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        "description": "# Tehran Stock Market\n\n[![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)\n![PyPI - Downloads](https://img.shields.io/pypi/dw/tehran_stocks.svg?color=blue)\n[![PyPI version](https://badge.fury.io/py/tehran-stocks.svg)](https://badge.fury.io/py/tehran-stocks)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black)\n\n<!-- ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/tehran-stocks.svg) -->\n\nA python package that helps to access TCCIM stock price history, Using OOP Interface\n\n## Features\n\n- Download All stocks prices\n- Download prices from a group (i.e ETFs or cars, etc.)\n- Download Price history of one specific Stock\n- After first setup available offline.\n- CommandLine Interface\n- Export data to csv, excel or Stata(dta)\n- Compatible with `sqlalchemy`\n- Compatible with `PANDAS`\n- Based on light `sqlite`\n\n## 0 - Install\n\n```bash\npip install tehran_stocks\n```\n\n## 1- Initialization\n\nFor first use you need initialize the database\n\n### 1-1 Command line\n\n```bash\nts-get init  # Set up to sqlite database\n```\n\n### 1-2 Python\n\n```python\nimport tehran_stocks\n# On first import package initialize itself\n```\n\nDuring initialization you will prompt for downloading all prices. if you answer yes it will download all prices, otherwise you can download data\n\n## 2- Download and Update prices\n\n### 2-1 Command line\n\n```bash\nts-get update # update  all price , or download all if no price exist\nts-get  group 34 ## 34 is the code for car's group.\nts-get get_groups ## get group name and group codes\n```\n\n### 2-2 Python\n\n```python\nfrom tehran_stocks import get_all_price, Stocks, update_group\n\nget_all_price() # download and(or) update all prices\n\nupdate_group(34) #download and(or) update Stocks in groupCode = 34 (Cars)\n\nStocks.get_group() # to see list of group codes\n```\n\n## 3- Access Data\n\nTo access data you can use `Stocks` which is an customized `sqlalchemy` object, which helps you to find prices on an easy way.\n\n### 3-1 Search Stocks\n\n```python\nfrom tehran_stocks import Stocks, db\n\n# You can use query to find stocks\nstock = Stocks.query.filter_by(name='\u0643\u06af\u0644').first() #find by symbol(\u0646\u0645\u0627\u062f)\n\nstock = Stocks.query.filter_by(code='35700344742885862').first() # find by code on tsetmc url\n\nstock = Stocks.query.filter(Stocks.title.like('%\u06af\u0644 \u06af\u0647\u0631%')).first() # Search by title\n\nstock_list = Stocks.query.filter_by(group_code =34).all() # find all Stocks in Khodro\n\nstock_list = Stocks.query.filter(Stocks.group_code.in_([13,34])).all() # all stocks in khodro and felezat\n\n\n## (Advanced)or run sql query using orm or raw sql\ndb.session.query(Stocks.group_code, Stocks.group_name).group_by(Stocks.group_code).all()\n\ndb.session.execute('select group_code , group_name from stocks group by group_name').fetchall()\n```\n\nNow easily access stock price and do whatever you want with `pandas` dataframes:\n\n```python\n# use data as a pandas dataframe\n>>> stock.df #\n      id               code        ticker  dtyyyymmdd    first     high      low    close        value      vol  openint per     open     last       date\n0  22491  35700344742885862  Gol-E-Gohar.    20040829  12000.0  12021.0  12000.0  12000.0  18841605000  1570000     2708   D  12000.0  12000.0 2004-08-29\n\n>>> stock.summary()\nStart date: 20040829\nEnd date: 20190714\nTotal days: 2987\n\n>>> stock.update()\n# update stock price history\n\n# Export to your preferred format\n>>> stock.df.to_csv('price.csv')\n>>> stock.df.to_excel('price.xlsx')\n>>> stock.df.to_stata('price.dta')\n\n```\n\n## Todo\n\n- [x] Create Database\n- [x] Download Data\n- [x] CommandLine Support\n- [ ] Jalali Support\n\n\n",
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