)50        self.assertIsInstance(kw_defined2.kwargs['some_ref'], Attrib)51        args = [b64encode(pickle.dumps(v))52                for v in [Attrib('the_attribute'), 'ip', 'dc455016e2e04a469c01a866f11c0854']]53        data = {'R': b64encode(pickle.dumps('1'))}54        # Comes from live data. Bug not identified, but there we are...55        data = {'inputs': ['Wait:1'], 'lookahead': 2, 'description': '',56                'outputs': [], 'args': args,57                'manual': False,58                'data': data, 'locks': [], 'pre_assign': [],59                'call': 'call.x',60                'internal': False, 'post_assign': [], 'id': 8,61                'result_key': None, 'defines': data,62                'class': 'eufrates.specs.Celery.Celery',63                'name': 'RS1:1'}64        Celery.deserialize(serializer, new_wf_spec, data)65def suite():66    try:67        import celery68    except ImportError:69        print("WARNING: Celery not found, not all tests are running!")70        return lambda x: None71    else:72        return unittest.TestLoader().loadTestsFromTestCase(CeleryTest)73if __name__ == '__main__':...

orm.py

Source:orm.py

1import time2from datetime import datetime, date3from decimal import Decimal4from sqlalchemy import create_engine5from sqlalchemy.ext.declarative import declarative_base6from sqlalchemy.orm import sessionmaker7from sqlalchemy.orm.attributes import InstrumentedAttribute8from sqlalchemy.types import String9from config import config10_db_url = 'postgresql+psycopg2://{user}:{password}@{host}/{db}'.format(**config.db_info)11engine = create_engine(_db_url, echo=config.db_echo)12Base = declarative_base(bind=engine)13Session = sessionmaker(bind=engine)14class AlchemyMixin(object):15    def __setattr__(self, key, value):16        # å½ç» String ç±»ååæ®µèµå¼æ¶éå¶åç¬¦ä¸²çé¿åº¦, å¦ Column(String(20)) ä¸æé¿åªè½æ 20 ä¸ªåç¬¦.17        if isinstance(value, str):18            the_attribute = getattr(self.__class__, key, None)19            if isinstance(the_attribute, InstrumentedAttribute):20                # is a column21                if isinstance(the_attribute.property.columns[0].type, String):22                    max_length = the_attribute.property.columns[0].type.length23                    value = value[:max_length]24        super().__setattr__(key, value)25    @classmethod26    def get(cls, object_id, session):27        """28        Get object by object id, if not find, return None.29        """30        the_object = session.query(cls).filter(31            cls.id == object_id32        ).first()33        return the_object34    def to_dict(self, **kwargs):35        """36        å°ä¸ä¸ª SQLAlchemy çå¯¹è±¡ (row, declarative_base) è½¬ä¸º dict.37        å¦æ kwargs æ columns, å columns æ¯ææéè¦çé¡¹; è¥æ excluded, å excluded æ¯è¦æé¤çé¡¹. äºèä¸å¯å¹¶å.38        """39        d = {}40        columns = kwargs.get('columns')41        if columns:42            columns = [x.key for x in columns]43        else:44            # ä¸éè¦çé¡¹45            excluded = kwargs.get('excluded')46            columns = set(x.name for x in self.__table__.columns)47            if excluded:48                excluded = set(x.key for x in excluded)49                columns -= excluded50        for column in columns:51            value = getattr(self, column)52            if isinstance(value, datetime):53                value = int(time.mktime(value.timetuple()))54            elif isinstance(value, date):55                value = value.isoformat()56            elif isinstance(value, Decimal):57                value = str(value)58            d[column] = value59        return d60def print_create_table_sql(model):61    """62    æå°ä¸æ°æ®è¡¨çåå»ºè¯å¥, ä»¥ä¾¿æå¨åå»ºç...63    """64    # from sqlalchemy.schema import CreateTable65    # print('#### Create table SQL for model {}: ####'.format(model))66    # print(CreateTable(model.__table__).compile(engine))67    # print('#' * 20)68def create_table_if_not_exist(the_object):69    """70    å¦æéè¦çè¡¨ä¸åå¨, åå»ºå®71    """...

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