{% block main_content %}{% end %}
This Bokeh app below served by a Bokeh server that has been embedded
in another web app framework. For more information see the section
Embedding Bokeh Server as a Library
in the User's Guide.
{{ script|safe }}
================================================
FILE: backend/web/templates/common/footer.html
================================================
{% block footer %}
{% end %}
================================================
FILE: backend/web/templates/common/header.html
================================================
{% block header %}
{% end %}
================================================
FILE: backend/web/templates/common/left_menu.html
================================================
{% block left_menu %}
{% end %}
================================================
FILE: backend/web/templates/common/meta.html
================================================
{% block meta %}
{% end %}
================================================
FILE: backend/web/templates/data_editor.html
================================================
{% extends "layout/default.html" %}
{% block main_content %}
{{ stockWeb.name }}
{{ stockWeb.name }}
{% for index,element in enumerate(stockWeb.columns) %}
{{ stockWeb.column_names[index] }}
{% end %}
| {% for column_name in stockWeb.column_names %} | {{ column_name }} | {% end %}
|---|
开源Python全栈股票系统，数据抓取、统计分析、报表展示。
2021年9月20日更新，发布2.0版本
1，修复bokeh的版本升级问题，可以显示趋势数据了。
2，使用 stock_zh_ah_name 做每日数据。
3，AkShare 升级到 1.1.9 版本。
2021年8月31日更新job服务
1，过滤包括：600，6006，601，000，001，002，且不包括ST的股票数据。。
2，使用 stock_zh_ah_name 做每日数据。
3，AkShare 升级到 1.0.80 版本。
2021年6月3日使用 AkShare 做数据抓取服务
1，使用 stock_zh_a_spot 做实时行情数据。
2，使用 stock_zh_a_daily 做历史数据统计。
3，升级基础镜像使用python3.7，AkShare 的 0.9.65 版本。
手写图片识别演示
result:
测试图片识别演示
{% for image in image_array %}
{% end %}
结果:
"-1"
欢迎使用股票系统。
{{ element["title"] }}
{{ element["desc"] }}
{% raw element["div"] %}
{% raw element["script"] %}
{% end %}
{% end %}
================================================
FILE: backend/web/templates/stock_web.html
================================================
{% extends "layout/default.html" %}
{% block main_content %}
{{ stockWeb.name }}
{{ stockWeb.name }}
{% for index,element in enumerate(stockWeb.columns) %}
{% if index < 15 %}
{% if element != 'eastmoney_url' %}
{{ stockWeb.column_names[index] }}
{% end %}
{% end %}{% end %}
| {{ column_name }} | {% end %}
|---|
欢迎使用股票系统。
欢迎使用股票系统。
任务测试
""" class MainPage(RequestHandler): def get(self): self.write(html_content) _workers = ThreadPool(10) _result = {} # 后台任务。 def blocking_task(n, tid): time.sleep(n) print(tid) _result[tid] = {"finish"} class AddJobHandler(RequestHandler): @gen.coroutine def get(self): tid = str(int(time.time() * 10000)) _workers.apply_async(blocking_task, (10, tid)) # 传递参数 10 秒。 self.write(tid) self.finish() # 先finish 掉，然后在后台执行。 class JobCheckHandler(RequestHandler): def get(self): tid = self.get_argument("tid") if tid in _result.keys(): out = _result[tid] # 结果 del _result[tid] # 删除tid的数据。 self.write(str(out)) else: self.write("") # main 启动。 if __name__ == "__main__": HTTPServer(Application([ ("/", MainPage), ("/add_job", AddJobHandler), ("/job_check", JobCheckHandler) ], debug=True)).listen(9090) print("start web .") IOLoop.instance().start() ================================================ FILE: backend/web/test_thread_v2.py ================================================ #!/usr/local/bin/python3 # -*- coding: utf-8 -*- import time from tornado.httpserver import HTTPServer from tornado.ioloop import IOLoop from tornado.web import Application, asynchronous, RequestHandler from tornado import gen from tornado.concurrent import run_on_executor from concurrent.futures import ThreadPoolExecutor # `pip install futures` for python2 # https://gist.github.com/methane/2185380 参考 html_content = """任务测试
""" class MainPage(RequestHandler): def get(self): self.write(html_content) MAX_WORKERS = 4 _result = {} class AddJobHandler(RequestHandler): # 必须定义一个executor的属性，然后run_on_executor 注解才管用。 executor = ThreadPoolExecutor(max_workers=MAX_WORKERS) @run_on_executor # 标记成后台程序执行。 def background_task(self, tid): time.sleep(10) # 传递参数 10 秒。 _result[tid] = {"finish"} @gen.coroutine def get(self): tid = str(int(time.time() * 10000)) self.background_task(tid) self.write(tid) class JobCheckHandler(RequestHandler): def get(self): tid = self.get_argument("tid") if tid in _result.keys(): out = _result[tid] # 结果 del _result[tid] # 删除tid的数据。 self.write(str(out)) else: self.write("") # main 启动。 if __name__ == "__main__": HTTPServer(Application([ ("/", MainPage), ("/add_job", AddJobHandler), ("/job_check", JobCheckHandler) ], debug=True)).listen(9999) print("start web .") IOLoop.instance().start() ================================================ FILE: backend/web/tornado_bokeh_embed.py ================================================ from jinja2 import Environment, FileSystemLoader from tornado.web import RequestHandler from bokeh.application import Application from bokeh.application.handlers import FunctionHandler from bokeh.embed import server_document from bokeh.layouts import column from bokeh.models import ColumnDataSource, Slider from bokeh.plotting import figure from bokeh.server.server import Server from bokeh.themes import Theme from bokeh.sampledata.sea_surface_temperature import sea_surface_temperature env = Environment(loader=FileSystemLoader('templates')) server_url = "http://localhost:9090/" class IndexHandler(RequestHandler): def get(self): print("index ...") template = env.get_template('bokeh_embed.html') script = server_document(server_url + 'bkapp') print(script) self.write(template.render(script=script, template="Tornado")) # self.write(html_content) def modify_doc(doc): df = sea_surface_temperature.copy() source = ColumnDataSource(data=df) plot = figure(x_axis_type='datetime', y_range=(0, 25), y_axis_label='Temperature (Celsius)', title="Sea Surface Temperature at 43.18, -70.43") plot.line('time', 'temperature', source=source) def callback(attr, old, new): if new == 0: data = df else: data = df.rolling('{0}D'.format(new)).mean() source.data = ColumnDataSource(data=data).data slider = Slider(start=0, end=30, value=0, step=1, title="Smoothing by N Days") slider.on_change('value', callback) doc.add_root(column(slider, plot)) # doc.theme = Theme(filename="theme.yaml") bokeh_app = Application(FunctionHandler(modify_doc)) # Setting num_procs here means we can't touch the IOLoop before now, we must # let Server handle that. If you need to explicitly handle IOLoops then you # will need to use the lower level BaseServer class. server = Server( {'/bkapp': bokeh_app}, num_procs=1, port=9999, extra_patterns=[('/', IndexHandler)] ) server.start() if __name__ == '__main__': from bokeh.util.browser import view print('Opening Tornado app with embedded Bokeh application on ' + server_url) server.io_loop.add_callback(view, server_url) server.io_loop.start() ================================================ FILE: docker-compose/.gitignore ================================================ # C extensions *.so data .idea *.iml .DS_Store *.zip *.log *.pyc doc /bin pkg *.tmp ================================================ FILE: docker-compose/LICENSE ================================================ Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. 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We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright [yyyy] [name of copyright owner] Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================ FILE: docker-compose/README.md ================================================ ## 镜像仓库选择 https://github.com/DaoCloud/public-image-mirror ```bash # python使用镜像 docker.m.daocloud.io/library/python:3.11-slim-bullseye # mysql使用： docker.m.daocloud.io/library/mysql:8 ``` ## 本地部署方法 ``` git clone git@gitee.com:pythonstock/docker-compose.git cd docker-compose docker-compose up -d ``` ## 访问地址 http://localhost:9090/ ## 查看日至，进入项目代码 ``` # 查看启动日志： docker logs -f stock # 进入stock容器 docker exec -it stock bash ``` ## 开发模式，映射stock 代码方法 直接使用 dev yml 即可，会映射stock到/data/stock 然后在外部修改代码容器中运行即可。 ```bash docker-compose -f dev-docker-compose.yml up -d ``` ```bash docker-compose -f docker-compose-v2.0.yml up -d ``` ## 老镜像还保存一个版本 ``` pythonstock/pythonstock:v2021 ``` ================================================ FILE: docker-compose/build_stock.sh ================================================ #!/bin/sh cd ../stock NOW_MONTH=$(date "+%Y-%m") DOCKER_TAG=pythonstock/pythonstock:latest DOCKER_TAG_MONTH=pythonstock/pythonstock:stock-${NOW_MONTH} echo " docker build -f Dockerfile -t ${DOCKER_TAG} ." docker build -f Dockerfile -t ${DOCKER_TAG} . echo " docker build tag xxx ${DOCKER_TAG_MONTH} " echo "#################################################################" echo " docker push ${DOCKER_TAG} " ================================================ FILE: docker-compose/dev-docker-compose-restart.sh ================================================ #!/bin/sh git pull sleep 1 docker-compose -f dev-docker-compose.yml down sleep 1 docker-compose -f dev-docker-compose.yml up -d echo "restart dev-docker-compose" ================================================ FILE: docker-compose/dev-docker-compose.yml ================================================ networks: stock-dev-network: driver: bridge version: "3" services: frontend: image: pythonstock/frontend-dev:latest build: context: . dockerfile: docker/DevFrontendDockerfile container_name: frontend ports: - "8080:8080" volumes: # 设置开发目录，方便开发调试 - "../frontend:/usr/src/app" environment: LANG: zh_CN.UTF-8 LC_CTYPE: zh_CN.UTF-8 restart: always networks: stock-dev-network: {} # 入口写死，手动启动应用。 entrypoint: /usr/src/app/docker-entrypoint.sh depends_on: - backend backend: image: pythonstock/backend-dev:latest build: context: . dockerfile: docker/DevBackendDockerfile container_name: backend ports: - "8888:8888" - "9090:9090" volumes: # 设置开发目录，方便开发调试 - "../backend/jobs/crontab:/var/spool/cron/crontabs/root" - "../backend/jobs/cron.minutely:/etc/cron.minutely" - "../backend/jobs/cron.hourly:/etc/cron.hourly" - "../backend/jobs/cron.daily:/etc/cron.daily" - "../backend/jobs/cron.monthly:/etc/cron.monthly" - "../backend:/data/stock" - "../backend/supervisor:/data/supervisor" - "./data/notebooks:/data/notebooks" - "./data/logs:/data/logs" environment: MYSQL_HOST: mysql-stock MYSQL_USER: root MYSQL_PWD: mysql-stock MYSQL_DB: stock_data MYSQL_PORT: 3306 LANG: zh_CN.UTF-8 LC_CTYPE: zh_CN.UTF-8 PYTHONIOENCODING: utf-8 restart: always networks: stock-dev-network: {} # 入口写死，手动启动应用。 #entrypoint: sleep 999999d depends_on: - mysql-stock mysql-stock: # image: hub.atomgit.com/library/mysql:5.7 # https://hub.atomgit.com/repos/amd64/mysql image: docker.m.daocloud.io/library/mysql:8 container_name: mysql-stock # 执行命令：https://juejin.cn/s/mysql%20healthcheck%20docker-compose healthcheck: test: ["CMD", "mysqladmin" ,"ping", "-uroot", "-pmysql-stock"] interval: 10s timeout: 5s retries: 5 ports: - "3306:3306" networks: stock-dev-network: {} volumes: - "./mysql/my.cnf:/etc/mysql/my.cnf" - "./data/mysql-stock/data:/var/lib/mysql" - ./mysql/init.sql:/docker-entrypoint-initdb.d/init.sql environment: MYSQL_ROOT_PASSWORD: mysql-stock MYSQL_DATABASE: stock_data TZ: Asia/Shanghai command: [ '--character-set-server=utf8mb4', '--collation-server=utf8mb4_general_ci', '--max_connections=3000' ] restart: always ================================================ FILE: docker-compose/docker/DevBackendDockerfile ================================================ # https://hub.docker.com/_/python?tab=tags&page=1&name=3.11-slim-bullseye # 用这个做为基础镜像，防止每次都进行构建。 #FROM docker.io/python:3.11-slim-bullseye FROM docker.m.daocloud.io/library/python:3.11-slim-bullseye # https://opsx.alibaba.com/mirror # 使用阿里云镜像地址。修改debian apt 更新地址，pip 地址，设置时区。 # 设置debian的镜像源 RUN echo "deb http://mirrors.aliyun.com/debian/ bullseye main non-free contrib" > /etc/apt/sources.list && \ echo "deb-src http://mirrors.aliyun.com/debian/ bullseye main non-free contrib" >> /etc/apt/sources.list && \ echo "deb http://mirrors.aliyun.com/debian-security/ bullseye-security main" >> /etc/apt/sources.list && \ echo "deb-src http://mirrors.aliyun.com/debian-security/ bullseye-security main" >> /etc/apt/sources.list && \ echo "deb http://mirrors.aliyun.com/debian/ bullseye-updates main non-free contrib" >> /etc/apt/sources.list && \ echo "deb-src http://mirrors.aliyun.com/debian/ bullseye-updates main non-free contrib" >> /etc/apt/sources.list && \ echo "deb http://mirrors.aliyun.com/debian/ bullseye-backports main non-free contrib" >> /etc/apt/sources.list && \ echo "deb-src http://mirrors.aliyun.com/debian/ bullseye-backports main non-free contrib" >> /etc/apt/sources.list && \ echo "[global]\n\ trusted-host=mirrors.aliyun.com\n\ index-url=http://mirrors.aliyun.com/pypi/simple" > /etc/pip.conf && \ ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \ echo "Asia/Shanghai" > /etc/timezone #增加语言utf-8 ENV LANG=zh_CN.UTF-8 ENV LC_CTYPE=zh_CN.UTF-8 ENV LC_ALL=C ENV PYTHONPATH=/data/stock # 增加 TensorFlow 的支持，使用最新的2.0 编写代码。目前还是使用 1.x 吧，还没有学明白。 # RUN pip3 install tensorflow==2.0.0-rc1 keras # RUN pip3 install tensorflow keras sklearn # 设置 vim 的语言配置 RUN mkdir -p /etc/vim/ && \ echo "set fileencodings=utf-8,ucs-bom,gb18030,gbk,gb2312,cp936" >> /etc/vim/vimrc && \ echo "set termencoding=utf-8" >> /etc/vim/vimrc && \ echo "set encoding=utf-8" >> /etc/vim/vimrc # 安装 mysqlclient akshare (pandas ,numpy) tornado bokeh # 安装 nodejs 库 # apt-get autoremove -y 删除没有用的依赖lib。减少镜像大小。1MB 也要节省。 # apt-get --purge remove 软件包名称 , 删除已安装包（不保留配置文件)。 RUN apt-get update && apt-get install -y git pkg-config net-tools procps gcc make python3-dev default-libmysqlclient-dev libxml2-dev cron && \ pip3 install mysqlclient sqlalchemy && \ pip3 install supervisor && \ pip3 install numpy pandas && \ pip3 install akshare --upgrade && \ apt-get install -y nodejs && \ pip3 install tornado torndb && \ pip3 install bokeh stockstats scikit-learn && \ apt-get --purge remove -y gcc make python3-dev default-libmysqlclient-dev libxml2-dev && \ rm -rf /root/.cache/* && apt-get clean && apt-get autoremove -y && \ cd /usr/local/lib/python3.11/site-packages && find ./ -name *.pyc | xargs rm -f # /usr/local/lib/python3.11/site-packages/pandas/ # 1.解决 pandas 数据插入问题。直接修改数据库驱动 sqlalchemy # 修改：statement.replace("INSERT INTO","INSERT IGNORE INTO") # /usr/local/lib/python3.11/site-packages/sqlalchemy/dialects/mysql/mysqldb.py # 增加了一个 IGNORE 参数。 # 2.解决torndb在python3下面的问题： # http://blog.csdn.net/littlethunder/article/details/8917378 # 3. 解决 type 问题，使用sed 进行替换。 # File "/usr/local/lib/python3.11/site-packages/torndb.py", line 260, in404 Not Found
An error occurred.
Sorry, the page you are looking for is currently unavailable.
Please try again later.
If you are the system administrator of this resource then you should check the error log for details.
Faithfully yours, nginx.
================================================ FILE: frontend/public/index.html ================================================
{{ title }}
{{ title }}
OOPS!
All rights reserved
wallstreetcn
{{ message }}
Please check that the URL you entered is correct, or click the button below to return to the homepage.
Back to home
基础库版本
1，pandas使用【 {{ pandasVersion }} 】版本，
2，numpy使用【 {{ numpyVersion }} 】版本，
3，sqlalchemy使用【 {{ sqlalchemyVersion }} 】版本，
4，akshare使用【 {{ akshareVersion }} 】版本，
5，bokeh使用【 {{ bokehVersion }} 】版本，
6，stockstats使用【 {{ stockstatsVersion }} 】版本，
相关资料信息
1，github项目地址。
2，博客地址。
2021年9月20日更新，发布2.0版本
1，修复bokeh的版本升级问题，可以显示趋势数据了。
2，使用 stock_zh_ah_name 做每日数据。
3，AkShare 升级到 1.1.9 版本。
2021年8月31日更新job服务
1，过滤包括：600，6006，601，000，001，002，且不包括ST的股票数据。。
2，使用 stock_zh_ah_name 做每日数据。
3，AkShare 升级到 1.0.80 版本。
2021年6月3日使用 AkShare 做数据抓取服务
1，使用 stock_zh_a_spot 做实时行情数据。
2，使用 stock_zh_a_daily 做历史数据统计。
3，升级基础镜像使用python3.7，AkShare 的 0.9.65 版本。
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