时间：2023-06-08 02:15:01 | 来源：网站运营
时间：2023-06-08 02:15:01 来源：网站运营
python Flask+爬虫制作股票查询、历史数据、股评词云网页： 自学python的数据分析，爬虫后，花了几天时间看视频学习Flask做了一个简单的股票查询网页。本来还想着加入一些其他功能，比如财务指标分析，舆情分析，最完美的想法是做成一个股票评分系统，输入股票代码可以自动输出分析结果和最终评分以及排名。但是限于没有服务器（不想花钱买）于是先到此为止，后面计划先实现股票评分的本地系统化，然后有机会再部署到网站上。有类似想法的欢迎交流~
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from flask import Flaskfrom flask import requestfrom flask import render_templatefrom flask import jsonify# import pymysqlimport uitlsimport sysfrom jieba.analyse import extract_tagsimport string# sys.setrecursionlimit(100000)stock_id = '600009'app = Flask(__name__)@app.route("/be")def get_data(): data = uitls.get_be_data(str(stock_id)) return jsonify({"股票名称": data[1],"当前价格": data[3],"成交量": data[6],"涨跌幅": data[32],"流通市值": data[44]})@app.route("/his", methods=["get", "post"])def get_history_data(): msg = uitls.get_history_data(str(stock_id)) print(msg) print(type(msg)) return jsonify({"日期":msg['日期'],"开盘价":msg['开盘价'],"收盘价":msg['收盘价'],"最低价":msg['最低价'],"最高价":msg['最高价']}) # jsonify({"日期": msg['日期'][0],"开盘价":msg['开盘价'][0]})@app.route("/gp", methods=["get", "post"])def get_guping(): data = uitls.get_guping(stock_id) d = [] for i in data: k = i.rstrip(string.digits) v = i[len(k):] ks = extract_tags(k) # print(v) for j in ks: if not j.isdigit(): d.append({'name': j, 'value': v}) return jsonify({'kws':d})@app.route("/time", methods=["get", "post"])def get_time(): return uitls.get_time()@app.route("/", methods=["get", "post"])def input_id(): return render_template("main.html")@app.route("/ind", methods=["get", "post"])def get_id(): global stock_id stock_id = request.values.get("股票代码") print(stock_id) return render_template("main.html")if __name__ == '__main__': app.run()2.main.html<!DOCTYPE html><html> <head link rel="shortcut icon" href="#" /> <meta charset="utf-8"> <title>股票数据</title> <script src="../static/js/jquery-3.5.1.min.js"></script> <script src="../static/js/echarts.min.js"></script> <script src="../static/js/echarts-wordcloud.min.js"></script> <link href = "../static/css/main.css" rel = "stylesheet"/> </head> <body> <div id = "title">股票查询</div> <form action="/ind"> 股票代码 <input name = "股票代码" placeholder="请输入股票代码"> <button>提交</button> </form> <div id = "tim">我是时间</div> <div id = "be"> <div class ="tex"><h2>股票名称</h2></div> <div class ="tex"><h2>当前价格</h2></div> <div class ="tex"><h2>成交量</h2></div> <div class ="tex"><h2>涨跌幅</h2></div> <div class ="tex"><h2>流通市值</h2></div> <div class ="num"><h1>123</h1></div> <div class ="num"><h1>123</h1></div> <div class ="num"><h1>123</h1></div> <div class ="num"><h1>123</h1></div> <div class ="num"><h1>123</h1></div> </div> <div id="bl" style="width: 800px;height:435px;">我是瞎做</div> <script> var hisdata = echarts.init(document.getElementById('bl')); var upColor = '#ec0000'; var upBorderColor = '#8A0000'; var downColor = '#00da3c'; var downBorderColor = '#008F28'; hisdata_option = { title: { text: '历史趋势', left: 0 }, tooltip: { trigger: 'axis', axisPointer: { type: 'cross' } }, legend: { data: ['日K', 'MA5', 'MA10', 'MA20', 'MA30'] }, grid: { left: '10%', right: '10%', bottom: '15%' }, xAxis: { type: 'category', data: [], scale: true, boundaryGap: false, axisLine: {onZero: false}, splitLine: {show: false}, splitNumber: 20, min: 'dataMin', max: 'dataMax' }, yAxis: { scale: true, splitArea: { show: true } }, dataZoom: [ { type: 'inside', start: 50, end: 100 }, { show: true, type: 'slider', top: '90%', start: 50, end: 100 } ], series: [ { name: '日K', type: 'candlestick', data: [], itemStyle: { color: upColor, color0: downColor, borderColor: upBorderColor, borderColor0: downBorderColor }, markPoint: { label: { normal: { formatter: function (param) { return param != null ? Math.round(param.value) : ''; } } }, data: [ { name: 'XX标点', coord: ['2013/5/31', 2300], value: 2300, itemStyle: { color: 'rgb(41,60,85)' } }, { name: 'highest value', type: 'max', valueDim: 'highest' }, { name: 'lowest value', type: 'min', valueDim: 'lowest' }, { name: 'average value on close', type: 'average', valueDim: 'close' } ], tooltip: { formatter: function (param) { return param.name + '<br>' + (param.data.coord || ''); } } }, markLine: { symbol: ['none', 'none'], data: [ [ { name: 'from lowest to highest', type: 'min', valueDim: 'lowest', symbol: 'circle', symbolSize: 10, label: { show: false }, emphasis: { label: { show: false } } }, { type: 'max', valueDim: 'highest', symbol: 'circle', symbolSize: 10, label: { show: false }, emphasis: { label: { show: false } } } ], { name: 'min line on close', type: 'min', valueDim: 'close' }, { name: 'max line on close', type: 'max', valueDim: 'close' } ] } }, { name: 'MA5', type: 'line', data: '', smooth: true, lineStyle: { opacity: 0.5 } }, { name: 'MA10', type: 'line', data: '', smooth: true, lineStyle: { opacity: 0.5 } }, { name: 'MA20', type: 'line', data: '', smooth: true, lineStyle: { opacity: 0.5 } }, { name: 'MA30', type: 'line', data: '', smooth: true, lineStyle: { opacity: 0.5 } }, ] }; </script> <div id="br" style="width: 800px;height:435px;">我是下游</div> <script> var gp = echarts.init(document.getElementById('br')); var ddd = [{ name: 'Farrah Abraham', value: 366, // Style of single text }]; var maskResource = new Image() maskResource.src=image1; gp_option = { title:{ text: '股评词云图', left:'center', }, //数据可以点击 tooltip:{ show:false }, series: [{ type: 'wordCloud', // The shape of the "cloud" to draw. Can be any polar equation represented as a // callback function, or a keyword present. Available presents are circle (default), // cardioid (apple or heart shape curve, the most known polar equation), diamond ( // alias of square), triangle-forward, triangle, (alias of triangle-upright, pentagon, and star. shape: 'circle', // A silhouette image which the white area will be excluded from drawing texts. // The shape option will continue to apply as the shape of the cloud to grow. // maskImage: maskResource, // // Folllowing left/top/width/height/right/bottom are used for positioning the word cloud // // Default to be put in the center and has 75% x 80% size. left: 'center', top: 'center', width: '70%', height: '80%', right: null, bottom: null, // Text size range which the value in data will be mapped to. // Default to have minimum 12px and maximum 60px size. sizeRange: [12, 60], // Text rotation range and step in degree. Text will be rotated randomly in range [-90, 90] by rotationStep 45 rotationRange: [-90, 90], rotationStep: 45, // size of the grid in pixels for marking the availability of the canvas // the larger the grid size, the bigger the gap between words. gridSize: 8, // set to true to allow word being draw partly outside of the canvas. // Allow word bigger than the size of the canvas to be drawn drawOutOfBound: false, // Global text style textStyle: { normal: { fontFamily: 'sans-serif', fontWeight: 'bold', // Color can be a callback function or a color string color: function () { // Random color return 'rgb(' + [ Math.round(Math.random() * 160), Math.round(Math.random() * 160), Math.round(Math.random() * 160) ].join(',') + ')'; } }, emphasis: { shadowBlur: 10, shadowColor: '#333' } }, // Data is an array. Each array item must have name and value property. data: [{ name: 'Farrah Abraham', value: 366, // Style of single text }] }] } </script> <script > function getatime(){ $.ajax({ url:"/time", success:function(d){ $("#tim").html(d) }, error:function(jqXHR, textStatus, errorThrown){ console.log(jqXHR.responseText); } }) } function get_be_data(){ $.ajax({ url:"/be", success:function(data){ $(".num h1").eq(0).text(data['股票名称']) $(".num h1").eq(1).text(data['当前价格']) $(".num h1").eq(2).text(data['成交量']) $(".num h1").eq(3).text(data['涨跌幅']) $(".num h1").eq(4).text(data['流通市值']) }, error:function(jqXHR, textStatus, errorThrown){ console.log(jqXHR.responseText); } }) } function get_guping(){ $.ajax({ url:"/gp", success:function(data){ gp_option.series[0].data = data.kws; gp.setOption(gp_option); }, error:function(jqXHR, textStatus, errorThrown){ console.log(jqXHR.responseText); } }) } function get_his_data(){ $.ajax({ url:"/his", success:function(msg){ var datalen = msg['日期'].length k_time =[] k_value = [] for (var i = 0; i < datalen; i++) { k_time.push(msg['日期'][i]); k_value.push([msg['开盘价'][i], msg['收盘价'][i], msg['最低价'][i], msg['最高价'][i]]) } console.log(k_time) console.log(k_value) function calculateMA(dayCount) { var result = []; for (var i = 0, len = k_value.length; i < len; i++) { if (i < dayCount) { result.push('-'); continue; } var sum = 0; for (var j = 0; j < dayCount; j++) { sum += k_value[i - j][1]; } result.push(sum / dayCount); } return result; } hisdata_option.xAxis.data = k_time; hisdata_option.series[0].data = k_value; hisdata_option.series[1].data = calculateMA(5); hisdata_option.series[2].data = calculateMA(10); hisdata_option.series[3].data = calculateMA(20); hisdata_option.series[4].data = calculateMA(30); hisdata.setOption(hisdata_option); }, error:function(){ console.log("获取失败"); } }) } setInterval(getatime,1000) setInterval(get_be_data,1000) get_his_data() get_guping() </script> </body></html>3 .main.cssbody{ margin: 0; background: #333;}#title{ position: absolute; width: 40%; height: 10%; top: 0; left: 30%; /* background-color: #666666; */ color: white; font-size: 30px; display: flex; align-items: center; justify-content: center;}#ins{ position: absolute; width: 40%; height: 20%; top: 10%; left: 0; background-color: grey;}#tim{ position: absolute; /* width: 30%; */ height: 10%; top: 5%; right: 2%; color: #FFFFFF; font-size: 20px; /* background-color: green; */}#be{ position: absolute; width: 100%; height: 30%; top: 10%; left: 0; color: white; /* background-color: #777777; */}#bl{ position: absolute; width: 50%; height: 60%; top: 40%; left: 0; background-color: #888888;}#br{ position: absolute; width: 50%; height: 60%; top: 40%; left: 50%; background-color: #999999;}.num{ width: 20%; float: left; display: flex; align-items: center; justify-content: center; color:yellow; font-size: 20px;}.tex{ width: 20%; float: left; font-family: "幼圆"; display: flex; align-items: center; justify-content: center; 4.utils.py import timeimport pymysqlimport urllib.requestimport pandas as pdimport requestsimport refrom bs4 import BeautifulSoupdef get_time(): time_str = time.strftime("%Y{}%m{}%d{} %X") return time_str.format("年", "月", "日")def get_conn(): conn = pymysql.connect(host='127.0.0.1', user='root', password='', db='stock', charset='utf8') cursor = conn.cursor() return conn,cursordef close_conn(conn,cursor): cursor.close() conn.close()def query(sql,*args): conn,cursor = get_conn() cursor.execute(sql,args) res = cursor.fetchall() close_conn(conn,cursor) return res# def get_be_data(*args):# sql = "SELECT * FROM hangqing where stockid = %s"# res = query(sql, args)# print(res)# return res[0]def get_be_data(code): url = 'http://qt.gtimg.cn/q=sh' + str(code) content = urllib.request.urlopen(url, timeout=2).read() content = content.decode("gbk").encode("utf-8").decode("utf8", "ignore") content = content.split('~') return contentdef get_history_data(code): url = 'http://quotes.money.163.com/service/chddata.html?code=0'+str(code) try: content = urllib.request.urlopen(url).read() content = content.decode("gbk").encode("utf-8") with open('E:/hisdata.csv', 'wb')as f: f.write(content) data = pd.read_csv('E:/hisdata.csv') # data = data.to_dict('record') data = data[["日期","开盘价","收盘价","最低价","最高价"]] # print(data) data = data.to_dict() data['日期'] = list(data['日期'].values()) data['开盘价'] = list(data['开盘价'].values()) data['收盘价'] = list(data['收盘价'].values()) data['最低价'] = list(data['最低价'].values()) data['最高价'] = list(data['最高价'].values()) data['日期'] = data['日期'][::-1] data['开盘价'] = data['开盘价'][::-1] data['收盘价'] = data['收盘价'][::-1] data['最低价'] = data['最低价'][::-1] data['最高价'] = data['最高价'][::-1] except Exception as e: print(e) return datadef get_guping(id): max_page = 2 # input('请输入爬取页数') b = [] # head = {'User-Agent':' Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.116 Safari/537.36'} for page in range(1, int(max_page) + 1): url = 'http://guba.eastmoney.com/list,{}_{}.html'.format(id, page) res = requests.get(url) soup = BeautifulSoup(res.text, 'html.parser') urllist = soup.find_all('div', {'class': 'articleh'}) for i in urllist: if i.find('a') != None: try: title = i.find('a').get_text() yuedu = i.find('span',{'class':'l1 a1'}).get_text() # time = i.find('span', {'class': 'l5 a5'}).get_text() # a = [title + yuedu] b.append(title + yuedu) except Exception as e: print(e) pass return b[7:]if __name__ == '__main__': msg = get_guping(600002) print(msg) 后面想要继续实现本地化的打分系统，因为虽然同花顺等炒股软件包含智能筛选功能，但是缺少一些个性化的分析指标，不知道我的这个想法是否可行？有没有价值去做？求建议！关键词：数据,历史,爬虫,股票
