Python Search.get_json_response方法代码示例

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def _find_snp_position(snp_track, name):
    if snp_track is None:
        query = ElasticQuery.query_match("id", name)
        elastic = Search(query, idx=ElasticSettings.idx('MARKER'))
        snpResult = elastic.get_json_response()
        if(len(snpResult['hits']['hits'])) > 0:
            snp = snpResult['hits']['hits'][0]['_source']
            chrom = snp['seqid'].replace('chr', "")
            position = snp['start']
            return {'chr': chrom, 'start': (position-1), 'end': position, 'name': name}
    else:
        mo = re.match(r"(.*)-(.*)", snp_track)
        (group, track) = mo.group(1, 2)
        try:
            snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper(), snp_track.upper())
        except SettingsError:
            snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper())+"/"+track

        query = ElasticQuery.query_match("name", name)
        elastic = Search(query, idx=snp_track_idx)
        snpResult = elastic.get_json_response()
        if(len(snpResult['hits']['hits'])) > 0:
            snp = snpResult['hits']['hits'][0]['_source']
            chrom = snp['seqid'].replace('chr', "")
            position = snp['start']
            return {'chr': chrom, 'start': (position-1), 'end': position, 'name': name}

    return {'error': 'Marker '+name+' does not exist in the currently selected dataset'}

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
    def filter_queryset(self, request, queryset, view):
        ''' Override this method to request just the documents required from elastic. '''
        q_size = view.paginator.get_limit(request)
        q_from = view.paginator.get_offset(request)

        filterable = getattr(view, 'filter_fields', [])
        print(filterable)
        print(request)
        filters = dict([(k, v) for k, v in request.GET.items() if k in filterable])
        criteria_idx = self._get_index(filters.get('feature_type', 'GENE_CRITERIA'))

        idx = criteria_idx
        if type(criteria_idx) == list:
            idx = ','.join(ElasticSettings.idx(name) for name in criteria_idx)
        else:
            idx = ElasticSettings.idx(criteria_idx)

        q = ElasticQuery(Query.match_all())
        s = Search(search_query=q, idx=idx, size=q_size, search_from=q_from)
        json_results = s.get_json_response()
        results = []
        for result in json_results['hits']['hits']:
            new_obj = ElasticObject(initial=result['_source'])
            new_obj.uuid = result['_id']
            new_obj.criteria_type = result['_type']
            results.append(new_obj)
        view.es_count = json_results['hits']['total']
        return results

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
    def get_object(self):
        q = ElasticQuery(Query.ids(self.kwargs[self.lookup_field]))
        s = Search(search_query=q, idx=getattr(self, 'idx'))
        try:
            result = s.get_json_response()['hits']['hits'][0]
            obj = ElasticObject(initial=result['_source'])
            obj.uuid = result['_id']
            obj.criteria_type = result['_type']

            # May raise a permission denied
            self.check_object_permissions(self.request, obj)
            return obj
        except (TypeError, ValueError, IndexError):
            raise Http404

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
    def post(self, request, *args, **kwargs):
        ens_id = self.request.POST.get('ens_id')
        marker = self.request.POST.get('marker')
        markers = self.request.POST.getlist('markers[]')

        if ens_id:
            sfilter = Filter(Query.query_string(ens_id, fields=["genes"]).query_wrap())
        elif marker:
            sfilter = Filter(Query.query_string(marker, fields=["marker"]).query_wrap())
        elif markers:
            sfilter = Filter(Query.query_string(' '.join(markers), fields=["marker"]).query_wrap())

        query = ElasticQuery.filtered(Query.match_all(), sfilter)
        elastic = Search(query, idx=ElasticSettings.idx('REGION', 'STUDY_HITS'), size=500)
        study_hits = elastic.get_json_response()['hits']

        ens_ids = []
        pmids = []
        for hit in study_hits['hits']:
            if 'pmid' in hit['_source']:
                pmids.append(hit['_source']['pmid'])
            if 'genes' in hit['_source']:
                for ens_id in hit['_source']['genes']:
                    ens_ids.append(ens_id)
        docs = utils.get_gene_docs_by_ensembl_id(ens_ids, ['symbol'])
        pub_docs = PublicationDocument.get_pub_docs_by_pmid(pmids, sources=['authors.name', 'journal'])

        for hit in study_hits['hits']:
            genes = {}
            if 'genes' in hit['_source']:
                for ens_id in hit['_source']['genes']:
                    try:
                        genes[ens_id] = getattr(docs[ens_id], 'symbol')
                    except KeyError:
                        genes = {ens_id: ens_id}
            hit['_source']['genes'] = genes
            if 'pmid' in hit['_source']:
                pmid = hit['_source']['pmid']
                try:
                    authors = getattr(pub_docs[pmid], 'authors')
                    journal = getattr(pub_docs[pmid], 'journal')
                    hit['_source']['pmid'] = \
                        {'pmid': pmid,
                         'author': authors[0]['name'].rsplit(None, 1)[-1] if authors else "",
                         'journal': journal}
                except KeyError:
                    hit['_source']['pmid'] = {'pmid': pmid}

        return JsonResponse(study_hits)

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def _build_frags_query(frags_idx, chrom, segmin, segmax):

    query = ElasticQuery.filtered(Query.terms("seqid", [chrom, str("chr"+chrom)]),
                                  Filter(RangeQuery("end", gte=segmin, lte=segmax)),
                                  utils.bedFields)
    fragsQuery = Search(search_query=query, search_from=0, size=10000, idx=frags_idx)

    # fragsResult = fragsQuery.get_result()
    # frags = fragsResult['data']
    fragsResult = fragsQuery.get_json_response()
    frags = []
    for hit in fragsResult['hits']['hits']:
        frags.append(hit['_source'])
    frags = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], frags)
    return frags

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
    def get_criteria_details(cls, feature_id, idx, idx_type, criteria_id=None):
        '''Function to get criteria details for a given feature_id. If criteria_id is given,
        the result is restricted to that criteria
        @type  feature_id: string
        @keyword feature_id: Id of the feature (gene => gene_id, region=>region_id)
        @type  criteria_id: string
        @keyword criteria_id: criteria_id eg: cand_gene_in_study, gene_in_region
        @type  idx: string
        @param idx: name of the index
        @type  idx_type: string
        @param idx_type: name of the idx type, each criteria is an index type
        '''
        query = ElasticQuery(Query.term("qid", feature_id))
        search = Search(query, idx=idx, idx_type=idx_type)
#        elastic_docs = search.search().docs
        criteria_hits = search.get_json_response()['hits']
        return(criteria_hits)

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def _build_hic_query(query, targetIdx, segmin=0, segmax=0):

    hic = []
    hicElastic = Search(query, idx=ElasticSettings.idx('CP_TARGET_'+targetIdx), search_from=0, size=2000)
    # hicResult = hicElastic.get_result()
    hicResult = hicElastic.get_json_response()
    if "error" in hicResult:
        return {'error': 'No search results found. Please try again.'}, segmin, segmax
    if len(hicResult['hits']['hits']) > 0:
        for hit in hicResult['hits']['hits']:
            hic.append(hit['_source'])
        if segmin == 0 or segmax == 0:
            (segmin, segmax) = utils.segCoords(hic)
            extension = int(0.05*(segmax-segmin))
            segmin = segmin - extension
            segmax = segmax + extension
        hic = utils.makeRelative(int(segmin), int(segmax), ['baitStart', 'baitEnd', 'oeStart', 'oeEnd'], hic)
    return hic, segmin, segmax

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def _build_exon_query(chrom, segmin, segmax, genes):
    # get exonic structure for genes in this section
    geneExons = dict()
    query_bool = BoolQuery()
    query_bool.must([Query.term("seqid", chrom)])
    if len(genes) > 0:
        for g in genes:
            query = ElasticQuery.filtered_bool(Query.query_string(g["gene_id"], fields=["name"]),
                                               query_bool, sources=utils.snpFields)
            elastic = Search(query, idx=getattr(chicp_settings, 'CP_GENE_IDX')+'/exons/', search_from=0, size=2000)
            # result = elastic.get_result()
            # exons = result['data']
            result = elastic.get_json_response()
            exons = []
            for hit in result['hits']['hits']:
                exons.append(hit['_source'])
            exons = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], exons)
            geneExons[g["gene_id"]] = sorted(exons, key=operator.itemgetter("start"))
    return geneExons

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def interaction_details(request):
    ''' Get interaction details for a given ensembl ID. '''
    ens_id = request.POST.get('ens_id')
    query = ElasticQuery.has_parent('gene', Query.ids(ens_id))
    elastic = Search(query, idx=ElasticSettings.idx('GENE', 'INTERACTIONS'), size=500)

    interaction_hits = elastic.get_json_response()['hits']
    ens_ids = []
    for hit in interaction_hits['hits']:
        for interactor in hit['_source']['interactors']:
            ens_ids.append(interactor['interactor'])
    docs = utils.get_gene_docs_by_ensembl_id(ens_ids, ['symbol'])
    for hit in interaction_hits['hits']:
        for interactor in hit['_source']['interactors']:
            iid = interactor['interactor']
            try:
                interactor['symbol'] = getattr(docs[iid], 'symbol')
            except KeyError:
                interactor['symbol'] = iid

    return JsonResponse(interaction_hits)

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def interaction_details(request):
    """ Get interaction details for a given ensembl ID. """
    ens_id = request.POST.get("ens_id")
    query = ElasticQuery.has_parent("gene", Query.ids(ens_id))
    elastic = Search(query, idx=ElasticSettings.idx("GENE", "INTERACTIONS"), size=500)

    interaction_hits = elastic.get_json_response()["hits"]
    ens_ids = []
    for hit in interaction_hits["hits"]:
        for interactor in hit["_source"]["interactors"]:
            ens_ids.append(interactor["interactor"])
    docs = _get_gene_docs_by_ensembl_id(ens_ids, ["symbol"])
    for hit in interaction_hits["hits"]:
        for interactor in hit["_source"]["interactors"]:
            iid = interactor["interactor"]
            try:
                interactor["symbol"] = getattr(docs[iid], "symbol")
            except KeyError:
                interactor["symbol"] = iid

    return JsonResponse(interaction_hits)

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def studies_details(request):
    """ Get studies for a given ensembl ID. """
    ens_id = request.POST.get("ens_id")
    sfilter = Filter(Query.query_string(ens_id, fields=["genes"]).query_wrap())
    query = ElasticQuery.filtered(Query.match_all(), sfilter)
    elastic = Search(query, idx=ElasticSettings.idx("REGION", "STUDY_HITS"), size=500)
    study_hits = elastic.get_json_response()["hits"]

    ens_ids = []
    pmids = []
    for hit in study_hits["hits"]:
        if "pmid" in hit["_source"]:
            pmids.append(hit["_source"]["pmid"])
        for ens_id in hit["_source"]["genes"]:
            ens_ids.append(ens_id)
    docs = _get_gene_docs_by_ensembl_id(ens_ids, ["symbol"])
    pub_docs = _get_pub_docs_by_pmid(pmids, sources=["authors.name", "journal"])

    for hit in study_hits["hits"]:
        genes = {}
        for ens_id in hit["_source"]["genes"]:
            try:
                genes[ens_id] = getattr(docs[ens_id], "symbol")
            except KeyError:
                genes = {ens_id: ens_id}
        hit["_source"]["genes"] = genes
        if "pmid" in hit["_source"]:
            pmid = hit["_source"]["pmid"]
            try:
                authors = getattr(pub_docs[pmid], "authors")
                journal = getattr(pub_docs[pmid], "journal")
                hit["_source"]["pmid"] = {
                    "pmid": pmid,
                    "author": authors[0]["name"].rsplit(None, 1)[-1],
                    "journal": journal,
                }
            except KeyError:
                hit["_source"]["pmid"] = {"pmid": pmid}

    return JsonResponse(study_hits)

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def genesets_details(request):
    """ Get pathway gene sets for a given ensembl ID. """
    ens_id = request.POST.get("ens_id")
    geneset_filter = Filter(Query.query_string(ens_id, fields=["gene_sets"]).query_wrap())
    query = ElasticQuery.filtered(Query.match_all(), geneset_filter)
    elastic = Search(query, idx=ElasticSettings.idx("GENE", "PATHWAY"), size=500)
    genesets_hits = elastic.get_json_response()["hits"]
    ens_ids = []
    for hit in genesets_hits["hits"]:
        for ens_id in hit["_source"]["gene_sets"]:
            ens_ids.append(ens_id)
    docs = _get_gene_docs_by_ensembl_id(ens_ids, ["symbol"])

    for hit in genesets_hits["hits"]:
        genesets = {}
        for ens_id in hit["_source"]["gene_sets"]:
            try:
                genesets[ens_id] = getattr(docs[ens_id], "symbol")
            except KeyError:
                genesets[ens_id] = ens_id
        hit["_source"]["gene_sets"] = genesets
    return JsonResponse(genesets_hits)

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def genesets_details(request):
    ''' Get pathway gene sets for a given ensembl ID. '''
    ens_id = request.POST.get('ens_id')
    geneset_filter = Filter(Query.query_string(ens_id, fields=["gene_sets"]).query_wrap())
    query = ElasticQuery.filtered(Query.match_all(), geneset_filter)
    elastic = Search(query, idx=ElasticSettings.idx('GENE', 'PATHWAY'), size=500)
    genesets_hits = elastic.get_json_response()['hits']
    ens_ids = []
    for hit in genesets_hits['hits']:
        for ens_id in hit['_source']['gene_sets']:
            ens_ids.append(ens_id)
    docs = utils.get_gene_docs_by_ensembl_id(ens_ids, ['symbol'])

    for hit in genesets_hits['hits']:
        genesets = {}
        for ens_id in hit['_source']['gene_sets']:
            try:
                genesets[ens_id] = getattr(docs[ens_id], 'symbol')
            except KeyError:
                genesets[ens_id] = ens_id
        hit['_source']['gene_sets'] = genesets
    return JsonResponse(genesets_hits)

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
def _build_snp_query(snp_track, chrom, segmin, segmax):
    snps = []
    snpMeta = {}
    maxScore = -1
    if snp_track and snp_track != 'None':
        # get SNPs based on this segment
        mo = re.match(r"(.*)-(.*)", snp_track)
        (group, track) = mo.group(1, 2)
        try:
            snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper(), snp_track.upper())
        except SettingsError:
            snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper())+"/"+track

        query = ElasticQuery.filtered(Query.terms("seqid", [chrom, str("chr"+chrom)]),
                                      Filter(RangeQuery("end", gte=segmin, lte=segmax)),
                                      utils.snpFields)
        snpQuery = Search(search_query=query, search_from=0, size=10000, idx=snp_track_idx)

        # snpResult = snpQuery.get_result()
        # snps = snpResult['data']
        snpResult = snpQuery.get_json_response()
        snps = []
        for hit in snpResult['hits']['hits']:
            snps.append(hit['_source'])
        snps = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], snps)

        data_type = ElasticSettings.get_label('CP_STATS_'+group.upper(), None, "data_type")
        snpSettings = getattr(chicp_settings, 'STUDY_DEFAULTS').get(data_type)

        for s in snps:
            if float(s['score']) > maxScore:
                maxScore = float(s['score'])
        snpSettings['max'] = maxScore

        snpMeta = snpSettings

    return snps, snpMeta

# 需要导入模块: from elastic.search import Search [as 别名]
# 或者: from elastic.search.Search import get_json_response [as 别名]
    def get_all_criteria_disease_tags(cls, qids, idx, idx_type):

        if qids is None:
            query = ElasticQuery(Query.match_all(), sources=['disease_tags', 'qid'])
            # search = Search(query, idx=idx, idx_type=idx_type, size=30000)
        else:
            query = ElasticQuery(Query.terms("qid", qids), sources=['disease_tags', 'qid'])
            # search = Search(query, idx=idx, idx_type=idx_type)

        search = Search(query, idx=idx, idx_type=idx_type)
        criteria_hits = search.get_json_response()['hits']
        hits = criteria_hits['hits']

        meta_info = {}

        criteria_disease_tags = {}
        for hit in hits:
            if idx == hit['_index']:
                qid = hit['_source']['qid']
                meta_desc = cls.get_meta_desc(idx, [hit['_type']])
                meta_info[hit['_type']] = meta_desc[idx][hit['_type']]

                criteria_desc = hit['_type']

                if qid not in criteria_disease_tags:
                    criteria_disease_tags[qid] = {}
                criteria_disease_tags[qid][criteria_desc] = hit['_source']['disease_tags']

        disease_tags_all = []
        for fid, fvalue in criteria_disease_tags.items():
            disease_tags_all = cls.get_all_criteria_disease_tags_aggregated(qid, fvalue)
            criteria_disease_tags[fid]['all'] = disease_tags_all

            criteria_disease_tags[fid]['meta_info'] = meta_info

        return(criteria_disease_tags)