API使我們能夠從服務器發(fā)出檢索數據的請求。API在許多方面都很有用，但其中之一是能夠為數據科學項目創(chuàng)建唯一的數據集。在本教程中，我們將學習一些用于Last.fm API的高級技術。
在我們的初學者大數據分析Python API教程中，我們使用了一個簡單的API，非常適合教授基礎知識：
a.它具有一些易于理解的終點。
b.因為它不需要身份驗證，所以我們不必擔心如何告訴API我們有權使用它。
c.每個端點響應的數據都很小，并且結構易于理解。
實際上，大多數API都比這更復雜，因此要使用它們，您需要了解一些更高級的概念。具體來說，我們將學習：
a.如何使用API??密鑰進行身份驗證。
b.如何使用速率限制和其他技術在API準則內工作。
c.如何使用分頁處理較大的響應。
本教程假定您了解使用大數據分析Python使用API??的基礎知識。如果您不這樣做，我們建議您開始我們的初學者API教程。我們還假設您具有大數據分析Python和pandas的中級知識。如果您不這樣做，則可以通過我們的大數據分析Python基礎課程免費開始學習。
使用Last.fm API
我們將使用Last.fm API。Last.fm是一項音樂服務，可通過連接到iTunes，Spotify等類似的音樂流應用程序并跟蹤您聽的音樂來建立個人資料。
他們提供對API的免費訪問權，以便音樂服務可以向其發(fā)送數據，還可以提供終結點，以匯總Last.fm在各種藝術家，歌曲和流派上擁有的所有數據。我們將使用他們的API建立熱門藝術家的數據集。
遵循API準則
使用API??時，請務必遵循其準則。如果您不這樣做，則可能會被禁止使用該API。除此之外，特別是當一家公司免費提供API時，請尊重他們的限制和準則，因為他們沒有提供任何東西。
查看API文檔中的Introduction頁面，我們會注意到一些重要的準則：
請在所有請求上使用可識別的User-Agent標頭。這有助于我們進行日志記錄，并減少被禁止的風險。
向last.fm API發(fā)出請求時，可以使用headers標識自己。Last.fm希望我們在標頭中指定一個用戶代理，以便他們知道我們是誰。我們將在稍后提出第一個請求時學習如何執(zhí)行此操作。
在確定要撥打多少次電話時，請使用常識。例如，如果要制作Web應用程序，請嘗試不要在頁面加載時點擊API。如果您的應用程序每秒持續(xù)撥打多個電話，則您的帳戶可能會被暫停。
為了構建我們的數據集，我們將需要向Last.fm API發(fā)出數千個請求。盡管他們沒有在文檔中提供具體的限制，但他們確實建議我們不要持續(xù)每秒進行多次呼叫。在本教程中，我們將學習一些限制速率的策略，或者確保我們不會過多使用它們的API，以便避免被禁止。
在發(fā)出第一個請求之前，我們需要學習如何使用Last.fm API進行身份驗證
使用API??密鑰進行身份驗證
大多數API都要求您進行身份驗證，以便他們知道您有權使用它們。身份驗證的最常見形式之一是使用API密鑰，就像使用其API的密碼一樣。如果在發(fā)出請求時未提供API密鑰，則會出現錯誤。
使用API??密鑰的過程如下：
a.您使用API??的提供者創(chuàng)建一個帳戶。
b.您需要一個API密鑰，該密鑰通常是一個長字符串，例如54686973206973206d7920415049204b6579。
c.您可以將API密鑰記錄在安全的地方，例如密碼保存器。如果有人獲得了您的API密鑰，那么他們可以使用偽裝成您的API。
d.每次發(fā)出請求時，您都提供API密鑰以進行身份??驗證。
要獲取Last.fm的API密鑰，請先創(chuàng)建一個帳戶。創(chuàng)建帳戶后，應轉到以下表格：
在每個字段中填寫有關您計劃如何使用API??的信息。您可以將“回調URL”字段保留為空白，因為僅當您正在構建要驗證為特定Last.fm用戶的Web應用程序時才使用此字段。
提交表單后，您將獲得API密鑰和共享密鑰的詳細信息：
請在安全的地方記下這些內容-本教程無需使用共享密鑰，但最好記下它，以防萬一您想做一些需要您作為特定用戶進行身份驗證的事情。
發(fā)出我們的第一個API請求
為了創(chuàng)建熱門藝術家的數據集，我們將使用chart.getTopArtists端點。
查看Last.fm API文檔，我們可以觀察到以下幾點：
a.看起來只有一個真實的端點，并且實際上每個“端點”都是使用method參數指定的。
b.文檔說此服務不需要身份驗證。盡管起初看起來似乎有些混亂，但它告訴我們的是，我們不需要身份驗證為特定的Last.fm用戶。如果您在此之上看，您會發(fā)現我們確實需要提供我們的API密鑰。
c.API可以返回多種格式的結果-我們將指定JSON，以便我們可以利用我們在大數據分析Python中使用API??的已知知識
在開始之前，請記住，當我們發(fā)出請求時，我們需要提供一個用戶代理標頭來標識自己。使用大數據分析Python請求庫，我們使用headers參數和標頭字典來指定標頭，如下所示：
我們將從定義API密鑰和用戶代理開始(本教程中顯示的API密鑰不是真正的API密鑰!)
接下來，我們將導入請求庫，為標頭和參數創(chuàng)建字典，然后發(fā)出第一個請求!
我們的請求返回的狀態(tài)碼為“ 200”，因此我們知道成功了。
在查看請求返回的數據之前，請考慮一下在本教程中我們將發(fā)出許多請求的事實。在這些請求中，許多功能將是相同的：
a.我們將使用相同的URL
b.我們將使用相同的API密鑰
c.我們將指定JSON作為我們的格式。
d.我們將使用相同的標題。
為了節(jié)省時間，我們將創(chuàng)建一個函數來為我們完成很多工作。我們將為該函數提供一個有效負載字典，然后將額外的鍵添加到該字典，并將其與其他選項一起傳遞以發(fā)出請求。
讓我們看一下該函數的外觀：
正如我們在初學者大數據分析Python API教程中所了解的那樣，大多數API都以JSON格式返回數據，并且我們可以使用大數據分析Python json模塊以更易于理解的格式打印JSON數據。
讓我們重新使用jprint()在該教程中創(chuàng)建的函數，并打印來自API的響應：
{
"artists": {
"@attr": {
"page": "1",
"perPage": "50",
"total": "2901036",
"totalPages": "58021"
},
"artist": [
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "1957174",
"mbid": "b7539c32-53e7-4908-bda3-81449c367da6",
"name": "Lana Del Rey",
"playcount": "232808939",
"streamable": "0",
"url": "https://www.last.fm/music/Lana+Del+Rey"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "588883",
"mbid": "",
"name": "Billie Eilish",
"playcount": "35520548",
"streamable": "0",
"url": "https://www.last.fm/music/Billie+Eilish"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "655052",
"mbid": "",
"name": "Post Malone",
"playcount": "34942708",
"streamable": "0",
"url": "https://www.last.fm/music/Post+Malone"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "2290993",
"mbid": "20244d07-534f-4eff-b4d4-930878889970",
"name": "Taylor Swift",
"playcount": "196907702",
"streamable": "0",
"url": "https://www.last.fm/music/Taylor+Swift"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "1166180",
"mbid": "f4fdbb4c-e4b7-47a0-b83b-d91bbfcfa387",
"name": "Ariana Grande",
"playcount": "124251766",
"streamable": "0",
"url": "https://www.last.fm/music/Ariana+Grande"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "1716587",
"mbid": "b8a7c51f-362c-4dcb-a259-bc6e0095f0a6",
"name": "Ed Sheeran",
"playcount": "92646726",
"streamable": "0",
"url": "https://www.last.fm/music/Ed+Sheeran"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "4084524",
"mbid": "420ca290-76c5-41af-999e-564d7c71f1a7",
"name": "Queen",
"playcount": "197850122",
"streamable": "0",
"url": "https://www.last.fm/music/Queen"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "4449534",
"mbid": "164f0d73-1234-4e2c-8743-d77bf2191051",
"name": "Kanye West",
"playcount": "250533444",
"streamable": "0",
"url": "https://www.last.fm/music/Kanye+West"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "3732023",
"mbid": "b10bbbfc-cf9e-42e0-be17-e2c3e1d2600d",
"name": "The Beatles",
"playcount": "526866107",
"streamable": "0",
"url": "https://www.last.fm/music/The+Beatles"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "3441963",
"mbid": "b49b81cc-d5b7-4bdd-aadb-385df8de69a6",
"name": "Drake",
"playcount": "147881092",
"streamable": "0",
"url": "https://www.last.fm/music/Drake"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "4778856",
"mbid": "a74b1b7f-71a5-4011-9441-d0b5e4122711",
"name": "Radiohead",
"playcount": "507682999",
"streamable": "0",
"url": "https://www.last.fm/music/Radiohead"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
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"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "4019451",
"mbid": "f59c5520-5f46-4d2c-b2c4-822eabf53419",
"name": "Linkin Park",
"playcount": "299550825",
"streamable": "0",
"url": "https://www.last.fm/music/Linkin+Park"
},
{
"image": [
{
"#text": "https://lastfm-img2.akamaized.net/i/u/34s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "small"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/64s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "medium"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/174s/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "large"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "extralarge"
},
{
"#text": "https://lastfm-img2.akamaized.net/i/u/300x300/2a96cbd8b46e442fc41c2b86b821562f.png",
"size": "mega"
}
],
"listeners": "487567",
"mbid": "c6bfb05d-f570-46c8-98e1-e25441189770",
"name": "Khalid",
"playcount": "15759258",
"streamable": "0",
"url": "https://www.last.fm/music/Khalid"
}
]
}
}
JSON響應的結構為：
1)具有單個artists鍵的字典，其中包含：
2)@attr包含許多有關響應的屬性 的鍵。
3)artist包含藝術家對象列表 的鍵。
讓我們單獨看一下'@attr'(屬性)鍵：
這個API端點的結果中總共有近三百萬位藝術家，我們正在單個頁面中顯示前50位藝術家。將結果分布在多個頁面上的技術稱為分頁。
處理分頁數據
為了建立包含許多藝術家的數據集，我們需要為每個頁面提出一個API請求，然后將它們放在一起。我們可以使用文檔中指定的兩個可選參數來控制結果的分頁：
1)limit：每頁要提取的結果數(默認為50)。
2)page：我們要獲取結果的哪一頁。
因為'@attrs'鍵為我們提供了總頁數，所以我們可以使用while循環(huán)并在頁面上進行迭代，直到頁面號等于最后一個頁面號為止。
我們還可以使用limit參數在每個頁面中獲取更多結果-我們將在每個頁面中獲取500個結果，因此我們只需要進行約6,000次調用，而無需進行約60,000次調用。
讓我們看一下如何構造代碼的示例：
正如我們剛才提到的，我們需要為此端點進行近6,000次調用，這意味著我們需要考慮速率限制以符合Last.fm API的服務條款。讓我們看一些方法。
限速
速率限制是使用代碼來限制我們達到特定API的每秒次數。速率限制將使您的代碼變慢，但是比完全禁止使用API??更好。
執(zhí)行速率限制的最簡單方法是使用大數據分析Python time.sleep()函數。此函數接受一個浮點數，該浮點數指定要等待的秒數，然后再繼續(xù)操作。
例如，以下代碼將在兩個打印語句之間等待四分之一秒：
因為進行API調用本身需要一些時間，所以我們很可能每秒要進行2到3次調用，而不是每秒休眠0.25秒所建議的4次調用。這足以使我們保持在Last.fm的閾值以下(如果我們要打他們的API數小時，我們可能會選擇一個更低的速率)。
另一種對速率限制有用的技術是使用本地數據庫來緩存任何API調用的結果，因此，如果我們兩次進行相同的調用，則第二次從本地緩存中讀取它。想象一下，在編寫代碼時，您發(fā)現語法錯誤并且循環(huán)失敗，因此您必須重新開始。通過使用本地緩存，您有兩個好處：
a.您無需進行不必要的額外API調用。
b.從緩存中讀取重復的調用時，無需等待額外的時間進行速率限制。
我們可以用來結合等待和緩存的邏輯如下所示：
為本地緩存創(chuàng)建邏輯是一項相當復雜的任務，但是有一個很棒的庫稱為requests-cache，該庫只需幾行代碼即可為您完成所有工作。
您可以使用pip安裝請求緩存：
然后，我們要做的就是導入庫并調用requests_cache.install_cache()函數，該庫將透明地緩存新的API請求，并在每次重復調用時都使用該緩存。
我們應該考慮的最后一件事是，我們的6,000個請求可能會花費大約30分鐘的時間，因此，我們將在每個循環(huán)中打印一些輸出，以便可以看到所有內容。我們將使用I大數據分析Python顯示技巧在每次運行后清除輸出，以便使筆記本中的內容看起來更整潔。
讓我們開始吧!
import time
from I大數據分析Python.core.display import clear_output
responses = []
page = 1
total_pages = 99999 # this is just a dummy number so the loop starts
while page < = total_pages:
payload = {
'method': 'chart.gettopartists',
'limit': 500,
'page': page
}
# print some output so we can see the status
print("Requesting page {}/{}".format(page, total_pages))
# clear the output to make things neater
clear_output(wait = True)
# make the API call
response = lastfm_get(payload)
# if we get an error, print the response and halt the loop
if response.status_code != 200:
print(response.text)
break
# extract pagination info
page = int(response.json()['artists']['@attr']['page'])
total_pages = int(response.json()['artists']['@attr']['totalPages'])
# append response
responses.append(response)
# if it's not a cached result, sleep
if not getattr(response, 'from_cache', False):
time.sleep(0.25)
# increment the page number
page += 1
Requesting page 5803/5803
第一次運行該代碼，大約需要半個小時。由于存在緩存，第二次會更快(可能不到一分鐘!)
處理數據
讓我們使用熊貓來查看responses列表中第一個響應的數據：
我們可以使用列表推導對的每個響應執(zhí)行此操作responses，為我們提供數據幀列表，然后使用該pandas.concat()函數將數據幀列表轉換為單個數據幀。
我們的下一步將是刪除圖像列，其中包含藝術家圖像的URL，從分析的角度來看，這些URL對我們并沒有真正幫助。
現在，讓我們使用DataFrame.info()和了解一些數據DataFrame.describe()：
我們原本希望有3,000,000名藝術家，但我們只有10,500名。其中只有10,000個是唯一的(例如，有重復項)。
讓我們在響應對象列表中查看藝術家列表的長度，以了解是否可以更好地了解出了什么問題。
看起來我們的請求中只有20個具有響應列表-讓我們按順序查看前50個，看看是否有某種模式。
看起來在前20個響應之后，此API不會返回任何數據-未記錄的限制。
這不是世界末日，因為10,000名藝術家仍然是大量數據。讓我們擺脫前面檢測到的重復項。
使用第二個Last.fm API端點增強數據
為了使我們的數據更有趣，讓我們使用另一個last.fm API端點來添加有關每個藝術家的一些額外數據。
Last.fm允許其用戶創(chuàng)建“標簽”以對藝術家進行分類。通過使用artist.getTopTags端點，我們可以從單個藝術家那里獲得頂級標簽。
讓我們以我們的一位藝術家為例，查看該端點的響應：
{
"toptags": {
"@attr": {
"artist": "Lana Del Rey"
},
"tag": [
{
"count": 100,
"name": "female vocalists",
"url": "https://www.last.fm/tag/female+vocalists"
},
{
"count": 93,
"name": "indie",
"url": "https://www.last.fm/tag/indie"
},
{
"count": 88,
"name": "indie pop",
"url": "https://www.last.fm/tag/indie+pop"
},
{
"count": 80,
"name": "pop",
"url": "https://www.last.fm/tag/pop"
},
{
"count": 67,
"name": "alternative",
"url": "https://www.last.fm/tag/alternative"
},
{
"count": 14,
"name": "american",
"url": "https://www.last.fm/tag/american"
},
{
"count": 13,
"name": "dream pop",
"url": "https://www.last.fm/tag/dream+pop"
},
{
"count": 12,
"name": "seen live",
"url": "https://www.last.fm/tag/seen+live"
},
{
"count": 10,
"name": "singer-songwriter",
"url": "https://www.last.fm/tag/singer-songwriter"
},
{
"count": 10,
"name": "trip-hop",
"url": "https://www.last.fm/tag/trip-hop"
},
{
"count": 7,
"name": "cult",
"url": "https://www.last.fm/tag/cult"
},
{
"count": 7,
"name": "sadcore",
"url": "https://www.last.fm/tag/sadcore"
},
{
"count": 7,
"name": "legend",
"url": "https://www.last.fm/tag/legend"
},
{
"count": 6,
"name": "Lana Del Rey",
"url": "https://www.last.fm/tag/Lana+Del+Rey"
},
{
"count": 6,
"name": "chamber pop",
"url": "https://www.last.fm/tag/chamber+pop"
},
{
"count": 5,
"name": "baroque pop",
"url": "https://www.last.fm/tag/baroque+pop"
},
{
"count": 4,
"name": "female vocalist",
"url": "https://www.last.fm/tag/female+vocalist"
},
{
"count": 4,
"name": "alternative pop",
"url": "https://www.last.fm/tag/alternative+pop"
},
{
"count": 4,
"name": "Retro",
"url": "https://www.last.fm/tag/Retro"
},
{
"count": 3,
"name": "art pop",
"url": "https://www.last.fm/tag/art+pop"
},
{
"count": 3,
"name": "chillout",
"url": "https://www.last.fm/tag/chillout"
},
{
"count": 3,
"name": "soul",
"url": "https://www.last.fm/tag/soul"
},
{
"count": 3,
"name": "USA",
"url": "https://www.last.fm/tag/USA"
},
{
"count": 3,
"name": "sexy",
"url": "https://www.last.fm/tag/sexy"
},
{
"count": 2,
"name": "new york",
"url": "https://www.last.fm/tag/new+york"
},
{
"count": 2,
"name": "rock",
"url": "https://www.last.fm/tag/rock"
},
{
"count": 2,
"name": "hollywood sadcore",
"url": "https://www.last.fm/tag/hollywood+sadcore"
},
{
"count": 2,
"name": "indie rock",
"url": "https://www.last.fm/tag/indie+rock"
},
{
"count": 2,
"name": "trip hop",
"url": "https://www.last.fm/tag/trip+hop"
},
{
"count": 2,
"name": "female",
"url": "https://www.last.fm/tag/female"
},
{
"count": 2,
"name": "jazz",
"url": "https://www.last.fm/tag/jazz"
},
{
"count": 2,
"name": "10s",
"url": "https://www.last.fm/tag/10s"
},
{
"count": 2,
"name": "folk",
"url": "https://www.last.fm/tag/folk"
},
{
"count": 2,
"name": "lana",
"url": "https://www.last.fm/tag/lana"
},
{
"count": 2,
"name": "electronic",
"url": "https://www.last.fm/tag/electronic"
},
{
"count": 2,
"name": "blues",
"url": "https://www.last.fm/tag/blues"
},
{
"count": 2,
"name": "2010s",
"url": "https://www.last.fm/tag/2010s"
},
{
"count": 2,
"name": "vintage",
"url": "https://www.last.fm/tag/vintage"
},
{
"count": 2,
"name": "alternative rock",
"url": "https://www.last.fm/tag/alternative+rock"
},
{
"count": 2,
"name": "overrated",
"url": "https://www.last.fm/tag/overrated"
},
{
"count": 2,
"name": "retro pop",
"url": "https://www.last.fm/tag/retro+pop"
},
{
"count": 2,
"name": "beautiful",
"url": "https://www.last.fm/tag/beautiful"
},
{
"count": 2,
"name": "melancholic",
"url": "https://www.last.fm/tag/melancholic"
},
{
"count": 2,
"name": "dark pop",
"url": "https://www.last.fm/tag/dark+pop"
},
{
"count": 1,
"name": "Hollywood Pop",
"url": "https://www.last.fm/tag/Hollywood+Pop"
},
{
"count": 1,
"name": "chill",
"url": "https://www.last.fm/tag/chill"
},
{
"count": 1,
"name": "americana",
"url": "https://www.last.fm/tag/americana"
},
{
"count": 1,
"name": "diva",
"url": "https://www.last.fm/tag/diva"
},
{
"count": 1,
"name": "sad",
"url": "https://www.last.fm/tag/sad"
}
]
}
}
我們實際上只對標簽名稱感興趣，然后僅對最受歡迎的標簽感興趣。讓我們使用列表推導來創(chuàng)建前三個標記名稱的列表：
然后我們可以使用該str.join()方法將列表轉換為字符串：
讓我們創(chuàng)建一個函數，使用該邏輯為所有藝術家返回最流行標簽的字符串，我們稍后將使用該字符串應用于數據框中的每一行。
請記住，該函數將大量連續(xù)使用，因此我們將重用time.sleep()先前的邏輯。
將此功能應用于我們的10,000行將需要不到一個小時的時間。因此，我們知道事情實際上正在進展中，我們將希望像以前一樣監(jiān)視輸出的操作。
不幸的是，在將函數與pandas Series.apply()方法一起應用時，我們不能使用手動打印輸出的方法。相反，我們將使用tqdm軟件包來自動執(zhí)行此操作。
讓我們看一下操作的結果：
完成并導出數據
在導出數據之前，我們可能希望對數據進行排序，以便將最受歡迎的藝術家放在頂部。到目前為止，我們只是將數據存儲為文本而不轉換任何類型：
首先，將偵聽器和播放計數列轉換為數字。
artists[["playcount", "listeners"]] = artists[["playcount", "listeners"]].astype(int)
現在，讓我們按聽眾數量排序
最后，我們可以將數據集導出為CSV文件。
下一步
在大數據分析Python使用Last.fm API獲取音樂數據中，我們學習了如何使用大數據分析Python來使用Last.fm API構建數據集：
a.如何使用API??密鑰通過API進行身份驗證
b.如何使用分頁從API端點收集更大的響應
c.如何使用速率限制以保持在API準則之內。
如果您想擴展學習范圍，則可以：
a.完成我們的交互式Dataquest API和抓取過程，您可以免費開始。
b.探索Lasts.fm API中的其他API端點。
c.嘗試使用此免費公共API列表中的一些數據。
填寫下面表單即可預約申請免費試聽！怕錢不夠？可先就業(yè)掙錢后再付學費！ 怕學不會？助教全程陪讀，隨時解惑！擔心就業(yè)？一地學習，可推薦就業(yè)！
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