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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def search_jobs( self, parent, request_metadata, search_mode=None, job_query=None, enable_broadening=None, require_precise_result_size=None, histogram_queries=None, job_view=None, offset=None, page_size=None, order_by=None, diversification_level=None, custom_ranking_info=None, disable_keyword_match=None, retry=google.api_core.gapic_v1.method.DEFAULT, timeout=google.api_core.gapic_v1.method.DEFAULT, metadata=None, ):
 """ Searches for jobs using the provided ``SearchJobsRequest``. This call constrains the ``visibility`` of jobs present in the database, and only returns jobs that the caller has permission to search against. Example: Args: parent (str):
 Required. The resource name of the project to search within. The format is "projects/{project\_id}", for example, "projects/api-test-project". request_metadata (Union[dict, ~google.cloud.talent_v4beta1.types.RequestMetadata]):
 Required. The meta information collected about the job searcher, used to improve the search quality of the service.. The identifiers, (such as ``user_id``) are provided by users, and must be unique and consistent. If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.talent_v4beta1.types.RequestMetadata` search_mode (~google.cloud.talent_v4beta1.types.SearchMode):
 Optional. Mode of a search. Defaults to ``SearchMode.JOB_SEARCH``. job_query (Union[dict, ~google.cloud.talent_v4beta1.types.JobQuery]):
 Optional. Query used to search against jobs, such as keyword, location filters, etc. If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.talent_v4beta1.types.JobQuery` enable_broadening (bool):
 Optional. Controls whether to broaden the search when it produces sparse results. Broadened queries append results to the end of the matching results list. Defaults to false. require_precise_result_size (bool):
 Optional. Controls if the search job request requires the return of a precise count of the first 300 results. Setting this to ``true`` ensures consistency in the number of results per page. Best practice is to set this value to true if a client allows users to jump directly to a non-sequential search results page. Enabling this flag may adversely impact performance. Defaults to false. histogram_queries (list[Union[dict, ~google.cloud.talent_v4beta1.types.HistogramQuery]]):
 Optional. An expression specifies a histogram request against matching jobs. Expression syntax is an aggregation function call with histogram facets and other options. Available aggregation function calls are: \* ``count(string_histogram_facet)``: Count the number of matching entities, for each distinct attribute value. \* ``count(numeric_histogram_facet, list of buckets)``: Count the number of matching entities within each bucket. Data types: - Histogram facet: facet names with format [a-zA-Z][a-zA-Z0-9\_]+. - String: string like "any string with backslash escape for quote(")." - Number: whole number and floating point number like 10, -1 and -0.01. - List: list of elements with comma(,) separator surrounded by square brackets, for example, [1, 2, 3] and ["one", "two", "three"]. Built-in constants: - MIN (minimum number similar to java Double.MIN\_VALUE) - MAX (maximum number similar to java Double.MAX\_VALUE) Built-in functions: - bucket(start, end[, label]):
 bucket built-in function creates a bucket with range of \`start, end). Note that the end is exclusive, for example, bucket(1, MAX, "positive number") or bucket(1, 10). Job histogram facets: - company\_id: histogram by [Job.distributor\_company\_id\`. - company\_display\_name: histogram by ``Job.company_display_name``. - employment\_type: histogram by ``Job.employment_types``, for example, "FULL\_TIME", "PART\_TIME". - company\_size: histogram by ``CompanySize``, for example, "SMALL", "MEDIUM", "BIG". - publish\_time\_in\_month: histogram by the ``Job.publish_time`` in months. Must specify list of numeric buckets in spec. - publish\_time\_in\_year: histogram by the ``Job.publish_time`` in years. Must specify list of numeric buckets in spec. - degree\_type: histogram by the ``Job.degree_type``, for example, "Bachelors", "Masters". - job\_level: histogram by the ``Job.job_level``, for example, "Entry Level". - country: histogram by the country code of jobs, for example, "US", "FR". - admin1: histogram by the admin1 code of jobs, which is a global placeholder referring to the state, province, or the particular term a country uses to define the geographic structure below the country level, for example, "CA", "IL". - city: histogram by a combination of the "city name, admin1 code". For example, "Mountain View, CA", "New York, NY". - admin1\_country: histogram by a combination of the "admin1 code, country", for example, "CA, US", "IL, US". - city\_coordinate: histogram by the city center's GPS coordinates (latitude and longitude), for example, 37.4038522,-122.0987765. Since the coordinates of a city center can change, customers may need to refresh them periodically. - locale: histogram by the ``Job.language_code``, for example, "en-US", "fr-FR". - language: histogram by the language subtag of the ``Job.language_code``, for example, "en", "fr". - category: histogram by the ``JobCategory``, for example, "COMPUTER\_AND\_IT", "HEALTHCARE". - base\_compensation\_unit: histogram by the ``CompensationUnit`` of base salary, for example, "WEEKLY", "MONTHLY". - base\_compensation: histogram by the base salary. Must specify list of numeric buckets to group results by. - annualized\_base\_compensation: histogram by the base annualized salary. Must specify list of numeric buckets to group results by. - annualized\_total\_compensation: histogram by the total annualized salary. Must specify list of numeric buckets to group results by. - string\_custom\_attribute: histogram by string ``Job.custom_attributes``. Values can be accessed via square bracket notations like string\_custom\_attribute["key1"]. - numeric\_custom\_attribute: histogram by numeric ``Job.custom_attributes``. Values can be accessed via square bracket notations like numeric\_custom\_attribute["key1"]. Must specify list of numeric buckets to group results by. Example expressions: \* count(admin1) \* count(base\_compensation, [bucket(1000, 10000), bucket(10000, 100000), bucket(100000, MAX)]) \* count(string\_custom\_attribute["some-string-custom-attribute"]) \* count(numeric\_custom\_attribute["some-numeric-custom-attribute"], [bucket(MIN, 0, "negative"), bucket(0, MAX, "non-negative"]) If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.talent_v4beta1.types.HistogramQuery` job_view (~google.cloud.talent_v4beta1.types.JobView):
 Optional. The desired job attributes returned for jobs in the search response. Defaults to ``JobView.SMALL`` if no value is specified. offset (int):
 Optional. An integer that specifies the current offset (that is, starting result location, amongst the jobs deemed by the API as relevant) in search results. This field is only considered if ``page_token`` is unset. For example, 0 means to return results starting from the first matching job, and 10 means to return from the 11th job. This can be used for pagination, (for example, pageSize = 10 and offset = 10 means to return from the second page). page_size (int):
 The maximum number of resources contained in the underlying API response. If page streaming is performed per- resource, this parameter does not affect the return value. If page streaming is performed per-page, this determines the maximum number of resources in a page. order_by (str):
 Optional. The criteria determining how search results are sorted. Default is "relevance desc". Supported options are: - "relevance desc": By relevance descending, as determined by the API algorithms. Relevance thresholding of query results is only available with this ordering. - "posting``_``\ publish\ ``_``\ time desc": By ``Job.posting_publish_time`` descending. - "posting``_``\ update\ ``_``\ time desc": By ``Job.posting_update_time`` descending. - "title": By ``Job.title`` ascending. - "title desc": By ``Job.title`` descending. - "annualized``_``\ base\ ``_``\ compensation": By job's ``CompensationInfo.annualized_base_compensation_range`` ascending. Jobs whose annualized base compensation is unspecified are put at the end of search results. - "annualized``_``\ base\ ``_``\ compensation desc": By job's ``CompensationInfo.annualized_base_compensation_range`` descending. Jobs whose annualized base compensation is unspecified are put at the end of search results. - "annualized``_``\ total\ ``_``\ compensation": By job's ``CompensationInfo.annualized_total_compensation_range`` ascending. Jobs whose annualized base compensation is unspecified are put at the end of search results. - "annualized``_``\ total\ ``_``\ compensation desc": By job's ``CompensationInfo.annualized_total_compensation_range`` descending. Jobs whose annualized base compensation is unspecified are put at the end of search results. - "custom``_``\ ranking desc": By the relevance score adjusted to the ``SearchJobsRequest.custom_ranking_info.ranking_expression`` with weight factor assigned by ``SearchJobsRequest.custom_ranking_info.importance_level`` in descending order. - "location``_``\ distance": By the distance between the location on jobs and locations specified in the ``SearchJobsRequest.job_query.location_filters``. When this order is selected, the ``SearchJobsRequest.job_query.location_filters`` must not be empty. When a job has multiple locations, the location closest to one of the locations specified in the location filter will be used to calculate location distance. Distance is calculated by the distance between two lat/long coordinates, with a precision of 10e-4 degrees (11.3 meters). Jobs that don't have locations specified will be ranked below jobs having locations. Diversification strategy is still applied unless explicitly disabled in ``SearchJobsRequest.diversification_level``. diversification_level (~google.cloud.talent_v4beta1.types.DiversificationLevel):
 Optional. Controls whether highly similar jobs are returned next to each other in the search results. Jobs are identified as highly similar based on their titles, job categories, and locations. Highly similar results are clustered so that only one representative job of the cluster is displayed to the job seeker higher up in the results, with the other jobs being displayed lower down in the results. Defaults to ``DiversificationLevel.SIMPLE`` if no value is specified. custom_ranking_info (Union[dict, ~google.cloud.talent_v4beta1.types.CustomRankingInfo]):
 Optional. Controls over how job documents get ranked on top of existing relevance score (determined by API algorithm). If a dict is provided, it must be of the same form as the protobuf message :class:`~google.cloud.talent_v4beta1.types.CustomRankingInfo` disable_keyword_match (bool):
 Optional. Controls whether to disable exact keyword match on ``Job.job_title``, ``Job.description``, ``Job.company_display_name``, [Job.locations][0], ``Job.qualifications``. When disable keyword match is turned off, a keyword match returns jobs that do not match given category filters when there are matching keywords. For example, for the query "program manager," a result is returned even if the job posting has the title "software developer," which doesn't fall into "program manager" ontology, but does have "program manager" appearing in its description. For queries like "cloud" that don't contain title or location specific ontology, jobs with "cloud" keyword matches are returned regardless of this flag's value. Please use ``Company.keyword_searchable_custom_fields`` or ``Company.keyword_searchable_custom_attributes`` if company specific globally matched custom field/attribute string values is needed. Enabling keyword match improves recall of subsequent search requests. Defaults to false. retry (Optional[google.api_core.retry.Retry]):
 A retry object used to retry requests. If ``None`` is specified, requests will not be retried. timeout (Optional[float]):
 The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. metadata (Optional[Sequence[Tuple[str, str]]]):
 Additional metadata that is provided to the method. Returns: A :class:`~google.gax.PageIterator` instance. By default, this is an iterable of :class:`~google.cloud.talent_v4beta1.types.MatchingJob` instances. This object can also be configured to iterate over the pages of the response through the `options` parameter. Raises: google.api_core.exceptions.GoogleAPICallError: If the request failed for any reason. google.api_core.exceptions.RetryError: If the request failed due to a retryable error and retry attempts failed. ValueError: If the parameters are invalid. """

        # Wrap the transport method to add retry and timeout logic.
        if "search_jobs" not in self._inner_api_calls:
            self._inner_api_calls[
                "search_jobs"
            ] = google.api_core.gapic_v1.method.wrap_method(
                self.transport.search_jobs,
                default_retry=self._method_configs["SearchJobs"].retry,
                default_timeout=self._method_configs["SearchJobs"].timeout,
                client_info=self._client_info,
            )

        request = job_service_pb2.SearchJobsRequest(
            parent=parent,
            request_metadata=request_metadata,
            search_mode=search_mode,
            job_query=job_query,
            enable_broadening=enable_broadening,
            require_precise_result_size=require_precise_result_size,
            histogram_queries=histogram_queries,
            job_view=job_view,
            offset=offset,
            page_size=page_size,
            order_by=order_by,
            diversification_level=diversification_level,
            custom_ranking_info=custom_ranking_info,
            disable_keyword_match=disable_keyword_match,
        )
        iterator = google.api_core.page_iterator.GRPCIterator(
            client=None,
            method=functools.partial(
                self._inner_api_calls["search_jobs"],
                retry=retry,
                timeout=timeout,
                metadata=metadata,
            ),
            request=request,
            items_field="matching_jobs",
            request_token_field="page_token",
            response_token_field="next_page_token",
        )
        return iterator