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How to use match_step method in Radish

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orientdb_query_execution.py

Source:orientdb_query_execution.py

1# Copyright 2018-present Kensho Technologies, LLC.2"""Workarounds for OrientDB scheduler issue that causes poor query planning for certain queries.3For purposes of query planning, the OrientDB query planner ignores "where:" clauses4that hit indexes but do not use the "=" operator. For example, "CONTAINS" can be used to check5that a field covered by an index is in a specified list of values, and can therefore be covered6by an index, but OrientDB will ignore this. When no equality ("=") checks on indexed columns7are present, OrientDB will generate a query plan that starts execution at the class with8lowest cardinality, which can lead to excessive numbers of scanned and discarded records.9Assuming the query planner creates a query plan where a location with CONTAINS is10the first in the execution order, the execution system will apply indexes11to speed up this operation. Therefore, it's sufficient to trick the query planner into12always creating such a query plan, even though it thinks indexes cannot be used in the query.13Valid query execution start points for the OrientDB query planner must satisfy the following:14    - Must not be "optional: true".15    - Must not have a "while:" clause nor follow a location that has one.16    - Must have a "class:" defined. This class is used for cardinality estimation, and to17      look for available indexes that may cover any "where:" clause that may be present.18The optimizations in this file improve performance by enabling execution start points according19to the following assumptions:20    1. Start points with "where:" clauses that reference only local fields (i.e. not tagged values21       from other query locations) are always better than start points without a "where:".22       This is because the filter will have to be applied one way or the other, so we might as well23       apply it early.24    2. If no such start points are available, we'd like to make available as many start points25       as possible, since we'd like OrientDB to start at the start point whose class has26       the lowest possible cardinality.27The process of applying the optimizations is as follows:28    - Exclude and ignore all query steps that are inside a fold, optional, or recursion scope,29      or have a "where:" clause that references a non-local (i.e. tagged) field.30    - Find all remaining query steps with "where:" clauses that reference only local fields.31    - If any are found, we guide our actions from assumption 1 above:32        - Ensure they have a defined "class:" -- i.e. the OrientDB scheduler will consider them33          valid start points.34        - Then, prune all other query steps (ones without such "where:" clauses) by removing their35          "class:" clause, making them invalid as query start points for OrientDB's scheduler.36    - If none are found, we guide our actions from assumption 2 above:37        - Ensure that all query points not inside fold, optional, or recursion scope contain38          a "class:" clause. That increases the number of available query start points,39          so OrientDB can choose the start point of lowest cardinality.40"""41from ..blocks import CoerceType, Filter, QueryRoot, Recurse, Traverse42from ..expressions import (43    BinaryComposition,44    ContextField,45    ContextFieldExistence,46    Literal,47    LocalField,48)49from ..helpers import get_only_element_from_collection50def _is_local_filter(filter_block):51    """Return True if the Filter block references no non-local fields, and False otherwise."""52    is_local_filter = True53    filter_predicate = filter_block.predicate54    def visitor_fn(expression):55        """Expression visitor function that looks for uses of non-local fields."""56        nonlocal is_local_filter57        non_local_expression_types = (ContextField, ContextFieldExistence)58        if isinstance(expression, non_local_expression_types):59            is_local_filter = False60        # Don't change the expression.61        return expression62    filter_predicate.visit_and_update(visitor_fn)63    return is_local_filter64def _classify_query_locations(match_query):65    """Classify query locations into three groups: preferred, eligible, ineligible.66    - Ineligible locations are ones that cannot be the starting point of query execution.67      These include locations within recursions, locations that are the target of68      an optional traversal, and locations with an associated "where:" clause with non-local filter.69    - Preferred locations are ones that are eligible to be the starting point, and also have70      an associated "where:" clause that references no non-local fields -- only local fields,71      literals, and variables.72    - Eligible locations are all locations that do not fall into either of these two categories.73    Args:74        match_query: MatchQuery object describing the query being analyzed for optimization75    Returns:76        tuple (preferred, eligible, ineligible) where each element is a set of Location objects.77        The three sets are disjoint.78    """79    preferred_locations = set()80    eligible_locations = set()81    ineligible_locations = set()82    # Any query must have at least one traversal with at least one step.83    # The first step in this traversal must be a QueryRoot.84    first_match_step = match_query.match_traversals[0][0]85    if not isinstance(first_match_step.root_block, QueryRoot):86        raise AssertionError(87            "First step of first traversal unexpectedly was not QueryRoot: "88            "{} {}".format(first_match_step, match_query)89        )90    # The first step in the first traversal cannot possibly be inside an optional, recursion,91    # or fold. Its location is always an eligible start location for a query.92    # We need to determine whether it is merely eligible, or actually a preferred location.93    if first_match_step.where_block is not None:94        if _is_local_filter(first_match_step.where_block):95            preferred_locations.add(first_match_step.as_block.location)96        else:97            # TODO(predrag): Fix once we have a proper fix for tag-and-filter in the same scope.98            #                Either the locally-scoped tag will have to generate a LocalField99            #                instead of a ContextField, or we'll have to rework the local filter100            #                detection code in this module.101            raise AssertionError(102                "The first step of the first traversal somehow had a non-local "103                "filter. This should not be possible, since there is nowhere "104                "for the tagged value to have come from. Values: {} {}".format(105                    first_match_step, match_query106                )107            )108    else:109        eligible_locations.add(first_match_step.as_block.location)110    # This loop will repeat the analysis of the first step of the first traversal.111    # QueryRoots other than the first are required to always be at a location whose status112    # (preferred / eligible / ineligible) is already known. Since we already processed113    # the first QueryRoot above, the rest of the loop can assume all QueryRoots are like that.114    for current_traversal in match_query.match_traversals:115        for match_step in current_traversal:116            current_step_location = match_step.as_block.location117            if isinstance(match_step.root_block, QueryRoot):118                already_encountered_location = any(119                    (120                        current_step_location in preferred_locations,121                        current_step_location in eligible_locations,122                        current_step_location in ineligible_locations,123                    )124                )125                if not already_encountered_location:126                    raise AssertionError(127                        "Unexpectedly encountered a location in QueryRoot whose "128                        "status has not been determined: {} {} {}".format(129                            current_step_location, match_step, match_query130                        )131                    )132                at_eligible_or_preferred_location = (133                    current_step_location in preferred_locations134                    or current_step_location in eligible_locations135                )136                # This location has already been encountered and processed.137                # Other than setting the "at_eligible_or_preferred_location" state for the sake of138                # the following MATCH steps, there is nothing further to be done.139                continue140            elif isinstance(match_step.root_block, Recurse):141                # All Recurse blocks cause locations within to be ineligible.142                at_eligible_or_preferred_location = False143            elif isinstance(match_step.root_block, Traverse):144                # Optional Traverse blocks cause locations within to be ineligible.145                # Non-optional Traverse blocks do not change the eligibility of locations within:146                # if the pre-Traverse location was eligible, so will the location within,147                # and if it was not eligible, neither will the location within.148                if match_step.root_block.optional:149                    at_eligible_or_preferred_location = False150            else:151                raise AssertionError(152                    "Unreachable condition reached: {} {} {}".format(153                        match_step.root_block, match_step, match_query154                    )155                )156            if not at_eligible_or_preferred_location:157                ineligible_locations.add(current_step_location)158            elif match_step.where_block is not None:159                if _is_local_filter(match_step.where_block):160                    # This location has a local filter, and is not otherwise ineligible (it's not161                    # in a recursion etc.). Therefore, it's a preferred query start location.162                    preferred_locations.add(current_step_location)163                else:164                    # Locations with non-local filters are never eligible locations, since they165                    # depend on another location being executed before them.166                    ineligible_locations.add(current_step_location)167            else:168                # No local filtering (i.e. not preferred), but also not ineligible. Eligible it is.169                eligible_locations.add(current_step_location)170    return preferred_locations, eligible_locations, ineligible_locations171def _calculate_type_bound_at_step(match_step):172    """Return the GraphQL type bound at the given step, or None if no bound is given."""173    current_type_bounds = []174    if isinstance(match_step.root_block, QueryRoot):175        # The QueryRoot start class is a type bound.176        current_type_bounds.extend(match_step.root_block.start_class)177    if match_step.coerce_type_block is not None:178        # The CoerceType target class is also a type bound.179        current_type_bounds.extend(match_step.coerce_type_block.target_class)180    if current_type_bounds:181        # A type bound exists. Assert that there is exactly one bound, defined in precisely one way.182        return get_only_element_from_collection(current_type_bounds)183    else:184        # No type bound exists at this MATCH step.185        return None186def _assert_type_bounds_are_not_conflicting(187    current_type_bound, previous_type_bound, location, match_query188):189    """Ensure that the two bounds either are an exact match, or one of them is None."""190    if all(191        (192            current_type_bound is not None,193            previous_type_bound is not None,194            current_type_bound != previous_type_bound,195        )196    ):197        raise AssertionError(198            "Conflicting type bounds calculated at location {}: {} vs {} "199            "for query {}".format(location, previous_type_bound, current_type_bound, match_query)200        )201def _expose_only_preferred_locations(202    match_query, location_types, coerced_locations, preferred_locations, eligible_locations203):204    """Return a MATCH query where only preferred locations are valid as query start locations."""205    preferred_location_types = dict()206    eligible_location_types = dict()207    new_match_traversals = []208    for current_traversal in match_query.match_traversals:209        new_traversal = []210        for match_step in current_traversal:211            new_step = match_step212            current_step_location = match_step.as_block.location213            if current_step_location in preferred_locations:214                # This location is preferred. We have to make sure that at least one occurrence215                # of this location in the MATCH query has an associated "class:" clause,216                # which would be generated by a type bound at the corresponding MATCH step.217                current_type_bound = _calculate_type_bound_at_step(match_step)218                previous_type_bound = preferred_location_types.get(current_step_location, None)219                if previous_type_bound is not None:220                    # The location is already valid. If so, make sure that this step either does221                    # not have any type bounds (e.g. via QueryRoot or CoerceType blocks),222                    # or has type bounds that match the previously-decided type bound.223                    _assert_type_bounds_are_not_conflicting(224                        current_type_bound, previous_type_bound, current_step_location, match_query225                    )226                else:227                    # The location is not yet known to be valid. If it does not have228                    # a type bound in this MATCH step, add a type coercion to the type229                    # registered in "location_types".230                    if current_type_bound is None:231                        current_type_bound = location_types[current_step_location].name232                        new_step = match_step._replace(233                            coerce_type_block=CoerceType({current_type_bound})234                        )235                    preferred_location_types[current_step_location] = current_type_bound236            elif current_step_location in eligible_locations:237                # This location is eligible, but not preferred. We have not make sure238                # none of the MATCH steps with this location have type bounds, and therefore239                # will not produce a corresponding "class:" clause in the resulting MATCH query.240                current_type_bound = _calculate_type_bound_at_step(match_step)241                previous_type_bound = eligible_location_types.get(current_step_location, None)242                if current_type_bound is not None:243                    # There is a type bound here that we need to neutralize.244                    _assert_type_bounds_are_not_conflicting(245                        current_type_bound, previous_type_bound, current_step_location, match_query246                    )247                    # Record the deduced type bound, so that if we encounter this location again,248                    # we ensure that we again infer the same type bound.249                    eligible_location_types[current_step_location] = current_type_bound250                    # Remove blocks that would emit a "class:" clause251                    if isinstance(match_step.root_block, QueryRoot):252                        new_root_block = None253                    else:254                        # The root_block can be a QueryRoot, Traverse, Recurse or Backtrack.255                        new_root_block = match_step.root_block256                    new_coerce_type_block = None257                    new_where_block = match_step.where_block258                    # If needed, add a type bound that emits an INSTANCEOF in the "where:" clause259                    if previous_type_bound is None and current_type_bound is not None:260                        instanceof_predicate = BinaryComposition(261                            "INSTANCEOF", LocalField("@this", None), Literal(current_type_bound)262                        )263                        if match_step.where_block:264                            # TODO(bojanserafimov): This branch needs test coverage265                            new_where_block = Filter(266                                BinaryComposition(267                                    "&&", instanceof_predicate, match_step.where_block.predicate268                                )269                            )270                        else:271                            new_where_block = Filter(instanceof_predicate)272                    new_step = match_step._replace(273                        root_block=new_root_block,274                        coerce_type_block=new_coerce_type_block,275                        where_block=new_where_block,276                    )277            else:278                # This location is neither preferred nor eligible.279                # No action is necessary at this location.280                pass281            new_traversal.append(new_step)282        new_match_traversals.append(new_traversal)283    return match_query._replace(match_traversals=new_match_traversals)284def _expose_all_eligible_locations(match_query, location_types, eligible_locations):285    """Return a MATCH query where all eligible locations are valid as query start locations."""286    eligible_location_types = dict()287    new_match_traversals = []288    for current_traversal in match_query.match_traversals:289        new_traversal = []290        for match_step in current_traversal:291            new_step = match_step292            current_step_location = match_step.as_block.location293            if current_step_location in eligible_locations:294                # This location is eligible. We need to make sure it has an associated type bound,295                # so that it produces a "class:" clause that will make it a valid query start296                # location. It either already has such a type bound, or we can use the type297                # implied by the GraphQL query structure to add one.298                current_type_bound = _calculate_type_bound_at_step(match_step)299                previous_type_bound = eligible_location_types.get(current_step_location, None)300                if current_type_bound is None:301                    current_type_bound = location_types[current_step_location].name302                    new_coerce_type_block = CoerceType({current_type_bound})303                    new_step = match_step._replace(coerce_type_block=new_coerce_type_block)304                else:305                    # There is a type bound here. We simply ensure that the bound is not conflicting306                    # with any other type bound at a different MATCH step with the same location.307                    _assert_type_bounds_are_not_conflicting(308                        current_type_bound, previous_type_bound, current_step_location, match_query309                    )310                # Record the deduced type bound, so that if we encounter this location again,311                # we ensure that we again infer the same type bound.312                eligible_location_types[current_step_location] = current_type_bound313            else:314                # This function may only be called if there are no preferred locations. Since this315                # location cannot be preferred, and is not eligible, it must be ineligible.316                # No action is necessary in this case.317                pass318            new_traversal.append(new_step)319        new_match_traversals.append(new_traversal)320    return match_query._replace(match_traversals=new_match_traversals)321def expose_ideal_query_execution_start_points(322    compound_match_query, location_types, coerced_locations323):324    """Ensure that OrientDB only considers desirable query start points in query planning."""325    new_queries = []326    for match_query in compound_match_query.match_queries:327        location_classification = _classify_query_locations(match_query)328        preferred_locations, eligible_locations, _ = location_classification329        if preferred_locations:330            # Convert all eligible locations into non-eligible ones, by removing331            # their "class:" clause. The "class:" clause is provided either by having332            # a QueryRoot block or a CoerceType block in the MatchStep corresponding333            # to the location. We remove it by converting the class check into334            # an "INSTANCEOF" Filter block, which OrientDB is unable to optimize away.335            new_query = _expose_only_preferred_locations(336                match_query,337                location_types,338                coerced_locations,339                preferred_locations,340                eligible_locations,341            )342        elif eligible_locations:343            # Make sure that all eligible locations have a "class:" clause by adding344            # a CoerceType block that is a no-op as guaranteed by the schema. This merely345            # ensures that OrientDB is able to use each of these locations as a query start point,346            # and will choose the one whose class is of lowest cardinality.347            new_query = _expose_all_eligible_locations(348                match_query, location_types, eligible_locations349            )350        else:351            raise AssertionError(352                "This query has no preferred or eligible query start locations. "353                "This is almost certainly a bug: {}".format(match_query)354            )355        new_queries.append(new_query)...

emit_match.py

Source:emit_match.py

1"""Convert lowered IR basic blocks to MATCH query strings."""2from collections import deque3import six4from .blocks import Filter, MarkLocation, QueryRoot, Recurse, Traverse5from .expressions import TrueLiteral6from .helpers import get_only_element_from_collection, validate_safe_string7def _get_vertex_location_name(location):8	"""Get the location name from a location that is expected to point to a vertex."""9	mark_name, field_name = location.get_location_name()10	if field_name is not None:11		raise AssertionError(u"Location unexpectedly pointed to a field: {}".format(location))12	return mark_name13def _first_step_to_match(match_step):14	"""Transform the very first MATCH step into a MATCH query string."""15	parts = []16	if match_step.root_block is not None:17		if not isinstance(match_step.root_block, QueryRoot):18			raise AssertionError(u"Expected None or QueryRoot root block, received: " u"{} {}".format(match_step.root_block, match_step))19		match_step.root_block.validate()20		start_class = get_only_element_from_collection(match_step.root_block.start_class)21		parts.append(u"class: %s" % (start_class,))22	if match_step.coerce_type_block is not None:23		raise AssertionError(u"Invalid MATCH step: {}".format(match_step))24	if match_step.where_block:25		match_step.where_block.validate()26		parts.append(u"where: (%s)" % (match_step.where_block.predicate.to_match(),))27	if match_step.as_block is None:28		raise AssertionError(u"Found a MATCH step without a corresponding Location. " u"This should never happen: {}".format(match_step))29	else:30		match_step.as_block.validate()31		parts.append(u"as: %s" % (_get_vertex_location_name(match_step.as_block.location),))32	return u"{{ %s }}" % (u", ".join(parts),)33def _subsequent_step_to_match(match_step):34	"""Transform any subsequent (non-first) MATCH step into a MATCH query string."""35	if not isinstance(match_step.root_block, (Traverse, Recurse)):36		raise AssertionError(u"Expected Traverse root block, received: " u"{} {}".format(match_step.root_block, match_step))37	is_recursing = isinstance(match_step.root_block, Recurse)38	match_step.root_block.validate()39	traversal_command = u".%s('%s')" % (match_step.root_block.direction, match_step.root_block.edge_name)40	parts = []41	if match_step.coerce_type_block:42		coerce_type_set = match_step.coerce_type_block.target_class43		if len(coerce_type_set) != 1:44			raise AssertionError(u"Found MATCH type coercion block with more than one target class:" u" {} {}".format(coerce_type_set, match_step))45		coerce_type_target = list(coerce_type_set)[0]46		parts.append(u"class: %s" % (coerce_type_target,))47	if is_recursing:48		parts.append(u"while: ($depth < %d)" % (match_step.root_block.depth,))49	if match_step.where_block:50		match_step.where_block.validate()51		parts.append(u"where: (%s)" % (match_step.where_block.predicate.to_match(),))52	if not is_recursing and match_step.root_block.optional:53		parts.append(u"optional: true")54	if match_step.as_block:55		match_step.as_block.validate()56		parts.append(u"as: %s" % (_get_vertex_location_name(match_step.as_block.location),))57	return u"%s {{ %s }}" % (traversal_command, u", ".join(parts))58def _represent_match_traversal(match_traversal):59	"""Emit MATCH query code for an entire MATCH traversal sequence."""60	output = []61	output.append(_first_step_to_match(match_traversal[0]))62	for step in match_traversal[1:]:63		output.append(_subsequent_step_to_match(step))64	return u"".join(output)65def _represent_fold(fold_location, fold_ir_blocks):66	"""Emit a LET clause corresponding to the IR blocks for a @fold scope."""67	start_let_template = u"$%(mark_name)s = %(base_location)s"68	traverse_edge_template = u'.%(direction)s("%(edge_name)s")'69	base_template = start_let_template + traverse_edge_template70	edge_direction, edge_name = fold_location.get_first_folded_edge()71	mark_name, _ = fold_location.get_location_name()72	base_location_name, _ = fold_location.base_location.get_location_name()73	validate_safe_string(mark_name)74	validate_safe_string(base_location_name)75	validate_safe_string(edge_direction)76	validate_safe_string(edge_name)77	template_data = {"mark_name": mark_name, "base_location": base_location_name, "direction": edge_direction, "edge_name": edge_name}78	final_string = base_template % template_data79	for block in fold_ir_blocks:80		if isinstance(block, Filter):81			final_string += u"[" + block.predicate.to_match() + u"]"82		elif isinstance(block, Traverse):83			template_data = {"direction": block.direction, "edge_name": block.edge_name}84			final_string += traverse_edge_template % template_data85		elif isinstance(block, MarkLocation):86			pass87		else:88			raise AssertionError(u"Found an unexpected IR block in the folded IR blocks: " u"{} {} {}".format(type(block), block, fold_ir_blocks))89	final_string += ".asList()"90	return final_string91def _construct_output_to_match(output_block):92	"""Transform a ConstructResult block into a MATCH query string."""93	output_block.validate()94	selections = (u"%s AS `%s`" % (output_block.fields[key].to_match(), key) for key in sorted(output_block.fields.keys()))95	return u"SELECT %s FROM" % (u", ".join(selections),)96def _construct_where_to_match(where_block):97	"""Transform a Filter block into a MATCH query string."""98	if where_block.predicate == TrueLiteral:99		raise AssertionError(u"Received WHERE block with TrueLiteral predicate: {}".format(where_block))100	return u"WHERE " + where_block.predicate.to_match()101def emit_code_from_single_match_query(match_query):102	"""Return a MATCH query string from a list of IR blocks."""103	query_data = deque([u"MATCH "])104	if not match_query.match_traversals:105		raise AssertionError(u"Unexpected falsy value for match_query.match_traversals received: " u"{} {}".format(match_query.match_traversals, match_query))106	match_traversal_data = [_represent_match_traversal(x) for x in match_query.match_traversals]107	query_data.append(match_traversal_data[0])108	for traversal_data in match_traversal_data[1:]:109		query_data.append(u", ")110		query_data.append(traversal_data)111	query_data.appendleft(u" (")112	query_data.append(u"RETURN $matches)")113	fold_data = sorted([_represent_fold(fold_location, fold_ir_blocks) for fold_location, fold_ir_blocks in six.iteritems(match_query.folds)])114	if fold_data:115		query_data.append(u" LET ")116		query_data.append(fold_data[0])117		for fold_clause in fold_data[1:]:118			query_data.append(u", ")119			query_data.append(fold_clause)120	query_data.appendleft(_construct_output_to_match(match_query.output_block))121	if match_query.where_block is not None:122		query_data.append(_construct_where_to_match(match_query.where_block))123	return u" ".join(query_data)124def emit_code_from_multiple_match_queries(match_queries):125	"""Return a MATCH query string from a list of MatchQuery namedtuples."""126	optional_variable_base_name = "$optional__"127	union_variable_name = "$result"128	query_data = deque([u"SELECT EXPAND(", union_variable_name, u")", u" LET "])129	optional_variables = []130	sub_queries = [emit_code_from_single_match_query(match_query) for match_query in match_queries]131	for (i, sub_query) in enumerate(sub_queries):132		variable_name = optional_variable_base_name + str(i)133		variable_assignment = variable_name + u" = ("134		sub_query_end = u"),"135		query_data.append(variable_assignment)136		query_data.append(sub_query)137		query_data.append(sub_query_end)138		optional_variables.append(variable_name)139	query_data.append(union_variable_name)140	query_data.append(u" = UNIONALL(")141	query_data.append(u", ".join(optional_variables))142	query_data.append(u")")143	return u" ".join(query_data)144def emit_code_from_ir(schema_info, compound_match_query):145	"""Return a MATCH query string from a CompoundMatchQuery."""146	match_queries = compound_match_query.match_queries147	if len(match_queries) == 1:148		query_string = emit_code_from_single_match_query(match_queries[0])149	elif len(match_queries) > 1:150		query_string = emit_code_from_multiple_match_queries(match_queries)151	else:152		raise AssertionError(u"Received CompoundMatchQuery with an empty list of MatchQueries: " u"{}".format(match_queries))...

main_tournament_results.py

Source:main_tournament_results.py

1import pandas as pd2from functions import get_soup3import re4# Get tournament days5def get_tournament_days(step):6    base_url_hit = 'https://bwf.tournamentsoftware.com/sport/matches.aspx?id='7    url_hit = base_url_hit + step8    soup_html = get_soup(url_hit)9    10    t_days = soup_html.find('ul', attrs={'class':'tournamentcalendar'})11    test = t_days.find_all('li')12    13    base_hit = 'https://bwf.tournamentsoftware.com'14    url_hit_tourney_days = []15    for i in test:16        url_hit_tourney_days.append(base_hit+re.search('href="(.*)"><span', str(i)).group(1))17    return url_hit_tourney_days18def get_game_results(soup_tournament_day, game_scores):19    match_table = soup_tournament_day.find('table', attrs={'class':'ruler matches'})20    match_table = match_table.find_all('tr')21    22    for step_match in match_table:23#    step_match = match_table[8]24        match_type = len(step_match.find_all('tr'))25        if match_type > 0:26            match_det = step_match27            match_step = match_det.find_all('tr')28            if match_type == 2:29                match_type = 'singles'30                p1a = match_step[0].text.split('[')[0].replace('\n', '')31                p2a = match_step[1].text.split('] ')[1].replace('\n', '')32                p1b = 'none'33                p2b = 'none'34                match_duration = match_det.find_all('td')[13].text35    #            a = match_det.find_all('td')[10].text.split(' ')36            elif match_type == 4:37                match_type = 'doubles'38                p1a = match_step[0].text.split('[')[0].replace('\n', '')39                p1b = match_step[1].text.split('[')[0].replace('\n', '')40                p2a = match_step[2].text.split('] ')[1].replace('\n', '')41                p2b = match_step[3].text.split('] ')[1].replace('\n', '')42                match_duration = match_det.find_all('td')[17].text43    #            a = match_det.find_all('td')[14].text.split(' ')44            if match_det.find('span', attrs={'class':'score'}) is None:45                a = 'Walkover'46            else:47                a = match_det.find('span', attrs={'class':'score'}).text48            if ((a == 'Walkover') | (a == 'No match')):49                if 'strong' in str(match_step[0]):50                    scores = ['Walkover Win', 'Walkover Loss']51                else:52                    scores = ['Walkover Loss', 'Walkover Win']53                build_list = {54                        'p1a': p1a,55                        'p1b': p1b,56                        'p2a': p2a,57                        'p2b': p2b,58                        'p1_scores': scores[0],59                        'p2_scores': scores[1],60                        'tournament_id': tournament_id,61                        'date': tournament_date,62                        'duration': match_duration,63                        'type': match_type64                        }65                game_scores.append(build_list)66            else:67                a = re.sub("\s+", " ", a.strip())68                a = a.split(' ')69                for i in a:70                    if i == 'Retired':71                        if 'strong' in str(match_step[0]):72                            scores = ['Walkover Win', 'Walkover Loss']73                        else:74                            scores = ['Walkover Loss', 'Walkover Win']75                    else:76                        scores = i.split('-')77                    build_list = {78                            'p1a': p1a,79                            'p1b': p1b,80                            'p2a': p2a,81                            'p2b': p2b,82                            'p1_scores': scores[0],83                            'p2_scores': scores[1],84                            'tournament_id': tournament_id,85                            'date': tournament_date,86                            'duration': match_duration,87                            'type': match_type88                            }89                    game_scores.append(build_list)90    return game_scores91tournament_list = pd.read_csv('data/00_source/tournament_list.csv', sep="|")92skip_list = [14, 21, 32, 52, 54, 57, 61, 63, 67, 69, 88, 93, 94, 95, 96, 116, 121, 122, 126, 129, 136, 138, 149, 155, 171, 177, 178, 179, 180, 183, 188, 194, 198, 200, 201, 204, 231, 233, 237, 241, 268, 270, 271, 282, 285, 293, 298, 324, 325, 340, 343, 362, 363, 367, 371, 375, 377, 383, 387, 405, 425, 430, 437, 453, 461, 465, 471, 474, 476, 479, 491, 492, 503, 518, 520, 522, 526, 533, 534, 537, 539, 547, 559, 570, 584, 590, 594, 600, 613, 623, 624, 647, 657, 658, 659, 685, 686, 702, 723, 760, 764, 807, 815, 818, 823, 831, 835, 836, 849, 850, 858, 875, 876, 878, 881, 890, 891, 898, 936, 942, 947, 948, 972, 983, 1036, 1069, 1071, 1083, 1085, 1091, 1108, 1109, 1124, 1153, 1172, 1175, 1228, 1229, 1230, 1231, 1232, ]93for step in range(max(skip_list), len(tournament_list)):94#step = 3295    if step not in skip_list:96    #        print(step)97        tournament_id = tournament_list['tournament_id'][step]98        print('{}: {}'.format(step, tournament_id))99        game_scores = []100        url_hit_tourney_days = get_tournament_days(tournament_id)101        102        test_t = get_soup(url_hit_tourney_days[0])103        104        if 'printonly flag' in str(test_t):105        106            for tourney_day in range(0, len(url_hit_tourney_days)):107                hit_tourney = url_hit_tourney_days[tourney_day]108                tournament_date = hit_tourney.split(';d=')[1]109                soup_tournament_day = get_soup(hit_tourney)110                game_scores = get_game_results(soup_tournament_day, game_scores)111            112            game_scores_df = pd.DataFrame(game_scores)  113            filename = "data/00_source/match_results_{}.csv".format(tournament_id)114            game_scores_df.to_csv(filename, index=False, sep='|', header=True)115        else:116            skip_list.append(step)...

eval_pprint.py

Source:eval_pprint.py

1#!/usr/bin/env python2from __future__ import print_function3import json4import copy5import sys6import argparse7import re8import numpy as np9basedir = "tmp_data/evaluation"10def parse_args():11    desc = 'Find highest and worse performing clusters'12    parser = argparse.ArgumentParser(description=desc)13    parser.add_argument(14        'k', type=str, default='600',15        help='Number of K to check or a bash-style range (start..end[..step])' \16        ' e.g., 100..1000..10, meaning 100 through 1000 k, with a step of 10.' \17        ' Note that step is optional and will default to 1.'18    )19    parser.add_argument(20        '--output', type=str, default='all',21        help='Output type: all or combined'22    )23    args = parser.parse_args()24    return args25def parse_range(range_str):26    if '..' not in range_str:27        return [int(range_str)]28    match_step = re.match('([0-9]+)\.\.([0-9]+)\.\.([0-9]+)', range_str)29    match_range = re.match('([0-9]+)\.\.([0-9]+)', range_str)30    if not match_range and not match_step:31        raise ValueError('Invalid range supplied %s' % range_str)32    start_k = None33    end_k = None34    step = 135    if match_step:36        start_k, end_k, step = match_step.groups()37    elif match_range:38        start_k, end_k = match_range.groups()39    return range(int(start_k), int(end_k), int(step))40def log(msg):41    sys.stderr.write("%s\n" % msg)42def load_object(filename, postprocess=json.loads):43    log("Loading object %s" % filename)44    with open(filename, 'r') as f:45        return postprocess(f.read())46def process_csv(csv_string):47    csv_lines = csv_string.strip().split('\n')48    lines = filter( lambda x: x, csv_string.split('\n'))49    data = {}50    for line in lines:51        cluster, words = line.split(',')52        data[cluster.strip()] = filter(lambda x: x, words.strip().split())53    return data54if __name__ == "__main__":55    args = parse_args()56    k_range = parse_range(args.k)57    models = [58        "fasttext_spherical",59        "word2vec_spherical",60        "fasttext_kmeans",61        "word2vec_kmeans",62        "lda_lda"63    ]64    template = {65        "eval": "%(base)s/fulltext_%(model)s_%(k)s_clusters_evaluation.json",66        "clust": "tmp_data/fulltext_%(model)s_%(k)s_clusters/clusters.csv"67    }68    cluster_scores = []69    for k in k_range:70        for model in models:71            filename_args = {72                "k": k,73                "base": basedir,74                "model": model75            }76            evalfile = template["eval"] % (filename_args)77            clustfile = template["clust"] % (filename_args)78            evals = load_object(evalfile)79            clusters = load_object(clustfile, postprocess=process_csv)80            for cluster in evals.keys():81                score = evals[cluster]['mean']82                cluster_labels = ", ".join(clusters[cluster])83                # print('cluster_eval %s' % cluster_eval)84                # print('cluster_labels %s' % cluster_labels)85                score_name = '%s-%s' % (model, k)86                if np.isnan(score):87                    continue88                cluster_scores.append([score, score_name, cluster_labels])89    seen_identifiers = {}90    for score, cluster_name, labels in sorted(cluster_scores):91        if args.output == 'all':92            print('%s %s %s' % (score, cluster_name, labels))93            continue94        unique_identifier = '%s %s' % (score, labels)95        if unique_identifier not in seen_identifiers:96            seen_identifiers[unique_identifier] = []97        seen_identifiers[unique_identifier].append(cluster_name)98    if args.output == 'combined':99        for identifier in sorted(seen_identifiers.keys()):100            score, labels = identifier.split(' ', 1)101            cluster_names = seen_identifiers[identifier]...

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