stock Download - stock Source code download

stock

Python

1.0.0

Download

Better help yourself in stock trading (losing money-.-)

2022-12-08 Update

The project code is currently being reconstructed. The directory structure may be slightly different from the description below. It will be slowly updated and modified later. Thank you for your attention and support.

analysis/data analysis part

datahub/ data collection part

fund/ Fund-related analysis part

*futu/Basic usage of Futu Niuniu interface*

hk_stock/ Hong Kong stocks section

k-line/ K-line technical form part

machine_learning/ machine learning prediction

trader/ trading part

ptrade/ptrade automatic trading real code

log/ storage log

common/ common functions and libraries

configure database connection and configuration

Usage tutorial:

Modify configure/sample_config.json The configuration file is named configure/config.json. According to different projects, modify the fields inside and modify your mysql, mongodb user name and password. If mysql, mongodb, etc. are not used in the project , no modification is required. The corresponding mapping relationship can be found in the source code in this file. This setting is mainly to facilitate switching between online and local databases with the same set of code, and does not use environment variables to store user passwords. Friends who need it can also change it themselves.

configure/setting.py

    def config(self, db_type='mysql', local='ubuntu'):
        db_dict = self.json_data[db_type][local]
        user = db_dict['user']
        password = db_dict['password']
        host = db_dict['host']
        port = db_dict['port']
        return (user, password, host, port)

    def get_engine(self, db, type_='ubuntu'):
        from sqlalchemy import create_engine
        user, password, host, port = self.config(db_type='mysql', local=type_)
        try:
            engine = create_engine(
                'mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8'.format(user, password, host, port, db))
        except Exception as e:
            print(e)
            return None
        return engine

    def get_mysql_conn(self, db, type_='ubuntu'):
        import pymysql
        user, password, host, port = self.config(db_type='mysql', local=type_)
        try:
            conn = pymysql.connect(host=host, port=port, user=user, password=password, db=db, charset='utf8')
        except Exception as e:
            print(e)
            return None
        else:
            return conn

    def mongo(self, location_type='ubuntu', async_type=False):
        user, password, host, port = self.config('mongo', location_type)
        connect_uri = f'mongodb://{user}:{password}@{host}:{port}'
        if async_type:
            from motor.motor_asyncio import AsyncIOMotorClient
            client = AsyncIOMotorClient(connect_uri)
        else:
            import pymongo
            client = pymongo.MongoClient(connect_uri)
        return client

At the end of the article, there are benefits for brokers: providing an automated order placing interface for brokers

Quantitative trading for coders, write their experiences into code and push it to github. The code and strategies will be kept updated. If you have good strategies or ideas and questions that you want to communicate, you can add a WeChat message at the end of the article.

New:

analysis directory data analysis section

analysis/get_zt_info Analyze the daily limit strength in the new sector
analysis/diagnose_stock stock diagnosis, whether there is a black history and Northeastern stocks
analysis/ipospeed Correlation between IPO issuance speed and index
analysis/fd_money The price limit of A-share orders within a certain period of time

fund

fund/LOFShareDection.py monitors LOF and ETF market share changes
fund/ark_funds.py obtains the daily position data of ARK ETF and writes it to mongodb
fund/fund_share_update.py Shanghai Stock Exchange, Shenzhen Stock Exchange fund exchange fund share monitoring
fund/fund_share_monitor.py Shanghai Stock Exchange, Shenzhen Stock Exchange fund share query, size changes
fund/fund_info_spider.py Jisilu Fund, Tencent Securities Fund discount rate, premium rate crawler
fund/etf_info.py Monitoring of market index fund holdings
fund/ttjj.py Get daily fund data
fund/xueqiu_private_fund.py Snowball private equity acquisition
fund/danjuan_fund.py Snowball Egg Roll Fund data acquisition
fund/danjuan_fund_data_analysis.py Snowball Egg Roll Fund Analysis

datahub (data source)

datahub/foreignexchange.py USD/CNY exchange rate monitoring
datahub/niwen.py Download Ningwen Convertible Bonds
datahub/public_private_fund_members.py Cemetery private equity fund member data
datahub/jucao_ammouncement.py Juchao announcement batch acquisition + PDF download
datahub/bond_industry_info.py Convertible bond industry distribution
datahub/ceiling_break.py daily limit board closure monitoring

k-line (K-line technical form recognition)

k-line/recognize_form.py Recognize common forms through talib, such as three crows, etc.

Already have:

datahub/black_list_sql.py records the list of all stocks with black history in the A-share market and stores them in the database
big_deal.py monitors daily large transactions in the A-share market
bond_monitor convertible bond monitoring
ceiling_break.py How many days after the opening of the new stock market can the new stock return to the opening price?
delivery_order.py exports the delivery order to Mysql, making it easy to find traces of the operation history of a certain clearance stock, and you can see your operation records at a glance
fetch_each_day.py -- Get the top 50 popular stocks with daily turnover rate
filter_stock.py Select stocks through different factor strategies, common ones such as price-earnings ratio, liquidity, number of shareholders, number of fund holdings, etc.
foreign_exchange.py gets the daily trend of the US dollar exchange rate and stores it in Mysql
get_break_high.py -- Get the stocks that broke 50-day highs on the day. Why not get 60 days? Because everyone is using it, and if there are too many people using it, it won’t be allowed.
ipospeed.py counts the correlation between the daily IPO new stock issuance speed and the market
ipo_stock.py new stock statistics
jisilu.py Get convertible bond market information from Jisilu
jubi.py - Get real-time data from domestic altcoin platforms
new_stock_break Analyze the opening timing of new stocks
new_stock_fund Obtain new funds and select funds that won the Science and Technology Innovation Board
pledged_validation.py Equity pledge data compilation
push_msn.py - SMS to remind you that the price or increase of a certain stock you set reaches your requirements
relationship_case.py The relationship between the released stocks and the market index every month
select_stock.py - Stock selection strategy, stocks selected based on your own experience.
SPSIOP_PRICE.py - Huabao oil and gas valuation obtains data through crawlers and then calculates it
stockInfo.py crawls market stock news messages and stores them in the ElasticSearch database
strategy_verify.py gets Snowball’s strategy and verifies it
simulation.py records its own simulation warehouse
strategy_verify.py - Get Snowball’s live trading strategy
win_or_lost_each_day.py -- Evaluate your daily profit and loss of each stock with 100% completion
zdt.py --The daily limit popularity of the stock market

Welfare

Brokerage quantitative order interface

Supports python language, can be deployed in the cloud or run locally, and supports A-share market stocks, convertible bonds, funds and other varieties.

Interface documentation

Rate

Low transaction fees:
Stocks in case; convertible bonds 0.4 million; fund ETF, LOF 0.5 million

After opening the quantitative interface, there is no additional fee and it can be used permanently.

Activation conditions: Different brokers have different thresholds

Broker 1: Deposit 1W after opening an account to open the account
Broker 2: After opening an account, you can open it by depositing 20,000 yuan.

Of course, there are also other mainstream brokers to choose from, such as Huatai, GF, Huabao, China Merchants, China International Finance Corporation, Galaxy Securities, etc., which can basically cover mainstream brokers.