YELP Extractor 2.0 π§
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YELP Extractor 2.0 π§
jupri/yelp
Try for free
7 days trial then $30.00/month - No credit card required now
β΄οΈ Scrape Business data from Yelp.com
You can access the YELP Extractor 2.0 π§ programmatically from your own applications by using the Apify API. You can choose the language preference from below. To use the Apify API, youβll need an Apify account and your API token, found in Integrations settings in Apify Console.
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1494 ],
1495 "type": "string",
1496 "description": ""
1497 },
1498 "sort": {
1499 "title": "π Sorting",
1500 "enum": [
1501 "recommended",
1502 "rating",
1503 "review_count"
1504 ],
1505 "type": "string",
1506 "description": ""
1507 },
1508 "include_media": {
1509 "title": "Fetch Media",
1510 "type": "integer",
1511 "description": "π‘ Number of media"
1512 },
1513 "media_category": {
1514 "title": "Media Category",
1515 "type": "string",
1516 "description": "π‘ Fetch only specific media group/tab. <i><code>(examples: \"food\" or \"interior\")</code></i>"
1517 },
1518 "media_group": {
1519 "title": "Media Grouping",
1520 "type": "boolean",
1521 "description": ""
1522 },
1523 "include_reviews": {
1524 "title": "Fetch Reviews",
1525 "type": "integer",
1526 "description": "π‘ Number of review"
1527 },
1528 "reviews_search": {
1529 "title": "Search",
1530 "type": "string",
1531 "description": "π‘ Search reviews."
1532 },
1533 "reviews_sort": {
1534 "title": "Sort",
1535 "enum": [
1536 "relevance_desc",
1537 "date_desc",
1538 "date_asc",
1539 "rating_desc",
1540 "rating_asc",
1541 "elites_desc"
1542 ],
1543 "type": "string",
1544 "description": ""
1545 },
1546 "reviews_rating": {
1547 "title": "Rating",
1548 "enum": [
1549 "5",
1550 "4",
1551 "3",
1552 "2",
1553 "1"
1554 ],
1555 "type": "string",
1556 "description": ""
1557 },
1558 "include_question": {
1559 "title": "Fetch Questions",
1560 "type": "integer",
1561 "description": "π‘ Number of question"
1562 },
1563 "question_sort": {
1564 "title": "Sort",
1565 "enum": [
1566 "recommended",
1567 "best",
1568 "most_answered"
1569 ],
1570 "type": "string",
1571 "description": ""
1572 },
1573 "include_tips": {
1574 "title": "Fetch Quick-Tips",
1575 "type": "integer",
1576 "description": "π‘ Number of quicktips"
1577 },
1578 "include_rating": {
1579 "title": "Rating Counts",
1580 "type": "boolean",
1581 "description": "π‘ Rating counts"
1582 },
1583 "dev_proxy_config": {
1584 "title": "π PROXY NETWORKING",
1585 "type": "object",
1586 "description": "π‘ <b>Supported protocol:</b><br><br><b>HTTP(S), SOCKS5</b><br><code>{http|socks5}://{user:pass}@{hostname|ip-address}:port</code><br><br><b>Example</b>: <code>socks5://example.com:9000</code>"
1587 },
1588 "dev_custom_headers": {
1589 "title": "π HTTP HEADERS",
1590 "type": "array",
1591 "description": "π‘ Additional HTTP Headers",
1592 "items": {
1593 "type": "object",
1594 "required": [
1595 "key",
1596 "value"
1597 ],
1598 "properties": {
1599 "key": {
1600 "type": "string",
1601 "title": "Key"
1602 },
1603 "value": {
1604 "type": "string",
1605 "title": "Value"
1606 }
1607 }
1608 }
1609 },
1610 "dev_custom_cookies": {
1611 "title": "π° HTTP COOKIES",
1612 "type": "array",
1613 "description": "π‘ Additional HTTP Cookies",
1614 "items": {
1615 "type": "object",
1616 "required": [
1617 "key",
1618 "value"
1619 ],
1620 "properties": {
1621 "key": {
1622 "type": "string",
1623 "title": "Key"
1624 },
1625 "value": {
1626 "type": "string",
1627 "title": "Value"
1628 }
1629 }
1630 }
1631 },
1632 "dev_transform_fields": {
1633 "title": "β»οΈ CUSTOM FIELD",
1634 "type": "array",
1635 "description": "π‘ <b>Transform the resulting output. Select only needed fields.</b><br><br>For nested object use <b>DOT</b>. For example: <pre>address.streetAddress</pre><br>For nested array use <b>NUMBER</b> <i>(index of array element starting from index=0)</i>. For example: <pre>images.0.url</pre>",
1636 "items": {
1637 "type": "object",
1638 "required": [
1639 "key",
1640 "value"
1641 ],
1642 "properties": {
1643 "key": {
1644 "type": "string",
1645 "title": "Key"
1646 },
1647 "value": {
1648 "type": "string",
1649 "title": "Value"
1650 }
1651 }
1652 }
1653 },
1654 "dev_dataset_name": {
1655 "title": "π CUSTOM STORAGE",
1656 "type": "string",
1657 "description": "π‘ <b>Save results into custom named Dataset, use mask to customize dataset name</b><br><br><code>{ACTOR} = actor name<br>{DATE} = date (YYYYMMDD)<br>{TIME} = time (HHMMSS)</code><br><br>This masks can be used to autogenerate Dataset Name.<br><br>example: <i><code>data-{DATE}</code></i><br>Depending on today date the dataset name will be: <code>data-20230603</code><i><br><br>default: <code>data-{ACTOR}-{DATE}-{TIME}</code></i>"
1658 },
1659 "dev_dataset_clear": {
1660 "title": "Clear Storage",
1661 "type": "boolean",
1662 "description": "Clear Dataset before insert/update."
1663 },
1664 "dev_no_strip": {
1665 "title": "Disable data cleansing",
1666 "type": "boolean",
1667 "description": "π‘ Keep/Save empty values <i><code>(NULL, FALSE, empty ARRAY, empty OBJECT, empty STRING)</code></i>"
1668 }
1669 }
1670 },
1671 "runsResponseSchema": {
1672 "type": "object",
1673 "properties": {
1674 "data": {
1675 "type": "object",
1676 "properties": {
1677 "id": {
1678 "type": "string"
1679 },
1680 "actId": {
1681 "type": "string"
1682 },
1683 "userId": {
1684 "type": "string"
1685 },
1686 "startedAt": {
1687 "type": "string",
1688 "format": "date-time",
1689 "example": "2025-01-08T00:00:00.000Z"
1690 },
1691 "finishedAt": {
1692 "type": "string",
1693 "format": "date-time",
1694 "example": "2025-01-08T00:00:00.000Z"
1695 },
1696 "status": {
1697 "type": "string",
1698 "example": "READY"
1699 },
1700 "meta": {
1701 "type": "object",
1702 "properties": {
1703 "origin": {
1704 "type": "string",
1705 "example": "API"
1706 },
1707 "userAgent": {
1708 "type": "string"
1709 }
1710 }
1711 },
1712 "stats": {
1713 "type": "object",
1714 "properties": {
1715 "inputBodyLen": {
1716 "type": "integer",
1717 "example": 2000
1718 },
1719 "rebootCount": {
1720 "type": "integer",
1721 "example": 0
1722 },
1723 "restartCount": {
1724 "type": "integer",
1725 "example": 0
1726 },
1727 "resurrectCount": {
1728 "type": "integer",
1729 "example": 0
1730 },
1731 "computeUnits": {
1732 "type": "integer",
1733 "example": 0
1734 }
1735 }
1736 },
1737 "options": {
1738 "type": "object",
1739 "properties": {
1740 "build": {
1741 "type": "string",
1742 "example": "latest"
1743 },
1744 "timeoutSecs": {
1745 "type": "integer",
1746 "example": 300
1747 },
1748 "memoryMbytes": {
1749 "type": "integer",
1750 "example": 1024
1751 },
1752 "diskMbytes": {
1753 "type": "integer",
1754 "example": 2048
1755 }
1756 }
1757 },
1758 "buildId": {
1759 "type": "string"
1760 },
1761 "defaultKeyValueStoreId": {
1762 "type": "string"
1763 },
1764 "defaultDatasetId": {
1765 "type": "string"
1766 },
1767 "defaultRequestQueueId": {
1768 "type": "string"
1769 },
1770 "buildNumber": {
1771 "type": "string",
1772 "example": "1.0.0"
1773 },
1774 "containerUrl": {
1775 "type": "string"
1776 },
1777 "usage": {
1778 "type": "object",
1779 "properties": {
1780 "ACTOR_COMPUTE_UNITS": {
1781 "type": "integer",
1782 "example": 0
1783 },
1784 "DATASET_READS": {
1785 "type": "integer",
1786 "example": 0
1787 },
1788 "DATASET_WRITES": {
1789 "type": "integer",
1790 "example": 0
1791 },
1792 "KEY_VALUE_STORE_READS": {
1793 "type": "integer",
1794 "example": 0
1795 },
1796 "KEY_VALUE_STORE_WRITES": {
1797 "type": "integer",
1798 "example": 1
1799 },
1800 "KEY_VALUE_STORE_LISTS": {
1801 "type": "integer",
1802 "example": 0
1803 },
1804 "REQUEST_QUEUE_READS": {
1805 "type": "integer",
1806 "example": 0
1807 },
1808 "REQUEST_QUEUE_WRITES": {
1809 "type": "integer",
1810 "example": 0
1811 },
1812 "DATA_TRANSFER_INTERNAL_GBYTES": {
1813 "type": "integer",
1814 "example": 0
1815 },
1816 "DATA_TRANSFER_EXTERNAL_GBYTES": {
1817 "type": "integer",
1818 "example": 0
1819 },
1820 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
1821 "type": "integer",
1822 "example": 0
1823 },
1824 "PROXY_SERPS": {
1825 "type": "integer",
1826 "example": 0
1827 }
1828 }
1829 },
1830 "usageTotalUsd": {
1831 "type": "number",
1832 "example": 0.00005
1833 },
1834 "usageUsd": {
1835 "type": "object",
1836 "properties": {
1837 "ACTOR_COMPUTE_UNITS": {
1838 "type": "integer",
1839 "example": 0
1840 },
1841 "DATASET_READS": {
1842 "type": "integer",
1843 "example": 0
1844 },
1845 "DATASET_WRITES": {
1846 "type": "integer",
1847 "example": 0
1848 },
1849 "KEY_VALUE_STORE_READS": {
1850 "type": "integer",
1851 "example": 0
1852 },
1853 "KEY_VALUE_STORE_WRITES": {
1854 "type": "number",
1855 "example": 0.00005
1856 },
1857 "KEY_VALUE_STORE_LISTS": {
1858 "type": "integer",
1859 "example": 0
1860 },
1861 "REQUEST_QUEUE_READS": {
1862 "type": "integer",
1863 "example": 0
1864 },
1865 "REQUEST_QUEUE_WRITES": {
1866 "type": "integer",
1867 "example": 0
1868 },
1869 "DATA_TRANSFER_INTERNAL_GBYTES": {
1870 "type": "integer",
1871 "example": 0
1872 },
1873 "DATA_TRANSFER_EXTERNAL_GBYTES": {
1874 "type": "integer",
1875 "example": 0
1876 },
1877 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
1878 "type": "integer",
1879 "example": 0
1880 },
1881 "PROXY_SERPS": {
1882 "type": "integer",
1883 "example": 0
1884 }
1885 }
1886 }
1887 }
1888 }
1889 }
1890 }
1891 }
1892 }
1893}Yelp.com Scraper OpenAPI definition
OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for YELP Extractor 2.0 π§ from the options below:
If youβd like to learn more about how OpenAPI powers GPTs, read our blog post.
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