Date (#4215)

* add version

* add stock_cyq_em

akshare/__init__.py

@@ -2557,9 +2557,10 @@
 1.11.41 fix: fix index_weibo_sina interface
 1.11.42 fix: fix stock_gpzy_pledge_ratio_em interface
 1.11.43 fix: fix get_futures_daily interface
+1.11.44 add: add stock_cyq_em interface
 """
 
-__version__ = "1.11.43"
+__version__ = "1.11.44"
 __author__ = "AKFamily"
 
 import sys
@@ -2574,6 +2575,11 @@
 
 del sys
 
+"""
+筹码分布
+"""
+from akshare.stock_feature.stock_cyq_em import stock_cyq_em
+
 """
 funddb-工具-估值情绪-恐贪指数
 """

akshare/stock_feature/stock_cyq_em.py

@@ -0,0 +1,313 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+"""
+Date: 2023/10/23 19:00
+Desc: 东方财富网-概念板-行情中心-日K-筹码分布
+https://quote.eastmoney.com/concept/sz000001.html
+"""
+import json
+from datetime import datetime
+
+import pandas as pd
+import requests
+from py_mini_racer import py_mini_racer
+
+from akshare.stock_feature.stock_hist_em import code_id_map_em
+
+
+def stock_cyq_em(symbol: str = "000001", adjust: str = "") -> pd.DataFrame:
+    """
+    东方财富网-概念板-行情中心-日K-筹码分布
+    https://quote.eastmoney.com/concept/sz000001.html
+    :param symbol: 股票代码
+    :type symbol: str
+    :param adjust: choice of {"qfq": "前复权", "hfq": "后复权", "": "不复权"}
+    :type adjust: str
+    :return: 筹码分布
+    :rtype: pandas.DataFrame
+    """
+    html_str = """
+    // @ts-nocheck
+
+    /**
+     * 计算分布及相关指标
+     * @param {number} index 当前选中的K线的索引
+     * @return {{x: Array.<number>, y: Array.<number>}}
+     */
+    function CYQCalculator(index, klinedata) {
+        var maxprice = 0;
+        var minprice = 0;
+        var factor = 150;
+        var start = this.range ? Math.max(0, index - this.range + 1) : 0;
+        /**
+         * K图数据[time,open,close,high,low,volume,amount,amplitude,turnoverRate]
+         */
+        var kdata = klinedata.slice(start, Math.max(1, index + 1));
+        if (kdata.length === 0) throw 'invaild index';
+        for (var i = 0; i < kdata.length; i++) {
+            var elements = kdata[i];
+            maxprice = !maxprice ? elements.high : Math.max(maxprice, elements.high);
+            minprice = !minprice ? elements.low : Math.min(minprice, elements.low);
+        }
+
+        // 精度不小于0.01 产品逻辑
+        var accuracy = Math.max(0.01, (maxprice - minprice) / (factor - 1));
+        /**
+         * 值域
+         * @type {Array.<number>}
+         */
+        var yrange = [];
+        for (var i = 0; i < factor; i++) {
+            yrange.push((minprice + accuracy * i).toFixed(2) / 1);
+        }
+        /**
+         * 横轴数据
+         */
+        var xdata = createNumberArray(factor);
+
+        for (var i = 0; i < kdata.length; i++) {
+            var eles = kdata[i];
+
+            var open = eles.open,
+                close = eles.close,
+                high = eles.high,
+                low = eles.low,
+                avg = (open + close + high + low) / 4,
+                turnoverRate = Math.min(1, eles.hsl / 100 || 0);
+
+            var H = Math.floor((high - minprice) / accuracy),
+                L = Math.ceil((low - minprice) / accuracy),
+                // G点坐标, 一字板时, X为进度因子
+                GPoint = [high == low ? factor - 1 : 2 / (high - low), Math.floor((avg - minprice) / accuracy)];
+            // 衰减
+            for (var n = 0; n < xdata.length; n++) {
+                xdata[n] *= (1 - turnoverRate);
+            }
+
+            if (high == low) {
+                // 一字板时，画矩形面积是三角形的2倍
+                xdata[GPoint[1]] += GPoint[0] * turnoverRate / 2;
+            } else {
+                for (var j = L; j <= H; j++) {
+                    var curprice = minprice + accuracy * j;
+                    if (curprice <= avg) {
+                        // 上半三角叠加分布分布
+                        if (Math.abs(avg - low) < 1e-8) {
+                            xdata[j] += GPoint[0] * turnoverRate;
+                        } else {
+                            xdata[j] += (curprice - low) / (avg - low) * GPoint[0] * turnoverRate;
+                        }
+                    } else {
+                        // 下半三角叠加分布分布
+                        if (Math.abs(high - avg) < 1e-8) {
+                            xdata[j] += GPoint[0] * turnoverRate;
+                        } else {
+                            xdata[j] += (high - curprice) / (high - avg) * GPoint[0] * turnoverRate;
+                        }
+                    }
+                }
+            }
+
+        }
+
+
+        var currentprice = klinedata[index].close;
+        var totalChips = 0;
+        for (var i = 0; i < factor; i++) {
+            var x = xdata[i].toPrecision(12) / 1;
+            //if (x < 0) xdata[i] = 0;
+            totalChips += x;
+        }
+        var result = new CYQData();
+        result.x = xdata;
+        result.y = yrange;
+        result.benefitPart = result.getBenefitPart(currentprice);
+        result.avgCost = getCostByChip(totalChips * 0.5).toFixed(2);
+        result.percentChips = {
+            '90': result.computePercentChips(0.9),
+            '70': result.computePercentChips(0.7)
+        };
+        return result;
+
+        /**
+         * 获取指定筹码处的成本
+         * @param {number} chip 堆叠筹码
+         */
+        function getCostByChip(chip) {
+            var result = 0,
+                sum = 0;
+            for (var i = 0; i < factor; i++) {
+                var x = xdata[i].toPrecision(12) / 1;
+                if (sum + x > chip) {
+                    result = minprice + i * accuracy;
+                    break;
+                }
+                sum += x;
+            }
+            return result;
+        }
+
+        /**
+         * 筹码分布数据
+         */
+        function CYQData() {
+            /**
+             * 筹码堆叠
+             * @type {Array.<number>}
+             */
+            this.x = arguments[0];
+            /**
+             * 价格分布
+             * @type {Array.<number>}
+             */
+            this.y = arguments[1];
+            /**
+             * 获利比例
+             * @type {number}
+             */
+            this.benefitPart = arguments[2];
+            /**
+             * 平均成本
+             * @type {number}
+             */
+            this.avgCost = arguments[3];
+            /**
+             * 百分比筹码
+             * @type {{Object.<string, {{priceRange: number[], concentration: number}}>}}
+             */
+            this.percentChips = arguments[4];
+            /**
+             * 计算指定百分比的筹码
+             * @param {number} percent 百分比大于0，小于1
+             */
+            this.computePercentChips = function (percent) {
+                if (percent > 1 || percent < 0) throw 'argument "percent" out of range';
+                var ps = [(1 - percent) / 2, (1 + percent) / 2];
+                var pr = [getCostByChip(totalChips * ps[0]), getCostByChip(totalChips * ps[1])];
+                return {
+                    priceRange: [pr[0].toFixed(2), pr[1].toFixed(2)],
+                    concentration: pr[0] + pr[1] === 0 ? 0 : (pr[1] - pr[0]) / (pr[0] + pr[1])
+                };
+            };
+            /**
+             * 获取指定价格的获利比例
+             * @param {number} price 价格
+             */
+            this.getBenefitPart = function (price) {
+                var below = 0;
+                for (var i = 0; i < factor; i++) {
+                    var x = xdata[i].toPrecision(12) / 1;
+                    if (price >= minprice + i * accuracy) {
+                        below += x;
+                    }
+                }
+                return totalChips == 0 ? 0 : below / totalChips;
+            };
+        }
+    }
+
+
+    function createNumberArray(count) {
+        var array = [];
+        for (var i = 0; i < count; i++) {
+            array.push(0);
+        }
+        return array;
+    }
+    """
+    js_code = py_mini_racer.MiniRacer()
+    js_code.eval(html_str)
+    adjust_dict = {"qfq": "1", "hfq": "2", "": "0"}
+    code_id_dict = code_id_map_em()
+    url = "https://push2his.eastmoney.com/api/qt/stock/kline/get"
+    params = {
+        "secid": f"{code_id_dict[symbol]}.{symbol}",
+        'ut': 'fa5fd1943c7b386f172d6893dbfba10b',
+        'fields1': 'f1,f2,f3,f4,f5,f6',
+        'fields2': 'f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61',
+        'klt': '101',
+        'fqt': adjust_dict[adjust],
+        'end': datetime.now().date().strftime("%Y%m%d"),
+        'lmt': '210',
+        'cb': 'quote_jp1',
+    }
+    r = requests.get(url, params=params)
+    data_json = r.text.strip("quote_jp1(").strip(");")
+    data_json = json.loads(data_json)
+    temp_df = pd.DataFrame([item.split(",") for item in data_json['data']['klines']])
+    temp_df.columns = [
+        'date',
+        'open',
+        'close',
+        'high',
+        'low',
+        'volume',
+        'volume_money',
+        'zf',
+        'zdf',
+        'zde',
+        'hsl',
+    ]
+    for item in temp_df.columns[1:]:
+        temp_df[item] = pd.to_numeric(temp_df[item])
+    temp_df['index'] = range(0, len(temp_df))
+    records = temp_df.to_dict(orient="records")
+    date_list = []
+    benefit_part = []
+    avg_cost = []
+    pct_70_low = []
+    pct_70_high = []
+    pct_90_low = []
+    pct_90_high = []
+    pct_70_con = []
+    pct_90_con = []
+    for i in range(0, len(records)):
+        mcode = js_code.call("CYQCalculator", i, records)
+        date_list.append(records[i]['date'])
+        benefit_part.append(mcode['benefitPart'])
+        avg_cost.append(mcode['avgCost'])
+        pct_70_low.append(mcode["percentChips"]['70']['priceRange'][0])
+        pct_70_high.append(mcode["percentChips"]['70']['priceRange'][1])
+        pct_90_low.append(mcode["percentChips"]['90']['priceRange'][0])
+        pct_90_high.append(mcode["percentChips"]['90']['priceRange'][1])
+        pct_70_con.append(mcode["percentChips"]['70']['concentration'])
+        pct_90_con.append(mcode["percentChips"]['90']['concentration'])
+    temp_df = pd.DataFrame([
+        date_list,
+        benefit_part,
+        avg_cost,
+        pct_90_low,
+        pct_90_high,
+        pct_90_con,
+        pct_70_low,
+        pct_70_high,
+        pct_70_con,
+
+    ]
+    ).T
+    temp_df.columns = [
+        "日期",
+        "获利比例",
+        "平均成本",
+        "90成本-低",
+        "90成本-高",
+        "90集中度",
+        "70成本-低",
+        "70成本-高",
+        "70集中度",
+    ]
+    temp_df['日期'] = pd.to_datetime(temp_df['日期'], errors="coerce").dt.date
+    temp_df['获利比例'] = pd.to_numeric(temp_df['获利比例'], errors="coerce")
+    temp_df['平均成本'] = pd.to_numeric(temp_df['平均成本'], errors="coerce")
+    temp_df['90成本-低'] = pd.to_numeric(temp_df['90成本-低'], errors="coerce")
+    temp_df['90成本-高'] = pd.to_numeric(temp_df['90成本-高'], errors="coerce")
+    temp_df['90集中度'] = pd.to_numeric(temp_df['90集中度'], errors="coerce")
+    temp_df['70成本-低'] = pd.to_numeric(temp_df['70成本-低'], errors="coerce")
+    temp_df['70成本-高'] = pd.to_numeric(temp_df['70成本-高'], errors="coerce")
+    temp_df['70集中度'] = pd.to_numeric(temp_df['70集中度'], errors="coerce")
+    return temp_df
+
+
+if __name__ == '__main__':
+    stock_cyq_em_df = stock_cyq_em(symbol="000001", adjust="")
+    print(stock_cyq_em_df)

docs/changelog.md

@@ -68,6 +68,10 @@
 
 ## 更新说明详情
 
+1.11.44 add: add stock_cyq_em interface
+
+    1. 新增 stock_cyq_em 接口
+
 1.11.43 fix: fix get_futures_daily interface
 
     1. 修复 get_futures_daily 接口
@@ -3012,6 +3016,8 @@
 
 ## 版本更新说明
 
+1.11.44 add: add stock_cyq_em interface
+
 1.11.43 fix: fix get_futures_daily interface
 
 1.11.42 fix: fix stock_gpzy_pledge_ratio_em interface