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Dadata API Client

Data cleansing, enrichment and suggestions via Dadata API

Latest Stable Version Total Downloads License

Thin PHP wrapper over Dadata API.

Installation

composer require hflabs/dadata

Requirements:

  • PHP 5.6+
  • Guzzle 6

Usage

Create API client instance:

> $token = "Replace with Dadata API key";
> $secret = "Replace with Dadata secret key";
> $dadata = new \Dadata\DadataClient($token, $secret);

Then call API methods as specified below.

Postal Address

> $response = $dadata->clean("address", "мск сухонская 11 89");
> var_dump($response);
array(80) {
  ["source"]=>
  string(31) "мск сухонская 11 89"
  ["result"]=>
  string(56) "г Москва, ул Сухонская, д 11, кв 89"
  ["postal_code"]=>
  string(6) "127642"
  ["country"]=>
  string(12) "Россия"
  ["federal_district"]=>
  string(22) "Центральный"
  ["region"]=>
  string(12) "Москва"
  ["city_area"]=>
  string(31) "Северо-восточный"
  ["city_district"]=>
  string(37) "Северное Медведково"
  ["street"]=>
  string(18) "Сухонская"
  ["house"]=>
  string(2) "11"
  ["flat"]=>
  string(2) "89"
  ["flat_area"]=>
  string(4) "34.6"
  ["flat_price"]=>
  string(7) "6854710"
  ["fias_id"]=>
  string(36) "5ee84ac0-eb9a-4b42-b814-2f5f7c27c255"
  ["timezone"]=>
  string(5) "UTC+3"
  ["geo_lat"]=>
  string(10) "55.8782557"
  ["geo_lon"]=>
  string(8) "37.65372"
  ["qc_geo"]=>
  int(0)
  ["metro"]=>
  array(3) {...}
}

Same API method as "validate and cleanse":

> $response = $dadata->clean("address", "мск сухонская 11 89");
> var_dump($response);
array(80) {
  ["source"]=>
  string(31) "мск сухонская 11 89"
  ["result"]=>
  string(56) "г Москва, ул Сухонская, д 11, кв 89"
  ...
  ["geo_lat"]=>
  string(10) "55.8782557"
  ["geo_lon"]=>
  string(8) "37.65372"
  ["beltway_hit"]=>
  string(7) "IN_MKAD"
  ["beltway_distance"]=>
  NULL
  ["qc_geo"]=>
  int(0)
  ...
}
> $response = $dadata->geolocate("address", 55.878, 37.653);
> var_dump($response);
array(4) {
  [0]=>
  array(3) {
    ["value"]=>
    string(47) "г Москва, ул Сухонская, д 11"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(49) "г Москва, ул Сухонская, д 11А"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(47) "г Москва, ул Сухонская, д 13"
    ...
  }
  ...
}
> $response = $dadata->iplocate("46.226.227.20");
> var_dump($response);
array(3) {
  ["value"]=>
  string(21) "г Краснодар"
  ["unrestricted_value"]=>
  string(66) "350000, Краснодарский край, г Краснодар"
  ["data"]=>
  array(81) {
      ...
  }
}
> $response = $dadata->suggest("address", "самара метал");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(49) "г Самара, пр-кт Металлургов"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(44) "г Самара, ул Металлистов"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(95) "г Самара, поселок Зубчаниновка, ул Металлургическая"
    ...
  }
  ...
}

Show suggestions in English:

> $response = $dadata->suggest("address", "samara metal", 5, ["language" => "en"]);
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(42) "Russia, gorod Samara, prospekt Metallurgov"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(39) "Russia, gorod Samara, ulitsa Metallistov"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(69) "Russia, gorod Samara, poselok Zubchaninovka, ulitsa Metallurgicheskaya"
    ...
  }
  ...
}

Constrain by city (Yuzhno-Sakhalinsk):

> $locations = [[ "kladr_id" => "6500000100000" ]];
> $response = $dadata->suggest("address", "Ватутина", 5, ["locations" => $locations]);
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(53) "г Южно-Сахалинск, ул Ватутина"
    ...
  }
}

Constrain by specific geo point and radius (in Vologda city):

> $geo = [[ "lat" => 59.244634,  "lon" => 39.913355, "radius_meters" => 200 ]];
> $response = $dadata->suggest("address", "сухонская", 5, ["locations_geo" => $geo]);
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(42) "г Вологда, ул Сухонская"
    ...
  }
}

Boost city to top (Toliatti):

> $boost = [[ "kladr_id" => "6300000700000" ]];
> $response = $dadata->suggest("address", "авто", 5, ["locations_boost" => $boost]);
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(85) "Самарская обл, г Тольятти, Автозаводское шоссе"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(81) "Самарская обл, г Тольятти, ул Автомобилистов"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(81) "Самарская обл, г Тольятти, ул Автостроителей"
    ...
  }
  ...
}
> $response = $dadata->findById("address", "9120b43f-2fae-4838-a144-85e43c2bfb29");
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(36) "г Москва, ул Снежная"
    ...
  }
}

Find by KLADR ID:

> $response = $dadata->findById("address", "77000000000268400");

Suggest postal office by address or code:

> $response = $dadata->suggest("postal_unit", "дежнева 2а");
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(6) "127642"
    ["unrestricted_value"]=>
    string(52) "г Москва, проезд Дежнёва, д 2А"
    ["data"]=>
    array(15) {
        ...
    }
  }
}

Find postal office by code:

> $response = $dadata->findById("postal_unit", "127642");
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(6) "127642"
    ["unrestricted_value"]=>
    string(52) "г Москва, проезд Дежнёва, д 2А"
    ["data"]=>
    array(15) {
        ...
    }
  }
}

Find nearest postal office:

> $response = $dadata->geolocate("postal_unit", 55.878, 37.653, 1000);
> var_dump($response);
array(2) {
  [0]=>
  array(3) {
    ["value"]=>
    string(6) "127642"
    ["unrestricted_value"]=>
    string(52) "г Москва, проезд Дежнёва, д 2А"
    ["data"]=>
    array(15) {
        ...
    }
  },
  ...
}
> $response = $dadata->findById("delivery", "3100400100000");
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(13) "3100400100000"
    ["unrestricted_value"]=>
    string(36) "fe7eea4a-875a-4235-aa61-81c2a37a0440"
    ["data"]=>
    array(5) {
      ...
      ["boxberry_id"]=>
      string(5) "01929"
      ["cdek_id"]=>
      string(3) "344"
      ["dpd_id"]=>
      string(9) "196006461"
    }
  }
}
> $response = $dadata->findById("fias", "9120b43f-2fae-4838-a144-85e43c2bfb29");
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(36) "г Москва, ул Снежная"
    ...
  }
}
> $response = $dadata->suggest("country", "та");
> var_dump($response);
array(4) {
  [0]=>
  array(3) {
    ["value"]=>
    string(22) "Таджикистан"
    ...
  },
  [1]=>
  array(3) {
    ["value"]=>
    string(14) "Таиланд"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(14) "Тайвань"
    ...
  }
  ...
}

Company or individual enterpreneur

> $response = $dadata->findById("party", "7707083893");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(23) "ПАО СБЕРБАНК"
    ["unrestricted_value"]=>
    string(23) "ПАО СБЕРБАНК"
    ["data"]=>
    array(29) {
      ["kpp"]=>
      string(9) "773601001"
      ["inn"]=>
      string(10) "7707083893"
      ...
    }
  },
  ...
}

Find by INN and KPP:

> $response = $dadata->findById("party", "7707083893", 1, ["kpp" => "540602001"]);
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(51) "СИБИРСКИЙ БАНК ПАО СБЕРБАНК"
    ["unrestricted_value"]=>
    string(51) "СИБИРСКИЙ БАНК ПАО СБЕРБАНК"
    ["data"]=>
    array(29) {
      ["kpp"]=>
      string(9) "540602001"
      ["inn"]=>
      string(10) "7707083893"
      ...
    }
  }
}
> $response = $dadata->suggest("party", "сбер");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(23) "ПАО СБЕРБАНК"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(48) "АО "СБЕРЭНЕРГОСЕРВИС-ЮГРА""
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(27) "АО "СБЕРБРОКЕР""
    ...
  }
  ...
}

Constrain by specific regions (Saint Petersburg and Leningradskaya oblast):

> $locations = [[ "kladr_id" => "7800000000000" ], [ "kladr_id" => "4700000000000"]];
> $response = $dadata->suggest("party", "сбер", 5, ["locations" => $locations]);

Constrain by active companies:

> $status = [ "ACTIVE" ];
> $response = $dadata->suggest("party", "сбер", 5, ["status" => $status]);

Constrain by individual entrepreneurs:

> $response = $dadata->suggest("party", "сбер", 5, ["type" => "INDIVIDUAL"]);

Constrain by head companies, no branches:

> $branch_type = [ "MAIN" ];
> $response = $dadata->suggest("party", "сбер", 5, ["branch_type" => $branch_type]);
> $response = $dadata->findAffiliated("7736207543");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(36) "ООО "ДЗЕН.ПЛАТФОРМА""
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(21) "ООО "ЕДАДИЛ""
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(21) "ООО "ЗНАНИЕ""
    ...
  }
  ...
}

Search only by manager INN:

> $response = $dadata->findAffiliated("773006366201", 5, ["scope" => "MANAGERS"]);
> var_dump($response);
array(3) {
  [0]=>
  array(3) {
    ["value"]=>
    string(21) "ООО "ЯНДЕКС""
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(13) "МФ "ФОИ""
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(22) "АНО ДПО "ШАД""
    ...
  }
}

Bank

> $response = $dadata->findById("bank", "044525225");
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(23) "ПАО Сбербанк"
    ["unrestricted_value"]=>
    string(23) "ПАО Сбербанк"
    ["data"]=>
    array(14) {
       ["bic"]=>
      string(9) "044525225"
      ["swift"]=>
      string(8) "SABRRUMM"
      ["inn"]=>
      string(10) "7707083893"
      ...
    }
  }
}

Find by SWIFT code:

> $response = $dadata->findById("bank", "SABRRUMM");

Find by INN:

> $response = $dadata->findById("bank", "7728168971");

Find by INN and KPP:

> $response = $dadata->findById("bank", "7728168971", 1, ["kpp" => "667102002"]);

Find by registration number:

> $response = $dadata->findById("bank", "1481");
> $response = $dadata->suggest("bank", "ти");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(28) "АО «Тимер Банк»"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(34) "АО «Тинькофф Банк»"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(65) "«Азиатско-Тихоокеанский Банк» (ПАО)"
    ...
  }
  ...
}

Personal name

> $response = $dadata->clean("name", "Срегей владимерович иванов");
> var_dump($response);
array(10) {
  ["source"]=>
  string(50) "Срегей владимерович иванов"
  ["result"]=>
  ...
  ["surname"]=>
  string(12) "Иванов"
  ["name"]=>
  string(12) "Сергей"
  ["patronymic"]=>
  string(24) "Владимирович"
  ["gender"]=>
  string(2) "М"
  ["qc"]=>
  int(1)
}
> $response = $dadata->suggest("fio", "викт");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(12) "Виктор"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(16) "Виктория"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(18) "Викторова"
    ...
  }
  ...
}

Suggest female first name:

> $filter = ["parts" => ["NAME"], gender => "FEMALE"];
> $response = $dadata->suggest("fio", "викт", 5, $filter);
> var_dump($response);
array(2) {
  [0]=>
  array(3) {
    ["value"]=>
    string(16) "Виктория"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(18) "Викторина"
    ...
  }
}

Phone

> $response = $dadata->clean("phone", "9168-233-454");
> var_dump($response);
array(14) {
  ["source"]=>
  string(12) "9168-233-454"
  ["type"]=>
  string(18) "Мобильный"
  ["phone"]=>
  string(16) "+7 916 823-34-54"
  ...
  ["provider"]=>
  string(50) "ПАО "Мобильные ТелеСистемы""
  ["country"]=>
  string(12) "Россия"
  ["region"]=>
  string(51) "Москва и Московская область"
  ["timezone"]=>
  string(5) "UTC+3"
  ["qc"]=>
  int(0)
}

Passport

> $response = $dadata->clean("passport", "4509 235857");
> var_dump($response);
array(4) {
  ["source"]=>
  string(11) "4509 235857"
  ["series"]=>
  string(5) "45 09"
  ["number"]=>
  string(6) "235857"
  ["qc"]=>
  int(0)
}
> $response = $dadata->suggest("fms_unit", "772 053");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(36) "ОВД ЗЮЗИНО Г. МОСКВЫ"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(68) "ОВД ЗЮЗИНО Г. МОСКВЫ ПАСПОРТНЫЙ СТОЛ 1"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(57) "ОВД ЗЮЗИНО ПС УВД ЮЗАО Г. МОСКВЫ"
    ...
  }
  ...
}

Email

> $response = $dadata->clean("email", "serega@yandex/ru");
> var_dump($response);
array(6) {
  ["source"]=>
  string(16) "serega@yandex/ru"
  ["email"]=>
  string(16) "[email protected]"
  ["local"]=>
  string(6) "serega"
  ["domain"]=>
  string(9) "yandex.ru"
  ["type"]=>
  string(8) "PERSONAL"
  ["qc"]=>
  int(4)
}
> $response = $dadata->suggest("email", "maria@");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(13) "[email protected]"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(15) "[email protected]"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(15) "[email protected]"
    ...
  }
  ...
}

Other datasets

> $response = $dadata->findById("fns_unit", "5257");
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(118) "Инспекция ФНС России по Канавинскому району г.Нижнего Новгорода"
    ["unrestricted_value"]=>
    string(118) "Инспекция ФНС России по Канавинскому району г.Нижнего Новгорода"
    ["data"]=>
    array(18) {
      ["code"]=>
      string(4) "5257"
      ["oktmo"]=>
      string(8) "22701000"
      ["inn"]=>
      string(10) "5257046101"
      ["kpp"]=>
      string(9) "525701001"
      ...
    }
  }
}
> $response = $dadata->suggest("region_court", "таганско");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(109) "Судебный участок № 371 Таганского судебного района г. Москвы"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(109) "Судебный участок № 372 Таганского судебного района г. Москвы"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(109) "Судебный участок № 373 Таганского судебного района г. Москвы"
    ...
  }
  ...
}
> $response = $dadata->suggest("metro", "алекс");
> var_dump($response);
array(4) {
  [0]=>
  array(3) {
    ["value"]=>
    string(37) "Александровский сад"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(24) "Алексеевская"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(54) "Площадь Александра Невского 1"
    ...
  }
  ...
}

Constrain by city (Saint Petersburg):

> $filters = [[ "city" => "Санкт-Петербург" ]];
> $response = $dadata->suggest("metro", "алекс", 5, ["filters" => $filters]);
> var_dump($response);
array(2) {
  [0]=>
  array(3) {
    ["value"]=>
    string(54) "Площадь Александра Невского 1"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(54) "Площадь Александра Невского 2"
    ...
  }
}
> $response = $dadata->suggest("car_brand", "фо");
> var_dump($response);
array(3) {
  [0]=>
  array(3) {
    ["value"]=>
    string(10) "Volkswagen"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(4) "Ford"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(5) "Foton"
    ...
  }
}
> $response = $dadata->suggest("currency", "руб");
> var_dump($response);
array(2) {
  [0]=>
  array(3) {
    ["value"]=>
    string(33) "Белорусский рубль"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(31) "Российский рубль"
    ...
  }
}
> $response = $dadata->suggest("okved2", "космических");
> var_dump($response);
array(5) {
  [0]=>
  array(3) {
    ["value"]=>
    string(139) "Производство космических аппаратов (в том числе спутников), ракет-носителей"
    ...
  }
  [1]=>
  array(3) {
    ["value"]=>
    string(139) "Производство частей и принадлежностей летательных и космических аппаратов"
    ...
  }
  [2]=>
  array(3) {
    ["value"]=>
    string(95) "Производство автоматических космических аппаратов"
    ...
  }
  ...
}
> $response = $dadata->suggest("okpd2", "калоши");
> var_dump($response);
array(1) {
  [0]=>
  array(3) {
    ["value"]=>
    string(91) "Услуги по обрезинованию валенок (рыбацкие калоши)"
    ...
  }
}

Profile API

Balance:

> $response = $dadata->getBalance();
> var_dump($response);
float(8238.20)

Usage stats:

> $response = $dadata->getDailyStats();
> var_dump($response);
array(2) {
  ["date"]=>
  string(10) "2020-07-27"
  ["services"]=>
  array(3) {
    ["merging"]=>
    int(0)
    ["suggestions"]=>
    int(45521)
    ["clean"]=>
    int(1200)
  }
}

Dataset versions:

> $response = $dadata->getVersions();
> var_dump($response);
array(3) {
  ["dadata"]=>
  array(1) {
    ["version"]=>
    string(26) "stable (9048:bf33b2acc8ba)"
  }
  ["suggestions"]=>
  array(2) {
    ["version"]=>
    string(15) "20.5 (b55eb7c4)"
    ["resources"]=>
    array(4) {
      ...
    }
  }
  ["factor"]=>
  array(2) {
    ["version"]=>
    string(16) "20.06 (eb70078e)"
    ["resources"]=>
    array(8) {
      ...
    }
  }
}

Development setup

$ composer install
$ ./vendor/bin/phpunit tests

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Make sure to add or update tests as appropriate.

Use Conventional Commits for commit messages.

This library uses CalVer with YY.MM.MICRO schema. See changelog for details specific to each release.

License

MIT

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Data cleansing, enrichment and suggestions via Dadata API

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