Typeahead.js Bloodhound 忽略高质量结果

Question

我的代码

var streetAddress = new Bloodhound({
    datumTokenizer: Bloodhound.tokenizers.obj.whitespace('value'),
    queryTokenizer: Bloodhound.tokenizers.whitespace,
    remote: {
        url: 'https://api.mapbox.com/v4/geocode/mapbox.places/%QUERY.json?proximity=-74,45&access_token=pk.********.********',
        wildcard: '%QUERY',
        prepare: function (query, settings) {
            //Just a function to remove an ajax header 'X-CSRF-TOKEN'
            startRequest();
            settings.url = settings.url.replace('%QUERY', encodeURI(query));
            return settings;
        },
        transform: function (response) {
            //Just a function to add back the removed ajax header
            endRequest();
            return response.features;
        }
    }
});

var test = $('#address-search .typeahead').typeahead({
    hint: false,
    highlight: false,
    minLength: 1
},
{
    display: 'place_name',
    source: streetAddress
});

我的转换函数正在返回以下响应的特征部分，以便我可以从预输入中访问 place_name 参数。

我查询的数据

{
    "type":"FeatureCollection",
    "query":[
        "1600",
        "pennsylvania",
        "ave"
    ],
    "features":[
        {
            "id":"address.170282823806239",
            "type":"Feature",
            "text":"Pennsylvania Ave NW",
            "place_name":"1600 Pennsylvania Ave NW, Washington, 20006, District of Columbia, United States",
            "relevance":0.99,
            "center":[
                -77.036698,
                38.897102
            ],
            "geometry":{
                "type":"Point",
                "coordinates":[
                    -77.036698,
                    38.897102
                ]
            },
            "bbox":[
                -77.05781199999998,
                38.89252299999999,
                -77.01844799999999,
                38.905058999999994
            ],
            "address":"1600",
            "properties":{

            },
            "context":[
                {
                    "id":"place.10719",
                    "text":"Washington"
                },
                {
                    "id":"postcode.757789931",
                    "text":"20006"
                },
                {
                    "id":"region.1190806886",
                    "text":"District of Columbia"
                },
                {
                    "id":"country.4150104525",
                    "text":"United States"
                }
            ]
        },
        {
            "id":"address.42492466560022",
            "type":"Feature",
            "text":"Pennsylvania Ave",
            "place_name":"1600 Pennsylvania Ave, Baltimore, 21217, Maryland, United States",
            "relevance":0.99,
            "center":[
                -76.634388,
                39.30307
            ],
            "geometry":{
                "type":"Point",
                "coordinates":[
                    -76.634388,
                    39.30307
                ]
            },
            "bbox":[
                -76.64626799999999,
                39.295034999999984,
                -76.62387699999998,
                39.313258999999995
            ],
            "address":"1600",
            "properties":{

            },
            "context":[
                {
                    "id":"place.10950",
                    "text":"Baltimore"
                },
                {
                    "id":"postcode.1084729612",
                    "text":"21217"
                },
                {
                    "id":"region.928365533",
                    "text":"Maryland"
                },
                {
                    "id":"country.4150104525",
                    "text":"United States"
                }
            ]
        },
        {
            "id":"address.67278193792769",
            "type":"Feature",
            "text":"Pennsylvania Ave",
            "place_name":"1600 Pennsylvania Ave, Miami Beach, 33139, Florida, United States",
            "relevance":0.99,
            "center":[
                -80.13459,
                25.789245
            ],
            "geometry":{
                "type":"Point",
                "coordinates":[
                    -80.13459,
                    25.789245
                ]
            },
            "bbox":[
                -80.13474099999999,
                25.776914999999992,
                -80.13365999999999,
                25.789956999999994
            ],
            "address":"1600",
            "properties":{

            },
            "context":[
                {
                    "id":"place.14360",
                    "text":"Miami Beach"
                },
                {
                    "id":"postcode.260297597",
                    "text":"33139"
                },
                {
                    "id":"region.3998021366",
                    "text":"Florida"
                },
                {
                    "id":"country.4150104525",
                    "text":"United States"
                }
            ]
        },
        {
            "id":"address.179234355186041",
            "type":"Feature",
            "text":"Pennsylvania Ave S",
            "place_name":"1600 Pennsylvania Ave S, Minneapolis, 55426, Minnesota, United States",
            "relevance":0.99,
            "center":[
                -93.376595,
                44.967257
            ],
            "geometry":{
                "type":"Point",
                "coordinates":[
                    -93.376595,
                    44.967257
                ]
            },
            "bbox":[
                -93.37759599999998,
                44.93132099999999,
                -93.37223099999997,
                44.970254999999995
            ],
            "address":"1600",
            "properties":{

            },
            "context":[
                {
                    "id":"place.20936",
                    "text":"Minneapolis"
                },
                {
                    "id":"postcode.2607442246",
                    "text":"55426"
                },
                {
                    "id":"region.4222030107",
                    "text":"Minnesota"
                },
                {
                    "id":"country.4150104525",
                    "text":"United States"
                }
            ]
        },
        {
            "id":"address.243590068555079",
            "type":"Feature",
            "text":"Pennsylvania Ave",
            "place_name":"1600 Pennsylvania Ave, Hartshorne, 74547, Oklahoma, United States",
            "relevance":0.99,
            "center":[
                -95.54508,
                34.841595
            ],
            "geometry":{
                "type":"Point",
                "coordinates":[
                    -95.54508,
                    34.841595
                ]
            },
            "bbox":[
                -95.57070949999998,
                34.84120059999999,
                -95.54433509999997,
                34.85049019999999
            ],
            "address":"1600",
            "properties":{

            },
            "context":[
                {
                    "id":"place.27314",
                    "text":"Hartshorne"
                },
                {
                    "id":"postcode.4130057309",
                    "text":"74547"
                },
                {
                    "id":"region.1788423601",
                    "text":"Oklahoma"
                },
                {
                    "id":"country.4150104525",
                    "text":"United States"
                }
            ]
        }
    ],
    "attribution":"NOTICE: You may cache this data for up to 30 days. © 2015 Mapbox and its suppliers. All rights reserved. Use of this data is subject to the Mapbox Terms of Service. (https://www.mapbox.com/about/maps/)"
}

我遇到的问题是 Bloodhound 丢弃了所有这些结果。同样，如果我使用“3360”的查询，那么它只会显示一个结果。我做错了什么得到糟糕的结果？

我还可以补充一点，我不知道某些参数是什么意思，比如我是否应该在 datumTokenizer 中更改 'value'。我也不确定 name: parameter 在 typeahead 中的用途，我已经排除了它。

在此先感谢您的帮助

Answer 1

在使用该插件数小时并查看 github 上的问题后，我得出的结论是该插件的支持不佳且漏洞百出。虽然它可能有很多星，但它有未解决的问题、未完成的拉取请求和糟糕的文档。此外，存储库已超过 3 个月未更新。我切换到 select2（jquery 插件），并且我在一个小时内得到了我最初想要起床和运行的功能。 我不推荐使用这个插件，因为它的支持很差，还有一些突出的问题。

Typeahead.js Bloodhound 忽略高质量结果

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javascript

jquery

typeahead.js

bloodhound