之前我寫了一個爬取淘寶商品的源碼，給了一個小伙子學習，本想著后面寫成文章分享給大家學習的，但沒成想被那個小伙子捷足先登了…今天還是拿出來分享給大伙！

是這樣的，之前接了一個金主的單子，他想在淘寶開個小魚零食的網店，想對目前這個市場上的商品做一些分析，本來手動去做統計和分析也是可以的，這些信息都是對外展示的，只是手動比較麻煩，所以想托我去幫個忙。

一、 項目要求：

具體的要求如下：

1.在淘寶搜索“小魚零食”，想知道前10頁搜索結果的所有商品的銷量和金額，按照他劃定好的價格區間來統計數量，給我劃分了如下的一張價格區間表：

2.這10頁搜索結果中，商家都是分布在全國的哪些位置？

3.這10頁的商品下面，用戶評論最多的是什么？

4.從這些搜索結果中，找出銷量最多的10家店鋪名字和店鋪鏈接。

從這些要求來看，其實這些需求也不難實現，我們先來看一下項目的效果。

二、效果預覽

獲取到數據之后做了下分析，最終做成了柱狀圖，鼠標移動可以看出具體的商品數量。

在10~30元之間的商品最多，越往后越少，看來大多數的產品都是定位為低端市場。

然后我們再來看一下全國商家的分布情況：

可以看出，商家分布大多都是在沿海和長江中下游附近，其中以沿海地區最為密集。

然后再來看一下用戶都在商品下面評論了一些什么：

字最大的就表示出現次數最多，口感味道、包裝品質、商品分量和保質期是用戶評價最多的幾個方面，那么在產品包裝的時候可以從這幾個方面去做針對性闡述，解決大多數人比較關心的問題。

最后就是銷量前10的店鋪和鏈接了。

在拿到數據并做了分析之后，我也在想，如果這個東西是我來做的話，我能不能看出來什么東西？或許可以從價格上找到切入點，或許可以從產品地理位置打個差異化，又或許可以以用戶為中心，由外而內地做營銷。

越往深想，越覺得有門道，算了，對于小魚零食這一塊我是外行，不多想了。

三、爬蟲源碼

由于源碼分了幾個源文件，還是比較長的，所以這里就不跟大家一一講解了，懂爬蟲的人看幾遍就看懂了，不懂爬蟲的說再多也是云里霧里，等以后學會了爬蟲再來看就懂了。

import csvimport osimport timeimport wordcloudfrom selenium import webdriverfrom selenium.webdriver.common.by import Bydef tongji():    prices = []    with open("前十頁銷量和金額.csv", "r", encoding="utf-8", newline="") as f:        fieldnames = ["價格", "銷量", "店鋪位置"]        reader = csv.DictReader(f, fieldnames=fieldnames)        for index, i in enumerate(reader):            if index != 0:                price = float(i["價格"].replace("￥", ""))                prices.append(price)    DATAS = {"<10": 0, "10~30": 0, "30~50": 0,             "50~70": 0, "70~90": 0, "90~110": 0,             "110~130": 0, "130~150": 0, "150~170": 0, "170~200": 0, }    for price in prices:        if price < 10:            DATAS["<10"] += 1        elif 10 <= price < 30:            DATAS["10~30"] += 1        elif 30 <= price < 50:            DATAS["30~50"] += 1        elif 50 <= price < 70:            DATAS["50~70"] += 1        elif 70 <= price < 90:            DATAS["70~90"] += 1        elif 90 <= price < 110:            DATAS["90~110"] += 1        elif 110 <= price < 130:            DATAS["110~130"] += 1        elif 130 <= price < 150:            DATAS["130~150"] += 1        elif 150 <= price < 170:            DATAS["150~170"] += 1        elif 170 <= price < 200:            DATAS["170~200"] += 1    for k, v in DATAS.items():        print(k, ":", v)def get_the_top_10(url):    top_ten = []    # 獲取代理    ip = zhima1()[2][random.randint(0, 399)]    # 運行quicker動作（可以不用管）    os.system(""C:/Program Files/Quicker/QuickerStarter.exe" runaction:5e3abcd2-9271-47b6-8eaf-3e7c8f4935d8")    options = webdriver.ChromeOptions()    # 遠程調試Chrome    options.add_experimental_option("debuggerAddress", "127.0.0.1:9222")    options.add_argument(f"--proxy-server={ip}")    driver = webdriver.Chrome(options=options)    # 隱式等待    driver.implicitly_wait(3)    # 打開網頁    driver.get(url)    # 點擊部分文字包含"銷量"的網頁元素    driver.find_element(By.PARTIAL_LINK_TEXT, "銷量").click()    time.sleep(1)    # 頁面滑動到最下方    driver.execute_script("window.scrollTo(0,document.body.scrollHeight)")    time.sleep(1)    # 查找元素    element = driver.find_element(By.ID, "mainsrp-itemlist").find_element(By.XPATH, ".//div[@class="items"]")    items = element.find_elements(By.XPATH, ".//div[@data-category="auctions"]")    for index, item in enumerate(items):        if index == 10:            break        # 查找元素        price = item.find_element(By.XPATH, "./div[2]/div[1]/div[contains(@class,"price")]").text        paid_num_data = item.find_element(By.XPATH, "./div[2]/div[1]/div[@class="deal-cnt"]").text        store_location = item.find_element(By.XPATH, "./div[2]/div[3]/div[@class="location"]").text        store_href = item.find_element(By.XPATH, "./div[2]/div[@class="row row-2 title"]/a").get_attribute(            "href").strip()        # 將數據添加到字典        top_ten.append(            {"價格": price,             "銷量": paid_num_data,             "店鋪位置": store_location,             "店鋪鏈接": store_href             })    for i in top_ten:        print(i)def get_top_10_comments(url):    with open("排名前十評價.txt", "w+", encoding="utf-8") as f:        pass    # ip = ipidea()[1]    os.system(""C:/Program Files/Quicker/QuickerStarter.exe" runaction:5e3abcd2-9271-47b6-8eaf-3e7c8f4935d8")    options = webdriver.ChromeOptions()    options.add_experimental_option("debuggerAddress", "127.0.0.1:9222")    # options.add_argument(f"--proxy-server={ip}")    driver = webdriver.Chrome(options=options)    driver.implicitly_wait(3)    driver.get(url)    driver.find_element(By.PARTIAL_LINK_TEXT, "銷量").click()    time.sleep(1)    element = driver.find_element(By.ID, "mainsrp-itemlist").find_element(By.XPATH, ".//div[@class="items"]")    items = element.find_elements(By.XPATH, ".//div[@data-category="auctions"]")    original_handle = driver.current_window_handle    item_hrefs = []    # 先獲取前十的鏈接    for index, item in enumerate(items):        if index == 10:            break        item_hrefs.append(            item.find_element(By.XPATH, ".//div[2]/div[@class="row row-2 title"]/a").get_attribute("href").strip())    # 爬取前十每個商品評價    for item_href in item_hrefs:        # 打開新標簽        # item_        driver.execute_script(f"window.open("{item_href}")")        # 切換過去        handles = driver.window_handles        driver.switch_to.window(handles[-1])        # 頁面向下滑動一部分，直到讓評價那兩個字顯示出來        try:            driver.find_element(By.PARTIAL_LINK_TEXT, "評價").click()        except Exception as e1:            try:                x = driver.find_element(By.PARTIAL_LINK_TEXT, "評價").location_once_scrolled_into_view                driver.find_element(By.PARTIAL_LINK_TEXT, "評價").click()            except Exception as e2:                try:                    # 先向下滑動100，放置評價2個字沒顯示在屏幕內                    driver.execute_script("var q=document.documentElement.scrollTop=100")                    x = driver.find_element(By.PARTIAL_LINK_TEXT, "評價").location_once_scrolled_into_view                except Exception as e3:                    driver.find_element(By.XPATH, "/html/body/div[6]/div/div[3]/div[2]/div/div[2]/ul/li[2]/a").click()        time.sleep(1)        try:            trs = driver.find_elements(By.XPATH, "http://div[@class="rate-grid"]/table/tbody/tr")            for index, tr in enumerate(trs):                if index == 0:                    comments = tr.find_element(By.XPATH, "./td[1]/div[1]/div/div").text.strip()                else:                    try:                        comments = tr.find_element(By.XPATH,                                                   "./td[1]/div[1]/div[@class="tm-rate-fulltxt"]").text.strip()                    except Exception as e:                        comments = tr.find_element(By.XPATH,                                                   "./td[1]/div[1]/div[@class="tm-rate-content"]/div[@class="tm-rate-fulltxt"]").text.strip()                with open("排名前十評價.txt", "a+", encoding="utf-8") as f:                    f.write(comments + "/n")                    print(comments)        except Exception as e:            lis = driver.find_elements(By.XPATH, "http://div[@class="J_KgRate_MainReviews"]/div[@class="tb-revbd"]/ul/li")            for li in lis:                comments = li.find_element(By.XPATH, "./div[2]/div/div[1]").text.strip()                with open("排名前十評價.txt", "a+", encoding="utf-8") as f:                    f.write(comments + "/n")                    print(comments)def get_top_10_comments_wordcloud():    file = "排名前十評價.txt"    f = open(file, encoding="utf-8")    txt = f.read()    f.close()    w = wordcloud.WordCloud(width=1000,                            height=700,                            background_color="white",                            font_path="msyh.ttc")    # 創建詞云對象，并設置生成圖片的屬性    w.generate(txt)    name = file.replace(".txt", "")    w.to_file(name + "詞云.png")    os.startfile(name + "詞云.png")def get_10_pages_datas():    with open("前十頁銷量和金額.csv", "w+", encoding="utf-8", newline="") as f:        f.write("/ufeff")        fieldnames = ["價格", "銷量", "店鋪位置"]        writer = csv.DictWriter(f, fieldnames=fieldnames)        writer.writeheader()    infos = []    options = webdriver.ChromeOptions()    options.add_experimental_option("debuggerAddress", "127.0.0.1:9222")    # options.add_argument(f"--proxy-server={ip}")    driver = webdriver.Chrome(options=options)    driver.implicitly_wait(3)    driver.get(url)    # driver.execute_script("window.scrollTo(0,document.body.scrollHeight)")    element = driver.find_element(By.ID, "mainsrp-itemlist").find_element(By.XPATH, ".//div[@class="items"]")    items = element.find_elements(By.XPATH, ".//div[@data-category="auctions"]")    for index, item in enumerate(items):        price = item.find_element(By.XPATH, "./div[2]/div[1]/div[contains(@class,"price")]").text        paid_num_data = item.find_element(By.XPATH, "./div[2]/div[1]/div[@class="deal-cnt"]").text        store_location = item.find_element(By.XPATH, "./div[2]/div[3]/div[@class="location"]").text        infos.append(            {"價格": price,             "銷量": paid_num_data,             "店鋪位置": store_location})    try:        driver.find_element(By.PARTIAL_LINK_TEXT, "下一").click()    except Exception as e:        driver.execute_script("window.scrollTo(0,document.body.scrollHeight)")        driver.find_element(By.PARTIAL_LINK_TEXT, "下一").click()    for i in range(9):        time.sleep(1)        driver.execute_script("window.scrollTo(0,document.body.scrollHeight)")        element = driver.find_element(By.ID, "mainsrp-itemlist").find_element(By.XPATH, ".//div[@class="items"]")        items = element.find_elements(By.XPATH, ".//div[@data-category="auctions"]")        for index, item in enumerate(items):            try:                price = item.find_element(By.XPATH, "./div[2]/div[1]/div[contains(@class,"price")]").text            except Exception:                time.sleep(1)                driver.execute_script("window.scrollTo(0,document.body.scrollHeight)")                price = item.find_element(By.XPATH, "./div[2]/div[1]/div[contains(@class,"price")]").text            paid_num_data = item.find_element(By.XPATH, "./div[2]/div[1]/div[@class="deal-cnt"]").text            store_location = item.find_element(By.XPATH, "./div[2]/div[3]/div[@class="location"]").text            infos.append(                {"價格": price,                 "銷量": paid_num_data,                 "店鋪位置": store_location})        try:            driver.find_element(By.PARTIAL_LINK_TEXT, "下一").click()        except Exception as e:            driver.execute_script("window.scrollTo(0,document.body.scrollHeight)")            driver.find_element(By.PARTIAL_LINK_TEXT, "下一").click()        # 一頁結束        for info in infos:            print(info)        with open("前十頁銷量和金額.csv", "a+", encoding="utf-8", newline="") as f:            fieldnames = ["價格", "銷量", "店鋪位置"]            writer = csv.DictWriter(f, fieldnames=fieldnames)            for info in infos:                writer.writerow(info)if __name__ == "__main__":    url = "https://s.taobao.com/search?q=%E5%B0%8F%E9%B1%BC%E9%9B%B6%E9%A3%9F&imgfile=&commend=all&ssid=s5-e&search_type=item&sourceId=tb.index&spm=a21bo.21814703.201856-taobao-item.1&ie=utf8&initiative_id=tbindexz_20170306&bcoffset=4&ntoffset=4&p4ppushleft=2%2C48&s=0"    # get_10_pages_datas()    # tongji()    # get_the_top_10(url)    # get_top_10_comments(url)    get_top_10_comments_wordcloud()

通過上面的代碼，我們能獲取到想要獲取的數據，然后再Bar和Geo進行柱狀圖和地理位置分布展示，這兩塊大家可以去摸索一下。

結語

項目源碼我都可以分享給大家，但也請大家尊重一下原開發者，千萬不要未經允許就擅自把別人的代碼編成你的故事，那個小伙子想找他聊聊他都不理我了…誒。