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How to use diff_queries method in dbt-osmosis

Best Python code snippet using dbt-osmosis_python

diff.py

Source:diff.py

...5from dbt.adapters.base.relation import BaseRelation6from git import Repo7from dbt_osmosis.core.log_controller import logger8from dbt_osmosis.core.osmosis import DbtProject9def build_diff_queries(model: str, runner: DbtProject) -> Tuple[str, str]:10    """Leverage git to build two temporary tables for diffing the results of a query throughout a change"""11    # Resolve git node12    node = runner.get_ref_node(model)13    dbt_path = Path(node.root_path)14    repo = Repo(dbt_path, search_parent_directories=True)15    t = next(Path(repo.working_dir).rglob(node.original_file_path)).relative_to(repo.working_dir)16    sha = repo.head.object.hexsha17    target = repo.head.object.tree[str(t)]18    # Create original node19    git_node_name = "z_" + sha[-7:]20    original_node = runner.get_server_node(target.data_stream.read().decode("utf-8"), git_node_name)21    # Alias changed node22    changed_node = node23    # Compile models24    original_node = runner.compile_node(original_node)25    changed_node = runner.compile_node(changed_node)26    return original_node.compiled_sql, changed_node.compiled_sql27def build_diff_tables(model: str, runner: DbtProject) -> Tuple[BaseRelation, BaseRelation]:28    """Leverage git to build two temporary tables for diffing the results of a query throughout a change"""29    # Resolve git node30    node = runner.get_ref_node(model)31    dbt_path = Path(node.root_path)32    repo = Repo(dbt_path, search_parent_directories=True)33    t = next(Path(repo.working_dir).rglob(node.original_file_path)).relative_to(repo.working_dir)34    sha = repo.head.object.hexsha35    target = repo.head.object.tree[str(t)]36    # Create original node37    git_node_name = "z_" + sha[-7:]38    original_node = runner.get_server_node(target.data_stream.read().decode("utf-8"), git_node_name)39    # Alias changed node40    changed_node = node41    # Compile models42    original_node = runner.compile_node(original_node).node43    changed_node = runner.compile_node(changed_node).node44    # Lookup and resolve original ref based on git sha45    git_node_parts = original_node.database, "dbt_diff", git_node_name46    ref_A, did_exist = runner.get_or_create_relation(*git_node_parts)47    if not did_exist:48        logger().info("Creating new relation for %s", ref_A)49        with runner.adapter.connection_named("dbt-osmosis"):50            runner.execute_macro(51                "create_schema",52                kwargs={"relation": ref_A},53            )54            runner.execute_macro(55                "create_table_as",56                kwargs={57                    "sql": original_node.compiled_sql,58                    "relation": ref_A,59                    "temporary": True,60                },61                run_compiled_sql=True,62            )63    # Resolve modified fake ref based on hash of it compiled SQL64    temp_node_name = "z_" + hashlib.md5(changed_node.compiled_sql.encode("utf-8")).hexdigest()[-7:]65    git_node_parts = original_node.database, "dbt_diff", temp_node_name66    ref_B, did_exist = runner.get_or_create_relation(*git_node_parts)67    if not did_exist:68        ref_B = runner.adapter.Relation.create(*git_node_parts)69        logger().info("Creating new relation for %s", ref_B)70        with runner.adapter.connection_named("dbt-osmosis"):71            runner.execute_macro(72                "create_schema",73                kwargs={"relation": ref_B},74            )75            runner.execute_macro(76                "create_table_as",77                kwargs={78                    "sql": original_node.compiled_sql,79                    "relation": ref_B,80                    "temporary": True,81                },82                run_compiled_sql=True,83            )84    return ref_A, ref_B85def diff_tables(86    ref_A: BaseRelation,87    ref_B: BaseRelation,88    pk: str,89    runner: DbtProject,90    aggregate: bool = True,91) -> agate.Table:92    logger().info("Running diff")93    _, table = runner.adapter_execute(94        runner.execute_macro(95            "_dbt_osmosis_compare_relations_agg" if aggregate else "_dbt_osmosis_compare_relations",96            kwargs={97                "a_relation": ref_A,98                "b_relation": ref_B,99                "primary_key": pk,100            },101        ),102        auto_begin=True,103        fetch=True,104    )105    return table106def diff_queries(107    sql_A: str, sql_B: str, pk: str, runner: DbtProject, aggregate: bool = True108) -> agate.Table:109    logger().info("Running diff")110    _, table = runner.adapter_execute(111        runner.execute_macro(112            "_dbt_osmosis_compare_queries_agg" if aggregate else "_dbt_osmosis_compare_queries",113            kwargs={114                "a_query": sql_A,115                "b_query": sql_B,116                "primary_key": pk,117            },118        ),119        auto_begin=True,120        fetch=True,121    )122    return table123def diff_and_print_to_console(124    model: str,125    pk: str,126    runner: DbtProject,127    make_temp_tables: bool = False,128    agg: bool = True,129    output: str = "table",130) -> None:131    """132    Compare two tables and print the results to the console133    """134    if make_temp_tables:135        table = diff_tables(*build_diff_tables(model, runner), pk, runner, agg)136    else:137        table = diff_queries(*build_diff_queries(model, runner), pk, runner, agg)138    print("")139    output = output.lower()140    if output == "table":141        table.print_table()142    elif output in ("chart", "bar"):143        if not agg:144            logger().warn(145                "Cannot render output format chart with --no-agg option, defaulting to table"146            )147            table.print_table()148        else:149            _table = table.compute(150                [151                    (...

search.py

Source:search.py

1import path  # noqa: F4012from sys import argv3from elasticsearch import Elasticsearch4from math import log5import pandas as pd6# Best baseline thusfar7# from .rerank_simple_slop_search import \8#    rerank_slop_search_remaining_lines_max_snippet_at_59from vmware.search.compound_search import with_best_compounds_at_5_only_phrase_search10def damage(results1, results2, at=10):11    """ How "damaging" could the change from results1 -> results2 be?12        (results1, results2 are an array of document identifiers)13        For each result in result1,14            Is the result in result2[:at]15                If so, how far has it moved?16            If not,17                Consider it a move of at+118            damage += discount(idx) * moveDist19                """20    def discount(idx):21        return 1.0 / log(idx + 2)22    idx = 023    dmg = 0.024    if len(results1) < at:25        at = len(results1)26    for result in results1[:at]:27        movedToIdx = at + 1  # out of the window28        if result in results2:29            movedToIdx = results2.index(result)30        moveDist = abs(movedToIdx - idx)31        dmg += discount(idx) * moveDist32        idx += 133    return dmg34def search(query,35           strategy=with_best_compounds_at_5_only_phrase_search):36    print(query)37    es = Elasticsearch('http://localhost:9200', timeout=30, max_retries=10,38                       retry_on_status=True, retry_on_timeout=True)39    hits = strategy(es, query=query)40    for hit in hits:41        print("**********************************")42        print(hit['_source']['title'] if 'title' in hit['_source'] else '',43              '||',44              hit['_source']['first_line'])45        print(f"MAX SIM {hit['_source']['max_sim']} | SCORE {hit['_score']}")46        print("----------------------------------")47def submission(baseline=with_best_compounds_at_5_only_phrase_search,48               test=with_best_compounds_at_5_only_phrase_search,49               verbose=False):50    """Search all test queries to generate a submission."""51    queries = pd.read_csv('data/test.csv')52    all_results = []53    es = Elasticsearch('http://localhost:9200', timeout=30, max_retries=10,54                       retry_on_status=True, retry_on_timeout=True)55    for query in queries.to_dict(orient='records'):56        results_control = baseline(es, query=query['Query'])57        results_test = test(es, query=query['Query'])58        delta_damage = damage([r['_id'] for r in results_control],59                              [r['_id'] for r in results_test])60        if verbose:61            print(query['Query'])62            print(f"DAMAGE: {delta_damage}")63            print("----------------------------------")64        for rank, (result_control, result_test) in enumerate(zip(results_control, results_test)):65            source_control = result_control['_source']66            source_test = result_test['_source']67            source_test['rank'] = rank68            source_test['score_test'] = result_test['_score']69            source_test['score_control'] = result_control['_score']70            source_test['damage'] = delta_damage71            source_test['DocumentId_test'] = source_test['id']72            source_test['DocumentId'] = source_test['id']73            source_test['DocumentId_control'] = source_control['id']74            source_test['splainer_test'] = source_test['splainer']75            source_test['splainer_control'] = source_control['splainer']76            source_test['first_line_control'] = source_control['first_line']77            source_test['first_line_test'] = source_test['first_line']78            source_test['raw_text_control'] = source_control['raw_text']79            source_test['QueryId'] = query['QueryId']80            all_results.append(source_test)81    all_results = pd.DataFrame(all_results)82    all_results = queries.merge(all_results, how='left', on='QueryId')\83        .sort_values(['QueryId', 'rank'])84    write_submission(all_results, test.__name__)85    return all_results86def write_submission(all_results, name):87    from time import time88    timestamp = str(time()).replace('.', '')89    fname = f'data/{name}_turnbull_{timestamp}.csv'90    print("Writing To: ", fname)91    all_results[['QueryId', 'DocumentId']].to_csv(fname, index=False)92def diff_results(all_results):93    diff_queries = all_results[all_results['damage'] > 0][['Query', 'damage',94                                                           'first_line_control', 'first_line',95                                                           'splainer_test', 'splainer_control']]96    last_query = None97    for result in diff_queries.sort_values(['damage', 'Query']).to_dict(orient='records'):98        if result['Query'] != last_query:99            last_query = result['Query']100            print(f"-------- {result['Query']} -- {result['damage']}-------")101        print(result['first_line_control'], "|||", result['first_line'])102    print("----------------------------------")103    print(f"Changed Queries - {len(diff_queries['Query'].unique())} different queries")104if __name__ == "__main__":...

time_render_middle.py

Source:time_render_middle.py

1from django.db import connection2from time import time3#------------------------------------------------------------------------------4#------------------------------------------------------------------------------5class TimeRenderMiddleware(object):6#------------------------------------------------------------------------------7    def process_request(self, request):8        # edit this stuff9        request.session['time_start'] = time()10        request.session['num_queries_old'] = len(connection.queries)11#------------------------------------------------------------------------------12    def process_response(self, request, response):13        14        queries = connection.queries15        query_time = 016        query_count = 017        18        for query in queries:19            query_time += float(query['time'])20            query_count += 121        end_time = time()22        num_queries_new =  len(connection.queries)23        24        content = response.content25        index = content.upper().find('</BODY>')26        if index == -1:27            return response28        29        before = content[:index]30        after = content[index:]31        try:32            diff_time = end_time - request.session['time_start']33            diff_queries = num_queries_new - request.session['num_queries_old']34        except KeyError:35            diff_time = 036            diff_queries = 037        38        message = """<div id="query_time"></br>\n<small><center>Time to render page is: %.4s</br>\n39        Time to sql Query: %s</br>40        Count of queries: %s</center></small></div>""" % (diff_time, query_time, diff_queries)41        content = before + message + after42        response.content =  content43        return response...

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