client.py

# This file was auto-generated by Fern from our API Definition.

import typing

from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
from ..core.request_options import RequestOptions
from ..types.aggregation_by import AggregationBy
from ..types.all_domain_links import AllDomainLinks
from ..types.all_links import AllLinks
from ..types.all_links_text import AllLinksText
from ..types.by_parse_date import ByParseDate
from ..types.content_sentiment_max import ContentSentimentMax
from ..types.content_sentiment_min import ContentSentimentMin
from ..types.countries import Countries
from ..types.from_ import From
from ..types.from_rank import FromRank
from ..types.has_nlp import HasNlp
from ..types.include_nlp_data import IncludeNlpData
from ..types.iptc_tags import IptcTags
from ..types.is_headline import IsHeadline
from ..types.is_opinion import IsOpinion
from ..types.is_paid_content import IsPaidContent
from ..types.lang import Lang
from ..types.loc_entity_name import LocEntityName
from ..types.misc_entity_name import MiscEntityName
from ..types.not_author_name import NotAuthorName
from ..types.not_countries import NotCountries
from ..types.not_iptc_tags import NotIptcTags
from ..types.not_lang import NotLang
from ..types.not_sources import NotSources
from ..types.not_theme import NotTheme
from ..types.org_entity_name import OrgEntityName
from ..types.page import Page
from ..types.page_size import PageSize
from ..types.parent_url import ParentUrl
from ..types.per_entity_name import PerEntityName
from ..types.predefined_sources import PredefinedSources
from ..types.published_date_precision import PublishedDatePrecision
from ..types.q import Q
from ..types.ranked_only import RankedOnly
from ..types.robots_compliant import RobotsCompliant
from ..types.search_in import SearchIn
from ..types.sort_by import SortBy
from ..types.sources import Sources
from ..types.theme import Theme
from ..types.title_sentiment_max import TitleSentimentMax
from ..types.title_sentiment_min import TitleSentimentMin
from ..types.to import To
from ..types.to_rank import ToRank
from ..types.word_count_max import WordCountMax
from ..types.word_count_min import WordCountMin
from .raw_client import AsyncRawAggregationCountClient, RawAggregationCountClient
from .types.get_aggregation_count_response import GetAggregationCountResponse
from .types.post_aggregation_count_response import PostAggregationCountResponse

# this is used as the default value for optional parameters
OMIT = typing.cast(typing.Any, ...)


class AggregationCountClient:
    def __init__(self, *, client_wrapper: SyncClientWrapper):
        self._raw_client = RawAggregationCountClient(client_wrapper=client_wrapper)

    @property
    def with_raw_response(self) -> RawAggregationCountClient:
        """
        Retrieves a raw implementation of this client that returns raw responses.

        Returns
        -------
        RawAggregationCountClient
        """
        return self._raw_client

    def get(
        self,
        *,
        q: Q,
        aggregation_by: typing.Optional[AggregationBy] = None,
        search_in: typing.Optional[SearchIn] = None,
        predefined_sources: typing.Optional[str] = None,
        sources: typing.Optional[str] = None,
        not_sources: typing.Optional[str] = None,
        lang: typing.Optional[str] = None,
        not_lang: typing.Optional[str] = None,
        countries: typing.Optional[str] = None,
        not_countries: typing.Optional[str] = None,
        not_author_name: typing.Optional[str] = None,
        from_: typing.Optional[From] = None,
        to: typing.Optional[To] = None,
        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
        by_parse_date: typing.Optional[ByParseDate] = None,
        sort_by: typing.Optional[SortBy] = None,
        ranked_only: typing.Optional[RankedOnly] = None,
        from_rank: typing.Optional[FromRank] = None,
        to_rank: typing.Optional[ToRank] = None,
        is_headline: typing.Optional[IsHeadline] = None,
        is_opinion: typing.Optional[IsOpinion] = None,
        is_paid_content: typing.Optional[IsPaidContent] = None,
        parent_url: typing.Optional[str] = None,
        all_links: typing.Optional[str] = None,
        all_domain_links: typing.Optional[str] = None,
        all_links_text: typing.Optional[str] = None,
        word_count_min: typing.Optional[WordCountMin] = None,
        word_count_max: typing.Optional[WordCountMax] = None,
        page: typing.Optional[Page] = None,
        page_size: typing.Optional[PageSize] = None,
        include_nlp_data: typing.Optional[IncludeNlpData] = None,
        has_nlp: typing.Optional[HasNlp] = None,
        theme: typing.Optional[Theme] = None,
        not_theme: typing.Optional[NotTheme] = None,
        org_entity_name: typing.Optional[OrgEntityName] = None,
        per_entity_name: typing.Optional[PerEntityName] = None,
        loc_entity_name: typing.Optional[LocEntityName] = None,
        misc_entity_name: typing.Optional[MiscEntityName] = None,
        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
        iptc_tags: typing.Optional[str] = None,
        not_iptc_tags: typing.Optional[str] = None,
        robots_compliant: typing.Optional[RobotsCompliant] = None,
        request_options: typing.Optional[RequestOptions] = None,
    ) -> GetAggregationCountResponse:
        """
        Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.

        Parameters
        ----------
        q : Q

        aggregation_by : typing.Optional[AggregationBy]

        search_in : typing.Optional[SearchIn]

        predefined_sources : typing.Optional[str]
            Predefined top news sources per country.

            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).

            Multiple countries with the number of top sources can be specified as a comma-separated string.

        sources : typing.Optional[str]
            One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.

        not_sources : typing.Optional[str]
            The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.

        lang : typing.Optional[str]
            The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.

            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).

        not_lang : typing.Optional[str]
            The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.

            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).

        countries : typing.Optional[str]
            The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.

            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).

        not_countries : typing.Optional[str]
            The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.

            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).

        not_author_name : typing.Optional[str]
            The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.

        from_ : typing.Optional[From]

        to : typing.Optional[To]

        published_date_precision : typing.Optional[PublishedDatePrecision]

        by_parse_date : typing.Optional[ByParseDate]

        sort_by : typing.Optional[SortBy]

        ranked_only : typing.Optional[RankedOnly]

        from_rank : typing.Optional[FromRank]

        to_rank : typing.Optional[ToRank]

        is_headline : typing.Optional[IsHeadline]

        is_opinion : typing.Optional[IsOpinion]

        is_paid_content : typing.Optional[IsPaidContent]

        parent_url : typing.Optional[str]
            The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.

        all_links : typing.Optional[str]
            The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.

            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).

        all_domain_links : typing.Optional[str]
            The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.

            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).

        all_links_text : typing.Optional[str]
            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.

            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.

            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).

        word_count_min : typing.Optional[WordCountMin]

        word_count_max : typing.Optional[WordCountMax]

        page : typing.Optional[Page]

        page_size : typing.Optional[PageSize]

        include_nlp_data : typing.Optional[IncludeNlpData]

        has_nlp : typing.Optional[HasNlp]

        theme : typing.Optional[Theme]

        not_theme : typing.Optional[NotTheme]

        org_entity_name : typing.Optional[OrgEntityName]

        per_entity_name : typing.Optional[PerEntityName]

        loc_entity_name : typing.Optional[LocEntityName]

        misc_entity_name : typing.Optional[MiscEntityName]

        title_sentiment_min : typing.Optional[TitleSentimentMin]

        title_sentiment_max : typing.Optional[TitleSentimentMax]

        content_sentiment_min : typing.Optional[ContentSentimentMin]

        content_sentiment_max : typing.Optional[ContentSentimentMax]

        iptc_tags : typing.Optional[str]
            Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.

            **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.

            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).

        not_iptc_tags : typing.Optional[str]
            Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.

            **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.

            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).

        robots_compliant : typing.Optional[RobotsCompliant]

        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        GetAggregationCountResponse
            A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.

        Examples
        --------
        from newscatcher import NewscatcherApi

        client = NewscatcherApi(
            api_key="YOUR_API_KEY",
        )
        client.aggregation_count.get(
            q='"supply chain" AND Amazon NOT China',
            search_in="title_content, title_content_translated",
            predefined_sources="top 50 US, top 20 GB",
            sources="nytimes.com,finance.yahoo.com",
            not_sources="cnn.com,wsj.com",
            lang="en,es",
            not_lang="fr,de",
            countries="US,CA",
            not_countries="UK,FR",
            not_author_name="John Doe, Jane Doe",
            from_="1 day ago",
            to="now",
            published_date_precision="full",
            by_parse_date=True,
            ranked_only=True,
            from_rank=100,
            to_rank=100,
            is_headline=True,
            is_opinion=True,
            is_paid_content=False,
            parent_url="wsj.com/politics,wsj.com/tech",
            all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
            all_domain_links="who.int,nih.gov",
            all_links_text="Nvidia,Tesla",
            word_count_min=300,
            word_count_max=1000,
            page=2,
            page_size=50,
            include_nlp_data=True,
            has_nlp=True,
            theme="Finance,Tech",
            not_theme="Crime,Sports",
            org_entity_name='"Apple Inc" OR Microsoft',
            per_entity_name='"Elon Musk" OR "Jeff Bezos"',
            loc_entity_name='"San Francisco" OR "New York City"',
            misc_entity_name='AWS OR "Microsoft Azure"',
            title_sentiment_min=-0.5,
            title_sentiment_max=0.5,
            content_sentiment_min=-0.5,
            content_sentiment_max=0.5,
            iptc_tags="20000199,20000209",
            not_iptc_tags="20000205,20000209",
            robots_compliant=True,
        )
        """
        _response = self._raw_client.get(
            q=q,
            aggregation_by=aggregation_by,
            search_in=search_in,
            predefined_sources=predefined_sources,
            sources=sources,
            not_sources=not_sources,
            lang=lang,
            not_lang=not_lang,
            countries=countries,
            not_countries=not_countries,
            not_author_name=not_author_name,
            from_=from_,
            to=to,
            published_date_precision=published_date_precision,
            by_parse_date=by_parse_date,
            sort_by=sort_by,
            ranked_only=ranked_only,
            from_rank=from_rank,
            to_rank=to_rank,
            is_headline=is_headline,
            is_opinion=is_opinion,
            is_paid_content=is_paid_content,
            parent_url=parent_url,
            all_links=all_links,
            all_domain_links=all_domain_links,
            all_links_text=all_links_text,
            word_count_min=word_count_min,
            word_count_max=word_count_max,
            page=page,
            page_size=page_size,
            include_nlp_data=include_nlp_data,
            has_nlp=has_nlp,
            theme=theme,
            not_theme=not_theme,
            org_entity_name=org_entity_name,
            per_entity_name=per_entity_name,
            loc_entity_name=loc_entity_name,
            misc_entity_name=misc_entity_name,
            title_sentiment_min=title_sentiment_min,
            title_sentiment_max=title_sentiment_max,
            content_sentiment_min=content_sentiment_min,
            content_sentiment_max=content_sentiment_max,
            iptc_tags=iptc_tags,
            not_iptc_tags=not_iptc_tags,
            robots_compliant=robots_compliant,
            request_options=request_options,
        )
        return _response.data

    def post(
        self,
        *,
        q: Q,
        aggregation_by: typing.Optional[AggregationBy] = OMIT,
        search_in: typing.Optional[SearchIn] = OMIT,
        predefined_sources: typing.Optional[PredefinedSources] = OMIT,
        sources: typing.Optional[Sources] = OMIT,
        not_sources: typing.Optional[NotSources] = OMIT,
        lang: typing.Optional[Lang] = OMIT,
        not_lang: typing.Optional[NotLang] = OMIT,
        countries: typing.Optional[Countries] = OMIT,
        not_countries: typing.Optional[NotCountries] = OMIT,
        not_author_name: typing.Optional[NotAuthorName] = OMIT,
        from_: typing.Optional[From] = OMIT,
        to: typing.Optional[To] = OMIT,
        published_date_precision: typing.Optional[PublishedDatePrecision] = OMIT,
        by_parse_date: typing.Optional[ByParseDate] = OMIT,
        sort_by: typing.Optional[SortBy] = OMIT,
        ranked_only: typing.Optional[RankedOnly] = OMIT,
        from_rank: typing.Optional[FromRank] = OMIT,
        to_rank: typing.Optional[ToRank] = OMIT,
        is_headline: typing.Optional[IsHeadline] = OMIT,
        is_opinion: typing.Optional[IsOpinion] = OMIT,
        is_paid_content: typing.Optional[IsPaidContent] = OMIT,
        parent_url: typing.Optional[ParentUrl] = OMIT,
        all_links: typing.Optional[AllLinks] = OMIT,
        all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
        all_links_text: typing.Optional[AllLinksText] = OMIT,
        word_count_min: typing.Optional[WordCountMin] = OMIT,
        word_count_max: typing.Optional[WordCountMax] = OMIT,
        page: typing.Optional[Page] = OMIT,
        page_size: typing.Optional[PageSize] = OMIT,
        include_nlp_data: typing.Optional[IncludeNlpData] = OMIT,
        has_nlp: typing.Optional[HasNlp] = OMIT,
        theme: typing.Optional[Theme] = OMIT,
        not_theme: typing.Optional[NotTheme] = OMIT,
        org_entity_name: typing.Optional[OrgEntityName] = OMIT,
        per_entity_name: typing.Optional[PerEntityName] = OMIT,
        loc_entity_name: typing.Optional[LocEntityName] = OMIT,
        misc_entity_name: typing.Optional[MiscEntityName] = OMIT,
        title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
        title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
        content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
        iptc_tags: typing.Optional[IptcTags] = OMIT,
        not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
        request_options: typing.Optional[RequestOptions] = None,
    ) -> PostAggregationCountResponse:
        """
        Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.

        Parameters
        ----------
        q : Q

        aggregation_by : typing.Optional[AggregationBy]

        search_in : typing.Optional[SearchIn]

        predefined_sources : typing.Optional[PredefinedSources]

        sources : typing.Optional[Sources]

        not_sources : typing.Optional[NotSources]

        lang : typing.Optional[Lang]

        not_lang : typing.Optional[NotLang]

        countries : typing.Optional[Countries]

        not_countries : typing.Optional[NotCountries]

        not_author_name : typing.Optional[NotAuthorName]

        from_ : typing.Optional[From]

        to : typing.Optional[To]

        published_date_precision : typing.Optional[PublishedDatePrecision]

        by_parse_date : typing.Optional[ByParseDate]

        sort_by : typing.Optional[SortBy]

        ranked_only : typing.Optional[RankedOnly]

        from_rank : typing.Optional[FromRank]

        to_rank : typing.Optional[ToRank]

        is_headline : typing.Optional[IsHeadline]

        is_opinion : typing.Optional[IsOpinion]

        is_paid_content : typing.Optional[IsPaidContent]

        parent_url : typing.Optional[ParentUrl]

        all_links : typing.Optional[AllLinks]

        all_domain_links : typing.Optional[AllDomainLinks]

        all_links_text : typing.Optional[AllLinksText]

        word_count_min : typing.Optional[WordCountMin]

        word_count_max : typing.Optional[WordCountMax]

        page : typing.Optional[Page]

        page_size : typing.Optional[PageSize]

        include_nlp_data : typing.Optional[IncludeNlpData]

        has_nlp : typing.Optional[HasNlp]

        theme : typing.Optional[Theme]

        not_theme : typing.Optional[NotTheme]

        org_entity_name : typing.Optional[OrgEntityName]

        per_entity_name : typing.Optional[PerEntityName]

        loc_entity_name : typing.Optional[LocEntityName]

        misc_entity_name : typing.Optional[MiscEntityName]

        title_sentiment_min : typing.Optional[TitleSentimentMin]

        title_sentiment_max : typing.Optional[TitleSentimentMax]

        content_sentiment_min : typing.Optional[ContentSentimentMin]

        content_sentiment_max : typing.Optional[ContentSentimentMax]

        iptc_tags : typing.Optional[IptcTags]

        not_iptc_tags : typing.Optional[NotIptcTags]

        robots_compliant : typing.Optional[RobotsCompliant]

        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        PostAggregationCountResponse
            A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.

        Examples
        --------
        from newscatcher import NewscatcherApi

        client = NewscatcherApi(
            api_key="YOUR_API_KEY",
        )
        client.aggregation_count.post(
            q='"supply chain" AND Amazon NOT China',
            aggregation_by="day",
        )
        """
        _response = self._raw_client.post(
            q=q,
            aggregation_by=aggregation_by,
            search_in=search_in,
            predefined_sources=predefined_sources,
            sources=sources,
            not_sources=not_sources,
            lang=lang,
            not_lang=not_lang,
            countries=countries,
            not_countries=not_countries,
            not_author_name=not_author_name,
            from_=from_,
            to=to,
            published_date_precision=published_date_precision,
            by_parse_date=by_parse_date,
            sort_by=sort_by,
            ranked_only=ranked_only,
            from_rank=from_rank,
            to_rank=to_rank,
            is_headline=is_headline,
            is_opinion=is_opinion,
            is_paid_content=is_paid_content,
            parent_url=parent_url,
            all_links=all_links,
            all_domain_links=all_domain_links,
            all_links_text=all_links_text,
            word_count_min=word_count_min,
            word_count_max=word_count_max,
            page=page,
            page_size=page_size,
            include_nlp_data=include_nlp_data,
            has_nlp=has_nlp,
            theme=theme,
            not_theme=not_theme,
            org_entity_name=org_entity_name,
            per_entity_name=per_entity_name,
            loc_entity_name=loc_entity_name,
            misc_entity_name=misc_entity_name,
            title_sentiment_min=title_sentiment_min,
            title_sentiment_max=title_sentiment_max,
            content_sentiment_min=content_sentiment_min,
            content_sentiment_max=content_sentiment_max,
            iptc_tags=iptc_tags,
            not_iptc_tags=not_iptc_tags,
            robots_compliant=robots_compliant,
            request_options=request_options,
        )
        return _response.data


class AsyncAggregationCountClient:
    def __init__(self, *, client_wrapper: AsyncClientWrapper):
        self._raw_client = AsyncRawAggregationCountClient(client_wrapper=client_wrapper)

    @property
    def with_raw_response(self) -> AsyncRawAggregationCountClient:
        """
        Retrieves a raw implementation of this client that returns raw responses.

        Returns
        -------
        AsyncRawAggregationCountClient
        """
        return self._raw_client

    async def get(
        self,
        *,
        q: Q,
        aggregation_by: typing.Optional[AggregationBy] = None,
        search_in: typing.Optional[SearchIn] = None,
        predefined_sources: typing.Optional[str] = None,
        sources: typing.Optional[str] = None,
        not_sources: typing.Optional[str] = None,
        lang: typing.Optional[str] = None,
        not_lang: typing.Optional[str] = None,
        countries: typing.Optional[str] = None,
        not_countries: typing.Optional[str] = None,
        not_author_name: typing.Optional[str] = None,
        from_: typing.Optional[From] = None,
        to: typing.Optional[To] = None,
        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
        by_parse_date: typing.Optional[ByParseDate] = None,
        sort_by: typing.Optional[SortBy] = None,
        ranked_only: typing.Optional[RankedOnly] = None,
        from_rank: typing.Optional[FromRank] = None,
        to_rank: typing.Optional[ToRank] = None,
        is_headline: typing.Optional[IsHeadline] = None,
        is_opinion: typing.Optional[IsOpinion] = None,
        is_paid_content: typing.Optional[IsPaidContent] = None,
        parent_url: typing.Optional[str] = None,
        all_links: typing.Optional[str] = None,
        all_domain_links: typing.Optional[str] = None,
        all_links_text: typing.Optional[str] = None,
        word_count_min: typing.Optional[WordCountMin] = None,
        word_count_max: typing.Optional[WordCountMax] = None,
        page: typing.Optional[Page] = None,
        page_size: typing.Optional[PageSize] = None,
        include_nlp_data: typing.Optional[IncludeNlpData] = None,
        has_nlp: typing.Optional[HasNlp] = None,
        theme: typing.Optional[Theme] = None,
        not_theme: typing.Optional[NotTheme] = None,
        org_entity_name: typing.Optional[OrgEntityName] = None,
        per_entity_name: typing.Optional[PerEntityName] = None,
        loc_entity_name: typing.Optional[LocEntityName] = None,
        misc_entity_name: typing.Optional[MiscEntityName] = None,
        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
        iptc_tags: typing.Optional[str] = None,
        not_iptc_tags: typing.Optional[str] = None,
        robots_compliant: typing.Optional[RobotsCompliant] = None,
        request_options: typing.Optional[RequestOptions] = None,
    ) -> GetAggregationCountResponse:
        """
        Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.

        Parameters
        ----------
        q : Q

        aggregation_by : typing.Optional[AggregationBy]

        search_in : typing.Optional[SearchIn]

        predefined_sources : typing.Optional[str]
            Predefined top news sources per country.

            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).

            Multiple countries with the number of top sources can be specified as a comma-separated string.

        sources : typing.Optional[str]
            One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.

        not_sources : typing.Optional[str]
            The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.

        lang : typing.Optional[str]
            The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.

            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).

        not_lang : typing.Optional[str]
            The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.

            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).

        countries : typing.Optional[str]
            The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.

            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).

        not_countries : typing.Optional[str]
            The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.

            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).

        not_author_name : typing.Optional[str]
            The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.

        from_ : typing.Optional[From]

        to : typing.Optional[To]

        published_date_precision : typing.Optional[PublishedDatePrecision]

        by_parse_date : typing.Optional[ByParseDate]

        sort_by : typing.Optional[SortBy]

        ranked_only : typing.Optional[RankedOnly]

        from_rank : typing.Optional[FromRank]

        to_rank : typing.Optional[ToRank]

        is_headline : typing.Optional[IsHeadline]

        is_opinion : typing.Optional[IsOpinion]

        is_paid_content : typing.Optional[IsPaidContent]

        parent_url : typing.Optional[str]
            The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.

        all_links : typing.Optional[str]
            The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.

            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).

        all_domain_links : typing.Optional[str]
            The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.

            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).

        all_links_text : typing.Optional[str]
            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.

            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.

            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).

        word_count_min : typing.Optional[WordCountMin]

        word_count_max : typing.Optional[WordCountMax]

        page : typing.Optional[Page]

        page_size : typing.Optional[PageSize]

        include_nlp_data : typing.Optional[IncludeNlpData]

        has_nlp : typing.Optional[HasNlp]

        theme : typing.Optional[Theme]

        not_theme : typing.Optional[NotTheme]

        org_entity_name : typing.Optional[OrgEntityName]

        per_entity_name : typing.Optional[PerEntityName]

        loc_entity_name : typing.Optional[LocEntityName]

        misc_entity_name : typing.Optional[MiscEntityName]

        title_sentiment_min : typing.Optional[TitleSentimentMin]

        title_sentiment_max : typing.Optional[TitleSentimentMax]

        content_sentiment_min : typing.Optional[ContentSentimentMin]

        content_sentiment_max : typing.Optional[ContentSentimentMax]

        iptc_tags : typing.Optional[str]
            Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.

            **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.

            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).

        not_iptc_tags : typing.Optional[str]
            Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.

            **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.

            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).

        robots_compliant : typing.Optional[RobotsCompliant]

        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        GetAggregationCountResponse
            A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.

        Examples
        --------
        import asyncio

        from newscatcher import AsyncNewscatcherApi

        client = AsyncNewscatcherApi(
            api_key="YOUR_API_KEY",
        )


        async def main() -> None:
            await client.aggregation_count.get(
                q='"supply chain" AND Amazon NOT China',
                search_in="title_content, title_content_translated",
                predefined_sources="top 50 US, top 20 GB",
                sources="nytimes.com,finance.yahoo.com",
                not_sources="cnn.com,wsj.com",
                lang="en,es",
                not_lang="fr,de",
                countries="US,CA",
                not_countries="UK,FR",
                not_author_name="John Doe, Jane Doe",
                from_="1 day ago",
                to="now",
                published_date_precision="full",
                by_parse_date=True,
                ranked_only=True,
                from_rank=100,
                to_rank=100,
                is_headline=True,
                is_opinion=True,
                is_paid_content=False,
                parent_url="wsj.com/politics,wsj.com/tech",
                all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
                all_domain_links="who.int,nih.gov",
                all_links_text="Nvidia,Tesla",
                word_count_min=300,
                word_count_max=1000,
                page=2,
                page_size=50,
                include_nlp_data=True,
                has_nlp=True,
                theme="Finance,Tech",
                not_theme="Crime,Sports",
                org_entity_name='"Apple Inc" OR Microsoft',
                per_entity_name='"Elon Musk" OR "Jeff Bezos"',
                loc_entity_name='"San Francisco" OR "New York City"',
                misc_entity_name='AWS OR "Microsoft Azure"',
                title_sentiment_min=-0.5,
                title_sentiment_max=0.5,
                content_sentiment_min=-0.5,
                content_sentiment_max=0.5,
                iptc_tags="20000199,20000209",
                not_iptc_tags="20000205,20000209",
                robots_compliant=True,
            )


        asyncio.run(main())
        """
        _response = await self._raw_client.get(
            q=q,
            aggregation_by=aggregation_by,
            search_in=search_in,
            predefined_sources=predefined_sources,
            sources=sources,
            not_sources=not_sources,
            lang=lang,
            not_lang=not_lang,
            countries=countries,
            not_countries=not_countries,
            not_author_name=not_author_name,
            from_=from_,
            to=to,
            published_date_precision=published_date_precision,
            by_parse_date=by_parse_date,
            sort_by=sort_by,
            ranked_only=ranked_only,
            from_rank=from_rank,
            to_rank=to_rank,
            is_headline=is_headline,
            is_opinion=is_opinion,
            is_paid_content=is_paid_content,
            parent_url=parent_url,
            all_links=all_links,
            all_domain_links=all_domain_links,
            all_links_text=all_links_text,
            word_count_min=word_count_min,
            word_count_max=word_count_max,
            page=page,
            page_size=page_size,
            include_nlp_data=include_nlp_data,
            has_nlp=has_nlp,
            theme=theme,
            not_theme=not_theme,
            org_entity_name=org_entity_name,
            per_entity_name=per_entity_name,
            loc_entity_name=loc_entity_name,
            misc_entity_name=misc_entity_name,
            title_sentiment_min=title_sentiment_min,
            title_sentiment_max=title_sentiment_max,
            content_sentiment_min=content_sentiment_min,
            content_sentiment_max=content_sentiment_max,
            iptc_tags=iptc_tags,
            not_iptc_tags=not_iptc_tags,
            robots_compliant=robots_compliant,
            request_options=request_options,
        )
        return _response.data

    async def post(
        self,
        *,
        q: Q,
        aggregation_by: typing.Optional[AggregationBy] = OMIT,
        search_in: typing.Optional[SearchIn] = OMIT,
        predefined_sources: typing.Optional[PredefinedSources] = OMIT,
        sources: typing.Optional[Sources] = OMIT,
        not_sources: typing.Optional[NotSources] = OMIT,
        lang: typing.Optional[Lang] = OMIT,
        not_lang: typing.Optional[NotLang] = OMIT,
        countries: typing.Optional[Countries] = OMIT,
        not_countries: typing.Optional[NotCountries] = OMIT,
        not_author_name: typing.Optional[NotAuthorName] = OMIT,
        from_: typing.Optional[From] = OMIT,
        to: typing.Optional[To] = OMIT,
        published_date_precision: typing.Optional[PublishedDatePrecision] = OMIT,
        by_parse_date: typing.Optional[ByParseDate] = OMIT,
        sort_by: typing.Optional[SortBy] = OMIT,
        ranked_only: typing.Optional[RankedOnly] = OMIT,
        from_rank: typing.Optional[FromRank] = OMIT,
        to_rank: typing.Optional[ToRank] = OMIT,
        is_headline: typing.Optional[IsHeadline] = OMIT,
        is_opinion: typing.Optional[IsOpinion] = OMIT,
        is_paid_content: typing.Optional[IsPaidContent] = OMIT,
        parent_url: typing.Optional[ParentUrl] = OMIT,
        all_links: typing.Optional[AllLinks] = OMIT,
        all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
        all_links_text: typing.Optional[AllLinksText] = OMIT,
        word_count_min: typing.Optional[WordCountMin] = OMIT,
        word_count_max: typing.Optional[WordCountMax] = OMIT,
        page: typing.Optional[Page] = OMIT,
        page_size: typing.Optional[PageSize] = OMIT,
        include_nlp_data: typing.Optional[IncludeNlpData] = OMIT,
        has_nlp: typing.Optional[HasNlp] = OMIT,
        theme: typing.Optional[Theme] = OMIT,
        not_theme: typing.Optional[NotTheme] = OMIT,
        org_entity_name: typing.Optional[OrgEntityName] = OMIT,
        per_entity_name: typing.Optional[PerEntityName] = OMIT,
        loc_entity_name: typing.Optional[LocEntityName] = OMIT,
        misc_entity_name: typing.Optional[MiscEntityName] = OMIT,
        title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
        title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
        content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
        iptc_tags: typing.Optional[IptcTags] = OMIT,
        not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
        request_options: typing.Optional[RequestOptions] = None,
    ) -> PostAggregationCountResponse:
        """
        Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.

        Parameters
        ----------
        q : Q

        aggregation_by : typing.Optional[AggregationBy]

        search_in : typing.Optional[SearchIn]

        predefined_sources : typing.Optional[PredefinedSources]

        sources : typing.Optional[Sources]

        not_sources : typing.Optional[NotSources]

        lang : typing.Optional[Lang]

        not_lang : typing.Optional[NotLang]

        countries : typing.Optional[Countries]

        not_countries : typing.Optional[NotCountries]

        not_author_name : typing.Optional[NotAuthorName]

        from_ : typing.Optional[From]

        to : typing.Optional[To]

        published_date_precision : typing.Optional[PublishedDatePrecision]

        by_parse_date : typing.Optional[ByParseDate]

        sort_by : typing.Optional[SortBy]

        ranked_only : typing.Optional[RankedOnly]

        from_rank : typing.Optional[FromRank]

        to_rank : typing.Optional[ToRank]

        is_headline : typing.Optional[IsHeadline]

        is_opinion : typing.Optional[IsOpinion]

        is_paid_content : typing.Optional[IsPaidContent]

        parent_url : typing.Optional[ParentUrl]

        all_links : typing.Optional[AllLinks]

        all_domain_links : typing.Optional[AllDomainLinks]

        all_links_text : typing.Optional[AllLinksText]

        word_count_min : typing.Optional[WordCountMin]

        word_count_max : typing.Optional[WordCountMax]

        page : typing.Optional[Page]

        page_size : typing.Optional[PageSize]

        include_nlp_data : typing.Optional[IncludeNlpData]

        has_nlp : typing.Optional[HasNlp]

        theme : typing.Optional[Theme]

        not_theme : typing.Optional[NotTheme]

        org_entity_name : typing.Optional[OrgEntityName]

        per_entity_name : typing.Optional[PerEntityName]

        loc_entity_name : typing.Optional[LocEntityName]

        misc_entity_name : typing.Optional[MiscEntityName]

        title_sentiment_min : typing.Optional[TitleSentimentMin]

        title_sentiment_max : typing.Optional[TitleSentimentMax]

        content_sentiment_min : typing.Optional[ContentSentimentMin]

        content_sentiment_max : typing.Optional[ContentSentimentMax]

        iptc_tags : typing.Optional[IptcTags]

        not_iptc_tags : typing.Optional[NotIptcTags]

        robots_compliant : typing.Optional[RobotsCompliant]

        request_options : typing.Optional[RequestOptions]
            Request-specific configuration.

        Returns
        -------
        PostAggregationCountResponse
            A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.

        Examples
        --------
        import asyncio

        from newscatcher import AsyncNewscatcherApi

        client = AsyncNewscatcherApi(
            api_key="YOUR_API_KEY",
        )


        async def main() -> None:
            await client.aggregation_count.post(
                q='"supply chain" AND Amazon NOT China',
                aggregation_by="day",
            )


        asyncio.run(main())
        """
        _response = await self._raw_client.post(
            q=q,
            aggregation_by=aggregation_by,
            search_in=search_in,
            predefined_sources=predefined_sources,
            sources=sources,
            not_sources=not_sources,
            lang=lang,
            not_lang=not_lang,
            countries=countries,
            not_countries=not_countries,
            not_author_name=not_author_name,
            from_=from_,
            to=to,
            published_date_precision=published_date_precision,
            by_parse_date=by_parse_date,
            sort_by=sort_by,
            ranked_only=ranked_only,
            from_rank=from_rank,
            to_rank=to_rank,
            is_headline=is_headline,
            is_opinion=is_opinion,
            is_paid_content=is_paid_content,
            parent_url=parent_url,
            all_links=all_links,
            all_domain_links=all_domain_links,
            all_links_text=all_links_text,
            word_count_min=word_count_min,
            word_count_max=word_count_max,
            page=page,
            page_size=page_size,
            include_nlp_data=include_nlp_data,
            has_nlp=has_nlp,
            theme=theme,
            not_theme=not_theme,
            org_entity_name=org_entity_name,
            per_entity_name=per_entity_name,
            loc_entity_name=loc_entity_name,
            misc_entity_name=misc_entity_name,
            title_sentiment_min=title_sentiment_min,
            title_sentiment_max=title_sentiment_max,
            content_sentiment_min=content_sentiment_min,
            content_sentiment_max=content_sentiment_max,
            iptc_tags=iptc_tags,
            not_iptc_tags=not_iptc_tags,
            robots_compliant=robots_compliant,
            request_options=request_options,
        )
        return _response.data